Reviewerly/exHarmony huggingface dataset:
Implementasi Algoritma K-Medoids Dalam Mengklasifikasi Barang Layak Lelang

Inventory Goods are items that are owned by a company that are recorded in the inventory book / assets of a company which have a period of use and must be replaced after passing the time specified by a company that is charged in the company's budget, while the auction is a process of buying and selling goods / services by offering to bidders, the auction participants who will give the highest price will win or get the items to be auctioned, data mining is closely related to data, information and knowledge. The data mining process begins by extracting data which then produces information, the K-Medoids Algorithm is a clustering method that functions to break down the dataset into groups, which will become 2 clustering, namely the items to be auctioned (C1) and the items to be discarded or discarded. destroyed because it is not suitable for auction, namely (C2). It is hoped that the system to be built is in accordance with the expectations of researchers, so that it can help make it easier for the auction committee to classify the items to be auctioned.
Case Study of Cloud Computing Security Issues and confidentiality Challenges

Cloud computing is a term, which involves virtualization, distributed computing, networking, software and web services. A cloud consists of several elements such as clients, data center and distributed servers. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc.Cloud Computing offers better computing through improved utilization and reduced administration and infrastructure costs. Cloud Computing is the sum of Software as a Service (SaaS) and Utility Computing. Cloud Computing is still at its infant stage and a very new technology. Therefore, most of the users are not very confident to adopt it.The main issue that faced the cloud computing is “security”. In this paper, we try to find out what countermeasures best strengthen the confidentiality, integrity and availability (CIA) of the implementation of cloud computing within the DOD This will be done by analyzing threats and countermeasures within the context of the ten domains comprising the Certified Information System Security Professional (CISSP) Common Body of Knowledge (CBK). The ten domains include access control; telecommunications and network security; information security governance and risk management; application security; cryptography; security architecture and design; operations security; business continuity planning and disaster planning; legal regulations, compliance, and investigation; and physical security. The results will provide a comprehensive guide for any Department of DefenseDoD entity attempting to secure its cloud solution.
An Application for Medical Diagnosis Using Correlation Coefficient With Modal Operators and Operator Identifying and Unary

This paper aims to study the Atanassov's correlation coefficient (A-CC) between two of Atanassov's intuitionistic fuzzy sets (A-IFS), obtained as images of intuitionistic fuzzy modal operators. The composition of modal operators are investigated, verifying under which conditions an A-CC preserves the main properties related to conjugate and complement operations performed on A-IFS. In addition, a simulation based on the proposal methodology using operators described above is applied to a medical diagnosis analysis.
STUDENTS’ INVOLVEMENT IN EFL ONLINE CLASSROOM DURING THE COVID-19 PANDEMIC ERA

One of the government's policies to stop the spread of the covid-19 pandemic is to shift face-to-face learning at school to distance learning at home. Online learning is not easy to do, it is different from conventional learning. In online classes, students were reluctant to participate in the in-class activities. This kind of reluctance made students lose motivation to learn languages. This study aims to see how the online learning model is to find out the students’ involvement in EFL online classes during the Covid-19 Pandemic at Senior High School in Bengkalis. This present study employs a descriptive case study as the research design. To collect the data, researchers used observation, video documentation, and interviews. Meanwhile, the data analysis technique used in this study were used qualitative data analysis techniques which include three activities, namely: data reduction, data presentation, concluding. The results of this study revealed that. Students could not see the screen display, teacher and student communicating to solve problems, there is a network disruption, students late response to teacher, the class leader is the student who always actively responds to the teacher, students do not respond to teacher directions, students sign in and sign out the zoom meeting
Implementasi Aplikasi E-Reporting Infrastructure (ERI) Sebagai Media Monitoring Pengaduan Kerusakan Fasilitas Kampus

The quality of educational facilities and infrastructure is a measure of the success of the teaching and learning process. Over time, these facilities and infrastructure will suffer damage and their quality will decline. Reports of damage to facilities and infrastructure are always made verbally. Another issue that arises is that Sarpras officers have not seen photographic evidence of the reported condition of the infrastructure. This problem can make it difficult for Sarpras agents to identify infrastructure. The reporting party often does not obtain information about the status of the response from the report. This issue is caused by the fact that no media can be used by the reporter to know the status of the reporting of user complaints. To minimize the reporting of damage errors, an information system can be applied. The application that can be applied in the problem of reporting damage to campus infrastructure is E-Reporting Infrastructure (ERI). This application aims to provide access for registrants and stakeholders to monitor each other's damage reports so that the priority scale for processing recommendations is immediately determined. The recommendations must be able to adapt to the variables which are the needs and priorities of management. The process of determining recommendations will be more stable if it is processed by an algorithm integrated into the ERI. The algorithm that will be applied is a practical and multi-criteria ranking algorithm, including Topsis and SAW. The computation results obtained will be compared in order to determine the efficiency and characteristics of the algorithm.
Facemask Detection with Alert System

Abstract: The Covid-19 is spreading across the globe. This infection spreads essentially through drops getting away from an individual contaminated with the covid, representing a threat to other people. The gamble of transmission is more noteworthy openly put. Probably the most ideal way to safeguard yourself from disease is to wear a facial mask in public regions, as expressed by the World Health Organization. In this task, we propose a strategy utilizing OpenCV and TensorFlow to recognize facial masks on a group of people. We prepared the model on various datasets so it can precisely tell regardless of whether the individual is wearing the mask. An admonition message is shown with a sound sign expressing that an individual was distinguished without a cover assuming an individual without a mask is recognized. In the wake of clicking OK, an alarm message with the depiction of the individual without a mask will be emailed and SMS. Watchwords: Opencv, Tensor stream, CNN, Smtplib, Twilio.
AN IMPROVED HAUSA WORD STEMMING ALGORITHM

The explosion of scientific publications in different domains coupled with the introduction and socialization of the internet experienced in the last few decades has made information more available than ever before. Consequently, digital storage capacity has been consistently doubling to reflect this geometric increase in information. In view of this, Information Retrieval (IR), nowadays considered the dominant form of information access has become even more critical. However, the problem of using free text in indexing and retrieval arising from spelling mistake, alternative in spelling, affixes and abbreviations has continued to bedevil the field of IR. To mitigate this problem, Stemming Algorithm was introduced in the 1960s. Stemming is an automated process of stripping all word derivatives of their inflectional affixes in order to obtain stem of the word. Because stemming is language specific, there are stemming algorithms designed specifically for most of the major languages in the world. With a speaker population of about 150 million Hausa language stands in need of a better stemming algorithm. This research is an attempt to improve upon the existing Hausa word stemming algorithm. Affix stripping method of conflation with reference lookup was used. Using Sirsat’s evaluation method, this research achieved 96.9% as Correctly Stemmed Word Factor (CSWF), Index Compression Factor – 74.76%, Words Stemmed Factor (WSF) – 70.44% and Average Word Conflation Factor – 59.47%.
Sociocultural activity in the context of library and information education and employers’ requirements

The growing importance of sociocultural activity as a public value, its opportunity and potential in the work of libraries is indicated. That causes the need to build and develop suitable professional competences of librarians. The major features of building the competences are revealed according to educational grounding (college, higher education or extended education) of the Republic of Belarus. Competences in sociocultural activity of current educational standard of undergraduate degree in specialty 1-23 01 11 Library and Information Activity of the Republic of Belarus and the research insights «The development of competency-based model of a graduating student with a degree in Library and Information Activity based on studying employers’ requirements» are correlated. Topical issues and solutions of organizing the educational process in the context of developing competences in sociocultural activity on the Faculty of Information and Document Communications of the educational establishment «The Belarusian State University of Culture and Arts» are defined.
Comparative Analysis of State-Of-the-Art Classifier with CNN for Cancer Microarray Data Classification

Cancer is currently one of the leading causes of death in the World. Microarray data has a crucial role in lowering the death rate. However, the intrinsic complexity of microarray data processing, such as high dimension, data redundancy, and noisy data, makes the process difficult. To address these challenges, machine learning provides solutions such as dimensionality reduction and optimization, however implementing these will raise computing complexity. When compared to traditional ML models, deep learning can narrate a solution without dimensionality reduction and optimization with excellent performance. Though both machine learning and deep learning aim to extract patterns from a dataset, deep learning is preferred because of its efficiency in handling microarray data. In the current research work, deep learning-based CNN has been considered as the classification model. The proposed CNN model has been evaluated over four benchmark datasets namely brain cancer, lung cancer, prostate cancer, and colon cancer. Next, the empirical analysis has been done in contrast to several ML algorithms such as SVM, RF, DT, kNN, LR, and NB. The result shows that CNN performs well as compared to other state-of-the-art ML algorithms.
Forecasting the cost of quotes using LSTM &amp; GRU networks

The paper considers modern recurrent neural networks (RNN). Most attention is paid to popular and powerful architectures – long chain of elements of short-term memory (LSTM) and controlled recurrent units (GRU). A software package for forecasting the cost of quotations has been written and a comparison of two methods has been made.
The Effect of Vocabulary Mastering And Reading Habits on The Ability of Writing Description Texts

The research aims to determine the effect of vocabulary mastery on students' English descriptive writing skills and the impact of reading habits on students' English descriptive writing skills, as well as the effect of vocabulary mastery and reading habits together on students' English descriptive writing skills. The population in this study was students of class X State Senior High School in Cibinong and the sample was 120 students. The sampling technique was processed using a simple random sampling method. Descriptive statistical methods were used in this research. The research instrument used was a questionnaire on students' vocabulary mastery, reading habits, and a descriptive text writing skill test. Data analysis used SPSS version 25, the significant level of = 0.05. The requirement analysis use normality test, homogeneity test, two-way ANOVA. The result of this research is vocabulary mastery by the value of sig. = 0.77 &lt; 0.05 does not have a significant effect on students' descriptive text writing skills, reading habits have a significant influence on students' descriptive text writing skills by the value of sig. = 0.01 &lt; 0.05 and there is no significant effect of vocabulary mastery and reading habits on students' writing skills by the value of sig. = 0.01 &lt; 0.265.
Refined Segmentation of K-Means Cluster Using Hidden-Markov Random Field (HMRF) for Leukemia Detection

Abstract: An important part in detecting and diagnosing leukaemia involves the microscopic examination of a patient’s blood sample. The type of malignant cells called the blasts is frequently determined by morphological alterations in White Blood Cells (WBCs). Real-time procedures are time-consuming, error-prone, and expensive. In order to overcome this problem the features such as the colour, shapes and texture can be extracted from the original image. This paper deals with the segmentation techniques. The segmentation process in automated approach is developed using k-means clustering (KMC) and Hidden-Markov Random Field (HMRF). This is also termed as Refined Segmentation (Re-Se). This analysis includes Aspirate Smear Images (ASI). First cell segmentation using a KMC is performed, then a Cell Image Representing Model (CIRM) using HMRF is build, estimating prototype variables using Expectation Maximization (EM) ratio, iterating until the best value is found, and finally achieving next phase called Refined Segmentation (Re-Se). Then, features including texture, geometry, colour, and statistical information are retrieved and used to categorize leukaemia cells from WBCs, by using Fuzzy Rule-Based Decision Support System (FRDSS). By incorporating more feature extraction techniques, the suggested method improves a blast of most immature cells identification for the Acute Myeloid Leukemia (AML) detection
IMPLEMENTATION OF TOTAL QUALITY MANAGEMENT IN HIGHER EDUCATION: AN EVALUATION OF THE RESULTS ACHIEVED BY THE PUBLIC AND PRIVATE UNIVERSITIES

Total Quality Management (TQM) is a way of managing everything in an organization or institution in order to get the level of excellence. The present study is conducted to investigate the implementation of TQM elements in public and private universities, the results achieved by the universities and to compare the implementation of TQM elements and results achieved by public and private universities. Mixed methods research design was used in this study. The population of the study was directors of quality enhancement cell (QEC), teachers and students. Semi-structured interviews were conducted to collect the data from directors of QECs. Close-ended questionnaires were used to collect data from teachers and students. Quantitative data were analyzed by mean scores. Thematic analysis was used to analyze the qualitative. In order to compare the results achieved by the public and private universities t.test was applied. The findings showed that public and private universities are struggling hard to implement TQM elements, but still they are lacking behind in some aspects like quality of infrastructure and quality assurance process, it is recommended to obtain feedback from students and teachers every semester, involve teachers in quality planning process, provide reward and appreciation to teachers for their better performance which may improve students and teachers’ level of satisfaction and quality of teaching learning process.
On English Learning Methods in Senior Three

English is one of the important subjects in senior high school. Only by learning English well can we obtain excellent &#x0D; college entrance examination results, and also lay a good foundation for future study and work. English learning has high &#x0D; requirements for the foundation. In order to make up for this deficiency, it often needs to spend more efforts. This paper mainly &#x0D; analyzes the problems encountered in the process of English learning, and tries to explore the best learning methods based on &#x0D; various conditions, hoping to further improve the quality of English learning and master more English knowledge.
Construction, Implementation and Evaluation of a Smart Classroom Based on Teaching Resource Database for Vocational Schools

Vocational education resource pool is designed to integrate “Internet +” technology into vocational education, so that it can promote the reform of educational philosophy, educational methodology and educational mechanism of vocational colleges. The most important battlefield of this reform is the classrooms, where we can start the construction of smart classrooms with the goal of improving learners’ core competence by changing thinking perspectives, building technology platforms, ensuring implementation of new mechanism, etc. To do so, it is necessary to construct and facilitate intelligent classrooms based on resource database. which enables educators to gain accurate data and comprehensive teaching resource. This paper focuses on the research and analysis of the ideas and methods of building and developing smart classroom based on resource database and establishes the evaluation system.
INTRODUCTION OF INNOVATIVE TECHNOLOGY OF STUDENT TRAINING BASED ON A MATRIX MODEL OF COGNITIVE ACTIVITY

The article discusses an innovative approach to the organization of self-educational activity of students based on a matrix model of cognitive activity, which allows us to consider the assimilation of educational material as a "movement" in modules. With the help of this model, it is possible to provide a mechanism for the necessary systematization of educational tasks of the subject module, to organize self-educational activities. As a result, all the presented educational material is decomposed into four activity levels, corresponding to the varying complexity of mastering educational information from the point of view of cognitive activity, which determines the choice of disciplinary modules. The principles of building modules are the same. At the beginning of each module there is a theoretical material, including definitions and basic concepts, as well as explanations for understanding the topic. Further, analyzed examples are given, using the above theoretical material. After them, tasks for independent solution are given, similar to those analyzed. With the help of the proposed teaching aids, the student can independently organize his educational activities at a convenient time for him, as well as exercise self-control and determine the level of his knowledge. The proposed technology has been tested at Samara State Transport University. The pedagogical experiment was carried out in the first and second year of full-time and part-time education in the study of mathematics.
Closed-form steady-state bias error of tracking filter using coordinated turn model for constant velocity target

This letter presents the derivation for the steady-state bias errors of a tracking filter using a coordinated turn (CT) model for tracking a target moving at a constant velocity as a tracking performance index of maneuvering target. The analysis of the tracking filter using the CT model indicates bias errors due to differences between the model-assumed motion (constant angular velocity) and target motion (constant velocity). We derive this bias error in the closed-form as expressed by the filter design parameters. Then, numerical simulations show that the derived bias errors are correct and can be efficiently used for filter design.
To Enhance Enterprise Resource Planning with Blockchain: Food Supply Chain

Blockchain (BCT) is commonly referred to as a distributed ledger technology (DLT). Blockchain is the central generation in monetary markets applications. A Food Supply chain and logistics are complicated procedures in recent times because of their lacking merchandise in travelling. Using (DLT) represents each transition as they circulate via a logistics community that combine may include (ERP) that could carry out the low transition fee. The number of research on traceability applications based on Blockchain aimed to improve the quality and safety of food. This paper pursues to address the space and make a foundation for destiny studies endeavours. ERP assists contributors in documenting price, date, location, and different facts for greater efficaciously coping with the provision. ERP combined with Blockchain can boom the traceability of the business delivery chain, decrease losses from entrepreneurs, enhance visibility and compliance over outsourced settlement production, and doubtlessly decorate an organization's (like supply services). Vendors can combine blockchain and ERP structures in a highly secure and trackable way utilizing immutable data for commercial enterprise transitions. ERP with BCT removes those belief gaps among siloed ERPs even as offering visibility in the course of the system. It has more safety and facts integrity. We have reviewed six studies papers on BCT in logistics Supply Chain (LSC); Food Supply is determined to finish applying enterprise resource planning (ERP). The literature regards distributed ledger in transition, mainly targeted on missing groups, integration with customer relationship management fills the missing in methodology. We have proven current logistics and delivery designed a blockchain structure that enables (FLSM).In structure, we've got targeted food supply, protocols, modules, and challenges, street maps in LSC.This paper concludes with references to final decisions.
The Ever-Growing Complexity of the Data Retention Discussion in the EU: An In-Depth Review of La Quadrature du Net and others and Privacy International

The data retention discussion in the EU is becoming ever more complex.In La Quadrature du Net and others and Privacy International, the CJEU applied its data retention standards to a wide variety of new facts, including data retention, transmission, and automated analysis, both for law enforcement and national security goals.Moreover, the CJEU identified a diverse range of situations in which EU law permits data retention and similar measures on a general and indiscriminate basis.The two judgments provide new opportunities for large scale data retention but raise novel questions about the scope of EU law over national security issues, and the CJEU's reasoning is too brief in some respects.