Reviewerly/exHarmony huggingface dataset:
Missing Data Imputation in High Dimensional Data Set using Local Similarity

Data quality is an important aspect for any data mining and statistical tasks. Presence of missing values in the dataset affects the data quality. Missing values refers to the event did not happen or the value does not exist. Data mining algorithms are not robust towards incomplete data. Imputation of missing values is necessary to improve the data quality for performing data mining and statistical analysis. The existing methods such as Expectation Maximization Imputation (EMI), A Framework for Imputing Missing values Using co appearance, correlation and Similarity analysis (FIMUS) use the whole dataset to impute missing values. In such cases, due to the influence of irrelevant record the accuracy of imputation may be affected. This can be controlled by only considering locally similar records to impute missing values. Local similarity imputation can be done through clustering algorithms such as k-means algorithm. K-means clustering efficiency depends on the number of clusters is to be defined by users. To increase the clustering efficiency, first distinctive value is imputed in place of missing ones and this imputed dataset is given to stacked autoencoder for dimensionality reduction which also improves the efficiency of clustering. Initial number of clusters to k-means algorithm is determined using fast clustering. Due to initial imputation, some irrelevant records may be partitioned to a cluster. When these records are used for imputing missing values, accuracy of imputation decreases. In the proposed algorithm, local similarity imputation algorithm uses only top knearest neighbours within the cluster to impute missing values. The performance of the proposed algorithm is evaluated based on Root-Mean-Squared-Error (RMSE) and Index of Agreement (d2). University of California Irvine datasets has been used for analyzing the performance of the proposed algorithm.
Research of various Data Mining Techniques for IoT Applications

In recent years everything is connected and passing through the internet, but Internet of Things (IOT), which will change all aspects of our lives and future. While the things are connected to the internet, they will generate the huge amount of information which has to be processed. The information that gathered from various IoT devices has to be recognized and organized according to the environments of their type. To recognize and organize the data gathered from different things, the important task to be played is making things passing through different Data Mining Techniques (DMT). In this article, we mainly focus on analysis of various Data Mining Techniques over the data that has been generated by the IOT Devices which are connected over the internet using DBSCAN Technique. And also performed review over different Data Mining Techniques for Data Analysis
Secure Data Retrieval on the Cloud: Homomorphic Encryption meets Coresets

Secure report is the problem of a client that retrieves all records matching specified attributes from a database table at the server (e.g. cloud), as in SQL SELECT queries, but where the query and the database are encrypted. Here, only the client has the secret key, but still the server is expected to compute and return the encrypted result. Secure report is theoretically possible with Fully Homomorphic Encryption (FHE). However, the current state-of-the-art solutions are realized by a polynomial of degree that is at least linear in the number m of records, which is too slow in practice even for very small databases. We present the first solution that is realized by a polynomial that attains degree independent of the number of records m, as well as the first implementation of an FHE solution to Secure report. This is by suggesting a novel paradigm that forges a link between cryptography and modern data summarization techniques known as coresets (core-sets), and sketches in particular. The key idea is to compute only a coreset of the desired report. Since the coreset is small, the client can quickly decode the desired report that the server computes after decrypting the coreset. We implemented our main reporting system in an open source library. This is the first implemented system that can answer such database queries when processing only FHE encrypted data and queries. As our analysis promises, the experimental results show that we can run Secure report queries on billions records in minutes on an Amazon EC2 server, compared to less than a hundred-thousands in previous FHE based solutions.
Implementation of Low Power Carry Skip Adder using Reversible Logic

Addition is a vital arithmetic operation. It is the base of commonly used arithmetic operations such as division, subtraction, and multiplication. Adder is a digital circuit that accomplishes addition of numbers. The one bit full adder is the basic block of an arithmetic unit. There are several adder designs implemented so far to reduce the power. However, each design suffers from exact drawback. Reversible logic is the growing technology in the current era. The numbers of input and output lines in reversible logic are equal. In reversible logic the inputs are to be recovered from the outputs. Reversible logic gates are defined by the user. In this paper Carry Skip Adder (CSKA) is implemented in two different designs i.e. design-I and design-II. Design-I is implemented using Peres gates with irreversible (XOR, AND, OR) logic gates. Design-II is implemented using PERES, TOFFOLI, and FREDKIN reversible logic gates. Design-I and design-II designs are synthesized and simulated by Mentor Graphics tool. Design-II is more efficient in terms of transistor count and power consumption compared to Design-I.
Identity Based Encryption and Identity Based Signature Scheme: A Research on Security Schemes

In computer based system, key for the problem of identification, authentication and secrecy can be found in the field of cryptography. Dependence on public key infrastructure and to receive certificates signed by Certificate Authority (CA) to authenticate oneself for exchange of encrypted messages is one of the most significant limitation for the widespread adoption of Public Key Cryptography (PKC) as this process is time engrossing and error prone. Identity based cryptography (IBC) aspires to reduce the certificate and key management overhead of PKC. IBC’s important primordial is Identity-based Encryption (IBE). IBE provided emergent for perception of Identity based signature (IBS) schemes. In this paper, overview of IBE and IBS schemes has been given. Also, a survey on various IBE and IBS schemes has been performed to review different problems related to them. Finally, feasibility and applicability of IBC in current and future environments has been discussed.
Penggunaan Media Word Webs Dalam Pembelajaran Kosa Kata Bahasa Inggris Di Sdnn 01 Suruh Tasikmadu Karanganyar

English learning for children called English for Young Learners (TEYL) is developing in various parts of the world, especially in developing countries including Indonesia. This policy began in Indonesia since the enactment of the 1994 Curriculum, and its implementation continues to be increasingly necessary. This is related to the government's efforts to prepare reliable and quality students, who will be able to compete at the national and international levels. English has become a very important language in the international community. Therefore, everyone is expected to be able to learn, master and understand English well. In Indonesia, English occupies an important priority as the first foreign language that must be studied and mastered by students and has been taught in schools ranging from kindergarten to university level. In learning English, there are four (4) language skills that must be learned by students, namely listening, speaking, reading, and writing. One of the important language skills to be learned by students is speaking. One element of language that needs to be improved to support speaking skills is vocabulary. Vocabulary plays an important role in word recognition. The more English vocabulary that is owned and mastered by students, the better they are at understanding various learning materials delivered in English. Mastery of a large and extensive English vocabulary can also improve students' ability to communicate using English. The introduction of English vocabulary in SDN 01 Suruh Tasikmadu Karanganyar can use learning media that is fun, easy and effective. The learning media is Word Webs. The Word Webs media has the benefit of increasing students' knowledge of English vocabulary and strongly supports speaking skills. Word Webs learning media is a learning media that can be used in the teaching and learning process of English especially Vocabulary. Through this Community Service Activity or Pengabdian Kepada Masyarakat, learning English using Word Webs media at SDN 01 Suruh Karanganyar feels more fun and memorable. This will make students feel enthusiastic and happy in learning English provided by using Word Webs media. This media can also help teachers in teaching English vocabulary to support students' speaking skills with fun.
Hand Gesture Recognition using Convexity Defect

Gestures are the simplest way of conveying a message, rather simpler than verbal means. It is the most primitive way of conversation. Gestures can also be the easiest and intuitive way of communicating with a computer, they can be used to communicate or convey information to computers, robots, smart appliances and many other pieces of machinery. It can eliminate the use of mouse and keyboard to some extent. The gestures cited are basically the variable positions as well as orientations of the hand. They can be detected by a simple webcam attached to the computer. The image is first changed into its corresponding RGB values and then to HSV values for better handling and feature recognition. The hand is segregated from the background using feature extraction. Then the values are matched in proximity of the coded values. Then the region of interest is calculated using the concept of convexity and background subtraction. The convex defect helps to define the contour efficiently. This method is invariant for different positions or direction of the gesture. It is able to detect the number of fingers individually and efficiently.
Development of the Edible and Poisonous Mushrooms Classification Model by using the Feature Selection and the Decision Tree Techniques

This research aims to develop a classification model for edible and poisonous mushrooms by applying the feature selection approach together with the decision tree technique. Two feature selection methods were applied, including 1) Chi-square and 2) Information Gain, while the effectiveness of the model was compared by three decision tree methods such as Iterative Dichotomiser3, C4.5 and Random Forest. The data used for classifying the edible and poisonous mushrooms derived from the Encyclopedia of Thai mushrooms and the book entitled “Diversity of Mushrooms and Macrofungi in Thailand”. The results of the model’s effectiveness evaluation revealed that the model using the Information Gain technique alongside with the Random Forest technique provided the most accurate classification outcomes at 94.19%; therefore, this model could be further applied in the future studies.
Design and Development of Financial Fraud Detection using Machine Learning

Financial ifraud iis ia igrowing iconcern iwith ifar ireachingconsequences iin ithe igovernment, icorporate iorganizations,finance iindustry, iIn iToday's iworld ihigh idependency ioninternet itechnology ihas ienjoyed iincreased icredit icardtransactions ibut icredit icard ifraud ihad ialso iacceleratedasonline iand ioffline itransaction.iAs icredit icardtransactions ibecome ia iwidespread imode iof ipayment, ifocus ihas ibeen igiven ito irecent icomputational imethodologies ito ihandle ithe icredit icard ifraud iproblem.iFinance ifraud iis ia igrowing iproblem iwith ifar iconsequences iin ithe ifinancial iindustry iand iwhile imany itechniques ihave ibeen idiscovered.iMachine ilearning ihas ibeen isuccessfully iapplied ito ifinance idatabases ito iautomate ianalysis iof ihuge ivolumes iof icomplex idata.iDatamining ihas ialso iplayed ia isalient irole iin ithe idetectionof icredit icard ifraud iin ionline itransactions.iFrauddetection iin icredit icard iis ia idata imining iproblem, iItbecomes ichallenging idue ito itwo imajor ireasonsfirst,theprofiles iof inormal iand ifraudulent ibehaviors ichangefrequently iand isecondly idue ito ireason ithat icredit icardfraud idata isets iare ihighly iskewed.iThis ipaper iuses iofDecision itree, iRandom iForest, iSVM iand ilogisticregression ion ihighly iskewed icredit icard ifraud idata.Recent iresearch ihas ishown ithat imachine ilearningtechniques ihave ibeen iapplied ivery ieffectively ito itheproblem iof ipayments irelated ifraud idetection.iSuch iMLbased itechniques ihave ithe ipotential ito ievolve ianddetectpreviously iunseen ipatterns iof ifraud.iIn ithispaper, iweapply imultiple iML itechniques ibased ionLogisticregression iand iSupport iVector iMachine ito itheproblemof ipayments ifraud idetection iusing ia ilabeleddatasetcontaining ipayment itransactions
The Role of Human Resource Management in the Context of Jordanian Higher Education: A Study of the Literature

This paper explores the role of Human Resource Management (HRM) in the context of Jordanian Higher Education (HE) through an evaluation of its application and development. The research is based on a systematic literature review and a content analysis of 18 peer-reviewed journal articles published between 2000 and 2018. The findings show that the role of HRM is constructive, yet traditional, operational, and underdeveloped in its application. This study also identified a range of unexplored areas of research that call attention to future context-related studies in the field of HRM.
Balint Technology in Pedagogy: Innovations or Transfer of Psychological Experience

The article considers individual problems in the field of vocational education and personnel training of specialists in education, possibilities of using innovative technologies in educational institutions of higher education, aimed at achieving the goals of education at a relevant level, as well as contributing to professional integration and psychological support of both students of vocational educational institutions of the pedagogical profile, and teaching staff.
COMPARATIVE ANALYSIS OF THE DEVELOPMENT OF ENGINEERING AND HUMANITARIAN STUDENTS’ LEARNING SKILLS

The aim of this research is identifying differences in the development of learning skills of students of engineering and humanitarian orientation in the process of their training at the University. Learning skills, as the ability to carry out the process of acquiring subject knowledge in various fields, are recognized by world experts. The importance of learning skills has increased especially at the present time, due to the need for self-development of competence in the process of professional activity after graduation. In the course of the study, the main and supplementary learning skills, as well as the ability to self-regulate training activities and academic performance of students of technical and humanitarian orientation, who are at different stages of training, were diagnosed. The results of this study show that the learning skills of students in both directions develop sideways in the process of subject learning, but this process has different results and character in relation to their development. Thus, engineering students have a higher level of learning skills and self-regulation by the end of their studies, while humanities students have a higher level of exposure to supplementary learning. Basic learning skills are developed better among engineering students with higher abilities to self-regulate learning activities, while for psychology students, this relationship is not found. In addition, the academic performance of engineering students increases with a high level of development of knowledge-building abilities, control of additional learning skills and self-regulation of educational activities. Academic performance of students in the Humanities increases with a high ability to implement independent building of knowledge, a high level of control over the motivational and volitional sphere and learning goals, as well as the ability to evaluate results in the course of educational activities.
Psychological perception by students of prosocial media

П. А. Кисляков, Е
METHODOLOGICAL DIFFICULTIES OF TEACHERS IN THE PROCESS OF USING INNOVATIVE PEDAGOGICAL TECHNOLOGIES

This article describes an experiment to study the methodological difficulties of teachers in the process of using innovative pedagogical technologies.On the basis of Moscow "School No. 1593" and Ulyanovsk "Mariinskaia Gymnasium" there was carried out the experimental work, which determined the understanding of teachers of the essence and main features of pedagogical technology, the distribution of time for preparing and conducting lessons and extracurricular activities, typical for the work of teachers in the capital and provincial schools.The problem is formulated related to the use of innovative forms of organization of training.
Automated Writing Evaluation: The Accuracy of Grammarly’s Feedback on Form

Automated Writing Evaluation (AWE) is gaining more and more presence, with Grammarly being a prominent example of this kind of software, which provides automated feedback on essay writing.While the Grammarly advertisement is full of praise regarding its ability to give meaningful feedback at various levels, including grammar or form, plagiarism, vocabulary and style, there has been little third party research to support these claims.Since Grammarly's vocabulary feedback accuracy has already been examined to some extent (Dodigovic, Mlynarski & Wei, 2016), this study was designed to evaluate the accuracy of Grammarly's grammar checker feedback.It did so by investigating the reports generated by Grammarly as a response to a small corpus of EFL writing, compiled from essays written by Armenian undergraduate students.The results were compared with those of human raters.In addition to Grammarly's error detection power, the study also investigated the kind of remediation that Grammarly suggested.The comparisons revealed that on detected errors of form, Grammarly mostly provides accurate feedback, with occasional inconsistencies.It was also found to provide mainly adequate remediation for the correctly detected errors of form.However, it also left a number of errors undetected, which led to the omission of remediation.The study concluded that, despite its considerable usefulness, when using Grammarly, English learners should avoid relying solely on its feedback.
Standard Statistical and Graph based Automatic Keyword Extraction

Automatic extraction of terms from a document is essential in the current digital era to summarize the documents. For instance, instead of go through the full documents, some of the author's keywords partially explain the discussions of the documents. However, the author's keywords are not sufficient to identify the whole concept of the document. Hence the requirement of automatic term extraction methods is necessary. The major categories of automatic extraction approaches falls mainly on some techniques such as Natural Language Processing, Statistical approaches, Graph Based approaches, Natural Inspired algorithmic approaches, etc. Even though there are numerous approaches available the exact automatic keyword extraction is a major challenge in areas, that reveals around documents. In this paper, a comparative analysis of Keyword extraction between standard Statistical approaches and Graph based approaches has been conducted. In standard statistical approaches, the terms are extracted on the basis of physical counts and in the Graph based approach, the documents are automatically constructed as graphs by applying centrality measures during the keyword extraction process. The results of both approaches were compared and analyzed.
A Fault Tolerant Han-Carlsonadder using Tmr Technique

A fault tolerant Han-Carlson adder is implemented using TMR technique. This paper suggests a technique of Triple Mode Redundancy (TMR) in which the vote is processedto produce a single output by a majority voting system.Synthesis and simulation are performed using Vivado(Xilinx). The circuitry is basically repeated in triplicate, as the name suggests, with a voting circuit used to transmit to the output the majority rule signals.
Transposition Algebras

The symbiotic relationship between groups and algebras goes back at least to Sophus Lie, who introduced Lie algebras to support the study of Lie groups.Later the classification of finite dimensional, complex, semisimple Lie algebras was in turn reduced (primarily by Weyl) to the classification of finite groups generated by Euclidean reflections.The topics discussed here had a similar start.Algebras were introduced to aid in the construction of finite simple groups, particularly those that are sporadic.These algebras then found a broader context, and there groups were reintroduced to aid in construction and classification.
Algorithm for Clustering the Moduli of RNS for the Application of Optimization of Time Complexity in Standard Cipher System

Residue number system (RNS) has emerged as a knocking field of research due to its high speed, fault tolerant, carry free and parallel characteristics. Due to these features it has got important role in high performance computing especially with reduced delay. There are various algorithms have been found as a result of the research with respect to RNS. Additionally, since RNS reduces word length due to the modular operations, its computations are faster compared to binary computations. But the major challenges are the selection of moduli sets for the forward (decimal to residue numbers) and reverse (residue numbers to decimal) conversion. RNS performance is purely depending on how efficiently an algorithm computes / chooses the moduli sets [1]-[6]. This paper proposes new method for selecting the moduli sets and its usage in cryptographic applications based on Schonhage modular factorization. The paper proposes six moduli sets {6qk1, 6qk+1, 6qk+3, 6qk+5, 6qk+7, 6qk+11} for the RNS conversions but the Schonhage moduli sets are expressed as the exponents that creates a large gap between the moduli’s computed. Hence, a new method is proposed to for computing moduli sets that helps in representing all the decomposed values approximately in the same range.