Reviewerly/exHarmony huggingface dataset:
Cryptocurrencies and Examples of Application

In this research paper, I aimed to answer the research question, which is "In what way will the emergence of cryptocurrencies affect the change of the conventional banking and financial system in general?" and to test the truth of the following hypothesis "Cryptocurrencies will make the financial system fairer and more efficient". In fulfilling the objectives of this research paper, I started by explaining the concept of cryptocurrency. It is almost impossible to explain the concept of cryptocurrencies without explaining their history and the ideas from which they were realized. In order to be able to answer the research question, I defined the "opponents" of cryptocurrencies in this research, and those opponents are banks and the entire financial system. In explaining the impact that cryptocurrencies have on banks and the financial system, I started by explaining the impact of cryptocurrencies on New Zealand's banking system. I continued by explaining the advantages of the credit system of "peer-to-peer" platforms compared to the credit system in the banking sector. I mentioned the possibility of including cryptocurrencies in the state's financial system and explained how this would affect the discretionary rights of the state and its institutions. The logical continuation of the research was national cryptocurrencies and their influence, which would not deny the state's discretionary rights. The discretionary rights of the Central Bank gave me the opportunity to analyze the risks of using cryptocurrencies at the state level, where perhaps the biggest risk, the risk of deflation, stood out. Against this risk, he mentioned the expansion of finance in the economy by means of the "crow-funding" system, which is characteristic of a country where the monetary system is based on cryptocurrencies. In my work, I did not even set the fiscal system, which is an integral part of the general financial system. The research also includes the impact of cryptocurrencies on El Salvador, as the only country that has implemented cryptocurrencies or Bitcoin in the monetary system, and only those quantitative data are relevant. I rejected the hypothesis in the short term, while accepting it as correct in the long term. In the conclusion, I quoted a sentence from a New Zealand Federal Reserve document, as a sentence that contains the essence of the paper.
Pengembangan Media Video Tutorial Pembuatan Macam-Macam Kampuh pada Mata Pelajaran Teknologi Menjahit Kelas X Tata Busana SMK Negeri 3 Kediri

This study is a development research to determine the level of feasibility by experts, namely material experts, media experts and linguists as well as to find out student responses to the video tutorial media for Making Various Kinds of Kampuh in the Class X Fashion Subject at SMK Negeri 3 Kediri. The research was developed using 4D model, namely define, design, develop and disseminate. The data collection method uses a media feasibility assessment questionnaire by Material Experts, Media Experts and Language Experts as well as student response questionnaires. The data analysis technique uses descriptive analysis techniques to process data from the validation results of media feasibility and student response data.The results of research and development of video tutorials for making various kinds of kampuh show the following results, (1) The feasibility level of the media by the Material Expert with an average score of 3.31 which is declared Very Feasible to be tested. The level of eligibility of the media by Media Experts with an average score of 3.73 which was declared Very Feasible to be tested. The feasibility level of the media by linguists with an average score of 3.50 which was declared Very Feasible to be tested. (2) The results of student responses in a small-scale trial with 6 people obtaining a score percentage of 89% are included in the Very Good category. While the results of student responses in the large-scale trial of 31 people obtained a score percentage of 92% included in the Very Good category.
Designing English Listening Materials for the 12th Grade Students of Paket C

This research was carried out to design English listening materials for the 12th-grade students of Paket C. What are the English listening material learning needs of Paket C students in the 12th grade? It was one of the two research questions that guided the study. How were the English listening materials for Paket C students in the 12th grade designed? Built on design This investigation was carried out using research. To gather data regarding the students' listening demands in EFL teaching, semi-structured interviews and open-ended questionnaires were used. Validations by media and material experts were also carried out. According to the results of the data analysis, Paket C pupils need English listening resources first. Second, the audio media was created using a bottom-up methodology while going through iterative design phases, including problem-solving analysis, media development, testing, and reflection. The tutor's book, the students' book, and the MP3 listening materials were the three products of the design procedures. In conclusion, the 12th-grade students of Paket C need English listening materials related to their activity/background/profession, future/material usefulness, educational background, surrounding environment, and life skill. All of the students need to aim to design English listening materials for the 12th-grade students of Paket C.
Keefektifan Pelatihan Pembuatan Worksheet Interaktif dengan Wizer.Me untuk Mengoptimalkan Pembelajaran di SDN 26 Mataram

This study aims to determine the effectiveness of training in making interactive worksheets with Wizer. me on the ability and knowledge of SDN 26 Mataram teachers in making interactive worksheets. This research is quantitative research with a pre-experimental design type one group pretest-posttest. This research includes population research because all 12 teachers are the research subjects. The instrument used was 10 multiple choice questions which were used as pretest and posttest questions. The data analysis technique used a normality test as a prerequisite for analysis, paired sample t-test, an effect size test, and an N-Gain test. All data are normally distributed as indicated by the normality test. The paired sample t-test test shows that there is a difference between the pretest and posttest values ​​where the posttest value is higher than the pretest value. The average value of the N-Gain score is 45.6944 or 46% (less effective). The minimum N-gain score is 0 and the maximum is 83.33%. The conclusion is that training on making interactive worksheets with Wizer. me is less effective in improving the skills and knowledge of SDN 26 teachers in making interactive worksheets.
Generation of random directions from the generalized von Mises–Fisher distribution

We introduce two algorithms for generating from the bimodal generalized von Mises-Fisher distribution on the sphere. This generalization of the von Mises-Fisher distribution is more flexible, in particular by allowing for multimodality, and it preserves many of the theoretical properties of the von Mises-Fisher. The first proposed generation algorithm is obtained from conditional simulation and acceptance-rejection. The second one is the Metropolis-Hastings with mixture of von Mises-Fisher as jumping or instrumental distribution. These two algorithms are compared through density estimations of generated polar angles.
Research on the value orientations of students using information and communication technologies

The current study is an attempt to compare online and offline results of research on students’ value orientations. The main scientific methods and approaches used in the current research are comparative analysis, online and offline comparison and statistical rank correlation. We defined the questionnaire’s content, formed its text and chose homogeneous representative groups. Results obtained both with classical (paper) technology and with information and communication technologies (ICT) are compared. The terminal and instrumental sets of values proposed by Milton Rokeach are compared. Based on the processed data, we draw conclusion about the reliability (validity) of online survey results. ICT is very helpful in conducting scientific research faster with fewer professionals involved but its time-consuming and requires numerous activities. Recommendations are given on the feasibility of using ICT in modern methods of sociological research. Work on the creation of modern research platforms, programs and algorithms that would ensure obtaining valid and informative results is prominent among the aspects of further scientific research.
Book Review

Journal Article Book Review Get access The Triumph of Uncertainty. Science and Self in the Postmodern Age. By Alfred I. Tauber. (Budapest: Central European University Press, 2022. Pp. xviii + 404. Price £68.00.) Bartlomiej Swiatczak Bartlomiej Swiatczak University of Science and Technology of China, China Search for other works by this author on: Oxford Academic Google Scholar The Philosophical Quarterly, Volume 73, Issue 3, July 2023, Pages 915–918, https://doi.org/10.1093/pq/pqad042 Published: 08 April 2023
A Hybrid Pelican Optimization Algorithm and Black Hole Algorithm for Kernel Semi-Parametric Fusion Modeling

This paper investigates the process of selecting a hyperparameter for use in a kernel semiparametric regression model for fusion data, which is an important tool in various scientific study fields. The selection of the best model to use in advance is not a simple task, and one of the most fascinating current advances in the application is the use of hybrid metaheuristics algorithms to increase the exploration and exploitation capacity of traditional meta-heuristic algorithms. In this study, a hybrid optimization method that combines the pelican algorithm with the black hole algorithm is presented, which achieves a lower mean squared error (MSE) in comparison to other competing techniques. Data merging through the suggested hybrid metaheuristics algorithm gives superior performance in terms of computing time when compared to both the CV-method and the GCV-method. This work has practical implications for researchers and practitioners who use statistical modeling techniques in their work, especially those dealing with data merging for improved accuracy and efficiency.
Hardware Security Analysis

Hardware is the backbone of all computing resources, and its security is of great importance. Compared with software vulnerabilities, hardware vulnerabilities are much harder to deal with because hardware cannot be patched easily as software. Thus, hardware developers heavily rely on hardware verification to find vulnerabilities in the prototype before the official release. In fact, in the hardware design cycle, hardware verification can take 60–75% of the time, and computing and human resources.
Concluding Remarks

Cybersecurity is today more critical than ever, given our society’s increasing reliance on cyber infrastructures and data. ML, which during the past 15 years has grown in sophistication, performance, and application scope, represents an important technology for enhancing cybersecurity.
FINANCING MODELS FOR HIGHER EDUCATIONAL INSTITUTIONS

Nowadays, one of the most pressing issues across the world is the efficient use of budgetary funds, ensuring their targeted spending, optimizing public expenditure and attracting private investment into national economies. This article provides a comparative analysis of studies by various local and foreign scientists on the essence of financing models for higher educational institutions in the republic, their specifics, and a mechanism for effective financing of the education system. As well as, it presents proposals and recommendations on procedures for financing higher education institutions in the country and expanding extrabudgetary financing of the higher education system.
The Role of Data Leakage Prevention System in CBDC

centralized database-based Central Bank Digital Currency (CBDC) system's vulnerability to cyberattacks and data leakage is a major concern. Any data leak can lead to large financial losses, irreversible reputational harm, and a decline in user confidence. To protect user information, the Reserve Bank of India has underlined the significance of a strong Data Leakage Prevention (DLP) system. While current incidents have demonstrated that the measures were insufficient to meet the standards, DLP may not be enough to defend CBDCs on its own. Incorporating Zero-Knowledge Proofs (ZKPs) and differential privacy tools into DLP solutions can improve their robustness and effectiveness. There is no one-size-fits-all solution for preventing data leakage, different solutions may be more effective in different scenarios. It's always a good idea to assess an organization's or system's specific needs and requirements before deciding on the best solution. It is also important to remember that there is no such thing as absolute security, and the possibility of zero-day attacks is always there. It is essential to continuously monitor and enhance security measures to stay ahead of new threats. To preserve their Central Bank Digital Currency systems and data, financial institutions and central banks must continue to be proactive and vigilant.
Application of Nonlinear Prediction and Linearization MPC in Path Planning

Nonlinear programming is an important research direction in the field of mathematics and engineering technology. It is widely used in economic management, system analysis and so on. In this paper, the nonlinear programming problem and the linearization MPC along the trajectory are introduced and simulated. Firstly, according to the optimal control principle, a prediction-based algorithm is proposed. Secondly, the optimal path is adjusted to meet the expected value, and then the parameters are transformed into unbiased least square factors to achieve the objective function of global optimization. Finally, the most reasonable and feasible scheme is obtained through MATLAB software simulation. The simulation results show the data comparison of three connection methods: minimum spanning tree, visual experiment and nonlinear prediction algorithm. The nonlinear shortest path is about 4.87% shorter than the minimum spanning tree length of the fixed point, and the performance of linearized MPC along the trajectory is excellent in path planning.
Improved Human-Object Interaction Detection Based on YOLO v5

For the problem of not achieving real-time detection in person interaction detection, propose a network model based on the improved YOLO v5 as the target feature recognition part. Based on the above problems, YOLO v5 is used as the network model for the feature extraction part and PPDM as the model for the character interaction detection part. The results show that the PPDM incorporating YOLO v5 improves the detection accuracy and speed to 58 FPS compared to the previous model, and that the improved YOLO v5-based character interaction detection is able to perform real-time detection at a higher frame rate and can meet the speed required for detection.
http://online-cig.ase.ro/jcig/DetNo.aspx?noL=Vol.%2022,%20No.%201/2023

Research Question: This study explores the impact of task interruptions on audit quality in Tunisia. Our research aimed to find out how Tunisian auditors felt about task interruptions and how they affected the quality of their assessment. Motivation: Our research question aims to clarify the perception of Tunisian auditors about interruptions and their impact on their judgments. This research highlights the position of Tunisian auditors on task interruptions and their impact on their quality of judgment. Idea: Its goal is to present several solutions for the auditors by creating a system where the bad interruptions are blocked to limit their impacts. Data: A triangulated study design was incorporated. Experimental and qualitative methods were used. Tools: We choose experimentation as a method of data collection to undertake hypothesis testing causal relationships. Findings: The results revealed that the interruptions of tasks do not affect the quality of judgment of the auditors in the Tunisian context. Furthermore, just the gender and length of work experience were included when evaluating the influence of various conditions. Contribution: Thus, this paper contributes to Tunisian audit research. Indeed, this study examines auditors' perceptions of task interruptions and their impact on their judgment quality. In addition, to attain the research's goal, this study relies on an experimental investigation and a qualitative confirmatory survey.
Challenges in the Use of ML for Security

This chapter discusses major challenges in the use of ML for security, which are very much the same as in other domains. The chapter covers issues related to training datasets, such as scarcity of training data, and dataset quality. It also covers ethics issues and discusses several key dimensions of ethics, namely explainability, fairness, robustness, transparency, and privacy. The chapter then concludes with a discussion about ML security. Because many such topics are being extensively investigated, the chapter also provides pointers to surveys and tutorial papers, where the reader can find technical details, classifications of proposed approaches, and further references.
Attack Management

Even well-secured systems can be breached. There are several reasons for this, including the complexity and dynamic nature of today’s systems, insider threats, zero-day vulnerabilities, and human errors. Therefore, as we have discussed in Chap. 6 , monitoring and anomaly detection activities are critical. However, one important task in the security life cycle is to take proper actions, based on the results of those activities. The goals of those actions include mitigating, containing, and recovering from the attack, while at the same time trying to maintain the system operational as much as possible. In this respect, it is important to mention that resilience to attacks is today increasingly critical as many systems have stringent continuity requirements.
Design of Composite Structure Optimization Model Based on Particle Swarm Optimization

As an optimization method, particle swarm optimization is developed on the basis of TSP problem. Therefore, it has certain advantages to apply it to the structural optimization design of composite materials of ships. Therefore, this paper conducts related investigation and research on particle swarm optimization and composite material structure optimization. This paper mainly uses the experimental method and the comparative method to conduct in-depth research on the optimization of the ship composite material structure. The experimental data show that, compared with the accurate results of finite element calculation, the support vector machine model has quite high calculation accuracy, and the errors of constraints and objective functions are both less than 0.5%.
Quantum-holistic categories of social communications

Today, among specialists in social communications there is a lack of knowledge about the quantum-holistic categories of social communications, both the process of social and the process of social activity. The aim of our study was to identify and describe quantum-holistic categories of social communication processes. Through our study, we have chosen a transformed methodology of holism, which argues that the integrity of the world is a consequence of creative evolution. Such evolution is guided by the intangible and unknowable «integrity factor» (in Jan Smuts's terminology). The transformation of the ideas of holism is based on the basic principles of quantum mechanics, which we have adapted to the social sciences. We also used in the study methods of analysis and synthesis, deduction and induction, and the method of classification. The research methodology determined the differentiation of quantum-holistic categories of social communications into social and public; identification of three mandatory elements of the philosophy of knowledge of any subject of discussion, namely: identification, content, and functionality; analysis of known and little-known concepts of classification of philosophical categories in order to identify features that are consistent with our methodological conceptual concept of quantum-holistic categories of social communication processes; on the basis of the carried out analysis of isolation and nomination of ontological (metaphysical) and epistemological (epistemological) descriptive categories of processes o f social communications. In conclusion, the author argues that the identification of quantum-holistic categories of social communication processes should be carried out both from a social and social point of view. The author proposes to consider as descriptive quantum-holistic categories of social communication processes «quantum (portion of energy)», «Whole», «Information», «living / inanimate», «action / peace», «society / non-society». Keywords: social communications, philosophy of communication, categories, quantum, holism.
A robust two-step adversarial debiasing with partial learning: medical image case-studies

The use of artificial intelligence (AI) in healthcare has become a very active research area in the last few years. While significant progress has been made in image classification tasks, only a few AI methods are actually deployed in clinical settings. A major hurdle in actively using clinical AI models is the trustworthiness of these models. Often, these complex models are utilized as black boxes in which promising results are generated. However, when scrutinized, these models reveal implicit biases during decision-making, such as having an unintended bias towards particular ethnic groups and sub-populations. In our study, we develop a two-step adversarial debiasing approach with partial learning that can reduce the disparity while preserving the performance of the targeted diagnosis/classification task. The methodology has been evaluated on two independent medical image case studies - chest X-rays and mammograms and showed promises in bias reduction while preserving the targeted performance on both internal and external datasets.
Triplet Loss-less Center Loss Sampling Strategies in Facial Expression Recognition Scenarios

Facial expressions convey massive information and play a crucial role in emotional expression. Deep neural network (DNN) accompanied by deep metric learning (DML) techniques boost the discriminative ability of the model in facial expression recognition (FER) applications. DNN, equipped with only classification loss functions such as Cross-Entropy cannot compact intra-class feature variation or separate inter-class feature distance as well as when it gets fortified by a DML supporting loss item. The triplet center loss (TCL) function is applied on all dimensions of the sample's embedding in the embedding space. In our work, we developed three strategies: fully-synthesized, semi-synthesized, and prediction-based negative sample selection strategies. To achieve better results, we introduce a selective attention module that provides a combination of pixel-wise and element-wise attention coefficients using high-semantic deep features of input samples. We evaluated the proposed method on the RAF-DB, a highly imbalanced dataset. The experimental results reveal significant improvements in comparison to the baseline for all three negative sample selection strategies.