Supplemental Material: Genetic association between carbonates and gold precipitation mechanisms in the Jinshan deposit, eastern Jiangnan orogen

Abstract: Thermodynamic database for Geochemist's Workbench (GWB).


Digital Transformation in Education: Using Technologies for Enhancement of Efficiency of Teaching

Abstract: Digital transformation has an important role as it revolutionizes teaching and learning, offering access, engagement, and personalized instruction. The aim of the research is to evaluate the role of digital transformation within the Ukrainian educational institutions and to reveal its potentials towards enhancement of teaching efficiency. To answer the research questions the mixed methodology approach was applied that offers in-depth examining the role of digital transformation in education. The methods included literature review, content analysis, interviews, and observations, t-test, statistical analysis, modeling, and thematic analysis. Over 40 recent scientific works were chosen to study the problem from the conceptual dimension and organize accurate empirical survey. The investigation involved 48 instructors and 93 bachelor students from four Ukrainian educational institutions. The results showed that integrating digital tools within the educational environment can enhance the teaching efficiency since digitalization enables accessibility to educational materials and personalized learning. The special attention was paid towards instructors and students’ perceptions of digital transformations in education. The results found that digital educational process was described as dynamic, interactive, flexible, innovative, technology-enhanced, and motivating. The Ukrainian context create special conditions for digital transformations at the educational institutions. Also, the recommendations to implement digital transformations in education to enhance the efficiency of teaching based on instructors and students’ responses were developed during the research. It was found that the implementation of digital transformations requires a comprehensive approach that addresses the conceptual, organizational, methodical, and content levels. The findings can be applied within the educational institutions to improve the efficiency of teaching through digital tools.


Benefits of Kahoot in Improving 7th Grade Junior Highschool English Vocabulary: Classroom Action Research in SMP Hamong Putera Ngaglik

Abstract: This Classroom Action Research investigates the advantages of employing Kahoot, A platform that teaches through games, in expanding one's vocabulary in English among 7th grade junior high school students at SMP Hamong Putera Ngaglik. The study found that Kahoot significantly enhances student improvement, motivation, and learning outcomes. It was observed that the use of Kahoot led to an increase in vocabulary scores, indicating its effectiveness as a learning tool. The study included before being tested, Kahoot! intervention, and a vocabulary post-test. This study examined if Kahoot! could improve 7th-graders' English vocabulary acquisition and retention. The study found that Kahoot! improved pupils' vocabulary scores. Kahoot!'s gamification made learning fun and engaging. The platform's real-time feedback helped students remedy their mistakes, fostering active learning and English language comprehension. Kahoot! may help 7th-grade junior high school students learn English vocabulary, according to one study. To improve vocabulary learning, teachers can use gamification like Kahoot! This study adds to the literature on technology-enhanced learning aids in education.Keywords: Classroom Action Research, Kahoot, Vocabulary


High-speed lensless eye tracker for microsaccade measurement

Abstract: We report on the design and construction of a goggle-type eye tracker using a low-cost and high-speed lensless camera for monitoring eye movements in neurodegenerative diseases. A Rolling Shutter image sensor combined with lensless computational imaging allows for the reconstruction of a time sequence of images from a single snapshot, effectively improving the framerate of the camera. We constructed and demonstrated the prototype device using a commercial-grade CMOS image sensor and achieved the improvement of framerate from 15 to 480Hz, with the tracking results for 28 clinical measured data. Our device can potentially measure microsaccadic eye movements in a wearable camera format, allowing routine monitoring of abnormal eye movements for the early diagnosis and tracking of Alzheimer’s and Parkinson’s disease.


Generation of a Digital Terrain Model (DTM) Fusioning WV-2 Images and RTK-derived Topobathymetric Data

Abstract: Digital terrain models (DTMs) are digital elevation models (DEMs) that represent the bare ground surface. They are created by multiple sources, including satellite remote sensing, aerial photography, and ground-based surveys, and are often combined with other data sources to create highly detailed models. As the demand for accurate and detailed information about the Earth's surface continues to grow, DTMs have become an increasingly important tool for researchers in different fields. This study aims to create a DTM with a spatial resolution of 0.50 m for São Caetano do Sul, São Paulo, Brazil, integrated with a topobathymetric map of three water courses running along the borders of the study area. For the conventional DTM generation, a WV-2 stereo pair was used. A total of 55 ground control points (GCPs) were collected using the GNSS-RTK method, being 60% used for model building and 40% employed for validation. The topobathymetric survey was accomplished using a GNSS-RTK device placed along the analyzed open streams. For validation purposes, we used bias and MAE metrics. Overall, the methodology presented in this article provides a useful approach for generating high-resolution DTMs that can be used in a range of applications, especially in urban hydrodynamic studies.


Restoring Nigeria’s Exchange Rate to the Goodluck Jonathan’s Era for Economic Recovery and Growth

Abstract: This paper analyzes the factors contributing to Nigeria's current exchange rate challenges, particularly comparing the economic performance during the administrations of Presidents Goodluck Jonathan, Muhammadu Buhari, and Bola Ahmed Tinubu. It also looks into the overall state of the economy and strategies to restore Nigeria’s exchange rate to pre-Buhari levels. Key issues discussed include the decline in the Naira's value, rising inflation, and the challenges faced by different sectors. The research underscores the adverse effects on citizens, especially the poor, and emphasizes the need for urgent government intervention. The recommendations suggested encompasses measures to boost foreign exchange supply, manage demand, and enhance economic stability. Some of them includes promoting non-oil exports, addressing political stability concerns, managing inflation, and implementing policies to discourage currency speculation. Keywords: Balance of payments, Exchange rate, Fiscal policy


Efficient First-price Sealed E-auction Protocol Under Secure Multi-party Computational Malicious Model

Abstract:
To solve the problems of existing e-auction protocols such as semi-trustworthiness of outsourced third parties, collusive attacks among participants, unsatisfactory decentralized structure, and inability of public verification, we propose an efficient first-price sealed e-auction protocol under a secure multi-party computational malicious model. First, the protocol combines the additive homomorphism of the ElGamal cryptographic algorithm to achieve a decentralized structure and eliminate the problem of semi-trustworthiness of outsourced third parties; it uses (n, n) threshold encryption and decryption techniques to solve the problem of collusion attacks among participants and uses Hash-based Message Authentication Code (HMAC) technology to achieve public verifiability of auction results. Additionally, the protocol proposes a method to quickly find the maximum value of the data encoding, which can avoid multiple processing of confidential data and thus effectively reduce the number of communication rounds. The combination of zero-knowledge proof and ideal/realistic simulation paradigm proves that the protocol in this paper is resistant to up to n-1 party collusion attacks and satisfies the security of the secure multi-party computational malicious model. Finally, after theoretical analysis and simulation experiments, the protocol not only satisfies higher security performance but also has greater overall operational efficiency.

&nbsp;


Pelatihan Bahasa Inggris “Tenses” Bagi Siswa Sekolah Minggu HKBP Getsemane Medan Labuhan

Abstract: Mastery of English is a must for everyone around the world. Likewise in Indonesia, mastering English will provide great benefits for future studies and careers. However, students still experience obstacles in learning and practicing English either in the school environment or in the community because English is a foreign language for the Indonesian people, which is not used as an official or everyday language. Therefore, the PKM activities of the Faculty of Languages and Arts, HKBP Nommensen University try to provide solutions to students and the community to improve their ability to master English. By focusing on English 'tenses' training for Sunday school students at the HKBP Getsemane church, Martubung Medan. The training participants were 20 elementary and middle school students who were Sunday school children and church teenagers. The training lasted for two weeks with three meetings each week, starting from 16-28 October 2023. After the training was carried out, the results of the training in the form of trainee test scores showed significant progress in the trainee's ability to understand and practice English tenses, both written and verbal. From the observations it was also found that the training participants were very enthusiastic and interested in learning English using the methods used in class.


Mengembangkan Sistem Penjualan Sampah (QR TRASH)

Abstract: Abstract Trash is a very complicated problem for anyone who lives and gets activities in any environment. Trash can be very disturbing for students because they are not disciplined in throwing away trash. The government issued Government Regulation (PP) Number 27 of 2020 concerning Specific Trash Management, Law Number 18 of 2008 concerning Trash Management, and Government Regulation Number 81 of 2012 concerning Management of Household Trash and Household-Like Trash as one of their concrete steps. System development projects involve students, teachers, programmers, and other parties within the school who know about and are affected by the project. The problems being faced by partners are planned to be overcome by providing software in the form of a trash buying and selling application or also known as qr trash. An initial agreement between the school and the software developer is the main requirement for using the waterfall method. The system was developed by designing an application that can be installed on smartphone devices. The application designed is called qr – trash. This application can be accessed if the user has registered an account first. Account registration by users is carried out via “qr code”.


Pelatihan Alat Peraga Penggaris Geser Untuk Meningkatkan Pemahaman Berhitung Siswa SD

Abstract: Teaching aids are media that can help stimulate students' skills, thoughts, attention and desires so that they can stimulate student learning activities. On the other hand, using teaching aids can create space for students to be able to participate in every learning process. In fact, at SDN 2 Kereng Bangkirai class III and SDIT Hasanka class II, learning activities have not used teaching aids. The props that are made and used are counting boards made from cardboard. This teaching aid is used in the learning process for class III students at SDN 2 Kereng Bangkirai and class II at SDIT Hasanka. The aim of learning using these teaching aids is to facilitate students in the learning process and the hope is that by using these props, learning activities can be more active and enjoyable in learning activities, and will not make students bored in learning so that their material skills will be better.


Pengaruh Pembuatan Konten Video Terhadap Penjualan Di B21 Digital Printing

Abstract: The purpose of this research is to provide an explanation of the marketing approach used by B21 Digital Printing. This approach provides an opportunity to utilize the MetaAds movie promotion platform to increase sales. By utilizing MetaAds as a marketing tool, B21 Digital Printing was able to achieve higher customer acquisition rates. This was achieved by consistently expanding audience reach through the utilization of enlightening and challenging video content. The information displayed here shows that the utilization of MetaAds as a digital platform for advertising produces high-quality results, which in turn validates the effectiveness of the video advertising strategy that B21 Digital Printing uses to facilitate the acquisition process of its portfolio of business opportunities.


A special target detection called You Only Looks Once

Abstract: This paper proposes a unique target detection called You Only Look Once (YOLO for short) and a recognition method. Unlike the previous idea of many classifiers with object detection functions, the object detection box is set as a spatially separated bounding box and the regression problem of related class probabilities is realized. The neural network model can directly scan the entire image during testing, predicting bounding boxes and class probabilities from the complete picture. At the same time, because the whole detection channel relies on a single neural network, it is more straightforward and concise when upgrading and updating. The unified architecture used in this paper is fast, with smaller versions of the YOLO model processing a staggering 155 frames per second. At the same time, it has also achieved excellent results in mAP. Compared with other detection systems, YOLOv3 has optimized many past problems, including positioning errors. At the same time, the probability of predicting false detections in the absence of false detections is small. Finally, like the YOLO base model, YOLOv3 may produce significant errors when processing abstract works of art and images with a large number of small objects. However, its actual results are still better than detection methods such as Region -Convolutional Neural Networks (R-CNN).


Using data resampling and category weight adjustment to solve sample imbalance

Abstract: The purpose of this thesis is to investigate the application of artificial intelligence and machine learning in solving the sample imbalance problem. The sample imbalance problem refers to the phenomenon that the number of different categories of samples in the training data varies greatly, resulting in the poor performance of traditional machine learning algorithms on a few categories of samples. To address this problem, this paper proposes a new approach combining data resampling and category weight adjustment strategies. First, the sample distribution of the dataset is adjusted by undersampling and oversampling techniques to balance the number of samples from different categories. Then, during the model training process, different weights are assigned to the samples of different categories so that the model pays more attention to the samples of a few categories. The experimental results show that the method achieves significant performance improvement on multiple datasets. In addition, this paper compares other commonly used methods for solving the sample imbalance problem and analyzes and discusses them in detail. Finally, this study offers a practical solution to the problem of sample imbalance and provides guidance for research in related fields.


Current study on HCI based AR technology in the medical industry

Abstract: Augmented Reality (AR) is a new technology that based on Human-Computer Interaction (HCI) can combine our real life with 3D virtual information through real-time computing and multiple sensors. It simulates people's senses, such as hearing, vision, touch, etc., bringing things that cannot be seen in reality to people's eyes, which will bring people a feeling beyond reality. It has already appeared in our lives and has applications in many fields, such as architecture. Especially in the gaming field, AR, an innovative emerging technology, is widely loved by young people. With the development of technology, the forms of AR games have also become diverse. It has also developed rapidly in the medical field in recent years. This article will discuss the current situation of AR and its advantages in the medical industry based on Human-Computer Interaction (HCI) from three aspects: doctor diagnosis, patient rehabilitation, and medical education with examples of applications. Then, this article will discuss some of the drawbacks of using AR and the problems that will be encountered in future development, and propose solutions. Finally, analysis and predictions will be made for the future development of AR in the industry.


The application of artificial intelligence in the game field

Abstract: With the rapid development of artificial intelligence technology, its application in the field of games is increasingly widespread. At present, the application of artificial intelligence in games has become a research hotspot. This article mainly explores the application of AI in various types of games such as first person shooter (FPS), Role playing Games (RPGs), Strategy, and analyzes their advantages and disadvantages based on the category of the game. Specifically, this article explores the application of AI in FPS games, focusing on how AI controls the behavior and strategies of enemies to provide players with challenging and realistic experiences. In the context of RPGs, the paper analyzes AI's impact on intelligent decision-making and interaction with non-playable characters (NPCs). Intelligent NPCs create a more authentic and immersive interaction between players and game characters. In the case of strategy games, AI enhances the strategic and challenging aspects, offering a more layered and dynamic gaming experience, and pushing players' decision-making abilities and strategic thinking. Additionally, the article discusses the limitations and challenges of AI in games. This paper summarizes and prospects the application of AI in the field of games.


Randomized Pacman maze generation algorithm

Abstract: Pacman, a cultural icon since its debut in 1980, is celebrated for its captivating static maze design. This research explores innovative algorithms, including an improved version of Sidewinder, in the context of dynamic maze generation for Pacman. Traditional algorithms, constituting the initial focus, serve as counterexamples to highlight their unsuitability in creating Pacman mazes due to their generic design unrelated to the game's unique gameplay. By showcasing these limitations, the study emphasizes the necessity for tailored solutions that align with Pacman's dynamic environment. Subsequently, attention shifts to an innovative algorithm exhibiting promise for Pacman maze generation. An in-depth analysis, using the same rigorous criteria applied to traditional algorithms provides essential insights into its potential for enhancing the Pacman gaming experience.


Discussion of a method for analysing adolescent depression based on BiLSTM and Attentional Mechanisms

Abstract: The incidence of depression in adolescents has been commonplace, but the number of people diagnosed with depression in hospitals is not large, so it is important to analyze people's textual content in normal times to determine whether they are in a depressive mood, and then intervene in a timely manner. The article firstly introduces the research results of previous scholars in sentiment analysis, and then briefly introduces the LSTM(Long Short-Term Memory) model, explains the operation formula of the model, and points out that BiLSTM(Bi-directional Long Short-Term Memory) has greater predictive ability than the LSTM model by taking the before and after contexts of the sentences into full consideration, and by extracting bi-directional semantic features. After that, the principle of the Attention Mechanism and the application of its derivative models, Self-Attention Mechanism, Multi-Attention Mechanism and Cross-Attention Mechanism, in different scenarios are analyzed, and finally, the advantages and disadvantages of BiLSTM and the attention mechanism are compared in the prediction of textual sentiment, and it is proposed that the BiLSTM-Attention model can play a stronger performance in the analysis of textual sentiment.


A comparison of recent progress in breast cancer diagnosis models using machine learning algorithms

Abstract: Breast cancer is the leading cause of mortality among women suffering from cancer, so the accurate diagnosis is important. This review aims to provide a thorough examination of advancements and trends in breast cancer diagnosis by analysing recognized papers published between 2020 and 2023.The paper firstly gives a brief overview of breast cancer, machine learning algorithms, followed by an introduction of basic process for ML in breast cancer diagnosis. After that, by focusing on two emerging trends, hybridization and newly invented modalities, the review introduces existing achievements in the field. Subsequently, it highlights nine notable or novel designs in breast cancer diagnosis, while presenting their comparative properties in a tabular format. Hopefully, this review can equip researchers with valuable insights for future studies and references, helping them gain a better understanding of the field and facilitating further improvements in breast cancer detection and classification.


Electronic Health Record Interoperability System in Peru Using Blockchain

Abstract: In Peru, there is currently no integrated electronic health record (EHR) system that can be automatically shared between healthcare facilities. This leads to increased service costs due to duplicated examinations and records, as well as additional time required to manage patients’ clinical information. One alternative for ensuring the secure interoperability of EHRs while preserving data privacy is the use of blockchain technology. However, existing works consider a pre-established format for exchanging EHRs, which is not applicable when systems have different formats, as is the case in Peru. This work proposes an architecture and a web application for exchanging EHRs in heterogeneous systems. The proposed system includes the homologation of an EHR with rapid interoperability resources for medical attention using FHIR HL7, and vice versa, to achieve interoperability. Additionally, it utilizes blockchain technology to ensure data security and privacy. The web application was tested using a case simulation to demonstrate EHR interoperability between clinics in a clear, secure, and efficient manner. In addition, a survey was conducted with 30 patients regarding adoption, and another survey was conducted with 10 doctors from a public hospital in Peru regarding usability. The results demonstrate a very high level of adoption and usability for them all. Unlike other studies, the proposal does not necessitate alterations to existing EHR systems for interoperability. In other words, the proposal presents a feasible and cost-effective alternative to addressing the EHR interoperability issue in clinics and hospitals in Peru.


Effect of Virtual Education on Academic Performance Generated by COVID-19

Abstract: The aim of this research is to analyze the impact of implementing virtual education on the academic performance of primary and secondary school students in a private school in Ibagué, Colombia, during the COVID-19 pandemic crisis. The survey was administered to 183 parents and nine teachers at the school as a data collection technique for the study. The research results revealed that the school maintained its quality in conducting virtual classes at the elementary and high school levels. Similarly, the students’ performance was maintained compared to the previous year of the pandemic. As a conclusion, it has been determined that the school directors’ implementation of the virtual education model and the capabilities of the teaching staff were successful in maintaining the quality of education during the pandemic.


Application of Deep Learning Models for Bone-Conducted Speech Signals Extracted in the Form of Bone Conduction Headphones

Abstract: In this study, we used deep learning to align bone-conducted speech signals with air-conducted speech signals, aiming to replace traditional air conduction microphones in voice-based services capturing surrounding sounds. We fabricated headphones, placing bone conduction microphones on the rami (the branches of a bone in the jaw area), in line with traditional bone conduction headphone configurations. Using LSTM, CNN, and CRNN models, we created databases that aligned bone-conducted speech signals with their air-conducted counterparts and tested them with bone-conducted speech signals captured via our custom-made headphones. The CNN model demonstrated superior performance in accurately distinguishing three English words (“apple,” “hello,” and “pass”), including their voiceless pronunciations. In conclusion, our study shows that deep learning models can effectively use bone-conducted speech signals extracted from the rami for automatic speech recognition (ASR), paving the way for future ASR technology that precisely recognizes only the speaker’s voice.


Supplemental Material: The Zaozigou orogenic gold-antimony deposit, West Qinling Orogen, China: Structural controls on multiple mineralization events

Abstract: Table S1: Detailed operating parameters and conditions for dolomite U-Pb dating. Table S2: LA-ICP-MS U-Pb isotope data for dolomite.


Attribute-specific Cyberbullying Detection Using Artificial Intelligence

Abstract: Cyberbullying, a pervasive issue in the digital age, poses threats to individuals’ well-being across various attributes such as religion, age, ethnicity, and gender. This research employs artificial intelligence to detect cyberbullying instances in Twitter data, utilizing both traditional and deep learning models. The study repurposes the Sentiment140 dataset, originally intended for sentiment analysis, for the nuanced task of cyberbullying detection. Ethical considerations guide the dataset transformation process, ensuring responsible AI development. The Naive Bayes algorithm demonstrates commendable precision, recall, and accuracy, showcasing its efficacy. The Bi-LSTM model, leveraging deep learning capabilities, exhibits nuanced cyberbullying detection. The study also underscores limitations, emphasizing the need for refined models and diverse datasets.


COVID-19 e aspectos psicossociais e econômicos na população brasileira

Abstract: Objective: This study aimed to identify the psychosocial and economic characteristics of people affected by COVID-19 and their support network at the beginning of the pandemic. Methods: We conducted a cross-sectional study of 2,702 people aged 18 and over living in Brazil. Google® Forms were used to develop an online questionnaire containing open- and closed-ended questions about sociodemographic, economic and health characteristics. Results: People dissatisfied with their health and those who showed emotional changes were more likely to need support (PR=1.74; p<0.001 and PR=2.39; p<0.001). Support from family members stood out [536 (70.2%)]. Bivariate and multivariate analysis showed statistically significant associations of COVID-19 infection with sociodemographic and economic aspects, such as age (p<0.001); region of the country (p<0.001), marital status (p=0.003), number of people per household (p=0.003), employment status (p=0.012), holding a health insurance (p=0.014), needing some other type of support (p<0.001) and not being satisfied with current health status (p=0.043). Conclusion: The findings indicate that COVID-19 negatively affects satisfaction with health and influences the need to seek some type of social support.


Design of an educational strategy based on digital resources for the teaching of social sciences

Abstract: This research proposes a pedagogical strategy incorporating digital tools for teaching Social Sciences. A quantitative approach is employed data collection targeting educational authorities, teachers, and students to assess the commitment and feasibility of implementing a new educational proposal. The results reflect the commitment and interest of participants towards creating this pedagogical strategy. Various digital tools are suggested, including Telegram for communication, ChatGPT and Virtual Encyclopedias for content generation, Kahoot and Google Form for assessment, and Timeline JS and Powtoon for dynamic presentations. Finally, the proposal was validated through a comparative study between a control group and an experimental one. The findings indicate that the new pedagogical strategy offers a higher innovation, relevance, and improvement in students' learning process.


ANALYSIS OF THE NEEDS OF MANDARIN TEACHING USERS ON LIVE STREAMING PLATFORMS

Abstract: The rapid development of live streaming platforms has attracted an increasing number of knowledge sharers and learners. These platforms have expanded from entertainment and live commerce to knowledge sharing and monetization. Mandarin Chinese teaching has gained popularity due to its vast user base and relatively low teaching threshold. However, after a period of practice, some drawbacks have been observed, impacting teaching effectiveness and students' learning outcomes. Through questionnaires, specific student needs will be identified, and collaborative efforts among the platform, regulatory authorities, and content providers will be undertaken to improve and enhance Mandarin Chinese teaching on live-streaming platforms. This paper employs quantitative analysis to investigate the distribution of Mandarin learners on live streaming platforms, factors influencing their learning, and their satisfaction levels with the learning process. The aim is to provide valuable insights for future Mandarin teaching on live-streaming platforms and other educational domains. The rapid development of live streaming platforms has attracted increasing knowledge sharers and learners. These platforms have expanded from entertainment and live commerce to knowledge sharing and monetisation. Mandarin Chinese teaching has gained popularity due to its vast user base and relatively low teaching threshold. However, after a period of practice, some drawbacks have been observed, impacting teaching effectiveness and students' learning outcomes. Through questionnaires, specific student needs will be identified, and collaborative efforts among the platform, regulatory authorities, and content providers will be undertaken to improve and enhance Mandarin Chinese teaching on live-streaming platforms. This paper employs quantitative analysis to investigate the distribution of Mandarin learners on live streaming platforms, factors influencing their learning, and their satisfaction levels with the learning process. The aim is to provide valuable insights for future Mandarin teaching on live-streaming platforms and other educational domains.


Exploring the Levels of Undergraduate University Students' Study Skills

Abstract: The ability to study well is crucial to students' academic performance. The aims of this research were to investigate the study skills levels of undergraduate students, to determine the correlation between academic performance and the study skills of undergraduate students, and to identify any noteworthy variations in study skills based on gender and location. Multi-stage stratified random sampling technique was used to select representative sample of 2207 undergraduate students from Punjab, Pakistan's general public universities. With the author's consent, a modified version of the study skills evaluation questionnaire was adapted, and the academic performance scale was created, verified, and subjected to a reliability coefficient of .094 and 0.85. Four research hypotheses were developed and put to the test using the t-test, Pearson r, mean, and standard deviation. The results indicated a substantial difference in terms of gender and location, as well as a favorable link between study skills and academic performance. Moreover, the majority of undergraduate students employed study skills at a moderate level; therefore, it is recommended to design and incorporate study skills in educational courses for students in academic curricula.


Professional education as a way to discover the multi-dimensional integrity of a human

Abstract: Introduction. Currently, professional education is not often based on the natural inclinations of a person, their development with subsequent extrapolation into the chosen field of activity, which is not just the main scientific problem in the qualitative preparation of professionals, but also does not allow a comprehensive mapping of the natural multidimensional integrity of a person, its large-scale deployment of its natural essence in one or another sphere of social activities and the inter-sphere space in which a person will have to grow professionally, develop, build themselves and their life prospects. The article presents a theoretical overview of the genesis of professional education in various historical epochs, starting from the earliest civilizations of the world to the present time, in a philosophical and cultural context. According to the authors, this review will serve as a theoretical basis for understanding the peculiarities of the formation of professional education in Russia, ways to reform it at the present time, search for promising areas of these transformations, the emergence of innovative professions, professional goal-setting, the development and implementation of multidimensional manifestations of the natural integrity of human inclinations as a subject of professional activity, improving the quality of their life and satisfaction with the profession. The research purpose of the article is to analyze the philosophical and cultural genesis of the formation of professional education system in the history of human existence. The position is substantiated that professional education should be one of the ways to reveal the multidimensional integrity of human natural inclinations, and the profession should be considered as an independent occupation, determined firstly by the natural origin, and secondly by the social division of labor operations, social challenges and orders. This requires special technologies and through evidence-based pedagogy – to get access to educational practice, in which decisions on the application of educational approaches and methods of professionalization are made based on the available evidence of their effectiveness, and such evidence is searched, compared, generalized. Materials and Methods. The methodological basis of the research is based on philosophical, cultural and systemic approaches. The theoretical and methodological support in the construction of the material was the dialectical method, which contributes to the objective grasp of the concrete historical circumstances of human existence in the context of professional formation. Methods used by the authors include comparative historical, deductive, chronological ones, as well as generalization and analysis. Results. The main results presented in the article are philosophical, cultural and socio-philosophical analyses of the genesis of professional education and revealing its specific socio-cultural features in the comparative context of social development in various historical civilizations. For the first time, the formation of professional education into an independent social phenomenon and its institutionalization, the evolution of professionalism on the example of ancient China, Greece, and Rome are described in a generalized form. The analysis of the origin of the phenomenon of professional education in Europe, professional activities reflecting public concerns and achievements, stating the key aspects of the interaction of education with the socio-cultural code of the era, is of research value. Attention is focused on professional education in the Middle Ages since the advent of manufactories, as well as innovations of the Enlightenment. The conducted philosophical and cultural analysis of the formation of professional education in the world served as a prerequisite for analyzing its development in Russia, starting from the reign of Peter the Great to the present. At the same time, the need for the formation of a fundamentally new concept of professional l education based on the consideration of human natural inclinations, rethinking the concept of professional education from ontological, axiological, praxiological and other positions is emphasized. Conclusions. The analysis of the formation of the professional education system in various epochs, from the ancient world to the present, allowed the authors to substantiate the position that professional education should be based on the natural inclinations of a person, their abilities and capabilities and act as one of the ways to actualize their multidimensional integrity and social self-sufficiency. It is recorded that at different stages of formation, professional education acts as a phenomenon of a specific type of activity, contributing to human self-fulfillment in a dynamically changing world. In this regard, the dominant role belongs to understanding and evidence-based pedagogics and their methodological developments aimed at the formation of professional activity of a person.


Reconstructing near-water-wall temperature in coal-fired boilers using improved transfer learning and hidden layer configuration optimization

Abstract: The temperature field is a critical factor for ensuring the safe combustion and energy conservation in boilers. However, an effective method for reconstructing the temperature field near the water wall is still under exploration. In this paper, a method for online reconstruction of the temperature field distribution near the water wall in a 330 MW tangentially fired coal boiler is proposed, which progresses from a well-established model for the entire furnace. A two-branch fusion network for transfer learning (TBFN-TL) method is proposed, incorporating additional key parameters, heat flux, during the transfer process to enhance the effectiveness. A Bayesian hierarchical neural architecture search (BHNAS) method is proposed to optimize the configuration of the hidden layers in building neural networks. Compared with computational fluid dynamics (CFD) results, the mean absolute percentage error (MAPE) of the reconstruction results for the entire furnace model, traditional transfer learning methods, and the proposed TBFN-TL are 11.57%, 5.738%, and 2.052%, respectively, demonstrating a significant enhancement. The proposed BHNAS method extends the search optimization space, obtaining more excellent configurations for the hidden layer nodes. The proposed methods have significant implications for temperature field reconstruction, the field of transfer learning, and the optimization of hidden layer configurations.


Optimizing Disaster Response: OptiDrone- Advanced Integration of Dijkstra's Algorithm and Cutting-Edge Software Solutions for UAV Path Planning and Obstacle Avoidance Efficiency

Abstract: The objective of the research is development of a specific concept called "OptiDrone," which is based on the integration of Dijkstra's Algorithm and the latest development of aerial vehicles' path planning and obstacle avoidance efficacy. The study involves a combination of theoretical and algorithmic refinement as well simulation-based experiments to test the effectiveness of OptiDrone in dynamic disaster scenarios. OptiDrone's combination of powerful route planning techniques along with advanced software programs is set to achieve a substantially higher response rate and operational resilience in the face of difficulties. The results add much value to the body of knowledge about UAV-assisted disaster management systems, indicating possible gains in efficiency and timeliness while addressing crisis situations. Different disciplines of disaster management, robotics, and software engineering can benefit from this research, which is a significant milestone towards the use of more efficient and innovative unmanned aerial systems in disaster response.


FOSTERING LITERACY SKILLS IN KINDERGARTEN THROUGH PROJECT-BASED POP-UP BOOK CRAFTING

Abstract: This study is an experimental research aimed at determining the influence of project-based pop-up book creafting on literacy skills. The population in this study consists of all kindergarten children in the city of Makassar. The research sample was selected using a probability sampling technique, and the selected kindergartens were Teratai UNM Kindergarten with 15 children and Ceria Kindergarten with 15 children. The study analyzes findings using descriptive analysis techniques and Independent-sample T-test. The results showed that the average post-test score of students who participated in project learning in the creation of pop-up books increased to 83.52, while students who participated in conventional learning reached 66.48. The hypothesis test results showed that the t value was 5.486 with a significance of 0.000, confirming a highly significant difference in literacy skills between the groups that followed project-based learning and conventional learning. Therefore, based on the research findings, improving literacy skills in children requires attention to the learning model used, ensuring that the provided learning activities are suitable and capable of stimulating child development.


A Building Model for Enhancing Information Systems Security

Abstract: Today, electronic systems and information have become no less important than food and water for human life. No one can deny this fact. Electronic information systems contribute to the development of life in many areas. But some electronic information systems should not be available for anyone to use, such as reading, operating, modifying or destroying without permission. This type of electronic information systems must be protected in some way based on the related situation. . Password-based authentication is the first defense for most information systems. Password security enhances the security of the entire information system. Therefore, password protection models become very important in such cases to help users improve authentication security. Researchers published various methods based on salting, hashing, symmetric encryption, and key splitting methods. The paper conducted by Saleh Al-Asali describes a method for generating a suitable secret key that is easy to memorize and remember, as he succeeded in generating a password that is strong and easy to remember. This paper improves the previous method by adding some improvements mentioned in the section described in the suggested method.


Needs Analysis for Education for Students with Health Impairments

Abstract: As the number of students with health impairments continues to increase and the need for customized educational support increases, interest in education for students with health impairments is increasing. This study explored deeply and comprehensively the development tasks in education for students with health impairments to solve current issues and response to educational changes. In specific, the needs of all subjects(public officials, teachers, teachers of consigned educational institutions, students, and parents) related to education for students with health impairments were investigated through focus group interviews. As a result of the study, a total of 10 needs related to the curriculum and contents, educational methods and evaluations, student and teacher support, and the new educational policies were identified, and we found that each need was closely related. Each need derived from this research explains the development tasks for the education of students with health impairments and the necessity of establishing a role for each subjects.


Analysis of early childhood teachers’ climate change teaching capabilities using IPA technique

Abstract: This study examined the importance and implementation of climate change teaching competencies for early childhood teachers. An IPA analysis was conducted to examine the priorities of educational content to strengthen early childhood teachers' climate change teaching capabilities. For this study, questionnaires were distributed and collected online to early childhood teachers working in kindergartens in Chungcheongbuk-do and Gyeonggi-do. The final research subjects sampled were 51 people. As a result of this study, looking at the difference between the current level and importance of early childhood teachers' climate change response practice competency and ecological citizenship competency, there was a significant difference. The importance of overall climate change response capabilities and ecological citizenship capabilities was higher than the current level. And looking at the results of the IPA analysis of early childhood teachers' climate change response practice capabilities, the strengthening and maintenance of teaching capabilities was found to be the will to implement climate change and climate change sensitivity. The capacity that requires intensive management was found to be the ability to reflect on climate change. According to the IPA analysis results among early childhood teachers' teaching competencies on ecological citizenship, the competency that required intensive management was participation, and the competency that required gradual improvement was justice. Through the results of this study, climate change teaching capabilities necessary for early childhood teachers were derived and the direction of teacher education for this was discussed.


Development Model of Basic ECG Algorithm Interpretation based on Android Application to Increase Ability of Nurses

Abstract: Introduction: ECG interpretation ability by nurses is still not appropriate, thus affecting the accuracy and speed of the next action that will be given to patients to reduce mortality. This study aimed to develop the use of an Android system based ECG interpretation algorithm application to improve the ability of nurse. Methods: Research development design to develop the Android system based ECG interpretation algorithm application. The sampling method used purposive sampling as many as 90 nurses in Universitas Airlangga Hospital, Surabaya, Indonesia. The independent variables were interpretation skills (rhythm, frequency, pacemaker, axis, extrasistole, block, enlargement of heart muscle, coronary heart disease, conclusion). The instruments that are used are ECG recording, ECG interpretation sheet, and focus group disscusion. The analysis used an independent t-test with a significance level of α ≤ 0.05. Results: The results of developing an ECG interpretation algorithm application based on the Android system have received recommendations from experts and feasibility tests have been carried out. There was a relationship between basic ECG interpretation capabilities with the use of an android system based ECG interpretation algorithm application. Increasing the ability of nurses had p value of 0,000. Conclusion: The application of an ECG interpretation algorithm based on an android system can improve nurses' abilities in interpreting basic ECG. For future researchers, it is necessary to develop and refine the Android system-based ECG interpretation algorithm application and this can be applied on a case-by-case basis.


Analysis the impact of digital campaign on healthcare provider-waste management provider

Abstract: This research aims to analyze the impact of digital campaigns on the relationship between health service providers and waste management service providers using qualitative methods. This research utilizes literature studies related to the research topic. This qualitative data will be analyzed using an inductive approach to identify patterns, thematic findings, and dynamics that emerge in the relationship between health service providers and waste management service providers after the implementation of the digital campaign. The results of this study are expected to provide in-depth insights into the role of digital campaigns in shaping and improving relationships between the healthcare and waste management sectors and the implications for sustainable waste management practices.


EMOTIONAL LEXICONS IN FOOD AND DRINK ADVERTISEMENTS

Abstract: The effectiveness of advertisement content is one of the most significant factors affecting consumers’ affective and behavioral intentions. Consumption emotions which consumers experience before, during and after using a product partly derive from their exposure to the advertisement. Various consumption emotions for different food products and experiences have been explored and validated. However, there has been little research that scrutinizes emotional lexicons in advertisements and how these lexicons affect consumer behaviors. This empirical research adopted content and thematic analysis to explore the emotional lexicons used in food and beverage advertisements. The study examined advertisers’ perspectives of emotional lexicon and the degree of influence on consumers’ perceptions and behaviors. The findings showed that three themes of the emotional words and expressions were used in food and beverage advertisements: sensory, affective, and behavioral evocative. This study made theoretical contributions to the knowledge of consumption emotion and provided valuable insights into the method and process of creating emotional lexicon. It also proposed a working list of emotional lexicons helpful for food and beverage advertising


IMPROVING STUDENTS’ ENGAGEMENT THROUGH THE PROGRESSION OF READING, WRITING, AND PRESENTING IN STUDYING LITERATURE

Abstract: This study was conducted to examine the implementation of a pedagogical approach called the progression of reading, writing, and presenting in studying American and British Literature among English majors at the Foreign Trade University. By drawing upon the principles of studentcentered learning, this study investigated the impact of this approach on students' levels of engagement. Within the framework of Fredericks et al. (2004), this study was expected to shed light on the current state of students' behavioral, emotional, and cognitive engagement with the course through a comprehensive analysis of 38 students' responses obtained from multiple sources, including questionnaires, self-reports, and interviews. The findings revealed a comprehensive understanding of students' engagement in learning American and British Literature and suggested effective strategies for enhancing student engagement in literature courses.


TECHNIQUES AND INNOVATIONS FOR WISDOM TOOTH EXTRACTIONS

Abstract: Background: Wisdom tooth extractions are common surgical procedures associated with post-operative complications. This quantitative analysis aimed to evaluate the efficacy of various surgical techniques and innovations in wisdom tooth extractions. Methods: A systematic review was conducted, searching databases for studies published between 2010 and 2024. Inclusion criteria encompassed studies investigating surgical techniques, innovations, and outcomes in wisdom tooth extractions. Data were synthesized, and meta-analyses were performed where applicable. Results: Thirty-two studies met the inclusion criteria. Minimally invasive techniques, including piezoelectric surgery and laser-assisted surgery, demonstrated significant reductions in post-operative pain scores compared to conventional techniques (mean difference: -1.5, 95% CI: -2.3 to -0.7, p < 0.001). Advanced imaging modalities, such as cone-beam computed tomography (CBCT) and computer-aided design/computer-aided manufacturing (CAD/CAM) technology, were associated with lower complication rates compared to conventional surgery (odds ratio: 0.45, 95% CI: 0.32 to 0.63, p < 0.001). Biologic adjuncts, such as platelet-rich plasma (PRP), demonstrated enhanced bone formation and reduced post-operative infection rates compared to controls (mean difference in bone formation: 2.0 mm, 95% CI: 1.5 to 2.5, p < 0.001). Conclusion: This quantitative analysis highlights the efficacy of minimally invasive techniques, advanced imaging modalities, and biologic adjuncts in improving outcomes of wisdom tooth extractions. Integration of these innovations into clinical practice has the potential to optimize patient care and enhance surgical outcomes.


Comparative Analysis of Controlled Substance Monitoring Systems Based on Health Information Technology: Focusing on Prescriptions and Dispensing

Abstract: This study was conducted to propose ways to improve the domestic system based on a comparative analysis of domestic and foreign Health Information Technology (HIT) system using cases to prevent misuse and abuse of controlled substances. Korea, the United States, and Australia were selected as the countries to be investigated as representative examples of nationwide use of HIT. Literature data was collected from the official website of the system operating organization and major literature databases and search engines such as Pubmed and Google Scholar using the name of each country's HIT system as a keyword. We focused on analyzing the purpose of system operation, target drugs, information collection method, system operation method, and compensation to system users. Korea’s Narcotics Information Management System (NIMS) is the only system that can track the serial numbers of controlled substances in connection with prescription and dispensing records, and is designed and operated with a focus on regulatory purposes to improve legal compliance. NIMS had a relatively long reporting cycle, so there were limitations in checking the latest controlled substances prescription and dispensing records. It was also the only system in which pharmacists did not have the authority and role to check and monitor prescription records. In order to effectively prevent misuse and abuse of controlled substances, the reporting cycle must be shortened by switching to a real-time monitoring system including nonreimbursement medications. In addition, there is a need to guarantee pharmacists the authority to request prescription records before dispensing and the roles that accompany this.


An Analysis of Policy Change in Multicultural Education using Kingdon's Multiple Stream Framework Model: Based on the Policy Change from 2013 to 2022

Abstract: The study applied Kingdon's multiple stream framework model to analyze the process of change in multicultural education support policies promoted from the Park Geun Hyen government to the Moon Jae Inn government, clarifying policy issues, policy alternatives, the flow of politics, the opportunity to open the window of politics, and the identity of policy leaders in the process of change. To achieve this research purpose, 2013-2022 was set as a timely range, and various data such as statistical data, press releases from the Ministry of Education, presidential election pledges, and government press releases were collected and analyzed. The main analysis results are as follows, the flow of policy problems consisted of statistical indicators such as the ratio of multicultural students and the enrollment rate, holding multicultural education forums, prejudice against multicultural children, and collective feedback through forums. Also, the flow of policy alternatives mainly consisted of presidential election pledges and proposals from lawmakers. In the flow of politics, the national atmosphere of the need for support for multicultural students and the changes of the administration were included. The window of multicultural education support policy opened twice, while the Park Geun Hyen government and the Moon Jae Inn government were playing the role of policy leaders who led the policy change.


Understanding Digital Natives Learning Experience through Japanese Language Exam at Nihongo Tesuto Bunkasai Competition by PGBJ Jabodetabek in 2023

Abstract: Integrating technology into Japanese language education has revolutionized the methods of instruction and learning. Especially while instructing the present generation known as digital natives. Educational institutions need to incorporate technology as a tool for teaching and learning due to the close relationship between digital natives and technology. This research aims to assess the utilization of the web-based test (SHIGURU) during the 2023 Bunkasai events organized by PGBJ-SMK (Forum of Japanese Language Teachers for Vocational High Schools) within the area of Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi). This study employs a descriptive research methodology that incorporates both quantitative and qualitative approaches. Data can be collected through direct observation, questionnaires, and interviews. The study utilized primary and secondary data sources, which were examined through triangulation procedures. This study examines the benefits and drawbacks of utilizing shiguru and delves into a comprehensive comprehension of how the digital generation acquires knowledge and how Japanese language education should incorporate pedagogical principles and practices to cater to the requirements of digital natives in contemporary Japanese language education.


STUDENTS’ USAGE OF CHATBOT IN WRITING ASSIGNMENTS: ISSUES RELATED TO ACADEMIC INTEGRITY

Abstract: The rise of artificial intelligence (AI), like ChatGPT chatbot, has generated heated discussions in the education field. While ChatGPT has gained popularity among students for its ability to provide instant and lengthy responses to academic questions, several teachers and researchers have voiced concerns regarding the authenticity and quality of the AI generated or facilitated works. This study investigates students’ attitudes towards using chatbots, their common practices of using chatbots in writing assignments, and the impacts on academic integrity. A questionnaire was issued to 80 first year students enrolling in a Global Citizenship Education course (in which students have Academic Writing module) at an international university in Hanoi. After that, 30 of these participants were interviewed. The preliminary data analysis revealed that while students had overwhelmingly positive attitudes toward the tool, they lacked a thorough understanding of the risks involved in using the chatbot. The study aims to contribute to the conversation of using AI in education as well as provide recommendations for promoting academic integrity while using Chatbots and similar tools. It calls for due attention be paid to developing procedures for or best practices of using Chatbots in the classrooms without compromising authenticity and academic integrity.


Readability and credibility evaluation of most-visited health websites based on eBizMBA and Alexa global ranking

Abstract: Introduction: Online health information is one of the most important and widely used sources of information. Currently, a significant number of individuals use the internet for health-related information to learn about health, disease, health promotion, and threats to their health.Material and Methods: This research examined the top 15 health websites based on their popularity in eBizMBA and Alexa rank from January to February 2022. A total of 30 health websites (15 from each category) were evaluated in terms of credibility by the use of Journal of the American Medical Association (JAMA) and health on the net foundation (HON) code. Also, the readability of the mentioned websites was evaluated by the use of four readability tools.Results: Most of the websites ranked by both Alexa and eBizMBA met the “Authority” and” Complementarity" criteria. When it comes to the readability of the 30 most visited health websites according to eBizMBA and Alexa analytics in the world, the analysis demonstrated that the readability of highly-ranked health websites was higher than the recommended level.Conclusion: Some of the websites had deficiencies according to the HONcode and JAMA criteria, and the average readability of the websites did not meet the gold standard. Despite the increasing use of the internet for medical information, these resources' poor quality and readability remain a barrier to informed decision-making of patients.


iSpring on English Language Teaching and Learning: A Literature Review

Abstract: iSpring is one of various software which is benefit in English language teaching and learning. There are numerous researches that bring up the use of iSpring to support the material and quiz development. This research aims at providing comprehensive literature review about iSpring in English language teaching and learning. This research’s objectives are investigating; 1) the roles of iSpring in English language teaching and learning and 2) the effectiveness of iSpring in English language teaching and learning. Qualitative research method with library research approach was used in this research. The data consists of 3 theses, 4 conference proceedings, 5 journal articles that taken mostly from Google Scholar. The data then analysed using content analysis to match the objective of this research. The findings showed that iSpring has several important roles for English language teaching and learning such as; making English teaching and learning activities becomes easier; helping students to learn English language; creating interest, motivation, confident, concentration, and independence for students in English learning; supporting all types of learning styles and various level of students in English learning; providing effective English teaching and learning activities; and also accommodating various English teaching methods. Besides that, this research also showed that iSpring was effective for foreign language distance learning, improving students’ independence on self-evaluation, improving receptive skill, and productive skills as well. Therefore, iSpring is suitable to be used in education, especially to support the English language teaching and learning.


The Prevalence of Smartphone Addiction and Its Relationship with the Level of e-Health Literacy in Medical Sciences Students

Abstract: Introduction: Smartphone addiction has increased in recent years, especially with the onset of COVID-19 among students. It is possible that as the level of eHealth literacy increases among students, their addiction to smartphones decreases. This study aims to investigate this hypothesis.Material and Methods: This cross-sectional study was conducted on 390 medical sciences students. Two standard questionnaires were used to gather data. The first questionnaire was the Smartphone Addiction Inventory Scale, and the second questionnaire was the eHealth Literacy Scale. Data were analyzed using descriptive and analytic statistics.Results: There was no significant relationship between the gender of the participants and the mean scores of smartphone addiction or eHealth literacy. However, the relationship between the age of the participants and the mean scores of smartphone addiction or eHealth literacy was significant. Only the relationship between the educational level of the participants and the mean scores of smartphone addiction was significant. The correlation between smartphone addiction and eHealth literacy in students was not significant.Conclusion: Age and educational level were significant factors influencing smartphone addiction. To decrease smartphone addiction and increase eHealth literacy, educational programs should be implemented for medical science students, who play a crucial role as future guardians of health.


Designing Academic Data Visualization Dashboard Using Google Data Studio at SMPN 8 Pariaman

Abstract: This study aims to use Google Data Studio to produce an academic data visualization dashboard system to display information, which can manage academic data, namely teacher attendance data and student grades, to provide decision-making support for decision makers in the monitoring process and evaluate school internal processes and monitor student grades at SMPN 8 Pariaman School. The type of research used is the R&D (Research and Development) approach SDLC (Systems Development Life Cycle) method with a prototype model. The stages carried out are communication, planning, modeling, construction and handover (handover). The system testing method studied uses questionnaire guidelines for functional testing to test system functionality to verifiers and usability testing to test system usability and suitability of functions and services to users. Based on the results of the validator functional test study, the results of meeting the functional requirements with both a value of 1 and 89% of the feasibility value of the system usability test are classified as very feasible. Therefore, it can be concluded that the academic data visualization dashboard system using Google Data Studio meets the requirements and is very suitable as a support for SMPN 8 Pariaman School in processing academic data on teacher attendance and student grades.


Web-Based Application For Parenting Patterns In Vocational Schools In The Environment Of Politeknik Pelayaran Sorong

Abstract: Digitalization of education is a logical consequence of developments over time, a response to educational services that are experiencing changes in both the learning system and learning culture. Developments in the field of education are closely related to the term innovation. Innovation in the realm of education is an obligation for all educational actors. Moreover, the development of science and technology is growing rapidly. The parenting pattern that has been implemented in most vocational schools within the Ministry of Transportation is still more of a manual system that cannot be connected directly to digitalization. The aim of the process of developing digitalization of parenting patterns is expected to increase efficiency and optimization in many ways, including efficiency and optimization of parenting activities, connectivity between institutions or units involved in parenting, access to data related to parenting patterns, personal data of cadets and caregivers, as well as ease of use. information in accessing rules relating to parenting patterns. The research method used is a mixed type of research. Mixed research is the use of two types of research, namely qualitative and quantitative in one study. The research location is planned to be carried out at a vocational school under the Ministry of Transportation (Poltekpel Sorong). This research then produced an online-based digitalization development desktop software and was then named the see cadet application website. This development and research uses the ADDIE Development Model, namely the analysis stage, design stage, development stage, implementation stage and evaluation stage.


An Extension Proof of Riemann Hypothesis by a Logical Entails Truth Table

Abstract: There were many mathematicians who tried to prove or disprove the statement of Riemann Hypothe-sis. However, none of them have been successfully approved by the Clay Mathematical Institute. In addition, to the best of this author’s knowledge, these mathematicians haven’t employed the technique of logical truth table during their proofs. With reference to this author’s previous proof in [1], this author have employed the method of multiplicative telescope together with the prime boundary gaps. In this extended version of my proof to the Riemann Hypothesis, this author tries to show that RH statement is true through the four cases of the conditional statements in the truth table. Three of the cases (I, II, IV) are found to be true for the conditional statement in the Riemann Hypothesis while only one (case III) is found to be false (and acts as the disproof by a counter-example). Moreover, there are also three sub-cases (i, ii, iii) [1] among these four tabled cases. The main idea is that the we may disproof the hypothesis statement that is similar to the RH one by first find a counter-example which is obviously a disproof (case III) to the (Riemann) hypothesis. But it is NOT compatible with the GÖdel’s Incompleteness Theorem. Otherwise either the disproof to the statement or the Gödel is incorrect which is impossible. Hence, the disproof is said to be incompatible with the Gödel. On the other hand, all of the other truth cases (I, II, IV) for the statement are indeed the examples for the pos-itive results to the Riemann Hypothesis statement and are compatible with the Gödel. Therefore, the only way to make a conclusion is to say or force the Riemann Hypothesis statement to be correct.In general, for any hypothesis with the conditional statements structure like the Riemann one, we may also prove them by the similar techniqe and the arguments of the truth table for their conditional statements together with the Gödel’s Incompleteness theorem to force the positive result for the hy-pothesis statement. Actually, there are many applications for the truth tables especially in the fields like language (structure & modeling) or in engineering (logic gates & programming) etc during our everyday usage.


Development of Android-based Interactive Learning Media to Improve Student Understanding Through Experiments on Optical Equipment Materials

Abstract: Learning media based on the Industrial Revolution 4.0 are required to link learning with technical advancements and dramatically improve the learning experience. This study aims to (1) create a product in the form of Android-based mobile-learning media that can carry out virtual experiments on learning about image creation in mirrors. (2) Assessing the practicality of the learning medium created for conducting experiments. (3) Understanding students' reactions to learning media based on Android. (4) Understanding students' comprehension of experiments utilizing the media generated. This research is development research, or R&D, based on the ADDIE development paradigm. There are five stages: 1) analysis, 2) design, 3) development, 4) implementation, and 5) evaluation. The subjects in this research were 28 class XI Science students. This research design is a one-group pretest-posttest design. Questionnaires and interviews were used to collect data regarding suitability and student responses in this research. The data analysis technique employed in this research uses the statistical Wilcoxon and n-gain tests. The Wilcoxon test results obtained a sign value (0.000) < 0.05, indicating differences in student learning outcomes before and after treatment, and the N-Gain test results showed that 50% of students had high understanding and 32% had moderate understanding. So the research findings reveal the feasibility of using Android-based interactive learning media to boost student knowledge through experiments on optical materials.


Trajectory Tracking Control Using Evolutionary Approaches for Autonomous Driving

Abstract: Capitalizing on the strides in artificial intelligence and the escalating demand for safer and more efficient traffic systems, the investigation unveils a trio of evolutionary algorithms - namely Grey Wolf Optimizer (GWO), Multi-Verse Optimizer (MVO) and Salp Swarm Algorithm (SSA) - in the context of hyperparameter calibration for the Proportional-Integral-Derivative (PID) controller. The PID controller, revered for its classical design and wide industrial adoption, forms the cornerstone of feedback control systems. To exemplify the utility of the proposed algorithms, two distinct trajectory scenarios are employed as target trajectories. Rigorous numerical evaluations, accompanied by graphical analyses, showcase the prowess of these algorithms in steering the trajectory tracking process. The study unfolds novel contributions, rendering an unprecedented application of these optimizers in the PID controller realm while offering a comprehensive scrutiny of their performances.


Gradient Vanishing Generative Adversial Networks Optimization In Medical Imaging: A Survey

Abstract: Deep learning has gained significant attention in recent years for its ability to imitate human abilities, such as visual and auditory perception. These algorithms use statistics to find patterns in data and have shown promising results in various applications. Generative adversarial networks (GANs) have emerged as one of the most powerful generative models that can produce visually appealing samples. However, GANs suffer from several problems, such as mode collapse, non-convergence, and training instability. The generator's gradient is eliminated when the discriminator is optimal, resulting in slow learning and vanishing gradients. In this paper, we review the challenges associated with training GANs and the various methods proposed to address these issues. Recent research has proposed several approaches, including architectural modifications, regularization techniques, and alternative loss functions. Despite these efforts, the instability problem persists, and no studies to date have fully resolved the challenges associated with training GANs. Our survey presents a focused analysis of current GAN training advancements, with a special emphasis on addressing gradient vanishing in medical imaging. We highlight key challenges, review optimization techniques to mitigate these issues, and propose a framework for future research aimed at enhancing GAN stability and interpretability. This work contributes to advancing GANs in medical applications, improving their performance in generating realistic, high-quality medical images.


Perencanaan Video Iklan dengan Teknik Motion Graphic untuk Promosi pada Universitas Swasta XYZ

Abstract: Marketing and promotion methods have significantly evolved in the rapidly changing digital era, impacting various sectors including higher education. Particularly, the promotion of study programs at private universities has faced challenges, notably within the Faculty of Computer Science. Despite its continuous growth and innovation, attracting prospective students has become increasingly difficult as interest in the program has declined this year. This trend underscores the need for more engaging and efficient promotional strategies. Motion graphic animation has emerged as a creative solution within the advertising and promotion industry. Its dynamic visual appeal and ability to simplify complex messages make it an invaluable tool in marketing communications. Utilizing motion graphic animations for study program advertisements not only highlights the faculty's technological advancements and innovations but also aims to attract a digitally savvy and visually oriented young audience. This paper discusses the development of marketing advertisements designed to attract new students to XYZ university, detailing the process from feasibility studies and initial planning to analysis, advertising system design, and implementation. The methodologies for data collection include interviews and observations, with the application developed using Adobe After Effect, Adobe Illustrator, and Adobe Audition.


Activities of Intellectual Property Propaganda in the Vocational Education System

Abstract: Currently, intellectual property violations are serious and tend to increase, especially in the education system, including the vocational education system. Lack of understanding of intellectual property regulations has unintentionally led to many cases of violation without even knowing it. This is necessary to improve people’s understanding of intellectual property and have appropriate behavior. This shows that appropriate propaganda activities are needed to improve this situation. Based on reference to State documents on intellectual property; surveying 300 people who are students, teachers, staff, and administrators at several vocational education institutions, the purpose of this study is to evaluate the current situation, point out the position, role, and importance the importance of intellectual property propaganda activities in the vocational education system, pointing out the causes of limitations and inadequacies; from there, propose solutions to improve the quality of intellectual property propaganda activities in the vocational education system in the future.


International and national service standardization systems

Abstract: The article provides an overview of the issues of service standardization. The features of international certification are covered. The author examines the types of standardization, as well as what advantages this type of certification provides.


Smart Bionic Vision: An Assistive Device System for the Vis-ually Impaired Using Artificial Intelligence

Abstract: Nowadays, Smart Glass emerges as a potential aid for individuals with visual impairments, offering the promise of enhanced quality of life. Designed for those seeking independent navigation with a sense of social ease and security, the concept revolves around the idea that visually impaired individuals prefer inconspicuous assistance tools. This paper delves into the significant advancements within wearable electronics, spotlighting additional features. This innovative glass offers a multifaceted solution for individuals with visual impairments, providing assistance in diverse scenarios. Beyond aiding in the reading of scripts, they excel at distinguishing between currencies, enabling users to navigate financial transactions with ease. The glasses also enhance color recognition, allowing wearers to perceive and appreciate the vibrant spectrum of the world around them. Additionally, the incorporation of obstacle detection technology ensures a heightened sense of safety by alerting users when they are in proximity to potential hazards. Furthermore, the glasses feature advanced facial recognition capabilities, contributing to a more inclusive and socially connected experience by detecting faces and fostering seamless interactions.


Social interactions in the higher education system in the context of informatization of society

Abstract: Informatization of various aspects of social life and digitalization of economic sectors changed the content of the activities of many social institutions. This touched upon the problem of social interactions in modern higher education. Practical actions in the aspect of digitalization of higher education require social reflection for their effective regulation. The purpose of the article is to determine the factors influencing the implementation of the main institutional functions of higher education through social interactions of teachers and students in the context of digitalization of higher education (in particular, during the transition to distance learning). The article discusses theoretical approaches to understanding digitalization processes, which are complemented by the well-known approaches to studying the essence of social interactions. Systemic and institutional approaches were used. The theoretical analysis of the features of social interactions using digital technologies is supplemented by a secondary analysis of sociological research on the problems of digitalization of the higher education system, the introduction of digital technologies and distance learning at universities, and the results of a sociological survey of the students at Penza State University (April–May 2020). The article describes the experience of leading universities in the use of artificial intelligence, big data analytics and the work of neural networks in university activities. On the basis of the conducted research and secondary data analysis, it was concluded that the institutional function of knowledge transfer in the higher education system was quite successfully performed in the new learning conditions. The possibilities of social interactions and communications with teachers and management structures of universities are influenced by technological, educational, organizational and communication factors. Under their influence, the professional and general cultural competencies of university graduates will be formed, which are prerequisites for them to occupy new social statuses after graduation.


Study on Regional Cultural Literacy for Korean Education : Focusing on Locality of Busan

Abstract: The purpose of this study is to propose the necessity of cultural literacy education in the Korean language focusing on the Busan region, and to suggest the direction of its educational content composition. To achieve this goal, we analyzed three monographs and one lecture related to studies pertaining to Busan with the aim of designing the framework for cultural literacy education targeting foreign exchange students in Korean education. As a result, we devised educational elements reflecting the locality of Busan based on various places in Busan over a 13-week period. We also made recommendations on how such locality can be implemented in cultural literacy education in terms of attitude, knowledge, context, and practical use.


Improving Balaghah Mastery Through Teams Games Tournaments with Crossword Puzzle Media in Higher Education

Abstract: The selection of appropriate teaching methods by educators and the optimization of learning media utilization are crucial factors in achieving success and effectiveness in the learning process. Accordingly, this research aims to examine the impact of using the Teams Games Tournament method with crossword puzzle media on the learning outcomes of Balaghah (Arabic rhetoric) students at the State Islamic University Imam Bonjol Padang. This research employed a quantitative approach with a quasi-experimental pretest-posttest control group design. Data collection techniques involved administering pretests and posttests to both the control and experimental groups. The collected data were analyzed using descriptive statistical tests, tests for normality and homogeneity (Kolmogorov-Smirnov test), and independent sample t-tests. The research results indicated a significant variation in student learning outcomes before and after using the Teams Games Tournament method with crossword puzzle media in Balaghah learning. Based on the findings, the average pretest scores for the experimental group and control group were 52.83 and 52.23, respectively, while the average posttest scores for the experimental group were 92.87 and 81.46 for the control group. The independent sample t-test showed a significance value of 0.000 < 0.05, indicating sufficient evidence to support the alternative hypothesis (Ha). Therefore, it was concluded that there was a significant difference in student learning outcomes before and after implementing the Teams Games Tournament method with crossword puzzle media in Balaghah learning. These findings validated the effectiveness of this method in enhancing understanding and student learning outcomes in Balaghah material.


Utilizing Blockchain for the Detection of Counterfeit Products

Abstract: The realm of supply chain management, pervasive challenges such as service redundancy, inadequate coordination among various departments, and a lack of standardization often stem from a fundamental issue – the absence of transparency. The escalating prevalence of product counterfeiting compounds these challenges, with counterfeit items significantly impacting legitimate firms.


Supplemental Material: Juvenile hafnium isotopic compositions recording a late Carboniferous–Early Triassic retreating subduction in the southern Central Asian Orogenic Belt: A case study from the southern Alxa

Abstract: Analytical methods, U–Pb geochronological data, zircon Lu–Hf-O isotopic compositions, whole-rock major and trace element data are presented in the Supplemental Material.


Prediksi Harga Saham Syariah menggunakan Bidirectional Long Short Term Memory (BiLSTM) dan Algoritma Grid Search

Abstract: Sharia stocks are one of the investment instruments in the Islamic capital market. In the capital market, it is known that stock prices are very volatile. This makes investors need to carry out a strategy for making the right decision in investing, one of which can be done by predicting stock prices. In this study, predictions were made using historical data on the closing price of Islamic shares of PT. Telkom Indonesia Tbk with the Bidirectional Long Short Term Memory (BiLSTM) method. In building the best prediction model, it is necessary to choose the right parameters and one way to do this is to use the grid search algorithm. Based on the results of the test analysis, it was found that the smallest Mean Absolute Percentage Error (MAPE) value was found in the BiLSTM model in the distribution of data with a percentage of 90% training data and 10% testing data and parameter values obtained based on parameter tuning using grid search, including the number of neurons 25, 100 epochs, 4 batches, and 0.2 dropouts. The MAPE obtained in this study was 10.83% and based on the scale on the MAPE value criteria, this shows that the resulting prediction model is accurate. As for the test results from the comparisons made on the BiLSTM and LSTM models using grid search as a tuning parameter and models without using a grid search or it can be called a trial and error approach as a tuning parameter, it is found that the model with better predictive performance is found in BiLSTM using a grid search. compared to other models.


Intervention to Enhance Reading Comprehension Skills of Grade 7 Students through Background Knowledge Activation, Repeated Readings, Reading Aloud, and Asking Questions

Abstract: This study sought to assess the reading proficiency of 23 purposively selected seventh-grade students at Caponayan National High School during the academic year 2023-2024, focusing on their reading comprehension levels. These assessments were the foundation for developing an effective reading program tailored to students’ needs. Over four weeks, data collection involved repeated reading-aloud sessions and immediate questioning post-reading. In the educational process carried out in the Philippines, the Informal Reading Inventory standard is used. The analysis revealed that the respondents demonstrated mastery of essential sight words, with only a few identified miscues. Significantly, the number of students experiencing frustration decreased from 16 to 4 after the intervention, accompanied by notable improvements in reading comprehension. The instructional level increased from 7 to 13, while the highest comprehension level, classified as independent, rose from 0 to 6. Assessing the students’ overall performance before and after the intervention indicated substantial progress. Statistical analysis demonstrated a significant difference before and after the intervention. Based on these findings, the study concludes that even a brief intervention can significantly improve students’ reading abilities.


The Contribution of EFL Students’ Vocabulary Mastery and Motivation to Writing Ability of Eighth-Grade Students at Smpn 5 Denpasar

Abstract: The ability to compose written messages in words, sentences, texts, and coherent words that readers can understand is known as writing ability. The objectives of this research were first to investigate how much the contribution of vocabulary mastery to writing ability, the second was to investigate how much the contribution of motivation to writing ability, and the third was to investigate how much the contribution of vocabulary mastery and motivation simultaneously to writing ability. This study was designed in the form of correlational research design. The population of this study was the eighth-grade students at SMPN 5 Denpasar. In this study, 149 students served as samples. They were chosen using a proportionate random sampling technique. Test of Multiple choice was for vocabulary mastery, questionnaire was for motivation and test of writing assignment was for writing ability, those were utilized to gather the data for this study. With the use of SPSS 26.0, linear and multiple regression analyses were performed on the data. The findings showed that there was high and significant contribution of vocabulary mastery to writing ability. The contribution of vocabulary mastery to writing ability was 69%, and there was high and significant contribution of motivation to writing ability. The contribution of motivation to writing ability was 70.5%. Moreover, the contribution of vocabulary mastery and motivation simultaneously to writing ability was 79.9%. It indicates that there was high and significant contribution of vocabulary mastery and motivation simultaneously to writing ability of eighth grade students of SMPN 5 Denpasar.


Digital Policing

Abstract: This chapter introduces the notion of cybercrime that is handled by digital policing. It considers the definition of cyber-dependent and cyber-enabled crimes as per the government's National Cyber Security Strategy 2022 glossary. Cybercrime and the police response are covered in policing degrees, which include an overview of the internet and more advanced topics, such as social media and the rapidity of technological development. Since technological change is likely to continue at an ever-increasing pace, a police officer must be able to recognize new forms of crime in new environments and take appropriate and timely actions. The chapter acknowledges that the main complication when dealing with cybercrime is often the international nature of evidence gathering.


User-Centric Security Frameworks in Cloud Computing

Abstract: The rapid proliferation of cloud computing has revolutionized data management, yet the integration of user-centric security frameworks within cloud service models remains a persistent challenge.This research endeavors to address this gap by proposing a Dynamic Resolution Allocation Approach aimed at optimizing the synergy between robust security measures and an enhanced user experience.The study begins with an exploration of the diverse challenges inherent in achieving a harmonious balance between security and usability, including issues related to cloud environment diversity, user privacy concerns, the dynamic cybersecurity landscape, and interoperability challenges.Leveraging principles of standardization, user-centric design, and continuous research adaptation, the Dynamic Resolution Allocation Approach seeks to offer a comprehensive solution.This paper delineates the methodology, challenges faced in user-centric cloud service models, the proposed dynamic resolution allocation framework, and its implementation and testing.It further discusses the implications of the proposed approach in optimizing user experience through transparency, user-friendly authentication, personalized security settings, educational resources, efficient incident response, clear communication, and continuous monitoring.The findings contribute to the ongoing discourse on user-centric security in cloud computing, presenting a novel approach to bridge existing gaps and enhance the overall security and usability of cloud service models.


Impact of person-job fit and person-organization fit on employee engagement: Moderating role of supervisor support

Abstract: Purpose: This study aimed to examine the impact of two fit concepts, namely, person-job fit (P-J) and person-organization fit (P-O), on employee engagement while taking supervisor support as the moderating variable. Research Methodology: The relationships among constructs were analyzed using correlation, and the study hypotheses were tested using regression. All employees of different mobile telecommunication companies in Bangladesh comprised the study population. The sample size was 100, which was taken using the judgmental sampling technique. Primary data were collected from a field-level survey using a structured questionnaire. Results: The results revealed a positive association between employee engagement and person-job fit, while person-organization fit had a similar association with engagement. The impact of these variables on employee engagement ultimately affects turnover intentions. This study also revealed that the association between person-organization fit and employee engagement is positively moderated by supervisor support. Limitations: The study used a common non-probability sampling technique and a small sample size, which is a limitation. Contribution: The insights will help managers to ensure a match between the job and organizational requirements and those of employees. The study will also inspire future research to connect Field Theory and social exchange theory (SET) with different concepts in different country and industry contexts. Novelty: For the first time in the relevant field, the study simultaneously connected field theory and SET theory with P-J and P-O fit with employee engagement.


A Study on the Effect of Media Literacy Competences on Responding to Fake News

Abstract: This study examined how individual media literacy competencies affect response behavior towards fake news, which is causing damage to individuals and society. Media literacy competencies are being emphasized as a means to minimize this damage. Therefore, the study investigated the relationship between individual demographic characteristics and media literacy competencies (critical competency, use production competency, social communication competency) concerning information distrust, information confirmation, and active response. This investigation utilized secondary data from the Korea Communications Commission's 2021 ‘Media Literacy Measurement Study to Support Media Education.’ The results of the study revealed a positive relationship between information distrust and critical competency, as well as a positive relationship between information confirmation and critical competency, social communication competency, use, and production competency. Additionally, active response exhibited a positive relationship with male participants, those with lower educational backgrounds, individuals with lower media usage times, critical competency, and social communication competency. Conversely, there was a negative relationship with use and production competency. This study found that media literacy competences which are emphasized as countermeasures against fake news, are related to fake news response behavior. Accordingly, as a countermeasure against fake news, it is proposed to strengthen individual media literacy competences through media education.


[Research on automatic generation of multimodal medical image reports based on memory driven].

Abstract: The task of automatic generation of medical image reports faces various challenges, such as diverse types of diseases and a lack of professionalism and fluency in report descriptions. To address these issues, this paper proposes a multimodal medical imaging report based on memory drive method (mMIRmd). Firstly, a hierarchical vision transformer using shifted windows (Swin-Transformer) is utilized to extract multi-perspective visual features of patient medical images, and semantic features of textual medical history information are extracted using bidirectional encoder representations from transformers (BERT). Subsequently, the visual and semantic features are integrated to enhance the model's ability to recognize different disease types. Furthermore, a medical text pre-trained word vector dictionary is employed to encode labels of visual features, thereby enhancing the professionalism of the generated reports. Finally, a memory driven module is introduced in the decoder, addressing long-distance dependencies in medical image data. This study is validated on the chest X-ray dataset collected at Indiana University (IU X-Ray) and the medical information mart for intensive care chest x-ray (MIMIC-CXR) released by the Massachusetts Institute of Technology and Massachusetts General Hospital. Experimental results indicate that the proposed method can better focus on the affected areas, improve the accuracy and fluency of report generation, and assist radiologists in quickly completing medical image report writing.医学影像报告自动生成任务面临疾病类型多样、报告描述缺乏专业性和流畅性等多重挑战。为解决以上问题，本文提出一种基于记忆驱动的多模态医学影像报告自动生成方法（mMIRmd），首先使用基于移位窗口的层次视觉转换器（Swin-Transformer）提取患者医学影像的多视角视觉特征，通过基于转换器的双向编码模型（BERT）提取病史信息的语义特征，然后将多模态特征进行融合，提高模型对不同疾病类型的识别能力。其次，使用医学文本预训练的词向量词典对视觉特征标签进行编码，以提高生成报告的专业性。最后，在解码器中引入记忆驱动模块，解决医学影像数据中的长距离依赖关系。本研究在印第安纳大学收集的胸部X光数据集（IU X-Ray）和麻省理工学院联合马萨诸塞州总医院发布的重症监护X光医疗数据集（MIMIC-CXR）上进行验证。实验结果表明，本文所提方法能更好地关注患病区域，提高生成报告的准确性与流畅性，可以辅助放射科医生快速完成医学影像报告的撰写。.


Temporal Output Discrepancy for Loss Estimation-Based Active Learning

Abstract: While deep learning succeeds in a wide range of tasks, it highly depends on the massive collection of annotated data which is expensive and time-consuming. To lower the cost of data annotation, active learning has been proposed to interactively query an oracle to annotate a small proportion of informative samples in an unlabeled dataset. Inspired by the fact that the samples with higher loss are usually more informative to the model than the samples with lower loss, in this paper we present a novel deep active learning approach that queries the oracle for data annotation when the unlabeled sample is believed to incorporate high loss. The core of our approach is a measurement Temporal Output Discrepancy (TOD) that estimates the sample loss by evaluating the discrepancy of outputs given by models at different optimization steps. Our theoretical investigation shows that TOD lower-bounds the accumulated sample loss thus it can be used to select informative unlabeled samples. On basis of TOD, we further develop an effective unlabeled data sampling strategy as well as an unsupervised learning criterion for active learning. Due to the simplicity of TOD, our methods are efficient, flexible, and task-agnostic. Extensive experimental results demonstrate that our approach achieves superior performances than the state-of-the-art active learning methods on image classification and semantic segmentation tasks. In addition, we show that TOD can be utilized to select the best model of potentially the highest testing accuracy from a pool of candidate models.