Reviewerly/exHarmony huggingface dataset:
Statistical Evaluation of Task Scheduling Algorithms in Cloud Environments

Task scheduling algorithms in cloud have come a long way, from simplistic algorithms like first come first serve, to bio-inspired & machine learning algorithms like Q-learning and genetic algorithms.The main objective of any task scheduling algorithm is to minimize the number of execution cycles needed to completely and effectively execute a given set of tasks.In this work, we present a comparison of different scheduling algorithms and their performance evaluation.The proposed research takes into consideration different nuances of cloud task scheduling, which include task length, task completion time, virtual machine configuration and task deadline.Moreover, the review also includes containers, which ensures that the scheduler works effectively on a container environment to improve efficiency of the cloud deployment.We propose different comparisons of the algorithms which are under different task conditions.In our analysis, we reviewed all the algorithms on different tasks and under different virtual machine (VM) configurations.As per the research, the machine learning based algorithms perform better in terms of overall task scheduling efficiency when compared with others.
Efficient Image Compression by Machine Learning

Media broadcasting with video streaming is booming day by day, image data compression is becoming essential.The key goal of image compression is to obtain a relatively small bit rate and a good visual quality of decompressed images.Artificial intelligence and machine learning are such technologies to carry out this task.Each picture is composed up of pixels.Those pictures are labeled as noisy pictures.We propose a convolution auto encoder neural network to compact the images by using the MNIST database where we up sample and down sample an image to increase and decrease its quality.We take 128 by 128 dimensional image.By generating a deep learning machine image, the image must be compressed and transformed to 128 by 1 dimensional vectors in order to obtain a clear original picture type.The main objective is to compress the picture without reducing its quality, predicting the value present in the compressed picture of the MNIST database.
Baruga Kare Guesthouse Makassar Financial Reporting System Based on FASS of MSMEs

The purpose of this study is to analyze the implementation of the Financial Accounting Standard System (FASS) cycle for Micro, Small, and Medium (MSMEs) entities using Wisma Kare Guesthouse as a case.Data were collected using observation and financial reporting document examination.It is found that financial documents were still very limited.The financial report only records cash for a month without proper debit -credit allocation for each transaction.This is a case study in a small guesthouse in the Indonesian cultural context.It needs more verification from other similar enterprises.The practical implication is an accounting report system in small business entities are still need more attention.Social implications of this study are that in order to contribute optimally for economic development, accounting system for small business in accommodation still need to be developed.The paper includes guidelines for implementing the Indonesian Accounting Standard system and relevant.
Névkezelési szabályok a magyar könyvtári feldolgozásban

Rules of name management in Hungarian library processes&#x0D; The paper describes the currently valid rules for recording proper nouns in Hungarian library cataloguing. For publications and manuscripts, the name types that must be recorded include, among others, authorship (name or organisational name), the place of publication (geographical name), personal and geographical names, and in the ‘about’ field event names and organisational names may be recorded. According to the rules of data processing, a distinction is made between description and classification, i.e. the name forms on the documents and the standardized name forms in descriptions. This latter type is regulated by Hungarian standards published between the end of the 1970s and the mid-1980s and a 2005 regulation. As these documents were made in the period of pre-computerized index cards, many libraries have created their own local rules for the present day. Technical development, the request for libraries to match their databases and the pos-sibilities of turning to foreign catalogues put emphasis on the need for updating Hungarian stan-dards and introducing so-called name spaces to ensure consistency.
Fully Automated Computer-Assisted Diagnostic Method for Mitosis Detection on Histology Slide Images of Breast Cancer

Background: Nowadays, advances in the field of medical science, especially the branch of histology, have made it possible to detect cancer, its growth rate, type, and extent of cancer malignancy. According to GLOBOCAN 2012, breast cancer ranks second in terms of prevalence and mortality [1]. The number of mitoses in histology slide images is considered as one of the three significant factors in grading breast cancer. The mitosis count is done manually by pathologists but automating the mitosis count process can decrease its time and costs. Different automatic techniques have been proposed in the literature for breast cancer mitotic counting [2-5]. Objectives: In this paper, we propose an automated method for accurate mitotic cell detection in breast cancer histology slide images. Methods: To evaluate experiments, we used the Mitos-ICPR 2012 dataset consisting of 50 HPFs with the train-to-test ratio of 70% to 30%, accounting for 35 images for training and 15 images for testing. These 50 HPFs were obtained by analyzing the texture of five different patients. Each slide was stained with standard Hematoxylin and Eosin (H&E) stains and two expert pathologists marked the mitotic cells with labels in 10 selected distinct microscopic HPFs at 40x magnification. The slides were scanned by two slide scanners, including Aperio Scanscope XT and Hamamatsu Nano-zoomer. Totally, there were 326 mitotic cells in this dataset [6]. As shown in Figure 1, the proposed fully automated system consisted of the following stages: segmentation and extraction of mitosis candidates using statistical Gaussian Mixture Model (GMM), feature extraction, and classification using SVM classifier (with different kernels) and decision tree classifier. After candidate extraction using GMM, to identify candidates as mitoses or non-mitoses, it was necessary to extract discriminant and reliable features. In the proposed feature extraction stage, we focused on the extraction of textural features including GLCM, CLBP, and statistical moments of filtered images by the Gabor filter in the RGB color space. Moreover, several shape features were proposed to achieve a better distinction of mitosis from non-mitosis candidates. The proposed shape features were based on calculating the Euclidean distance of boundary pixels from the center of each cell. Two types of textural and shape features were combined with each other to provide the final feature vector with a length of 214. Results: The visual results of the proposed automated mitosis detection system for a sample histopathology slide image are shown in Figure 2. Conclusion: The detailed experimental results demonstrated the promising performance of the proposed fully automated method for mitosis detection with F-measure (91.49%).
PENERAPAN METODE WATERFALL DALAM PEMBUATAN SISTEM INFORMASI DANA KAS KECIL PADA PT. NATUR PESONA INDONESIA

The growing of a company, then the system used must follow the development of the Times, the role of technology in petrifying accounting process in a long-growing company, the main reason is efficiency, time saving, and cost. to achieve the results of the output of financial statements correctly PT. Natur Pesona Indonesia needs this one system. Because At PT. Natur Pesona Indonesia manages the financial records manually, from the acceptance, expense, and archiving of data that is still in progress with the process of acceptance and expense. Therefore, it is possible that when the process takes place error in recording, the less accurate report is made and delays in search of necessary data. The design of this information system is the best solution to solve the problems that exist in this company and with a computerized system can be achieved an effective and efficient activity in support of activities at PT. Natur Pesona Indonesia. and with a computerized system an effective and efficient activity can be achieved in supporting activities at PT. Pesona Indonesia. A computerized system is better with method waterfall than a manual system to run more effectively and efficiently and a petty cash fund system that is now more conducive than the previous system.
PEMANFAATAN ANIMASI MACROMEDIA FLASH DALAM MENINGKATKAN HASIL BELAJAR

Abstract&#x0D; This study aims to implement macromedia flash animation in improving student learning outcomes on the topic of buffer solutions. This research was conducted in the first semester of the basic chemistry course with the topic of buffer solution. The samples in this study were first semester students at the University of Riau divided in 2 classes. This study is quasi-experimental, by making treatment in the experimental class (animation class) by comparing with the control group. The hypotheses tested in this study are: Ha = There are differences in the level of learning outcomes of the experimental class and the control class and H0 = There is no difference in the level of learning outcomes of the experimental class and the control class. Hypothesis testing is done by the independent sample T-Test on SPSS 22 with a significance level of 0.05 which used gain score. Based on the results and discussion it can be concluded that the experimental class has an increase in learning outcomes by 57%, while the increase in student learning outcomes in the control class is only 39%, which is about 2/3 of the increase in learning outcomes of the experimental class. Based on the results of the hypothesis test it can be concluded that Ha is accepted, namely there are differences in the level of learning outcomes of experimental class and control class where significance is equal to sig = 0.000, this value is smaller than the significance level of 0.05.&#x0D; &#x0D; Keywords: animation, macromedia flash, learning media, learning outcomes, buffer solutions&#x0D;
ASSESSMENT OF THE LEVEL OF STUDENTS’ MATURITY IN THE FIELD OF CITIZENSHIP THROUGH THE STATE EXAM IN SOCIAL STUDIES

The article presents the results of the state exam in social studies in Altai Krai in 2017-2019. The analysis of the exam results in informative blocks is carried out, which allows us to evaluate the basic knowledge necessary for the formation of citizenship. Substantial gaps have been identified among graduates that negatively affect the formation of citizenship. The evaluation of the effectiveness of the main state exam as the means for determining the level of formation of citizenship of students was given.
Paint adsorption on walls: I. Fractal-Stochastic model

Adsorption processes on surfaces is highly relevant in the industry since they allow specific characteristics to be obtained, from fixing materials such as paints to the efficiency of reactions on catalysts.Although this relationship can be estimated using the adsorption isotherms, there are practical problems associated with its obtention when it is about paint adsorption on walls: complex characteristics of the analyzed system since there is no fluid phase that is in contact with the surface (no concentration of adsorbate can be measured, as is done in traditional adsorption processes) In this case, a phase change occurs when the paint drying process takes place, so only the concentration of the pigment is known, and how it is distributed on the surface, this data is insufficient to build the adsorption isotherm.A stochastic model was obtained allowing the adsorption representation for coatings, estimating the equilibrium constant associated with the adsorption process and the distribution of active sites from the fractal dimension observed in the mesoscopic scale and adsorbate concentration at equilibrium.Two paint-coated surfaces were evaluated finding the adsorption value predicted from the use of the proposed model.From the morphology of the surface, predictive behaviors can be performed..
ACADEMIC PROGRAM “DIGITAL PROJECTS LIBRARIES MANAGEMENT”: DEVELOPMENT EXPERIENCE AND IMPLEMENTATION PROSPECTS

The importance of professional training of library personnel industry, who have management and digital competences, has been substantiated. The grounds for the development of the academic program of professional training of the specialists in the field of e-libraries innovative programs and projects management have been presented. The aim and the subject matter of the Master’s academic program “Libraries E-Projects Management” in the field of training 38.04.02 “Management” have been characterized. The features of Master’s degree education program at the State University of Management have been highlighted, such as focusing on the practical aspects and transferring the studying experience into actual professional activities, the multidisciplinary approach as digital projects management personnel training strategy, cooperation with leading libraries of the country etc. The importance of attracting specialists who have not only academic degrees and titles, but also significant experience not only in library practice, but also in management activities, to teaching specialized disciplines, has been noted. The possibilities of developing an extended Master’s program focused on modern museums and archives in addition to library specialists have been indicated.
MAINTAINING THE FUNDAMENTALITY OF MATHEMATICAL EDUCATION AS AN ESSENTIAL CONDITION FOR CONTINUING EDUCATION

The problem of maintaining the fundamental nature of mathematical education is considered as the condition for lifelong education. The article substantiates the idea that fundamental mathematical education will help cultivate the student’s&nbsp;self-motivation&nbsp;for education; it will contribute to the formation of the ability to learn, the implementation of the developing function of mathematical education and the intellectual flowering of personality.
AUTOMATIC ATTENDANCE SYSTEM USING FACE RECOGNITION

Nowadays, as computers are powerful enough for implementing complex algorithms, there are numerous applications that people utilize computers to run. In which, facial recognition is one of the most active fields of applications. In fact, computers can not only automatically identify who a person is, but also operate 24/7, which human beings cannot endure. This leads to the replacement of people by computers in some repetitive and real-time applications. In this work, we apply facial recognition into an attendance checking system that uses faces of registered people to check their attendance. This system has a GUI, which allows user-to-system interaction and attendance marking will be easy through recognizing the face of the student with the help of the recognition algorithm and mark the attendance. Cascade classifier is using to detect face. The Local Binary Pattern Histogram algorithms for this technology using face recognition, this system saves time more time and also monitor students and they can verify their attendance status with the help of the Register Number.
Free-text and Structured Clinical Time Series for Patient Outcome Predictions

While there has been considerable progress in building deep learning models based on clinical time series data, overall machine learning (ML) performance remains modest.Typical ML applications struggle to combine various heterogenous sources of Electronic Medical Record (EMR) data, often recorded as a combination of free-text clinical notes and structured EMR data.The goal of this work is to develop an approach for combining such heterogenous EMR sources for time-series based patient outcome predictions.We developed a deep learning framework capable of representing free-text clinical notes in a low dimensional vector space, semantically representing the overall patient medical condition.The free-text based time-series vectors were combined with time-series of vital signs and lab results and used to predict patients at risk of developing a complex and deadly condition: acute respiratory distress syndrome.Results utilizing early data show significant performance improvement and validate the utility of the approach.
Offline Handwritten Hindi Word Recognition

There are few approaches to character distinguishing proof.Basic stages of character recognition incorporate pre-processing, segmentation, features extraction and classification of features.A few classification techniques have been talked about in this paper, such as neural network, System Vector Machine (SVM), coordinating models, etc.The issue of character affirmation has been turned out from different viewpoints.One of the foremost well-known ways is as character grouping.Character course of action could be a zone wherein a system can recognize the assorted information boosts in an imperative gathering as shown by the highlights show within the data character.In this paper we investigate the Hindi Offline written by hand word acknowledgment (HWR) that we are making.In the HWR, we utilize OCR Framework, OCR is the strategy of taking pictures or pictures of letters or typhoid content and interpreting them into data that the computer can effectively translate and in Convolutional Neural Network (CNN).The proposed framework has been prepared on tests of a sizably voluminous set of database pictures and tried on tests pictures from utilizer characterizes information set and from this try we accomplished exceptionally tall apperception comes about.
GPA Comparison of Students Admission in SNMPTN and SBMPTN in Department of Physics Education FKIP Unsyiah

&lt;p&gt;The comparative research with a quantitative approach aims to find out the comparison of the GPA of student admission the SNMPTN and SBMPTN entry points at the Department of Physics Education FKIP Unsyiah. The sample in this study were students of Physics Education 2017-2018 who admission form the SNMPTN 47 students and the SBMPTN 57 students. The collection of research data through the documentation method of admission and transcripts of students grades at the Department of Physics Education FKIP Unsyiah. Analysis and processing data using comparative analysis for two different samples (independent) with using the two samples t-tests. The result of t&lt;sub&gt;test&lt;/sub&gt; (t&lt;sub&gt;0&lt;/sub&gt;) = 0,71 and t&lt;sub&gt;table&lt;/sub&gt; (t&lt;sub&gt;α&lt;/sub&gt;) = 1,980. The conclusion in the study, there is no difference in the GPA of students who pass through the SNMPTN and SBMPTN entrance lines at the Department of Physics Education FKIP Unsyiah for the 2017-2018 class.&lt;/p&gt;
A Comprehensive Science Mapping Analysis of Textual Emotion Mining in Online Social Networks

Textual Emotion Mining (TEM) tackles the problem of analyzing the text in terms of the emotions, it expresses or evokes.It focuses on a series of approaches, methods, and tools to help understand human emotions.The understanding would play a pivotal role in developing relevant systems to meet human needs.This work has drawn significant interest from researchers worldwide.This article carries out a science mapping analysis of TEM literature indexed in the Web of Science (WoS), to provide quantitative and qualitative insight into the TEM research.To explain the evolution of mainstream contents, various bibliometric indicators and metrics are used which identify annual publication counts, authorship patterns, performance of countries/regions, and institutes.To further supplement this study, various types of network analysis are also performed like co-citation analysis, co-occurrence analysis, bibliographic coupling, and co-authorship pattern analysis.Additionally, a fairly comprehensive manual analysis of top-cited and most-used journal and proceeding papers is also conducted to understand the growth and evolution of this domain.As per the authors' knowledge, this manuscript provides the first thorough investigation of TEM's research status through a bibliometric examination of scientific publications.Expedient results are recorded that will allow TEM researchers to uncover the growth pattern, seek collaborations, enhance the selection of research topics, and gain a holistic view of the aggregate progress in the domain.The presented facts and analysis of TEM will help the researchers' fraternity to carry out the future study.
Research on Set Theory Based on Paraconsistent Logic

Different from ZF axiomatic set theory, the paraconsistent set theory has changed the basic logic of set theory and selected paraconsistent logic which can accommodate or deal with contradictions, it effectively avoids the whole theory falling into a non-trivial dilemma when there are contradictions in set theory.In this paper, we first review the history and current situation of the praconsistent set theory; then, we give three kinds of paraconsistent logic which can be used to construct the praconsistent set theory among many kinds of paraconsistent logics.And then, we analyze the differences of methods of the paraconsistent set theory with strong or weak structure of paraconsistent logic and get different paraconsistent set theory.Finally, we verify that paraconsistent set theory is a new method to solve the paradox of set theor.The development of paraconsistent set theory can solve the difficulties in the development of set theory in a unique way, which is not only the extension of the application of paraconsistent logic, but also the new form and new trend of the development of set theory.
KETERAMPILAN MENULIS DENGAN MODEL PAKEM MELALUI TEKNIK ‘MENJADI WARTAWAN JUNIOR’ DI SEKOLAH DASAR

This research is motivated by the condition of students' writing abilities that are still low. One method that is considered appropriate is the PAKEM model by positioning students as junior journalists. The research method that I use is a quasi-experimental research method with a quantitative approach. The quantitative approach is used to obtain a picture of the ability of students to write reports on interviews through the technique of 'Becoming a Junior Reporter'. In addition, this study also uses a qualitative approach to describe the profile data of students' ability to write reports on the results of interviews through the technique of 'Becoming a Junior Journalist' before the learning approach to writing through the 'Becoming a Junior Journalist' technique is applied. The 'Become a Junior Journalist' technique is effective for improving students' ability to write reports based on an increase in the average pretest score of 57.47 to 78.50 on the average posttest score. Meanwhile, the final average value of the control class was 57.00 in the pretest and increased by 68.78 on the average posttest score. There was a difference in gain of 21.03 in the experimental group and 11.78 in the control group. This proves that writing ability can be improved with the PAKEM model through junior journalist techniques.