Reviewerly/exHarmony huggingface dataset:
Digital Transformation in Education: Using Technologies for Enhancement of Efficiency of Teaching

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

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

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

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

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

&lt;p&gt;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.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Pelatihan Bahasa Inggris “Tenses” Bagi Siswa Sekolah Minggu HKBP Getsemane Medan Labuhan

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 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

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

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

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

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

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

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

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

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

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

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

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.