Reviewerly/exHarmony huggingface dataset:
Web Based CSE Department Management System

The project is aimed at developing an application for the "CSE Department Management System" of the college. The system is an application that can be accessed and effectively used throughout the organization with proper login enabled. This system can be used as an application for the teachers in the college to manage the Department. The key feature of this project is that information on the application managed by teachers. Our project provides the facility of maintaining the details of the students. It reduces the manual work and consumes less paper work to reduce the time. This project is developed with ASP.NET , C# and MYSQL. I.INTRODUCTION CSE Department Management System is a formal sociotechnical, organizational system designed to collect, process, store, and distribute information.In an educational institution, there is a need to record information as pertains to members of the institutions, especially students, so ease is achieved when retrieval of said information is needed.CSE department management system or Department management system is a management information system for education establishments to manage student data easily and without stress.Department Systems provide capabilities for documenting grades and transcripts, computing results of student tests and other assessment scores; building student schedules; tracking student attendance; and managing many other student related data needs in a department.
RECOVERY OF MISSING DATA USING ENHANCED PROBABILISTIC MATRIX FACTORIZATION

Recommendation systems are one of the most widespread forms of machine learning in modern society.Whether you are looking for your next show to watch on Netflix or listening to an automated music playlist on Spotify, recommender systems impact almost all aspects of the modern user experience.One of the most common ways to build a recommendation system is with matrix factorization, which finds ways to predict a user's rating for a specific product based on previous ratings and other users' preferences.In this project, we compare and contrast several PMF-based models by applying them to find missing values in music recommendation system.Motivated by the observation that incorporating user network information is not as effective as constraining the user feature vector with latent constraint similarity matrix, we developed Constrained Kernelized PMF (cKPMF) model.We show that cKPMF is the most effective model for our task at hand among the models explored in this project.In this article we formulate the missing value estimation as a recommender system problem.
A Study on The Second Year Students’ Ability to Comprehend Reading Text Based on The Level of Knowledge Questions at SMAN 1 Sijunjung

This study was designed to describe the ability of the second year students to comprehend reading text according to the levels of question at SMAN 1 Sijunjung. To be more specific it aimed at describing students’ ability to comprehend reading text according to the levels of knowledge question, comprehension question, application question and analysis question.&#x0D; This research was descriptive in nature. The population of this research was the second year students at SMAN 1 Sijunjung. The number of members of population was 165 students. The researcher took 80 students as the sample. In selecting sample, the researcher used stratified cluster random sampling technique.&#x0D; The data of this research were the students’ scores on comprehending text according to the levels of question. To take the data, the researcher used reading test. In analyzing the data, there were some steps she used: the first was presentation of raw scores and calculation of Mean and Standard Deviation. The second was classifying the students’ ability into high, moderate, and low ability. The third was determining the percentage of the students who had high, moderate, and low ability.&#x0D; The result of the data analysis showed that the ability of the second year students to comprehend reading text according to the levels of question at SMAN 1 Sijunjung was moderate. It was proved by the fact that 41 students (51.25%) had moderate ability. Specifically, the ability of the students to comprehend reading text at the level of knowledge question was moderate. It was proved by the fact that 53 students (66.25%) had moderate ability.&#x0D; Based on the findings above, it was suggested that the teachers give more exercises, beginning from the low levels of question to the high levels of question. It was also suggested to the teachers that they must promote a discussion to answer the questions on the texts being taught.
Cyborg ontics

The article is devoted to the analysis of ontic dispositions of modern reality. The modern reality is the post-, smart-, cyber-reality of the modern semi-artificial semi-living post-human cyborg. Imperatives that have been funding the cultural and ontic space of man for thousands of years, such as pain, fear, desire for pleasure, death, etc., are no longer in the zone of the sacred or metaphysical, but rather in the sphere of planned and pragmatically oriented technology. Modern cluster and virtual-based construction of the living world format the world around according to the patterns of information space, in which both time and space, technological or production chains, social ties, models of interaction and existence are formed in a smart and post-temporal and spatial paradigm that deconstructs the classical models of time, space and cultural environment as a whole. In the modern cultural environment and, accordingly, in the ontic space of the post-human cyborg, the logic of building a medial virtual-digital reality is incorporated. The article provides a cultural-philosophical and hermeneutical analysis of the main provisions of the new ontic space of modernity (logic of “logistics”, binarism, “logic of order”). It is shown that in the virtual and digital life world there is a transformation of personal parameters: structures of thinking, patterns of behavior, as well as ways of self-identification. To describe this phenomenon, the term “digital identity” is proposed, and its characteristics are given: foundation by virtual-digital means, dematerialization of relationships and actions, prosthetics by network organs, subjective non-autonomy and obedience to orders. The authors draw conclusions about the nature and essential features of the posthuman cyborg as a natural product of the new virtual digital reality.
Research and Performance of Recognition System of the Human Activity with a Filter Bank of Gabor by Hidden Markov Model

recognition of human movement is one of the huge growing generation. It has a massive feature for example supervision (movements evaluation), safety (walker detection), manage (character-computer interfaces); content material- based video retrieval, and plenty of others. Human interest reputation device of is a device of identifying a selection of Human sports activities beside a few saved sample Human interest. In this paper Human activity reputation machine for popularity of man or woman is provided. It gets facts of individual photo and look for comparable interior the store pics. Human interest can be visible as fit or now not fit if there can be in shape or not matched in stop result. consumer cannot create a few form of regulate inside the stored photo documents, i.e. a purchaser isn't always accredited to insert or dispose of photographs from the garage records. The manager of the scheme has verification to make changes in the storage facts. The supervisor of the scheme has verification to make adjustments inside the storage statistics. Biometrics device of automatic Human hobby recognition system acting recognition is supplied. Extraction of capabilities is finished through the usage of the use of Gabor filter out to this tool. function extraction of the picture is convolving with Gabor clear out and extra person pattern era set of guidelines is used to determine a hard and rapid of realistic and non redundant functions of Gabor. Hidden Markov models for matching the input Human interest photograph to the stored pics is used.
Geochemical Modelling Data of Groundwater in the O’Kiep, Namaqualand Region, South Africa – 2013 to 2019: A Case of Evidenced Contamination by Historical Mining Activity

The integration of hydrogeochemical characteristics techniques and geochemical modelling were used to identify the significant factors governing groundwater hydrogeochemical evolution in the Namaqualand.The groundwater was classified into four sets namely: Ca -Mg -HCO 3 , Na -K -HCO 3 , Na -K -Cl -SO 4 , and Ca -Mg -Cl -SO 4 between the periods of 2013 and 2019.The geochemical model PHREEQC suggests some geochemical reactions and mineral phases being responsible for the evolution of the groundwater chemistry and indicating that the groundwater hydrogeochemical evolution is mainly controlled by carbonate mineral dissolutions, cation exchange, precipitation and weathering.The increase in SO 4 -concentration in the period of 2019 in groundwater was most likely due to sulfide-mineral oxidation.The contributions of anthropogenic sources were associated with the closed metalliferous mine, metalliferous solid waste, and acid rock drainage; it is predicted that the risk of potentially toxic elements in the study area will probably increase in groundwater in a long-term.The accumulation of SO 4 -in the groundwater maybe due to the arid climate of the area.The groundwater of O'Kiep has been exposed to the progressive deterioration of water quality, with particularly significant increases in Na, Cl and SO 4 .This information would contribute to risk assessments and evaluation of remediation strategies.It is therefore anticipated that the groundwater contamination will continue to persist in the study area for many years if the mitigative strategies are not implemented.
The review of “Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using Artificial Neural Networks” by Braghiere et al., 2019

This paper presents the evaluation of the relation of aerosol optical depth and surface fluxes of mass and energy on three study sites using Artificial Neural Networks and radiative transfer modeling.The impact of atmospheric aerosols on the carbon balance over three sites in South America were investigated, in the deforestation arch of the Amazon forest, making use of a novel approach, combining two different types of modeling techniques.
APLIKASI CRM JASA SERVIS AIR CONDITIONER PADA JAYA SERVICE BERBASIS ANDROID

In the current era, many Android applications have been used in the process of requesting goods or services that can facilitate activities, especially placing orders, especially in the case study below using services made by the company CV. Jaya Service, this service is difficult to promote by CV. Jaya Service because it only posts small banners on the side of the road so that the income level of this ac service does not increase or even decrease. In addition, the current process, customers always order ac service directly to the location, this takes a long time, and in the sales inspection process it becomes difficult and takes a long time. Customer relation management is needed to maximize activities or Many marketing items, sales, and sales processes are currently done automatically. Analytical customer relation management is very useful in exploiting data from customers in order to increase the quality value of the company, through a CRM business strategy that will be combined with a process, humans, with technology. assist in the process of adding customers related to sales, converting the company to permanent members, and maintaining existing permanent members, satisfied and loyal permanent members. This study aims to design a CRM Service AC Service on Android-based Jaya Service. From the results of this study, the system built can make it easier for customers to order ac service easily directly via cellphones and can provide convenience to Jaya Service in seeing incoming orders and the results of service order transactions.
A Survey on Dynamic News Recommendation System via Social Media using Machine Learning Framework

Now-a-days people can read news from several sources around the world. This paper investigates a novel user profile model to express users' preferences from different aspects. Then, considers the scope of the user's preferences for historical news, and propose a method to calculate the desire weight of historic news consistent with the user's analysing behaviour and the popularity of news. This method may want to assemble user profiles greater correctly. Additionally, represents a dynamic technique for news recommendation, wherein each short-term and long-term user preferences are taken into consideration. The contribution work is to implement location-aware personalized news recommendation with explicit semantic analysis (LP-ESA), which recommends news using both the users' personal interests and their geographical contexts. The experimental consequences show that BAP technique and LP-ESA technique can fundamentally increase the recommendation outcome.
Penilaian Kualitas Informasi Dokumen Rekam Medis Pasien Rawat Inap Pada Kasus Cerebral Infarction di RSUD Sleman D.I.Yogyakarta

The assessment of the quality of medical record document information can help to find out the scores thatdetermine the level of quality of information produced by inpatient medical record documents in cases ofcerebral infarction. Based on preliminary studies, it has been carried out at Sleman District GeneralHospital. Yogyakarta on February 26, 2020 found a problem related to the contents of incomplete medicalrecord documents. This study aims to assess the quality of inpatient medical record document informationin the case of Cerebral Infarction in Sleman D.I.Yogyakarta Hospital. Descriptive method and crosssectional research design by observing 23 medical record documents taken from the sampling resultsusing the Slovin method to obtain a sample of 204 populations related to cases of cerebral infarction in theinpatient unit. Research results The assessment of the quality of information on medical record documentsuses four dimensions of product and service performance for information quality. Dimension assessmentwas considered good because of the results of 13 scores in filling out the inpatient medical recorddocuments that became the study sample. The contents of medical record documents which wereconsidered to be still poor were the contents of the clarity of the doctor's writing and the completeness ofthe name and signature of the care provider, one of which was at the DPJP.
Tag recommendation based on topic hierarchy of folksonomy

As a recommendation problem, tag recommendation has been receiving increasing attention from both the business and academic communities. Traditional recommendation methods are inappropriate for folksonomy because the basis of such mechanism remains un-updated in time owing to the bottleneck of knowledge acquisition. Therefore, we propose a novel method of tag recommendation based on the topic hierarchy of folksonomy. The method applies the topic tag hierarchy constructed automatically from folksonomy to tag recommendation using the proposed strategy. The method can improve the quality of folksonomy and can evaluate the topic tag hierarchy through tag recommendation. The precision of tag recommendation reaches 0.892. The experimental results show that the proposed method significantly outperforms state-of-the-art methods (t-test, p-value < 0.0001) and demonstrates effectiveness with respect to data sources on tag recommendation.
Social Media Sentimental Research using Machine Learning Techniques

Social media is the main resource to collect information about people opinion towards different topics as they spend most of their time on social media and share their thoughts. In this technical paper we present the applications of sentimental analysis. As we chosen twitter as our analysis platform we show how to connect to twitter and run analysis queries. We illustrate approach to issue with the model to different fields and show the best results.
Nonlinear Autoregressive Recurrent Neural Network Model for Quality of Service Prediction

Due to the advances in computer networks, Internet and multimedia communications, Quality of Service (QoS) monitoring and assessment become an increasingly important. The importance of assessing QoS stems from the fact it may reflect the resources availability of a network that may provide solutions for QoS provision, routing, monitoring, management … etc. In the literature, several monitoring and measurement approached and methods have been developed to quantify and predict the QoS of multimedia applications transmitted over such networks. In this research, a new QoS prediction system will be designed. The proposed system is based on using the Nonlinear Autoregressive with eXogenous input model (NARX) using recurrent neural network. This prediction system uses in addition to the QoS parameters; previous measured QoS values will used as inputs to this model. The expected output of this new model is the forecasted QoS. The proposed model will be trained, tested, validated and then optimized to provide a good estimate of the QoS provided by the given network. Simulation results are expected to show that the proposed model will have high accurate QoS prediction capabilities compared to other QoS assessment systems adopted in the literature.
PSYCHOLOGICAL ASPECTS OF USING BIG DATA TECHNOLOGY IN THE CONTEXT OF DISTANCE LEARNING

The issue of studying a person's abilities to perceive a large amount of information during the period of distance learning is poorly understood and extremely relevant. The problem of our research is the identification of modern technologies for supporting education system specialists in working with a large amount of information, the ability to perceive and analyze it, as well as reducing the level of information fatigue among educational workers during distance learning, since the digitalization of education has an intense negative impact on mental processes of employees, on their psychological and social well-being. The article describes the results of a theoretical study of the interdisciplinary convergence of the indicated problem, expanding the understanding of Big Data technology through the psychology of abilities and the psychology of education. At the same time, the authors of the article note the increasing role of Big Data technology in the modern conditions of a pandemic and distance learning. Big Data technology or «Big Data» means a certain system of methods and some algorithms for working with large amounts of data. These data sets are aimed at acquiring a qualitatively new understanding of what this information carries. Now there are four main directions of the formation of large volumes of data in the education system. These are online training systems, internal information systems of educational organizations, information about employees and the requirements of the organization's management to potential employees, information about students. Having studied the main directions of Big Data development when processing large amounts of various information, we found links with the implementation of Big Data methods, tools and technologies in the field of education and the efficiency of employees. The authors identified and studied an important function of Big Data in the period of distance learning – it is the creation of psychological well-being of employees of the education system and the leveling of the problem of information fatigue.
Emphasize the Cloud Security Using Various Substitution Techniques

Cloud computing is the technology used for storing the Information and packages on faraway servers and accessing them through the net rather than saving or installing them to your non-public or office pc. The time period cloud is used because information and programs are saved on a cloud or collection of web servers and computers owned by a third party. Most issues start from the fact that the person loses manipulate of his or her records, because it's miles stored on a laptop belonging to a person else (the cloud provider). Cloud Computing affords a platform with an superior and efficient way to store statistics inside the cloud. The functioning of Cloud Computing is significantly distressed with the aid of problems including that of statistics safety, integrity, theft, loss and presence of inflamed applications. These troubles are the important dangers to the consumer to transport their statistics to the cloud. we have analyzed various Substitution techniques to attain high level of security to cloud storage.
A Dwt and Scrambling Based Blind Watermarking Algorithm for Digital Images Authentication

Like the other multimedia that is spread on the Internet, images are also vulnerable to theft and attacks. Protecting the image is therefore an urgent necessity because it represents a large proportion of the digital content. Authentication and ownership protection are the basic demands of image security and these are achieved by applying watermarking techniques. For the Muslim world, the Holy Quran has its sanctity, which does not accept any controversy or doubt. As part of keeping pace with modern technology, digital copies of the Holy Qur’an are available, which are widely distributed all over the world. Therefore, it is necessary to ensure that these copies maintain their integrity and ensure that there are no malicious manipulations. In this paper, we propose an image watermarking scheme to authenticate the images of digital version of Holy Quran using discrete wavelet transform DWT. Here a fragile watermark is used to clarify whether there is any modification occurred to the intended images. Initially the cover image is decomposed by DWT where 2nd and 4th level coefficients are exploited for watermark embedding. The intended watermark is obtained by scrambling the original cover image. Then the scrambled image is inserted into the DWT coefficients by several trials using different embedding gains. To evaluate our system and see how effective it is to detect any error or manipulation, PSNR, SSIM and MSE are employed beside that they are acting as an imperceptibility measure. Results proved that our method has achieved a good level of imperceptibility and can detect any slight tamper. It is necessary to bear in mind that this method is valid for application to normal color images as well and gives an excellent level of efficiency.
Spelling Pronunciation versus Relaxed Pronunciation in Foreign Language Teacher Education

Accurate pronunciation is an important part of learning any language, and especially when non-native students are trained to be English language teachers. Good pronunciation is more than just mastering individual sounds since it also requires understanding intonation, stress, pitch and junctures. In this respect, first things first, two functional issues come to the stage: Spelling pronunciation versus relaxed pronunciation. Spelling pronunciation depends on the use of a pronunciation that is based on spelling that includes common pronunciation of the silent vowel and consonant letters. The converse of spelling pronunciation is pronunciation spelling which produces the creation of a new spelling form on the basis of pronunciation. In this study, the contrastive positioning of spelling pronunciation versus pronunciation spelling in English words, phrases, clauses, and sentences will be analyzed to train the English teachers.
Security Reputation Metrics

Security reputation metrics (aka. security metrics) quantify the security levels of organization (e.g., hosting or Internet access providers) relative to comparable entities. They enable benchmarking and are essential tools for decision and policy-making in security, and may be used to govern and steer responsible parties towards investing in security when economic or other decision-making factors may drive them to do otherwise.