Reviewerly/exHarmony huggingface dataset:
Мethod of analysis for analyzing phishing messages

The development and widespread introduction of the Internet into everyday life has transformed both economic and social relations. The representation of these relations in digital form has created a digital economy, characterized by an active exchange of information, quick access to information resources, and the transfer of payments to the digital dimension. Social relations in the digital world are represented by social networks, instant messengers, which also provide economic services. At the same time, the new space, the transformed economy and social relations give rise to new threats. Users themselves actively expose information about themselves and their loved ones, photos of vacations and locations to the public. In addition to social networking, viewing entertainment content and online games, bank settlement transactions are popular. The popularization of Internet banking leads to an increased interest in stealing data from intruders. The result of this is an increase in the number of scammers who aim to obtain confidential user information. In addition, since the beginning of the war, the number of cyber attacks on public authorities, critical information infrastructure facilities and organizations containing critical information has increased. One of the well-known methods of stealing such information is phishing attacks. At the same time, most users underestimate the severity of these attacks and do not pay enough attention to protection systems. This, in turn, leads to wider consequences. Therefore, the problem to be solved is to present a method for analyzing phishing messages that can be used to reduce the probability of reaching the goal of a phishing attack. At the same time, it is known that attackers improve and modify the methods of implementing attacks, and therefore, classifying phishing attacks to increase user awareness is an urgent task. The result of the work is the proposed classification of phishing attacks and the presented method for analyzing phishing messages.
Philosophical Foundations of Modern Pedagogical Education

The article describes the tendency of integration of pedagogical concepts of education on a philosophical basis. The philosophical approach involves a certain method of studying education — "philosophizing", which is directly related to the study of a person, his life, his personality, the search for means that help him in self-determination, finding the meaning of life.
A Critical Reflection on the Ecumenical Movement in Korean Churches

The ecumenical movement is a movement pursuing the unity of Christian churches. However, Korean churches have experienced the division of churches because of the ecumenical movement. A movement for the union and unity of churches has become a crucial factor in the conflict and division of Korean churches: The ecumenical movement has become a trauma for Korean churches. The existing studies on the Korean ecumenical movement have taken a historical or institutional approach that focuses on its history and ecumenical institutions, respectively. This article is interested in revealing the whole features of the Korean ecumenical movement. It deals with the Korean ecumenical movement within a historical trajectory, including the theoretical, social, and liturgical aspects. Through this categorical, integrated, and comprehensive approach, the topographic map of the Korean ecumenical movement can be drawn multi-dimensionally and holistically. To achieve this goal, this article consists of three main sections in addition to an introduction and a conclusion. The second section outlines a brief survey of its historical trajectory of the ecumenical movement in Korea. The section three deals with three areas, such as theology, institution and liturgy. Theological aspects including creed and confession, ecumenical institutions and organizations, and liturgical and practical activities including worship and prayer meetings. The forth section deals with the status, features, and prospects of the Korean ecumenical movement. The status of the ecumenical movement is described by three dimensions: the religious topography of Korean religions and Korean Christianity, the leading generation of the ecumenical movement, and the core theme of the ecumenical movement. With a description of six characteristics, the prospect of the Korean ecumenical movement is presented from the perspective of the direction of the ecumenical movement, the new generation of the ecumenical movement, and the ecumenical education.
Revisiting Grammatical versus Pragmatic Competence in Learning a Language

This study aims to revisit the difference between grammatical and pragmatic competence in language learning. This paper design is library research by studying books, journals, literature, notes, and reports related to grammatical and pragmatic competence. The data sources for this project report are relevant books and previous studies in the form of journal articles about grammatical and pragmatic competence. Result of the study stated that knowing only grammatical or language rules without knowing when and where the rules must be applied is insufficient. It addresses not only grammar but also meaning. This could imply that there should be more practice exercises for identifying grammatical and pragmatic errors. The teachers should then encourage their students to be aware of grammatical and pragmatic errors and treat them seriously. As a result, this study has brought this issue to light and may aid language learners in developing their pragmatic ability.
Analysis and prediction for credit card fraud detection dataset using data mining approaches

Analysis of fraud detection is one of the recent research areas in data analytics. Credit card fraud is rapidly increasing in different ways significantly with modern technology. The Credit card consumers and processing financial company have losing large amount annually. The fraudsters rapidly and continuously try to find and follow novel technologies to commit the illegal actions against consumers. In COVID-19 pandemic situations online shopping trends growing exponentially and parallelly increase Credit card fraud rapidly. In this paper we trained different data mining techniques with statistical approaches for credit card fraud detection. Numerical illustrations to prove the proposed results.
AN ANALYIS OF TEACHER’S STRATEGIES IN TEACHING SPEAKING IN EMERGENCY REMOTE TEACHING CONTEXT

This article aims to explore the teacher’s strategies in teaching speaking in emergency remote teaching (ERT), this research using qualitative approach with observation, interview and documentation. The result of this research is that are faced the students are found the difficulties. There are in an attention in learning process, students still little in vocabulary, students are doesn’t brave and confident in speak directly when they in online class, the students are faced the unstable signal when they in online class.The researcher will give some appropriate strategy. Firstly, based on the students’ difficulties. For difficulty in speaking teaching with ERT, students need to pay attention to and learn in a social media, such as Whatsapp, Zoom, Google Classroom and soon. So, students need to master in speaking context to make it easier to speak in english. Especially in pronounciation and grammar, students must understand how to use pronounciation correctly and adequately according to their function. For difficulty in limited vocabulary, students must master the vocabulary to help students in speaking without repeating the same words and delivering clear ideas. For difficulty in pronounciation, students should learn how to pronuoun correctly in speaking learning and doing a lot of practice in speaking.
Indonesian Student Perceptions on Face-To-Face Learning, Online Learning And Blended Learning

Education must be meticulously planned in order to equip the next generation to confront the challenges of the workplace and to participate actively and responsibly in society. As a result of the pandemic, education has seen a shift in the direction of asynchronous learning methods, which were previously used in traditional learning methods. With the growth of the internet, educational practices are becoming increasingly oriented towards technology and communication-based learning strategies, ranging from the online learning model to blended learning. The information gathered from these pupils is still qualitative raw data collected in an online form and transformed to an excel spreadsheet. The raw data is processed in such a way that the data processing findings are subjected to a thorough qualitative descriptive analysis
Advancement of natural language programming, machine learning and electronic health records for the digital health science field

The widespread use of “electronic health record systems (EHRs)” in health care provides a large amount of real-world data, opening up new opportunities for medical trials. “Deep learning, a subset of machine learning (ML)”, has experienced a meteoric rise in popularity over the last six years, owing to advances in computing power and the accessibility of enormous new datasets. “Natural language processing (NLP)” approaches have been used as an “artificial intelligence strategy” to obtain information from medical narratives in EHRs, as a huge quantity of useful clinical knowledge is contained in clinical stories. This NLP capacity may enable “automated chart review in clinical care to identify individuals with distinct clinical features” and decrease methodological heterogeneity in establishing “phenotypes, masking biological heterogeneity in allergy, asthma, and immunology research”. Aim of this research paper is to understand the advanced technologies such as “Machine Learning, Natural Language Programming” are helpful for digital health field. In this context, secondary data collection method is used to gather information related to this topic.
The Importance of Agile Technique in Comparison to Sequential Design Models

Software development procedures are constantly evolving to monitor and evaluate the quality and to save money and time. Numerous organizations are migrating away from traditional business models and toward agile methodologies. The purpose of this paper is to illustrate both traditional and agile software development approaches and the numerous techniques associated with them. This analysis conducted identical investigations into two radically different ways of thinking about product development: traditional methods and agile approaches. The paper is supported by several studies commissioned by various organizations to determine the transition from the traditional to the agile paradigm. The follow-up and data analysis explore and reveal changes and emerging trends that arose announcement of the agile technique which is mentioned in this paper, and also has gained increasing prominence in agile in product development over the last couple of years.
Sistem Pakar Untuk Mendiagnosis Penyakit Kanker Payudara Menggunakan Metode Certainty Factor Berbasis Web

Information technology has been widely applied in the medical field to assist doctors in diagnosing cancer and also for patients to find out the extent of the disease. The number of patients with breast cancer at the Regional General Hospital, Prof. dr. W. Z. Yohannes in 2020 until November reached 77 patients. The still high number of breast cancer sufferers is the background for this research, with the aim of this expert system being able to help provide clear information for patients or the general public so that they can find out the symptoms they are experiencing early on.&#x0D; The method used in this study is the Certainty Factor (CF) method. The Certainty Factor method is a method to prove whether a fact is certain or uncertain and also describes the level of expert confidence in the problems at hand. The application is designed using the PHP programming language and MySQL database, and the methodology used in this research is the Expert System Life Cycle (ESLC) method. The result of this research is an expert system application for diagnosing breast cancer that can help the general public in diagnosing breast cancer, especially helping patients get information to consult quickly about symptoms and diseases of breast cancer.
The Impact of E-Learning on the Level of Perceived Self-Efficacy among Secondary School Students in Government Schools in Karak Governorate

The study aimed to identify the impact of e-learning on the level of perceived self-efficacy among secondary school students in government schools in Karak Governorate. The study relied on the (analytical descriptive) method, by using the (paper) and (electronic) survey methods. The study population consisted of all secondary school students in government schools in Karak governorate, who were registered in the second semester of the academic year (2020/2021). The study sample consisted of (1413) male and female students, and the study sample was chosen by random method. The researcher designed and built the study tool, which consisted of a focus for personal variables and consisted of (gender, academic stage, specialization). The main axis of measuring the level of (perceived self-efficacy) associated with (e-learning), which included three main areas (self-confidence, persistence and perseverance, emotionality, problem solving), and the questionnaire was formed in its final form on the scale as a whole in all its fields (27). paragraph. The five-step Likert scale was used to build the study tool. To answer the study questions, the following statistical methods were relied on: (frequencies and percentages, arithmetic averages, standard deviations, Cronbach Alpha stability coefficient). The most important results of the study indicated that the effect of e-learning on the level of perceived self-efficacy among secondary school students in government schools in Karak governorate was (low), and there were no statistically significant differences at the level of significance (0.05α≤) in the study sample vocabulary estimates on the effect of E-learning at the level of perceived self-efficacy among secondary school students due to study variables. The most important recommendations of the study indicated the need to take measures to improve and raise the atmosphere of perceived self-efficacy in the e-learning process, through improving and developing the philosophy of e-learning in proportion to the psychological, social, intellectual and cognitive needs of students. Keywords: e-learning, perceived self-efficacy, secondary school students. DOI: 10.7176/JEP/13-19-10 Publication date: June 30 th 2022
Kako osigurati primjenu etične blockchain tehnologije u trgovačkom društvu

The law does not follow the dramatic development of new technologies, including the distributed ledger technology (hereinafter: DLT), often called blockchain (hereinafter: BC). There are numerous examples of the application of these technologies in a company. An underregulated environment emphasizes the need of an ethical approach in situations where a company decides to select a new BC tool, as well as to identify a relevant body in the company that will ensure the selection and implementation BC technological solutions in an ethical and impartial manner. The development of an ethical framework for BC solutions is not only needed as a substitute for the missing legal regulation, but should also be an independent regulatory effort. To this end, technology scandals are being investigated in which significant deviations from the fundamental promises of BC technology have occurred during hacker attacks. It was examined whether the same system recovery procedures were applied in factually similar situations. It was found that recovery procedures were substantially diverging, which raises strong ethical concerns. Therefore, regulatory initiatives calling for ethical BC technology are explored. In the last part of the paper, the author proposes two alternatives as an answer to the question who should be in charge in the company to ensure that BC technology solutions are selected and applied in an ethical and impartial manner. Although companies are free to set up their “ethical and prevention of conflict of interest system” autonomously, they might consider to select a technology committee for that role or a compliance officer. Either way, companies should decide whether to design ethical and conflict of interest control as ex ante or ex post, given the importance of the corporate function or operation that is going to be digitalized by applying BC technology solutions.
Fire As A First Cause Of Phenomenon In Gaston Bachelard's The Psychoanalysis Of Fire And Igor Stravinsky's The Rite Of Spring

In this paper, the ballet of Igor Stravinsky The Rite of Spring is interpreted from the perspective of Gaston Bachelard’s philosophical thought. Bachelard’s systematic psychoanalysis of literary images in The Psychoanalysis of Fire is applied to the interpretation of musical images in The Rite of Spring. Bearing in mind that rhythm is a key characteristic of Stravinsky’s composition, the paper analyses the immediate correspondences between Stravinsky’s and Bachelard’s perception and interpretation of rhythm in the works under consideration.
Aplikasi Sistem Pakar Untuk Mengidentifikasi Biota Laut Berbasis Website

Indonesia has very wide waters and has a diversity of marine ecosystems. This diversity makes people want to know information about various marine ecosystems and marine biota easily and quickly without having to buy or read books about marine ecosystems. Along with the development of technology and information in everyday life, it can be used to solve these problems by designing an expert system that can contain various information to identify various types of marine biota. To design the expert system, it takes several stages such as needs analysis, knowledge acquisition, system design, coding, and testing the system. In this research, applying the knowledge base of rule based relation with the knowledge representation of decision tree. The marine biota expert system is designed based on a website. This expert system produces an accuracy of 100%
How Global Observation embedding in Vertical-Horizontal Federated Learning

Federated learning (FL) has recently emerged as a transformative paradigm that jointly train a model with distributed devices while avoiding the need for central data collection. Due to the limited observation range, the devices only contain local information, which limits the quality of trained models. In this case, combining the global information into FL may be helpful. However, in horizontal FL, the central agency only acts as a model aggregator without utilizing its global observation. Meanwhile, the global data may not be directly transmitted to agents for data security. Then how to utilize the global observation residing in the central agency while protecting its safety thus rises up as an important problem in FL. In this paper, we develop a vertical-horizontal federated learning (VHFL) scheme, where the global feature is shared with the agents in a procedure similar to that of vertical FL. It is shown by experiments that the proposed VHFL could enhance the accuracy compared with horizontal FL while protecting the central data from being announced.
Assessment of normal and abnormal behaviour of people with dementia in living environment through non-invasive sensors and unsupervised AI

The objective of this work is to define a measurement protocol to compute and distinguish abnormal from normal behavior of older people with early to middle stage dementia living alone at home using training artificial intelligence (AI) algorithms (in specific K-means, Agglomerative and Spectral Clustering Algorithms). Unlabeled activities of daily living (ADLs) databases were acquired from an AI-based sensor network composed of three Passive Infrared (PIR) motion sensors and two door sensors which are installed in voluntary participants’ houses in Italy, Netherlands, Switzerland and Norway. Our blind approach proposes an unsupervised learning-based solution, representing real-world use case where it is not possible to provide accurate labeling and annotation of the sensor data. Results indicate two out of three algorithms, which applied for 32 participants during 75 days of recording, are valid to create clustering groups for participants with acceptable Silhouette coefficient of 0.77 and 0.65 for K-means and Agglomerative clustering, respectively, and 0.13 for Spectral clustering method that makes this algorithm less reliable respect to others.
Penerapan media film stop motion dalam pembalajaran IPS pada kelas IV di SD

The purpose of this study is to describe the application of the use of stop motion film media in social studies learning in elementary schools. This study used descriptive qualitative method. There are two sources of data from this study, namely class teachers and fourth grade elementary school students. Collecting data from this research using observation, interview and documentation techniques. The data obtained from observation is that the teacher uses stop motion film media in the learning process, with this researchers can find out how the application of stop motion film media in the learning process, especially in social studies learning. In this study, the researchers obtained the results of interviews with classroom teachers and fourth grade students regarding the application of the workings of stop motion film media. The results of observations and interviews of teachers and students showed that the stop motion film media obtained by means of stop motion film media worked well and were very happy with this stop motion film media, with the stop motion film media students' enthusiasm for learning increased and students found it easier to understand learning material being taught.
Research on Liver Segmentation of CT Image Based on Deep Active Contour Model

Liver cancer is one of the liver diseases with a high morbidity and mortality. At present, surgery is still the main treatment method for liver cancer. Therefore, it is particularly important to accurately segment the liver on CT imaging. Deep learning-based algorithms struggle to derive shape priors due to the irregular shape of the liver and blurring organ borders in CT images. We present a two-stage 3D deep active contour model 3DAC based on the V-net and CV models, in which the neural network is guided to learn the global features by regressing the signed distance map. The signed distance function can also be used as an initialization level set function. Then, the active contour model is extended to three dimensions to enable evolution of the overall liver surface. The advantages of the proposed method for liver segmentation were validated on the AbdomenCT-lK dataset. Compared with the DALS method, the Dice coefficient and the Jaccard coefficient are improved by 4.29% and 4.58%, the ASD and 95HD indicators are improved by 5. 96mm and 10. 04mm, which proves the effectiveness and robustness of the proposed method.
General nonlinear function neural network fitting algorithm based on CNN

This paper proposes a generic neural network fitting algorithm based on CNN for nonlinear functions that overcomes the challenges of a large number of nonlinear functions in terms of hardware deployment and computing circuit generality in diverse neural network models. The model takes advantage of the principle that functions have varying degrees of difficulty fitting in different spaces, mapping the input to high-dimensional space with 1x1 convolution, and utilizing CNN to extract features of nonlinear functions with its strong feature extraction ability in high-dimensional space. Furthermore, MaxPool and ReLU improve the ability of nonlinear fitting. When fitting Tanh, Sigmoid, and ELU activation functions with 16bit accuracy, the proposed algorithm has an average error of less than 0.0006, with a parameter size of 5.793 k.