Reviewerly/exHarmony huggingface dataset:
Software tool for detecting fake video content using the Deepfake technology of the GAN algorithm

In the modern world, one of the main and urgent problems is false content: news, videos, photos, etc. Early on in the development of Deepfake technology, it was used by amateur users to generate multimedia content by matching human facial expressions and phrases, usually owned by recognizable individuals, to create fake media that looked genuine. But the situation is changing, and Deepfake technology is being used not for compromising, but for campaigning and attracting political supporters. The purpose of the study: Software implementation of the video content recognition algorithm, synthesized using the Deepfake technology of the GAN algorithm, with acceptable accuracy. In the work, a software implementation was proposed that analyzes the video and makes a decision about the authenticity of this one. The main architectures of the GAN algorithm are presented, as well as the opportunities and threats of using deepfake technology. An analysis of the features of the Xception and ResNeXt models trained using neural networks was carried out. Methods: For the system to work, it is necessary to select suitable neural networks based on performance results, which can be ResNeXt, XceptionNet or any other neural network. As part of this work, ResNeXt and XceptionNet will be considered and used in the software implementation, as well as BlazeFace is a pre-trained human face recognition model used to recognize faces in extracted images. Results: The function input is the path to the video (in the file system). The sample is frame-by-frame checked for the presence of a face in each individual frame, if the recognition was successful, the data is added to the list. Optionally, you can leave a fixed number of samples with the best quality among those presented.
Self-didactic principles of activating self-educational activities of students

The article describes the relationship between the concepts of “self-education”, “self-educational activity” and “individual work” of students. The essence of the concept of “self-educational activity of a student” has been defined. The autodidactic principles of activating students’ self-educational activities are analyzed. Self-educational activity of a student is defined as an active activity of the student himself, which involves the motives and desire to acquire education continuously throughout the whole life in conditions of constant updating of knowledge, improvement of abilities, skills, not only for the professional self-realization in the future activity, but also for the sake of self-development, development of potential opportunities of one’s own personality. The connection between the concept of self-education and autodidactics as a self-educational system-technology of students’ independent acquisition of new knowledge, development of skills and abilities, formation of an active personal position, actual interest search, presence of intentions, conscious needs to learn throughout the life and creation of conditions for their implementation is outlined.
Determining the Best School using the Concept Generalized Picture Fuzzy Soft Set

Determining the best school in the education system is an essential task. One approach that can be used to determine the best school is using the generalized picture fuzzy soft set (GPFSS) concept. GPFSS is an extension of the picture fuzzy soft set (PFSS) concept in which each parameter is defined a picture fuzzy set (PFS) stating the level of importance of the parameter. This research proposes the GPFSS approach to determine the best schools. This approach is based on consideration of several factors, namely the quality of the school environment, the quality of school facilities, the quality of teachers, the quality of the learning process, and school achievement. The research results show that the GPFSS approach can accurately determine the best schools. The best schools based on the GPFSS approach have a good school environment, facilities, quality teachers, learning processes, and good school performance
Analysis of Sales Business Process Modeling and Stock Control at Raja Optik

Abstract— The purpose of this research is to offer modeling of new business processes to overcome the problems of the sales cycle and stock control. The method used is a qualitative method that directly observes the object of study, the Raja Optik MSME. Researchers use BPMN to describe ongoing business processes (as is) and to design and propose new business processes (to be). The results showed that there were several weaknesses in the sales process and stock control due to technology, method, material, and human factors. There is no mutually integrated system between branch stores and warehouse. There is also the risk of fraud by changing the denomination of the invoice, as the invoice remains in the form of an invoice. The process of moving archive notes from branch stores to be submitted to the admin every week causes the risk of losing invoices. This manual people to people process carries a high level of risk during the sales reporting process. As part of the lens inventory movement, the store contacts the warehouse to inquire about stock availability. With so many branch stores, stocks cannot be presented in real time to facilitate stock transfers between branches. Additionally, manual inventory reconciliations are required when moving inventory between stores or warehouses. As a result, information systems for sales and stock control did not function effectively and efficiently. Computer-aided business process modeling for sales and stock control has been proposed in hopes of overcoming the weaknesses identified in the current Raja Optik.Keywords—Accounting Information System; Sales; Stock Control; BPMN
Classification of Tutoring Teachers Uses the Concept of The Correlation Coefficient

Picture Fuzzy Set is a development of the intuitionistic fuzzy set concept. Picture Fuzzy Set is modeled in a situation when facing human opinion which involves more answers: yes, abstention or neutral, no and rejection. Therefore, to deal with situations like this, the concept of the proposed correlation coefficient is used to calculate the degree of correlation between picture fuzzy set that aim to group different objects. The correlation concept used in picture fuzzy set uses two formulas. And in deciding on a problem, we use the grouping method for picture fuzzy sets introduced by Xu et al [11]. There are four forms of classification.
Fault detection in wireless sensor networks with deep neural networks

This paper addresses the challenge of fault detection in Wireless Sensor Networks (WSNs), commonly used in fields like environmental monitoring and healthcare. WSNs, prone to various faults due to their deployment in unpredictable environments, require effective solutions for fault detection. Traditional machine learning approaches show limitations such as unsuitability for streaming data and the detection of a single fault type. We propose the use of deep neural networks, particularly Recurrent Neural Networks (RNNs), for fault detection in WSNs, focusing on temperature and humidity data. The paper emphasizes the importance of careful model selection, tuning, and thorough evaluation to enhance the accuracy and robustness of fault detection in real-world WSN applications.
MRCNet: Multi-Level Residual Connectivity Network for Image Classification

Computer vision obtains object and environment information by simulating human visual senses and borrowing human sensory activity. As one of the main tasks of computer vision, image classification can be used not only for face recognition, traffic scene recognition, image retrieval, and automatic photo categorization but also as a theoretical basis for target detection and image segmentation. In this paper, we use the existing CNN architecture network-ConvNeXt. By adapting and modifying the residual connectivity and convolutional structure of the network, we achieve a balance between classification accuracy and inference speed. These modifications are able to reduce both computation and memory consumption while keeping accuracy largely unchanged, thus better facilitating network lightweighting.
Multipartite quantum key agreement against d-dimensional collective-dephasing noise

In this paper, we introduce a novel model for collective-dephasing noise in [Formula: see text]-dimensional space. After that, we construct a multi-particle entangled state to resist the given collective-dephasing noise. Based on the measurement laws of multi-particle entangled state under two different bases, we propose a multipartite quantum key agreement protocol. In this protocol, multiple participants would obtain [Formula: see text]-dimensional secret key even if the quantum channel is influenced by collective-dephasing noise. The security analysis indicates that this protocol can resist both dishonest participant attack and the outsider attacks which include intercept-resend attack and entangle-measure attack. By comparing with the existing QKA protocols, it is clear that our protocol has greater universality from the perspective of dimensionality and number of participants.
Improvement Competency of Teachers and Students to Improve Capabilities in Security Awareness Aspects at SMK Pustek Serpong

Program Kemitraan Kepada Masyarakat (PKM), we propose in PUSTEK Serpong Vocational School that is targeted is Computer and Network Engineering (TKJ) students. Until now there have been several obstacles that occurred during the implementation and learning activities, namely in the previous curriculum there were materials and teaching materials for Network Security and since 2013 the curriculum and teaching materials have disappeared, and there is a need for discussion and material. In the form of learning modules for Network Security competencies. The results of this PKM are expected to gain an increase in scientific capacity and competence by 80% for Network Security training at the PUSTEK Serpong Vocational School. So that at the end of this PKM activity, the proposer hopes and tries with the knowledge and application of the training provided to students, to be able to motivate and provide Information Communication Technology (ICT) knowledge, especially in the field of Computer Network technology and Network Security, so that future students can be prepared use in the world and work industry.
Yuval Sharon’s Twilight: Gods (2020-21)

Yuval Sharon’s Twilight: Gods is a drive-through opera that presents a contemporary vernacular reimagination of Richard Wagner's Götterdämmerung. Motivated by pandemic-related concerns, it was staged in the Detroit Opera House Parking Center in October 2020 and subsequently in Chicago’s Millennium Lakeside Parking Garage in April 2021. Rejecting immersion, my article puts forth re-enchantment as a phenomenological model, which captures the sense of play underlying site-specific opera. I build on Carolyn Abbate’s notion of “ludic distance” in positing that re-enchantment is derived not despite, but because of our hyperawareness of the creative tensions present in the hybrid media and technologies fleshed out before us. Moving on then to more specifically ideological—and ethical—considerations, I interrogate the racialized scripting underpinning the opera’s display culture. Employing Matthew Morrison’s Blacksound, I examine Scene 4 (“Siegfried’s Funeral March”) in demonstrating how it reveals an attempt to muster Detroit/Blacksound in the commodified packaging of Black signifiers for the edification of an elite, mostly white audience. A musical collaboration premised on “fitting” Black music into the dominant Western paradigm perpetuates musical essentialism. Similarly problematic questions ensue from examining the ethics and politics of collaboration with the two Black poets who contribute to the productions in uneven ways. It is an open question whether, in the end, the creative team has succeeded in fulfilling the redemptive terms it has set for itself. I conclude by stimulating further questions and reflections on how a socially progressive and anti-Racist opera would look and sound like in 21st-century America.
Discourse “Ndasmu” on twetter after the 2024 Presidential Election Debate in Indonesia Topic Modeling and Sentiment Analysis

The purpose of this study is to examine the conversation that transpired on Twitter following the Indonesia 2024 presidential election debate, with particular attention on the phrase "Ndasmu." To better comprehend the speech patterns and attitudes that surface in online interactions, this research use topic modeling and sentiment analysis. The following Twitter data collection steps are part of this research methodology: To retrieve relevant tweets, use the Tweepy library to access the Twitter API. Access can only be obtained using a Twitter API key. Pre-processing Text: Eliminating superfluous characters, links, and mentions from the text data. Tokenizing text means breaking it up into individual words or phrases. eliminating stop words. Topic Modeling: Non-negative Matrix Factorization (NMF) or Latent Dirichlet Allocation (LDA) are two methods used for topic modeling. Two well-liked Python packages for topic modeling are Scikit-learn and Gensim. Sentiment analysis can be done with TextBlob or NLTK. While TextBlob makes things easier, NLTK offers more customization options. Visualization: Producing word clouds for subjects and sentiment distribution, among other visual representations of the data, requires the use of tools like Matplotlib or Seaborn. It is anticipated that the study's findings would provide light on the prevailing themes in the "Ndasmu" discourse and the attitudes that accompanied the presidential debates. These findings can help us comprehend the dynamics of public opinion and how individuals react to important political occasions like debates for the presidential nomination.
Development of Characterized Digital Comics for Junior High School Students in Social Studies Learning

This study is aimed at developing the material for social science study at Junior High School by using characterized digital comics. The study uses a research and development model popularized by Borg and Gall. The types of data used in this research are qualitative and quantitative data. Qualitative data was obtained based on criticism and suggestions for improvement from validators. Quantitative data was obtained based on the results of filling out a questionnaire in the form of objective product assessment scores. The instruments used for data collection were open and closed questionnaires. Based on the results of data analysis from media experts, a feasibility value was obtained from media experts 149 a maximum value of 152 so that a percentage of 98% was obtained, from material experts a feasibility value was obtained of 112 from a maximum value of 114 so that a percentage of 98% was obtained, and the results of scale group trials limited (10 students) obtained a score of 890 out of a total of 1000 so that a percentage of 89% was obtained. This shows that the digital comic with characters being developed is classified as "very valid" and can be implemented. In brief, the results of developing digital comics with characters are appropriate and can be recommended to be used in social science studies at junior high schools.
Determining The Concentration of Heavy Metals in Soil Contaminated with Crude Oil at Al-Kasak and Al-Qayyarah Sites According to Environmental Indices of Pollution

Contaminated soil samples were collected from Al-Kasak refinery and Al-Qayyarah refinery in western and southern Nineveh, at specific distances in six dimensions (0, 50, 100, 150, 200, 300) meters from the source of pollution, to study the concentrations of heavy metals Pb, Mn, Ni, Cd, and the effect of oil refinery pollutants on some soil pollution standards, in addition to some physical and chemical properties of the soil and their concentrations. The results showed an increase in the concentration of heavy metals in the soil near the sources of pollution, with cadmium significantly superior to Al-Qayyarah site over Al-Kasak site (491.744) mg/kg, and lead, nickel and manganese recorded a higher concentration at Al-Kasak site compared to Al-Qayyarah site (166.356, 114.687, 36.487) mg/kg, respectively, and the order of mineral elements in the two study sites was Cd&gt;Pb&gt;Ni&gt;Mn.&#x0D; As for the Contamination Factor (CF), it was Cd &gt; Pb &gt; Ni &gt; Mn with values of 684.50, 9.91, 5.13, and 0.1701, where the concentration factor was highly polluted for cadmium and lead, and with significant contamination for nickel, while manganese was low in contamination, cadmium recorded severe pollution at Al-Qayyarah site compared to Al-Kasak site, while lead, nickel and manganese recorded significant contamination at Al-Kasak site compared to Al-Qayyarah. In addition, the pollution load index (PLI) was at the level of 5.81, 4.67 highly polluted at D1 and D2, while the rest of the percentages were at the level of 2, moderate pollution, Al-Kasak site had the highest pollution (PLI) value of (6.28), while the ecological risk (ER) averaged (20534.88, 16896.71, 19867.11, 19063.14, 18721.07, 18888.61), which indicates that all the sites had very high pollution, and the ecological risk index was also within the limits of very high pollution, with the highest value on D1 recorded (20568.45), and the potential ecological risk of cadmium was very high at Al-Qayyarah site with a value of (19410.95) compared to Al-Kasak site, where the ecological risk of lead, nickel and manganese was very high, and the ecological risk indices for Al-Qayyarah site were high compared to Al-Kasak site. The aim of the study is to estimate the concentration of heavy metals, according to environmental indices and the impact of oil refineries on the ecosystem in raising the level of heavy metal concentration.
Research of the Experience of Creation, Classification of Foreign Campuses and Peculiarities of their Financing

In modern conditions of spatial development, university campuses have undergone significant changes, representing not only platforms for joint research of science and business, but also the centers of urban innovation districts, which form an innovative community in the city and adjacent territories, having a significant impact on the socio-economic development of the region. The purpose of this work is to study foreign experience in the creation, operation and financing of foreign campuses for further application in the implementation of projects for the creation of new university–type campuses on the territory of the Russian Federation. The objectives of the research in the article were: the issues of systematization of foreign campuses by type of territorial location, scale, type of settlement and architecture; comparative grouping of infrastructure in foreign and Russian university campuses; financing mechanisms for the creation and operation of foreign campuses. Methodology – a system of scientific methods for grouping infrastructure facilities on foreign campuses, tabular synthesis of accounting and analytical information on the availability and movement of income and expenditure of national budgets, based on the best foreign experience. Within the framework of this article, the authors assessed the stages of creation and commissioning of campuses based on the experience of a number of countries: China, South Korea, Japan, France, Finland, Austria, which allows us to conclude that flexibility and diversity in design schemes in accordance with local characteristics, commissioning and modernization of campus facilities in Russia. As a result of generalization of the best world practice in the field of creation and functioning of university campuses, the article develops recommendations for assessing the appropriateness of financing and evaluating the effectiveness of budgetary funds of university campuses in the Russian Federation.
Metacognitive Competencies as Determinants of Competitiveness of a Teacher’s Personality

The paper analyzes the issues of determining the competitiveness of a person (on the example of teachers) by formed metacognitive competencies. In modern scientific discourse, this issue is revealed, firstly, in the context of determining the leading factors and mechanisms for training competitive specialists in the higher education system, and secondly, from the point of view of ensuring the formation of attitudes and sustainable abilities for continuous self-development and self-improvement among students of all levels of education. . An integrated consideration of the two named aspects will allow designing the educational process with a guarantee of the formation of the actual and the creation of a basis for the prospective competitiveness of the individual. The aim of the study was to substantiate the complex of metacognitive competencies as factors in the competitiveness of the individual. Its achievement is ensured by the use of theoretical (analysis, generalization, systematization and concretization of scientific data) and practical (questionnaires, peer review) methods, which together made it possible to determine the presence and nature of the relationship between competitive qualities and metacognitive competencies of the individual. The research of modern scientists in the field of competitiveness has led to the determination of the structure and content of this personal characteristic, including social and professional character qualities (moral, communicative, organizational, constructive, etc.), competence properties (knowledge and skills, characteristics of thinking, experience), motivational - value phenomena (socially and professionally oriented motives and interests, goals and values, attitudes, etc.). Works in the field of goals and set educational outcomes led to the understanding of metacognitive competencies as the basis for achieving these results, led to the fixation of their structural composition (metacognitive knowledge, metacognitive strategies, metacognitive thinking), and made it possible to identify the most generalized content composition. The integration of the two groups of data made it possible to put forward an assumption about the interconnectedness of the two groups of qualities, which was proved empirically.
Analisis DistilBERT dengan Support Vector Machine (SVM) untuk Klasifikasi Ujaran Kebencian pada Sosial Media Twitter

Hate speech is a significant issue in content management on social media platforms. Effective classification of hate speech plays a crucial role in maintaining a safe social media environment, combating discrimination, and protecting users. This study evaluates a hate speech classification model using SVM with linear and polynomial kernels. The dataset used consists of labeled Indonesian-language tweets. The importance of developing an effective classification model to address hate speech has led to the utilization of DistilBERT as a feature extraction method. However, DistilBERT has high-dimensional features, necessitating dimensionality reduction to reduce model complexity. Therefore, in this study, the PCA dimensionality reduction method is implemented with various scenarios of dimensionality, namely 10, 20, 30, 40, and 50. Evaluation is performed using F1-Score, and the entire study is evaluated using 10-fold cross-validation. The evaluation results indicate that in the scenario with a linear kernel, the model achieves the highest F1-Score of 0.75 in the 50-dimensional scenario. Meanwhile, in the scenario with a polynomial kernel, the model achieves the highest F1-Score of 0.7857 in the 50-dimensional scenario. These findings demonstrate that the use of a polynomial kernel with 50 dimensions yields the best performance in classifying hate speech.