Reviewerly/exHarmony huggingface dataset:
Motivation in English Language Learning: Case Studies Students of English Depatment of Sisingamangaraja XII Tapanuli University

This research investigates the motivation of students studying English at the Department of English, Sisingamangaraja XII Tapanuli University. Motivation plays a crucial role in language learning, influencing learners' engagement, persistence, and overall success in acquiring a second language. The study employs a qualitative approach, utilizing case studies to delve into the unique experiences and perspectives of individual students. The research employs qualitative research methods, including interviews, observations, and document analysis, to gather rich and in-depth data from a selected group of students. Findings from the case studies of knowledge on language learning motivation and provide practical implications for educators, curriculum developers, and policymakers aiming to enhance the English language learning experience for students in similar contexts. Understanding the intricate dynamics of motivation is essential for fostering a positive and conducive learning environment that promotes language proficiency and academic success.
Measurement Digital Transformation Capability on Operational Performance (Case Study: Bank BJB)

With the changes in market environments and the development of digital technology, the banking industry urgently needs to develop the capability to adapt to profound changes in strategy and business processes. This study constructed the dimensions of a digital transformation capability that contains threehub factors (sensing, organizing, and restructuring) under the dynamic capability theory. This study collected 100 sets of company data through a survey and investigated the relationships of a company’s strategy orientation, digital transformation capability, and operational performance by using SPSS and SmartPLS. The results show that strategic orientation (Customer Orientation and Technology Orientation) has a positive impact on a digital transformation capability and that digital transformation capability has a positive impact on operational performance. In addition, the digital transformation capability plays a mediating role between strategic orientation and operational performance. Doubtlessly, the company needs, to focus on building their own digital transformation capabilities (Sensing, Organizi,ng and restructuring) to create new business value. A digital transformation capability will encourage company to integrate their business processes and routines through digital technology to achieve a competitive advantage.
HANDWRITTEN SIGNATURE RECOGNITION USING NEURAL NETWORKS

This work is devoted to solving the problem of signature recognition using neural networks. The authors proposed the use of convolutional neural networks to determine the signature class. Signatures play an important role in financial, commercial and legal transactions, their recognition guarantees the security of not only information, but the whole person. The use of neural networks for signature recognition allows you to reliably identify a user in an automated mode. The authors have developed a convolutional neural network, and also proposed an algorithm that consists of image preprocessing, including background segmentation, noise reduction, and image normalization. Image preprocessing improves the quality of the network. Next, feature extraction is performed, which consists of global features, such as the ratio of the height to width of the signature, the maximum horizontal histogram and the maximum vertical histogram, the horizontal center and the vertical center of the signature, the endpoints of the signature, the signature area, training a neural network with extracted features, recognition the owner of the handwritten signature and then predicting the class of the signature.&#x0D; Purpose – development of a handwritten signature recognition algorithm using neural networks.&#x0D; Methodology: the methods of computer vision were used in the work; deep learning methods, as well as object-oriented programming methods.&#x0D; Results: developed a handwritten signature recognition algorithm using a neural network.&#x0D; Practical implications: the application of the results obtained is useful in forensic analysis of documents, since a person uses a signature on a regular basis to sign checks, legal documents, contracts and other paper media that need protection. Therefore, when someone tries to copy a signature, a problem arises that can lead to undesirable consequences in the form of theft and further use of both personal data and other valuable secret information.
Design and Development of Product Sales Website Using the Waterfall Methodology: An Academic Approach

The development of digital technology and the internet has significantly changed the business landscape, especially in terms of product marketing and promotion. One area that has been significantly affected is the MSME (Micro, Small, and Medium Enterprises) industry. MSMEs often face challenges in expanding their market and increasing their revenue due to limited resources and limited accessibility. The existence of a website can make it easier for business actors to promote their products in order to reach wider marketing and make it easier and faster for consumers to find product information provided by business owners. The purpose of this research is to create a marketing website using a Waterfall with the help of WordPress software.
Digital Visualization Tools in Training Students of Economic Higher Education Institutions

This article analyzes the results of a study aimed at identifying the assessment by university students of the role of physical culture in the upbringing and development of personality. During the implementation of the project, a sociological survey was conducted on the basis of the author's questionnaire, in which 124 students of the Omsk branch of the Financial University under the Government of the Russian Federation who have no restrictions on physical education for health reasons took part. &#x0D; The results of the study give grounds to assert that only 41% of students regularly engage in physical culture and sports. At the same time, the overwhelming majority of respondents noted the positive impact of classes on physical health and the development of important personal qualities such as, for example, willpower, self-confidence and purposefulness.&#x0D; The low motivation of respondents to engage in physical culture and sports, to a large extent, as the survey showed, is due to the lack of commitment to a healthy lifestyle in many families (84%). In addition, physical education classes do not take into account individual characteristics and current fitness techniques to the proper extent, which also contributes to a decrease in students' interest. An important component of the formation of a positive attitude among young people to physical culture and sports is the equipment of university gyms with modern physical education equipment and inventory. &#x0D; The results of the study can be used in the development of programs of the discipline "Physical Culture" and effective methods that contribute to the development of sustainable motivation among students to engage in physical culture and sports not only during their studies at the university, but also throughout their lives.
Vector leptoquark $U_3$: A possible solution to the recent discrepancy between NOvA and T2K results on CP violation

In the current epoch of neutrino physics, many experiments are aiming for precision measurements of oscillation parameters. Thus, various new physics scenarios which alter the neutrino oscillation probabilities in matter deserve careful investigation. Recent results from NOvA and T2K show a slight tension on their reported values of the CP violating phase $\delta_{CP}$. Since the baseline of NOvA is much larger than the T2K, the neutral current non-standard interactions (NSIs) of neutrinos with the earth matter during their propagation might play a crucial role for such discrepancy. In this context, we study the effect of a vector leptoquark which induces non-standard neutrino interactions that modify the oscillation probabilities of neutrinos in matter. We show that such interactions provide a relatively large value of NSI parameter $\varepsilon_{e \mu}$. Considering this NSI parameter, we successfully explain the recent discrepancy between the observed $\delta_{CP}$ results of T2K and NOvA. We also briefly discuss the implication of $U_3$ leptoquark on lepton flavour violating muon decay mode $\mu \to e \gamma$.
Virtual Reality, Augmented Reality, Mixed Reality, Holograms and Holodecks

This paper provides a preliminary overview of different forms of reality, comparing and contrasting them with one another. It argues the definition of the term "reality" is ambiguous. This motivates an internalization of elements from a technology standpoint, e.g., biological, 3D printed, Flying Light Speck illuminations, etc.
Effect of Using Chemdroid (Chemistry on Android) Media on Students' Self-Efficacy in Thermochemistry Material

This study aims to see the effect of using Chemdroid media on students’ self-efficacy in a thermochemistry topic. Chemdroid is Chemistry on Android. Self-efficacy is related to students’ beliefs in activities in the classroom. This type of research is quasi-experimental using post-test only control group design. In this study, two different classes were used which were declared to be normalyy distributed and homogeneous. The first class is the control class (CC-Class) which conducts conventional learning media as usual. The second class is the experimental class (EC-Class) which uses Chemdroid media for thermochemistry topic as a learning media in the classroom. Both classes have the same learning time, teacher and learning model. The instrument used in this study is a self-efficacy questionnaire that has been developed in previous studies but has been adapted to current research. The statement items used in this measuring instrument are 22 statements with 6 aspects. The test used is the Mann Whitney with the help os the SPSS program. The result of the analysis state that the significance is smaller than level of conficence. This proves that there is a significant difference with the use of Chemdroid media for a thermochemistry topic on the self-efficacy of the control class and experimental class students.
Evaluating Ordinal Pattern Features for 2D Colored Noise Classification

This study explores the potential of permutation entropy and statistical complexity for analyzing time series and image data of varying dimensions and noise types to extract features for computational vision. We projected one dimensional colored noise of different sizes and one and two-dimensional 1/f noise with different embedding dimensions to observe changes in permutation entropy and statistical complexity. The results of this study provide insights into the usefulness of the permutation entropy and statistical complexity in the analysis of complex time series data for future parameter extraction.
Cooperative Path Planning of Ground-air Robots for Distributed Photovoltaic Inspection

Abstract Facing the Distributed PV generation inspection scenario, to overcome the low efficiency of traditional manual inspection and the insufficient endurance of existing UAV inspection, UAV aerial inspection and UGVs to provide energy supply in the road network are adopted, and a path planning method that prioritizes the meeting points is proposed. Firstly, the improved genetic algorithm is used to plan the inspection path of each UAV, then the UAV path is clustered to determine the optimal number of meeting points, then the adaptive particle swarm algorithm is used to find the best location of the meeting points in the road network, and finally, the patrol path with the meeting points is optimized twice. Through the simulation test of the standard data set and real data, the effectiveness of the proposed method in solving the path planning problem of distributed photovoltaic coordinated inspection by ground-to-air robots is verified.
Penerapan Model Pembelajaran Berbasis Proyek untuk Meningkatkan Aktivitas dan Keterampilan Analisis Sastra

Abstract The purpose of this study was to improve literary analysis activities and skills using a project-based learning model in the Indonesian Literature study program, Faculty of Teacher Training and Education, Jambi University. The method used in this research is Classroom Action Research (PTK) which was carried out in two cycles in the Oral Literature Study course. In the first cycle, two meetings were held and the second cycle was held three meetings. Each cycle is carried out in the stages of planning, implementation, observation, and reflection. The data were analyzed in accordance with the predetermined assessment rubric. In the first cycle, the students' activity scores increased, 80% of which reached the good category score and 20% reached the very good category score compared to the activity scores obtained in the pre-cycle. As for the value of the results of literary analysis in cycle I, it has not yet reached the target, namely not exceeding 50% of students getting good and very good category scores. In cycle II, the value of activity and the results of literary analysis experienced a significant increase, namely 100% of students getting very good category scores for activity scores and 80% of students getting good scores and 20% getting very good scores for the results of literary analysis. Based on these values, it can be said that the application of the Project Based Learning learning model in the Oral Literature Study course to improve activities and oral literature analysis skills is appropriate and effective to be applied. Keywords: Activity, Skill, Literature Analysis, PjBL
Formation of bachelors of pedagogical education skills in organization of control measures at elective courses in informatics

Elective courses play an important role in the profile education of high school students. Thanks to them, it is possible to expand or deepen the knowledge and skills of schoolchildren in a particular subject area, prepare them for choosing a profession or passing the state final certification. An important place in elective courses is occupied by control measures, with the help of which the teacher both determines the level of readiness of students to pass the elective and assesses the success of the student in mastering the course material. In this regard, the future teacher must master the methodology for organizing elective courses, including the ability to develop or select materials for control activities. Taking into account the transition of education in pedagogical universities to the “Core of Higher Pedagogical Education”, it becomes difficult to prepare for elective courses in computer science. Therefore, the article shows one of the ways for students to master the skills of organizing and conducting elective courses through one of the university disciplines. The development of tasks for control measures, designed by students in the study of university discipline, is given.
An Efficient Strong Asymmetric PAKE Compiler Instantiable from Group Actions

Password-authenticated key exchange (PAKE) is a class of protocols enabling two parties to convert a shared (possibly low-entropy) password into a high-entropy joint session key. Strong asymmetric PAKE (saPAKE), an extension that models the client-server setting where servers may store a client’s password for repeated authentication, was the subject of standardization efforts by the IETF in 2019–20. In this work, we present the most computationally efficient saPAKE protocol so far: a compiler from PAKE to saPAKE which costs only 2 messages and 7 group exponentiations in total (3 for client and 4 for server) when instantiated with suitable underlying PAKE protocols. In addition to being efficient, our saPAKE protocol is conceptually simple and achieves the strongest notion of universally composable (UC) security. In addition to classical assumptions and classical PAKE, we may instantiate our PAKE-to-saPAKE compiler with cryptographic group actions, such as the isogeny-based CSIDH, and post-quantum PAKE. This yields the first saPAKE protocol from post-quantum assumptions as all previous constructions rely on cryptographic assumptions weak to Shor’s algorithm.
Toward an Empirical Theory of Sense: A Corpus-Based Study of Mandarin Conceptual Lexicalization

The empirical theory of sense is one of the most challenging and least studied topics in computational lexical semantics. Previous studies have focused on disambiguation and sense tagging, both of which rely on prior knowledge of the inventory of possible senses of a word. However, because prior lexical knowledge cannot be assumed, and linguistic behavior is the only information available for determining both the number and the definition of senses of any given word, the study presented in this chapter proposed predicting sense clusters for each target word based on distributional information from corpora. In addition, the study intended to find all possible linguistic information and lexical senses of words automatically by employing distributional information. Using collocational information from the Chinese Gigaword Corpus, usage examples of four target words—chi1 “eat,” wan2 “play,” huan4 “change,” and shao1 “burn”—were clustered into different sense divisions. These automatically discovered senses were then compared with the manually analyzed senses of these words in Chinese WordNet and Xiandai Hanyu Cidian (The Contemporary Chinese Dictionary) to evaluate their accuracy and coverage. Finally, the automatically discovered sense divisions were tested against an offline psycholinguistic experiment using multiple-choice tasks (Burton et al. 1991).
Fast UAV Image Mosaicking by a Triangulated Irregular Network of Bucketed Tiepoints

To take full advantage of rapidly deployable unmanned aerial vehicles (UAVs), it is essential to effectively compose many UAV images into one observation image over a region of interest. In this paper, we propose fast image mosaicking using a triangulated irregular network (TIN) constructed from tiepoints. We conduct pairwise tiepoint extraction and rigorous bundle adjustment to generate rigorous tiepoints. We apply a bucketing algorithm to the tiepoints and generate evenly distributed tiepoints. We then construct a TIN from the bucketed tiepoints and extract seamlines for image stitching based on the TIN. Image mosaicking is completed by mapping UAV images along the seamlines onto a reference plane. The experimental results showed that the image mosaicking based on a TIN of bucketed tiepoints could produce image mosaics with stable and fast performance. We expect that our method could be used for rapid image mosaicking.
The Use of Instagram Integrated Learning Media Against Student Learning Motivation in Reaction Rate Material

The purpose of this study was to determine the effect of using Instagram integrated learning media on students' learning motivation in the matter of reaction rate. This study used a qualitative descriptive method by using a questionnaire to find out the increase in the results of students' learning motivation. This research was conducted at one of the public high schools in Malang City involving 33 students of class XI IPA 4. The data analysis used was in the form of a qualitative test of students' learning motivation. The results of the study show that the use of Instagram learning media can increase students' learning motivation regarding the reaction rate material.
Weak Zero-Knowledge via the Goldreich-Levin Theorem

Obtaining three round zero-knowledge from standard cryptographic assumptions has remained a challenging open problem. Meanwhile, there has been exciting progress in realizing useful relaxations such as weak zero-knowledge, strong witness indistinguishability and witness hiding in two or three rounds. In particular, known realizations from generic assumptions obtain: (1) security against adaptive verifiers assuming fully homomorphic encryption among other standard assumptions (Bitansky et. al., STOC 2019), and (2) security against non-adaptive verifiers in the distributional setting from oblivious transfer (Jain et. al., Crypto 2017). This work builds three round weak zero-knowledge for NP in the non-adaptive setting from doubly-enhanced injective trapdoor functions. We obtain this result by developing a new distinguisher-dependent simulation technique that makes crucial use of the Goldreich-Levin list decoding algorithm, and may be of independent interest.
Features of Proposed System for Electronic Learning at Universities

The world is today a scientific and technological revolution, has been an explosion in terms of information and cognitive, and the changes undergone by the world related to the rapid flow of information and the enormous potential for storage and processing. The computer is a product of scientific and technical progress today, is also at the same time one of the pillars of leading this progress; making it the recent focus of educators and those interested in the educational process and education, has paid educational computer systems, and called for use both in school management Or teaching. It has been shown to most computer users experience the process in many developed countries that computer education, if used in the right place at the time - can achieve excellent results in the classroom. This, in turn, include training teachers to use the best technology so they can plan appropriate and report the appropriate place and time required to reach teachers and students alike to master the skills and scientific facts and concepts contained in school decisions and less time building positive trends as well as assistance in the evaluation and test students.
The culture of reading for acquisition and learning of content knowledge for English language and literature in English in higher education

This study aims to explore the culture of reading literary texts in higher education and the strategies that can enhance the acquisition and learning of the content knowledge for both English Language and Literature in English. The study adopted an interpretivist paradigm and qualitative research design. The study is qualitative in nature. Language in/for/with content and schema theories form the basis for the study. The former holds that language cannot be acquired outside content whilst schemata are stored mental structures that determine the acquisition of new knowledge; thus, literary content knowledge may not be acquired/learned outside linguistic and communicative competencies and vice versa. Data were collected from the relevant literature from the past six years. It was interpreted and analysed thematically. The results showed that students' habit of reading is poor which affects their academic performance. In addition, new technological devices make learning easier and more accessible, but it negatively affects students' ability to read authentic texts for information and entertainment. The study therefore concludes that university students do not read literary texts because of the bad use of information and communication technology. However, the use of digital libraries could improve the situation. The findings suggest that institutions of higher learning should have strategies to engage linguists and literary scholars in the habit of reading literary texts. University libraries should be equipped with relevant and updated digital reading materials.