Reviewerly/exHarmony huggingface dataset:
Pemberdayaan Generasi Z Dalam Pengolahan Sampah Organik Untuk Mewujudkan Desa Sehat Ramah Lingkungan

Generation Z is able to have great characteristics and potential to improve their environment which has been damaged by individuals who do not want to protect their own environment. Based on data obtained from the 2020 Waste Management Information System (SIPSS), Bondowoso Regency produces 287.18 tonnes/day of waste. Tangsil Kulon Village is one of the villages in Bondowoso Regency which is also a waste producing area. This increase in waste generation can be overcome by processing waste in several ways, one of which is using the help of Black Soldier Fly (BSF) fly larvae, namely maggots. Community empowerment methods are fully implemented in the field, namely using community education and training methods. This activity was carried out in the context of realizing Tangsil Kulon Village as a Healthy, Environmentally Friendly Village, which was carried out through community counseling and empowerment, namely using community education methods and training and direct practice with assistance from activity facilitators. The results of the activity showed that there was an increase in understanding and skills of the first target regarding how to process inorganic waste using the waste bank method, which was 13.99%, then the second regarding processing organic waste with maggots, namely 5.27%, and the third regarding making fertilizer. compost, namely 10.53%
Efforts to improve information system-based residents administration services

The aim of community service at Rukun Warga 06, Antapani Wetan Subdistrict, Bandung City is to provide information system facilities to enhance the efficiency of activities related to managing residents administration. This administration involves the issuance of certificates for various purposes, ensuring transparency in residents' contributions, and providing a platform for reporting community problems or aspirations. The method employed in this service begins with problem identification, analysis to prioritize urgent needs, system development, and outreach to gather feedback from users for evaluation. The result is improved efficiency in residents administration management, enhanced transparency in contributions, and simplified reporting of problems or aspirations.
Preparing for the future: Enhancing financial literacy for elementary school students

Shopping is a normal behavior for meeting needs. However, when spending activities lead to consumptive behavior, it can have a negative impact on one's financial management. Based on observations, many parents of students at SDI Sutojayan have expressed concerns about their children's consumerist behavior. This community service aims to enhance children's financial literacy, covering financial sources and money management. The program is implemented in several stages, including the creation of educational teaching aids, financial literacy counseling, and evaluation. The program's results indicate an improvement in children's understanding of money appreciation, as they become aware of the money's origins. The use of educational teaching aids has enhanced their comprehension of how to manage money, whether it's for shopping, charitable activities, or saving.
Autonomous Cargo Carrier Robot in GPS Denied Indoor Environment

The mobile robot industry, which has become a rapidly growing sector, can easily perform many activities or tasks that can be dangerous, laborious or tiring for humans. A mobile robot helps people by performing the desired tasks in areas such as medical, military, household and cargo. Robots, which perform their duties indoor or outdoor environments, use navigation systems to reach the desired destination. While the global positioning system is generally used in the external environment, different navigation methods are used in the indoor environment. The accuracy of navigation is of great importance when passing through complex, narrow and obstructed roads while going to the relevant target location in the indoor environment. In this study, a cargo carrier robot that can autonomously travel to a location determined by the user in indoor conditions has been developed. After the target point is determined, the cargo vehicle takes action automatically from the starting point, and continuously detects location in order to reach the target with the compass sensor on it. Ultrasonic sensors have been used so that the cargo vehicle can continue to move without hitting any object that may come in front of it while it is going to the target location. A mobile application has been developed to give the destination location of the cargo vehicle and to follow the vehicle. The movements of the autonomous vehicle are controlled by the commands sent via Bluetooth.
Persistence, vision, networks, collaboration - leadership in information retrieval research

The library and information science community has its share of inspirational research pioneers building a corpus of knowledge to influence and construct the future. Intuitive search interface design, the psychology and mechanics of information retrieval and information seeking behaviour are key development priorities. In December 2021, Ian Ruthven, Professor of Information Seeking and Retrieval at the Department of Computer and Information Sciences, University of Strathclyde, presented the seventh annual Strix Memorial Lecture entitled: ‘Google’s what you use when Alexa doesn’t know the answer, Uncle Ian.’ It was inspired by an innocent comment made by his young niece. People create their own models of how information works for them. Information seeking behaviour is social and shaped by life, so there are infinite iterations of queries and limitless perceived solutions to perceived problems. We explore Ian’s work and his observation that there is so much potential to progress research by placing information seeking and retrieval within the broader societal and cultural framework of what people or populations want from or do with information.
Research on the Application of Computer Control Technology in Electronic Circuits

This article mainly studies the application of computer control technology in electronic circuits, analyzes the work efficiency of computer control technology from the actual situation, and attempts to find the entry points for upgrading computer control technology. This is of great significance for improving the performance and reliability of electronic circuits, achieving automation and intelligent control, improving work efficiency and product quality, and other aspects. Through research, it has been found that computer control technologies supported by different core technologies have different applicable ranges and functional advantages. For example, computer control technology based on microcontroller regulation has advantages such as high integration, small size, low power consumption, high reliability, and strong programmability. However, system design and debugging are difficult, computing power is limited, and scalability is limited. It is mainly suitable for industrial control, computer networks, and communication fields.
The study of unreported igneous body, and its economic interest at Abu Zerriq area, north AlKufrah region, SELibya

This research deals with mineralogical and petrological investigation of an igneous intrusion located atAbu Zerriq area, with a distance of about 160 Km north to Al Kufrah town. Although the occurrence ofigneous activities has not been reported before in this area, field inspections, followed by examinationof thin sections under polarized microscope, have shown that this outcrop represents an igneousintrusion that comprises concentric rings of basalt and rhyolite. The basalt mainly is composed of lathsof calcic plagioclase, relicts of altered olivine (partly serpentinized), quite abundant pyroxene crystals,and needle-like and anhedral opaque mineral (probably ilmenite). The economic interest of these rocksas a source of aggregates for construction is an important objective in this study. In order to determinethe compressive strength of the rock samples, rock strength tests have been carried out. The results ofthese tests indicate that the studied rocks have high compressive strength, and they are muchrecommended for the purpose of civil constructions. The relatively large size of the material in thisigneous body, and its close proximity to the constructed road, considerably increase its mining interest.
2019 Tony Kent Strix Memorial Award Winner

In 2019, the UK electronic information Group (UKeiG), in partnership with the International Society for Knowledge Organisation UK (ISKO UK), the Royal Society of Chemistry Chemical Information and Computer Applications Group (RSC CICAG) and the British Computer Society Information Retrieval Specialist Group (BCS IRSG), was delighted to announce that the winner of the prestigious Tony Kent Strix Memorial Award for 2019, in recognition of his major and sustained contributions to the field of information retrieval, was Professor Ingemar J. Cox, Department of Computer Science at University College London.&#x0D; Professor Cox is Head of UCL’s Media Futures Research Group and a Professor at the Department of Computer Science at the University of Copenhagen. His current research interests include information retrieval and data analytics of online social media, twitter and query logs.
Reinforcement Learning Guided Spearman Dynamic Opposite Gradient-based Optimizer for Numerical Optimization and Anchor Clustering

Abstract As science and technology advance, the need for novel optimization techniques has led to an increase. The recently proposed metaheuristic algorithm, Gradient-based optimizer (GBO), is rooted in the gradient-based Newton's method. GBO has a more concrete theoretical foundation. However, GSR and LEO operators in GBO still have some shortcomings. The insufficient updating method and the simple selection process limit the search performance of the algorithm. In this paper, an improved version is proposed to compensate for the above shortcomings, called RL-SDOGBO. First, during the GSR phase, the Spearman rank correlation coefficient is used to determine weak solutions on which to perform dynamic opposite learning. This operation assists the algorithm to escape from local optima and enhance exploration capability. Second, to optimize the exploitation capability, reinforcement learning is used to guide the selection of solution update modes in the LEO operator. RL-SDOGBO is tested on 12 classical benchmark functions and 12 CEC2022 benchmark functions with seven representative metaheuristics, respectively. The impact of the improvements, the scalability and running time of the algorithm, and the balance of exploration and exploitation are analyzed and discussed. Combining the experimental results and some statistical results, RL-SDOGBO exhibits excellent numerical optimization performance and provides high-quality solutions in most cases. In addition, RL-SDOGBO is also used to solve the anchor clustering problem for small target detection, making it a more potential and competitive option.
AI-assisted super-resolution cosmological simulations III: Time evolution

Abstract In this work, we extend our recently developed super-resolution (SR) model for cosmological simulations to produce fully time-consistent evolving representations of the particle phase-space distribution. We employ a style-based constrained generative adversarial network (StyleGAN) where the changing cosmic time is an input style parameter to the network. The matter power spectrum and halo mass function agree well with results from high-resolution N-body simulations over the full trained redshift range (10 ≤ z ≤ 0). Furthermore, we assess the temporal consistency of our SR model by constructing halo merger trees. We examine progenitors, descendants and mass growth along the tree branches. All statistical indicators demonstrate the ability of our SR model to generate satisfactory high-resolution simulations based on low-resolution inputs.
The Analysis of Economic Differences among Prefecture-level Cities in Hebei Province Based on K-means Clustering

The K-means clustering algorithm is applied to perform cluster analysis of 11 prefecture level cities in Hebei Province under six economic indicators such as analysis regional GDP, annual average salary, fiscal revenue, disposable income of rural residents, disposable income of urban residents, total volume of imports and exports. After standardizing the data from different regions in 2014 and 2019, the optimal number of clusters obtained through elbow method is four, which means that the 11 prefecture level cities are divided into four classes: economically developed areas, relatively developed areas, moderately developed areas, and underdeveloped areas. It is shown that Tangshan, Langfang, and Baoding have risen from the second, third, and fourth class to the first, second, and third class, respectively. Finally, an analysis of economic differences is conducted for different classes of regions, and relevant suggestions is provided based on the classification of economic development characteristics in each region.
RELEVANSI EVALUASI PENGELOLAAN DAERAH IRIGASI TALAWAAN MERAS PROVINSI SULAWESI UTARA

AbstractThe objectives of this research were:: 1) to obtain information about evaluationin the Talawaan Meras Irrigation Area, 2) To evaluate the Management of IrrigationNetworks in the Talawaan Meras Irrigation Area. This research was carried outdirectly in the field and data collection was carried out using survey methods andinterviews with several selected respondents, as well as measurement/calculation ofthe characteristics of variables related to irrigation networks carried out directly onthe research object. The conclusions from this study are (1) The research location ofMS.3.Kr, which was originally 20 ha for rice fields, now the designation is no longerrice fields, but inland fisheries. (2) Measurement of water discharge in the secondarychannel at the MS.3.Kr location uses the float method, and the average dischargeobtained is 0.16 m^3/second. (3) The existing irrigation structures in the TalawaanMeras Irrigation Area are all in good condition and can function properly. (4) Theplanting season determined by the Agriculture Service is not in accordance with thefacts on the ground. (5) In the last 2 years, performance evaluation in the TalawaanMeras Irrigation Area on MS.3.Kr has not been carried out properly due to a lack ofoperational funds. Funds that should have been there have been focused on Covid-19funds. (6) There are 9 irrigation network officers in Talawaan Meras, but not all ofthem are active. At the MS.3.Kiri location, there is only one irrigation network officerwho has taken over all the tasks at that location.Keywords : evaluation, irrigation area management, Talawaan Meras
A quantum segmentation algorithm based on background-difference method for NEQR image

Quantum image segmentation algorithm can use its quantum mechanism to rapidly segment the objects in a quantum image. However, the existing quantum image segmentation algorithms can only segment static objects in the image and use more quantum resource(qubit). In this paper, a novel quantum segmentation algorithm based on background-difference method for NEQR image is proposed, which can segment dynamic objects in a static scene image by using fewer qubits. In addition, an efficient and feasible quantum absolute value subtractor is designed, which is an exponential improvement over the existing quantum absolute value subtractor. Then, a complete quantum circuit is designed to segment the NEQR image. For a ${2^n}$$\times$${2^n}$ image with gray-scale range of [0,$2^q$-1], the complexity of our algorithm is O($q$), which has an exponential improvement over the classical segmentation algorithm, and the complexity will not increase as the image's size increases. The experiment is conducted on IBM Q to show the feasibility of our algorithm in the noisy intermediate-scale quantum (NISQ) era.
PERFORMANCE TESTING ON WEB INFORMATION SYSTEM USING APACHE JMETER AND BLAZEMETER

The Abiansemal Bali Global Vocational School Teacher Information System is a web-based application that makes teachers' work easier, which is the implementation of applied science in the field of technology. As the number of teachers increases, server performance needs to be evaluated to ensure it can handle requests from each teacher. This research tested the performance of an Information System Website using two tools, namely Apache JMeter and BlazeMeter. This test includes four modules: login page, updating teacher profile, uploading images, and creating questions. Testing uses 50 and 100 samples with a ramp-up period of 10 seconds and several loops of 1. Test results show that the system works well on these modules, with a stable average response time, increased throughput, and decreased deviation. This information reveals system performance and can help make improvements and optimizations to improve the speed and quality of the user experience. Performance testing with Apache JMeter and BlazeMeter is a useful method for testing the performance of web-based information systems.
Integrated CNN and Waterwheel Plant Algorithm for Enhanced Global Traffic Detection

Traffic detection is critical in ensuring road safety and efficient traffic management, demanding deploying accurate and practical algorithms. This research explores the fusion of Convolutional Neural Networks (CNNs) and the Waterwheel Plant Algorithm to augment global traffic detection capabilities, utilizing a diverse dataset primarily collected from Turkey. A comprehensive evaluation of prominent CNN architectures, such as VGG19Net, AlexNet, ResNet-50, GoogLeNet, and a generic CNN, underscores substantial efficacy, with the CNN achieving an accuracy of 92.14%. Introducing the Waterwheel Plant Algorithm (WWPA) further enhances performance, as exemplified by the hybrid WWPA-CNN model, exhibiting an impressive accuracy of 97.28%. These findings highlight the promising synergies between traditional optimization algorithms and advanced neural networks, showcasing the potential for innovative developments in traffic monitoring systems and broader applications within computer vision. The statistical analyses, encompassing ANOVA and the Wilcoxon Signed Rank Test, robustly underscore the significance of this integrated approach. As the research contributes to the evolution of traffic monitoring systems, these insights provide a solid foundation for advancements in the field, fostering innovation and shaping the future landscape of computer vision applications.
Determinants of Contact Tracing Apps: An Adoption Study Using UTAUT Model

In the aftermath of the coronavirus (COVID-19) outbreak that impacted human lives globally, a contact tracing app was introduced to control and ease tracking processes via smartphone-based to track positive cases and potential contacts. Major concerns about trust, personal information leakage, and data privacy stored in the system would reserve citizens' willingness to adopt and use the technology. This study focuses on the adoption of contact tracing mobile apps in looking at the key determinants influencing user’s acceptance. An extended Unified Theory of Acceptance and Use of Technology (UTAUT) model was used in this study. A cross-sectional online survey was conducted between September and October2021 and Partially Least Squares (SmartPLS) was used to evaluate about 400 users in Malaysia. The findings revealed that 50.9 % in behavioural intention to adopt a contact tracing app. The highest acceptance rate was among users aged 26 to 35. Effort expectancy was the most important predictor, followed by performance expectancy, perceived risk (of COVID-19), social influence and perceived credibility. Sustainable usage among the users were also being discussed to avoid abundant or inexhaustible use of mobile apps especially relates to health concerns and to prepare for potential new pandemics, such as "Disease X", which were characterised by more infectious and dangerous diseases outbreaks. Keywords: Contact tracing apps (CTAs), Corona virus (COVID-19), Intention to adopt, use of technology, UTAUT.
A Proposed Text Encryption inside Video Using Harris Corner Detection and Salas20 Encryption Algorithm

Text encryption in video is a vital tool in many industries where protecting sensitive information is of highest concern. Algorithms and automated detection methods commonly struggle to locate hidden text in video frames. This resistance increases the security of the concealed information because it is challenging for uninvited parties to detect the presence of encrypted text. This research suggests a novel method for text encryption inside video utilizing the Salsa20 encryption algorithm and Harris Corner Detection. The goal of this study is to increase the secrecy and security of textual information that is embedded in video content. First step is locateing important corners or spots inside the video frames, the Harris Corner Detection method is first used. These corners act as strong feature points that can be used to incorporate text. Without degrading the video's overall visual quality, the Harris Corner Detection method aids in precisely localizing the places where text may be concealed. Second, the encryption key is generated using the Salsa20 encryption technique. Salsa20 is a popular stream cipher that offers reliable encryption and effective operation. The embedded text is converted into a cipher text by XOR it with the encryption key before embedding it in the video, guaranteeing its confidentiality and protecting it from unauthorized access. Comparing the suggested method to current text encryption methods reveals a number of advantages. The Harris Corner Detection technique integrates text into video frames so that it blends in less noticeably, making it more difficult for adversaries to identify the existence of hidden information. Salsa20's use further guarantees the encrypted text's high level of security and protection, defending it against potential attacks. The proposed system is evaluated using MSE, PSNR, correlation, NPCR, UACI and entropy, these evaluation metrics provide excellent results.
Empowering Seventh-Grade Students with Crossword Puzzle for Vocabulary Mastery

Students often struggle with mastering vocabulary in their English learning journey, necessitating English teachers to seek solutions. One viable strategy teachers can adopt is the integration of crossword puzzles to enhance students’ vocabulary mastery. Specifically, the study sought to determine if providing crossword puzzles to the SMP Negeri 3 Banawa seventh-grade students could enhance their vocabulary proficiency. To measure the impact of this approach, the researcher employed pre-test and post-test assessments as evaluation tools in a quasi-experimental study. Through purposive sampling, the researcher selected two classes, VII B and VII D, each with 29 students, as the study’s sample groups. Subsequently, data analysis revealed a significant disparity between the pre-test and post-test scores in the experimental class. Notably, the computed p-valued (two-tailed) was 0.000, falling below the predetermined significance level of 0.05, signifying the acceptance of the hypothesis. In conclusion, implementing the crossword puzzle in this study led to a noticeable improvement in the vocabulary mastery of seventh-grade students at SMP Negeri 3 Banawa.