Reviewerly/exHarmony huggingface dataset:
Cost Effective Hybrid Fault Tolerant Scheduling Model for Cloud Computing Environment

Cloud computing provides flexible and cost effective way for end users to access data from multiplatform environment.Despite of support by the features of cloud computing, there are also chances of resource failure.Hence there is a need of a fault tolerant mechanism to achieve undisrupted performance of cloud services.The task reallocation and duplication are the two commonly used fault tolerant mechanisms.But task replication method results in huge storage and computational overhead, when the number of tasks is increasing gradually.If the number of faults is high, it incurs more storage overhead and time complexity based on task criticality.In order to solve these issues, we propose to develop a Cost Effective Hybrid Fault Tolerant Scheduling (CEHFTS) Model for cloud computing.In this model, the Failure Occurrence Probability (FoP) of each VM is estimated by finding the previous failures and successful executions.Then an adaptive fault recovery timer is maintained during a fault, which is adjusted based on the type of faults.Experimental results have shown that CEHFTS model achieves 43% reduced storage cost and 13% reduced response delay for critical tasks, when compared to existing technique.
Time Management Skills of Middle Managers of Russian Companies: Evaluation Experience

The speed of change in the external environment forces companies to be more flexible and mobile. Among other things, this result is achieved through changes in organizational structures, delegation of authority, increasing the role of departments and middle managers. A modern manager is increasingly becoming a leader, not only an administrator. Limited time resources and new challenges that middle managers face make the issue of time management relevant. This paper examines the time management skills of middle managers in Russian companies. The study was carried out according to the author's methodology in various regions of the Russian Federation in the second half of 2020 - early 2021. The obtained results characterize the time management skills of middle managers in Russian companies ambiguously. On the one hand, the majority of middle managers of Russian companies have basic time management skills, many of them are actively involved in the goal setting and planning of the division's activities and have a horizon of planning their own activities from several weeks to several months. Most managers are relatively good at achieving their goals – 5 out of 6 middle managers meet their goals by 70% or more. Many managers have developed their managerial competencies not only in practice but also in the process of obtaining basic and additional education in the field of management. Unclear tasks assigned to subordinates, focus of inexperienced managers on performing the functions of specialists, and insufficiently developed competencies in the field of delegation of authority lead to additional time, which could be spent on solving more important tasks. We also note a fairly high share of time spent by managers on the preparation of reports and other documents. More than half of the time is spent on urgent and important work. This means that managers work in conditions of continuous stress and that the lack of time inevitably affects the quality of the work performed. The results confirm the importance of developing managers' time management skills, especially for those who do not have sufficient work experience and/or education in the field of management.
HAND GESTURE DETECTION USING SEGMENTATION

Hand gesture detection is a project which recognizes the gesture of hands and detect accordingly.Hand Gesture recognition is an important technique for creating user-friendly interfaces.Hand gesture is recognized by robots, for example, can take human commands, and those who are deaf or who cannot speak, can recognize the sign language for communication.Hand gesture recognition in video games could help by allowing players to use gestures to interact with the game rather than a controller.Moreover, to account for the infinite number of possible hand positions in three dimensions, such an algorithm must be more robust.It must also be capable of working with video rather than static images.
A critical success factors for software project manager in GVTs within covid-19 pandemic

The covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study is trying to identify the critical success factors (CSFs) for software project manager. A literature review was conducted to identify the CSFs. Next, an online survry was conducted to rank those factors according to their propriety. An online survey was distributed among the software developers, project managers, and academicans. The statistical package for social science (SPSS) version 22 was used to analyze the data collection. Twelfth CSFs were identified in this study. Also, the findings indicated that leadership skills factor is the highest factor level ranking in this study.
Big Data, AI and Border Enforcement of Intellectual Property Rights

Customs surveillance of intellectual property (IP) is 'an efficient way to quickly and effectively provide legal protection to the right-holder', 1 since it makes it possible to 'nip the infringements in the bud'.
Development of the Information Security Management System Standard for Public Sector Organisations in Estonia

Standardisation gives us a common understanding or processes to do something in a commonly accepted way. In information security management, it means to achieve the appropriate security level in the context of known and unknown risks. Each government’s goal should be to provide digital services to its citizens with the acceptable level of confidentiality, integrity and availability. This study elicits the EU countries’ requirements for information security management system (ISMS) standards and provides the standards’ comparison requirements. The Estonian case is an example to illustrate the method when choosing or developing the appropriate ISMS standard to public sector organisations.
A Comparative Analysis of Filter-Based Feature Selection Methods for Software Fault Prediction

The rapid growth of data has become a huge challenge for software systems. The quality of fault predictionmodel depends on the quality of software dataset. High-dimensional data is the major problem that affects the performance of the fault prediction models. In order to deal with dimensionality problem, feature selection is proposed by various researchers. Feature selection method provides an effective solution by eliminating irrelevant and redundant features, reducing computation time and improving the accuracy of the machine learning model. In this study, we focus on research and synthesis of the Filter-based feature selection with several search methods and algorithms. In addition, five filter-based feature selection methods are analyzed using five different classifiers over datasets obtained from National Aeronautics and Space Administration (NASA) repository. The experimental results show that Chi-Square and Information Gain methods had the best influence on the results of predictive models over other filter ranking methods.
NEW TRENDS IN CYBERCRIME IN THE MALDIVES - MOVING BEYOND LEGAL MEASURES IN THE NEW NORM

INTRODUCTION The health emergency crisis due the COVID-19 pandemic has created challenges globally. The same applies to the Maldives, as lockdown and social distancing measures was enforced, the use of virtual communication by public authorities, businesses and individuals likewise increased. The new normal of working from home, video conferencing and meetings, online learning and shopping have created a large group of vulnerable users, providing more opportunities for cybercriminals to exploit. In a time where resources are diverted to fight against the COVID-19 pandemic, the law enforcement, investigative and judicial procedures may be delayed or disrupted due to compulsory prevention measures. The changing face of cybercrime needs to be addressed through non-legal measures to reduce the detrimental effect. OBJECTIVES New cybercrimes have emerged during the pandemic, which has affected the vulnerable users in a difficult and unprecedented time. The objective of the study is to identify the nature of cybercrime, including the emerging crimes and to examine how these issues could be addressed through legal and non-legal measures. METHODOLOGY The methodology adopted is through the study of secondary data collected through research of recent articles, legal statutes and newspaper articles from March 2020 until present. The data collected was applied through study, observation and analysis. SIGNIFICANCE This study will identify the emerging crimes during the pandemic, and bring together different approaches, including non-law measures to highlight the best method to address this issue. FINDINGS/RESULTS Forms of cybercrimes identified as prevalent in the country, namely (1) misinformation; (2) phishing and (3) privacy issues. Misinformation and disinformation regarding the virus, cures and conspiracies plays a key role in undermining the public trust and the effectiveness of the public safety measures. The ability to take action through legal measures were limited due inabilty to investigate, non-existence of applicable provisions, underreporting and late reporting amongst others. Non-legal measures such as awareness campaigns and cyber-education were utilised to empower vulnerable groups, especially children and seniors against emerging new forms of cybercrimes. CONCLUSIONS With the changing face of cybercrime and the prolonged uncertain future due to COVID-19, there should less reliance on the law and more proactive measures enacted at all levels to reduce the harmful effects.
Analisis Pandangan Siswa Kelas VI SD Negeri Purbo 03 terhadap Pembelajaran Daring Via Zoom Meeting

Internet-based learning that is carried out online has become very intense by teachers in Indonesia since the covid-19 pandemic, one of which is SD N Purbo 03. SD N Purbo 03 teachers as users of distance learning services have a very significant role in transferring knowledge, facilitate, and assist students in learning. So, before seeing further how the learning process through applications, it is very necessary to know in advance how the students view the current conditions and in particular the use of Zoom Meeting media as a media for distance learning. This study uses a qualitative method by presenting sources as research subjects. The results showed that online learning in class VI SD N Purbo 03 with Zoom Meeting was divided into three stages, namely the learning planning stage, learning implementation and evaluation. Students' views on online learning through Zoom Meetings based on student experiences show that Zoom Meeting gives a pleasant impression of learning because in the implementation of learning Zoom Meeting gives the impression of learning like in a school where students and teachers are connected to each other even though virtually, the successful implementation of Zoom Meeting as a learning medium can not be separated from the involvement of parents in monitoring the online learning process.
Incorporating Presuppositions of Competency Questions into Test-Driven Development of Ontologies (S)

Ontology authoring is a complicated and error-prone process since the knowledge being modelled is expressed using logic-based formalisms, in which logical consequences of the knowledge have to be foreseen.Many approaches intended to make this task easier, use competency questions (CQs), being questions expressed in natural language to trace both the correctness and completeness of the ontology at a given time.However, CQs hold so-called presuppositions that have to be satisfied by the ontology to obtain meaningful answers from CQs.Moreover, CQs have to be expressed using a formal language, like ontology query language (SPARQL-OWL), to query the ontology.In this paper, we propose an extension of test-driven ontology development approach by formalization of presupposition satisfaction tests in terms of SPARQL-OWL queries, as well as providing translations of CQs into SPARQL-OWL queries if presupposition tests are passed.We provide a detailed description of the proposed framework and how to incorporate such tests in the workflow of test-driven development of ontologies.It is the first framework available for formalization of SPARQL-OWL queries out of CQs with their presupposition tests.
An Empirical Study of Web Page Structural Properties

The paper reports results on an empirical study of the structural properties of HTML markup in websites. A first large-scale survey is made on 708 contemporary (2019–2020) websites, in order to measure various features related to their size and structure: DOM tree size, maximum degree, depth, diversity of element types and CSS classes, among others. The second part of the study leverages archived pages from the Internet Archive, in order to retrace the evolution of these features over a span of 25 years. The goal of this research is to serve as a reference point for studies that include an empirical evaluation on samples of web pages.
Electronic Voting Technology Inspired Interactive Teaching and Learning Pedagogy and Curriculum Development for Cybersecurity Education

Cybersecurity is becoming increasingly important to individuals and society alike. However, due to its theoretical and practical complexity, keeping students interested in the foundations of cybersecurity is a challenge. One way to excite such interest is to tie it to current events, for example elections. Elections are important to both individuals and society, and typically dominate much of the news before and during the election. We are developing a curriculum based on elections and, in particular, an electronic voting protocol. Basing the curriculum on an electronic voting framework allows one to teach critical cybersecurity concepts such as authentication, privacy, secrecy, access control, encryption, and the role of non-technical factors such as policies and laws in cybersecurity, which must include societal and human factors. Student-centered interactions and projects allow them to apply the concepts, thereby reinforcing their learning.
E-Voting application development based on android: A case study election chairman of HIMANIFO Universitas Muhammadiyah Magelang

Election Chairman of HIMANIFO has obstacles namely the lack of students participation in the voting because they can not attend in the election, while the voting is done using paper media. Due the problems the author proposes to design and build a system of Android-based E-Voting for the election of Chairman and Deputy Chairman of HIMANIFO. The application is built using the Unified Approach development method. Applications that produced a website and Android, the web will help administrators to manage students and chairman candidate data, and receive incoming voice. Android app helps students to conduct voting. The purpose of this system is to make it easier for students to carry out the voting process and for students to participate in voting. The results of this study provide convenience in the election of students. Sudents can vote anywhere and can save paper.
A New Feature Filtering Approach by Integrating IG and T-Test Evaluation Metrics for Text Classification

High dimensionality is one of the main issues associated with text classification, such as selecting the most discrepant features subset for classifier's effective utilization is a difficult task.This significant preprocessing stage of selecting the relevant features is often called feature selection or feature filtering.Eliminating the non-relevant and noise features from the original feature set will drastically reduce the size of the feature set and the time complexity of the classification models and also improve or maintain their performance.Most of the existing filtering method produced a subset with relatively high number of features without much significant impact on running time, or produced subset with lesser number of features but results in performance degradation.In this paper, we proposed a new bi-strategy filtering approach that integrates Information Gain with t-test that selects a subset of informative features by considering both the score and ranking of respective features.Our approach considers the results' disparity produced by the benchmark metrics used in order to maximized and lessen their advantage and disadvantage.The approach set a new threshold parameter by computing V-score of the features with minimum scores present in both the two subsets and further refined the selected features.Hence, it reduces the size of the features subset without losing much informative features.Experiment results conducted on three different text datasets have shown that the proposed method is able to select features that are highly discrepant and at the same time achieves a significant improvement in terms of classification accuracy and F-score at the cost of a minimum running time.
PECULIARITIES OF APPLICATION OF INNOVATIVE LEARNING TECHNOLOGIES DURING STUDYING THE DISCIPLINE “LIFE SAFETY AND OCCUPATIONAL HEALTH AND SAFETY”

The possibility of applying innovative technologies, in particular the case method, during the study of “Life Safety and Health” in the educational process at the Lviv University of Trade and Economics is considered. The author's experience of using innovative technologies of problem analysis is presented. The method of case technologies has been proposed and implemented in the educational process and organization of scientific work of students learning the discipline “Life Safety and Health”, which promotes the development of creative potential and is interested for participants of the learning process via modeling real situations. Students forget the experience of public speaking, publish the results of their own research, receive performance appraisal. It is shown that the case method as an effective means of organizing educational process, allows to learn combined theoretical knowledge with the realization of life, activates cognitive interest in the studied discipline, promotes the development of research, communication and contributes to formation of creative decision-making skills. The obtained results confirm the need for purposeful scientific and methodological implementation of the case method in the educational process, which involves the creation of appropriate conditions for innovative search and innovative transformations in consciousness.
The simplification of computationals in error correction coding

The object of research is the processes of error correction transformation of information in automated systems. The research is aimed at reducing the complexity of decoding cyclic codes by combining modern mathematical models and practical tools. The main prerequisite for the complication of computations in deterministic linear error-correcting codes is the use of the algebraic representation as the main mathematical apparatus for these types of codes. Despite the universalism of the algebraic approach, its main drawback is the impossibility of taking into account the characteristic features of all subclasses of linear codes. In particular, the cyclic property is not taken into account at all for cyclic codes. Taking this property into account, one can go to a fundamentally different mathematical representation of cyclic codes – the theory of linear automata in Galois fields (linear finite-state machine). For the automaton representation of cyclic codes, it is proved that the problem of syndromic decoding of these codes in the general case is an NP-complete problem. However, if to use the proposed hierarchical approach to problems of complexity, then on its basis it is possible to carry out a more accurate analysis of the growth of computational complexity. Correction of single errors during one time interval (one iteration) of decoding has a linear decoding complexity on the length of the codeword, and error correction during m iterations of permutations of codeword bits has a polynomial complexity. According to three subclasses of cyclic codes, depending on the complexity of their decoding: easy decoding (linear complexity), iteratively decoded (polynomial complexity), complicate decoding (exponential complexity). Practical ways to reduce the complexity of computations are considered: alternate use of probabilistic and deterministic linear codes, simplification of software and hardware implementation by increasing the decoding time, use of interleaving. A method of interleaving is proposed, which makes it possible to simultaneously generate the burst errors and replace them with single errors. The mathematical apparatus of linear automata allows solving together the indicated problems of error correction coding.
Multilevel Privacy Controlling Scheme to Protect Behavior Pattern in Smart IoT Environment

Traditional approaches generally focus on the privacy of user’s identity in a smart IoT environment. Privacy of user’s behavior pattern is an important research issue to address smart technology towards improving user’s life. User’s behavior pattern consists of daily living activities in smart IoT environment. Sensor nodes directly interact with activities of user and forward sensing data to service provider server (SPS). While availing the services provided by a server, users may lose privacy since the untrusted devices have information about user’s behavior pattern and it may share data with adversary. In order to resolve this problem, we propose a multilevel privacy controlling scheme (MPCS) which is different from traditional approaches. MPCS is divided into two parts: (i) behavior pattern privacy degree (BehaviorPrivacyDeg), which works as follows: firstly, frequent pattern mining-based time-duration algorithm (FPMTA) finds the normal pattern of activity by adopting unsupervised learning. Secondly, patterns compact algorithm (PCA) is proposed to store and compact the mined pattern in each sensor device. Then, abnormal activity detection time-duration algorithm (AADTA) is used by current triggered sensors, in order to compare the current activity with normal activity by computing similarity among them; (ii) multilevel privacy design model: we have divided privacy of users into four levels in smart IoT environment, and by using these levels, the server can configure privacy level for users according to their concern. Multilevel privacy design model consists of privacy-level configuration protocol (PLCP) and activity design model. PLCP provides fine privacy controls to users while enabling users to set privacy level. In PLCP, we introduce level concern privacy algorithm (LCPA) and location privacy algorithm (LPA), so that adversary could not damage the data of user’s behavior pattern. Experiments are performed to evaluate the accuracy and feasibility of MPCS in both simulation and real-case studies. Results show that our proposed scheme can significantly protect the user’s behavior pattern by detecting abnormality in real time.