Reviewerly/exHarmony huggingface dataset:
Study On Impact Of Self-Realization And Its Impact On Employee Engagement

Engaged Employees deeply and proudly recognize themselves physically, cognitively, and emotionally connected with the organization throughout performances in varied roles within the organization. They act as drivers of monetary and market success. They provide outstanding performances by attempting to stretch themselves and endlessly attempt to reach the goals by setting new standards of excellence. Due to this, Employee engagement has gained momentum in business organizations across the world. Employees are engaged only when organizations have healthy work culture and communication practices, wherever they get platforms to and opportunities to grow and develop their potential. These days’ competitors will emulate the performance of the service provided however they cannot replicate the vigour, dedication, and absorption of their employees at the workplace. With this introduction, this paper outlines how Employee engagement may be enhanced through self-realization in retail service sectors.This study provides a methodology for measuring impact of these antecedents on facilitating employee Engagement. This study seeks to research the link between every dimension of self-realization and employee engagement and is an attempt to work out whether Employees’ perceptions of organizational culture are associated with their level of employee engagement.
A STUDY ON USAGE BEHAVIOUR TOWARDS VIRTUAL ASSISTANT WITH SPECIAL REFERENCE TO HOME USERS IN CHENNAI

Virtual assistant is boon for everyone in this new era of 21st century. It has paved way for a newtechnology where we can ask questions to machine and can interact with Intelligent VoiceAssistant as people do with humans. This new technology attracted almost whole world in manyways like smart phones, laptops, computers etc. Some of the significant Voice Assistants are likeSiri, Google Assistant, Cortana, and Alexa. IVAs are becoming increasingly popular but stillenthusiasm inside the people has been developing. The users requesting the climate, makingnotes, requesting headings, composing an instant message, requesting an address and setting aschedule and found that members were very positive to utilizing discourse interfaces. There werestill some improvements in voice speech recognition and people are searching best in contextualunderstanding too. The basic requirements of a user is to feel free and work in relax way.Virtual assistants can do everything from answer questions, tell jokes, play music, and controlitems in the home such as lights, thermostats, door locks, and smart home devices. They canrespond to many voice commands, send text messages, make phone calls, set up reminders.
THE USE OF COMMUNICATION STRATEGIES BY THE TEACHER IN ESP CLASS AT UNIVERSITY OF MUHAMMADIYAH MALANG

Teaching in the classroom by using English has raised the problem. The students faced the problem to understand the teacher’s talk because of lack of vocabulary. In order to solve this, the teachers are able to communicate to the students actively by using their hands, imitating sound, inventing new words, or describing what they mean. These ways of communicating are called communication strategies (CSs). EFL teachers are not always aware of the importance of teaching communication strategies to their students or, if they are aware, they do not explicitly train their students to use them. They do not use these strategies themselves to serve as a model to their students. This study investigated the communication strategies used by the teacher in ESP Class and the potential factors that influence the communication strategies they use in the class. The data came from three sources: (1) Transcription from audio recording of the teacher in teaching and learning process. (2) Interview with the teacher. (3) And observation note taking during the process of teaching. The results indicated that the most frequently communication strategy used by the teacher in class is code-switching, and learning activity, students’ comprehending and teacher’ habit are factors that influenced the communication strategies used.
The Teaching Dimension of Kernel Perceptron.

Algorithmic machine teaching has been studied under the linear setting where exact teaching is possible. However, little is known for teaching nonlinear learners. Here, we establish the sample complexity of teaching, aka teaching dimension, for kernelized perceptrons for different families of feature maps. As a warm-up, we show that the teaching complexity is $\Theta(d)$ for the exact teaching of linear perceptrons in $\mathbb{R}^d$, and $\Theta(d^k)$ for kernel perceptron with a polynomial kernel of order $k$. Furthermore, under certain smooth assumptions on the data distribution, we establish a rigorous bound on the complexity for approximately teaching a Gaussian kernel perceptron. We provide numerical examples of the optimal (approximate) teaching set under several canonical settings for linear, polynomial and Gaussian kernel perceptrons.
Uniformization of hyperelliptic curves as a systematic approach to establishing decision regions of hyperbolic signal sets

In this paper, we present a new approach to designing hyperbolic signal sets matched to groups using Whittaker’s proposal in the uniformization of hyperelliptic curves via Fuchsian differential equations (FDEs). This approach provides a systematic procedure of establishing the decision region (fundamental polygon) of a hyperbolic signal as well as the associated Fuchsian group, and consists of the following four steps: (1) Obtaining the genus, g, by embedding a discrete memoryless channel (DMC) on a Riemann surface; (2) Selecting a set of $$(2g+1)$$ or $$(2g+2)$$ symmetric points in the Poincaré disk to establish the hyperelliptic curve; (3) From the FDE via algebraic manipulations to arrive at the hypergeometric differential equation (HDE) to obtain the solutions; and (4) Quotients of the FDE linearly independent solutions give rise to the generators of the associated Fuchsian group whose subgroup provides the uniformizing region, implying the determination of the decision region (Voronoi region) of a digital signal. Hence, the following results are achieved: (1) from the solutions of the FDE, the Fuchsian group and subgroup generators are established, and consequently, the desired signal set matched to the Fuchsian subgroup may be constructed; (2) a relation between the parameters of the $$\{p,q\}$$ tessellation and the degree of the hyperelliptic curve is established. Knowing g, related to the hyperelliptic curve degree, and p, the number of sides of the fundamental polygon derived from Whittaker’s uniformizing procedure, the value of q is obtained from the Euler characteristic leading to one of the $$\{4g,4g\}$$ or $$\{4g+2, 2g+1\}$$ or $$\{12g-6,3\}$$ tessellation. These tessellations are essential for their rich geometric and algebraic structures, both required in classical and quantum coding theory applications.
Developing Synthetic Materials for Percussion Instruments

There is a need for new, sustainable materials to make wooden percussion instruments. Many of the woods used in producing these instruments are exotic or endangered woods. Some companies have switched to fiber-reinforced (glass or carbon) plastics or polymers, but these instruments do not always have the desired sound. Without the necessary desired sound and an increasing need to replace wood, attention must be given to studying and experimenting with other materials. Research shows that the properties of different woods are critical when selecting which materials to use in which instruments. The Young’s Modulus, hardness, density, grain direction, and adaptability to moisture are the properties that determine the speed and color/tone of the sound of the instrument. Data was collected to determine what types of sounds and responses musicians favor in percussion instruments. With that in mind, analyzing the frequency response of different materials are key. Vibrational analysis of soundwaves using a vibrometer, to study the frequency difference between a reference laser and a beam testing a surface, was performed to quantify the difference in the sound of traditional wood instruments along-side synthetic material made instruments. Such information reveals the properties desired and responses that must be replicated when designing new synthetic materials for instrument making. Using the data collected, production of a sustainable prototype materials can begin.
LibGuides: Library Helpful Hints for Off-Campus Use: Blue Tooth Keyboard for smart phones

A guide to help students access library resources to complete assignments when they are not on campus An option to help you use your smart phone as a computer if a laptop or desk top computer is not available.
Privacy Preservation, Data Mining

The growing popularity and development of data mining technologies bring serious threat to the security of individual's sensitive information. An emerging research topic in data mining, known as privacy preserving data mining (PPDM), has been extensively studied in recent years. The basic idea of PPDM is to modify the data in such a way so as to perform data mining algorithms effectively without compromising the security of sensitive information contained in the data. Current studies of PPDM mainly focus on how to reduce the privacy risk brought by data mining operations, while in fact, unwanted disclosure of sensitive information may also happen in the process of data collecting, data publishing, and information (i.e., the data mining results) delivering. The author is trying to reduce the privacy risk brought by data mining operations. Privacy among the data provided is maintained. That is by preventing the any data leak, data movement or any third party access to it. Also maintain the refresh rate for third party access and performed the data mining using the k-means clustering. The collected data is showed in graph format which shows the histogram of average improvement of structure.
Ran Method That Performs Nested Scalable No SQL Transaction and Data Analytics

Last decade records a large quantity of data transition occurring web. Today’s world is connected by Social Networking sites that have immense size of databases. Currently, there's no utility existing for remodeling SQL databases into NoSQL databases. NoSQL could be a new trend; there's no software system or utilities that are designed for the specified conversion. Most of the utilities developed, were developed for changing one variety of SQL database to a different SQL database. To market Hybrid database design together with an electronic information service and NoSQL database, an information Adapter system is planned. It will affect database transformations employing a database synchronization mechanism. It focuses on sanctioning effective database Analytics on Scaled-out Object Storage Systems. There's implementation of a database. Analytics Layer on associate degree Object based Storage Cluster to perform in-place Map-Reduce computation on existing data. It keeps the strengths of RDBMS as ACID properties and at an equivalent time by providing the advantages of NoSQL through a middle layer that keeps track of all running transactions and manages with alternative layers with co-occurring transactions. The info Adapter uses a SQL layer acceptive queries from application services, in order that original application remains intact. The info Adapter conjointly controls question flow throughout information transformations. Associate degree approach that performs computation on existing large-scale information in associate degree Object Storage system while not moving information anyplace and outcomes of this approach are analyzed. This define will deliver strict consistency while not poignant measurability and handiness of NoSQL Databases.
Insurance Process using Blockchain

Blockchain is a fast disruptive technology becoming a key instrument in the shared economy. In recent years, Blockchain has not only received a considerable amount of attention from many research and government institutions but also from academy and industry. Since it is considered a breakthrough technology, it could bring benefits to many different sectors. Insurance is one of the sectors that, among others, which started to carefully examine the possibility of blockchain. The field of Insurance has taken a giant leap at the threshold of the twentieth century. Over time insurance has become an integral part of the life of man all over the world.Claim management is one of the most challenging business processes in the insurance sector. With the number of stakeholders involved, the dependencies and the logistics, there is a need to eliminate manual involvementsInsurance process is an expert system which generates the rules and regulations for the assessment of general damage using the key information in the medical report, surveyor report, loss accessor’s report. The insurance process regulates the payment of general damages also payment of the loss of future earnings.The objective of the paper is to give a gist about how the insurance company settles the claims, the procedure that is followed, which does not involve any intermediate.
V-ML: VISUALIZATIONS FOR MACHINE LEARNING

Data visualization is a quite new and promising field in computer science. It uses computer graphic effects to reveal the patterns, trends and relationships out of datasets. However, there is a dearth of visualization tools for deep learning algorithms along with the details buried in the algorithms that are properly accounted for. Gaining an understanding of this technology is somewhat difficult. While the theory is important, it is also helpful for novices and users not familiar with machine learning to develop an intuitive feel for the effect of different hyperparameters and structural variations. We propose a visualization tool for some of these algorithms along with the description of “intricate details” that often result in novices describing them as ‘black boxes’.
Current Trends in Insurance Fraud in Russia: Evidence from a Survey of Industry Experts

This study aims to explore the current trends in fraud prevention in the insurance industry in Russia. Survey responses from 20 experts and professionals of the leading insurance companies in Moscow were collected. More than a half of them are former police officers who work at security or investigation departments. Survey data analysis was employed. According to the experts’ opinion, existing gaps in the legislation and difficulties in cooperation with the police are the main sources of inefficiency of fraud prevention strategies utilised by the Russian insurance companies. The respondents agreed that both insurers and fraudsters actively use new technologies. Fraudulent claims in compulsory third party liability motor insurance remain the most common activity among Russian criminals, although they quickly expand to health and property insurance. Typically, an insurance fraudster is a 34-year old male with a college/university degree who cooperates with an insurance broker in 42 percent of cases. Based on this, a set of recommendations aimed at increasing the efficiency of insurance fraud prevention was produced.
An Algorithm for Concurrency control in Transactions for E Wallet

It is a period of online exchanges, managing daily installments through e-wallet for shopping, paying to merchant, also to fulfill all the liquid cash requirement through wallet money with no physical notes or currency involved for transaction, wallet exchange help to web advancements. The cash move and gross repayment is conceivable in only hardly any seconds. The web innovations have been utilizing and still new idea dependent on past encounters are currently coming into exploration and confab. A lot of research papers for wallet creation and inner cycle are accessible. Uncommonly, wallet measure through various methodologies like BC (Bank Channel) Wallet, RBI Wallet, Domestic Pay Service Wallet are principle thought in this exploration work. The exchange cycle faces numerous issues, these issues influence the backer, bank, client regarding misfortune in business. Whereas the client is additionally unsatisfied and unable to do finish wallet procedures. This paper presents a recreation examination of the versatility on simultaneous exchange handling over a combination of portable and fixed exchanges, because of moderate organization availability and down worker might be a similar exchange prepared twofold because of which RBI rules infringement happen and backer, client, bank, specialist all is grieved and misfortune the real business. This paper execution normally utilizes conflict location dependent on the Hidden label bases exchange accommodation through which copying any exchange is preposterous, it ensures that every exchange has prepared just a solitary path under RBI rules or wallet terms.
Rule Discovery for Exploratory Causal Reasoning

We study the problem of discovering reliable causal rules from observational data.Traditional descriptive rule discovery techniques do not suffice to this end, asthey struggle with the consistent detection of (potentially rare) conditions thathave a strong effect on an output variable of interest. Among the sources ofinconsistency are that naive empirical effect estimations have a high variance,and, hence, their maximization is highly optimistically biased unless the searchis artificially restricted to high frequency events. Secondly, observational effectmeasurements are often highly unrepresentative of the underlying causal effectbecause they are skewed by the presence of confounding factors. This is a concernespecially in scientific data analysis.To address these issues, we present a novel descriptive rule discovery approachbased on reliably estimating the conditional effect given the potential confounders.We demonstrate that the corresponding score is a conservative and consistent effectestimator, identify the admissible data generation process under which causalrule discovery is possible, and derive an efficient optimization algorithm thatsuccessfully detects valuable rules on a multitude of real datasets. Important forboth causal and associational data exploration, the presented approach naturallyallows for iterative rule discovery, where new non-redundant rules can be found bytreating previously discovered rules as confounders in subsequent iterations.
Evoking Emotions from Tweets: lexicon based method of Sentimental Analysis

AbstractTwitter a micro-blogging platform has gained huge popularity for its instant and quick information diffusion feature. Marketers are increasingly using social media to disseminate information related to their products and promotions on the social media. The robust growth of banking sector and its convergence with the new technology has brought in the revolutions in the economy. The purpose of the study is to ascertain the sentiment of the customers of India’s leading private bank on the popular social media platform “Twitter”. The study collects 5000 recent tweets of hdfc bank from its customer care twitter handle. The article uses R software for analysis and R studio for graphical interface to perform NLP - sentiment analysis using the “syuzhet” package given by saif mohammad which is based on NRC lexicon. Findings of the study reveal that people have positive sentiment towards hdfc bank and customers trust the bank. The findings also reveal the presence of considerable negative sentiment and display of sadness emotion. Emotions of anticipation are also on the higher side which state that people have higher expectations from the bank and its products and services. The study provides insights to managers of hdfc bank by suggesting them to reduce negative sentiment and sadness emotions of the customers by handling issues and complaints more effectively and indulge more in promotional activities which could surprise and delight their customers since these emotions are on a lower score. The study also states its shortcomings and also hints future researchers by providing limitations and avenues of future research which is across platforms and sector.
A Comprehensive Look at Korean Language Functions and Discourse Competence in the Works by Nikolai Spafariia and Lorenz Lang

Jakobson's model of the functions of language distinguishes six elements, or factors of communication, that are necessary for communication to occur: (1) context, (2) addresser (sender), (3) addressee (receiver), (4) contact, (5) common code and (6) message. To fulfill, this study tried to have a comprehensive look at Korean language functions and discourse competence in the works of Nikolai Spafariia and Lorenz Lang. Studying Korea in Russia has a long and meaningful history, which began in the XVII century and continued to develop intensively already from the end of the XIX century. The first complete and realistic description of the Korean state was given by the Russian traveler and ambassador to China - Nikolai Spafariia. The data collected by N. Spafariia and the works provided to Russian society, in particular, the chapters providing sufficiently complete information about a hitherto little-known country - Korea, were the first works that told about the history, economy, and culture of this country. As well as N. Spafaria, L. Lang made a great contribution to collecting information about the Korean state, in particular about trade.  Until the end of the XVIII century, detailed information about Korean trade collected by L. Lang was a reliable source both for Russian and for Western European researchers.
Primary School Pre-Service Teachers' Perceptions of Effective Online Learning by Using LINE Application during Covid-19 Pandemic

The Covid-19 pandemic that has hit Indonesia since March 2020 suddenly forced learning from elementary to tertiary levels to be carried out online. The LINE application is a social media platform that has live features. This application is an alternative that is used as a means of emergency learning during the Covid-19 pandemic. This study aimed to describe the perceptions of Sanata Dharma University PGSD students on the effectiveness of online learning using the LINE application. The subjects of this study were 252 students. The method used is descriptive quantitative through online surveys. This study's results were the students' perceptions of using the LINE application on the effectiveness of learning showed that 73.4% of students received clear levels of information. As many as 67, 9% of students stated that they were ready to accept learning, as many as 71% of students were motivated, as many as 58.7% of students stated that they were effective in terms of time, 63.5% of students felt that the learning objectives were achieved, as many as 67.9% of students stated that the use of LINE was quite attractive and interactive, and 71% stated that the use of the LINE application was sufficient to support learning. Students also conveyed that the advantages of this application are saving on internet quota usage, while the weakness of this application is the absence of a recording feature. This research concludes that students' perceptions state that using the LINE application is effective for learning. 5% of students felt that the learning objectives were achieved, as many as 67.9% of students stated that the use of LINE was quite attractive and interactive, and as many as 71% stated that using the LINE application was sufficient to support learning. Students also conveyed that this application's advantages are saving on internet quota usage, while the weakness of this application is the absence of a recording feature.