Reviewerly/exHarmony huggingface dataset:
Learned Lossless Image Compression Through Interpolation With Low Complexity

With the increasing popularity of deep learning in image processing, many learned lossless image compression methods have been proposed recently. One group of algorithms that have shown good performance are based on learned pixel-based auto-regressive models, however, their sequential nature prevents easily parallelized computations and leads to long decoding times. Another popular group of algorithms are based on scale-based auto-regressive models and can provide competitive compression performance while also enabling simple parallelization and much shorter decoding times. However, their major drawback are the used large neural networks and high computational complexity. This paper presents an interpolation based learned lossless image compression method which falls in the scale-based auto-regressive models group. The method achieves better than or on par compression performance with the recent scale-based auto-regressive models, yet requires more than 10x less neural network parameters and encoding/decoding computation complexity. These achievements are due to the contributions/findings in the overall system and neural network architecture design, such as sharing interpolator neural networks across different scales, using separate neural networks for different parameters of the probability distribution model and performing the processing in the YCoCg-R color space instead of the RGB color space.
The role of sign tracking in the formation of process addiction

Current treatment for process addiction, such as gambling disorder and game addiction, is primarily psychotherapy, and effective pharmacotherapy has not been established. One reason is the lack of appropriate behavioral test batteries for mice to identify the causes of addiction and conduct pharmacological tests. The scarcity of high-value rewards is generally considered the cause of addiction, and experimental behavioral tasks have been proposed accordingly. In recent years, however, it has become clear that signs that foretell rewards are involved in the formation of gambling addiction. In the present study, we developed a 2-hole nose poke-selective operant task for mice in which two retractable levers were used as predictive signs for the reward. As a result, mice showed adherence to the option with predictable rather than unpredictable reward signs. Adherence to the predictable reward signs continued even after the reward probability decreased. We also found that the suboptimal behavior formation was correlated with the frequency of sign tracking. This study allows us to study the role of sign tracking in the shape of process addiction using genetically engineered mice and drug administration models.
Decentralized smart contract software service using ETHEREUM blockchain non-fungible tokens

The decentralized technologies of the Ethereum blockchain were analyzed, based on the principles of which a decentralized software service solution was proposed using a smart contract implemented in the specialized Solidity programming language. This contract acts as one of the elements of the server-client application and is the server part for processing methods of interaction with the Ethereum blockchain. The methods include a set of various functions, including for interacting with a collection of non-fungible tokens. The metadata that describes the digital product (non-fungible tokens) is directly linked to the blockchain and resides in a decentralized repository for its most reliable and long-lasting existence. The Ethereum blockchain, in addition to development tools, provides stable support for developers and users thanks to the popular decentralization paradigm, and the relevance and constant development of technologies lead to user interest in products created on their basis. Non- fungible tokens can be used as a cryptocurrency unit, and the decentralized application itself as a platform for collecting funds for a specific purpose. The methods of creating decentralized software services using smart contracts of non-fungible tokens were studied. The selection of the main nodes of the decentralized application is substantiated. A detailed functional diagram of the operation of the basic smart contract methods is proposed together with a diagram that describes all the functional nodes of the decentralized application in general. The results of the interaction of the client part of the software service with the smart contract of the Ethereum blockchain are also demonstrated.
Hubungan antara Tingkat Kecanduan Game Online dengan Prestasi Akademik SiswaSMA

&lt;p class="Abstract"&gt;&lt;span lang="EN-US"&gt;The present study aims to : (1) describe students' online game addiction and academic achievement in senior high school students, (2) examine the relationship between online game addiction and academic achievement. This correlational study involved 155 respondents, recruited using the cluster sampling technique. The data were collected using the author's online game addiction questionnaire and the final exam results for mathematics, Bahasa Indonesia, and English subjects. The validity test covered the construct and empirical validity, while the reliability was determined using Cronbach's Alpha with SPSS 25. The data were analyzed using descriptive and inferential statistics. The result showed that most students have moderate online game addiction (82%, n= 127) and moderate academic achievement (62%, n =96). The hypothesis result showed a significance value of 0.015 and a correlation coefficient of 0.195, indicating that the hypothesis was supported. In other words, students' online game addiction level is associated with their academic achievement. Future studies are recommended to explore other factors affecting students' academic achievement, such as learning motivation, intelligence, and learning style.&lt;/span&gt;&lt;/p&gt;
Detecting word boundaries in an undeciphered script: The Byblos syllabary

The Byblos writing system (ca. 1500 BC) comprises 15 inscriptions, with the largest one containing 461 clearly discernible signs. Some further 28 unassigned fragments found in the Levante and in Italy are tentatively assigned to the Byblos corpus too. We have created a Unicode letter for each sign variant found in these inscriptions and transcribed the corpus. Feeding the corpus into our RegEx- based deciphering tool, we established a preliminary (dynamic) syllabary laying a foundation for computer-assisted deciphering efforts of the Byblos script. A first sequence analysis allows to detect morphemes and word boundaries, so that even without knowing the sound values, we gain some insight into the syntax of the language depicted by these beautiful graphemes.
Improving students’ writing skills by using mind-mapping assisted by MindMeister at the twelfth graders in SMA Negeri 2 Ujungbatu

The study focuses on improving students’ writing skills through a mind-mapping strategy assisted by the MindMeister application in writing news text. This classroom action research was conducted in two cycles. This study was held in SMA Negeri 2 Ujungbatu, Rokan Hulu Regency, Riau. The sample is 30 twelfth-grader students. The variable measured was students’ writing skills. The data was collected using a pretest-posttest, observation checklist, and questionnaire. The pre-test score was 59.57, while the post-test was 82.23. The writing test in the second cycle reached 78.22. The mind mapping assisted by the MindMeister application strategy can influence writing skills. The analysis of the questionnaire and observation also supported that the strategy is appropriate in teaching writing news text. The teacher should be creative and innovative to create enjoyable learning processes to motivate students in writing.
Review of Mel’čuk, Igor. 2021. Ten Studies in Dependency Syntax. Berlin/Boston: De Gruyter Monton

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A Method of Square Root Central Difference Kalman Filter for Target Motion Analysis

The central differential Kalman filter (CDKF) and square root central differential Kalman filter (SR-CDKF) are widely used methods for addressing nonlinear problems in target motion analysis. However, for the bearings-only target motion analysis by single observer, sometimes the CDKF and the SR-CDKF experience the divergence problem or even filter interruption due to the observer’s mobility and system noise. To solve these problems, SR-CDKF is improved, and an adaptive singular value decomposition square root center difference Kalman filter (ASVDSR-CDKF) is proposed. The covariance square root update method based on the singular value decomposition method is deduced. The error discriminant statistics and adaptive factors are constructed. When the disturbance is too large, the adaptive factor is automatically adjusted and the square root updating form is selected. The simulation of bearings only target motion analysis is carried out under three different conditions, and the performance of CDKF, SR-CDKF, square root unscented Kalman filter (SR-UKF) and the proposed ASVDSR-CDKF method are compared. The simulation results demonstrate that the proposed method not only has high accuracy, but is also more stable than the other three methods.
i-Bond: A Next Generation Bond’s Issuing Service System

To address the issues of the bond market’s low transparency, information disclosure efficiency, and rating’s ability to reveal risks, this paper proposes a blockchain-based bond primary market issuance service system, for companies to issue bonds efficiently at low cost. This paper presents the architecture design of the next-generation decentralised bond issuance service system. In addition, this paper also presents a new bond issuance bidding mechanism. Through the two-dimensional auction, the collusion between bond issuers has significantly been reduced, and the hidden danger of market manipulation has been eliminated. A prototype system was built on Hyperledger for proof of concept and performance evaluation.
Credit Card Fraud Detection

Now a days online transactions have become an important and necessary part of our lives. Credit card fraud detection is presently the most frequently occurring problem in the present world. This is due to the rise in both online transactions and ecommerce platforms. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. As frequency of transactions is increasing, number of fraudulent transactions are also increasing rapidly. In order to reduce fraudulent transactions, machine learning algorithms like Naïve Bayes, Logistic Regression, and KNNetc. are discussed in this paper. The same set of algorithms are implemented and tested using an online dataset. Through comparative analysis it can be concluded that Logistic regression, naïve Bayes,and K-Nearest Neighbor (KNN) algorithms perform better in fraud detection.
Using Mobile Applications for Teaching English Vocabulary to Young Language Learners (YLLs): Investigating the Short- and Long-term Impacts

Using Mobile Applications for Teaching English Vocabulary to Young Language Learners (YLLs): Investigating the Short- and Long-term Impacts
SMART SHOES FOR FLAT FEET

This paper proposes the smart shoes classifying a normal, Plano-valgus foot and Toe walking in autism, and to provide the information to paediatrician. Therefore, we propose a prototype smart shoe for temporal identification and correction for child with abnormal walking patterns consisting of uneven pressure distributions. We focus on identifying and providing feedback for it abnormal walking patterns. This smart shoe including force sensitive resistor sensors, coin vibrators, Memory storage, a microcontroller (18F2520), a GPS, a GSM, a power supply, and a Smart Software application on a Smartphone (like thing show, pocket IOT Internet of things). Keywords: Force sensor resistor, coin vibrator, GPS, GSM, Microcontroller, walking pattern, software application.
The Objectives, Roles, and Functions of Technical Guidance (TG) for Strengthening the Competence of Teachers of Computer-Based Written Examination Subjects

This study aims to explore the role, objectives, and functions of technical guidance for teachers in charge of written exams in preparation for entrance exams to state universities. This research activity was conducted in Sulawesi. Sampling was carried out at the Golden Tulip Essential Makassar Hotel, Jalan Sultan Hasanudin, number 43, Sawerigading, Ujung Pandang District, Makassar City, South Sulawesi. The main objective of this research is to find out the initial results before being given training and after being given training (technical guidance) on ways to answer questions about the Joint Selection for State Higher Education Entrance (SBMPTN). The method used in this research is the comparative method. The results of the trial before the training and after the training showed a significant difference. In other words, teachers can get pretty good grades after being guided, fostered, and specifically tested in training activities designed by the organizing committee for technical guidance to strengthen the competence of teachers in computer-based written exams.
Case Study and Consideration of Design Approach Methods Used in the Development of Information and Communication Systems

The Design Dept. of Mitsubishi Electric Corp. has been researching the Design Approach method for a proposal approach to information system design. This paper presents a case study of the use of this methodology in the development of an information communication system and discusses the similarities and differences between the research phase and actual development. As representative examples, I report practical results applied to a large facility maintenance system and a medium-sized library system. Although the basic process of formulating a concept from a workshop and environmental analysis by the parties involved is common, it was found that the order of the process differs from case to case and that a detailed internal environmental analysis is necessary to lead to the development of a specific UI design.
Line of Sight (LOS) rate estimation in strap down seekers using discrete-time extended state observer.

Line of Sight (LOS) rate estimation in strap down seekers using discrete-time extended state observer.
ANALYSIS OF LITERATURE PSYCHOLOGY IN THE SOEKRAM TRILOGY NOVEL BY SAPARDI DJOKO DAMONO

This study aims to describe and determine the psychological value of literature in the novel Trilogi Soekram by Sapardi Djoko Damono. The method used for this research is a descriptive qualitative method. This method is used to describe systematically, factually and accurately about the psychological value of literature, especially the personality structure according to Sigmund Freud's id, ego, superego in the novel. The techniques used in this research are document study and content analysis. The type of study technique that this researcher uses is collecting quotes from the novel Trilogi Soekram. The data is in the form of quotations containing the psychological value of literature. The analysis technique is done through grouping and analyzing data. The psychological value of literature on the personality structure of the id with a total of 22 quotes, the personality structure of the ego with a total of 19 quotes, and the personality structure of the superego with a total of 13 quotes. The results of this study become one of the alternative teaching materials used in high schools (SMA) and universities. The values generated from this research can be used as teaching materials aimed at shaping the character through the personality values of students related to behavior in schools and colleges.
Digital Watermarking via Inverse Gradient Attention

Watermarking is the procedure of encoding desired information into an image to resist potential noises while ensuring the embedded image has little perceptual perturbations from the original image. However, the neglect of considering the pixel importance within the cover image of deep neural models will inevitably affect the model robustness for digital watermarking. Targeting at the problem, in this paper, we propose a novel deep watermarking scheme with Inverse Gradient Attention (IGA), combing the ideas of adversarial learning and attention mechanism to endow different importance to different pixels. With the proposed method, the model is able to spotlight pixels with more robustness for embedding data. Empirically, extensive experiments show that the proposed model outperforms the state-of-the-art methods on two prevalent datasets under multiple settings. Besides, we further identify and discuss the connections between the proposed inverse gradient attention with high-frequency regions within images.
The Effectiveness of Virtual Leadership Requirements in Saudi Universities Considering the Indicators of the National Center for E-Learning

The study sought to determine the effectiveness of virtual leadership requirements in Saudi universities in light of the indicators of the National Center for E-Learning. The questionnaire was adopted in this research and was given to a sample of 33 faculty members at the University of Hail. The study used a descriptive analytical technique. The research came to the conclusion that the mathematical mean of the three study dimensions—ideal influence, inspirational motivation, and empowerment—had a high level of effectiveness and within a range of 68% to 84%.The results also showed the absence of obstacles, as the arithmetic mean of the field of obstacles was (2.42), which is in a weak degree. Through the results, it was found in the study procedures that there is an effectiveness of the requirements of virtual leadership at the University of Hail in the light of the indicators of the National Center for E-Learning.
Students’ Experiences of Left-Right Game in Writing Narrative Text: A Narrative Inquiry Study

The present study is aimed at exploring students’ experiences of using left-right game in writing narrative text. Narrative inquiry is used to capture students’ experiences of left-right games told in their narrative frames. This study concerned one class at the tenth grade purposively determined senior high school students in Indonesian context which consist of thirty-one students. Student’s narrative frame, semi structured interview and observation are the instruments employed to collect data. Their narratives reflect positive experiences in using left right games as a strategy to help them in writing narrative text. The findings of this study show that 87 % of the students state positive experiences in using left-right game activity in writing narrative text. They state that left-right game is a fun activity, they feel enthusiast when the teacher conduct left-right game. The students who engage through left-right game activity can find the way to equally and mutually collaborate in producing better a piece of writing.
The Effect of Artificial Intelligent Technology Used (Duolingo Application) To Enhance English Learning

This research aims to figure out the effect of Artificial Intelligence Technology in Duolingo Application to Enhance Speaking and Listening Ability. This study uses a quantitative technique where the researcher conducts experimental research using a quasi-experimental design. This research was completed at Hamzanwadi University with the subjects of this study were all students of second semester with class C English program with a total of 31 students. Where 16 students were the experimental class and 15 students were the control class. The results of the information investigation utilized descriptive statistics in analyzing the data and for hypothesis testing using normality test, homogeneity test, T-test and One Way- ANOVA. The means score for the speaking experimental class is 88.63, then 75.38 for the listening, and for the speaking control class it is 80.53, then 52.13 for the listening. Then with the result of significance (Sig.) 0.000 0.05. In conclusion, that there is an influence by utilizing the Duolingo application to enhance speaking abilities in second semester of Hamzanwadi University in the English Education Study Program for the academic year 2022-2023.
Language Learning Attitudes and Reading Comprehension Achievement at A Private Junior High School in East Java, Indonesia: A Correlational Study

The attitudes of learners influence their ability to acquire English as a foreign language. In terms of its impact on learners, a good attitude leads to successful learning, whereas a negative attitude leads to failure. During the preliminary study, the researcher found that those who were eager to learn could do the reading test well. On the other hand, the students who were not welcome to English had difficulty to understand and finish the test. Therefore, the research aimed to investigate the relationship between language learning attitude and reading comprehension achievement. This research was conducted at the seventh-grade students at a private junior high school in East Java, Indonesia. The population of this study was 153 students and the sample taken was 43 students. The method used in this research was quantitative method with correlational design. The instruments used to gather the data were language learning attitude questionnaire and midterm examination as reading comprehension test. Both scores were analyzed and calculated using statistical procedure of Pearson Product Moment correlation. The result showed that there was a moderate positive correlation between language learning attitude and reading comprehension achievement (rxy = +0.349). The hypothesis testing showed that p-value (0.022) was less than the level of significance (0.05) which means that H0 was rejected and Ha was accepted. The research findings indicated that there was a correlation language learning attitude and reading comprehension achievement of the seventh-grade students.
КОМУНІКАТИВНА КОМПЕТЕНТНІСТЬ МАЙБУТНІХ ПСИХОЛОГІВ ЯК ПСИХОЛІНГВІСТИЧНА ПРОБЛЕМА

Modern education is focused on formation of the basic and professional competences in applicants of higher education with a view to successful implementation of youth in future professional activities and harmonious development of personality. Competence includes a set of basic knowledge, skills, and abilities, humanitarian values that help people to find their place in the professional world and realized themselves in accordance with their skills.