Reviewerly/exHarmony huggingface dataset:
Analisa Data Kepuasaan Siswa Dalam Pembelajaran Online Menggunakan Metode Service Quality

The student's satisfaction in this covid-19 era is crucial to figuring out what level of quality services are available in school institutions. The study aims to find out the students' level of satisfaction with online study at SMK al - amanah, this study is a descriptive quantitative study with a population of 102. In this matter student satisfaction will be measured using a servqual and importance performance analysis method in this case where it talks about dimensions of waited, responsiveness, assurance, anticipation and tangibles. The instrument of this study is done with the interview manner and the dissemination of the questionnaire. The data of the collected questionnaires are calculated and prepared, and the quality of the service is specifically known. With the spread of the questionnaire, it can be seen the result of a student's dissatisfaction with the service given. Data prepared for servqual methods with the help of SPSS 24.0 and importance performance analysis. The results from the selected student satisfaction data can be used as an evaluation material for schools to improve online learning. The results of this study show every dimension on the servqual that is tangibles, valence, responsiveness, assurance, and emphaty. Indicating that the gap or responsive gap is the biggest quality value dimension of -0.72 and the smallest gap or gap there is in realibility of -0.22
MENINGKATKAN HASIL BELAJAR MATEMATIKA TENTANG SIFAT-SIFAT BANGUN RUANG MELALUI MODEL PEMBELAJARAN MAKE A MACHT PADA SISWA KELAS V SD NEGERI JEMBAYAT 06 SEMESTER 2 TAHUN PELAJARAN 2017/2018

The purpose of this research was to reveal that the application of the Make a macht learning model can improve student learning outcomes. This research uses the Classroom Action Research method. The collection of data uses tests and observations. Analysis of the data uses quantitative descriptors. Research location in Jembayat State Elementary School 06 Tegal Regency. The object of action in this research  is student learning outcomes. The research lasted for 4 months starting in February 2018 until May 2018. The research subjects were fifth grade students of SDN Jembayat 06 semester 2 of the year 2017/2018 as many as 29 people. The results of the research show that through the make a macht learning model can improve student learning outcomes. The average value of student learning outcomes in cycle 1 reached 71.4 and in cycle 2  reached 79.7 up by 8.3 points. Classical completeness of cycle 1 reached 76%, cycle 2 reached 100%, up by 24%. The researcher concluded that using the make a macht learning model can improve student learning outcomes.
Theoretical and Practical Training of Future Art Teachers in the Digital Environment

The paper deals with the conditions of higher education during the COVID-19 pandemic, which was realized in the digital environment due to the measures. The online training of future art teachers has brought many negative as well as positive changes. The paper contains an analysis and interpretation of students’ opinions of the Department of Creative Arts and Art Education, Faculty of Education, Constantine the Philosopher University in Nitra in connection with the process of online education in the academic year 2020/2021.
Determining Critical Factors Affecting NCD Patients Intention to Adopt IoT Based Healthcare Wearable Device (HWD) In Malaysia

With the advent of science and technology, the average life expectancy of the world's population has lengthened. This, coupled with sedentary lifestyles, is leading to an increase in the number of geriatric populations with chronic diseases (non-communicable diseases - NCDs). Malaysia is facing a real and serious threat from non-communicable diseases (NCDs) and their effects, resulting in economic losses due to low productivity and tremendous pressure on existing health services. To address this growing problem, the healthcare sector has moved into the era of health information technology (HIT) by using IOT-based wearable health devices for continuous patient monitoring without the need for regular hospital visits. However, studies have shown that trust has a significant impact on decision making when using e-health services. Our main objective is to identify the reason for the gradual adoption of this new technology by end users, which results in denying the healthcare industry the benefits that could otherwise be achieved through the adoption of IoT technology.Purpose -The purpose of this research is to identify the critical factor that may influence NCD patients' intention to adopt IoT-based wearable devices and to explore the behavioural intention to use IoT-based wearable devices among NCD patients by applying UTAUT theory with the addition of moderating variables.
THE CONTRIBUTION OF LEARNING MOTIVATION AND READING COMPREHENSION SKILL TOWARD WRITING BIOGRAPHY TEXT SKILL (KONTRIBUSI MOTIVASI BELAJAR DAN KETERAMPILAN MEMBACA PEMAHAMAN TERHADAP KETERAMPILAN MENULIS TEKS BIOGRAFI)

The purpose of this research was to describe some of the following. (1) The contribution of learning motivation of writing biography text of students. (2) The contribution of reading comprehension skill of writing biography text of students. (3) The contribution of learning motivation and reading comprehension skill together to writing biography text of students of class VIII Junior High School in Pesisir Selatan. This research was a quantitative research using correlational method. The population was class VIII students Junior High School of Pesisir Selatan Regency. The sample is 110 students. Techniques to data analysis using Pearson Product Moment Correlational test, multiple regression, t test, and F test. The results of the research are. 1) The learning motivation contribute significant by 20% to writing biography text. 2) The reading comprehension skill contribute significant by 37.5% to writing biography text. 3) The learning motivation and reading comprehension skill together contribute by 38% to the writing biography text. Based on the result of the research, can conclusion is learning motivation and reading comprehension skills together contribute and significant relationship to writing biography text skills.
Social Media Text Classification Method Based on Character-Word Feature Self-attention Learning

Long tail effect and excessive out-of-vocabulary(OOV)words in social media texts result in severe feature sparsity and reduce classification accuracy.To solve the problem,a social media text classification method based on character-word feature self-attention learning is proposed.Global features are constructed at the character level to learn attention weight distribution,and the existing multi-head attention mechanism is improved to reduce parameter scale and computational complexity.To further analyze character-word feature fusion,OOV sensitivity is proposed to measure the impact of OOV words on different types of features.Experiments on several social media text classification tasks indicate that the effectiveness and classification accuracy of the proposed method are obviously improved in terms of fusing word features and character features.Moreover,the quantitative results of OOV vocabulary sensitivity index verify the feasiblity and effectiveness of the proposed method.
The pragma-dialectical view of comparison argumentation

The pragma-dialectical typology of argument schemes consists of three main categories: symptomatic argumentation, comparison argumentation and causal argumentation. The subcategories and variants of these main categories have not yet been distinguished systematically. In this contribution the authors start doing so by distinguishing the most important subtypes and variants of comparison argumentation. They argue that two distinct subtypes of comparison argumentation need to be distinguished: descriptive comparison argumentation and normative comparison argumentation.
Hand Gesture Recognition Algorithm to Identify American Sign Language

Sign language is the most expressive and natural way which is used by hearing and visually impaired people for communication. These people use their hands for communicating with each other, which is not understandable to the normal person. And overall leads the isolation of these peoples from rest of the word. Also, different country has different languages for communication between normal as well as people who have severe hearing impairments. Therefore, the objective of this paper is filling the gap between normal and deaf people through design an algorithm to recognize the different characters of specifically American Sign Language by gesture recognition of the human hand. This proposed algorithm used the information based on the contours and convexity shortcomings to identify the American Sign Language alphabets and digits. The key aim of the proposal is to identify the 17 characters and 6 digits of the American Sign Language without support of any specialized hardware, or any other complex machine learning algorithms. Simulation results validate that, the proposal recognize the American Sign Language alphabets and digits with accuracy more than 85 percent with simple and less complex algorithm within a specified time limits. Keywords: Sign Language, American Sign Language, Gesture Recognition, OpenCv, Contours, Convexity.
Qualitative and Quantitative Evaluation of Encryption Algorithms

This paper presents the evaluation of various major encryption algorithms. The paper also discusses a mathematical method to assess the algorithms based on factors such as speed and memory usage of the algorithm that impact the efficiency of these algorithms. First, it discusses the factors that affect the efficiency, speed, and memory usage of the algorithm and then describes a relation between these factors in such a way that it is mathematically optimal and also computationally feasible. The current work also presents a general idea of how the internal components of the cipher affect the execution cycle and determine a relation between them. Evaluation results are discussed in detail and concluded that the Blowfish algorithm is performed best among all discussed algorithms.
Social-Interactive Sports Monitor for Children Using Augmentative and Alternative Communication

This article has been retracted.
Cloud Computing-Based Smart Healthcare System

Cloud computing is a very promising area for researchers as smart and cost-effective healthcare systems are demanded in this pandemic era. This book chapter focuses on a Cloud computing–based smart healthcare system using electroencephalogram (EEG) signals. The main objective of this work is to prepare a smart healthcare system so as to help separate sleep disorder subjects and normal subjects and alcoholic subjects and normal subjects based on fractal dimension calculation with minimum complexity and less time. The real-time EEG data can be uploaded on the hospital's Cloud. The Cloud-based healthcare system is trained with algorithms for finding various features that are given to the classifier automatically to detect whether the person is suffering from a sleep disorder, alcoholic disorder, or is normal. This work uses fractal dimensions as a measure of complex EEG signals that detect and interpret transients. The work reported here is based on Higuchi's Fractal Dimension (HFD) and Katz's Fractal Dimension (KFD) methods. Signals are treated in a time domain to find HFD and KFD. Work is carried out on various combinations of three different classes viz: the EEG signals of 21 sleep disorder subjects, 20 alcoholic subjects, and 20 normal subjects. HFD provides a true detection rate of 90% for both the combination of sleep disorder subjects and alcoholic subjects and for the combination of sleep disorder subjects and normal subjects, whereas the true detection rate achieved for the combination of alcoholic and normal subjects is 62%. This work reveals that the fractal dimension algorithm is a strong and effective method for detection of different brain pathologies.
On one-lee weight and two-lee weight $ \mathbb{Z}_2\mathbb{Z}_4[u] $ additive codes and their constructions

<p style='text-indent:20px;'>This paper mainly study <inline-formula><tex-math id="M2">\begin{document}$ \mathbb{Z}_{2}\mathbb{Z}_{4}[u] $\end{document}</tex-math></inline-formula>-additive codes. A Gray map from <inline-formula><tex-math id="M3">\begin{document}$ \mathbb{Z}_{2}^{\alpha}\times\mathbb{Z}_{4}^{\beta}[u] $\end{document}</tex-math></inline-formula> to <inline-formula><tex-math id="M4">\begin{document}$ \mathbb{Z}_{4}^{\alpha+2\beta} $\end{document}</tex-math></inline-formula> is defined, and we prove that is a weight preserving and distance preserving map. A MacWilliams-type identity between the Lee weight enumerator of a <inline-formula><tex-math id="M5">\begin{document}$ \mathbb{Z}_{2}\mathbb{Z}_{4}[u] $\end{document}</tex-math></inline-formula>-additive code and its dual is proved. Some properties of one-weight <inline-formula><tex-math id="M6">\begin{document}$ \mathbb{Z}_{2}\mathbb{Z}_{4}[u] $\end{document}</tex-math></inline-formula>-additive codes and two-weight projective <inline-formula><tex-math id="M7">\begin{document}$ \mathbb{Z}_{2}\mathbb{Z}_{4}[u] $\end{document}</tex-math></inline-formula>-additive codes are discussed. As main results, some construction methods for one-weight and two-weight <inline-formula><tex-math id="M8">\begin{document}$ \mathbb{Z}_{2}\mathbb{Z}_{4}[u] $\end{document}</tex-math></inline-formula>-additive codes are studied, meanwhile several examples are presented to illustrate the methods.
Bitcoin Trace-Net: Formal Contract Verification at Signing Time

Smart contracting protocols promise to regulate the transfer of cryptocurrency amongst participants in a trustless manner. A safe smart contract implementation should ensure that each participant can always append a contract transaction to the blockchain in order move the contract towards secure completion. To this goal, we propose Bitcoin Trace-Net, a contract verification framework which generates an executable symbolic model from the underlying contract implementation. A Trace-Net model consists of a Petri Net formalism enriched with a Dolev-Yao-like actor knowledge model. The explicit symbolic actor knowledge model supports the verification of contracts featuring cryptographic sub-protocols, which may not be observable on the blockchain. Trace-Net is sufficiently expressive to accurately model blockchain semantics such as the delay between a transaction broadcast and its subsequent confirmation, as well as adversarial blockchain reorganizations of finite depths, both of which can break smart contract safety. As an implementation-level framework, Trace-Net can be instantiated at run-time to monitor and verify smart contract protocol executions.Keywords: Bitcoin; smart contracts; symbolic analysis; model checking
Out-of-plane displacement measurement using laser parallel fringes generated in camera with diffraction grating

In this study, a diffraction grating was used for generating laser parallel fringes in a camera. Phase analysis method using those laser parallel fringes were used to measure out-of-plane displacement. A green laser of line projection function, a diffraction grating and an industrial camera were used as an experimental device. Object images with laser parallel fringes projection before and after displacement were taken by the camera. Laser parallel fringes can be generated in a camera and displacement was successfully measured by phase analysis of laser parallel fringes.
Exploring multi-programming for quantum algorithms

Today's quantum computing is performed on Noisy Intermediate-Scale Quantum (NISQ) hardware. The NISQ era allows for a limited number of qubits with several physical limitations. As NISQ devices have unavoidable noisy quantum operations, we can execute only small circuits on a quantum machine to get reliable results. But, this leads to the quantum hardware under-utilization issue. With the increase of hardware qubit number and the improvement of error rates, it becomes possible to execute multiple circuits on a quantum chip simultaneously, enhancing the throughput and the utilization of NISQ hardware. Thus, we address a timely problem on how to execute reliably multiple quantum programs on given quantum hardware. This is the first attempt to propose a complete multi-programming process flow for executing an optimal number of workloads in parallel, ensuring output fidelity by analyzing the hardware limitations.
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for  Incremental Object Detection

Deep networks have shown remarkable results in the task of object detection. However, their performance suffers critical drops when they are subsequently trained on novel classes without any sample from the base classes originally used to train the model. This phenomenon is known as catastrophic forgetting. Recently, several incremental learning methods are proposed to mitigate catastrophic forgetting for object detection. Despite the effectiveness, these methods require co-occurrence of the unlabeled base classes in the training data of the novel classes. This requirement is impractical in many real-world settings since the base classes do not necessarily co-occur with the novel classes. In view of this limitation, we consider a more practical setting of complete absence of co-occurrence of the base and novel classes for the object detection task. We propose the use of unlabeled in-the-wild data to bridge the non co-occurrence caused by the missing base classes during the training of additional novel classes. To this end, we introduce a blind sampling strategy based on the responses of the base-class model and pre-trained novel-class model to select a smaller relevant dataset from the large in-the-wild dataset for incremental learning. We then design a dual-teacher distillation framework to transfer the knowledge distilled from the base- and novel-class teacher models to the student model using the sampled in-the-wild data. Experimental results on the PASCAL VOC and MS COCO datasets show that our proposed method significantly outperforms other state-of-the-art class-incremental object detection methods when there is no co-occurrence between the base and novel classes during training.
PRIMENA INFORMACIONIH TEHNOLOGIJA U NASTAVI BULOVE ALGEBRE

In various scientific disciplines, especially in mathematics, com- puter science, technology, economy, sociology and medicine, solutions to many problems can be transformed in the form of “yes” or “no” or “0” or “1”. This fact, among other things, accelerated the development of electronics and digital tech- nology, and thus Boolean algebra, especially two-valued Boolean algebra. The pa- per contains three chapters. The first chapter discusses the definition of Boolean algebra, two-valued Boolean algebra and Boolean functions. The second chapter deals with the application of Boolean algebra in computer science through logic gates. The third chapter considers the application of logic gates and various ex- amples from information technology in teaching mathematics, so that students can more easily understand Boolean algebra and logical operations.
Translation techniques used in translating a smartphone user manual

As many smartphones are imported from overseas and the user manuals are written in English, the translation of a user manual is, therefore, very important for the Indonesian customers whose English is not their second language. Good translation results are then very essential in order that the customers understand the information easily and clearly. The focus of this research is the bilingual English-Indonesian Samsung’s GT-19500 user manual. This research aims to find translation techniques applied in the book. In this descriptive research, the sentences were the tokens that were recorded in Microsoft Excel. The tokens were then analyzed based on the categories of translation techniques in question. It was found that there were nine translation techniques used in the user manual. The translation techniques used in Samsung’s GT-19500 user manual are borrowing (41%), literal translation (25%), calque (13%), transposition (7%), equivalence (6%), adaptation (5.3%), modulation (3%), and omission (2%). Therefore, the techniques used in translating a smartphone user manual are unique to this type of document because the document consists of many terms without Indonesian equivalence.
RESEARCH ON THE AUTHENTICITY OF ACCOUNTING INFORMATION BASED ON BLOCKCHAIN AND ERP SYSTEM

The authenticity of accounting information is related to the issue of corporate credibility, and is increasingly valued by the state. With the development of IT, technologies of the new era have emerged, and these technologies have been gradually applied to the field of accounting and have achieved good responses. Because of the current financial fraud and other problems of enterprises, the article proposes that blockchain technology and ERP system can be used to improve the authenticity of accounting information in preventing tampering and internal control, and gives suggestions on both the enterprise and national levels.
DIGITAL HYBRID LEARNING INDIVIDUAL QUALITY ASSESSMENT IN EUROPEAN AND ORIENTAL LANGUAGES PROGRAMS: STUDENT CASE STUDY IN UKRAINE

The global pandemic and subsequent quarantine measures and restrictions have posed an array of challenges to the structure and procedure of higher education workflow, which significantly influenced the scope of individual experiences, projected outcomes and estimated quality of higher education in countries across the world.This study focus is the in-depth assessment of the case of individual digital distance and blended learning experiences by students of different tiers (Bachelor's level, Master's level, Graduate school level) in European (French, Italian, Spanish, English) and Oriental (Mandarin Chinese, Japanese) Languages university level programs at Borys Grinchenko Kyiv University of Ukraine through the span of educational activities in the time-frame of COVID-19 quarantine measures of March 2020 to January 2021.The survey and analysis of different ICT tools is used to assess the parameters and challenges of individual quality and efficiency of translation of the real life Foreign Languages Acquisition practices into digital hybrid format, involving activation of interdisciplinary skills and cross-sectorial activities, assisted by ICT tools.The online survey of over 300 students of European and Oriental Languages programs provides for disclosure of a comprehensive case of student satisfaction with digitized foreign languages education, systematized individual experiences and quality estimation of e-learning and hybrid learning in the framework of COVID-19 lockdown; assessment of individual experiences and quality of e-learning and hybrid learning in the framework of COVID-19 lockdown as compared to traditional, face-to-face learning formats for foreign languages; individual quality assessment of learning process design, programmed learning outcomes and projected competencies for university programs of Oriental and European languages in the framework of COVID-19 lockdown and quarantine measures.
The Devil is in the Details: The CIS General Insurance v IBM UK Decision — More Lessons Learned from the Failed Technology Project

Article The Devil is in the Details: The CIS General Insurance v IBM UK Decision — More Lessons Learned from the Failed Technology Project was published on October 1, 2021 in the journal Computer Law Review International (volume 22, issue 5).