Reviewerly/exHarmony huggingface dataset:
MOTIVASI BELAJAR SISWA KELAS KHUSUS DAN KELAS REGULER DI MTsN 4 BANDA ACEH

Learning motivation is a psychological condition that encourages someone to do something that will cause changes in human activity. A person's learning motivation is influenced by two factors, namely intrinsic factors which include physiological (physical condition) and psychological (attitudes, talents, interests, intelligence, and cognitive abilities). While the second factor is extrinsic factors which include the environment (natural and social), parental attention, curriculum, teachers, learning facilities, teaching methods, and administration. This research was conducted at MTsN 4 Banda Aceh, this study aims to determine the differences in learning motivation between students in special and regular classes. This study is a comparative study, the population in this study were all students of MTsN 4 Banda Aceh as many as 565 students, the sample in this study was 168 students who were determined by simple random sampling technique consisting of 84 special class students and 84 regular class students. The data collection technique was carried out using a Likert scale, data analysis was carried out by using the t test (Independent Sample T-Test). The results showed that there was a difference in learning motivation between special class students and regular class students as indicated by the tcount coefficient of 1,983 which was greater than ttable of 1,974 (1,983&gt;1,974) and the significance value of 0.000 was smaller than 0.05 (0.000&lt;0, 05). So the result is that Ho is rejected and Ha is accepted, meaning that there is a difference in learning motivation between students in the special class and the regular class.
Comparative Objective Analysis of video quality Between H.265/HEVC and H.264/AVC

This paper shows the difference in video quality between two compressed videos using H.264 AVC (Advanced Video Coding) and H.265 HEVC (High Efficiency Video Coding) encoders. To evaluate video completely it should be prepared video files that have a variety of bit rates and content. There are many video quality assessment methods. We can divide the min to subjective and objective methods. Subjective are conducted by a human perception and objective are conducted by a computer software which is calculating the video quality. All of these methods have theirs advantages and disadvantages. To generate compressed videos from the original video FFmpeg (Fast Forward-moving picture experts group) converter has been used. MSU-VQMT (Moscow State University’s Video Quality Measure- mentTool) was used to perform comparative objective analysis of video quality. Delta, MSE (mean square Error), MSAD (Mean Sum of Absolute Difference), PSNR (Peak Signal-to-Noise Ratio), and SSIM (Structural Similarity Index Measure) metrics were measured. The result from FFmpeg shows that the size of the compressed video using the H.265 codec has been decreased by 50% compared to the compressed video using the H.264 codec. The comparison of metrics shows that delta, MSAD, PSNR, and SSIM values of H.265 encoded video was decreased, while Delta and MSE value was increased compared to H.264 encoded Video. That’s mean the overall video quality was decreased but the video size was enhanced.
The competition-independence game with prevention

The competition-independence game, as introduced by Phillips and Slater, is played on a graph by two players, Diminisher and Sweller, who are taking turns in choosing a vertex that is not in the closed neighborhood of any of the previously chosen vertices. The goal of Diminisher is to minimize the (maximal independent) set of chosen vertices at the end of the game, while Sweller wants just the opposite. Assuming that both players are playing optimally according to their goals, two graph invariants arise depending on who starts the game. In this paper, we introduce a variation of the game in which players are allowed at any stage in the game to use an alternative move called prevention. That is, a player can decide that in his/her move he/she will mark (not choose!) a previously unplayed vertex x by which x is prevented to be chosen during the rest of the game; in particular, x is not in the final set of chosen vertices. Given a graph G, and assuming that both players play optimally according to their goals, ?Id(G) (resp.?Is(G)) denotes the size of the set of chosen vertices in the competition-independence game with prevention if Diminisher (resp. Sweller) moves first. By using the Partition Strategy we prove that for any positive integer n, ?Id(Pn) = [2n+3/6] and ?Is(Pn) = [2n+4/6]. While it is not hard to establish the general bounds, 1 ??Id(G) ? [n/2] and 1 ??Is(G) ? [n/2], we characterize the classes of (connected) graphs G that attain each of the four bounds. Finally, a close connection of the new game with a version of the coloring game called the packing coloring game is established for graphs with diameter 2, and several open problems are posed.
Sentiment Analysis for Online Shopping in the UAE: A Case of Business Analytics

The massive acceptance of blogs and social mediaunlocks the access for consumers to express their opinions and views about thehappiness or disappointment of online shopping. Sentiments of blogs and social media are instantaneous and economically feasiblethan the traditional technique of collecting responses. Consumers in the UAE are prone to use blogs and social mediafor giving feedback and responses about the products purchased online. The research thus finds its importance in the context and uses tworesearch hypotheses to recognize the applicability of blogs and social media as a tool for online responses. Three industry sectors,electronics, fashion, and travel, are taken in the research for comprehensive analysis. Overall, 1200 responses are collected from4 blogs (based on the sector), and another 1200 responses are from 4 social media channels (Facebook, Twitter, YouTube, andInstagram). The responses are analyzed using the QDAP (Quantitative Discourse Analysis Package) dictionary in R programming. Keywords: QDAP, s-commerce, sentiment analysis, t_test, online-based-brand community (OBBC), two-tailed hypotheses test
Supplementary Figure 1 from Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses

&lt;p&gt;Illustration of microcalcifications and masses in the breast&lt;/p&gt;
Table S7 from Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses

&lt;p&gt;Association between a genetic predisposition to breast cancer (using family history of breast cancer and estrogen-receptor specific polygenic risk scores) among women withour breast cancer&lt;/p&gt;
Table S5 from Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses

&lt;p&gt;Association between a genetic predisposition to breast cancer and % mammographic density&lt;/p&gt;
Table S6 from Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses

&lt;p&gt;Association between a genetic predisposition to breast cancer and mammographic features among women who did not develop breast cancer during follow-up&lt;/p&gt;
PENGEMBANGAN WEB PROGRAM LATIHAN BERBASIS DIGITAL

The research aims to develop a digital application for preparing an exercise program to make it easier for trainers to prepare an exercise program. This research uses Agile Development Methods. This research was conducted at the Faculty of Sports Science, Unesa, involving a sample of 50 students. The sampling technique in this study used a purpose random sampling technique. Data collection techniques using surveys. Based on the results of observations made to the sample, a total of 78% of the sample stated that the development of this application was going very well, 14% was good and 8% was sufficient. It can be concluded that this digital-based training program web is suitable for use by trainers in preparing training programs.
Image dehazing method quality assessment

Abstract：In recent years，responding to subjective assessment results in assessment methods by targeting the quality of dehazing algorithms has become common，but this lacks quantitative description.However， existing objective quality assessment methods and subjective assessment have been inconsistent，and the two sometimes diverge.Therefore，to improve the objective quality assessment performance of a dehazing method，a full reference dehazing method quality assessment based on artificially synthesized images is pro• posed here.First，a synthetic image dataset is established that includes reference haze-free，synthetic hazy，and dehazed images obtained by using eight state-of-the-art dehazing algorithms on these synthetic hazy images.Second，we classify quality problems that might be introduced by the dehazed images.Third，by combining clarity-related features and existing objective methods of image quality assessment，a dehazing method quality assessment is proposed through mutual integration of image visibility，structural 文章编号 1004-924X
Metode Pembelajaran PAI Mengatasi Kesulitan Siswa Membaca Iqra’ di Kelas 1 SDIT Baiturrahim Parik Putuih Agam

Learning to read Iqra' which is held at SDIT Baiturrahim Parik Putuih It is a routine activity that is carried out every morning after the Dhuha prayer, Iqra' learning is carried out before carrying out the teaching and learning process, namely at 08.30 WIB, reading the Koran is carried out for 30 minutes. The formulation of the problem in this study includes the following: 1). What is the method of Islamic Religious Education in overcoming reading difficulties for iqra' grade 1 students at SDIT Baiturrahim Parik Putuih. 2). What methods are used by Islamic religious education teachers in overcoming Iqra reading difficulties for grade 1 students at SDIT Baiturrahim Parik Putuih. This study uses a type of qualitative research, data collection techniques that the authors apply in the preparation of this article, namely observation and interviews. The results of this study indicate that: 1). the method of Islamic religious education in overcoming students' difficulties in reading iqra' by using the iqro method (reading the letters of the Koran fluently) and this method does not require various tools because it is only aimed at reading it. .2) What methods do Islamic Religious Education teachers use in overcoming Iqra' reading difficulties, namely using individual, individual or individual teaching? Individuals advance one by one to the teacher according to each page. parents to encourage their children to continue learning to read Iqra' at home so that their children are fluent in reading Iqra' at school.
Effect of Using Dialogue Technique in Teaching Speaking at Eighth Grade of MTs N 7 Pasaman Barat

The purpose of this research was to determine the effect of using dialogue technique in teaching speaking. The researcher has done at MTsN 7 Pasaman Barat. This research was carried out because the students had some problems in speaking English. It was caused by several factors there were the students had difficulties to say something or express their idea. Then, the students had limited vocabulary, so the students did not speak English well. Besides that the students lack of confidence in speaking and have low pronunciation ability. In addition the teacher used monotonous ways in students speaking practice. In this research a quasi-experimental design was used by the researcher. The researcher used pre-test and post-test to experimental class and control class. The population of this research was the eighth grade students of MTsN 7 Pasaman Barat. The sample was 8B as experimental class taught by using dialogue technique and 8A as control class and taught without using dialogue technique. To determine the sample, the experimental and control class, the researcher utilized SPSS 20 to examine the data and check for normality and homogeneity. The researcher utilized the t-test formula to test the hypothesis and consulted the results in a t-table with level of significance of 0.05. From the calculation of the research the pre-test and post-test score in experiment class, it was found that there was a significant effect of using dialogue technique in teaching speaking. It was proven by the value t-calculated of experimental class in pre-test and post-test was higher than t-table (6.042 &gt; 2.021). Then there was a significant difference between students who were taught using dialogue technique and those who were taught without them. The value of t-calculated in post-test from the experimental and control classes was greater than t-table (5.883 &gt; 2.021). The last hypothesis was that teaching with dialogue technique was higher than teaching without dialogue technique in terms of improving students speaking skill. In the post-test, the mean score of the experimental class was greater than the control class (14.174 &gt; 0.174).
Using Trust Measures to Optimize Neighbor Selection for Smart Blockchain Networks in IoT

The blockchain paradigm is currently modifying all the major Internet of Things (IoT) application domains, giving the opportunity of constructing decentralized environments in which trustful and anonymous activities can be efficiently performed. Blockchain proposes an approach which assures data saved on a distributed ledger would be continuously synchronized and in such a way the ledger will remain consistent. The distributed ledger has the responsibility to maintain a higher level of consistency. Given a connected network, the Optimum Neighbor Selection (ONS) of paths can be obtained by finding the Minimum Spanning Tree of the network. However, none of past approaches proposed in the literature to construct ONS considered the problem of having nodes with low levels of reliability in the network and even malicious or fraudulent nodes, that is a situation very common in an IoT environment. In this paper, we propose an optimized blockchain ONS algorithm, called Trust-based ONS (TONS), which allows the miners to communicate with a globally-optimized selection of neighbors. The algorithm can also guarantee that these nodes are the most reliable miners. We also describe an experimental simulation campaign we have performed to evaluate the effectiveness and the efficiency of our approach.
Technology of psychological and pedagogical support of professional development of pedagogical workers as an effective tool of the modern education

The article describes the technology of psychological and pedagogical support for the professional development of teachers. Also identifies the main principles on the basis of which a model of professional development and the technology of its support were developed. The levels, components and forms of psychological and pedagogical support have been determined. The stages of the experimental study of the effectiveness of the technology of psychological and pedagogical support are described: ascertaining, formative, control. The analysis of a sample of respondents is carried out, the results of a pilot study are presented. The formative stage of the experiment is described in detail at which in the system of continuing education of teachers, such forms of professional development as: distance courses of in-depth study of psychology for preschool teachers, primary school teachers, middle and senior-school teachers, trainings, seminars, workshops, master classes were used. Alsopresented the results of an empirical study of the effectiveness of the implementation of the technology of psychological and pedagogicalsupport in the system of continuous education.
GASTeN: Generative Adversarial Stress Test Networks

Concerns with the interpretability of ML models are growing as the technology is used in increasingly sensitive domains (e.g., health and public administration). Synthetic data can be used to understand models better, for instance, if the examples are generated close to the frontier between classes. However, data augmentation techniques, such as Generative Adversarial Networks (GAN), have been mostly used to generate training data that leads to better models. We propose a variation of GANs that, given a model, generates realistic data that is classified with low confidence by a given classifier. The generated examples can be used in order to gain insights on the frontier between classes. We empirically evaluate our approach on two well-known image classification benchmark datasets, MNIST and Fashion MNIST. Results show that the approach is able to generate images that are closer to the frontier when compared to the original ones, but still realistic. Manual inspection confirms that some of those images are confusing even for humans.
How efficient is Machine Learning in detecting financial fraud using mobile transaction metadata?

Global data has shown that each day the number of fraudulent transactions is exponentially increasing. As digital fraud continues to increase, machine learning and AI are being used to curb this increase. This paper will focus on the development and analysis of a machine learning model used to detect financial fraud in mobile money transactions. The aim of this paper is to discuss how effective a machine learning model can be in detecting fraud. This algorithm makes use of the Naïve Bayes model to detect fraud. To prove this, the results have been provided by using a confusion matrix, precision and recall which indicate the effectiveness of the model. The accuracy of the developed model is 0.996 with a precision and recall of both above 0.99. This work explores and develops a solution to one of the biggest breaches in digital security.
A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

Prediction systems are an important aspect of intelligent decisions. In engineering practice, the complex system structure and the external environment cause many uncertain factors in the model, which influence the modeling accuracy of the model. The belief rule base (BRB) can implement nonlinear modeling and express a variety of uncertain information, including fuzziness, ignorance, randomness, etc. However, the BRB system also has two main problems: Firstly, modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy. Secondly, interpretability is not considered in the optimization process of current research, resulting in the destruction of the interpretability of BRB. To balance the accuracy and interpretability of the model, a self-growth belief rule base with interpretability constraints (SBRB-I) is proposed. The reasoning process of the SBRB-I model is based on the evidence reasoning (ER) approach. Moreover, the self-growth learning strategy ensures effective cooperation between the data-driven model and the expert system. A case study showed that the accuracy and interpretability of the model could be guaranteed. The SBRB-I model has good application prospects in prediction systems.
Analisis metode chi_squared automatic interection detection untuk klasifikasi uang jemput pada tradisi pernikahan di kecamatan pariaman utara

One of the areas in Minangkabau which is famous for its marriage customs is Pariaman.Because there is a bajapuik tradition that requires a uang jemput for Ajo Piaman.According to the Head of the Nagari Customary Density in North Pariaman District, Ajo Piaman's uang jemput are certainly different and the factors that affect Ajo Piaman's uang jemput are employment, education, age, income, title, marriage, property, and year of marriage.The population of this study is partly Ajo Piaman and the sample is 100 Ajo piaman in North Pariaman District who are married.The purpose of this study was to determine the factors that affect Ajo Piaman's uang jemput and to find out the results of the classification of Ajo Piaman's uang jemput using CHAID analysis.The results of this study indicate that education, income and year of marriage factors affect uang jemput in North Pariaman District.
Elliptic Curve Cryptosystem for Digital multimedia, General Review

Various Cryptography algorithms are used to keep the transmission of data safe from intruder and to secure the connection between sender and receiver. This article provides an overview of ECC, including the algorithm process, fundamental protocols, and different ECC systems and applications. EC over fields also represents by numerous graphical representations of cryptographic processes. Comparison tables are included that list the ratio of key size between ECC and RSA (the nearest method to ECC), in factors of overhead, power availability and required storage, which indicates fast running with less bandwidth in case of elliptic curve method. In the other hand some previous works related to the topic were compared according to the functions of properties, measurement methods, and type of the data used, results were collected in traceable manner for the purpose of making it available to researchers and those interested in ECC.
Kombinasi Analytical Hierarchy Process, C4.5, dan Particle Swarm Optimization pada Klasifikasi Pegawai

Decision Tree C4.5 is widely implemented in various research fields in determining classification, but there are still weaknesses in Decision Tree C4.5, one of which is that it cannot rank each alternative. In this study, to overcome the weakness of Decision Tree C4.5, a combination of Analytical Hierarchy Process (AHP) methods, Decision Tree C4.5, and Particle Swarm Optimization (PSO) methods is proposed in the case study of employee classification for promotion recommendations. The research begins by determining the criteria and weighting criteria from the interview results which are then processed with AHP to produce employee ratings and eligibility labels for the classification process. The classification process uses the Decision Tree C4.5 method which is optimized with the PSO algorithm so as to produce employee eligibility data for promotions. The results of the combined research of AHP, Decision Tree C4.5, and PSO methods show that AHP can produce employee ratings based on performance and potential criteria, and Decision Tree C4.5 classification and optimization with PSO have better accuracy results, namely 95.80% compared to Decision Tree C4.5 method without PSO optimization is 93.40%. Based on the results of the ranking and classification of this research can be used as a basis for promotion of employees.
Realistic Image Synthesis of Imperfect Specimens using Generative Networks

This work explores conditional Generative Adversarial Networks (cGANs) as a tool to create realistic appearing CT slice images with pre-defined imperfections for the verification of automated defect detection algorithms. We aim to create an effective and efficient technique to simulate defects in CT slice images by implementing a new method which can simulate realistic textures and shapes. The problem is stated as an image to image translation task, where a new image is generated based on a given semantic description of the desired realistic image. This semantic description is a material based segmentation of the image with additional circular segments indicating the rough size and position of the intended defect. Based upon related work on cGANs, a convolutional neural network architecture is introduced and applied to our task. This method was trained and evaluated using 2D slice images derived from industrial CT datasets of automotive pistons. Our method showed promising results, producing convincing images in under one minute of computation with image resolutions of 256 by 256 pixels.