Reviewerly/exHarmony huggingface dataset:
Energy-Efficient Change Detection Approach Based on Approximate Computing

The process of image change detection involves the identification and examination of variations or disparities within an image when compared to one or more other images. This method finds extensive application across diverse domains, such as video surveillance, environmental monitoring, and the analysis of satellite imagery. Within the framework of this research paper, we introduce an image change detection technique centered on Discrete Cosine Transform (DCT) with an emphasis on frequency analysis. Our approach introduces two distinct variants of approximate DCT, namely, the coefficient-optimized ADCT-C and the further pixel-optimized ADCT-P. The experimental findings unveil compelling advantages, with the approximate ADCT-C demonstrating a notable reduction of 60.86% in area requirements and a 64.77% decrease in power consumption when contrasted with the precise DCT. Furthermore, we employ the proposed approximate DCT variants in tandem with the change detection algorithm presented in this paper. Comparative evaluations with alternative approximate DCT methods highlight the efficacy of our approach. Notably, ADCT-C outperforms its counterparts across all three image tests, exhibiting the highest Peak Signal-to-Noise Ratio (PSNR) values.
Mitigating the Negative Effect of Telepresence Robots via an Empathy-Eliciting Robot Moderator

Despite various advantages that telepresence robots offer in mediated interaction, the users of these robots have been found to be perceived as less trustworthy compared to their communication partners who are physically present (i.e., collocated participants) in multiparty interaction contexts [1]. In this study, we investigate whether an empathy-eliciting behavior of a social robot moderator can affect the way the personality of telepresence robot users is judged by their collocated partners. In a within-subject design, middle school students (N=48) were put into groups of three - two onsite and one via a telepresence robot - and were instructed to complete an escape room moderated by a social robot. In addition to facilitating the experiment session, the robot moderator asked a question which was aimed at creating empathy toward the telepresence robot operator. We collected data on the perceived personality of participants via two questionnaires, one before and one after the empathy-eliciting question. The analysis of the data shows that following the empathy-eliciting intervention, collocated participants rated telepresence robot pilots as significantly more trustworthy and less tense, irritable, shy, and faultfinding. Furthermore, remote participants rated collocated students as significantly more trusting and outgoing, and significantly less tense. Moreover, the robot moderator was regarded as more desirable after it made the intervention. The findings suggest that not only does the empathy-eliciting question improve the way the personality of telepresence robot pilots is judged by collocated participants, it also improves how remote participants judge the personality of their teammates.
Proof of Concept of Using HoloLens 2 for AR Immersive Training in Complex Medical Scenarios

This study proposes a preliminary new simulation approach using an immersive AR device for medical and paramedical complex training scenarios in hospital and pre-hospital tasks as a substitute for the current real and virtual simulations. The simulation activities selected for testing the proposed AR-based approach consist of: 1) setting up an operating room for an Endovascular Aneurysm Repair intervention for evaluating the interactions between the user and virtual objects; 2) navigating a road accident scenario for evaluating the integration between real and virtual objects. The results of the first trials show that the application maintains, from a standstill position, 60 fps as suggested by Microsoft to provide the best experience possible. Moreover, the results of a users' study, involving 11 subjects, show good responses about realism and fusion between real and virtual objects, usability and interactions, and immersion in the scenarios using the application.
Anomaly Detection Method Based on Gaussian Mixture Model and Orthogonal Generative Adversarial Network

In the analysis of power grid data, a critical task is to identify samples that significantly deviate from others, which constitutes anomaly detection. Presently, anomaly detection methods based on deep generative models face challenges related to complex network structures and difficult training processes. Addressing these issues, this paper proposes a lightweight anomaly detection method for power grid data based on Gaussian Mixture Model and Orthogonal Generative Adversarial Network. This approach combines traditional statistical techniques with advanced deep learning methods. In comparison to anomaly detection methods relying solely on deep generative models, this method features a more concise network structure, reducing both the model's complexity and training time, while retaining a certain level of expressive power.
Research on Power Security Management and Control System Based on Big Data Algorithm and Internet of Things Technology

Safety has always been the eternal theme of power grid construction and development. State Grid Corporation always puts safety in production at the top of all its work. In order to adapt to the promotion of national economy and the development of State Grid Corporation, it is necessary to ensure the safe and stable operation of the national power supply system and reliable power supply for the people. How to implement effective management and control, achieve comprehensive coverage of production site safety supervision in the jurisdiction and its subordinate jurisdictions, avoid supervision blind spots, and realize remote supervision anytime and anywhere is a problem worthy of discussion. In this paper, the simulation data show that the safety management system designed in this paper has a lower risk coefficient of field operation than the initial system, which can effectively ensure the safety of field workers and instruments. There are inherent disadvantages such as poor global coordination, lack of active early warning, and lag of system fusion data. It has obvious advantages in stability, autonomy of management and control, accuracy of early warning, and intelligence of operation and maintenance in extreme environments. Through big data algorithm and Internet of Things technology, the differentiated power safety management and control needs of power companies can be met, which has good popularization and application value.
Simulation Analysis of Seismic Model of Building Structures Based on Hybrid Intelligent Algorithm

In today’s modernization, although there are few casualties under the earthquake, the economic losses are huge. Performance-based seismic design method can select performance targets according to the engineering site conditions and the importance of building structures, and realize the performance targets quantitatively in the design. In this paper, a method for predicting the seismic performance of frame structures based on uniform deformation and hybrid intelligent algorithm of differential evolution (DE) and particle swarm optimization (PSO) is proposed, and the iterative calculation of bending-shear frame structures with different floors is carried out, so that the high-precision uniform deformation optimization design is realized and the optimal stiffness distribution law of structural floors is obtained. The running performance of the algorithm is simulated and analyzed through experiments. Compared with the existing research results, it is verified that the established empirical function has high accuracy, which can provide accurate and effective reference for structural optimization design oriented to uniform deformation and improve calculation efficiency. optimizing the design of building structure can not only make the design scheme meet the requirements of seismic code, but also ensure that the important performance indexes of the structure are optimal or better, thus realizing the performance-based seismic design concept.
Analisis Sistem Pemantauan Pemisah Sampah Logam dan Non Logam berbasis Internet of Things

&lt;p&gt;&lt;em&gt;Waste has become a serious problem, especially in big cities, not only in Indonesia but also around the world. Waste production continues to increase along with population growth, and changes in consumption patterns and people's lifestyles have increased the amount of waste, the type, and the diversity of waste characteristics. Waste bins are infrastructure available in every city park that makes it easier for park visitors to dispose of waste. make it easier for park visitors to dispose of waste. In some places, There are no bins based on the basic material of the waste, namely metal bins and non-metal bins that can be monitored in real-time. So a smart trash can is made that can sort metal or non-metal waste that can be monitored in real-time with the Internet of Things. The hardware used is Metal Proximity Sensor, Infrared Sensor, Servo Motor, Ultrasonic Sensor, MQ135 Gas Sensor, and ESP32 Microcontroller. The capacity in the trash can be monitored through the Blynk application, which will provide notification when the trash can is full. Based on the test results of the volume reading of the trash can, the success of the sensor to open and close is 99.26%. To sort non-metal waste and metal waste using proximity sensors with the results of testing the reading of waste objects obtained success in non-metal waste by 95% and metal waste by 100%.&lt;/em&gt;&lt;/p&gt;
Speech Recognition pada Kontrol Gerak Tangan Bionik berbasis Raspberry Pi dan Arduino

&lt;p&gt;&lt;em&gt;The bionic hand is a broad bio-mechatronic device that incorporates various concepts involving biology and mechatronics. In this journal, the authors research finger movements in bionic hands using voice commands. In designing this bionic hand, the author made a mechanical design using a 3D printing machine. The hardware design used by the Raspberry Pi to process voice data is then transmitted to Arduino to carry out servo movement commands so that it can move bionic fingers. Software design uses the Python language using the Google text-to-speech API. From this research, data was generated with 100% accuracy. The movement of bionic fingers moves according to the commands spoken.&lt;/em&gt;&lt;/p&gt;
WATER INFRASTRUCTURE IN ANCIENT CITY OF TROWULAN MAJAPAHIT. A LESSON FROM THE PAST FOR PLANNING A NEW CAPITAL CITY OF INDONESIA

Indonesia plans to move its capital city from Jakarta on the island of Java to a jungle city on the island of Borneo called Nusantara. However, a large sceptical arose when planning a smart and sustainable city from scratch. This paper examines in a broad manner of water infrastructure situation during the ancient period of Indonesia, Majapahit period from the historical literature. The present paper aims to show the water management and sanitation practices from Trowulan peoples which have survived and managed their civilization in harmony with nature over a century. The results suggest that water infrastructure in Trowulan city not only used for agricultural purposes (irrigation) but also used for environmental protection such as drainage and flood control. We believe by reconsidering the historical approaches to water management of Trowulan people and applying modern technologies to improve its functionality is expected to give a solution to current water-related environmental problems in Nusantara the new capital city of Modern Indonesia.
Pemilihan Algoritma Machine Learning Yang Optimal Untuk Prediksi Sifat Mekanik Aluminium

&lt;em&gt;This study designs and compares optimal machine learning models to predict the mechanical properties of aluminum, including Yield Strength (YS) and Tensile Strength (TS), based on the percentage composition of aluminum's chemical elements. The machine learning modeling in this study has nine input variables consisting of aluminum chemical elements such as Al, Mg, Zn, Ti, Cu, Mn, Cr, Fe, Si, and two output or target variables consisting of YS and TS. Additionally, Heatmap correlation is used to observe the correlation between chemical elements and the mechanical properties of aluminum. Three machine learning algorithms, namely Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN), are compared in this study. The comparison of these algorithms shows that Random Forest (RF) outperforms the other algorithms in predicting YS with MAE of 11.44, RMSE of 14.282, and R value of 0.93. On the other hand, ANN performs better in predicting TS with MAE of 19.593, RMSE of 22.005, and R value of 0.947.&lt;/em&gt;
KINERJA OJEK ONLINE DAN KONVENSIONAL DI KOTA KENDARI

This study aims to measure the performance of two-wheeled public transportation, online and conventional motorcycle taxis. Snowballing technology penetrates the transportation sector and provides convenience and flexibility at users' fingertips. Users are faced with a choice of online and conventional transportation that still survives today. Using the perception assessment approach, the Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) methods use a Likert rating scale for users who use online motorcycle taxis and conventional motorcycle taxis. There are five variables: Tangible, Reliability, Responsiveness, Assurance, and Empathy. The results show that CSI for online motorcycle taxis has a value of Very Satisfied to Satisfied. In contrast, for conventional motorcycle taxis, there is a variable with a value of Very Dissatisfied, namely Reliability, and Assurance has a value of Fairly Satisfied. Other than that, it's worth Very Satisfying. The IPA method describes these variables into 56 attributes, detailed in 11 attributes in Quadrant I, namely the Top Priority category, and 17 attributes in Quadrant II, namely Maintain Achievement. The others are included in Quadrants III and IV with low importance. Abstrak Penelitian ini bertujuan untuk mengukur kinerja angkutan umum roda dua, ojek online dan konvensional. Penggunaan teknologi yang berkembang pesat merambah hingga ke sektor transportasi dan memberikan kemudahan serta fleksibilitas di ujung jari pengguna. Pengguna dihadapkan dengan pilihan akan transportasi online maupun konvensional yang masih bertahan hingga kini. Dengan pendekatan penilaian persepsi metode Customer Satisfaction Index (CSI) dan Importance Performance Analysis (IPA) menggunakan skala penilaian Likert terhadap masyarakat pengguna yang menggunakan ojek online dan ojek konvensional. Terdapat 5 variabel yaitu: Tangible, Reliability, Responsiveness, Assurance, dan Empathy. Hasil menunjukkan bahwa CSI untuk ojek online bernilai Sangat Puas hingga Puas, sedangkan untuk ojek konvensional terdapat variabel yang bernilai Sangat Tidak Puas yaitu Reliability, dan Assurance bernilai Cukup Puas. Selain itu bernilai Sangat Puas. Metode IPA menjabarkan variabel tersebut ke dalam 56 atribut, yang terinci pada 11 atribut dalam Kuadran I yaitu kategori Prioritas Utama, 17 atribut dalam Kuadran II yaitu Pertahankan Prestasi. Adapun lainnya masuk dalam Kuadran III dan IV dengan kepentingan rendah.
ANALISA PENGAMBILAN KEPUTUSAN UNTUK MENENTUKAN SUBKONTRAKTOR SPESIALIS DENGAN METODE TOPSIS

ABSTRACT&#x0D; The building construction sector is a complex industry, so it is necessary to split the work and divide (deliver) it to subcontractors. In determining these subcontractors, stakeholders are faced with many and various methods in making decisions so that the selection of subcontractors can be determined optimally. This study analyzes and compares the two MADM TOPSIS methods. This research takes a case study of the subcontractor selection process carried out by the main contractor at PT. Cipta Griya Semesta. This study consists of 4 alternative subcontractors with 6 assessment criteria with the criteria of general aspects, financial aspects, technical aspects, managerial aspects, work safety aspects and reputation aspects. Based on the ranking results using these 2 methods, subcontractor D will be selected to help carry out the ongoing project.&#x0D; Keyword: Topsis, Subcontractor, Construction
Unveiling the Shadows: A Comprehensive Exploration of Advanced Persistent Threats (APTs) and Silent Intrusions in Cybersecurity

The advent of Advanced Persistent Threats (APTs) and quiet intrusions, which are covert attacks, poses a severe challenge to the modern cybersecurity environment. This thorough study aims to shed light on the intricate world of APTs by exploring several topics, including attack methods, difficulties in detection, and the constantly changing patterns that influence the landscape of digital threats. The foundation of our inquiry is a thorough review of the literature, which makes it possible to identify critical knowledge gaps. Examining past APT efforts provides a crucial background for understanding how these advanced cyber threats have developed. The research approach is described in total, covering techniques, instruments, and strict case study requirements. This creates a solid foundation for an in-depth and perceptive analysis of silent incursions. It paves the way for a thorough investigation and promises a sophisticated comprehension of APTs, their tactics, and the difficulties in identifying and lessening their effects. This study's combination of a detailed research methodology, historical context, and a literature review positions it as a valuable contribution to cybersecurity
Transformation of Economic Education (Bibliometric Analysis)

This study aims to identify trends in economic education research as a reaction to the dynamics of changing economic phenomena, which are key topics for economic education discussions. Economic education must change to address concerns with the changing demands for economic education in terms of graduate competencies, employment prospects, and community needs. Trend analysis is conducted by bibliometric analysis to meet this objective. The technique used is bibliometric analysis, which involves four stages: establishing the goal and scope of the study, choosing the appropriate bibliometric analysis tools, gathering data for analysis, and finally conducting the analysis and summarizing the results. The data source comes from the Google Scholar database which is collected through the Publish or Perish application using a combination of the keywords economic education, entrepreneur education, and job prospects. Data are in the form of articles published in journals and proceedings for 2017-2022. A total of 1,458 data were selected to become 1,390 data for analysis. The analysis technique used is a performance analysis and network analysis using the VOS Viewer application. The results of the performance analysis show that many studies on economics education have been published in reputable international journals and have received high citations.
Pemberian Reward dan Punishment untuk Meningkatkan Minat dan Motivasi Belajar Siswa pada Mata Pelajaran Kearsipan Kelas X OTKP SMK Al Washliyah 9 Perbaungan

The purpose of this study is to understand how to increase student motivation and achievement at the X-level math and tata kelola perkantoran in SMK Swasta Al Washliyah 9 Perbaungan by using rewards and sanctions. This study is a PTK (penelitian tindakan kelas) study. This investigation is conducted in two steps, with each step consisting of perencanaan, tindakan execution, observation, and refleksi. The subjects of this study are the 19 students in the SMK Swasta Al Washliyah 9 Perbaungan's Grade X Otomatics and Tata Kelola. Summary data is derived from the number of students, teachers, and available school-related documents. Data collection methods include reviewing observation, testing, documentation, and wawancara results. Method for data validity using method for triangulating set of data. In contrast, data analysis employs scribal and quantitative methods of analysis. According to the results of the study, it can be concluded that using a reward and punishment system can increase student motivation and engagement in the X OTKP class at SMK Swasta Al Washliyah 9 Perbaungan.
Implementasi Program Literasi terhadap Eskstrakkulikuler di MTSN 2 Medan

This study aims to explain the condition of the extracurricular literacy program at MTSN 2 Medan. In addition, it also explains the effectiveness and constraints that occur in the development of this literacy program at MTSN 2 Medan. This research uses descriptive qualitative research. This study provides an overall picture of the conditions, effectiveness, and obstacles that occur in literacy programs. The results of the research show that the literacy program has not run optimally. Problems with the literacy program in learning Indonesian that occurred at MTSN 2 Medan included irrelevant learning strategies, the availability of inadequate and incomplete facilities and infrastructure, and students' low interest in reading. Sources of data in this study are documents and school implementation processes literacy program. The data in this study were collected using documentation, interviews and observation methods. The results of this study indicate that the governance of extracurricular literacy at MTSN 2 Medan is as follows (1) First, the school planning for the literacy program has been carried out by setting literacy goals for the school movement program. However, this planning has not been based on a needs analysis (2) extracurricular activities about Indonesian that have not been implemented at this school (4) the control that has been carried out is still limited to ensuring that the Thursday reading program is carried out or not. Controls to improve program quality have not been carried out. The management of the school literacy movement program needs to be managed properly, starting from the strategic planning process, organizing by giving job descriptions, implementing programs in accordance with strategic planning, and continuous evaluation&#x0D; Keywords Indonesian, Ekstrakulikuler, Program Literacy
Meningkatkan Keterlibatan Siswa di Kelas Menggunakan Model Pembelajaran Think Pair Share

There is still low student learning participation. There has not been an application of a learning model that attracts students and can foster active student learning participation and students also still find it difficult to understand the material being learned during learning. The data collection techniques used in this study were observation and documentation. Qualitative data analysis techniques to determine how much student learning participation has increased. In this Class Action Study, researchers plan 2 cycles of action using the Kemmis and Mc Taggart model research procedures. Kemmis and Mc Taggart's model research begins with planning then action, observation and reflection. The hypothesis in this study is that the use of the Think Pair Share learning model can increase student learning participationThe Think-Pair-Share strategy is a group discussion strategy which is a participatory pedagogic concept through social interaction, togetherness, and action-oriented communication explaining that TPS is a learning method developed by combining independent and group learning methods. With this TPS, students will be helped in changing the positive behavior in communication skills that occurs when they listen to each other and bring out mutual respect. Think Pair Share learning model activities can develop the thinking of individual students because of the thinking time, so that the quality of answers can also increase. By using the Think Pair Share type cooperative learning learning model, before discussing in groups, students try to think first, then discuss with their partners so that students already have material to bring in group discussions. This can be a strong factor in improving students' ability to respond to questions and foster an attitude of mutual help to each other. Thus, students will be actively involved in the learning process and can improve learning outcomes.&#x0D; Keywords: Author Guidelines; Journal Al-Kharaj; Article Templates