Reviewerly/exHarmony huggingface dataset:
Unsupervised based Crimes Cluster Data Using Decision Tree Classification

Crime cluster data set contains a traditional of input paths without slightly target values. The unsupervised machine learning practice is to find groups of similar cases in difficult data, controlling the data is distributed in a space called clustering or density estimation. True class labels are not provided to bring forward modest word usage for sample space. Cluster data are classified into subgroups using decision tree that do not have the parameters of an unsupervised learning process, where each cluster tells approximately about the types and classes contained in the data. Typically, this method is used to determine the tree classification pattern and to analyze data with small sample sizes. The experimental result will be used to follow the Gaussian Mixture Model composite sample distribution based on Expectation Maximization in the Crime Cluster data set.Keywords-Crimes Cluster Data Set, Decision Tree, Expectation Maximization, Gaussian Mixture Model, Unsupervised Machine Learning.
Time evolution law of Wigner operator in diffusion channel

As is well known, the evolution of quantum state can be replaced by its Wigner function’s time evolution. The Wigner function of a quantum state is the same as the density matrix of a quantum state, because they both contain many messages, such as the probability distribution and phases. Thus, the important information about the quantum state in the evolution process can be obtained more quickly and effectively by studying the Wigner function of a quantum state. In this paper, based on the classical diffusion equation, the diffusion equation of the quantum state density operator is derived by using the &lt;i&gt;P&lt;/i&gt; representation of the density operator. Furthermore, by introducing the Weyl ordering symbol of the quantum operator, the corresponding Weyl quantization scheme is given. In addition, the evolution equation of Wigner operator in diffusion channel is established by using another phase space representation of density operator—Wigner function, and the solution form of Wigner operator is given. In this paper, we derive the evolution law of Wigner operator in quantum diffusion channel for the first time, that is, the form of Wigner operator at any time in the evolution process. Based on this conclusion, the evolution of coherent states through quantum diffusion channels is discussed.
Diagnosis of Lung Disease Using Learning Vector Quantization 3 (LVQ3)

Lung disease is one of the diseases with the highest number of patients in Indonesia. Lung disease is a disease with many types and symptoms that are almost the same as each other. This study uses an artificial neural network Learning Vector Quantization 3 (LVQ3), to diagnose lung disease. The data used in this study were 113 medical records, with seven types of lung disease, and 27 symptoms of the disease. From the experimental results, the best LVQ3 parameters from this study are using m = 0.15, and the learning rate = 0.15. LVQ3 produces the best accuracy value for training data at 87.5% of 80 data, and accuracy for test data 88% of 33 data.
PROBLEMS AND PROSPECTS OF DEVELOPMENT, QUALITY OF PROVIDING EDUCATIONAL SERVICES IN MODERN SOCIOECONOMIC CONDITIONS

The article discusses the shortcomings in the activities of educational organizations, factors and conditions affecting the quality of the provision of educational services. The authors consider various measures of a mobilization nature that can have an impact on improving the quality of the provision of educational services in educational institutions.
TO THE QUESTION ABOUT THE METHODS OF TEACHING PEDAGOGY IN CONDITIONS OF DISTANCE LEARNING

Processes of modernization of teacher education in Russia at the end of 2019-2020 were significantly complicated by the outbreak of coronavirus infection. One of the urgent measures was the transfer of the work of educational organizations to a remote mode of work. The organization of online interaction assumed the use of special techniques for building the educational process, forms of control, methods of communication through Internet technology, as well as specially undertaken organizational and administrative measures. The purpose of the study is to identify and scientifically substantiate certain aspects of the teaching methodology of pedagogy by means of distance learning in the context of the 2019-2020 pandemic. The article specifies certain features of pedagogy as an academic discipline: the use of a plurality of methodological pedagogical knowledge, including that based on the theories of existentialism, neo-Thomism, pragmatism, neobehaviorism, etc .; orientation in the goal-setting of the process of preparing future teachers not so much on the ideas of globalism, but on the principles of practicality, moderation and attainability; formation of the content of the course of pedagogy in accordance with the educational order; practical orientation, subject-subject orientation of technologies for implementing the course of pedagogy; orientation of the monitoring of the quality of pedagogical education to the use of complex assessment tools that allow to establish not only the level of formation of cognitive, activity components, but also the emotional-value component of general professional competencies, etc. new educational tasks of the pedagogy course that arose in the context of the implementation of distance education are formulated, proposed for discussion some conclusions about teaching pedagogy by means of distance learning: about the features of goal-setting of the course of pedagogy, the content and technologies of organizing students' independent educational activities, about the need to use subject-oriented learning technology, about the forms of organizing the educational process, etc.
Interpretable Reinforcement Learning With Neural Symbolic Logic

Recent progress in deep reinforcement learning (DRL) can be largely attributed to the use of neural networks. However, this black-box approach fails to explain the learned policy in a human understandable way. To address this challenge and improve the transparency, we introduce symbolic logic into DRL and propose a Neural Symbolic Reinforcement Learning framework, in which states and actions are represented in an interpretable way using first-order logic. This framework features a relational reasoning module, which performs on task-level in Hierarchical Reinforcement Learning, enabling end-to-end learning with prior symbolic knowledge. Moreover, interpretability is enabled by extracting the logical rules learned by the reasoning module in a symbolic rule space, providing explainability on task level. Experimental results demonstrate better interpretability of subtasks, along with competing performance compared with existing approaches.
The Role of E-marketing and Finding Job Opportunities for Young People on Social Media; An Empirical Sociological Study in Al-Diwaniyah City

The world is currently experiencing a technological revolution in various sectors of life. Information and communications have become among the most important environments for business today. Among the aspects of this progress is the tremendous revolution that occurred through the emergence of Internet technology in the field of marketing. The present study revolves around the role played by the new economy in opening new fields to work with less effort and less cost to improve the lives of individuals. It highlights the reasons why young people are interested in it. The importance of the present study is due to tackling electronic marketing that has spread and increased positive and negative points in its use in the field of marketing, which increased. The importance of studies. The major objective of the present study is to identify the role of e-marketing in opening a new market for work in social networking sites. The results of the present study indicate that females are more interested in buying through social media. The majority of respondents know that they have been shopping on social media and that they have become more popular than before. There is an increasing demand of young people to sell through social media, which represents an opportunity for them to work from home. The results of the present study indicate that commodity trading through social media has contributed to finding job opportunities for young people and provided an opportunity to increase income and improve the standard of living.
Optimization of Activated Sludge Process in Wastewater Treatment System Using Explainable Neural Network

In this paper, we proposed DO(Dissolved Oxygen) neural network model and DO Control of activated sludge process in wastewater treatment system. Explainable neural network was utilized to decide water qualities which have a much influences in DO biological operation. These water qualities was to be inputs of DO neural network. Also, in regulations, effluent COD, T-N, T-P, pH, SS are hourly to transmitted in Korea Environment Corporation. If these data are exceed the standard, the penalty is given. So, these data are very exact and is controlled by operators critically. So, these data is to be inputs of DO neural network model. DO neural network model is to be utilized for optimal DO set-point which is controlled by blower. As one blower is connected to several aeration tanks, it is difficult to control DO in each aeration tank. Each aeration tank has 2-4 DO sensors which have different values. These are problems in automatic DO control. We also propose practical control solution by valve control logic and DO sensors calibration. The validity of the method is proved by applying to the DO neural network model of activated sludge process which was developed in previous research. The result show that the performance of the proposed model was improved in comparison of previous fuzzy model and conventional neural network models. Also, applicability is proved by field test of DO control in real activated sludge process in wastewater treatment system. In the future, it will be more effective in saving of blower power if this methodology is connected to control of blower valves.
Overview of Methods to Avoid User Profiling

Nowadays online communication services have obtained a stronger impact in our world. Some companies that provide communication services take advantage of them to create user profiles, which they further use to send undesired advertisements (Ads), or spam, to their users. This article explores several methods, developed based on different areas of knowledge including natural language processing, steganography, cryptography, which can help a user to avoid being profiled while sending and receiving texts over the internet.
PENGARUH PENGUASAAN TEKNOLOGI INFORMASI TERHADAP AKURASI KERJA POLISI DI POLRES KABUPATEN KERINCI

This study aims to determine the effect of information technology mastery on the accuracy of police work at the Polres Kabupaten Kerinci. The formulation of the problem posed is: Is there Information Technology Mastery on the Accuracy of Police Work? How big is the influence of information technology mastery on the accuracy of police work. The results of the research are based on the results of the analysis of the Information Technology Mastery variable towards the accuracy of police work, where the t value is 2.512 (sig 5% <1.683), so Ho is rejected, which means that Information Technology mastery has an effect on the accuracy of police work. Meanwhile, the influence of Information Technology Mastery on Police Work Accuracy was 0.307 or 30.7%. This shows that the restructuring variation can explain the variation (movement pattern) of the performance value of 30.7%.
Freedom of Speech and Social Networks in the Age of Terrorism: A Comparative Analysis

1. Hate Speech: An Uncertain Definition. – 2. Freedom of Speech in the Age of Terrorism: the USA Case. – 3. Hate Speech on Social Networks in the USA. – 4. European Models of Offline and Online Freedom of Speech. – 5. Hate Speech on the Internet in Europe between Private and Collateral Censorship. – 6. European Union Proposal on the Prevention of Terrorist Content Online. New Regulation, Old Issues. – 7. Conclusion.
INVENTORY INFORMATION SYSTEM OF PHARMACEUTICAL WAREHOUSE OF HEALTH OFFICE OF MERAUKE DISTRICT

The pharmaceutical warehouse in the pharmaceutical sub-department of the Merauke District Health Office is a center for drug distribution in and out of the Merauke Regency area. Until now, the system used in harmaceutical warehouses is still semi conventional in the process of data collection of drugs. This study aims to make an inventory information system application in the pharmacy warehouse to be faster in carrying out inventory data collection and reporting drug distribution out and that goes to the pharmaceutical warehouse. The method used is data collection using literature studies, interviews, and observations and forward chaining in system implementation. Application testing method is by conducting a simulation, the results obtained in this study based on the simulation results are an inventory control system supplying the goods produced can be used to conduct real time monitoring of stock positions, reorder points, and periodic reviews. The rule-based forward-chaining inference method that is applied can process the facts that occur regarding changes inwarehouse stock and stock renewal warnings.
Light-Weight Selective Image Encryption for Privacy Preservation

To protect personal privacy and confidential preservation, access control is used to authorize legal users for safe browsing the authorized contents on photos. The access control generates an authorization rule according to each permission assignment. However, the general access control is inappropriate to apply in some social services (e.g., photos posted on Flickr and Instagram, personal image management in mobile phone) because of the increasing popularity of digital images being stored and managed. With low maintenance loads, this paper integrates the data hiding technique to propose an access control mechanism for privacy preservation. The proposed scheme changes the partial regions of a given image as random pads (called selective image encryption) and only allows the authorized people to remedy the random pads back to meaningful ones which are with similar visual qualities of original ones.
Modal Logic of Digital Transformation: Relentless Pace to “Exo-Intellectual” Platform

It is a generally accepted opinion that digital transformation of the economic and production infrastructure of today’s society are natural result of technologies evolution of in which information processing factors start to play the lead role with building “smart” machines capable in autonomic manner performing tasks that typically require human intelligence. Machine mind, consciousness and artificial intelligence (AI) now are priority interdisciplinary branches of natural and computer science with multiple approaches and advancements in virtually every sector of the production and entertainment industry. The popularity of the idea of artificial intelligence is due to some factors: computer technology has become prevalent; digitalization transforming touched of nearly every corner of the humane world, science and technology. But here is a threat that the chaotic relentless pace of human intellectual development may push technological evolution to the unstable attractor known as “flickering mind” [1]. The article is devoted to the analysis of the role that logic and ethics can play in the process of technology development, especially in the aspect of fundamental research and adaptation of the education system to new challenges associated with the symbiosis of human intelligence and computer modeling capabilities to predicts the possible ways of evolution. This symbiosis forms a new technological reality, the essence of which can be expressed by the word exo-intelligence, which means computer technologies that can simulate cognitive functions – new class of mathematical objects which phenomenological features will be discussed below.
Hybrid Huffman Tree Model for Securing Medical Data Using Steganography

Steganography is the method by which confidential data can be camouflaged in plain sight with the help of an unsuspecting “cover” data. Digital Steganography refers to the art of concealing a confidential piece of information inside a non-suspecting carrier. In image steganography, within a cover image, a secret message is concealed and it is important to make sure there should not be any alterations in the visual or statistical features of the image. The proposed work makes use of a number of concepts like Edge Detection of cover image, Least Significant Bit Replacement of edge pixels, Huffman Tree compression, and mutation, to name a few. Least Significant Bit substitution is a very popular method due to its ease of implementation and high data hiding capacity. The secret key used for swapping in the initial tree is converted from binary to decimal format and is sent through some other secure transmission channel to increase security.
Learning to Recognize Patch-Wise Consistency for Deepfake Detection.

We propose to detect Deepfake generated by face manipulation based on one of their fundamental features: images are blended by patches from multiple sources, carrying distinct and persistent source features. In particular, we propose a novel representation learning approach for this task, called patch-wise consistency learning (PCL). It learns by measuring the consistency of image source features, resulting to representation with good interpretability and robustness to multiple forgery methods. We develop an inconsistency image generator (I2G) to generate training data for PCL and boost its robustness. We evaluate our approach on seven popular Deepfake detection datasets. Our model achieves superior detection accuracy and generalizes well to unseen generation methods. On average, our model outperforms the state-of-the-art in terms of AUC by 2% and 8% in the in- and cross-dataset evaluation, respectively.
Segments of the Scientific Space of Scientist and Librarian of the Late 19Th — the Early 20Th Century M. Ryazantsev

Relevance. The iconic figure of the late 19th — the early 20th centuries is the talented scholar and librarian M. V. Ryazantsev. He contributed to the development of veterinary science and at the same time the development of librarianship.The purpose of the article is to summarize the segments of multifaceted creative activity of professor and librarian M. V. RyazantsevResearch methodology is based on general scientific principles of historical knowledge, application of methods of analysis and synthesis, generalization, using archival materials.Results. The segments of the scientific space of M. V. Ryazantsev are scientific, educational, scientific and organizational work and scientific-communication aspect, as well as library, editorial and translation activities. He personally conducted 16 studies. More than 48 studies were carried out under his guidance and assistance. In 1896 M. V. Ryazantsev was approved by the professor of the Department of Physiology. His lectures epitomized the illustrations of the results of his own research. He trained many eminent scientists.The peculiarity of his scientific and organizational activity was the problem solving of the construction and equipment of new educational and scientific classes, reconstruction of clinics, and organization of physiological laboratories. The significance of his scientific communications during foreign internships in Germany, Austria-Hungary, Switzerland and France in 1899, 1910, and 1912 is revealed.The scholar made a significant contribution to the development of library activities. On the basis of archival data, it was found out that Professor M. V. Ryazantsev had devoted twenty-six years to the library activities. He is to introduce a number of innovations to improve the quality of the library work and ensure library processes, enhance the information and methodological functions of libraries.Novelty. The paper is the first attempt for the description of the segments of the scientific space of Professor and Librarian M. Ryazantsev.The practical significance. The materials of the study can be used in preparing general works on the history of science and library information science.Conclusions. M. Ryazantsev’s scholarly communications contributed to the expansion of his scientific interests, the introduction and dissemination of advanced ideas, the development of the library.
Efficient update of multilinear singular value decomposition in background subtraction applications

Subtraction techniques are used to distinguish moving objects or foregrounds that are being tracked from a static background. To prevent possible local misclassifications, the subspace spanned by low-rank features computed from a multilinear singular value decomposition (MLSVD), can be used to filter out noises or gradual changes from the background. However, as it is prohibitively expensive to compute a new MLSVD from scratch at every iteration, we propose an adaptive and efficient method for updating an MLSVD by reusing previous decompositions while tracking more accurate decomposition errors. The experimental results reveal that the proposed MLSVD update algorithm exhibits a faster execution speed and better accuracy than other MLSVD update algorithms used in background subtraction applications.
Designing a Model of English for Tourism Materials Using Communicative Approach at English Department of Sultan Ageng Tirtayasa University

The present study aims to determine and propose a model of material for English for Tourism using communicative approach. The present study uses a research and development methodology (R&D). The data collecting techniques are documentation, questionnaires, and interviews. The data gathered from documentation and interviews were analysed using content analysis while the data obtained from the questionnaires were analysed quantitatively using SPSS. The results of data analysis indicate that (1) the materials used of English for Tourism are based on lecturer’s assumptions, (2) based on the expert  validation, the model material of English for Tourism falls into a very feasible category with the percentage of 86.76 %. The teaching materials based on the results of the students responses by the percentage is in the category of good (78.9 %). Based on the validation both from expert and students it could be concluded that a model of EFT material using communicative approach seems to be feasible to be applied in English Department of Sultan Ageng Tirtayasa University.
Reception and Structure

This chapter discusses the results of an experiment testing audience response to Robert Morris’s <italic>Clear Sounds among Hills and Waters</italic> (1989, revised 2013), for solo piano, under five different preparatory conditions: simple identification (ID), program note (PN), aesthetic/visual introduction by the composer on video (AES), structural/aural introduction by the composer on video (STR), and the combination of all of the preceding (CMB). Qualitative analysis of responses suggested that preparations ID, STR, PN, AES, and CMB, in that order, were increasingly beneficial for audience appreciation and understanding. The piece’s context and meaning needed to be explained before structural information could be employed effectively. The combination of aesthetic with structural information was more helpful than either alone. <italic>Indirect knowledge</italic> about the piece must translate into <italic>direct knowledge</italic> for greater impact. The chapter then explores broader issues implicated in audience reception of new music: characteristics of the listener, social and cultural factors, and features of the musical language, described by analogy to phonetics, morphology, syntax, and semantics. Stimuli for the experiment, including Leong’s performance of <italic>Clear Sounds</italic> on video, may be found online.