Reviewerly/exHarmony huggingface dataset:
Investigating Ontology-Based Data Access with GitHub

Data analysis-based decision-making is performed daily by domain experts. As data grows, getting access to relevant data becomes a challenge. In an approach known as Ontology-based data access (OBDA), ontologies are advocated as a suitable formal tool to address complex data access. This technique combines a domain ontology with a data source by using a declarative mapping specification to enable data access using a domain vocabulary. We investigate this approach by studying the theoretical background; conducting a literature review on the implementation of OBDA in production systems; implementing OBDA on a relational dataset using an OBDA tool and; providing results and analysis of query answering. We selected Ontop ( https://ontop-vkg.org ) to illustrate how this technique enhances the data usage of the GitHub community. Ontop is an open-source OBDA tool applied in the domain of relational databases. The implementation consists of the GHTorrent dataset and an extended SemanGit ontology. We perform a set of queries to highlight a subset of the features of this data access approach. The results look positive and can assist various use cases related to GitHub data with a semantic approach. OBDA does provide benefits in practice, such as querying in domain vocabulary and making use of reasoning over the axioms in the ontology. However, the practical impediments we observe are in the “manual” development of a domain ontology and the creation of a mapping specification which requires deep knowledge of a domain and the data. Also, implementing OBDA within the practical context of an information system requires careful consideration for a suitable user interface to facilitate the query construction from ontology vocabulary. Finally, we conclude with a summary of the paper and direction for future research.
SemReasoner - A High-Performance Knowledge Graph Store and Rule-Based Reasoner

Knowledge graphs have become essential for integrating data from heterogeneous sources powering intelligent applications. Integrating data from various sources often results in incomplete knowledge that needs to be enriched based on custom inference rules. Handling a large number of facts requires a scalable storage layer that must be seamlessly integrated into the reasoning algorithms to guarantee efficient evaluation of rules and query answering over the knowledge graph. To this end, we present SemReasoner, a comprehensive, scalable, high-performance knowledge graph store and rule-based reasoner. SemReasoner includes a deductive reasoning engine and fully supports document store functionality for JSON documents. SemReasoner’s modular architecture is easy to extend and integrate into existing IT landscapes and applications. We evaluate SemReasoner against the state-of-the-art rule-based reasoning engines using test cases from OpenRuleBench. The results show that SemReasoner outperforms existing engines in most test cases.
Abnormal Activity Recognition in Private Places Using Deep Learning

Using computer and machine vision technology, the process of analysing human motion is known as "human activity recognition," or HAR. Anomaly detection in security systems is one of the situations in which human activity recognition is useful. As the demand for security growing, surveillance cameras have been widely installed as the foundation for video analysis. Identifying anomalous behaviour demands strenuous human effort, which is one of the main obstacles in surveillance video analysis. It is necessary to establish video recording in order to automatically catch anomalous activities. Using deep learning methods, our intelligent video surveillance system can identify an anomaly in a video. Real-time detection of the actions is also possible, and these video frames will be afterwards preserved as photographs in the system for the user to examine.The suggested Abnormal Activity Recognition system was created with the goal of identifying and detecting irregularities through a live feed in the banking sector, more specifically in an ATM setting.The initial phase of the study focuses on the application of image deep learning techniques to recognise various items and spot unusual behaviour using ATM monitoring systems.
THE BENEFITS OF PHYSIOTHERAPY IN ALZHEIMER’S DISEASE SYMPTOMS

Introduction: The Alzheimer’s Disease is a progressive condition that affects the memory and other cognitive functions, impactaring negatively the the life of patients and their relatives. The physical therapy is an important alley in the treatment of these individuals, by aiming to improve their autonomy, well-being and independency. Objective: To show the benefits of the physical therapy treatment in patients with Alzheimer. Method: It was performed a bibliographic review research utilizing the Google Scholar, SciELO and PubMed databases in Portuguese, Spanish and English languages. Conclusion: It was found that the physical therapy is of high importance for the life quality maintenance in the population affected by the Alzheimer’s Disease, because it presents benefits in physical capabilities and motor skills such as: improved flexibility, strength gain, improved cardiovascular capacity, balance and better cognition.
Cyber Terror Threats Against Nuclear Power Plants

After the Cold War period, with the restructuring of the world, globalization, the revolution in information technology and the reconstruction of capitalism have created a new type of society, the "network society". The dependence of countries on information technologies, especially the internet, has increased day by day, and it has become almost impossible for individuals, state institutions and private companies to continue their activities independently of cyberspace, which is described as the fifth operational area. This situation has made it a critical priority to ensure the physical and cyber security of nuclear power plants, which carry the energy burden of the societies and at the same time pose great security risks. In this period, states, state-sponsored and radical terrorist groups that wanted to close the power deficit against military and economically strong states, started to develop asymmetric methods of struggle. In the end new threat vectors such as cyber terrorism have emerged and states that have moved many institutions and services to cyberspace have become more vulnerable to malicious attacks and terrorist activities. In this study, the concept of terrorism and cyber terrorism have been examined and focused on the SCADA systems of nuclear power plants and in the last section cyber security of these systems have been evaluated. This Implementation of this model aims to simplify the process for all organizations in the Nuclear Sector—regardless of their size, cybersecurity risk, or current level of cybersecurity sophistication—to apply the principles and best practices of risk management. Ultimately, the framework and this implementation model are focused on helping individual organizations reduce and better manage their cybersecurity risks, contributing to a more secure and resilient sector overall.
Characteristics of the Local Malay Traditional Pelangi Cloth Motifs and Patterns Design

This project established the characteristics of the local Malay traditional Pelangi cloth motifs and the specialty of their pattern design. The field research was conducted through observation at selected museums around Malaysia Peninsular, and interviews with curators and textile experts at the national craft institute, to gather the data and information through visual documentation of Pelangi cloth, for analysis purposes. The result discovered how the identification approach showed the recognition of motifs and patterns design was developed according to the Pelangi cloth traditional characteristics base on textile structure, motifs shape, pattern design arrangement, colour, technique, and product processes. This paper also shows the comparison between the local traditional Pelangi cloth with one of the traditional textiles in Malaysia to look into the relationships between them. This paper also successfully explains the types of traditional Pelangi cloth motifs more clearly since this textile industry has died out and is still not highlighted to the public.
Fractal characteristics of particle groups and mechanochemical effects of Yellow River sediment after mechanical grinding

This paper investigated the fractal characteristics of particle groups and the mechanochemical effects of mechanically grinding Yellow River Sediment (MGYRS). The particle groups of MGYRS had good fractal characteristics, and the fractal dimension had a better correlation with the particle size, distribution and specific surface area of MGYRS, which could well reflect the changes in the physical properties of MGYRS. After mechanical milling, the analysis by XRD, FT-IR and XPS microscopic tests revealed that: the crystallinity and grain size of mineral crystals in MGYRS decreased with the increase in milling time. The electron binding energy of Si2p, Al2p and O1s shifted to the low-energy direction, and the chemical valence state of silicon atoms appeared Si3+ due to the breakage of the Si-O-Si/Al chemical bond. These changes in internal structure and chemical valence state were the microscopic manifestations of mechanochemical effects. The activation rate of MGYRS increased with the increase of grinding time, which was the macroscopic manifestation of mechanochemical effects.
A Study on character articles of Korea and China in the 18th Century: Focusing on the works of Kwon Sang-il and Zhu Hyeon, who intensively covered 節․烈

This paper was planned as part of a study to understand the universality and specificity of character articles in the late Joseon Dynasty. In the 18th century, when character accounts in the late Joseon Dynasty showed various changes, Kwon Sang-il and Joo Gyun, literati in Korea and China, intensively covered 節·烈. Kwon Sang-il’s character stories record women who chose to die after their husbands died. Joo-gyun’s works have a mixture of 烈行 and 節行. The fact that Kwon Sang-il’s works emphasized sincerity stems from the fact that women’s fidelity and protection are regarded as ‘the manifestation of virtue’. On the other hand, the fact that Joo Gyun emphasized the character’s will is the result of looking at the behavioral style of women’s 志操 protection from the dimension of ‘realization of duty’. On the other hand, all the works related to 節烈, starting with Kwon Sang-il, are selecting characters from the existing conservative point of view, which venerated the woman who gave up her life. This is a different aspect from Korea’s Inmuljeon or China’s character articles of the same period, which also recognized the value of 節烈. Also, this is contrary to the 18th century Korean character articles accepting various changes in terms of characters, experiences, and descriptions. In the end, it can be seen that Korean character writers of this period still maintained a conservative view on the behavior of a wife.
テンプレートマッチングを用いた追跡問題に対する荷電多粒子群最適化の提案

The visual tracking problem can be solved by performing template matching on each frame, which can be treated as a dynamic optimization problem. On the other hand, Charged Particle Swarm Optimization (CPSO) is a PSO variant for dynamic optimization, which maintains swarm diversity by introducing charged particles and repulsion vectors into the velocity update step. CPSO uses a unified pre-determined amount of charge for all particles, which is difficult to deal with various moves of the optimal solution. Instead of a unified value, in this paper, we propose introducing diverse charged particles into CPSO, referred to as Multi-swarm CPSO (MCPSO). Specifically, MCPSO employs multiple sub-swarms and assigns different amounts of charge to particles in each sub-swarm, which leads to diverse moving characteristics of particles. Moreover, each particle is limited to receiving repulsion force only from other particles in the same sub-swarm, which results in various sub-swarms with different behaviors. The optimization performance of MCPSO is assessed by a numerical experiment using five benchmark functions compared with standard PSO and CPSO. In addition, the effectiveness of MCPSO for visual tracking using template matching is verified by a comparison experiment with nine synthetic sequences.
Exploring Educational Content Found in Modern Historical Landscapes in Integrated Social Studies Education

Purpose: The purpose of this study was to propose Integrated Social Studies Education using issuesrelated to the place memory found in modern historical landscapes. Methods: Conducted literature research, field surveys, and analyzed the national curriculum alongwith the contents of education. Results: Currently, different methods have seen proposed and many regions have seen a positive andmodern transformation of negative place memories related t``o colonial rule based on the formationof regional identity. In this study, issues about modern historical landscapes in which colonial andmodern memories compete were applied to the Integrated Social Studies Education. This researchstudy proposed a teaching plan to utilize the concept of landscapes of new cultural geography andexamples of conflicts about place memories as parts of cultural education Integrated Social Studies. Conclusion: This subject involved integrated thinking. The research finding are thus suitable for dealingwith disputes over modern historical landscapes in a unified society. This study has educationalsignificance in that it focused on the reproduction of memories in history by geographical landscapes,and specifically suggesting a new understanding of the problems of the existing modern historicallandscapes, Nevertheless, this study has limitations with respect to the anti-Japanese struggle andethnocentric descriptions.
Research Trends in Steganography Based on Artificial Intelligence

Steganography is a technology capable of protecting data by hiding the existence of data. Recently, with the development of deep learning technology, deep learning-based steganography are being developed. Deep learning can learn by analyzing high-dimensional features of data, so it can improve the performance and quality of steganography. In this paper, we investigated the research trend of image steganography based on deep learning.
A Study on the Role and Potential of Oral Literature Classes as a University Major Education

This paper reviews the current issues of the oral Literature course, based on the Korean Oral Literature course at Ewha Womans University, and proposes plans with cases in order to raise the possibilities and objectives of Korean oral Literature as a university major. The 15-week Korean oral Literature course covers various genres such as folk narratives, Shaman’s songs(muga), folk songs, pansori, and folk plays. Because the regions, histories and genres of works are diverse, works and topics are selected according to the professor’s teaching goal. In terms of students, in addition to Korean Literature majors, students from other departments with interests in classics, contents, and oral language, and as the proportion of foreign students increases in the university, foreign students are also increasing in the Korean Oral Literature course. Even if the aspects of utilization are highlighted in the curriculum due to the change in the university, the study of Korean traditional literature should aim for the social values ​​that we dream of. Since the research on Oral literature started as research on folk/minority literature, we should consider its basic nature while considering the collective wisdom and symbolic value creation of the community. In addition, we must consider the locality and reality as a genre that is still alive. In the class, students were encouraged to pre-learn videos and materials before the class, and each genre was arranged with group presentations and discussions to dynamically construct the class. In the situation where foreign students are increasing, comparative literary perspectives were used to lead their participation and review the universality and specificity of Korean oral literature, and cultural perspectives were used to interpret Korean oral literature in different eras and cultural regions. This not only deepens our understanding of Korean oral literature, but also moves towards deepening our understanding of humans and society by analyzing current social and cultural phenomena from the perspective of Korean oral literature, challenging familiar situations and values. Thus, Korean oral classes that focus on our daily lives and stories should expand their academic role even in the midst of university change.
A study on teaching methods of Korean classical novels as a college major: focusing on writing practice and approaches to key words

This paper agrees with the crisis that college education faces related to Korean classical literature. In order to overcome this crisis, it suggests ways to effectively teach Korean classical novels. First, this paper investigates the current status of the curriculum related to classical novels in the departments of Korean language and Korean language education across the country. The thing that stands out the most is the increase in subjects regarding cultural contents. Accordingly, the author ran a curriculum that suggested students to create new cultural contents by taking sources from Korean classical literature. In the beginning of the curriculum, students analyzed worthy cultural contents in various fields. There are various types of cultural contents such as a web novel, web toon, movie, play, musical, drama, game and advertisement. Out of them, students chose contents based on classical literature, and investigated the features and factors of popularity. After that, they created new stories and character types that content consumers would be interested in. Many of these stories were about independent female characters, explorers and travelers, active communicators, characters who fall in love, and had a happy ending. In the “Reading Korean classical novels through key words” class, students can learn the features of Korean literature and the differences between classical literature and contemporary literature by investigating key words. They can think deeply about the subjects by choosing a key word out of several and figuring out how the keyword is shaped in a novel. By reading several classical novels, students can develop reading skills and get familiar with classical literature. Furthermore, they can develop writing skills by expressing how they can relate lessons from novels to their own lives.
Finite-Time Bounds for AMSGrad-Enhanced Neural TD

Although the combination of adaptive methods and deep reinforcement learning has achieved tremendous success in practical applications, its theoretical convergence properties are not well understood. To address this issue, we propose a neural network-based adaptive TD algorithm, called NTD-AMSGrad, which is a variant of temporal difference learning. Moreover, we rigorously analyze the convergence performance of the proposed algorithm and establish a finite-time bound for NTD-AMSGrad under the Markov observation model. Specifically, when the neural network is wide enough, the proposed algorithm can converge to the optimal action-value function at a rate of, where is the number of iterations.
Factors to choose from or exclude from the education of Korean classical poetry at the university

In the past, classical poetry education in the Department of Korean Language and Literature had some autonomy compared to the middle and ordinary classes, which were standardized and uniformed according to the national evaluation. However, the nationalistic emotion that early Korean literature scholars would have felt while facing the surviving classical works does not gain sympathy from today’s students. Even some classical writers have become the subject of satire and ridicule. In the past, students learned classical poetry step by step from beginner to advanced, or examined it deeply according to the times and genres. In addition, each department had a choice, including other subjects. However, more than two-thirds of Korean literature departments currently operate only one subject. In lectures outside the lecture room, popular songs about hometown were used as a medium to elicit responses to classical poetry. However, it was still a task to gain sympathy for the younger generation in the classroom. One of the two recently published publications shows the trend of the times, from beginner to advanced, and the first book shows the trend according to the times. As a collaboration of academia, the list of works by these co-authors is worth referring to. It is necessary to develop consistent textbooks written by one person as well as the diversity of co-authors. It is important to pay attention to examples of work analysis and response that can respect students’ experiences and gain empathy.
A-BBL: A Risk Prediction Model for Patient Readmission based on Electronic Medical Records

With the spread of medical digitization, electronic health record data has been accumulated in large quantities, laying the foundation for intelligent medical changes. ICU data is mined and analyzed to identify the risk of patient readmission in a timely manner, prevent and control the deterioration of patients' conditions, and reduce the burden of patient costs. However, due to the poor quality of medical data, potential information cannot be effectively mined. In view of the above problems, a patient readmission risk prediction model A-BBL is proposed. By extracting and analyzing the patient 's discharge summary information, the readmission risk of discharged patients within 30 days is predicted. The A-BBL model consists of three parts: firstly, BioBert is used to pre-train the medical text data, extract the semantic information of the medical text, and then generate the corresponding word vector. Then, the sequence model BiLSTM is used to capture the context information and model the input sequence. Finally, the self-attention mechanism is used to extract the key information in the input sequence, enhance the vector representation ability of the sequence, thereby improving the performance and accuracy of the model, so as to predict the readmission rate of patients. Based on the MIMIC-III real medical data set, the A-BBL model for patient readmission prediction proposed in this paper is verified. Compared with the baseline model, the accuracy is improved by 7.2 %. This study can help medical staff better understand and pay attention to the progression of critically ill patients, im-prove the survival rate of patients, and reduce the readmission rate of patients.
Applied research of equipment management solutions with alliance blockchain technology

This paper is based on the general consideration of equipment management schemes under the alliance blockchain technology. It is sought that the state of mission, according to the pre-existing equipment management scheme, leads to a variety of conditions. To better adapt the existing scheme to the new situation of equipment mission requirements, it is urgent to update the management scheme by using new technological means. According to the equipment construction development plan, focus on the development of special warfare anti-terrorism equipment management and business needs, based on the existing equipment management foundation and technology development, be sure to simplify business processes, and improve the timeliness of equipment management program relevance.