Reviewerly/exHarmony huggingface dataset:
Credit Card Fraud Detection using Machine Learning

Now a days credit card plays a very important role in the lives of the human being. It becomes an important part of the businessman, global activities and many more. Even using credit cards give us a most widely used of benefits when it used with the responsibility and carefully, and very small credit and financial harm is also caused by fraudulent activities or transactions. There are a lot of techniques are given to encounter the scope in credit. In spite of, whatever the methods are used they have the same goal of clog the card fraud and each one has its own advantage, drawback and the characteristics too. The deficiency and the good of the credit card detection-methodologies are description and dissimilarity. Moreover, a taxonomy of reference techniques are classified in two fraud-detection perspective, as misuse (supervised) and absurdity (unsupervised) is given. Again, a taxonomy of methods is presented supported caliber to process the categorical and numerical datasets. Other kind of datasets are made in the literature then mentioned and sorted in real and club into the group of the data and therefore the dominant and customary attributes are removed for prosecute application. Consequently, for the new researches, the issues for credit card fraud-detection are described as per the recommendations.
Mining publication papers via text mining Evaluation and Results

Data nowadays is the language of technologies as every process needs a data to be processed the input is data and the output also is data. Analyzing the data is a significant task especially with the increasing production of the data particularly data as a text, it would be difficult to manually analyze the data, extract information and detect the hidden patterns from unstructured text. Data mining is automated technique for gathering or deriving a new high-quality information and uncover the relations among the data. Text mining is one of main branches of the data mining however data mining is more comprehensive this paper, an overview for mining the publication papers via text mining techniques and their results and evaluation would be presented as following: the first approach is keywords extraction using natural language processing (NLP) approach, the second approach named entity recognition and the last approach is document clustering where machine learning techniques are applied to the both of them
Analisis Rantai Markov dalam Memprediksi Status Pasien COVID-19 di Indonesia

COVID-19 is an infectious disease caused by a new type of corona virus, beta coronavirus. The spread of COVID-19 can occur through human interactions. On March 9, 2020 the WHO (World Health Organization) officially declared COVID-19 a pandemic. This means that COVID-19 has spread widely in the world. Until now, there has not been found a drug to treat COVID-19. So, it is necessary to predict when the COVID-19 pandemic will end. This study discusses the Markov chain method in predicting the status of COVID-19 patients in Indonesia. The prediction of the number of people who are positive for COVID-19, recovered, and die can be one of the government's bases for determining when the large-scale social restrictions (PSBB) will end. The results of the study stated that the COVID-19 pandemic in Indonesia would end at the end of 2020. On December 5, 2020 there were no more people infected with COVID-19 with a cure rate of 29.815% of patients with COVID-19 and a death rate of 3, 5933%.
Russian Legislation On Distance Learning In Higher School: Trends And Prospects

The global crisis transformation caused by the COVID-19 pandemic has fundamentally changed standards and radically updated the education system around the world.Currently, almost all Russian and foreign educational organizations are involved in the learning process, which is carried out through distance learning technologies.The article analyzes the regulatory framework for the use of distance learning technologies in the implementation of higher education programs.The system of legal regulation of education includes a significant number of normative acts of various levels and directions, which constitute a multi-level and complex structure.Currently, the system of laws and other legal acts on educational activities is increasingly expanding and improving.The advantages and disadvantages of the current legislation in this area are noted.The national education system, as the main resource of social progress, should be built on the basis of progressive legislation that has absorbed the best practices of domestic and world science and practice in the field of education.That is why it is necessary to improve the norms and provisions of the main branches of law affecting the education system.The article discusses the development of the relevant local regulations by educational organizations.The conclusion is made about the need to analyze the legal regulation of distance learning in educational activities.
Does Bitcoin Cash Have a Mind of its Own, or Will Bitcoin Always Determine its Future?

Bitcoin Cash is a cryptocurrency which was spun-off from Bitcoin in 2017. It was a result of a disagreement over Bitcoin’s 1mg block size which it was felt hindered transaction times. The Bitcoin Cash block size was initially set at 8mg allowing more transactions to be verified at a time, resulting in faster transaction times and was increased to 32mg in May 2018. Evidence points to a high correlation between Bitcoin and Bitcoin Cash prices but this only provides limited support for determining the direction of Bitcoin Cash price changes, not for the size of the price change. To enhance the understanding of the influence that Bitcoin has over Bitcoin Cash a multiplier is calculated which provides a picture of the difference between Bitcoin and Bitcoin Cash prices. The use of a multiplier provides an alternative point of view. The price of the two coins has moved further and further apart from an initial situation in July 2017, with Bitcoin 6.6 times the Bitcoin Cash price, to March 2021 where the Bitcoin price is now over 100 times the price of Bitcoin Cash. Just viewing them as highly correlated, indicating Bitcoin’s influence over the direction Bitcoin Cash price movements isn’t the whole story. Bitcoin Cash isn’t attached by a tether to Bitcoin but rather an elastic band. How far this will stretch before breaking, leaving Bitcoin Cash to find its own future, remains to be seen.
Multi‐branch network with hierarchical bilinear pooling for person reidentification

Because of issues such as viewpoint changes, posture variations, and background cluttering, the task of person reidentification (Re-ID) remains challenging. The model of combining global features and part features has been widely used in person Re-ID technology in recent years, but these efforts ignored feature interaction between the convolutional layers and thus lost detailed information conducive to identifying pedestrians under different cameras. To achieve interaction between hierarchical features, a multibranch network with hierarchical bilinear pooling (MBN-HBP) is proposed. The network consists of a global branch, a part-level branch, and a hierarchical bilinear pooling (HBP) branch. The person features extracted by the network include not only global and part-level features but also detailed HBP features. The final feature representation will be more robust to deal with the complex surveillance environment. By conducting comprehensive experiments, competitive performance on the Market-1501, DukeMTMC-Re-ID, and CUHK03 datasets is obtained.
Study Of Emotionality Of Teachers Employed With A Special Remedial Educational Institution

Emotional stability is an important characteristic of teachers, contributing to the implementation of educational activities.The most emotionally vulnerable profession that is affected by stress factors is that of "a teacher of a special remedial educational institution (SREI)", since they have to deal with profession-related challenges that arise in the face of a lack of time, significant emotional and metabolic expenditures.The study involved 40 teachers employed with a special educational institution, with different pedagogical experience (1-25 years), aged 23-68, and with higher defectologic education.There were 13 primary-school teachers, 19middle-school and 9both primary-and middle-school.The participants were both females and males.Fifteen teachers had the highest certification; tenthe lowest certification, fifteenno certification.A theoretical and methodological basis of the study is made up of a systematic approach, an activity approach, a competence-based approach, the concept of personal professional development, the theory of emotional phenomena.The authors applied theoretical (analysis of psychological and pedagogical literature, generalization, goal-setting, modeling) and empirical methods (A Study of Emotional Burnout by V. Boiko), ascertaining experiment).The findings showed that 86.6 % of the participants had a mature resistance phase; in 6.6 % of the teachers it was still under way, in 13.4 % the phase was immature; 46.7 % of the teachers involved had an emerging stress phase and in 20 % of the participants it was mature; the exhaustion phase was still under way in 26.6 %, and in 20.2 % it was mature.
Reporting R&D expenditure: A visual approach for technology managers and senior executives

Visualizations have the potential to be a powerful means of communication, especially for quantitative data, helping managers to see significant patterns and deviations. To be effective, visuals need to be appropriate for the task and properly designed. Most organizations tend to limit themselves to a small repertoire of rather simplistic graphs and charts. More expressive and intuitive representations can be deployed to provide both useful and engaging formats. This article presents a new composite form of visualization that has been designed to better convey research and development budget and expenditure figures to senior executives. In addition to providing a summary overview of the data, this functionally designed visualization offers a means to structure discussions in management meetings and provoke examination of what the data means in terms of financial allocations, top budget holders, requested funds, potential shortfalls, and weak/strong performing areas. The visualization deploys a combination of Sankey flow streams, mini pie charts, technology readiness levels, bar charts, annotated tick-marks, and graphic equalizer-style tally bars. Using a real-world dataset, an illustrative example is provided. This novel combination of visual objects provides an exemplar, which other organizations can adapt and apply, to support funding reviews and investment decision-making.
ANALISIS PERBANDINGAN PADA ALGORITMA BELLMAN FORD DAN DIJKSTRA PADA GOOGLE MAP

The Bellman Ford algorithm and the Dijkstra algorithm are often used in determining the shortest path. Bellman Ford's Algorithm and Dijkstra's Algorithm have the same way of working because both algorithms have the same strategy, Greedy. In the Greedy strategy the first step taken is to choose the side with the smallest weight among all sides connected from the initial node to the neighbor node. Compared to the Dijkstra algorithm, the Bellman Ford algorithm is superior because the Bellman Ford algorithm can complete calculations on graphs that have negative values. Determination of the shortest path using the Bellman Ford algorithm and the Dijkstra algorithm as a route reference used in determining the route from the Tembesi campus to the Tiban campus. This research was conducted to compare the two algorithms on the Google Map in terms of both the complexity of the space and the complexity of the time needed to provide a sol
A Novel Erbium-Doped Fiber Laser Chaotic Circuit Based on Memristor and Its Circuit Implementation

In this paper, a new chaotic system is proposed by adding a magnetron memristor to an erbium-doped fiber laser circuit, and its dynamical characteristics are analyzed. A special periodic coexistence attractor phenomenon was discovered during the analysis, which affects the dynamical characteristics of the system by changing the time parameters of the AC power supply and it is controllable. Finally, the chaotic system is implemented by constructing an equivalent analog circuit. Theoretical analysis and simulation results show that the new erbium-doped fiber laser chaotic system has good dynamical characteristics and it is easy to implement. Meanwhile, the rich dynamical characteristics of the system provide a basis for its application in image encryption and other fields.
AntVMp: An Approach for Energy-Efficient Placement of Virtual Machines Using Max–Min Ant System

The demands for Internet services are rapidly increasing in almost all the sectors which are provided through cloud datacenters. Cloud datacenters are equipped with high-end servers or physical machines (PMs) that execute user requests using virtual machines (VMs). These datacenters consume enormous amounts of energy for the processing of user requests as well as cooling of the equipment. Energy consumption (EC) also impacts the climate through the production of carbon traces. In the proposed work, this problem has been addressed using an ant-based meta-heuristic approach (AntVMp). Our work mainly focused on the offline placement of VMs in the datacenter to maintain the consumption of energy. AntVMp is compared with other VM placement heuristic methods and results state that AntVMp significantly improves the system performance in terms of EC.
Conceptual Model Of Managing A System For Preparing Students For Engineering Specialties

The article notes the engineering education importance for the Republic of Crimea.Attention is paid to the demand's low level for engineering professions among potential applicants entering higher educational institutions for engineering specialties.The scientific and pedagogical literature's brief analysis on the future specialty's choice, on the prospects for professional growth, on the problem of preparing applicants for an engineering education and the specialized schools and classes' development is given.The information and educational space structure for training future engineers in the Crimean region is considered.The informational and educational space state of the Republic of Crimea is analyzed.This revealed the need to develop a conceptual model for managing the system of training schoolchildren entering engineering specialties.In the informational and educational space regional system, a triad is involved school / secondary vocational education -higher school -enterprise, has become the subject of analysis, and subsequently an instrument to achieve the most high-quality and cost-effective students' training in educational institutions of higher education in the region.In the course of the study, interviews and questionnaires were carried out for schoolteachers, higher education teachers, schoolchildren and students who entered the engineering specialties in higher educational organizations in 2019-2020.
The Role of Computer Gaphics in Developing Students Space Imagination

According to experts, as a means of computer training, changes in the method and form of teaching are characteristic features of information technology. Therefore, the issue of identifying and generalizing the problems of teaching drawing in general secondary schools remains relevant.Because there are a number of issues related to the use of computer graphics in the process of teaching spatial geometric objects and drawing, they have been theoretically sufficiently addressed in the course of our research.
Rancang Bangun Sistem Informasi Geografis Pemetaan lokasi dan spesifikasi Hotel di Kota Palopo Berbasis Website

Palopo as one of the cities in South Sulawesi Province that is developing, especially in the field of tourism as conveyed by Andi Enceng as the Tourism Cadre of Palopo City, then Palopo was also appointed as the host of national activities such as national seminars of universities and international conference ICONSS. This makes many tourists who visit not only want to enjoy the beauty of nature, culture and so on but also to attend national activities carried out in palopo city, so that facilities and infrastructure related to lodging is needed in palopo city such as one of them is a hotel. However, information about the location of the inn is still not widely known. The information they get is less accurate in terms of geography, of course the limitations of information will be an obstacle for people who want to travel, especially for those who live outside palopo city to find information on the location of a nearby hotel location. The purpose of this research is to create a design of geographic information system mapping location and specifications of hotels in palopo city basedwebsite design interface and database system, make the system in accordance with the design that has been created and implement the system that has been created and conduct tests on the system. In data collection, the authors used methods of literature studies, observations and interviews. Meanwhile, in the development of the author's system using research and development method refers to the waterfall model. The software used is sublime text as text editor, PHP as programming language, MySQL for database management and xampp as its server. Testing techniques used in this system is black box testing techniques, Based on the tests that have been done that the design of geographic information system mapping location and specifications of hotels in the city of Palopo based website is feasible and in accordance with the required functions. The expected results in this study design this website provides all the data related to hotels in palopo city and has been adjusted in advance so as to facilitate parties in operating the system.
On the Integration of Artificial Intelligence and Blockchains 3.0: Prospects and Challenges

Many factors have led to recent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML). Among these factors, Deep Neural Networks (DNN), activations functions, large volumes of collected data, and significant computational and storage resources. Despite these advances, innovation in AI still in its infancy and remains out of reach due to cybersecurity and data privacy issues, and difficulties to decentralize the machine learning processes among peer-to-peer networks to gain access to data and resources at the edge. Blockchain technology is gaining more attention beyond cryptocurrencies and Fintech. Distributed applications (DApps) with smart contracts are at the core of recent efforts to build decentralized Artificial Intelligence and Machine Learning applications. These are two different technologies but their integration advocates a paradigm shift of building secure, scalable and smart applications and services in decentralized and trustless environments.In this talk, we shed light on challenges and opportunities from AI/ML, blockchains 3.0 and cybersecurity perspectives and identify the need for fundamental research and new architectural design to build next generation of trustworthy AI/ML systems.
Activity Content Of Education As A Prerequisite For Students' Professional Competence Mastering

This article describes the characteristics of the action-related content of education in the context of a person-oriented approach to education.The action-related content includes methods of cognition specific to each educational field and methods of students' activity.The research shows that education is perceived by most students as a sphere that is disconnected from real practice, as well as from the life goals and plans of the students themselves.We assume that the decline in the quality of education is largely connected with a set of characteristics, including the action-related content of education.The teacher should organize the educational process in such a way that the student is the creator himself, and is not just the host country of the training.The creation of appropriate motives should be considered as a necessary condition for mastering professional competence by students.However, in our opinion, not enough attention is paid to the formation of responsibility among students.We consider the concept of responsibility as a key element when forming students' action-related motives.The data obtained in the course of the research indicate that students do not have a clear understanding of the content of the responsibility concept.The purpose of this work is to consider the characteristics of the action-related content of education in the context of a personality-oriented approach and to determine the ways of forming action-related motives in students.The formation of responsibility can become an important direction of qualitative change in modern Russian education.
Transfer learning and Auto-ML: A geoscience perspective

Abstract Deep learning continues to receive increasing attention from researchers and has been successfully applied to many domains. This paper further extends the work from Zabihi Naeini and Prindle (2018) by adopting and examining two classes of Machine Learning techniques and their applications in geoscience with a pragmatic view. These are Transfer Learning and Automated Machine Learning or Auto-ML (Feurer and Klein, 2015). Although machine learning (ML) is known to be most efficient and accurate when trained on a large volume of data, there are cases in practice where ML methods are also implemented with limited available data. In such cases ML algorithms are less efficient in generalising to new data and it is where Transfer Learning can add value. This is shown in an automatic petrophysical interpretation task where Transfer Learning is compared with training from scratch given a new geological area of interest, i.e., a set of wells in a different area. We show the efficiency of Transfer Learning in obtaining a model that generalizes successfully for the new wells investigated.
The color phi phenomenon: Not so special, after all?

We show how anomalous time reversal of stimuli and their associated responses can exist in very small connectionist models. These networks are built from dynamical toy model neurons which adhere to a minimal set of biologically plausible properties. The appearance of a “ghost” response, temporally and spatially located in between responses caused by actual stimuli, as in the phi phenomenon, is demonstrated in a similar small network, where it is caused by priming and long-distance feedforward paths. We then demonstrate that the color phi phenomenon can be present in an echo state network, a recurrent neural network, without explicitly training for the presence of the effect, such that it emerges as an artifact of the dynamical processing. Our results suggest that the color phi phenomenon might simply be a feature of the inherent dynamical and nonlinear sensory processing in the brain and in and of itself is not related to consciousness.
Towards a Joint Ontology of Quran and Hadith

The Quran and the Hadith are two religious texts used by Muslims as reference to perform their daily religious obligations. Hence, developing a computational tool to better understand and link these different texts would be useful for Islamic scholars, learners, and laymen. We hypothesise that linking them using a knowledge-based approach by extending a Quran ontology to cover the Hadith is possible. However, there are several Quran ontologies and none of these were rigorously evaluated using a standard ontology evaluation method. For this reason, we started our experiment by enumerating and discussing the existing Quran ontologies. Then the best candidates of the enumerated ontologies are evaluated using a corpus-based approach to visualize the overlap between these ontologies and the Hadith. Our experiment shows that one Quran ontology could be used as a starting point for a larger scope of an Islamic ontology that covers both the Quran and Hadith.