Reviewerly/exHarmony huggingface dataset:
Computing the decomposable entropy of belief-function graphical models

In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy (d-entropy). This paper provides an algorithm for computing the d-entropy of directed graphical D-S belief function models. We illustrate the algorithm using Almond's Captain's Problem example. For belief function undirected graphical models, assuming that the set of belief functions in the model is non-informative, the belief functions are distinct. We illustrate this using Haenni-Lehmann's Communication Network problem. As the joint belief function for this model is quasi-consonant, it follows from a property of d-entropy that the d-entropy of this model is zero, and no algorithm is required. For a class of undirected graphical models, we provide an algorithm for computing the d-entropy of such models. Finally, the d-entropy coincides with Shannon's entropy for the probability mass function of a single random variable and for a large multi-dimensional probability distribution expressed as a directed acyclic graph model called a Bayesian network. We illustrate this using Lauritzen-Spiegelhalter's Chest Clinic example represented as a belief-function directed graphical model.
A Study on the Construction of Virtual Simulation Experiments for Basketball Projects

Background: Virtual simulation experiments, as a new teaching method and approach, have gradually been introduced into higher education and received recognition from a large number of education professionals. Considering the successful application of virtual simulation experiments in other disciplines, this study aims to employ virtual simulation technology to construct a virtual simulation experiment for basketball projects, with the goal of promoting the application of virtual simulation technology in sports and health education.&#x0D; Methods: The main research methods employed in this study include expert interviews, questionnaire surveys, and software development approaches. A questionnaire survey was conducted among 230 students from six universities, and interviews were conducted with 15 relevant individuals. The demands and requirements of university teachers and students regarding virtual simulation experiments for basketball projects were summarized and refined. The experiment was developed using 3D Studio MAX and Maya as modeling tools. Finally, all aspects of this research were completed through functional validation and application effectiveness evaluation.&#x0D; Results: In the survey stage of needs assessment, a total of 230 questionnaires were collected from six universities. Among them, 63.63% of students claimed to have a relatively good understanding of virtual simulation experiments, 78% of students considered virtual simulation experiments to be of significant importance in teaching, and 84.71% of students regarded this teaching method as relatively relaxed. The development process involved the development of six modules, and after the completion of each module, Unity 3 was used for integration, resulting in the completion of the experiment. Subsequently, functional validation of the virtual simulation was conducted, achieving a 100% pass rate in the testing of various scenarios. An effectiveness evaluation questionnaire was utilized, and the scores from the six dimensions and 20 indicators ranged from a minimum of 3 to a maximum of 5, indicating that university students generally recognized and were satisfied with various aspects of virtual simulation experiments.&#x0D; Conclusion: The construction and application of virtual simulation experiments in China are still in the initial stages, primarily focusing on theoretical research. The virtual simulation experiments were categorized into six sections: basic theoretical learning, technical and tactical application, physical fitness, presentation and competition, rules and refereeing, and observation and evaluation. Various test scenarios were established to assess the interface, performance, and functionality, and both functional validation and application effectiveness evaluation questionnaires yielded positive results. These findings strongly support the assertion that the virtual simulation experiment constructed in this study can serve as an effective supplementary tool for basketball teaching in universities.
Causes of proof construction failure in proof by contradiction

Failure to deduce false suppositions in proof by contradiction is still considered “more difficult” than proving the conditional to in proof by contraposition. This study aims to identify the types of proof construction failures based on the action steps of proof by contradiction, then offer a framework of construction failure hypothesis specifically used in proof by contradiction. The research data were collected and analyzed from the work of students who have agreed to be research participants, a total of 83 students. The results of the analysis of student work successfully identified four types of failures, namely formulating suppositions, constructing and manipulating suppositions, identifying contradictions, and disproving suppositions. These four types of failures then became the material for the development of the hypothesis framework of a failure to construct proof by contradiction, which consists of 17 hypothesis nodes divided into three main hypotheses, namely: operational (action), affective (emotional), and foundational (logical reasoning). The failure hypothesis framework justifies that the sources of the failure of proof construction in proof by contradiction are understanding of the act of producing a proof by contradiction, emotionality towards the coherence of the construction steps, disproving suppositions, beliefs, use of appropriate definitions-theorems and axioms, and cognitive tension in proof by contradiction; and formal logic of the act of producing a proof by contradiction, as well as differences in the underlying logic with other acts.
The Digital Practices of Portuguese Children (6-18) during Covid-19 Lockdown

The Covid-19 pandemic was addressed, in most European countries, with a mandatory lockdown period, during which the use of digital technologies was intensified, for remote working, communication, entertainment, consumption and learning. Our research aims to map the digital practices of Portuguese children (6-18) during lockdown (between March 19th and May 2nd 2020), focusing on their experience of formal Education and on their wellbeing. &#x0D; Our empirical work follows a mixed method, combining an online survey to a representative sample of 509 dyads of parents and children (10-18) and in-depth interviews to families with younger children (6-12). &#x0D; Our findings confirm a significant intensification of the use of digital technologies by children, partly required by school, partly due to the lack of alternatives for entertainment and socialization. Most children find using digital technologies for long periods, due to remote schooling, tiresome and feel anxious due to recurrent news about Covid-19.
중장년 여성학습자의 금융이해력(Financial Literacy) 향상을 위한 요구 탐색 – 금융행위를 중심으로

This study focused on the improvement of financial literacy of middle-aged women learners, and explored the learning needs of middle-aged women's 'Financial Behavior' at a specific level through qualitative research methods. 12 research participants in the 40s and 60s were interviewed by focus groups and groups, and themes were derived using the qualitative content analysis. Participants said that the purpose of financial activity was to achieve ‘economic freedom’. For this reason, they expect four educational needs for ideal financial behavior. These are ‘education needs for insufficient financial knowledge, education needs for planned financial management, systematic education needs for practice, and vocational education needs to secure stable income’. The results of the study are expected to be reflected in future middle-aged women and adult financial education programs. Given that the research participants connected financial education with vocational education, it was confirmed that financial education in lifelong education should not only deliver financial knowledge but also help actual financial behaviors.
Religions Education and Massive Open Online Courses (MOOCs) in Korea: Current Status and Characteristics

[연구 목적] 본 연구의 목적은 한국형 온라인공개수업(K-MOOC) 중 종교 주제의 강좌들에 대한 조사와 분석을 통해 온라인 종교교육의 현황을 정리하고 그 특징들을 파악하기 위한 것이다. [연구 내용] K-MOOC 플랫폼에서 종교 관련 강좌 현황을 수집하여 개설 강좌들의 공통점과 차이점을 확인하였다. 이 중 종교학을 주제로 전체 내용을 구성한 2개 강좌를 선정하여 실제로 수강하면서 구성요소와 내용적 측면을 분석하여 그 특성을 도출하였다. [결론] 연구 결과, 2022년 12월을 기준으로 종교 관련 강좌는 전체 K-MOOC 강좌 수(1300여개) 중 43개에 해당하였다. 이 강좌들은 주제에 따라 종교학 일반에 대한 강좌, 특정 종교에 대한 이해를 구하는 강좌, 인문교육[문학, 사학, 철학]으로서의 종교를 활용한 강좌로 구분할 수 있다. 그 중 종교학 분야에 집중한 2개 강좌의 사례 분석 결과, 내용적 측면에서 종교에 대한 지식 습득을 넘어 종교와 관련된 다양한 현상을 받아들이는 다원적 태도를 함양하는 것을 목적으로 한다. 체계적 측면으로는 한 주 내에 이수할 수 있는 학습 분량으로 20분 내외의 비디오 영상들과 퀴즈, 토론, 읽기자료 등으로 강좌가 구성되었다. 이와 같은 구성은 여타의 K-MOOC 강좌들과 유사한 양상을 보이는데, 이는 종교학 강좌만의 제한점이 아닌 K-MOOC 플랫폼의 한계로 간주된다. 이 연구를 통하여 온라인 종교교육의 가능성은 긍정적으로 엿볼 수 있었지만, 양질의 종교교육이 이루어지기 위해서는 MOOCs와 같은 온라인 학습환경을 활용하는 것 이상으로 교수자와 운영진의 노고가 요구되는 것을 확인할 수 있었다.[PURPOSE] The purpose of this study is to present the possibility and direction of online religious education through research and analysis of religious-themed courses among Korean Massive Open Online Clourse (K-MOOC). [CONTENTS] In this study, the current status of religion-related courses was collected on the K-MOOC platform and the characteristics of the courses opened were identified. Also, we selected two courses that represent the entire field of religious studies. As we took the courses, we analyzed the components of the course and the content aspects of the course to determine its characteristics. [RESULTS] As a result, as of December 2022, religion-related courses accounted for 43 of the total number of about 1300 K-MOOC courses. It can be divided into religious studies in general, which seek an understanding of specific religions and utilize religion as a humanities education according to the subject. Among them, as a result of the case analysis of two courses focused on religious studies, the purpose is to cultivate a pluralistic attitude that reaches beyond acquiring knowledge and accepts various phenomena related to religion. In the systematic aspect, the course consists of videos, quizzes, discussions, and reading materials. The composition of this course shows a similar aspect to other K-MOOC courses, which is considered a limitation of the platform, not a religious studies. We can find a positive aspect to the possibility of online religious education. But also, it will be need that the efforts are required beyond the use of online learning environments such as MOOCs.
A Study on the Impact of Hardware Limitations in Multi-Rotor UAVs on Coverage Path Planning Models

Search and explore missions through patrolling UAVs need effective strategies for area coverage.Various methodologies for coverage path planning were explored and analyzed through the ROS-Gazebo simulation environment using the Hector quadrotor model.Considering the impact of hardware limitations, simulations were conducted, for such missions where the UAV is needed to switch frequently between search and localize modes.This study investigated raster-scan exploration, expanding spiral search and zigzag pattern coverage to analyze the impact of limitations from Hector UAV on these models.The evaluation parameters were percentage of covered area, number of turns and time taken by the UAV.
A Proposal of Shoulder-surfing Attack Countermeasure Method with Improved Usability

Shoulder-surfing attacks are one of the most familiar password exploitation attacks.It is vulnerable to be attacked while unlocking a smartphone screen.The smartphone users need to take countermeasures against that attack.The fingerprint-based screen unlock system has become the norm, but it is not safe, as there has been increased in the user's fingerprint theft.The existing methods to prevent the shoulder-surfing attacks are effective against such attacks, but many of them are complicated to operate, and difficult to use.In this paper, we propose the prevent method for surfing attacks that it is easy to use.The tool's user operates the lower buttons, moves characters to on the trump's marks in specified advance.The user can input as likely as the password.On the other hand, the attacker does not understand the input characters only shown these buttons has been pushed.
Weather Forecast System for Mobile Devices

In the 21st century, the Internet has developed rapidly, and its technology has reached an unprecedented level.In the 21st century, many personal computers appeared in daily life, and people began to be familiar with obtaining the required information through the Internet.Subsequently, as mobile development technology became increasingly popular and rapidly occupied the Internet market, the development of mobile terminals also made a breakthrough.At present, Android and iOS platforms dominate mobile platforms.Most applications are developed based on a single platform, and the development efficiency is not ideal.Therefore, cross platform technology has gradually entered the vision of developers, easing the problem of cross platform development.It provides opportunities to meet people's needs for real-time, accurate and diverse weather information.The development of such applications should focus on the design of interfaces and the realization of key functions.
A lightweight low-light image enhancement network

Existing methods based on deep learning have achieved great success in low-light image enhancement.However, the existing methods generally have a large amount of computation and poor generalization ability for low-light images in different scenes.In order to solve this problem, this paper explores a feasible way to introduce auxiliary blocks in the training process.These blocks can connect the feature map inputs of each stage to the inputs of the first stage to explore whether the model converges.In the prediction phase, due to the superior capabilities of the network, we use only one basic block for inference, so as to greatly reduce the computational cost.Owe to the flexibility of the network, the model can easily handle low-light images in a variety of complex environments.
Enhancement methodology for low light image

In order to solve the problems such as low brightness, high noise and poor contrast in weak illumination images, there are several methods proposed to address this issue.Usually, these methods are categorized into two different ways.One is based on traditional light-based technology, the other is based on machine learning technology.The low-light image enhancement is often a challenging task because the noises in dark areas are amplified with the overall brightness and contrast of the image.With the development of machine learning techniques, deep learning networks are becoming the popular research topics recently to overcome the disadvantages of noisy dots.Based on the deep analysis of the current research work, we proposed a novel network and carried out lots of comparison experiments to analysis the performances of these methods.By training, validation and testing on the datasets, the evaluation criterious are defined and utilized to analysis the efficiency of the methods.With the results, we draw the conclusion that the efficient low-light image method can make up for the shortcomings of the environment, bring better viewers' experience and provide preprocessing for subsequent high-level computer vision tasks, such as target recognition, face recognition, semantic segmentation, etc.
Event-Driven Particle Filter for Tracking Irregularly Moving Objects

Conventional object tracking techniques that use general-purpose cameras and particle filters find it difficult to track irregularly and rapidly moving objects.To track an irregularly moving object without losing sight, quickly measuring the position of the object is necessary.In this study, we used a fast-response event-based camera, which is a bioinspired camera that produces a spiking output.We propose an event-driven particle filter that performs processing in response to the input from an event-based camera.Our proposed method was evaluated by presenting an eventbased camera with a rectangular motion pattern that combines periodic and constant-velocity motions at various speeds.The experimental results demonstrated that our proposed method could track objects in a test video.
Designing a Narrative Generation Game Based on the Russian Invasion of Ukraine

In a previous paper, we proposed an automatic narrative generation game.In this paper, we propose a game concept based on the framework of the automatic narrative generation game.The proposed game is based on the ongoing Russian invasion of Ukraine (beginning in February 2022).The game is based on an analog game in which participants advance a shared storyline mainly through dialog.The proposed game facilitates story generation.Accordingly, as an application, we intend to use the game to support the creation of stories.
A Four-dimensional Conservative Chaotic System and Its Application in Image Encryption

In this paper, a four-dimensional conservative chaotic system is firstly analyzed and investigated.It is found that the four-dimensional conservative chaotic system shows some complex dynamics, such as multi-stability and strong pseudo-randomness.Secondly, based on pseudo-random sequences and two-dimensional discrete wavelet transform, an image encryption algorithm is realized.Finally, all the experiment results and the security analysis show that the algorithm show good encryption characteristics, which further prove the image encryption algorithm.
The Staged Knowledge Distillation in Video Classification: Harmonizing Student Progress by a Complementary Weakly Supervised Framework

In the context of label-efficient learning on video data, the distillation method and the structural design of the teacher-student architecture have a significant impact on knowledge distillation. However, the relationship between these factors has been overlooked in previous research. To address this gap, we propose a new weakly supervised learning framework for knowledge distillation in video classification that is designed to improve the efficiency and accuracy of the student model. Our approach leverages the concept of substage-based learning to distill knowledge based on the combination of student substages and the correlation of corresponding substages. We also employ the progressive cascade training method to address the accuracy loss caused by the large capacity gap between the teacher and the student. Additionally, we propose a pseudo-label optimization strategy to improve the initial data label. To optimize the loss functions of different distillation substages during the training process, we introduce a new loss method based on feature distribution. We conduct extensive experiments on both real and simulated data sets, demonstrating that our proposed approach outperforms existing distillation methods in terms of knowledge distillation for video classification tasks. Our proposed substage-based distillation approach has the potential to inform future research on label-efficient learning for video data.
PERANCANGAN BUSINESS TO BUSINESS PADA TOKO TUNAS BARU SIMPANG PINOH

The Tunas Baru store has challenges in service both conventionally and via Whatsapp. The owner only employs two employees so resellers have to queue. In addition, the large number of orders via WhatsApp makes it difficult for owners to reply to chats one by one and prepare orders so that mistakes can occur in preparing orders. The purpose of this study is to design a B2B website at the Tunas Baru store to ease the work of the owners and employees, make it easier to order goods and save time on sales transactions at the Tunas Baru store. This research is in the form of a case study with a research method using Design Science Research (DSR). The development method uses Rapid Application Development (RAD). The programming languages ​​used are PHP, Javascript, HTML and MySOL database server. The system modeling uses UML (Unified Modeling Language). This research produces a B2B website at the Tunas Baru store that can be used by owners to manage product data, display sales reports, manage product stock, view payments, view orders and manage users level. Then the resellers can search and order goods through the website. In addition, website users can register to become a resellers of the Tunas Baru store
PERSEPSI MAHASISWA DALAM PERKULIAHAN DARING PADA MATA KULIAH BAHASA INDONESIA DI UNIVERSITAS AMIKOM YOGYAKARTA

This study aims to describe student perceptions of the implementation of online lectures in the Indonesian language course at Amikom University, Yogyakarta. The results of the study show that most students have a positive perception of the implementation of online lectures in Indonesian courses. This perception is measured from three aspects, including aspects of the lecture process, aspects of lecturer competence, and aspects of facilities. In the aspect of the lecture process, most students gave a positive perception of the online lecture process. Students think that online lectures can train for independent learning and save on transportation costs. In terms of lecturer competence, most students agree that lecturers are competent so that online lectures can run smoothly. Meanwhile the aspect of facilities, some students stated that facilities in the form of internet networks could be an obstacle in online lectures. However, students always get positive support from parents in online lectures
Target Tracking Based on Radon Transform Data Appearance Modeling

This article mainly focuses on an important challenge in target tracking in complex environments the real-time performance of algorithm operation. A new target appearance model based on Radon transform data is studied, and it is introduced into the correlation filtering framework for filtering template training. A fast tracking algorithm and target scale update scheme based on correlation filtering are proposed. The experimental results show that the tracking algorithm proposed in this paper has better robustness and real-time performance compared to current mainstream tracking algorithms, providing a new technical approach for research related to object detection and tracking. The tracking algorithm proposed in this article can also be seen as a framework, where the projected object can not only be the grayscale of the original pixel, but also include multi-channel color values, HOG, and other attributes.
Behavioural antecedents of Bitcoin trading volume

This paper aims to examine the behavioural determinants of Bitcoin trading volume within a cross-country framework of 14 world economies plus the Eurozone. We introduce a basic taxonomy of behavioural indicators, distinguishing between consumer confidence, economic policy uncertainty (EPU), and indicators of financial volatility. Our estimations reveal that the Bitcoin trading volume can be predicted more accurately by EPU than by any other class of indicators. Finally, we identify the COVID-19 shock as a catalyst for a psychologically-driven Bitcoin market and find evidence that Bitcoin was a macro hedging instrument in the pandemic. To obtain our results, we conducted a panel Granger causality test, employing the Least Squares Dummy Variables (LSDV) estimator. Contrary to previous research, we found that market fundamentals (industrial production and equity market volume) became significant drivers of Bitcoin trading during the pandemic. This conclusion was preserved when we used the LSDV corrected estimator, which is more suitable for panels with a smaller time dimension. Apart from the practical implications for traders, this paper provides researchers with detailed steps for applying Granger causality testing in panel data settings.