Reviewerly/exHarmony huggingface dataset:
Skill Suits of LIS Professionals: Towards Modern Paradigm

Present era of information society having a tagline “Information is commodity” leads to switching of academic libraries to information centers. Presently Information communication Technology has dramatically changed academics, research and development. Earlier academic libraries play role in procure the formal library resources i.e. resources in conventional or printed format and cater traditional library services. With influence of ICT and transformation in education system information is becoming part and parcel of academic process as well as research and development. With Advent of ICT the role of academic libraries is shifting from Library to Information Retrieval centre along with structure i.e. traditional to digital, hybrid, virtual or paperless library. Ultimately to overcome these challenges it’s essential for librarians to adopt new “Skill Suit” which assist themselves in smooth working. Keyword: LIS Profession, Skill Suit, Technical Skills, Generic Skills, Five Laws of Librarianship Cite this Article Satvashila T. Salgar. Skill Suits of LIS Professionals: Towards Modern Paradigm. Journal of Advancements in Library Sciences. 2019; 6(Special Issue 1): 160s–164s.
Falling Shadow Theory Applied to UP-Algebras

Based on the theory of fuzzy sets and falling shadows, the notion of a falling UP-subalgebra and a falling UP-ideal of a UP-algebra is introduced, and several properties are investigated.Relations between falling UP-subalgebras and falling UP-ideals are given. Relations between fuzzy UP-subalgebras (resp., fuzzy UP-ideals) and  falling UP-subalgebras (resp., falling UP-ideals) are established.
The correlation between plagiarism perception and users trust about the accuracy of turnitin software at The University of Indonesia

Plagiarism is an act that violates the law, have been cases that have occurred in Indonesia and the world, and most have occurred in the academic scope. The cause of plagiarism is influenced by many factors, one of them is the lack of provisions or standards that clearly someone can be said to be the perpetrator of plagiarism. However, regardless ofthe actions that occur, technological advancements encourage software that can prevent the emergence of plagiarism, namely the Turnitin software. In this case one of the stateuniversities, The University of Indonesia has used it in order to prevent and overcome plagiarism. But the absence of provisions or standards regarding plagiarism raises different perceptions in each person related to the problem of plagiarism, and this raises different beliefs as well when people use the Turnitin software. Therefore, this study discusses whether the perception of plagiarism in each person relates to the user's trust in the accuracy ofTurnitin software, especially among the academic community of the University of Indonesia. The approach that used in this study is quantitative explanative by using the University of Indonesia academic community as many as 85 people as respondents. The results of the study indicate the correlation of perceptions of plagiarism (X) with the user's trust in the accuracy of Turnitin software (Y), and have a positive correlation. Based on the results of the coefficient t count of 3.590 while the t table is 1.663 (3,590>1,663) with a significance level of 0.05, thenis rejected so that there is a correlation between variable X and Y. The correlation is classified as a low correlation, with a correlation coefficient of 0.389.
Sentiment Expression on SNS According to Gender and User Activity Level

Objective: The primary aim of this study was to examine the sentiment expression according to gender and user activity level with a particular focus on the social networking site of Twitter.BR Background: With the vast and ever-growing popularity of social networking services, sentiment analysis on SNS has become widely used in data science for analysis of user`s feedback and opinion mining.BR Method: The messages posted from 13.4 million twitter users (6.9 million male users) for 11 months were analyzed and the message polarity, sentiment strength and the type (evaluative/factual) of messages were explored.BR Results: The results showed that the average sentiment strength of female users was significantly (p 0.01) higher than that of male users and the average sentiment strength of highly active male users was lowest among groups. It also showed that the highly active male users tend to post more negative messages than other groups and female users express significantly more positive sentiment than male users for both highly and less active user levels.BR Conclusion: It implies that the gender and activity level differences of users should be considered in sentiment analysis on social media data to gain valuable insights.BR Application: The results of this study could be used as quantitative, empirical data and design guidelines for developing sentiment analysis and opinion mining systems on SNS.
The Dark Side of Things

Over the last years the Internet of Things (IoT) has become a reality, moving from a futuristic topic to something pretty much everybody has some experience with. We are all using apps that tell us how to remain fit, and enable us to remotely control our heating, monitor health conditions and even in some cases save people’s lives. These are of course only a small fraction of the endless applications of IoT. Gartner predicts that by 2020 more than 20 billion connected “Things” will be in use, and some estimates are even higher. That is a lot of “Things” that will know something about us! Whilst IoT opens the doors to new opportunities (and who would not like a fridge that checks what is missing and send a reminder on what to buy?), it also creates new challenges on the security and privacy side. New Things are launched daily on the market, but how much do companies invest in securing users’ access, privacy, and users’ data collected by Things and often residing on the providers’ cloud? Things collect an enormous amount of data that in the wrong hands may lead to dangerous data leaks. This section provides an overview on Federated Identity Management (FIM) and its key aspects; it continues with exploring the challenges to expand the traditional federated identity management to IoT and provides an overview on how to authenticate devices and secure the way the data they collect are transmitted in a secure way.
Strong Designated Verifier Signature Scheme with Undeniability and Strong Unforgeability in the Standard Model

Strong designated verifier signature can provide an efficient way to protect the identity privacy of the signer and the integrity of the data transmitted over the public channel. These characteristics make it very useful in outsourcing computing, electronic voting, electronic bidding, electronic auction and other fields. However, most strong designated verifier signature schemes are unable to identify the real signature generator when the signer and the designated verifier dispute a signature. In addition, the existing strong designated verifier signature schemes in the standard model rarely satisfy strong unforgeability, and thus cannot prevent the attacker from forging a valid signature on any previously signed message. Therefore, designing a strong designated verifier signature scheme without random oracles that satisfies strong unforgeability and undeniability is very attractive in both practice and theory. Motivated by these concerns, we design the first undeniable strong designated verifier signature scheme without random oracles, in which the arbiter can independently perform the judgment procedure to prove whether a controversial signature is generated by the signer or the designated verifier. Under standard assumptions, the scheme is proved to be strongly unforgeable in standard model. Furthermore, it not only achieves non-transferability and privacy of the signer’s identity but also satisfies the undeniable property of traditional digital signature schemes. Performance analysis results show that the length of the signer’s private key, the designated verifier’s private key and signature length are 40 bits, 40 bits and 384 bits, respectively. Compared with he related schemes, the proposed scheme has higher performance in signature length, private key size and computational overhead. Finally, we show how to apply it to implement outsourcing computation in cloud computing.
Implementación de cuentos motores en Educación Infantil en niños y niñas con y sin discapacidad

This article proposes an educational innovative consistent experience in implementing moving stories with visual support in a classroom of Preschool Education. The design of the stories is based on the interests of the children, being important an observation and previous knowledge, organizing the space and the necessary material. The story is accompanied of visualization of images projected in digital slate and the children proceed to the execution of the actions requested in the narrated argument. A questionnaire is elaborated to evaluate so much the different areas of development (personal-social, adaptative, communicative, cognitive and psychomotor) as the implementation of the meetings concluding that the motive story is a playful, flexible resource, with possibility of adjustment to the needs of the student body; it reduces relational bows; it offers experiential learning and promotes the autonomy; the interest of the children wakes up with and without disabilities as well as that the utilization of the visual support helps them to visualize and understand the story of the story and the action to exercise.
THE LEGAL ISSUES OF THE ARTIFICIAL INTELLIGENCE, INTELLECTUAL PROPERTY RIGHTS AND DATA PROTECTION

The explosion in computing and artificial intelligence brings many legal challenges. One of the primary areas for legal interest is the field of copyright when such systems are part of the process of creating works. The status of such works varies according to the legal systems under which they are reviewed, and this article compares two such foundations.
DESIGNING A VIRTUAL TRAINING LAB FOR FUTURE EDUCATORS OF VOCATIONAL TRAINING IN FOOD TECHNOLOGY

Аrticle analyzes the definition of the concept of “virtual laboratory”, considers the features of using virtual laboratories at various stages of laboratory work, gives examples and indicates the advantages of creating them for the training system for teachers of vocational education in food technology. A design model for the functioning of a virtual training laboratory using algorithms for the operation of technological equipment is proposed. The ways of implementing modern approaches in the preparation of future teachers of vocational training in food technology are presented. The algorithm of virtual laboratory work is considered on the example of the discipline "Equipment of restaurant facilities" in the simulation format. The implementation of laboratory work in virtual laboratories contributes to the formation of the intellectual development of students, allows pedagogically balanced use of modern software in the educational process and the assimilation of knowledge at a more conscious and deep level. The positive dynamics of the qualitative indicators of the formation of professional competence of future teachers of vocational training was followed after classes using virtual laboratory work. In the process of developing the virtual laboratory work we presented, psychological requirements were taken into account, the essence of which is a phased solution of problem situations programmed by the teacher, which strengthen the students' semantic and logical activity. A thorough mastery of the knowledge gained during the execution of the virtual laboratory complex provides an appropriate level of development of scientific developments and technological management of the educational process. The structure of virtual laboratory work presented by us makes it possible to provide such components of the learning process as enhancing knowledge to perform research and control knowledge.Keywords: virtual laboratory, vocational training teachers, food technology, laboratory work, technological equipment.
Dynamic Network Configuration: An Effective Defensive Protocol for Public Blockchain

To earning unfair profits, adversaries can attack the legitimate nodes in the Bitcoin network with selfish mining, the eclipse attack and the information delaying attack. In this paper, we study the patterns of the above attacks and then present a scheme to enhance the security of the Bitcoin network. First, we propose a new structure for the Bitcoin network called double-layer dynamic network, which improves the defense capability of Bitcoin against several attacks. Second, we design a new structure for the blocks in the Bitcoin network, which provides a way to store the IP addresses in the blocks. Third, we present a novel network protocol named dynamic network configuration for public blockchain. Our protocol pushes the updating of IP addresses in the blocks and changes the construction of the network periodically. From theoretical analysis and simulated evaluation, we find that under our protocol, the Bitcoin network can defend against the selfish mining, the eclipse attack and the information delaying attack effectively.
IMPROVING THE WEB SEARCH USING SEARCH ENGINES OPERATORS

The amount of information stored in the Web is huge and without help from search engines it becomes almost impossible to find what you want. The search engines try to index as many web pages as possible. On April 3 rd 2018 there were over 45.5 billion webpages indexed by Google and just over 4 billion web indexed by Bing. Even with the help of search engines, the number of addresses of pages returned by them for a simple query is quite large and we, as people, must look through those pages to find what we are really interested in. Finding the URLs in such a huge data space is challenging and requires some special techniques for refining and reducing the number of returned addresses. In our paper we present some interrogation modifiers and search operators used by the Google search engine to reduce significantly the number of the search results and to increase the quality of that results. The presented techniques and commands for search engines that can be used for finding similar web pages or even to find web pages which repeat information from another sources.
Multivariate Attention Network for Image Captioning

Recently, attention mechanism has been used extensively in computer vision to deeper understand image through selectively local analysis. However, the existing methods apply attention mechanism individually, which leads to irrelevant or inaccurate words. To solve this problem, we propose a Multivariate Attention Network (MAN) for image captioning, which contains a content attention for identifying content information of objects, a position attention for locating positions of important patches, and a minutia attention for preserving fine-grained information of target objects. Furthermore, we also construct a Multivariate Residual Network (MRN) to integrate the more discriminative multimodal representation via modeling the projections and extracting relevant relations among visual information of different modalities. Our MAN is inspired by the latest achievements in neuroscience, and designed to mimic the treatment of visual information on human brain. Compared with previous methods, we apply diverse visual information and exploit several multimodal integration strategies, which can significantly improve the performance of our model. The experimental results show that our MAN model outperforms the state-of-the-art approaches on two benchmark datasets MS-COCO and Flickr30K.
Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge

Abstract The clustering method is one of the important methods that can be used to analyze the big volume of data that should be grouped accordingly as much as possible. Depending on the characteristics of the data available today and to deal with big data challenges, several clustering methods have been developed. But, in many situations, we cannot know a priori the number of clusters in the dataset. This refers to an important problem in cluster analysis or determining the numbers of clusters. In this context, this paper describes some clustering methods, with special attention to the Visual Assessment Tendency (VAT) algorithm as one of the known methods. This algorithm is implemented in advanced technologies to analyze big data. Keywords: Big data, clustering tendency, k-means, knowledge, visual assessment algorithm. JEL Codes: C10, C38
Requisites for Development of a Regulated Secondary Market in Digital Assets

The component parts of a more complete market system in digital assets are steadily being assembled. The initial focus on the primary market has increasingly expanded to the secondary market. Cryptoexchanges are a particular subject of interest given their growing predominance and the exchange-like or intermediary-like roles they may undertake at various times.This paper considers the pathway issues for the development of a regulated secondary market in digital assets. It explores the conditions necessary to develop a regulatory framework that does not also serve to reshape and confine the possibilities offered by cryptographic consensus technology. To achieve core regulatory objectives, what regulation attaches to will need to be sensitive to the characteristics of different centralized and decentralized cryptoexchange models as well as the digital assets traded on them. The problem of establishing accountability and anchoring locus in relation to decentralized cryptoexchanges is considered. How the common characteristics of digital assets impact on the ability to develop secondary market regulation that meaningfully meets policy objectives is reviewed.The potentially discriminating effect of imposing regulatory oversight on an industry in which different models of operation are still emerging must be carefully weighed. It is suggested that development of the regulatory framework should be model-neutral, form-independent and remain focused on the oversight of functions and establishing accountability for wrongdoing. Regulation should not be prematurely imposed in a manner that may inhibit the ability of private market regulation to develop effective outcomes that align with public policy concerns. Any development of regulatory oversight must also contemplate the involvement of intermediaries providing services specific to digital assets as well as intermediaries already involved in traditional markets.It is proposed that it is necessary to cease looking at the regulation of exchange systems and intermediary conduct in isolation from the characteristics of digital assets. There is a clear prospect for a more fundamental interaction between secondary market activity and the asset design process that could better facilitate the formation of regulatory building blocks. This depends on the development of an effective public-private partnership.
Interaction Models Of Teaching And Learning Listening Of The Seventh Grade At Mtsn Pantai Hambawang Barabai Academic Year 2017/2018

Listening is also one of four skills in English where this skill is the first that have to be learned first before learning another skills. Listening very important in teaching and learning process because the students must understand about what teacher’s talking about. In the teaching and learning process, the models of teaching and learning interaction in classroom is very important as it constitutes part of the teaching and learning process. (Dagarin, 2004, p. 128) stated classroom interaction is interaction between the teacher and the students that occur in the classroom during the teaching and learning process.The research design used a descriptive qualitative method. The researcher used the English teacher of the seventh grade of MTsN Pantai Hambawang Barabai to collect factual data. And also the subject of this research is English teacher, and the object in this research is the interaction models in teaching and learning process.Based on the research result, the researcher found that the types of learning models in listening skill used by teacher were using audio visual media, such as used a speaker. And also only one teacher who speak to the whole class. Then all students listen about what the teacher has said.
Can Bio-Inspired Swarm Algorithms Scale to Modern Societal Problems?

Taking inspiration from nature for meta-heuristics has proven popular and relatively successful. Many are inspired by the collective intelligence exhibited by insects, fish and birds. However, there is a question over their scalability to the types of complex problems experienced in the modern world. Natural systems evolved to solve simpler problems effectively, replicating these processes for complex problems may suffer from inefficiencies. Several causal factors can impact scalability; computational complexity, memory requirements or pure problem intractability. Supporting evidence is provided using a case study in Ant Colony Optimisation (ACO) regards tackling increasingly complex real-world fleet optimisation problems. This paper hypothesizes that contrary to common intuition, bio-inspired collective intelligence techniques by their very nature exhibit poor scalability in cases of high dimensionality when large degrees of decision making are required. Facilitating scaling of bio-inspired algorithms necessitates reducing this decision making. To support this hypothesis, an enhanced Partial-ACO technique is presented which effectively reduces ant decision making. Reducing the decision making required by ants by up to 90% results in markedly improved effectiveness and reduced runtimes for increasingly complex fleet optimisation problems. Reductions in traversal timings of 40-50% are achieved for problems with up to 45 vehicles and 437 jobs.
Attack-Resilient Connectivity Game for UAV Networks using Generative Adversarial Learning

The continuous link connectivity is critical for the efficient collaboration of multiple unmanned aerial vehicles (UAVs). However, the UAV communication environments are not only harsh, but are also confronted with the threats of smart attackers, which pose great barriers in maintaining the links unblocked. In this paper, we leverage the paradigm of the Generative Adversarial Network (GAN) to formulate an attack-resilient connectivity game between a pair of neighboring UAVs and an attacker. In the three-agent adversary game, the attacker acts as the generator, which attempts to generate highly approximate information as the UAVs so as to maximize its jamming capability; while the pairwise UAVs act as the discriminators, which attempt to enhance the capability of refusing the fake information (i.e., the opponent's attack). As the state-of-the-art GAN learning algorithms suffer from the instability dilemma (i.e., either with the unsuccessful convergence or with the low generation/discrimination performance), we incorporate the conditional GAN with the least square objective loss function as well as the mean square error such that the attacker can improve the detection capability from UAVs' historical activity patterns and the UAVs can accordingly adjust the connectivity strategy. We validate the effectiveness of the proposed algorithm through extensive evaluations. Results demonstrate that the proposed algorithm can improve the convergence efficiency, reduce the connection latency, and enhance the attack-resilience capability significantly.
ViTALiSE: Virtual to Augmented Loop in Smart Environments

Future workplaces will be smart environments providing human users with features and functionalities augmenting their capabilities while lowering their cognitive/physical efforts. ViTALiSE is a vision of future smart environments integrating Human-Agent Collectives (HAC) with Digital Twins (DTs) fostering the synergistic interplay between the physical and digital reality.