Reviewerly/exHarmony huggingface dataset:
Online estimation methods for irregular autoregressive models

In the last decades, due to the huge technological growth observed, it has become increasingly common that a collection of temporal data rapidly accumulates in vast amounts. This provides an opportunity for extracting valuable information through the estimation of increasingly precise models. But at the same time it imposes the challenge of continuously updating the models as new data become available. Currently available methods for addressing this problem, the so-called online learning methods, use current parameter estimations and novel data to update the estimators. These approaches avoid using the full raw data and speeding up the computations. In this work we consider three online learning algorithms for parameters estimation in the context of time series models. In particular, the methods implemented are: gradient descent, Newton-step and Kalman filter recursions. These algorithms are applied to the recently developed irregularly observed autoregressive (iAR) model. The estimation accuracy of the proposed methods is assessed by means of Monte Carlo experiments. The results obtained show that the proposed online estimation methods allow for a precise estimation of the parameters that generate the data both for the regularly and irregularly observed time series. These online approaches are numerically efficient, allowing substantial computational time savings. Moreover, we show that the proposed methods are able to adapt the parameter estimates quickly when the time series behavior changes, unlike batch estimation methods.
Centralization potential of automotive E/E architectures

Current automotive E/E architectures are subject to big changes: Computing-power-intensive advanced driver-assistance systems, bandwidth-hungry infotainment systems, the connection of the vehicle with the internet and the consequential need for cyber-security drives the centralization of E/E architectures. A centralized architecture is often seen as a key enabler to master those challenges. Available research focuses mostly on the different types of E/E architectures and contrasts their advantages and disadvantages. There is a research gap on guidelines for system designers and function developers to analyze the potential of their systems for centralization. The present paper aims to make centralization potential quantifiable. To achieve this, we conducted a literature review and qualitative interviews with practitioners. From literature, we have identified seven automotive system properties reaching limitations in current automotive architectures: busload, functional safety, computing power, feature dependencies, development and maintenance costs, error rate, modularity and flexibility. The system properties are interpreted as quantitative evaluation criteria for an estimation whether centralization brings a benefit for the overall system performance. In the interviews, we have validated centralization and its fundament - the conceptual systems engineering - as capabilities to diminish the limitations. Based on this research, system designers can optimize their systems to face the previously mentioned challenges and avoid the evolution towards a monolithic architecture.
New Encryption Algorithm with Improved Security

The design of new cryptographic algorithms, as a rule, has the main goal of improving their resistance to cryptanalysis methods. Since cryptanalysis methods are constantly being improved, when designing crypto algorithms, it becomes necessary to create new non-standard approaches that can effectively resist the existing cryptanalysis methods. This paper describes in detail a new crypto algorithm created using an original technique aimed at radically improving cryptographic strength. The paper provides both brief theoretical justifications and a complete technical description of the crypto algorithm.
Cryptocurrency Crime

As cryptocurrencies have gained popularity since the creation of Bitcoin in 2008, so too has crime involving them risen. In 2021, victims lost approximately $14 billion to cryptocurrency crime, an increase of 79% from the previous year (Chainalysis® 2022). This figure includes many, but not all, of the types of crime we discuss in detail in this chapter. Research from 2018 estimated that, at the time, 46% of all Bitcoin transactions involved illicit activity—attributed to 26% of all its users at the time—totaling $76 billion per year (Foley et al. 2019). Many of the crimes contributing to more recent figures also involve newer segments of the wider cryptocurrency space, such as decentralized finance (DeFi) and non-fungible tokens (NFTs).
DEVELOPMENT OF LEADERSHIP QUALITIES OF YOUTH IN AN INNOVATIVE SOCIETY

In this article, the necessity, opportunities, and possibilities of developing the leadership qualities of young people in the innovative society, the socio-psychological importance of engaging young people in leadership activities in the conditions of globalization, suggestions and recommendations regarding the development of this quality in young people are described.
Human-Computer Interaction (HCI) Interventions for People with Disabilities

Access to computer technology is of vital importance to people with disabilities, Human behaviour inference through smart pervasive technologies is a new research avenue. Sophistication in interaction modalities with self-customization based on context makes interaction easier in natural settings. Despite greater sophistication, the disabled and elderly people still face difficulties in interacting with smart devices. Articles published in Science Direct between 2015 and 2019 (July) were screened in this research. This is because of its respectable position in the field of technology and the peer-reviewed secured structure of this database. From a total of 75 articles within the scope of the screening 50 articles were included in the study. Through this research, Human-Computer Interaction (HCI) Interventions for People with Disabilities, and learning activities in recent years will be determined and a new way will be shown to researchers. "Human-computer interaction for disabilities people" keywords were used during the research process and all the articles with "disabilities" keywords were included in this study. The results revealed that most studies in the field of human-computer interaction for disabled people were published in 2017 in Spain. It emerged that experimental research was used maximum as a research model. Quantitative data collection tools were used mostly as a means of data collection. The results shown that the intellectual was selected as the type of disabilities in these articles. It is seen that augmented reality based on 3D hologram is the used technology.
Toward fixed point and pulsation quantum search on graphs driven by quantum walks with in- and out-flows: a trial to the complete graph

We treat a quantum walk model with in- and out-flows at every time step from the outside. We show that this quantum walk can find the marked vertex of the complete graph with a high probability in the stationary state. In exchange of the stability, the convergence time is estimated by $$O(N\log N)$$ , where N is the number of vertices. However, until the time step O(N), we show that there is a pulsation with the periodicity $$O(\sqrt{N})$$ . We find the marked vertex with a high relative probability in this pulsation phase. This means that we have two chances to find the marked vertex with a high relative probability; the first chance visits in the pulsation phase at short time step $$O(\sqrt{N})$$ , while the second chance visits in the stable phase after long time step $$O(N\log N)$$ . The proofs are based on Kato’s perturbation theory.
YouTube Clone by Using Ethereum Block Chain

Decentralized video sharing structures are much like video sharing structures wherein creators post content material and customers view it. However, the primary distinction lies withinside the community in the back of the decentralized video sharing platform. A peer-to-peer (P2P) community of decentralized video sharing structures helps the steady switch of files. To make sure speedy facts switch, facts is break up into smaller blocks for less complicated switch and download, making sure quicker downloads and browsing. The decentralized video sharing platform transfers facts over a P2P community, however with an extra layer of blockchain era encryption. Less operational value, higher fault tolerance, much less consider necessities among garage carriers and facts owners, and much less vulnerability to attacks. An occasion in blockchain era has delivered a decentralized garage mode to the public. Video transcoding is extensively carried out in video streaming commerce, changing films into a couple of codecs for extraordinary audiences.
Prediction of Unemployment In India Using Fb Prophet

The unemployment rate is a key indicator of economic performance and financial market risk. The main causes of unemployment in India are Large population, lack of professional qualifications, or poorly educated workforce. Labor-intensive sectors have suffered from a slowdown in private investment, especially after the banknote withdrawal. The Covid surge has made unemployment one of the biggest problems in India. The purpose of this project is to predict the future unemployment rate in India using the FB Prophet model. This model is used to predict the future values and developed by Facebook. There are many predictive model in unemployment using LSTM and ARIMA model but the values are not much precise, so we proposed the FB Prophet model for predicting the precise value. We can get a precise with the help of FB Prophet Model. The values are predicted using the FB prophet model and the predicted values are displayed in the form of graph.
Intelligent Blockchain-Based Secure Framework for Transaction in Mobile Electronic Payment System

The rate of smartphone purchases is rising daily, and mobile payments are now frequently accepted in various areas. It is essential to transfer money completely safe as well as quick. The encrypted distributed ledgers function provides verified real-time transaction confirmation without the necessity for intermediaries like banks and clearinghouses; blockchain provide quick, secure, decentralized, and inexpensive transaction services. Blockchain technology makes money transfer simpler with transparency and financial data security. Through these capabilities, blockchain has attracted interest from around the world. However, some challenges arise while completing some financial security needs. This work proposes a framework for secure mobile payments based on blockchain technology. The advantages of blockchain are discussed and how blockchain technology provides multi-level authentication to secure mobile based financial transactions. Due to the increased safety and confidentiality of users on mobile payment apps, the suggested system takes into account the need of developing a safe application for the mobile transactions. We have also addressed the security related challenges of blockchain based payment applications and provided potential solutions.
Research on the evaluation method of communication ability in business english teaching

According to the evaluation characteristics of business English language communication ability, a fuzzy principal component classification evaluation method for the elderly language communication ability is proposed. The main component analysis method is used to calculate the weight of each evaluation index, and the fuzzy comprehensive evaluation method is used to classify the comprehensive grade of language communication ability. The reliability of the evaluation method proposed in this paper is verified by using index data.
Enhance Mobile Phone Digital Camera Images Using Band Reject Filter and Discrete Fourier Transform

These days, We know that mobile phones with camera are very common to used by most of the people because of their ease of use and carry . So I figured I need for mobile phone images processing. These images are often subjected to a variety of types of distortion, such as noise, poor illumination, and blur due to transmission , image acquisition and mobile movement during capturing scene. This Degradation leads to produce distorted images are not suitable for viewing or application. To overcome this degradation, this paper presents image improvement in mobile phone by distortion removal using Band Reject Filter and DFT to obtain on the best clear image. Periodic noise is sinusoidal of several of certain frequencies and periodic in nature. It looks identical to the bars that the image is covered. The proposed method is subjected to eliminate this noise from a set of images using Band Reject Filter using discrete Fourier transform that attenuate and replace a number of degradation bands. Then, computes the peak signal to noise ratio metric for each band. After that, select the largest value of each band for the purpose the making one clear image. Finally, the bands that carry value large are merged to produce a one image. The final image is converted to the spatial domain using an inverse Fourier transform. The experimental outcomes indicate that the proposed method improves the degraded image by a greater percentage without using the better value for metric and makes image more clear and informative compare with the input image.
Investigating the Validity and Reliability of a Comprehensive Essay Evaluation Model of Integrating Manual Feedback and Intelligent Assistance

How to respond effectively and efficiently to students’ writing and to maximize the potential of feedback to promote student writing skills deserves careful consideration. The use of intelligent algorithms to assist teachers in the manual evaluation of students’ essays is of practical value and importance in the context of "artificial intelligence + education". The existing intelligent evaluation techniques are subject to the interference of many factors such as openness of questions and students' language expression abilities. For this reason, this study conducts a study on comprehensive essay evaluation method with intelligent assistance and manual feedback and on reliability and validity tests. Before the intelligent evaluation, the semantic integrity of students' essays is analyzed, and a semantic integrity analysis model of students' essays based on BERT model is constructed. A fusion similarity algorithm for essay answer key points is proposed by extracting these characteristics that have an impact on the evaluation results, such as technique preferences, paragraph content and paragraph topic of the essays. The Siamese and ESIM networks are combined to propose an intelligent evaluation model for students’ essays, and the model framework and working principle are described in detail. The experimental results verify the effectiveness of the constructed model.
Development of a Web Application for Learning Basic Mandarin Chinese

The College of Information and Communications Technology of Bulacan State University offers Mandarin Chinese as a foreign language course in one of its programs. The main objective of this study is to develop a web application that focuses on giving Mandarin Chinese dictionaries, lessons, assessments, and tests. Upon the development of the web application, topics under basic Mandarin Chinese, covering Hànyǔ Shuǐpíng Kǎoshì (HSK) Levels 1 and 2, are considered as its contents since they contain essential topics for learning Mandarin Chinese. The web application for basic Mandarin Chinese was evaluated by its intended end-users and technical experts in web application development using the standard software quality evaluation criteria based on ISO/IEC 25010. The acceptability ratings of intended end-users and technical experts are 4.56 and 4.58, respectively, with a descriptive interpretation of Extremely Acceptable. These ratings show that the Mandarin Chinese language web application was developed well, with appropriate functionalities, features, and content. Upon its implementation, this Mandarin Chinese language web application may be used as an additional tool in teaching and learning Mandarin Chinese.
Teaching Quality Evaluation of Engineering Cost Courses Based on Fuzzy Analytic Hierarchy Process

The prosperous economic development and the investment and construction of several construction projects have substantially promoted the demands for talents in the engineering cost specialty. Nowadays the engineering cost specialty programs in many universities are faced with the strong applicability problem of specialized courses, and the teaching design for such specialized courses fails to meet the demands of the construction industry that enjoys high-speed development. A novel method to accurately evaluate the professional courses on the basis of the fuzzy analytic hierarchy process (FAHP) was proposed in this study. The weights of course evaluation indexes were determined by the FAHP, thus realizing the quantitative evaluation of course teaching quality. This study combined the teaching reform practice in analyzing the special characteristics of the engineering cost course. Based on the theory of outcomes-based education and multiple evaluation approaches, it established a closed-loop model for the progressive development of teaching management and expounded the evolutionary process and driving pattern of course teaching evaluation. Results demonstrate that an evaluation index system consisting of 22 evaluation indexes in 5 dimensions is suitable for the course, the teaching quality ratings can be quantified by this method, such as 81.43 points, and they can provide a certain reference for the course construction and teaching quality evaluation of this specialty. The proposed method provides a good prospect to optimize the teaching quality evaluation in the professional curriculums.
Learning in Online Environment

The study emphasizes personality development, the development of students' emotional intelligence, the facilitation of learning (the creation of an atmosphere that stimulates learning), when it seeks the answer to "how, when why a student learns and how learning looks and feels from the inside". Research conducted among the students at the Milton Friedman University will be presented, regarding how they think about motivation, how their personality traits influence their learning activities, what their learning strategy is and based on all this, how they evaluate the methodological base of teaching tools that support their learning
The Effect of RPG Maker Mobile Learning Model in Learning English

The aimed of this research was to measure the effect of application (RPG) MakerMV. This research belongs to experimental research and quasi experimental design. It described about the effect of using of the application. The research methodology was a quantitative method. The population of this study was one Class XI students from MA Siti Khadijah, and the sample was twenty students or two classes throughpurposive sampling. The research result showed that this application were very effective and very easy to use.The researcher concluded that the experimental group through this application in the right way. The average percentage of student activity is 75.6%, which is included in both categories.The experimental group had higher score (429) after learning English vocabulary using direct method than control group (274). The conclusions of this study was RPG Maker mobile effective in the teaching learning English. This study recommended to use this aplication in teaching english. The application help students to follow the lesson
Visual Analysis of the Hotspots and Frontier of Research on Boarding Students in China by Using CiteSpace—Based on the Chinese Social Studies Citation Index Database (2010-2022)

This study aimed to explore the current status and hotspots of research on Chinese boarding students.Literature on research studies studying Chinese boarding students from January 1, 2010, to December 30, 2022, was retrieved from the China National Knowledge Infrastructure Database (CNKI).CiteSpace 6.1.R6 software was used to visualize and analyze authors, institutions, and keywords.In total, 416 papers were included.The results found that (1) research about boarding students in China has shown a steady increase over a decade, but has shown a fluctuating downward trend since 2016.(2) In the process of researching boarding students, a more central network of research institutions has formed, comprising a complex collaborative network centered on the Institute of Nutrition and Food Safety of the Chinese Center for Disease Control and Prevention, as well as key figures such as Sun Jing, Pu Wei, and Ma Guansheng.(3) From multiple dimensions of keywords, clustering, and mutation, rural boarding students from elementary school to high school are a group that has received high attention; education and physical health status issues, mental health, and school adjustment have been research hotspots from the time the group was established to the present.(4) The frontiers of research on boarding students are focused on school adjustment, cognitive skills, peer relationships, psychological capital, and physical activity.
Sosialisasi dan Pelatihan Penggunaan Aplikasi SIDOKAR Bagi Kelompok Kerja Dalam Mempersiapkan Akreditasi Rumah Sakit Umum Puri Raharja Denpasar

Hospital accreditation is critical to improving healthcare quality, reducing patient harm, protecting patients, communities, and human resources, and promoting government health initiatives. One of the problems encountered during accreditation was when the surveyor conducted a document audit. The team needed help showing the documents because they needed to be structured appropriately. The large number of documents in the form of hardcopy allows the document to be damaged or lost. The holding of training and socialization of SIDOKAR application-based technology can solve this problem which is expected to help organize and search documents quickly. The methods used in this activity are lectures and mentoring. The conclusion from this activity was that the activity was successfully realized by monitoring how well each working group was prepared to welcome the accreditation survey. In addition, the implementation of socialization and training also shows that the application can assist the working group in increasing the efficiency, effectiveness, and quality of the accreditation preparation process.
Elucidating multifinal and equifinal pathways to developmental disorders by constructing real-world neurorobotic models

Vigorous research has been performed to accumulate biological and theoretical knowledge about neurodevelopmental disorders, including molecular, neural, computational, and behavioral characteristics, but these findings remain fragmentary and do not elucidate integrated mechanisms. An obstacle is the heterogeneity of developmental pathways causing clinical phenotypes. Additionally, in symptom formations, the primary causes and consequences of developmental learning processes are often indistinguishable. Here, we introduce a developmental neurorobotics approach for overcoming problems due to the dynamic, complex properties of neurodevelopmental disorders. Specifically, by constructing neurorobotic models with predictive processing mechanisms of learning, perception, and action, we can simulate formations of integrated causal relationships among neural, computational, and behavioral characteristics while considering developmental learning processes. This framework enables binding neurobiological hypotheses (excitation-inhibition imbalance, functional disconnection), computational accounts (unusual encoding of uncertainty), and clinical symptoms. Developmental neurorobotics approaches may serve as a complementary research framework for integrating fragmented knowledge and overcoming the heterogeneity of neurodevelopmental disorders.