Reviewerly/exHarmony huggingface dataset:
Local Historical E-resources in the Educational Process

Digitization and mediatization of information raise the issue of user access to electronic information resources. Given the need to form and strengthen the regional and national identity, study and promote historical and local lore information and providing access to it, the integration of such information into educational practices to master it by young people has become more important. The article is devoted to the coverage and substantiation of effective approaches to using local lore electronic resources in the educational process. During the research, the descriptive method, methods of comparison and generalization concerning the experience of use in the field of education of local lore electronic resources of libraries were used. The methods of included observation and periodic monitoring, applied during the development and maintenance of the functioning with the participation of the author of the local history resource "Kraeved" (kraeved.od.ua) (starting from 15.03.2020), proved to be effective. An analytical and survey method was used to analyse the available theoretical work on the research topic. The novelty of the obtained results lies in the coverage and substantiation of the specifics of the use of electronic local history information resources in the educational process in different countries, in particular during the study of students of historical specialties, and some countries – students majoring in cultural studies and art history. The most comprehensive electronic local history information resources are used in the United States, where their historical and local history content attracts not only teachers and students but also a wider range of users: genealogists, writers, engineers, urban planners, architects, realtors and documentary filmmakers. The obtained results of the research testified to the tendency to use library local lore electronic information resources in the educational process. Their creation, interest of users in the information presented on them and its use during training testify to the importance of local lore content designed to promote the formation of the historical and cultural identity of the region in the context of national history and the formation of national historical memory in combination with historical thought. The generalization of foreign experience and perspective domestic practices of using local library electronic resources in the educational process allows substantiating effective approaches to the organization of such activities, intensification of involvement of domestic library local lore electronic information resources in solving information problems related to educational activities. The intensive development of digital library projects in the educational environment will open additional ways to implement the tasks of libraries to ensure wide access of users to local history information sources and the maximum disclosure of their information potential.
Automatic identification of synthetically generated interlanguage transfer phenomena between brazilian portuguese (L1) and english (L2)

Transfer phenomena between Portuguese (L1) and English (L2) produced by Brazilian learners are well documented in the literature. However, the identification and classification of these processes are made mainly through transcriptions, a slow and laborious process done by specialized linguists. The rapid identification of these phenomena would be of great value for software doing proficiency placement tests and could be used in language schools, distance education, computer-assisted pronunciation training (CAPT) or by autodidacts and researchers. The present work analyzed possible techniques and tools that can be used in the automatic identification of some transfer processes. The data for the grapho-phonic-phonological transfer were synthetically generated in the Google Translate™ TTS system. Then we tested three classification algorithms to perform the identification: k-Nearest Neighbor, Centroid Minimum Distance, and Artificial Neural Networks. The results indicate that these techniques are of great value for Linguistics and for new software applications in language learning.
The Roles of Aesthetics and Information Quality on Continued Use of Digital Library (CUDL) by Malaysian Postgraduate Students

A digital library is a new information system provided by libraries and information centers around the world, including in Malaysia.It is important to study the reasons why and how users accept and use digital libraries.The objective of this study is to investigate the roles of aesthetics where it divided into two types which are classical aesthetics and expressive aesthetics; and information quality on users' continued use of a digital library.The study proposes to investigate the factors that are expected to influence the intention of postgraduate students to continued use of the digital library based on three models: a modified UTAUT2 model, an aesthetics model, and Delone and McLean's Information Success Model.Postgraduate students from University Sains Malaysia (USM) will be selected as the sample to test the research questions and fulfil the research objectives of the study.It is expected that this research will provide new insights into research on continued use of the library (CUDL) in a digital environment.
A List of Risks and Mitigation Strategies in Agile Projects

Different factors affect the proper software development processes execution, such as the lack of progress monitoring and deficiencies in team skills. These factors, called risks, are depending on the peculiarities of each project. The goal of this work is to identify common risks in agile development projects and to propose mitigation strategies for these risks. To do that, we performed a mapping review to obtain 17 common agile risks. The mitigation strategies to these risks were defined considering activities, roles and artifacts from Scrum, Kanban, and DevOps. To facilitate the visualization of the risks and the mitigation strategies, we developed a web page that has been successfully evaluated by students of last year of informatics engineering career.
Deep Reinforcement Learning Algorithms for Multi-Agent Systems - A Solution for Modeling Epidemics

Multi-agent reinforcement learning (MARL) consists of large number of artificial intelligence-based agents interacting with each other in the same environment, often collaborating towards a common end goal. In single-agent reinforcement learning system the change in the environment is only due to the actions of a particular agent. In contrast, a multi-agent environment is subject to the actions of all the agents involved. Multiagent systems can be deployed in various applications like stock trading to maximize profits in stock market, control and coordination of a swarm of robots, modeling of epidemics, autonomous vehicle and traffic control, smart grids and self-healing networks. It is not possible to solve these complex tasks with a pre-programmed single agent. Instead, the many agents should be trained to automatically search for a solution through reinforcement learning (RL) based algorithms. In general, arriving at a decision in a multi-agent system is almost close to impossible due to exponential increase of problem size with an increase in the number of agents. In this paper, multi-agent systems using Deep Reinforcement Learning (DRL) is explored with a possible application in modeling of epidemics. Different stochastic environments are considered, and various multi-agent policies are implemented using DRL. The performance of various MARL algorithms was evaluated against single agent RL algorithms under different environments. MARL agents were able to learn much faster compared to single RL agents with a more stable training phase. Mean Field Q-Learning was able to scale and perform much better even in the situation of hundreds of agents in the environment and is a sure candidate to model and predict the epidemics, in the existing frightening dangerous situation of corona pandemic.
Penerapan representasi visual menggunakan komik sebagai upaya meningkatkan kemampuan berpikir kritis dan penguasaan konsep siswa pada materi sistem saraf

The purposes of this research were to analyze the application of visual representations using comics as an effort to improve student’s critical thinking skills and mastery of concepts in nervous system material. The subject of this study is second grade-students in Senior High School. The method used in this research is Quasi experimental. The results of student’s critical thinking skills have increased higher in the experimental class, although the results of the critical thinking skills of the two classes are in the moderate category, the results of critical thinking in the experimental class showed that the increase in N-Gain was higher with N-Gain = 0.64 (medium category) while N-Gain in the control class = 0.53 (medium category). The results mastery of concepts in experimental class have n-gain is higher the n-gain control class with n-gain is 0.71 (high category), and the control class n-gain is 0.53 (medium category). The results of student responses showed that the majority of students were interested in using comic visual representations of 83.33%. Therefore it can be concluded that the use of comics can improve thinking skills and mastery of concepts better.
MODERN EDUCATIONAL EQUIPMENT IN ELECTRICITY AS A MEANS OF FORMATION PROFESSIONAL COMPETENCE IN PHYSICS

The article highlights the results of the organization of laboratory work using a modern digital training panel on electricity in a laboratory workshop on physics, which was developed and manufactured in Lutsk by the R &amp; D center Mirroschool. As a result of the research, we proposed a method of organizing laboratory work in physics using a training panel. The article contains a fragment of laboratory work in physics, which allows to intensify the cognitive activity of students in teaching physics. The guidelines will be useful primarily for physics teachers and instructors who conduct laboratory work and demonstrations on electricity, laboratory technicians in physical laboratories who work with physical equipment, and will be useful to students who master the knowledge of experimental science. The training panel on electricity fully provides training rooms for physical classrooms, laboratories and training facilities in the section «Electrodynamics», which are used in the school curriculum approved by the Ministry of Education and Science of Ukraine. The panel can be used by both teachers and lecturers in higher education institutions. Of course, laboratory work and demonstrations of general secondary education institutions are quite easy to modernize and adapt, which allows you to use other training panels that are presented in the market of educational equipment. But when it comes to higher education or colleges, the list of laboratory work can be significantly reduced, or simply have to use additional educational equipment and laboratory workshops. The electric training panel is a modern, school, educational equipment, which, among other things, successfully agrees with the educational norms of the new Ukrainian school and STEM education. The panel meets all requirements: language legislation, education standards, compliance with sanitary legislation, fire and electrical safety, health care requirements, etc. Also, all consumables are available for purchase in Ukraine. Key words: laboratory work, demonstration, method, training panel, education.
The role of student self-government in the envi-ronment of technical university

Forming the future specialist’ social responsibility during the studies is an urgent problem of higher education, as social responsibility is an important personal characteristic that is directly related to solving professional and life problems. The formation of students’ social responsibility is influenced by many factors, one of which is the activities of student self-government. Goal. The determination of the role of student self-government bodies in the university environment and in the students’ social responsibility formation. Methodology. The use of situations of involving in real professional-labor relations, participation in competitions, exhibitions, solving production tasks, example of life and activity of senior colleagues, collective labor actions and courses and groups is a powerful integrative factor that contributes to the formation of a responsible attitude of future professionals to performing their duties, and as a consequence, increasing the level of social responsibility. The positive consequences of involving students in self-government are manifested in the emotional uplift of students, expanding the range of their interests, positive and active attitude to self-improvement, in the pursuit of ethical behavior, skills of emotional and volitional self-regulation, etc. Results. An effective involvement of student self-government bodies in the management of a higher educational institution in order to increase social responsibility. Originality. It is shown that the bodies of student self-government have wide possibilities of influence on forming students’ social responsibility through providing the purposeful forming of necessary knowledge and skills needed for development of responsibility. Practical value. The importance of student self-government in the formation of students’ social responsibility is confirmed in the protection of educational, scientific, social, creative, national-cultural, spiritual, sports, economic and other interests of students, the formation of skills of future organizers, leaders.
BTDetect: An Insider Threats Detection Approach Based on Behavior Traceability for IaaS Environments

How to detect malicious insiders&#x2019; improper access to tenant data has become more crucial in IaaS cloud environment, especially with the cloud administrators gaining more control on customers&#x2019; virtual machines and data in reality. In this paper, we propose an insider threats detection approach based on behavior traceability called BTDetect. First, we analyze the service invocation interfaces of IaaS cloud environment, such as computing service, remote call, management implementation and virtualization management, and condense the complete process of cloud user behavior. Using tree-based modeling technique, a behavior-tree construction algorithm is proposed to construct the normal behavior tree that can describe various legal operations of cloud users. Second , we set up trace points of cloud service behavior on multi-layer cloud service APIs, then we collect information of each interface being invoked across multiple nodes. Third, we use underlying virtualization behavior keyword matching technology to match the collected behaviors with the user's normal behavior tree and then the malicious internal threat can be identified through tree-based integrity analysis. Finally, some experiments are conducted to evaluate the feasibility and veracity of the proposed method in Openstack platform. The results suggest that our method can not only identify internal threat but also have high recognition rate.
Disruptive Engineering: Maximizing the Feedback Relationship between Industry 4.0 and the Nigerian Engineering Education Sector

The Fourth Industrial Revolution (4IR) continues to drive a fusion of physical, digital and biological technology in ways that are rewriting the norms in engineering practice by introducing new approaches such as Internet of things (IoT) and the Industry 4.0 paradigm, that are poised to also change the educational sector globally. Nigeria is yet to tap into the full potential of the Third Industrial Revolution. The relationship between 4IR and engineering education is considered as a positive feedback loop. 4IR technologies have great potential to enhance the quality of the Nigerian engineering education system, which in turn fosters an improved engineering education sector that is better-equipped to produce sustainable outcomes in Industry 4.0 era. This paper explores the potentials for application of 4IR technologies in improving the Nigerian engineering education delivery system by review and suggests ways through which the educational system can enhance the potentials of its educands to become competitive professionals in the disruptive-technology engineering era. It was concluded that the feedback relationship which exists between engineering education and Industry 4.0 needs rapt attention of stakeholders in order to address the reality of disruptive technology. Keywords— Industrial revolution, Internet of things, Engineering education, Positive feedback, Disruptive technology
Academics’ use of educational technology in the curriculum: Uncovering the matter of choice

At the boundary [of functionings and capabilities] is the matter of choice, where a person exercises his or her agency, having the requisite set of capabilities, to make choices from a range of options and alternatives, if such a choice achieves his or her well-being.(Walker 2006a:105)
Depth-guided Deformable Convolutions for RGB-D Saliency Object Detection

Recently, RGB-D salient object detection(SOD) has attracted increasing research interests, and existing methods have achieved huge success owing to well-designed feature extraction and fusion. However, in existing methods, the depth maps cannot be utilized entirely since RGB and depth are usually concatenated together as an entirety and then feed into the backbone to extract features, which cannot achieve the spatial supervision between both modals. In this letter, we propose a Depth-guided Deformable 3D Convolution (Guided-Conv) to solve this problem. Specifically, the Guided-Conv obtains the sampling offset of the 3D convolution kernel guided by the extra depth input, enabling the convolutional layer to change the receptive field and adapt to geometric cross-modal transformations. Besides, the Guided-Conv also incorporates geometric cues into the forward propagation by producing spatially adaptive filter weights. Based on comprehensive experiments on several extensively used bench-marks, the Guided-Conv yields strong results against several state-of-the-art RGB-D SOD approaches based on four key evaluation metrics.
Mapping application for Greater Bandung Area using Web Technology

Mapping is needed to determine the condition of spatial data and non-spatial data from an area. This research produces a mapping application based on geographic information systems that display spatial data and boundaries of 888 villages located in the Greater Bandung Area, which consists of Bandung City, Cimahi City, Bandung Regency, West Bandung Regency, and Sumedang Regency. The method used is the Software Development Life Cycle with Waterfall model. The technology used is the application programming interface from Openstreet MapBox and ArcGIS. Based on testing applications that can access online found that the application built can 100% display the mapping of all areas in the Greater Bandung Area to the district level. This research is useful for developing the tourism and creative industries of MSMEs based on each region's geographical conditions, both for the community and the government.
Mel Frequency Cepstral Coefficients based Bacterial Foraging Optimization with DNN-RBF for Speaker Recognition

Objectives: To improve the accuracy and to reduce the time complexity of the Speaker Recognition system using Mel-Frequency Cepstral Coefficients (MFCCs) and Bacterial Foraging optimization (BFO) with DNN -RBF.Method: The MFCCs of each speech sample are derived by pre-processing the audio speech signal.The features are optimized with BFO algorithm.Finally, the probability score for each speaker is generated to identify the speaker.Then the features are classified towards the target speaker using DNN-RBF.For the proposed MBFOB speaker recognition function, the TIMIT read corpus is used.It contains a total of 6300 phrases, 10 phrases each.Findings: the identity of user is validated in the fields of authentication and surveillance for recognition of speaker.By using the audio speech signal, features are extracted.This paper suggests an MBFOB solution based on Mel-frequency Cepstral Coefficients and DNN-RBF with BFO, for the identification of speakers.The speech utterance from the TIMIT data corpus is preprocessed to obtain MFCC feature vectors DNN-RBF is used for the purpose of classifying the speaker and the feature vectors in the output layers are optimized with Bacterial Foraging optimization.Finally, the scores for each speaker are calculated to identify the speaker.Different output metrics like EER, DCF, Cavg and accuracy are used to test the proposed speaker recognition technique.The execution time of this proposed method is found to be lesser than the other existing methods.The experimental findings are contrasted with other current methods and it shows the efficiency of our approach.Novelty: A novel MFCC-based Bacterial Foraging Optimization with Deep Neural Network-Radial Basis Function (DNN-RBF) for identification of exact speaker is proposed in this study.
The Impact of Social Responsibility on the Market Value for Services Corporations, Service Type as a Marketing Variable

The study aims to know the impact of social responsibility as a cost and also to show the market value of the Jordanian services corporations listed on the Amman Stock Exchange. “Services type” was used as a variable for the relationship rate in this study. The descriptive approach was used and applied to the data of 37 companies during the period from 2012-2019. The researcher also used statistical methods such as the arithmetic mean and standard deviation to describe the study data, and the test of linear regression and correlation analysis, in order to test the study hypotheses. Among the most important results that have been reached, there is an impact of social responsibility as costs and the disclosure of the market value of services companies. The study also showed a modified effect of services type on the relationship between social responsibility disclosure and market value.Based on the preceding, the study recommended expanding the social responsibility disclosure, which helps the company build a strong name as a desirable institution, which enhances the image of the company and the name of the product in the services market and among customers.
Multidomain Fusion Data Privacy Security Framework

With the collaborative collection of the Internet of Things (IoT) in multidomain, the collected data contains richer background knowledge. However, this puts forward new requirements for the security of data publishing. Furthermore, traditional statistical methods ignore the attributes sensitivity and the relationship between attributes, which makes multimodal statistics among attributes in multidomain fusion data set based on sensitivity difficult. To solve the above problems, this paper proposes a multidomain fusion data privacy security framework. First, based on attributes recognition, classification, and grading model, determine the attributes sensitivity and relationship between attributes to realize the multimode data statistics. Second, combine them with the different modal histograms to build multimodal histograms. Finally, we propose a privacy protection model to ensure the security of data publishing. The experimental analysis shows that the framework can not only build multimodal histograms of different microdomain attribute sets but also effectively reduce frequency query error.