Reviewerly/exHarmony huggingface dataset:
몽골인 학습자의 한국문화 인식 조사 연구

This study aims to determine the degree of Korean cultural cognition in Mongolian learners studying the Korean language and culture. Korean language learners in Mongolia face the issue of being unable to directly become acquainted with Korean culture. Therefore, there is a need to organise training that creates a cultural learning classroom environment and decreases culture shock to support Korean cultural cognition. Within the framework of the research, the learners’ knowledge, and attitude towards Korean culture, cultural experiences, obstacles caused by Korean and Mongolian cultural differences, and overcoming of these obstacles were identified. In doing so, this study defined the Korean cultural cognition of the Mongolian learners. Specifically, its predominant finding was based on a survey conducted among the learners at Ulaanbaatar 2 Sejong Institute. First, teaching institutions, movies, and dramas play a primary role in learning Korean. Second, the knowledge of the Mongolian learners of Korean culture was reasonably high, at 52.2%-90.4%. Third, 52.6%-86.2% of the learners have some Korean cultural experience. Fourth, the cultural attitude of the learners towards Korean culture was 62.2%-91.6% positive. Last, 62.2%-91.6% of the learners reported a certain cultural difference between Korean and Mongolian cultures. 66% of the learners admitted that they had faced some obstacles caused by cultural differences. However, they emphasised that they are learning to overcome such obstacles.
Ensemble Learning Improvement through Reinforcement Learning Idea

Ensemble learning is one of the learning methods to create a strong classifier through the integration of basic classifiers that includes the benefits of all of them. Meanwhile, weighting classifiers in the ensemble learning approach is a major challenge. This challenge arises from the fact that in ensemble learning all constructor classifiers are considered to be at the same level of distinguishing ability. While in different problem situations and especially in dynamic environments, the performance of base learners is affected by the problem space and data behavior. The solutions that have been presented in the subject literature assumed that problem space condition is permanent and static. While for each entry in real, the situation has changed and a completely dynamic environment is created. In this paper, a method based on the reinforcement learning idea is proposed to modify the weight of the base learners in the ensemble according to problem space dynamically. The proposed method is based on receiving feedback from the environment and therefore can adapt to the problem space. In the proposed method, learning automata is used to receive feedback from the environment and perform appropriate actions. Sentiment analysis has been selected as a case study to evaluate the proposed method. The diversity of data behavior in sentiment analysis is very high and it creates an environment with dynamic data behavior. The results of the evaluation on six different datasets and the ranking of different values of learning automata parameters reveal a significant difference between the efficiency of the proposed method and the ensemble learning literature.
The Cross-Domain Identity Authentication Scheme Has no Trusted Authentication Center in the Cloud Environment

This paper analyzes the existing problems of cross-domain authentication models and proposes a new cross-domain authentication model because there is no trusted authentication center in the cloud environment. The model is based on the certificateless public-key cryptosystem. It takes advantage of the transformability of heavy signature; A resigned proxy is introduced between two different domains for identity transformation. The authentication work is mainly concentrated in the key generation center KA and Proxy in different domains to reduce information interaction and computation between users and cloud service providers. At the same time, this message’s identity information is added to each request message of the user, and check the identification information in the received reply message to confirm whether it is a reply to the application message. This method can prevent malicious attacks and improve security. The results show that the scheme satisfies key security, message unforgeability, and communication information confidentiality.
Tfd: Telecom Fraud Detection Using Consolidated Weighted Reputation Algorithm

Noisy phone calls are aggravating and distracting, as well as frustrating. They may be classed as 'nuisance', 'emergency', 'random', and 'unsolicited' calls. Users have no inherent privileges on the internet; rather, their personalities are produced without any arrangement or evidence of involvement. It costs the U.S. communications company $8 billion per year to avoid call spam on the phone grid. Between January 2014 and June 2018, the FTC (Federal Trade Commission) received over 22 million reports of fraudulent and illegal telemarketing calls. Nowadays, the mobile network is used to issue automatic phone calls such as robocalls. Since it operates on text, we struggle with the following: What tactics and methods do we use to combat spam? Telephone TFD (Telecom Fraud Detection) here is discussed first. Concerning spam, we advanced our proposal by proposing a targeted traffic detection using a single weighted credibility algorithm with appropriate weighting criteria.
A framework based on security issues in cloud computing

This paper is focused on the topic framework based on security issues in cloud computing. This paper present’s a good description of cloud computing. It tells about different types of cloud SaaS, PaaS, and IaaS and its characteristics. It also describes disadvantages of it which may lead to security issues. We did a good review of previous works which represented many ideas for a framework. This paper discusses threats like malicious insider, data breaches, etc. This paper also describes attacks and ways to protect them. A framework was designed through which we can very easily protect sensitive data from unauthorized use.
Generation of Rectangular Matrix Key for Hill Cipher Algorithm Using Playfair Cipher

Hill cipher is a cryptographic algorithm that uses matrix as a key by utilizing modulo operations. The key matrix used is usually made randomly as a square matrix. In this study, a key matrix was created using the Playfair Cipher algorithm as a rectangular matrix. The use of the Playfair Cipher algorithm makes it easy for users to remember key matrices, while remaining safe when distributed. Beside the key matrix security, use of a rectangular key matrix produces a longer and more complicated ciphertext to find the linear equation.
STRATEGIES TO INCREASE PURCHASE OF DATA PACKAGES FOR TELKOMSEL KARTUHALO CUSTOMERS

The number of Telkomsel customers as of March 2018 is 196.3 million, which 105.8 million are customers with active user data categories. Based on data from Telkomsel, it can be seen that the majority of Telkomsel customer data usage is dominated for the use of Communication, Social, and Video. That Telkomsel can do Clustering based on customer behavior and make a combination of data packages that match with the characteristics of each group, it will make it a new breakthrough for Telkomsel to increase data package purchases. The purpose of this study was to determine the characteristics of kartuHALO customers and determine the number of clusters that match with the characteristics obtained. Then determine the right strategy for Telkomsel to increase the purchase of data packages for KartuHalo customers The theory approach used in this research is Marketing Mix, Pricing Strategy, Market Segmentation, Customer Behavior, and Personalized Marketing. Data collection method is done by using kartuHalo customer population data along with pre-defined variables that have been determined based on expert opinions which are then tested for significant variables using the Random Forest algorithm. Then from the variables chosen based on ranking used for cluster formation with the K-Means method. Analysis and processing of data is done using SPSS modeler software Keywords: Clustering, K-Means, Personalized Marketing
The evolution of Blockchain and it’s adoption

A blockchain is at its core a spread data set of exchanges and records, alternatively state it as a public record of the multitude of exchanges and digitals occasions that have occurred even once between the sharing gatherings. Each execution in the public record or you can call it as an open record is checked and confirmed by generally most of the individuals holding the public record. Once input, data can’t be erased. The blockchain contains guaranteed and obvious record noted of every exchange made anytime. The Bitcoin, happens to be the most standard model that uses blockchain innovation. The advanced type of cash bitcoin itself is astoundingly faulty anyway the major blockchain innovation has worked immaculately and found huge extent of employments in both the worlds, monetary and non-monetary.&#x0D; The fundamental thought behind blockchain is the establishment that it sets for a framework where a conveyed lion's share is needed in the online computerized world. This encourages anybody needing to take an interest to check if a specific exchange occurred ever. You can modify Public Ledger holding of a couple or state a couple of more than that however won't have the option to fulfill the rest and henceforth the occasion would perhaps come up short. Blockchain has made it conceivable to build up a non-inclination, open and versatile advanced economy for incorporated type of frameworks also.&#x0D; This entire paper would tell you the pro et contra of the Blockchain Technology and furthermore, it's applications in the monetary and non-monetary world. We will likewise discuss the different chances that Blockchain Technology has opened up for different organizations and would definitely be an innovation that would acquire the upset in the period of Internet.
A Framework for Integrating Gesture Generation Models into Interactive Conversational Agents

Embodied conversational agents (ECAs) benefit from non-verbal behavior for natural and efficient interaction with users. Gesticulation – hand and arm movements accompanying speech – is an essential ...
Influence of Social Media English on the Communication Pattern of University Undergraduates in North-Central Zone, Nigeria

This study sought to make an empirical enquiry into the influence of social media English on the communication pattern of undergraduates in North Central Nigeria. A survey design was adopted for the study with a population of 70,255 students across the seven Federal and State universities in North-Central Nigeria. A simple random sampling technique was used to select three faculties from each of the universities after which a purposive sampling technique was used to select one department each from the select faculties. A sample size of 383 students was used for the study which was determined through the use of Australian calculator after which a proportionate stratified random sampling was adopted to get an accurate representation of each select school in the sample size. Findings revealed that the students were involved in the use of social media English and this they even did in formal settings. Further findings revealed that the usage of social media English is preferred among the undergraduates for communication; this shows that they have positive attitudes towards the use of social media English. It was also revealed that the undergraduates are quite addicted to the use of social media English and this seems to have negatively altered their communication pattern. Based on the findings, it was concluded that social media English is prevalent among undergraduates and that if usage is not curtailed, graduates will be produced who do not know how to spell properly or make proper English expressions, even in formal occasions. The researchers recommended that for students to achieve effective communication, they should maintain the habit of clarity in their written communication and should not really depend on social media English with its accompanying spellings as the only mode of communication that is easier and time effective, but should realise its negative influence on their writing skills.
For Thine Is the Stretch, the Power, and the Glory: Bibliometrics as a Branch of Relaxation Kinetics

A stretched exponential function taking the form, f(x) = exp(-x^β), x ∈ [0, ∞), β ∈ (0, 1], characterizes decay, diffusion, and relaxation phenomena known as Kohlrausch-Williams-Watts (KWW) processes. Recent work, particularly on relaxation kinetics in metallic glasses, has described the conditions under the shape parameter β deviates from its usual value. Where β > 1, the corresponding exponential function is compressed rather than stretched.The β-generalized exponential function provides good parametric fits for two measures of influence in legal academia: law review impact factors and Social Science Research Network (SSRN) downloads per author. A stretched exponential function models impact factors from 2007 through 2019. A compressed exponential function describes SSRN downloads per author by law school, except the single outlier atop the rankings. A power law distribution fits the SSRN data, but only for the top 100 schools.The fact that the value of the exponent β straddles the value of 1, which characterizes an ordinary exponential function, is not a trivial artifact of fitting a model to observed bibliometric data. Treating the reciprocal of β as a rough measure of heterogeneity, h = 1/β, suggests that impact factors and SSRN downloads measure different aspects of academic influence in law. Law reviews, especially as the stigma of online publishing recedes, have become more heterogeneous. By contrast, the compressed rather than stretched exponential kinetics of SSRN data implies the presence of avalanche-like processes in the posting and sharing of preprints among legal scholars.
PENERAPAN PEMBERKASAN MENGGUNAKAN APLIKASI BANK INDONESIA RECORDS MANAGEMENT SYSTEM (BI-RMS) PADA DIVISI ARSIP BANK INDONESIA

This observation aims to find out how process Application of Filling Using the Application Bank Indonesia Records Management System (BI-RMS) on Divisi Arsip Bank Indonesia. The background to problem that prompted the author to make observations about filling was considering the use value and function of archives that are so important for organizing life so the need for good archive management by following the dynamics of technological developments that occur in the community. From observation made in Divisi Arsip Bank Indonesia archive management activities including the filling activities, have taken advantage of technology. As a tool for processing, accessing and disseminating and preserving archives. Application of Filling Using the Application Bank Indonesia Records Management System consists of file collection activities, rapid, input and validation, printing of label and list of file contents. And file storage in storage media.
A Study to Convert Big Data from Dedicated Server to Virtual Server

Data is vast in recent years. The amount of data circulated in our daily activities is uncountable. These data need to be secured for future use. The method of storing these data has numerous ways. Through this research paper, it is aimed to convert the already existing data in a dedicated server to a virtual server. The decision of this conversion is required urgently as data dealt are extracted from the vehicle GPS system. The large amount of data that is dealt needs to be secured for future references. Storing these every day is a huge task because every minute is transacted and all these need to be saved. As a whole, an entire set of data that is processed every minute takes a huge amount of saving space. These research papers will extent a suggested solution to convert the existing data from dedicated server to a virtual server.
Ecological aspects of physical and mathematical training of students of modern college under conditions of globalization as pre-requisite for development of cognitive activity

Examined is the role of ecological environmental component of physical and mathematical training, that determines the responsibility of professional activity in the context of development under conditions of high-tech economy. The analysis of the state of physical and mathematical training is given, the role of ecological aspects of physical and mathematical training of students of modern college in development of cognitive activity occurring in the context of globalization is shown, that mechanisms of increasing ecological culture of students of modern college are revealed.
A Novel Approach for Performance Analysis of Dynamic Information Integration

Abstract Data analysis and management was not a problem few years ago as the amount of data generated was not as huge as to cause any complexity. But in the recent years the amount of data being generated has increased exponentially. Thus management and analysis has become a problem since the traditional database management systems were not designed to handle such large amounts of data. The relational database management systems still can handle large data sets, but it increases the complexity thus making it a difficult task. Hadoop comes into picture as a solution to this problem. Hive which is an open source data warehouse built on the Hadoop framework provides a solution to handle large datasets. It provides an SQL tongue called Hive Query Language (HQL) for querying and processing of large sets of data. But the problem with RDBMS is that it takes more time when queries are applied to convert data in rows to columns, i.e., horizontal to vertical. This limitation of Relational Database Management System (RDBMS) is improved by using the combination of UDF and HQL in Hive. With the help of this approach, many calculations that are outside the scope of built in RDBMS operations and functions in Hive like query many columns, combine several column values into one and transformations that are taking more time in RDBMS, can be solved easily. In the proposed work seven different data sets are taken from web for experimental results. Aggregating queries using RDBMS and Hive are run on these data sets with the combination of UDF. The results obtained on these data sets show that combination of UDF with HQL is better than RDBMS when aggregation queries are fired on horizontal data and to join many columns in one. In the proposed work datasets of varying sizes have been analyzed using RDBMS, i.e., MySQL and MS SQL and then using Hive. Different comparison has been done which shows the advantage of using Hive over RDBMS. Keywords: MySQL, MS SQL, Hadoop, Hive, UDF, HQL, HiveServer2, Dlimit, Processing Big Data Cite this Article Vikash Kumar Garg, Ashish Oberoi, Manish Arora. A Novel Approach for Performance Analysis of Dynamic Information Integration. Journal of Advances in Shell Programming . 2019; 6(1): 27–41p.
The end of digital trust is near: how clibrated trust can help us

Trust is paramount for creating social and business relations, adopting technology, cooperating and creating economic value. With an increasingly digital economy, no wonder the importance of digital trust is advocated by so many scholars and businesses alike. However, contrary to purported common wisdom, we propose that actual trust is not created through communicating one’s trustworthiness, and should not be an isolated goal in itself. Rather, real trustworthiness comes from actively practicing fair and transparent policies and conduct, the establishment and maintenance of which rests with both the trustor (e.g., a customer) and the trustee (e.g., a supplier). In this paper, we introduce the concept of calibrated trust, and how it relates to the need for increased customer involvement.
Automatic Construction of Sememe Knowledge Bases via Dictionaries

A sememe is defined as the minimum semantic unit in linguistics.Sememe knowledge bases (SKBs), which comprise words annotated with sememes, enable sememes to be applied to natural language processing.So far a large body of research has showcased the unique advantages and effectiveness of SKBs in various tasks.However, most languages have no SKBs, and manual construction of SKBs is time-consuming and labor-intensive.To tackle this challenge, we propose a simple and fully automatic method of building an SKB via an existing dictionary.We use this method to build an English SKB and a French SKB, and conduct comprehensive evaluations from both intrinsic and extrinsic perspectives.Experimental results demonstrate that the automatically built English SKB is even superior to HowNet, the most widely used SKB that takes decades to build manually.And both the English and French SKBs can bring obvious performance enhancement in multiple downstream tasks.
Blockchain-based secure and trustworthy sensing for IoT-based smart cities

Due to recent technical advances in both wireless communication and smart device capabilities, Internet of Things (IoT) emerges as the novel enabling paradigm for various smart city applications, including smart transportation, smart energy, smart water, and smart home. Because of the critical or even life-dependent nature of many such applications, security and trustworthiness have both become major concerns for the integration and utilization of both sensing and actuating capabilities in IoT. In addition, mobile crowdsensing has recently emerged as an additional means that complements the existing infrastructure-based sensing paradigm, which is also vulnerable to various cyberattacks. In this chapter, we will investigate the security and trust issues in IoT-based smart city applications and explore how to enhance their security and trustworthiness by using the emerging blockchain technology. More specifically, the threat model, attack surface, and the corresponding countermeasures for IoT-based smart cities will be first investigated. Then, we will explore how the blockchain technology could help one to enhance the security and trustworthiness in IoT. Finally, some existing challenges and future research directions will both be discussed.
Speaking Skill’s Language Anxiety Experienced by Freshers of English Language Education Department in Islamic Private University

The aims of this study is to find out the language anxiety levels encountered by the freshmen of English Language Education Department, the reasons of the language anxiety, and how the students cope with the language anxiety. It is a mixed-method study conducted in an Islamic private university in Malang. The population included 128 English Language Education Department freshmen in the academic year 2019/2020. Through convenience sampling, 32 students from six speaking classes were obtained. A survey using Foreign Language Classroom Anxiety (FLCAS) questionnaire and interview were applied as the techniques to gather the data. The findings revealed that 91% freshmen are identified to experience a medium level of anxiety (76-119). Besides, the reasons of the language anxiety included communication apprehension, fear of negative evaluation, and fear of making mistakes in the test. Several ways to cope with the language anxiety comprised practicing before class and keeping the up with the positive mind.