Reviewerly/exHarmony huggingface dataset:
A Literature Survey on Algorithms for the Optimal Load Balancing in Cloud Computing Environments

Abstract: This paper provides a survey of the existing literature and research carried out in the area of Optimal load balancing in servers. Load balancing in cloud computing is one of the important aspects for efficient delivery of resources and computing . The process of distributing workloads and computing resources in a cloud computing environment is cloud load balancing. It allows enterprises to manage application or workload demands by allocating resources among multiple computers, networks or servers. Hosting the distribution of workload traffic and demands that reside over the internet. It helps enterprises achieve high performance levels for very reasonable costs which is lower than traditional on premises load balancing technology . By taking advantage of clouds' scalability and agility cloud load balancing technology meets rerouted work demands and also improves overall availability. Load balancing can provide health checks for cloud in addition to the workload and traffic distribution .Performance analysis of different existing load balancing algorithms based on different parameters is to be carried out and the algorithm will be optimized for the better performance in cloud. The main purpose of the proposed paper will be to get help in the design of new algorithms in future.
Analisa Prediksi Varietas Buah Salak yang Sesuai dengan Lahan Daerah Kabupaten Banjarnegara Menggunakan Algoritma C45

Salak is a potential horticultural sector that is a leading commodity in Banjarnegara. Salak fruit varieties have fruit categories that have their advantages. Variants of salak fruit include ivory salak, granulated sugar salak, pondoh salak, and honey salak. Based on data released from the relevant government agencies, further research was carried out related to analyzing and conducting research to predict salak fruit varieties. This variety is suitable for land in every area in Banjarnegara with predictive analysis using the C4.5 algorithm. This method has been widely developed to classify and predict a case with a fairly high degree of accuracy. From this study, researchers hope that it can contribute farmers to determining the type of salak fruit that is most suitable for the land they own so that later the harvest obtained by farmers can be maximized
Pengembangan E-Learning Menggunakan PHP Native pada SMK Muhammadiyah 1 Padang

This study aims to measure the validity, practicality and effectiveness of web-based e-learning. This e-learning design aims to support the learning process so that teachers and students can more easily access teaching materials in the form of videos, images, and other files. This research uses research and development (R&amp;D) methods. The research model used is the ADDIE development model, with the design and development steps being Analysis, Design, Develop, Implementation and Evaluation. The research subjects were 30 students in the Department of Automotive Light Vehicle Engineering at SMK Muhammadiyah 1 Padang. Based on the results of the validity test conducted by the experts as a whole, it was 82.86% and it was interpreted that web-based e-learning was valid to be used. The results of the overall practicality test assessment of the practicality of web-based e-learning is 93.66%, so that the practicality level can be interpreted as very practical to use. The results of the effectiveness assessment test obtained a value of 95.60%, so that the level of effectiveness, which is interpreted as very effective, is used.
The Mix of Latin American Populist Constitutionalism

Abstract In this article, we study Latin American populist constitutions and their uses, seeking to analytically understand whether populist constitutionalism is, indeed, a thing. We posit that Latin American populist constitutionalism is a particular form of mixed constitutionalism in three senses: first, as a specific combination of substantive traits that includes both empowering and (some) constraining devices; second, as a peculiar politics of constitutional change that incorporates popular mobilization against pre-existing institutions as a key trait; and third, as a particular practice of constitutional enforcement that involves weak and selective implementation, often through institutional capture. By considering not only the texts of constitutions but also the ways in which they are changed and implemented, we hope to complement legal perspectives of mixed constitutions with a sociopolitical analysis of practices and contexts. By capturing the distinctive contribution of Latin American populism to the discussion of mixed constitutions, we seek to challenge both legal conceptions of constitutionalism that reduce it to negative or constraining features, and political conceptions of populism that simply equate it to authoritarian rule.
Spatial Mapping of Landslide Susceptibility Level in Pacitan District Using Analytical Hierarchy Process and Natural Break

Pacitan district has a high potential for landslides. Landslide is a hydrometeorological disaster that causes loss of life, property loss, and environmental damage. Disaster preparedness is very necessary for the wider community in dealing with landslide emergency response situations. Applications to determine the level of vulnerability to landslides are very useful to minimize the impact and losses on the Pacitan community. This study aims to make an application for assessing the level of landslide susceptibility using the analytical hierarchy process and natural break based on the factors that cause landslides in the sub-district or village of Pacitan district. The factors that cause landslides in Pacitan district consist of weather, history of landslides, land slope, and history of earthquakes. The results of the AHP and natural break classifications are visualized in the form of a spatial map into 3 categories, namely high, medium and low vulnerability levels. The results of the AHP classification and natural break in the 2016-2020 data have a good average GVF value of 0.77. This shows that in general, the results of the 2016-2020 data classification are correct. Mobile device-based applications provide convenience for the public in accessing information as an effort to improve landslide disaster preparedness.
Pelatihan pembuatan media interractive quiz menggunakan power point dan quiziz

Teachers are the main key in efforts to improve the quality of education. Improving and developing the professionalism of teachers in the 21st century, it can be done with ICT-based learning. One alternative is to make interactive quiz media using PowerPoint and quiziz. Making this media was chosen because some teachers have never evaluated learning using technology. Especially during the current pandemic conditions, teachers are expected to be more creative in providing subject matter and keep students enthusiastic about learning from home. With the implementation of this training, it is expected that teachers can master and utilize the PowerPoint media and quiziz application in providing learning evaluations. Based on the training that has been given, it is known that the participants are very interested and feel helped by this interactive quiz media creation training. It can be seen from the results of the evaluation of the questionnaire given at the last meeting, that 85% of the participants were very satisfied with the training provided.
Student Perspectives on Using Virtual Reality to Create Informal Connection and Engagement

Following the global pandemic, educators relied heavily on live videoconferencing options and online meeting spaces to host class in lieu of traditional, in-person classroom learning. Yet, exhaustion and Zoom fatigue fueled a lack of engagement in such online spaces, while simultaneously the need for more informal connection to support learners’ emotional well-being emerged. This study aims to better understand how online learners perceive the use of virtual reality (VR) as an alternative platform to informally connect and engage with one another, and to ascertain the impact on their satisfaction and motivation for such engagement. Specifically, the investigation sought to examine participant perceptions of social presence felt, the ability to connect and exchange informally, and the impact on motivation, digital literacy, and satisfaction overall.
A Survey on Machine Learning Based Techniques for Sign Language Translation System

Abstract: Sign language is the communication method used to bridge the gap among mute and deaf people and the rest of the people. But most people are not familiar with sign language, so communication becomes difficult among mute, deaf and the rest of the people. Improvement in machine learning technology has led to research on its application in sign language recognition and translation system. This paper presents a review of different sign language recognition and translation systems and the various techniques like classification algorithms that were implemented in them. We have found that although many sign language recognition and translation system exist none of them provides efficient and real-time conversation of sign language into audio and many sign language recognition and translation system are hand movement sensor-based which are not affordable to everyone. So, we have also discussed a sign language translation system integrated into a video calling application, in which we will be using a single shot multibox detector for hand detection, for feature extraction Inception V3 will be used, and support vector machines for classification, attention network for generating semantically correct sentences and a text to speech synthesizer for audio output. This system will be easy to access and affordable as it use
Perhitungan Estimasi Upaya Pengembangan Software Pulsa Online dengan Fuzzy C-Means dan Fuzzy K-Means

Top-up can be done by prepaid and postpaid. Top-up at this time can also be done by way of online purchases. Credit with a prepaid system is a real-time top-up. Payments are made before the customer uses credit. Prepaid credit is different from postpaid which is not real-time and is done after the customer uses credit. Before credit can be used, it is necessary to create a credit server first. In this case, limited resources become an obstacle in completing the credit server creation which will later be used by credit users. Therefore, it is necessary to estimate the effort in the development of the server application, so that the estimation can be known, both in terms of resources, and processing time to estimates in terms of costs. In this case, the appropriate method should be used to overcome the obstacle and reduce the risk of software development. There are several ways to use the Fuzzy K-Mean and Fuzzy C-Means methods to complete the creation of impulse servers, perform analysis and interpretation, and provide information and actions for the quality of research output, education, and evaluation research. The result of the grouping comparison is to produce a derivative formula for the Fuzzy K-Mean and Fuzzy C-Means algorithms.
Evaluation of Hazards and Operability Study for Optimization Operation of Industrial Processes

With the recent advances in technology, smart cities are rapidly earning momentum thanks to the quality of citizens' life that smart cities help improve. To provide better lives, smart cities should host several applications to increase the efficiency and accessibility of services. Since these services involve the conveyance of significant data among the smart cities' cloud and the dwellers over the Internet, security and privacy are critical. This paper proposes an authentication protocol with a full aggregation signature to secure the smart city applications. A certificateless aggregate signature (CLAS) is used for smart city real applications such as secure routing and database outsourcing. The proposed CLAS achieves message authentication, user anonymity, constant signature size, unlinkability, and is resistant to replay attacks. Also, we have proved that the proposed scheme is resistant to all malicious adversaries. Finally, the performance evaluation results show that the proposed CLAS performs better than existing relevant schemes.
HOTSPOT PREDICTIVE MODELING USING REGRESSION DECISION TREE ALGORITHM

Forest fires had always become an international issue influencing many life sectors, including environmental, social, and economic. The forest fire in 2013 was regarded as one of the worst forest fire tragedies in history, not only in Indonesia but also in the world. Detection of hotspots on the earth's surface by the satellite can be an indication of land and forest fire occurrence. This research aims to build a predictive model of monthly hotspots in Rokan Hilir Regency using the regression tree algorithm. Several variables related to weather information are included, such as rainfall, sea surface temperature, and southern oscillation index. This research used 245 training data and 43 testing data, resulting a predictive model with a correlation of 0.875 and an error rate of 0.166. Based on the values, we can conclude that the performance of the model is considerably good.
CAN MOBILITY AFFECT GRAMMAR AT THE MORPHOSYNTACTIC LEVEL? A STUDY IN BRAZILIAN PORTUGUESE

In this paper, a study about the presence of the definite article before possessed NP (D-presence) in Brazilian Portuguese is carried out with a sample constituted by sociolinguistic interviews with students from the Federal University of Sergipe (UFS), Brazil, to observe whether the distribution pattern of the variable suggests an effect of mobility in the students’ speech. An analysis is carried out with a sample from the Deslocamentos 2020 dataset, composed of sociolinguistic interviews with college students from Universidade Federal de Sergipe (UFS), balanced for degree of mobility (students from Sergipe, Alagoas, and Bahia), time in the undergraduate program, and sex (n = 60). Results show that D-presence is sensitive to dialectal factor, with D-absence predominating in data from Sergipe and Alagoas, and D-presence predominating in data from Bahia, but it is not sensitive to the integration into the new community considering speakers’ time in the undergraduate program. This result contributes to revealing how mobility affects grammar at the morphosyntactic level.
Recognition of Handwritten Arabic Names using Probabilistic Neural Networks

Emancipation of the computers from the limited in space data entry tools (such as keyboards) and its possession of the ability of hearing and reading, remains an area of active research in computer science for more than four decades.During this period, the researchers have provided a considerable number of methods and algorithms for the computerization of hearing and reading in what is known as Pattern Recognition in computer science.One of these methods is the Holistic Approach, which has proved its efficiency in the fast recognition.The usage of neural networks with the holistic method has special importance, as it helps to determine the transition to the analytical method very easy.This paper presents successful recognition experiments of probabilistic neural networks to recognize holistically the most common Arabic names.This network was succeeded in recognizing a high proportion of Arabic names very quickly because it does not segment the words.
Sosialisasi CerMat Sebagai Implementasi Model Pembelajaran Matematika Berdasarkan Sistem Among Di SMPK Kesuma Cakranegara

Devotion aims to overcome the problems found in the form of low student learning outcomes at Kesuma Cakranegara Junior High School. in addition, socialization activities as an initial alternative in improving the competence of teachers, especially in the pedagogical competence of mathematics teachers of Kesuma cakranegara Junior High School. The result is in the form of teacher awareness about the importance of student awareness in learning independently. Increasing teacher knowledge about CerMat as an Implementation of Mathematics Learning Model Based on Among System in SMPK Kesuma Cakranegar. With the awareness of teachers, the next activity can be done, namely lesson study to create a role model for CerMat-based learning teachers.
AN EFFICIENT CNN ARCHITECTURE FOR OBJECT DETECTION AND CLASSIFICATION IN IMAGES USING DEEP LEARNING

Object Classification has received wide attention due to its real time applications using deep learning technique. It is a process of classifying objects into predefined and semantically meaningful categories. Due to less accuracy ,sometimes gives inaccurate result and wouldn’t be effective. Object Classification using CNN algorithm is a proposed system in which image is inserted and object is classified and displayed in UI based on trained model.Inthis,it extracts features from the image, undergoes three architectures and high accuracy output will be considered to overcome existing difficulties. Objects can be easily detected and identified by humans. The visual system of human is very fast and accurate and can perform complex tasks like object identification and detection very easily .Situation like where we have to find from so many things and trying to find that key will take long time and we have to face some difficulties. Object classification is very important for applications in automatic visual surveillance system. The process of classifying objects into predefined and semantically meaningful categories using its features is called object classification. In this paper we propose a new model for detection and classification of objects by taking the features to classify the detected objects using Deep Neural Network (DNN). Deep Neural Networks are capable of handling large higher dimensional data with billions of parameters as like human brain. Simulation results obtained illustrate that the proposed classifier model produces more accurate results for feature extraction and DNN for classification.
Purwarupa RFID Student Smart Card Berbasis Raspberry pada Sekolah Menengah Kejuruan GT

The conventional attendance system has problems and raises many questions so that administrative management becomes less effective and efficient. The focus of research is on making attendance tools an automatic attendance system by utilizing student cards as a tool to collect attendance data. Methods of collecting data were obtained by direct visits, interviews, and literature review. The analysis method is obtained by comparing the old system with the new one using the system development life cycle. The prototype method used in this research is the rapid prototyping approach. The RFID prototype for the attendance system uses student cards as a tool for attendance. So that the card becomes more useful and multi-functional. The purpose of this research is to help GT Vocational School in making a better automatic attendance system so that the system can make it easier for staff and teachers to manage attendance. The attendance system uses student cards as a tool for attendance, can make students more independent in the attendance process, and teachers just confirm on the website, and they don”t need to bring attendance papers anymore. With the automatic attendance system, all data is integrated into the website, the administrative section no longer prepares attendance papers for each teaching and learning activity.
US2022-Print-Ad

With the rapid advancements in digital technologies and the exponential growth of digital artifacts, automated filtering of cybercrime data for digital investigation from a variety of resources has become the need of the hour. Many techniques primarily based on the “Approximate Matching” approach have been proposed in the literature to address this challenging task. In the year 2019, Chang et al. proposed one such algorithm - FbHash: A New Similarity Hashing Scheme for Digital Forensics that was shown to produce the best correlation results compared to other existing techniques and also resist active adversary attack, unlike others. However, no performance analysis of the tool was given. In this work, we show that the current design structure of FbHash is slower and memory intensive compared to its peers. We then propose a novel Bloom filter based efficient version, i.e., FbHash-E that has a much lower memory footprint and is computationally faster compared to FbHash. While the speed of FbHash-E is comparable to other state-of-the-art tools, it is resistant (like its predecessor) to “intentional/intelligent modifications that can fool the tool” attacks, unlike its peers. Our version thus renders FbHash-E fit for practical use-cases.We perform various modification tests to evaluate the security and correctness of FbHash-E. Our experiment results show that our scheme is secure against active attacks and detects similarity with 87% accuracy. Compared to FbHash, there is only 3% drop in accuracy results. We demonstrate the sensitivity and robustness of our proposed scheme by performing a variety of containment and resemblance tests. We show that FbHash-E can correlate files with up to 10% random-noise with 100% detection rate and is able to detect commonality as small as 1% between the two documents with an appropriate similarity score. We also show that our proposed scheme performs best to identify similarities between different versions of software or program files. We also introduce a new test, i.e., consistency test, and exhibit that our tool produces consistent results across all files under a fixed category with very low standard deviation, unlike other tools where standard deviation under a fixed test varies significantly. This shows that our tool is more robust and stable against different modifications.
Pengukuran User Experience Terhadap Penggunaan Aplikasi SIMVONI dengan Pendekatan Metode HEART

SIMVONI is an acronym for the Virtual Indonesia Museum Application, which is a museum digitization service in the form of a virtual tour 3600. Every digital service requires feedback from users or visitors to achieve the basic goals of developing the service, not preparation for SIMVONI's efforts to become a digital e-museum in Indonesia. The purpose of this study is to analyze the impact of user experience on using SIMVONI through the website. This study uses a quantitative approach with the HEART method which is analyzed using Importance Performance Analysis (IPA). The number of respondents used for the sampling test is 257 provided that they have visited the SIMVONI page at least once. The results showed that there were 10 of 34 HEART items recommended for improvement (action) on SIMVONI, while the most important factors to get attention for improvement in a quick time were Retention and Engagement.
On the Legitimacy of Exhaustion of Rights in Non-Fungible Token Transactions of Digital Works

As the golden rule of resolving the conflict between intellectual property and right in rem of the same object, exhaustion of rights aims to avoid the influence of exercising intellectual property right on right in rem. The academic circle is unable to come to any agreement concerning the discussion of extending the rule of exhaustion of rights to the regulation of utilizing works in digital conditions. The blockchain technology and market have a transformative impact on the copyrights in the digital environment. NFT and the mode of NET of digital works have reshaped the traditional ecology of online works transmission and utilization, offering opportunities for the exhaustion of rights to be applied in the network environment. Hence, it is the right moment to create the digital environment to apply the exhaustion of copyrights.