Reviewerly/exHarmony huggingface dataset:
A Study on the Mediating Effect of Goal Orientation and Cultural Orientation between the Intrinsic Characteristics of Online Learning and Learning Satisfaction

The educational situation in Korea inevitably raises problems with evaluativeism, excessive competition, mental stress, and antisocial behaviors such as bullying and suicide. Therefore, among the various positive effects of online learning, in paiticular, the relationship with creativity development, which is being mainly discussed in the global era, will be investigated. The purpose of this study is to empirically test whether cultural orientations (interdependent selfindependent self) and goal orientations (learning goal·pe1f01mance goal) mediates relationships between characteristics of online learning (intrinsic·extrinsic) and learning satisfaction. After collecting survey data from one hundred seventeen Korean college students, having online-learning experiences, regressional analyses and mediational analyses have been employed to analyse the hypothesized relationships. The followings have been found: first, there were significantly positive relationships between intrinsic characteristics of online learning and cultural and goal orientations. Second, a significantly positive relationship between intrinsic characteristics of online learning and learning satisfaction has been found. Third, cultural and goal orientations were found to be positively related to one's learning satisfaction. Last, it has been detected that cultural and goal orientations mediate the relationship between characteristics of online learning (intrinsic·extrinsic) and learning satisfaction. Its implications in Korean culturε and educational context havε been suggested. The results of this study suggest that the intrinsic characteristics of online learning can increase learning satisfaction, but it is more effective for learners who havε a desire for creative thinking.
A Decision Support System Based on Neural Network and Genetic Algorithm: Case Study of Breast Cancer

Introduction: Artificial intelligence has been changing the way healthcare has been provided in many high-risk environments or areas with poor healthcare facilities. The emergence of epidemics and new diseases, as well as the crucial role of early diagnosis in prevention and the adoption of more effective treatments have highlighted the need for accurate design and self-organization of Clinical Decision Support Systems (CDSSs).Material and Methods: In this study, a CDSS based on a neural networks (NN) and genetic algorithm is proposed. Since, on the one hand, the performance of the neural network (NN) is highly dependent on its parameters, and on the other hand, there is a constant need for optimization experts to fine-tune the parameters in the use of new data, a new chromosomal structure is proposed to automatically extract the optimal NN architecture, the number of layers and neurons. The goal is to increase the reusability of the model and ease of use by health experts.Results: To evaluate the performance of the model, two standard breast cancer (BC) datasets, WBC and WDBC, were used. The model uses 70% of the data set for training and the remaining equally used for evaluation and testing. The test accuracy of the proposed model on WBC and WDBC datasets was 98.51 and 97.55%, respectively. The optimal NN architecture on WBC consisted a three-hidden layers with 18, 15 and 19 neurons in each layers, and on WDBC consisted one hidden layer with a single neuron.Conclusion: The proposed chromosomal structure is able to derive optimal NN architecture. In according to the high classification accuracy of the model in the diagnosis of BC and providing the different architectures in accordance with the hardware implementation considerations, the proposed model can be used effectively in the diagnosis of other diseases.
Prediction of Electric Load Neural Network Prediction Model for Big Data

Spike sorting algorithms is a considerable significant way to collect neural signals in neural signal acquisition systems. One method to realize this function in hardware aspect is to use absolute-value detector. In this paper, the common circuit topology is given by using static CMOS and PTL technology. Then, through comparing with the delay and energy of unit reference inverter, the optimal energy-delay model when sacrificing extra 50% delay can be obtained by the way changing the size of CMOS and Vdd simultaneously, which save nearly 83% energy dissipate than minimal delay model.
Financial Policy Measures to Strengthen Liquidity in the Real Estate Project Financing Market

As financial markets and economic conditions are rapidly changing around the world and the domestic real estate market is turning into a recession, credit crunch and liquidity risks are expanding in the real estate PF market. Accordingly, in this study, a financial policy plan that can supply liquidity to the domestic real estate market and reduce the delay rate was proposed. First, in the case of using P-CBO, a plan to support desired funds through the issuance of new corporate bonds using corporate bonds of construction companies that are difficult to raise and refinance in the housing finance market as an underlying asset It is a plan to guarantee and purchase from government-run banks and finances. In addition, a plan was proposed to jointly invest by comprehensive financial investment companies and purchase ABCP directly with the funds. On the other hand, in the case of unsold housing utilization, the housing builder's financing plan for unsold housing was designed by dividing it into unsold housing after completion and unsold housing before completion.
A method for analyzing suspect-filler similarity using convolutional neural networks

Eyewitness misidentifications are one of the leading factors in wrongful convictions. This study focuses on the structure of the lineups, which is one of the factors that cause misidentification, and the use of artificial intelligence (AI) technologies in the selection of fillers to be included in the lineups. In the study, AI-based face recognition systems are used to determine the level of similarity of fillers to the suspect. Using two different face recognition models with a Convolutional Neural Network (CNN) structure, similarity threshold values close to human performance were calculated (VGG Face and Cosine similarity = 0.383, FaceNet and Euclidean l2 = 1.16). In the second part of the study, the problems that are likely to be caused by facial recognition systems used in the selection of fillers are examined. The results of the study reveal that models responsible for facial recognition may not suffice alone in the selection of fillers and, an advanced structure using CNN models trained to recognize other attributes (race, gender, age, etc.) associated with similarity along with face recognition models would produce more accurate results. In the last part of the study, a Line-up application that can analyze attributes such as facial similarity, race, gender, age, and facial expression, is introduced.
Developing English Materials with Religious Content for Students of State Hindu University of I Gusti Bagus Sugriwa Denpasar

Contextual and integrated teaching and learning is one of the most important issues to discuss in the respect of educating students with particular social background. This empowers students to actively learn a subject because the material provided is close to their daily lives while being integrated to other subject. This study aims to develop an English teaching material integrated with Hindus religious values for students of State Hindu University of I Gusti Bagus Sugriwa Denpasar, employing a Research and Development design by adopting the ADDIE model. Further, students are expected to not only improve their English skills, but also strengthen their religious values. The analysis phase includes needs analysis by examining the current syllabus, observing the teaching in classroom, and interviewing students. During the design process, the product is decided to be in a form of e-module integrating religious values. Development process focuses on the validity test of the product and also field tryout to examine the product’s practicality and usability. The validity test involves five experts on content, layout, and display of the product where all components resulted in valid category. The result on the field tryout toward small group also reveal that the content aspect get 717 points (78%) and categorized as good, the layout aspect get 620 points (77%) and categorized as good, and language aspect get 435 (75%) and being categorized as good. The result of this study is expected to provide lecturers with options in teaching English as compulsory subject in higher Education.
Extreme Learning Machine Algorithm in Sentiment Analysis and Its Applications: Systematic Literature Review

Natural language processing and machine learning are used to define and extract human emotions from unstructured text using a technique called sentiment analysis. Many organizations and companies today want to use this to recognize and act accordingly on the customer or user's features. This increases the importance and effectiveness of emotion analysis and the diversity of algorithms used day by day. One of these algorithms is the Extreme Learning machine. The Extreme Learning machine (ELM) algorithm is an important machine learning algorithm for emotion analysis and classification. In this study, the method used in the ELM's emotional analysis is systematic research that shows that the context and its applications have been studied. A systematic review of the works published between 2020 and 2022 was carried out using Web of Science and Google Scholar databases. After the first and in-depth screening of the literature, 10 of the 28 articles were selected from the review process. The articles have been reviewed based on the purpose of the study and research questions. According to the research results, different methods were used in the emotional analysis, mostly with the ELM, and ELM’s performance was improved. Quality analysis of treatment summaries is used in different areas, such as health care, education, and website product assessments. ELM's use of emotion analysis has resulted in most social media data as a scope, especially the Twitter platform.
A CRITICAL DISCOURSE ANALYSIS OF MEDICAL ASSOCIATIONS AND RESEARCH JOURNALS ON OBESITY USING VAN DIJK’S MODEL

The present study aims at exploring the CDA approach to determine the differences in the discourse of research articles in medical journals and associations. The study investigates how the associations delete, select, construct or generalize information for their benefits. The information was gathered from medical research articles and associations about obesity. World Health Organization (WHO), Obesity Medicine Association (OMA), National Institutes of Health (NIH), National Health Services (NHS), Healthline, Mayo Clinic are among the organizations that have been chosen for this study. The macro structure of Van Dijk model is used to address the research questions and to determine whether medical journals and associations are on the same page or not. As a result, associations have more authority than journals. The results of this descriptive self-study are summarized in graph charts and tables.
Identifikasi Serangan Low-Rate DDOS Berbasis Deep Learning

LowRate DDoS (LDDoS) is a variation of DDoS attack that sends fewer packets than conventional DDoS attacks. However, by sending a smaller number of packets and using a unique attack period, low-rate DDoS is very effective in reducing the quality of an internet network-based service due to full access. On the other hand, the low-rate DDoS with its nature also makes it difficult to detect because it looks more mixed with normal user access. The Deep Learning model that will be used in this research is the RNN LSTM (Long Short Term Memory) model. LSTM is a neural network architecture which is good enough to process sequential data. This model is better than the simple RNN model. The research method is adapted to the SKKNI No. 299 of 2020. However, this research will be carried out until the model development stage, namely the evaluation model. From the results of the research that has been done, it can be concluded that the RNN LSTM model can be used to classify low-rate DDOS attacks using feature selection. The accuracy of the training data on the validation data is around 98% and after visualizing the data for accuracy and loss, it can be concluded that the model is quite good, aka there is no underfitting or overfitting. While the accuracy obtained for testing data is 0.97%.
Effectiveness of a Proposed Program for Using Smartphones in Developing the Skills of Functional Expression among First-Year Secondary Students in Sana'a City

The study aimed to assess the effectiveness of a proposed program to use smartphones by first-year secondary students in Sana'a city to develop their skills of functional expression. To achieve this objective, the semi-experimental method was adopted with a sample of (60) first-year secondary students who were selected by the purposive sampling method. The sample was divided into two groups (control and experimental), taking into consideration their homogeneity. The experimental group was introduced to the proposed program, while the control group was taught in the traditional method. The research instruments included a list of functional expression skills and a test of the same skills. The study results revealed statistically significant differences between the two groups in the overall results of the post-test in favor of the experimental group. There were also statistically significant differences between the pre- and post-test results in favor of the experimental group. This confirmed that the proposed programhad an impact on the development of students’ skills of functional expression. In light of the results, the study stressed the need to utilize smartphone applications in teaching Arabic courses and other courses. It was also recommended to introduce mobile applications-based teaching and learning, as this would boost the performance of high school students.
Differential evolution algorithm based on grid entropy and Bessel mutation strategy

In order to further improve the exploration and exploitability of Differential Evolution (DE) algorithm, Bessel mutation strategy based on grid entropy is proposed to improve iLSHADE-RSP algorithm. The new algorithm is called BiLSHADE-RSP. It has the following features: (1) A grid entropy for observing the convergence of the population is proposed to be used as a signal of applying Bessel mutation strategy; (2) A mutation strategy based on Bessel curve is designed to enhance the exploitability of DE. BiLSHADE-RSP is compared with five algorithms, namely iLSHADE-RSP, LSHADE-RSP, L-SHADE, DCDE and FNADE. We use CEC2017 test suit to verify the performance of the proposed algorithm. Experimental results show that the improvement in BiLSHADE-RSP algorithm has achieved the best effect on complex test functions, and its solution accuracy is better than the current popular DE variants.
Pengaruh Lingkungan sekolah dan lingkungan keluarga terhadap prestasi belajar siswa kelas X SMK Fajar Moyongkota

ABSTRAK&#x0D; Penelitian ini bertujuan untuk mengetahui pengaruh Lingkungan Sekolah dan Lingkungan Keluarga terhadap Prestasi Belajar Siswa Kelas X SMK Fajar Moyongkota. Metode penelitian ini adalah metode survey dengan 40 sampel. Teknik yang digunakan dalam pengumpulan data adalah teknik kuisioner (angket), observasi dan dokumentasi. Hasil penelitian dianalisis dengan metode analisis regresi linear berganda, dan analisis korelasi ganda. Adapun hasil dari penelitian ini yaitu (1) variabel Lingkungan Sekolah berpengaruh positif dan signifikan terhadap Prestasi Belajar Siswa Kelas X SMK Fajar Moyongkota sebesar 19,44%, thitung= 3,030 &gt; ttabel = 2,024 dan fhitung = 54,88 &gt;ftabel 4,08. (2) variabel Lingkungan Keluarga berpengaruh positif dan signifikan terhadap terhadap Prestasi Belajar Siswa Kelas X SMK Fajar Moyongkota sebesar 22,27%, thitung= 3,301&gt; ttabel = 2,024 dan fhitung = 56,27&gt;ftabel4,08. (3) variabel Lingkungan Sekolah dan Lingkungan Keluarga berpengaruh positif dan signifikan terhadap Prestasi Belajar Siswa Kelas X SMK Fajar Moyongkota sebesar 80,65%, dan fhitung = 7,86 &gt;ftabel 3,25.&#x0D; Kata Kunci : Lingkungan Sekolah, Lingkungan Keluarga, Prestasi Belajar&#x0D; ABSTRACK&#x0D; This study aims to determine the effect of the school environment and family environment on the learning achievement of class X students at Smk Fajar Moyongkota. This research method is a survey method with 40 samples. The technique used in data collection is a questionnaire technique (questionnaire), observation and documentation. The results of the study were analyzed using multiple linear regression analysis and multiple correlation analysis. The results of this study are (1).The school Environment variable has a positive and significant effect on the learning Achievement of Clas X Students of Smk Fajar Moyongkota vocation school by 19,44% tcount 3,030 &gt; ttablel = 2.024 and fcount =54,88 &gt; ftable 4,08 (2).The family environment variable has a positive and significant effect on the learning achievement of Class X students at Smk Fajar Moyongkota vocation school by 22,27%. Tcount 3,301 &gt; ttable= 2,024 and fcount = 56,27 &gt; ftable 4,08. (3). The variables of the school Environment and Family Environment have a positive and significanteffect on the Learning Achievement of class X Students of Smk Fajar Moyongkota vocational School as large as 80,65%, and fcount =7,86 &gt; ftable 3,25.&#x0D; Keywords: School Environment, Family Environment, Learning Achievement&#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Pengaruh Perhatian Orang Tua Dan Motivasi Belajar Terhadap Hasil Belajar Siswa Di SMK Negeri 1 Bolaang

ABSTRAK&#x0D; Penelitian ini bertujuan untuk mengetahui pengaruh perhatian orang tua dan motivasi belajar terhadap hasil belajar siswa di SMK Negeri 1 Bolaang. Metode penelitian ini adalah metode kuantitatif dengan sampel 64 orang. Teknik yang digunakan dalam pengumpulan data adalah teknik observasi, kuesioner (angket) dan dokumentasi. Hasil penelitian dianalisis dengan metode analisis regresi ganda, analisis korelasi sederhana dan korelasi ganda. Adapun hasil dari penelitian ini menunjukan (1) Perhatian Orang Tua berpengaruh signifikan terhadap Hasil Belajar Siswa dengan jumlah thitung lebih besar dari ttabel = 9,074 &gt; 1,669 (2) Motivas Belajar berpengaruh signifikan terhadap Hasil Belajar Siswa dengan jumlah thitunglebih besar dari ttabel = 6,082 &gt; 1,669 (3) Perhatian Orang Tua dan Motivasi Belajar berpengaruh signifikan terhadap Hasil Belajar Siswa di SMK Negeri 1 Bolaang sebesar 29,92% dengan jumlah Fhitung lebih besar dari Ftabel = 76,888 &gt; 4,00.&#x0D; &#x0D; Kata Kunci : Perhatian orang tua, Motivasi belajar dan Hasil belajar siswa&#x0D; &#x0D; ABSTRACK&#x0D; This study aims to determine the effect of parental attention and learning motivation on student learning outcomes at SMK Negeri 1 Bolaang. This research method is a quantitative method with a sample of 64 people. The techniques used in data collection are observation, questionnaires and documentation. The results of the study were analyzed using multiple regression analysis methods, simple correlation analysis and multiple correlations. The results of this study show (1) Parental Attention has a significant effect on Student Learning Outcomes with a tcount greater than table 9,074 1,669 (2) Motivation = Learning has a significant effect on Student Learning Outcomes with a tcount greater than table = 6.082 &gt; 1.669 (3) Parental Attention and Learning Motivation have a significant effect on Student Learning Outcomes at SMK Negeri 1 Bolaang by 29.92% with the F number greater than F 76.888 &gt; 4.00. table.&#x0D; Keywords: Parents' attention, learning motivation and student learning outcomes.
An Analysis of Women's Language Features used by the Three Indonesian Female Travel Bloggers

This research focuses on women’s language features used by the three Indonesian female travel bloggers on blogspot.com and wordpress.com. It was aimed to investigate types of women’s language features used by the three Indonesian female travel bloggers and the most dominant types of women’s language features used by the three Indonesian female travel bloggers. This research was carried out using descriptive qualitative research. The data came from the script of 15 blog posts written by the three Indonesian female travel bloggers. The findings revealed that the three Indonesian female travel bloggers utilized nine types of women’s language features, they are lexical hedges or fillers, tag question, rising intonation on declaratives, empty adjectives, intensifiers, hypercorrect grammar, super polite forms, avoidance of strong swear words, and emphatic stress. The scripts of the three Indonesian female travel bloggers contain a total of 628 language features. During the analysis of the data, it revealed that the researchers were unable to discover precise colour terms because it was unrelated to the 15 blog posts. There was no correlation among the theme on 15 blog posts and the ability to use precise colour terms back then. The three Indonesian female travel bloggers dominantly employed hypercorrect grammar to prove that they concerned about their grammar.
The Effect of Using Edmodo Learning Media and Learning Motivation on Fiqih Learning Outcomes

This study aims to find the effect of using Edmodo learning media on learning outcomes, the effect of learning motivation on learning outcomes, and the interaction between Edmodo learning media and learning motivation on Fiqh learning outcomes for students of class VIII MTsN 2 Medan. This type of research is a quantitative study with a population of all eighth-grade students consisting of 10 classes (401 students). Based on the Cluster Random Sampling technique, one class is used as a learning class with Edmodo media and another without Edmodo media. The research instruments used were tests and questionnaires. The normality test for learning outcomes data is the Liliefors test, and the homogeneity test is Fisher's and Bartlett’s tests. The data analysis technique used two-way ANOVA at significant = 0.05. The study’s results revealed an influence of Edmodo learning media on students' fiqh learning outcomes, where students' fiqh learning outcomes with Edmodo learning media were higher (26.22) than students' non-Edmodo learning media fiqh learning outcomes (23.25). The influence of learning motivation on learning outcomes obtained fiqh learning outcomes of students with high learning motivation was higher (27.12) than that of students with low learning motivation (22.03). While the interaction between learning media and learning motivation on students' fiqh learning outcomes through the results of the 2 x 2 ANOVA factorial calculation, the interaction factor value F = 9.113 and the P-Value = 0.004 smaller than 0.05. Thus there is an interaction between learning media and learning motivation on students' fiqh learning outcomes at MTsN 2 Medan.