Reviewerly/exHarmony huggingface dataset:
INVESTIGATING HOFSTEDE CULTURAL DIMENSIONS AMONG ENGINEERING STUDENTS

International cooperation is impossible without intercultural competencies of employees and their readiness to work in multicultural teams. Therefore, engineering students should be aware of cultural differences between nations, understand their cultural dimensions criteria, and be capable to find contact with people from other cultures. The paper used G. Hofstede survey methods to evaluate the levels of cultural dimensions of Master’s degree engineering students in a Russian university. The data obtained were compared to the Cultural Compass online databank. The majority of cultural dimensions parameters matched the figures from the online databank, while two dimensions, namely, “power distance” and “uncertainty avoidance” gave different results. The survey and its results were later discussed with the students. The discussions showed that the students were open for a dialog, and interested in improving their intercultural competencies. The investigation results showed that by engaging engineering students into discussing cultural diversity and unity issues we can provide a higher efficiency team work of the local and international students. This experience has a positive impact on the competitiveness of the future graduates. Further research will enlarge the number of students participating in cultural surveys.
New model, to evaluate the implementation of LMS in institutions at a higher level, through the supplies of the student

The information and communication technologies-ICT, have more use with the implementation of Learning Management System-LMS; The present study was carried out to evaluate the use of four LMS in a university, to identify acceptance and performance, through the student's inputs, the LMS used: Edmodo, Classroom, Schoology and Moodle, the methodology consisted of 4 stages; 1) LMS selection, 2) conFiguretion LMS, 3) evaluation of acceptance factors and 4) calculation of statistical coefficients. The results obtained from the four LMS, Google Classroom in its conFiguretion has the highest level of performance, with an average of 73%; while for the statistical coefficients; Of seven factors evaluated for the level of acceptance, those with the greatest preference for the learners were System Factors FS (82%), Anxiety and innovationAI (80%) and Virtual Library BV (43%).
«ERASMUS+» PROJECTS AS A TOOL FOR THE DEVELOPMENT AND INTERNATIONALIZATION OF AGRICULTURAL EDUCATION

The article examines processes underpinning the formation of the culture of internationalization using as an example implementation of international projects at Russian Timiryazev State Agrarian University (RSAU-MTAA). The objective of the article is to study the factors of the polyspatial environment of the university as instruments of internationalization. The novelty of the research is to present the synergistic effect of the interaction of various innovation groups in terms of internationalization culture formation in the context of the European Higher Education Area development, as well as quality enhancement and higher education modernization in the era of digitalization and expansion of Industry 4.0. The practical significance of the study is in future application of the research results for the development of internationalization processes in individual universities, and introduction as the educational material in various in-service training courses for university staff.
Identificação de Perfis Depressivos em Redes Sociais Utilizando Aprendizado de Máquina: um Mapeamento Sistemático

Depression is a psychological disorder that affects millions of peoplein theworld, regardless of their age, social class or nationality. In theliterature, different techniques have been studying to analyze andrecognize this disease such as Natural Language Processing, SentimentAnalysis, and Machine Learning. In this paper, we describe asystematic mapping to identify evidence regarding techniques thatare often used to identify depressive profiles.We analyzed 472 studiesand we selected 25 primary studies. These studies indicate thatthe SVM and NB techniques have been most used to detect possibledepressive profiles in social networks. Furthermore, Twitter andFacebook with 35,5% and 22,6%, respectively were the social mediamost have been used by users’ express their feelings regarding themost varied subjects.
E-cash Payment Scheme in Near Field Communication Based on Boosted Trapdoor Hash

In the modern world, there is rapid progress in the Internet and information technology that is becoming more important in the field of Electronic commerce. The majority of the clients use the electronic cash process as an alternative to using real cash. But in this E-cash method, there is a problem faced by most of the customers that is the privacy and safety of the client. In order to preserve the privacy of this mechanism, the trapdoor hash function plays a vital role in the construction of secure digital signatures. This secure digital signature is broadly used in different fields nowadays. Near Field Communication (NFC) is nowadays a popular technology to facilitate enabling the payment technique of consumers with the mobile token system. This paper suggests an adapted scheme that integrates boosted trapdoor hash and NFC technology to enhance E-cash payment robustness with minimum computation cost. Boosted trapdoor hash relies on appending some bits to the original signature to increase the digital signature’s security and reduce the modular reduction in onlinecomputation. Since the processing does not require the operation of division, it is easier than other schemes to implement in the environment of smartphones. The suggested scheme can be used with mobile devices effectively in E-payment.
Design and Implementation of Image Forgery Detection System Based on Cloud Computing

The masses of people urgently need a platform to help them identify the authenticity of network images, but the existing image forgery detection algorithms generally have high thresholds and poor real-time problems, making it difficult for the public to provide efficient detection services. Therefore, this paper proposes a cloud-based network image forgery detection system that uses B/S architecture, integrates multiple algorithms, and uses cloud computing and GPU computing technologies to improve system throughput and detection speed. Experimental results show that the system can effectively detect copy-move and splicing forgeries, and the GPU's speedup ratio reaches 6.5, which significantly improves the detection speed and throughput of the system.
Viewpoint-Aware Channel-Wise Attentive Network for Vehicle Re-Identification

Vehicle re-identification (re-ID) matches images of the same vehicle across different cameras. It is fundamentally challenging because the dramatically different appearance caused by different viewpoints would make the framework fail to match two vehicles of the same identity. Most existing works solved the problem by extracting viewpoint-aware feature via spatial attention mechanism, which, yet, usually suffers from noisy generated attention map or otherwise requires expensive keypoint labels to improve the quality. In this work, we propose Viewpoint-aware Channel-wise Attention Mechanism (VCAM) by observing the attention mechanism from a different aspect. Our VCAM enables the feature learning framework channel-wisely reweighing the importance of each feature maps according to the "viewpoint" of input vehicle. Extensive experiments validate the effectiveness of the proposed method and show that we perform favorably against state-of-the-arts methods on the public VeRi-776 dataset and obtain promising results on the 2020 AI City Challenge. We also conduct other experiments to demonstrate the interpretability of how our VCAM practically assists the learning framework.
REACT-M: uma Abordagem Ágil para o Gerenciamento de Requisitos de Software

Agile methods provide support to software engineeringactivities, aiming to reduce some of problems of the traditionalapproaches. Quality products can be developed by agilemethodology in less time and budget. Requirements engineeringis a building block of software development. Therefore, thesearch for agile practices for the evolution of requirementsbecomes relevant. Although several researches have been carriedout on the role of requirements engineering in agilemethodologies, there is still a need for studies that seek to alignagile approaches to requirements development and managementprocesses that satisfy highly accepted quality models in themarket. This paper aims to establish an agile approach tosupport software requirements management, based on asystematic literature mapping that draws on existing approachesin agile methodologies that support requirements managementactivities.
A Path for Tracking Funded Research and Compliance

Abstract To better understand how CHORUS [1] is creating a future where the output flowing from funded research is easily and permanently discoverable, accessible, and verifiable, this article will share the story of its origins, present an overview of its services, and look at what’s in the pipeline. Working closely with organizations from all corners of the scholarly community, CHORUS is helping to establish new foundational standards, metrics, and metadata. This work is enabling CHORUS to introduce new and expanded capabilities—notably, tracking research datasets and integrating institutional identifiers—that support the continuing evolution of a sustainable and connected open-science infrastructure.
Smart Data Logger for Solar and Wind Power Generation

As solar and wind power generation systems are becoming more and more popular owing to the depleting fossil fuels, smarter monitoring systems with precision data logging are an active area of development. The data accumulated are very useful if analyzed properly, and hence, the data logged so far need to be accurate without significant error. In this paper, a smart design and implementation of a microcontroller-based data acquisition system are presented to monitor solar irradiance and speed of wind as these are the primary parameters deciding power generation in a solar–wind hybrid power plant. A pyranometer is used as a solar radiation sensor, and an anemometer senses wind speed. Temperature (solar insolation) and generated power have also being logged. A relationship has been tried to develop among the key parameters and dependent variables.
Training Wide Residual Hashing from Scratch

Deep supervised hashing aims to encode high-dimensional data into low-dimensional compact hash codes, which is important for solving large-scale image retrieval problems. In recent years, deep supervised hashing methods have achieved some positive outcomes. However, these methods can not meet expectations without fine-tuning from the off-the-shelf networks pre-trained on large-scale classification dataset. To cope with this problem, we rethink the paradigm of fine-tuning on deep supervised hashing and propose training deep supervised hashing from scratch. Based on this new perspective, we propose a wide residual hashing model trained from scratch, which can greatly improve the training time and reduce the model size. To the best of our knowledge, our method is the first framework that can train deep hashing networks from scratch without losing performance. By training from scratch, the parameters of the model are more less and our results are superior to state-of-the-art hashing algorithms. We hope the insights in this paper will open a new avenue for learning deep hash codes from scratch and transfer to further tasks not explored in this work.
Neural Network Design for Multimedia

Neural network architecture design is playing the most important role in recent fast development of multimedia technology. In this talk, I mainly introduce the research and development efforts in designing neural networks from two orthogonal lines: 1) how these neural network models are bio-inspired, e.g. the 1x1 convolution simulates the function of cell-body of a neuron, and 2) how these models are more hardware-friendly or motivating the next-generation of AI chips, e.g. the selective convolution is expecting new design of hardware. These two lines of efforts are collaboratively enhancing the overall efficiency of multimedia systems.
Direct temporal mode determination for the characterization of temporally multiplexed high dimensional quantum entanglement

We report a direct method that measures the exact form of temporal modes. We then apply this method to a pulse-pumped parametric amplifier and demonstrate telecom band temporally multiplexed multi-dimensional continuous variables quantum entanglement.
The use of Twitter and Facebook Social Media in Communicating &amp; Disseminating Weather and Climate Information by Kenya Meteorological Department

Today, traditional media is still a significant part of disseminating weather and climate information, still they have not been able to reach out to all users of the target audience alone. On the other hand, social media platforms such as Twitter, Facebook, YouTube, Instagram, etc. are used as a tool of communicating weather and climate information to various users in a well-organized manner like never before. Using a scientific research methodology of case study, the research was designed to explore how the Kenya Meteorological Department (KMD) is using Twitter and Facebook accounts for weather and climate information dissemination to various users.
Neighborhood preserving discrimination for rotor fault feature data set dimensionally reduction

NPP (Neighborhood Preserving Projections) is an incremental subspace learning methods which has a nature of maintaining the data local neighborhood geometry constant. To improve the discriminatory power of NPP, NPD (Neighborhood Preserving Discrimination) algorithm was proposed to be used for the rotor system fault data set feature dimensionality reduction. Floyd algorithm based on graph theory and MMC (Maximum Margin Criterion) were introduced in the NPP which makes NPD avoid the short-circuit problem that occurs in the high curvature high dimensional space data sets, while enhancing data discrimination information during the dimensionality reduction. In addition, NPD can maintain the manifold of data set unchanged. At last, the rotor-bearing experiment has been made to verify the effectiveness of the NPD method.
Team leadership and its personal background in the studengroup

The article anylyses the theoretical and methodological basis for the study of the problem of team leadership in the student environment: the importance of team formation in the student environment, the essence of the concept of "leadership", the psychological components of effective team leadership. Team leadership is seen as the ability of a leader to gain authority in one’s group, thereby gaining the primary right to make group decisions, as well as to recognize the strengths of others and delegate task management functions to others. Also, command leadership is seen as a process of allocating authoritative personalities in a group and facilitating them to develop leadership qualities of other members of the group, which leads to the emergence of coordinated teamwork. It is noted that tactics of the leader’s influence on the group can determine the effectiveness of team leadership. His typical actions, internal psychological features, ability to update the desired features in a specific situation. The authors consider the internal psychological features of students, which determine the command style of leadership, as follows: flexibility, originality, critical thinking, orientation to solving problems in difficult situations; desire for cooperation, diplomacy, ability to manage and resolve conflicts, organizational skills, communication skills; striving for self-development and self-improvement. The essence of the empirical study of the psychological components of effective team leadership in a student environment is highlighted.
The Effect of English Conversation Videos on Students’ Listening Skill

The purpose of this research was to prove that using an English conversation videos is effective in teaching listening skill. This research conducted in SMP Muhammadiyah 1 Wonosobo. The population of this research is eight-grade students, and the sample is 40 students. The method of this research is quantitative method and using pre-experimental design. To collect the data, the writer used a pre-test, and post-test that given to the students. The resulting score of the data indicated that, the total score of students in the pre-test was 2350 with the average were 58.75. The total student's post-test score is 3080 with an average of 77. The results of the pre-test and post-test were calculated using a t-test. The calculation of the data result indicates that the t-count was 2.26 with t-table is 1.69 at the 0.05-significance level. Therefore, this implies that the alternative hypothesis (H1) is accepted, and the null hypothesis (H0) is rejected. The writer concluded that using English conversation videos on studies in teaching English was effective to improve students’ listening skills.
A Study of Hybrid Approach for Face Recognition Using Student Database

The student’s attendance plays a very important role during their academic year. Teachers have to spend a lot of time and attention to maintaining the students’ attendance records punctually and regularly. Face recognition is the best and smart solution for the maintenance and keeps a regular attendance record of the students for the teachers in their academic year so that they can concentrate on the student`s academic developments. Here, we combine two basics feature extraction techniques, i.e., PCA for low dimensionality reduction and LDA for feature extraction whereas an SVM classifier is used for face classification. We perform the experiment using the Student Database (SDB) of different age groups of students, which are collected in different lighting conditions, with different facial poses and expressions. The results obtained from the combination of PCA, LDA are very satisfactory and we successes to reduce the time duration for marking attendance.
High-dimensional quantum key distribution using polarization-phase encoding: security analysis

In this work, we introduce a high-dimensional polarization-phase (PoP)-based quantum key distribution protocol, briefly named PoP[Formula: see text], where [Formula: see text] is the dimension of a hybrid quantum state including polarization and phase degrees of freedom of the same photon, and [Formula: see text] is the number of mutually unbiased bases. We present a detailed description of the PoP[Formula: see text] protocol as a special case, and evaluate its security against various individual and coherent eavesdropping strategies, and in each case, we compare it with the BB84 and the two-dimensional (TD)-PoP protocols. In all the strategies, the error threshold and the effective transmission rate of the PoP[Formula: see text] protocol are far greater than the other two protocols. Unlike most high-dimensional protocols, the simplicity of producing and detecting the qudits and the use of conventional components (such as traditional single-photon sources and quantum channels) are among the features of the PoP[Formula: see text] protocol.
Pengaruh Kajian Praktik Lapangan (KPL) dan Pembelajaran Microteaching Terhadap Kesiapan Mengajar Mahasiswa Prodi Pendidikan Teknik Mesin Universitas Negeri Malang

KPL and mictroteaching study are course programs of education as an effort to equip and give an experience of real teaching to education students. This study used ex post facto research method with quantitative approach. Population and sample of this study were Mechanical Engineering Education students of 2015 generation. Instrument used in this study as data collecting technique was an questionnaire. Results of study: 1) Analysis result of hypothesis test of KPL showed significance (0,001 &lt; 0,05). 2) Analysis result of hypothesis test of microteaching study showed significance (0,000 &gt; 0,05). 3) Analysis result of F test (simultaneity test) KPL and microteaching study showed significance (0,000 &lt; 0,05) and Fcount &gt; Ftable (57,642 &gt; 3,11).Keywords: Kajian Praktik Lapangan (KPL), Microteaching Study, Readiness in Teaching
The crisis of trust in COVID-19 pandemic: can blockchain technology help?

BACKGROUND: The widespread death and disruption caused by COVID-19 pandemic has revealed the failure of existing institutions to protect the health and well-being of humanity Lack of accurate and timely data along with pervasive misinformation is causing even more harm and growing tension between data privacy and public health concerns OBJECTIVE: This paper describes how blockchain, with its distributed trust networks and cryptography-based security, may provide solutions to some of these data-related trust problems METHODS: Blockchain is being applied in innovative ways that are relevant to the current COVID-19 crisis We describe examples of the challenges in existing technologies to track medical supplies and infected patients and how blockchain technology applications may help in these situations RESULTS: This review of existing and potential applications of blockchain technology for medical care show how its distributed governance structure and privacy preserving features may create a trustless system that helps resolve the tension between privacy and public health needs in the fight against COVID-19 CONCLUSIONS: Blockchain relies on a distributed, robust, secure, privacy-preserving, and immutable record framework that can transform the nature of trust, value sharing, and transactions for the better A nationally coordinated effort to explore blockchain for addressing the failures of existing systems and a partnership of academia, researchers, business, and industry is suggested to expedite the adoption of blockchain in healthcare
Informatics Open Library: Innovation in Developing Electronic- Service Case Study Departemen Informatics ITS

Background of the study: Many of information resources available in the central library and Departemen Informatics of ITS, in various formats, printed, non- printed, electronic collections, and other media that require users to search for independent information, so users are faced with various search and location options.Purpose: This study aims to identify the problem of ability of library user to find the needs of information resources and Designing an integrated library information system in the Informatic Open Library application to solve user problems to find the needs of information resources. Method: This research uses qualitative approach with descriptive methods.Findings: Application development related to services and data security must continue to be done as well as analysis should be done every year by comparison with the analysis of the previous year to improve service quality at the highest level.Conclusion: Based on the results of research in the field, the implementation of the Informatic Open Library has been good, the aim of facilitating services for Siva ITS Department of Information has been achieved and provides benefits for lecturers. Librarian, education staff, students, and institutions. The role of librarians and librarian collaboration with lecturers and students is a supporting factor in the successful implementation of the Informatic Open Library application.