Reviewerly/exHarmony huggingface dataset:
ENHANCE EFFICIENCY OF SOLAR ENERGY CONVERSION SYSTEM USING ANFIS WITH ISOLATED MODE

This paper shows performance investigation on enhance efficiency of standalone solar energy conversion system using ANFIS based MPPT controller. Now a days many researches are going in the field of renewable energy technologies to bridge the gap between supply and demand. Due to the Intermittent nature of renewable sources, operating standalone operation of them is highly unreliable causes interruption in power supply to the load. A solar photovoltaic system with MPPT based on Adaptive-Network-Based Fuzzy Inference System (ANFIS) is used for stable operation and to meet the supply with the load demand. The application of ANFIS based MPPT technique requires detailed study and analysis of the Solar Photovoltaic (SPV) system. Adaptive-Network-Based Fuzzy Inference System based MPPT technique is used along with Solar PV system as they can provide fast and accurate response to various environmental conditions. The Levenberg-Marquardt algorithm is used to train the neural network for MPPT in the photovoltaic system. This developed control strategy is able to control the devices and various power interface circuitry used therein. The main aim of this paper is to ensure a maximum power output coordinating appropriate control strategy with sources &amp; compare the performance analysis of the ANFIS based MPPT with conventional incremental conductance based MPPT for the SPV system. The simulation studies have been carried out to find out the SPV system performance with different input conditions such as typical solar radiation and temperature. The Simulation test results show variable power generation and verifies that the performance of the integrated system with this control strategy is effective for the real-time installation. The simulation results shows that the performance of this developed control strategy for receiving maximum power output from the standalone SPV system is farfetched. Simulation test results show variable power generation and verify the performance of the integrated system with control strategy is overall effective for real-time installation. The developed system is essential in an isolated region where an existing grid is unable to supply secure power generation and system is beneficial with smartly feed ultimate power generation sources.
Website Evaluation of DISPERDAG Section of the Average Price of Standard Needs Using the WEBQUAL 4.0 Method

DISPERDAG of Madiun City is one of the organizations that has utilized technology. The community can easily access and get price updates for basic necessities at Pasar Besar City of Madiun. The Internet helps support strong governance management, which benefits its effectiveness. Its functions include making it easier to get information, access public services, communicate with the public, and others. DISPERDAG aims to continue to provide quality services. The quality of services provided to the public must complement the implementation of website-based services so that the public continues to use SISKAPERBAPO services. To provide the best service to users, government institutions should prioritize service quality. Therefore, the success of the service quality of the SISKAPERBAPO website has not been known as long as the website is implemented. This is because there has never been an evaluation of website quality based on user satisfaction. It goes without saying that a website that is useful for assisting users in obtaining information must maintain quality in terms of information delivery and user interaction. Good service quality is offered from the user's point of view as well as the service provider's point of view.
Prediction of Planning Value School Shopping Income Budget with Multiple Linear Regression

The School Expenditure Budget Plan or RAPBS is the pillar of school management for allocating the revenue budget and use of school funds to meet all school needs for one year. However, there are problems that occur in the management of the RAPBS, namely the difficulty of grouping the RAPBS data annually, making it difficult to predict the budget for the coming year. This research was conducted to study and implement the Multiple Linear Regression algorithm in predicting the value of data on income and expenditure budget plans which are a reference in planning future budgets. To support predictions of planned school budgets and income, BUMS data, Aid data, School Program Cost data, Original School Revenue data, Other Sources data, and Total Budget data are used. The prediction system method used consists of the planning stage, the analysis stage, the modeling stage, interface design, and implementation using the PHP and MySQL programming languages for database management and system testing and analysis. The results of testing the data analysis using the multiple linear regression method with SPSS software have a 100% result according to the manual calculations performed.
Creativity Support Tools and Convergent Thinking: A Preliminary Review on Idea Evaluation and Selection

Creativity Support Tools (CSTs) have grown exponentially in the HCI field. However, this growth has always leaned towards divergent thinking, thus neglecting convergent thinking. We confirm this information based on a preliminary review between 2012 and 2022 in the ACM Digital Library. Our findings confirm that researchers and practitioners have been primarily interested in developing tools to support idea generation, minimizing studies on evaluating and selecting ideas. We focused our research on four major points: i) the domain of the tool, ii) the type of system and interface developed in the tools, iii) the methodology used, and iv) the creative context of the tools. Based on this information, we contribute six guidelines to support the improvement of existing CSTs and the development of new CSTs.
MODELING REGRESSION ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (RANFIS) FOR PANEL DATA

Panel data combine cross-sectional and time-series data. Data on economic, business, social, and development issues are often presented in panel data. In constructing the panel data regression model, it is necessary to take various steps for testing the model specifications, including the Chow test and the Hausman test. This study constructed a classical panel data regression model and the regression adaptive neuro-fuzzy inference system (RANFIS). The RANFIS model is a regression model by applying fuzzy and neural network (NN) techniques expected to overcome the problem of uncertainty. One of the main problems in constructing an optimal RANFIS is selecting input variables. The input variables of RANFIS are selected on the basis of the best classical regression. These inputs are classified into optimal clusters, which depend on the degree of fuzzy membership functions. The rule bases of RANFIS are determined on the basis of optimal inputs and its clusters. The empirical study in this research is to construct a panel data regression model for the Human Development Index (HDI) in Central Java in 2017-2019. HDI depends on several variables such as the school participation rate, number of health workers, public health complaints, population growth rate, and poverty severity index as predictor variables. Based on classical regression, three variables were used as optimal inputs for RANFIS modeling. Evaluation of model performance was measured based on the RMSE and MAPE values. Based on the RANFIS, the values of RMSE and MAPE were 3.227 and 3.299, respectively. Keywords: Panel Data Regression, Human Development Index, Regression Adaptive Neuro-Fuzzy Inference System DOI： https://doi.org/10.35741/issn.0258-2724.58.3.57
EFFECTS OF INFORMATION QUALITY AND SERVICE QUALITY ON SAUDI ARABIA’S HIGHER EDUCATION INSTITUTION E-LEARNERS’ SATISFACTION

Electronic learning, or e-learning as it is more frequently known, is a type of interactive learning that uses information and communication technology to provide a learning experience with enough freedom. During the COVID-19 pandemic, e-learning has attracted much attention in the education sector because it offers learners several advantages, such as flexible learning opportunities, distance learning opportunities, consistency in learning, time savings, tracking capabilities, minimal cost facilities, quick response, and interactive learning facilities. This study evaluated the effects of service and information quality on e-learner satisfaction in Saudi Arabian higher education institutions. A quantitative approach was used to conduct the study. Information was gathered from Saudi Arabian higher education institutions. 350 questionnaires were examined. Structural equation modeling (AMOS SEM) was used to analyze the effects of the relationship between information quality and service quality in terms of e-learners' satisfaction. The study findings showed that information quality and service quality have a significant effect on e-learners’ satisfaction. Therefore, this paper suggests that concerned authorities pay particular attention to ensuring quality and current policies and standards to address the issues that may affect e-learners' satisfaction with e-learning in higher education institutions in Saudi Arabia. Keywords: E-Learners’ Satisfaction, Electronic Learning, Information Quality, Service Quality, Higher Education Institutions DOI： https://doi.org/10.35741/issn.0258-2724.58.3.60
Use of hate speech and social evaluation of a politician’s image

We investigated whether the use of hate speech by politicians impacts the social evaluation of their image, as measured by the semantic differential method developed by Cwalina et al. (2000). The participants (N = 105, Polish nationals) evaluated the profiles of three well-known Polish politicians from different parties – Krzysztof Bosak, Radosław Sikorski, and Włodzimierz Czarzasty – and a fictional politician named Jacek Wiśniewski. Participants made evaluations before and after reading hateful posts from each politician. The participants’ political views and their alignment with the electoral programs of the politicians being evaluated, as well as demographic variables such as gender and age were also measured. The results showed that hate speech adversely affected the politician’s image, as evaluated by the participants. As a consequence of the experimental manipulation, all of the politicians whose profiles were presented for evaluation were judged more negatively. In particular, the negative evaluations concerned the politicians’ competences (unqualified and provincial), their emotionality (excitable and aggressive), and their attitude towards other people (insincere and unfriendly). Detailed analyses also showed that: (a) respondents who sympathized with the views of specific politicians tended to evaluate them more positively, (b) hate speech was more harmful to the image of politicians
Sample Size in Multiple Regression Models: A simulation study

The aim of the research is to study the efficiency of the following indicators of the multiple regression model, i.e., the value of "F", R2, Adj., R2, Standard Beta B, Unstandard Beta B, and EMS, in the light of different sample sizes using three methods of multiple regression (standard – gradual – hierarchical). The descriptive method was used. The research community consisted of a virtual community that simulates reality, and it was obtained through the simulation method. It consists of 500 items, created using Mics. Excel program, which are observations that represent one dependent variable denoted by the symbol (Y), and five independent variables, coded (X1, X2, X3, X4, X5), with the aim of evaluating the efficiency of the indicators of multiple regression models (standard - progressive - hierarchical), in light of the different number of samples, range from (10 ≤ n ≥ 500). It was noticed that the conditions of multiple regression were not available in samples less than 50, so the indicators of regression models were studied with sample numbers ranging from (50 to 500). The results indicated that all the multiple regression models indicators increase and improve with increasing the number of the sample, and the best estimate for the regression models was when (n = 225), at a rate of (45) for each independent variable, as the value of R2 was (43%), and was equal to the value of the modified R2, and it was All indicators are good, and by increasing the sample from that, and until reaching the entire population (n=500), the percentage of improvement in the indicators was small, and the value of R2 was (45%). The results also indicated that there is no reliance on only one indicator to judge the quality of the multiple regression models, as well as the difference in the efficiency of the indicators according to the number of the sample, and the statistical method used, especially in the number of small samples. The study recommended using large samples in multiple regression studies, relying on more than one indicator to know the efficiency of regression models, and taking into account the regression method used according to the importance of the researcher's variables.
Phenomenology of place in contemporary theater

The director incorporates the philosophical effect of place into theatre performance to enhance the recipient's awareness. The director is vital to any theatrical performance, and their philosophical effect on the contemporary stage is immense. Through their creative vision, the director can combine elements of the script and performers to create an experience for the audience that sparks contemplation and enables more profound engagement with the play. This research aimed to study the artistic phenomenon and its impact on artistic achievement and divided it into four sections. In terms of defining the terminology, the second section is the theoretical framework. The first is the concept of phenomenology in the theatrical direction, an indicator most prominent of those applied by directors. The second section deals with place theatrical, and the researcher concludes the second section with the most critical indicators. In the third section, the researcher identified the research community and the sample selection method, analyzed the sample, and concluded with the sample analysis results. In the fourth section, the most important results of this research are extracted, and conclusions are drawn.
An Interactive Medium to Introduce Sasando Traditional Music Using Multimedia Development Life Cycle Method

ActionScript-based programming is one of the software which includes applications that teachers widely use to create interactive learning media in the world of education. ActionScript-based programming technology is a type of graphic animation software that can create a graphic object that can be animated without using other supporting software. At present, there are many educational circles to expedite the process of learning activities, especially for students. Interactive learning media is one means of delivering subject matter that is very important to apply today. In implementing student learning at school, it is necessary to present a practical and theoretical learning system which is the main point in helping to develop student competence. One form of culture in Indonesia is the traditional musical instrument Sasando. Sasando belongs to the chordophone instrument because it is played by picking it. The form of Sasando itself is in the form of a guitar, violin or harp. The central part of the Sasando is in the form of a long bamboo tube. In the middle, rounded from top to bottom, there is a wedge to stretch the strings. Developing interactive learning media requires a software development method; one of the development methods used is the MDLC (Multimedia Development Life Cycle) method. Making the MDLC has five stages: Concept, Design, Material Collecting, Assembly, and Testing
Syntactic Features of the Japanese “-negau” and Korean “-himanghada” Sentence

This study examined the syntactic structure and characteristics of the sentence constructions using the Japanese term “-negau” and the corresponding Korean term “-himanghada.” The data for the study were extracted from “Syounagon” a corpus published by Japan’s National Institute of Japanese Language and Linguistics, and the example sentences were modified in a way that did not affect the study. Native Japanese and native Korean speakers assisted in determining the data’s sufficiency. The study’s results are summarized as follows. First, it is observed that the deep structure of the Japanese “-negau” and “-himanghada” sentence constructions are bi-clause structures in nature. These considerations were presented through the semantic domain and the phenomenon of honorific expression. Second, “-negau” and “-himanghada,” sentence constructions with a bi-clause sentence structure exhibit syntactic structures known as control and raising structures, depending on the functional characteristics of the sentence. The phenomenon of meaning interpretation of idiomatic expressions examined such conclusions. Third, the Japanese “-negau” and Korean “-himanghada” sentence constructions exhibit surface-level characteristics of the mono-clause sentence structure. This was suggested through the cleft sentence phenomenon that appears in the “-negau” and “-himanghada” sentence constructions. The results of the study, as described above, can be considered a universal characteristic that can be applied to other hopeful verb phrases found in Japanese and Korean.
K(OIM) - A New Model of Creativity Based on the Concept of Knowledge Clusters

The World Economic Forum states that by 2025, the top five skills employers will be looking for are innovation, complex problem-solving, critical thinking, creativity, and originality.Looking at these qualities closely, one can argue that all these skills are somehow related to creativity itself.However, despite a myriad of publications, there are many myths and misconceptions about creativity.To date, there is no unique model that can assimilate all different views on creativity.The present work is an attempt to empirically create a new model of creativity called the "K(OIM) Model of Creativity".The concept of Knowledge Clusters, proposed by the author in his earlier work, is at the center of the K(OIM) model of creativity.The proposed creativity model is based on the three simple cognitive processes; O-observation, I-imagination, and M-manifestation operating under the influence of K-knowledge clusters.The author suggests that the knowledge clusters corrupt an individual's observation, limit the imagination, and inhibit the manifestation process and that the crux of creativity lies in the individual's ability to control these knowledge clusters.The greater the control over knowledge clusters, the better is the creativity of individuals.The author further suggests that the creative contribution happens in five ways based on different combinations of stock of knowledge and knowledge clusters.Based on this, the difference between scientific and technical creativity (which comes from implicit knowledge), artistic and literary creativity (which comes from social knowledge and the knowledge clusters) and managerial creativity (which comes from the ability to effectively control knowledge clusters) has been explained for the first time in this paper.
Disciplina positiva como modelo para la mejora del comportamiento escolar de estudiantes de básica superior dirigidos por practicantes

Discipline control is one of the most important processes of teaching work, especially during their formative stage, since it is here that they acquire sufficient practical bases to cope with school behavior during their careers. Faced with the problem of discipline and behavior, it is proposed to use the positive discipline model to generate behavior changes in students who are in charge of teaching practitioners, which generate long-term attitudes consistent with the successful teaching process. . The main objective of our work is to analyze the influence of the use of positive discipline strategies, in the control of the school behavior of upper basic students of a public school in the north of Quito (Ecuador), where the members of the the sample. The results show that both for the experimental group and for the control group, the perception of school behavior is modified at the end of the investigation to show a substantial improvement in school behavior. It is concluded that positive discipline is correctly constituted in a set of strategies that allow modifying behaviors and improving school discipline.
Hybrid Model for Sentiment Analysis of Bitcoin Prices using Deep Learning Algorithm

Bitcoin is a decentralized digital currency, which is not controlled by a single authority or government. Bitcoin uses blockchain technology to verify transactions and guarantee user security and privacy. The fluctuating value of bitcoin is influenced by opinions that develop because many people use these opinions as a basis for buying or selling bitcoins. Knowledge to find out the market conditions of bitcoin based on public opinion is very necessary. This study aims to develop a hybrid model for bitcoin sentiment analysis. The dataset used came from comments on the Indodax website chat room, as many as 2890 data were successfully collected, then do data preprocessing, translate to english, text labeling and used hybrid parallel CNN and LSTM using word embedding glove 100 dimensions. Results of the experiments conducted, at 90:10 data splitting and 100 epochs is the best model with 88% accuracy, 86% precision, 78% recall and 81% f1-score, while the classification of opinion text comments on indodax chat results in 64.22% neutral comments, 21.14% positive comments and 14.63% negative comments. Based on research results, use of a parallel hybrid model provides a high accuracy value in classifying text, from these results positive comments are more than negative so that investors are advised to buy bitcoins.&#x0D;
CGC-Net: A Context-Guided Constrained Network for Remote-Sensing Image Super Resolution

In remote-sensing image processing tasks, images with higher resolution always result in better performance on downstream tasks, such as scene classification and object segmentation. However, objects in remote-sensing images often have low resolution and complex textures due to the imaging environment. Therefore, effectively reconstructing high-resolution remote-sensing images remains challenging. To address this concern, we investigate embedding context information and object priors from remote-sensing images into current deep learning super-resolution models. Hence, this paper proposes a novel remote-sensing image super-resolution method called Context-Guided Constrained Network (CGC-Net). In CGC-Net, we first design a simple but effective method to generate inverse distance maps from the remote-sensing image segmentation maps as prior information. Combined with prior information, we propose a Global Context-Constrained Layer (GCCL) to extract high-quality features with global context constraints. Furthermore, we introduce a Guided Local Feature Enhancement Block (GLFE) to enhance the local texture context via a learnable guided filter. Additionally, we design a High-Frequency Consistency Loss (HFC Loss) to ensure gradient consistency between the reconstructed image (HR) and the original high-quality image (HQ). Unlike existing remote-sensing image super-resolution methods, the proposed CGC-Net achieves superior visual results and reports new state-of-the-art (SOTA) performance on three popular remote-sensing image datasets, demonstrating its effectiveness in remote-sensing image super-resolution (RSI-SR) tasks.