Reviewerly/exHarmony huggingface dataset:
Use of electronic resources among teachers and scholars in Banaras Hindu University, Varanasi, Uttar Pradesh (Bharat): A survey

The advancement of the information technology and web technology have brought changes to existing information storage and retrieval system such as Digital library, online database, digital repository, virtual library, etc. Libraries have witnessed tremendous changes in recent years in terms of their collection and services. Information explosion and user's demand of the users required the development of a more comprehensive library collection. Publishers have now started publishing on-line version/electronic versions of their printed journals. Owing to the cost of journals, many colleges and universities are unable to procure these journals. Ministry of HRD and UGC has started procuring the e-resources from the 25 world-class publishers under consortia mode at a much reduced price for all university libraries. BHU library is one of the beneficiaries of this UGC-INFONET Digital Library Consortium. The present study is the part of Ph.D. research work of one of the authors. To ascertain the usage of the e-resources available to the BHU library by the teachers and scholars, this survey was conducted. The present investigation discusses the use of electronic resources (e-journals, e-books, online/ offline databases, web resources) which are made available by the INFLIBNET Centre in e-resource consortium like UGC-INFONET Digital Library Consortium by the teachers and scholars of BHU. The present study was conducted as a part of doctoral research work from January 2015 to July 2015.
Design of Big Data Platform for Automatic Production Line of Handicraft Structure

Abstract The automation production line of handicraft structural parts are taken as the research object in this paper, and big data platform is constructed through data modeling, data collection, data analysis and data visualization technologies, including data perception layer, communication layer, storage layer and analysis and display layer. The data acquisition layer obtains the multi-source heterogeneous information source at the bottom of the handicraft processing workshop, transmits it to the big data platform based on the OPC UA protocol for the data analysis of equipment status, production efficiency, product quality and other data, and displays the results through the visualization technology in real time to realize the real-time dynamic control of the handicraft processing process.
An Ecological Equilibrium Dynamics Optimization Approach

In order to solve the problem of complex function optimization, the ecological balance dynamics-based optimization (EBDO) algorithm is proposed based on the Lotka–Volterra ecological balance dynamics. The algorithm assumes that there are three populations of nurturers, consumers, and decomposers in an ecosystem. The self-plowing is mainly the plant; the consumer is mainly the animal who feeds on the nourish; the decomposer mainly breaks down the dead body of the consumer, and the nutrient is supplied to the self-raised person. According to the relationship among the populations in the above ecosystem, the consumer-autotrophic operator, the self-coter decomposer operator, the decomposer-consumer operator and the growth operator are constructed. The growth change of the population of the self-employed, the consumer and the decomposer is equivalent to the search space trying to move from one location to another. The algorithm has the characteristics of strong search ability and global convergence, it provides a solution for solving complex optimization problems.
Evaluation of apps used in an educational context

Lately we have seen a continuous increase in the use of technologies in teaching and learning processes and more specifically in the use of mobile technologies inside and outside the classroom. Rather than indifference or refusal, this tendency is a harnessing of latent potential and an effort to adapt school to the importance of technology in society. New ways of teaching and learning using the smartphone allow the design of activities that apply apps as a didactic tool for use in the classroom. The aim of this research is to find a set of indicators that permit teachers to evaluate apps from a repository they have used, are using or intend to use in educational context and want to share with the community to facilitate their proper adoption. The problem of the possible impacts of the use of the smartphone on memory, attention or other cognitive dimensions is out of the scope of this work: we focused essentially on its potential as a means to explicit knowledge and increase motivation and collaboration. So, we propose an analysis organized into three categories and 23 attributes.
Migration and Integration Strategy of Virtual Machines in Cloud Data Center Based on HPGA

[Purpose] Server virtualization technology is the basic form for the cloud data center to serve customers. While the cloud data center reduces the SLA violations in the early stage, the increase in the utilization of resources such as virtual machine servers and network equipment and decrease in energy consumption have become an important issue for reduction of operating costs. Therefore, on the background of the cloud data center network based on SDN technology, this paper studies a cloud data center resource utilization and energy consumption optimization strategy through virtual machine migration and integration. [Method] The technology based on SDN is firstly introduced, the approximate optimal solution FFD algorithm for the multidimensional vector bin packing problem is then presented, the Partheno-Genetic Algorithm (PGA) is then recommended, finally a Hybrid Partheno genetic Algorithm (HPGA) based on the both is established and a mathematic model is created. [Results] By combining the advantages of FFD and PGA, this paper improves the utilization of the resources of the entire cloud data center, reduces energy consumption, and prevents the occurrence of computing “hot spots”. [Conclusion] Experiments in CloudSim prove the effectiveness of the algorithm. Compared with FFD and PGA algorithms, it is able to enhance the efficiency of the Data Center effectively, and obtain the optimal solution more quickly, thereby balancing the physical resources of the server.
Trusting in patterns

Human beings are natural “pattern sniffers” (Cuoco, Goldenberg, & Mark, 1996), and a sensitivity to patterns is nowhere more critical than in the study of mathematics. Indeed, mathematics is sometimes defined as the study of patterns (e.g., Devlin, 1994). But, this attention to patterns has to be more than mindless ‘pattern spotting’ that fails to engage with the deep structure of the mathematics.
The System of Elective Courses in the Anglo-Saxon Educational Tradition

The article deals with one of the key characteristics of the American education, the elective system of courses that was a reply for the community demands. Also, it became the outcome of relationship of educational institutions with various social groups whose support was crucial for the survival and well-being of American colleges and universities. For the American educational system, the abovementioned characteristics was the result of its historic process of the national educational system development. The author argues that this feature, sometimes aggressively imposed in Russia, might become destructive and bring to the deterioration and even destroy the unique educational system built in absolutely opposite principles than the educational system of the USA. The article analyzes the given characteristic of the US educational system and shows the critique of the American educators and experts, which gives an opportunity to ponder in depth and make a responsible decision in terms of copying the feature into the Russian educational system.
Detecting Tax Evaders Using TrustRank and Spectral Clustering

Indirect taxation is a significant source of livelihood for any nation. Tax evasion inhibits the economic growth of a nation. It creates a substantial loss of much needed public revenue. We design a method to single out taxpayers who evade indirect tax by dodging their tax returns. Towards this, we derive six correlation parameters (features), three ratio parameters from tax return statements submitted by taxpayers, and another parameter based on the business interactions among taxpayers using the TrustRank algorithm. Then we perform spectral clustering on taxpayers using these ten parameters (features). We identify taxpayers located at the boundary of each cluster by using kernel density estimation, which are further investigated to single out tax evaders. We applied our method on the iron and steel taxpayer’s data set provided by the Commercial Taxes Department, Government of Telangana, India.
Case Study of Job Crafting Program for Pre-Service Teacher

이 연구는 예비교사들이 참여하는 교육실습이 보다 의미있는 교육기회가 될 수 있도록 교육실습 전에 ‘예비교사를 위한 잡크래프팅’ 프로그램을 실행하여 그 효과를 확인하고 프로그램의 강점과 개선사항을 도출하는 데 목적이 있다. 이를 위해 ‘교사용 잡크래프팅 프로그램’을 예비교사들의 상황에 맞게 수정하여 예비교사들을 대상으로 교육실습 참여 전에 실행하였다. 예비교사들의 잡크래프팅 수준의 추이를 파악하기 위해 3차(잡크래프팅 교육 전, 후, 교육실습 후)에 걸쳐 예비교사들을 대상으로 잡크래프팅 검사를 수행하였다. 잡크래프팅 검사 결과, 예비교사들의 잡크래프팅 수준은 프로그램 실행 전<프로그램 실행 후<교육실습 후로 점차 높아졌다. 프로그램에 참여한 예비교사들은 잡크래프팅 프로그램이 자기이해, 교직이해, 교직직무수행 측면에서 도움을 주어 교직에 대한 의미를 확인하고 교육실습이 보다 주도적으로 이루어지는 데 도움이 되었다고 평가하였다. 이와 함께 잡크래프팅 프로그램이 효과적으로 운영될 수 있도록 구체적인 가이드라인 제공, 사전준비활동 제공, 성찰활동 추가, 상호작용 및 피드백 시간 확대가 필요하다고 하였다. 예비교사를 위한 잡크래프팅 프로그램은 예비교사들이 교사로서의 소명의식을 구체화하고 자신과 직무에 대한 이해를 높여 교육실습 및 이후 교사로서의 직무수행에 긍정적인 도움을 줄 것으로 기대할 수 있다.The purpose of this study is to execute a job crafting program for pre-service teachers and to identify its effects while drawing out the strengths and improvements of the program so that the educational practice can be a more meaningful educational opportunity. To this end, the Teacher Job Crafting Program was modified to suit the needs of pre-service teachers and they participated in this program before the standard teacher training. In order to analyze the effectiveness of the program, job crafting tests were conducted for preliminary teachers in three stages (before and after the job crafting program and after teaching practice). The results indicate that the level of job crafting of pre-service teachers increased slightly after the program and significantly after teaching practice. The pre-service teachers evaluated that the job crafting program helped them to understand themselves, their teaching, and perform their teaching duties, thereby helping them to identify the meaning of the teaching profession and to make their teaching practice more proactive. In addition, it was suggested to provide specific guidelines, preliminary preparation activities, add reflection activities, and increase interaction and feedback time so that job crafting programs can be more effectively operated. This job crafting program for pre-service teachers is expected to help pre-service teachers with their calling by increasing their abilities as teachers and in implementing future job crafting.
Enhancing Image Caption Quality with Pre-post Image Injections

This paper focuses on the effects of injecting images in image captioning architectures that use deep learning. We explore these effects using the merge architecture for image captioning. The neural network design involves using encoders that encode both images [using a convolutional neural network (CNN)] and the captions [using a long short term memory (LSTM)/gated recurrent unit (GRU)] associated with the image in two separate branches. Traditionally, in the merge architecture, the context of the image is introduced, only after the LSTM encodes the caption. This is otherwise known as the “post-inject” architecture. In this paper, we propose that injecting the image encoding from the CNN before as well as after encoding the caption shows improved quality of captions, without an increase in the number of weights to be trained. Benchmark tests in support of this conclusion were conducted on the Flickr8k dataset. This would be a “pre + post inject” architecture, which in turn produces image captions of better quality, without the overhead of having to train extra weights to attain this enhanced quality.
S-boxes Construction Based on Quantum Chaos and PWLCM Chaotic Mapping

For a security system built on symmetric-key cryptography algorithms, the substitution box (S-box) plays a crucial role to resist cryptanalysis (decoding). In this paper, we incorporate quantum chaos and PWLCM chaotic mapping into a new method of S-box design. Over the obtained 500 key-dependent S-boxes, we test the S-box cryptographical properties on bijection, nonlinearity, SAC, BIC, differential approximation probability, and sensitivity to the key, respectively. The results show that the cryptographic characteristics of proposed S-Box has met our design objectives and can be applied to data encryption, user authentication and system access control.
SOCIAL IDENTITY OF CADETS – FUTURE MILITARIES

The article presents the results of research on the social identity of cadets – future militaries. In this case, social identity is defined as the direction of individual knowledge on belonging to a particular social group that has an emotional and appraised value for an individual and his/her membership in the group. Self-concepts and values are the leading structural components of social identity. The results of the empirical study indicate that a significant group for the cadets – future militaries is not their membership group, with which they have to spend almost all their time, but an informal group where they feel free, relaxed, and supportive. The study of the Self-concept components shows a predominance of reflective Self at the most respondents. This confirms the results of the choice of informal groups as significant ones, where cadets have creative, friendly relationships that give them a sense of growth and development, or where they simply meet their personal needs. It is empirically determined that the students are more inclined to domination than subordination, which confirms the conclusion that their study group is not the significant one. Cadets – future militaries highly value the health, love, life wisdom and existence of good and loyal friends, as well as politeness, cleanliness, independence, responsibility, and firmness of will. The sample value the least the beauty of nature and art, creativity, the happiness of others, indifference to their and strangers’ negative qualities, as well as sensitivity.
Quantized feedback particle filter for unmanned aerial vehicles tracking with quantized measurements

Many existing state estimation approaches assume that the measurement noise of sensors is Gaussian. However, in unmanned aerial vehicles tracking applications with distributed passive radar array, the measurements suffer from quantization noise due to limited communication bandwidth. In this paper, a novel state estimation algorithm referred to as the quantized feedback particle filter is proposed to solve unmanned aerial vehicles tracking with quantized measurements, which is an improvement of the feedback particle filter (FPF) for the case of quantization noise. First, a bearing-only quantized measurement model is presented based on the midriser quantizer. The relationship between quantized measurements and original measurements is analyzed. By assuming that the quantization satisfies [Formula: see text], Sheppard’s correction is used for calculating the variances of the measurement noise. Then, a set of controlled particles is used to approximate the posterior distribution. To cope with the quantization noise of passive radars, a new formula of the gain matrix is derived by modifying the measurement noise covariance. Finally, a typical two-passive radar unmanned aerial vehicles tracking scenario is performed by QFPF and compared with the three other algorithms. Simulation results verify the superiority of the proposed algorithm.
An optimization-based deep belief network for the detection of phishing e-mails

Purpose Phishing is a serious cybersecurity problem, which is widely available through multimedia, such as e-mail and Short Messaging Service (SMS) to collect the personal information of the individual. However, the rapid growth of the unsolicited and unwanted information needs to be addressed, raising the necessity of the technology to develop any effective anti-phishing methods. Design/methodology/approach The primary intention of this research is to design and develop an approach for preventing phishing by proposing an optimization algorithm. The proposed approach involves four steps, namely preprocessing, feature extraction, feature selection and classification, for dealing with phishing e-mails. Initially, the input data set is subjected to the preprocessing, which removes stop words and stemming in the data and the preprocessed output is given to the feature extraction process. By extracting keyword frequency from the preprocessed, the important words are selected as the features. Then, the feature selection process is carried out using the Bhattacharya distance such that only the significant features that can aid the classification are selected. Using the selected features, the classification is done using the deep belief network (DBN) that is trained using the proposed fractional-earthworm optimization algorithm (EWA). The proposed fractional-EWA is designed by the integration of EWA and fractional calculus to determine the weights in the DBN optimally. Findings The accuracy of the methods, naive Bayes (NB), DBN, neural network (NN), EWA-DBN and fractional EWA-DBN is 0.5333, 0.5455, 0.5556, 0.5714 and 0.8571, respectively. The sensitivity of the methods, NB, DBN, NN, EWA-DBN and fractional EWA-DBN is 0.4558, 0.5631, 0.7035, 0.7045 and 0.8182, respectively. Likewise, the specificity of the methods, NB, DBN, NN, EWA-DBN and fractional EWA-DBN is 0.5052, 0.5631, 0.7028, 0.7040 and 0.8800, respectively. It is clear from the comparative table that the proposed method acquired the maximal accuracy, sensitivity and specificity compared with the existing methods. Originality/value The e-mail phishing detection is performed in this paper using the optimization-based deep learning networks. The e-mails include a number of unwanted messages that are to be detected in order to avoid the storage issues. The importance of the method is that the inclusion of the historical data in the detection process enhances the accuracy of detection.
An Authenticated E-Voting System Using Biometrics and Blockchain

In every republic, the security of an election plays an irreversible impact on the outcome of the election results which determine the growth of the nation. The diversity of the electronic voting systems poses an enormous challenge in the credibility of the voting procedure. In addition, it has to minimize the cost of having a national election, while fulfilling and increasing the security conditions. The recently popularized blockchain technology assists in escalating the security issues, which may disrupt many traditional systems including the voting system. The immutability property and the decentralized architecture of the blockchain technology are exploited to make it an appropriate base for an e-voting application. Blockchaining voting scheme allows transparency, immutability and control of the voting ballot to the end user. This paper addresses the successful deployment of a usable and efficient e-voting system built on Ethereum Smart Contracts which provides a high level of transparency. Biometric Authentication is implemented to ensure that a voter is privileged to cast only his vote and eliminates masquerading.
Red Queen in the Repository

&#x0D; One of the grand curation challenges is to secure metadata quality in the ever-changing environment of metadata standards and file formats. As the Red Queen tells Alice in Through the Looking-Glass: â€œNow, here, you see, it takes all the running you can do, to keep in the same place.â€ That is, there is some â€œrunningâ€ needed to keep metadata records in a research data repository fit for long-term use and put in place. One of the main tools of adaptation and keeping pace with the evolution of new standards, formats â€“ and versions of standards in this ever-changing environment are validation schemas. Validation schemas are mainly seen as methods of checking data quality and fitness for use, but are also important for long-term preservation. We might like to think that our present (meta)data standards and formats are made for eternity, but in reality we know that standards evolve, formats change (some even become obsolete with time), and so do our needs for storage, searching and future dissemination for re-use. Eventually, we come to a point where transformation of our archival records and migration to other formats will be necessary. This could also mean that even if the AIPs, the Archival Information Packages stay the same in storage, the DIPs, the Dissemination Information Packages that we want to extract from the archive are subject to change of format. Further, in order for archival information packages to be self-sustainable, as required in the OAIS model, it is important to take interdependencies between individual files in the information packages into account. This should be done already by the time of ingest and validation of the SIPs, the Submission Information Packages, and along the line at different points of necessary transformation/migration (from SIP to AIP, from AIP to DIP etc.), in order to counter obsolescence.&#x0D; This paper investigates possible validation errors and missing elements in metadata records from three general purpose, multidisciplinary research data repositories â€“ Figshare, Harvardâ€™s Dataverse and Zenodo, and explores the potential effects of these errors on future transformation to AIPs and migration to other formats within a digital archive.&#x0D; &#x0D;
Learning Arabic Media Related Vocabulary through Twitter at the University of Alabama

This research paper aims to investigate the effect of utilizing Twitter in a foreign language classroom and how it would affect students’ attitudes towards learning Arabic media related vocabulary. The researchers used qualitative and quantitative methods as a methodological approach to the study. The subjects of the study are American undergraduate students studying Arabic for their third semester, 11 participated in the study. The participants were asked to open Twitter accounts in order to practice reading up-to-date tweets from global news agencies. Participants took pre and post-tests, then were asked to take a questionnaire; a structured interview was also carried out along with reflections to have a better understanding of the students’ attitude towards the use of Twitter in the classroom. The data were gathered throughout the semester and analyzed qualitatively and the participants’ responses were coded for certain themes and then analyzed. The findings indicated that the students had a positive attitude towards the use of Twitter in learning vocabulary for specific topics -in this study media/political-related vocabulary- in the foreign language classroom. In addition, the quantitative data used as confirmation and showed vocabulary gains after the Twitter treatment. The study’s findings can be applied to any foreign language and can have important implications and recommendations for language teachers and educators in the field. The findings will add valuable recommendations on how to integrate social media platforms in a foreign language classroom.