Reviewerly/exHarmony huggingface dataset:
Covid-19 pandemic and the employees experience: motivation of the staff within an event organizing company

Due to the COVID 19 pandemic, everyone must respect the rules of social distancing. During this time, most of the people have felt trapped in a continuous loop in which the concept of time and space was just a distant dream. Even if the economic situation during this pandemic is not so dramatic many people have been unmotivated to work, most of them, currently working remotely. Switching to online is more difficult to keep up with everyday work activities. However, many jobs can be successfully done remotely. Unfortunately, while working from home, the employees can be easily distracted, which lowers their productivity. Reaching a minimum level of motivation and productivity, we decided to include in this research paper a case study on the motivation of the artistic staff within an event organizing company during the pandemic. By reviewing the results of the case study we want to analyze the specific factors of the human resources management that have an impact on the evetns organinzing comapnies including the evolution of the motivation and introduce some ways that can grow the motivation and make employees feel comfortable while working from home
Promising plans and practical use of ICT in education: Sub-Saharan Africa perspectives

Introduction. Information and communication technologies (ICT) in the field of education have become indispensable for many countries. Digital transformation of school has conquered the minds of many educationists in Sub-Saharan Africa which long suffered from low attendance rates and lack of qualified teachers. This is a developing region with unstable educational opportunities and ICT use is believed to be a central form solution for the future effective functioning of learning programmes. Materials and methods. General scientific theoretical methods and comparative analysis were used to analyze actual statistical data, take insight into existing online learning platforms, expert’s accounts. Results. Both the general problems of ICT application in education and its functioning in the context of national educational systems in such countries as Uganda and Kenya were analyzed. Unique evidence from this rapidly developing region underscores the need of a balanced and comprehensive approach to the strategies of the digital education reforms at school. Сonclusions. ICT introduction risks not to be an effective factor in the management of educational process without taking into account behavioral and sociocultural context as well as without thorough development of all levels of educational system. Though the article is addressed to the experts in the field of education and African studies, it will be of considerable interest to all practitioners concerned with the implementation of ICT in teaching practice.
Modeling Method of Underwater Vehicle Dynamic System Based on Simulink and Fluent Co Simulation

Based on the dynamic behavior simulation of underwater vehicle, aiming at the limitation of dynamic behavior and fluid dynamics in single environment, a collaborative simulation solution based on MATLAB/Simulink and Fluent is proposed. This paper first introduces the operation mechanism of MATLAB/Simulink and Fluent, analyzes the technical feasibility of CO simulation between the two simulation environments, and puts forward three feasible interface modes. On this basis, this paper focuses on the basic idea and specific implementation method of two embedded co simulation methods: embedded Matlab / Simulink in fluent and embedded fluent in MATLAB/Simulink, as well as parallel co simulation method. This co simulation method not only provides an effective means to study the close coupling between object motion and fluid dynamics in fluid environment, but also provides a solution to other physical phenomena closely coupled with fluid.Keywords-MATLAB/Simulink; Fluent; data fusion; collaborative simulation.
Semantic Drift in Multilingual Representations

Multilingual representations have mostly been evaluated based on their performance on specific tasks. In this article, we look beyond engineering goals and analyze the relations between languages in computational representations. We introduce a methodology for comparing languages based on their organization of semantic concepts. We propose to conduct an adapted version of representational similarity analysis of a selected set of concepts in computational multilingual representations. Using this analysis method, we can reconstruct a phylogenetic tree that closely resembles those assumed by linguistic experts. These results indicate that multilingual distributional representations that are only trained on monolingual text and bilingual dictionaries preserve relations between languages without the need for any etymological information. In addition, we propose a measure to identify semantic drift between language families.We perform experiments on word-based and sentence-based multilingual models and provide both quantitative results and qualitative examples. Analyses of semantic drift in multilingual representations can serve two purposes: They can indicate unwanted characteristics of the computational models and they provide a quantitative means to study linguistic phenomena across languages.
Measuring the applicability of user-generated social tags along with expert-generated LCSH descriptors in Sociology: a heuristic study

The study attempts to compare user-generated social tags with expert-generated LCSH descriptors of one thousand sociology books. The objective is to examine if social tags can be used to enhance the accessibility of library collections. The study found that both datasets do not follow the same vocabulary. Though, the Spearmans’ rank correlation (0.89) indicates a good association between common terms in both vocabularies. The Jaccard similarity coefficient (J = 0.13, 0.14, 0.17, 0.15 and 0.16) in different word clusters proves that top frequent social tags and top frequent LCSH descriptors used by users and experts are different. The comparison with each book also reveals that 555 books (55.5%) have 50 to 100 percent matching between both vocabularies. LCSH descriptor vocabulary contains more subject terms (24) than social tag vocabulary (12) out of the top thirty frequent terms. The comparison of social tags with MARC subfields ($a, $x, $y, $z, $v) reveals that users use more or less all the subfield terms as tags but either they do not use chronological terms ($y) for tags or use different terms other than experts for chronological information. Further, comparison with each book title reveals that social tags alongside LCSH descriptors can enhance the title-based search of libraries. Moreover, the study suggests that usage of social tags will not only enhance the accessibilities of library resources under sociology but also complement to controlled vocabularies by supplementing a variety of terms other than experts.
On the Professional Competence of a Mathematics Teacher

This article aims to show the science competencies of future mathematics teachers and the factors that shape them, as well as the effects of the use of their abilities by a teacher with science competencies in the classroom. In particular, the use of mathematical models in solving problems in algebra and its importance.
The Dose Evaluation Of In Vitro and In vivo Test In Kartini Research Reactor Facility Using PHITS Code

Dose Evaluation of In Vitro and In Vivo Test In Kartini Reasearch Reactor BNCT Facility Using PHITS Code. this research is about dose analysis for in vitro and in vivo test by using PHITS program. The source of the neutron comes from a reactor that has been modified by previous researchers. In this research used mouse model. Modeling is done by modeling a mouse into a simple cylindrical geometry with a tumor modeled with the sphere geometry inside the cylinder
A New Approach for Trust Calculation in Internet of Things

IoT (internet of things) is defined as a worldwide framework for information world, which provides advanced services by connecting physical and virtual things through information technology and adoptable communication available in the evolution process. IoT is just applied to overcome the concerns related to safety. Sharing information among different devices can affect the private information of users. Therefore, a proper approach mechanism is required to prevent the risk of malicious and vulnerable failures. Multi-services IoT is vulnerable to many types of malicious attacks. Trust management provides a potential solution for safety issues of distributed networks. In this article, an algorithm is designed in order to calculate trust, which does not calculate the amount of trust for all neighbors and just calculates it for suspicious neighbors located in the list of suspicious nodes. Subsequently, energy consumption in comparison to the approach of basis article has so much decrease.
CONTENT CHARACTERISTICS OF DIGITAL CULTURE OF FUTURE PRIMARY SCHOOL TEACHERS OF ENGLISH

The mass implementation of digital technologies in all the life spheres changes the demands to future teachers’ training who are responsible for preparing the young generation to interacting, communicating, learning, and generating new knowledge in innovative digital society. The article looks into the relevant issue of defining the content characteristics of digital culture of future primary school teachers of English. The relevance of the research is proved by the analysis of a number of official documents that are regulatory foundation of conducting scientific research of education system digital transformation. The issue of developing teachers’ digital culture is a subject of studying of domestic (O. Bazeliuk, V. Bykov, L. Havrilova, M. Zhaldak, M. Leshchenko and others) and foreign scientists (С. Bassett, J. Bushati, V. B. de S. Júnior, J. E. Hasmujaj, E. Lezha, E. Nonato, A. K. F.Nunes, F. S. C. Pimentel, G. Tuxhari and others). The purpose of the article is to define the content characteristics of the concept “digital culture of future primary school teacher of English” and to theoretically substantiate its structural units. Based on the analysis of domestic and foreign researches, the digital culture is determined as a system unity of future teachers’ personal qualities that is characterised by the awareness of information needs that encourage a person to search for information, perform action for its processing and using; knowledge, skills and practical experience to implement information and communication technologies and develop electronic educational resources while conducting professional activities; rules and norms of behaviour in digital environment. It is emphasised that the structural components of digital culture include the following units: digital literacy and behaviour in digital environment. The author concludes that the development of digital culture corresponds to the requirements of the evolution of digital society, taking into account the processes of reforming and modernising of education in Ukraine with the basis on the constant teacher’s self-development. Key words: digital culture, professional teacher training, digital literacy, professional self-development, behaviour in digital environment, information and communication technologies.
Risk Perception of Migrating Legacy Systems to the Cloud

With the use of Cloud Computing as a method of delivering information infrastructure resources, the enterprise may move legacy applications to the cloud in order to achieve a variety of benefits. There are many ideas in the literature to model the essential elements of migration, all of which have been confirmed through concrete case studies. A variety of reference models have also been identified in addition to these proposals which have been developed with the goal of consolidating the various researches and attempting to extend their applicability. Based on the above, this paper chooses a reference model for migration of legacy systems to the cloud and suggests a framework for estimating the perceived risk score for each legacy system migration. The paper provides a proof of concept on the government sphere to explain the method's applicability. Keyword phrases: cloud computing, legacy networks, migration, comparison model, risk perception.
TIMING OF MESSAGES AND PERCEIVED SELF-EFFICACY FOR TREATMENT AMONG PEOPLE LIVING WITH HIV/AIDS IN HOMA BAY COUNTY, KENYA

Purpose: The purpose of this study was to ascertain the effect of timing of mobile phone text messaging (as a communication strategy employed in the text for adherence intervention) on perceived self-efficacy for treatment among people living with HIV/AIDS in Homa Bay County, Kenya.&#x0D; Methodology: Overall the study used a quasi-experimental design involving a control and an intervention group to assess the effect of the text messaging. This paper focusses on the intervention group. The key variables discussed in this paper are timing and perceived self-efficacy. The study comprised of both quantitative and qualitative data. Simple linear regression models and multi-linear regression models were used to estimate the relationship between the independent variable (timing of messages) and the dependent variable (self-efficacy). Qualitative data was analysed thematically and narratives provided under each section in verbatim.&#x0D; Findings: The intervention group of the study achieved a sample size of 77.92 per cent (n=247/317). Timing of the messages was found to have a statistically significant relationship with perceived self-efficacy as a standalone predictor variable. However when broken down into components (morning, noon and evening) none had a relationship with self-efficacy index. Similarly, when combined with other variables that were studied (type of messages, frequency and language), timing did not have a relationship with self-efficacy.&#x0D; Unique contribution to theory, practice and policy: Programs and partners involved in designing and implementing mHealth solutions need to consider and involve participants in determining communication strategies that can be effective. Timing is one of the many strategies that patients should take part in. This would ensure that interventions are highly acceptable and effective and ensure that it provides a sufficiently interesting and rewarding experience.
Financial Openness and Stability in the West African Economic and Monetary Union: A Multiple Time Scale Analysis

This paper examines the causal relationship between financial openness and financial stability in the West African Economic and Monetary Union (WAEMU) from 1993 to 2011. We use two indicators of financial openness: the de jure financial openness and the de facto financial openness. We propose a new dynamic approach to instability measurement based on wavelet filters that provide a measure of financial instability at different time scales. Then, we apply the Feasible Generalizable Least-Squares (FGLS) model to study the panel causality at each time scale. The results show a causal relationship between financial openness and financial stability. However, the nature of the causality depends on the business cycle, the nature of financial instability and the financial openness indicator. Therefore, a more appropriate monetary policy and effective financial inclusion, exchange rate and banking policies could address the negative effects of financial openness on financial stability.
Method for Visual Video Defects Detection using Machine Learning

The main problem to be solved by this research is the imperfection of the video testing process.Nowadays this process involves mainly manual testing, which is inefficient due to the high probability of human errors, significant time, and material costs.In order to improve this process, we have created a convolutional neural network that can detect defects in video frames with high probability.We have also built a prototype of a software system that can automatically detect defects in video using the created and trained convolutional neural network.
Secured Storage Path Using Cryptographic Virtual Mapping for Cloud Applications

Cloud computing can be seen as a working model in an environment that provides cloud users with access to virtualized and configurable computing resources, which can be easily specified as a shared pool of services from the cloud service provider's paid to use applications. The cloud storage path service has gained greater appeal due to the amazing growth of digital data. Cloud users can be relieved from the local data storage path and maintenance burden using cloud storage path services. It has difficulty maintaining the secure storage path because of many security challenges of that system like the disruption of services, loss of privacy, etc., on the cloud's data storage path in the previous system. To overcome this drawback, this disclosure provides the proposed Cryptographic Virtual Mapping(CVM) system readable data for secure storage page mapping in a virtual mapping environment in cloud computing. Asymmetric Key Encryption Algorithm can be used for the encryption of massive data. This encryption process is less computationally expensive and consumes minimum time for performing the encryption and decryption of the cloud storage data. This method determines the propagation of data verification based cryptographic input data to decide the input key. The address is under a suspected control of a user of interest. The secure storage for dynamically changing data stored in the cloud is achieved using a well-known data structure called a linked list. This linked list is generated and maintained by the data owner. Using this solution, operations such as inserting, modifying, appending and deleting dynamic data are possible without downloading the entire data from the cloud server. The experimental results prove that the Cryptographic Virtual Mapping method has the highest probability of detecting damage or deformation of dynamically changing data.
Semantic feature augmentation for fine-grained visual categorization with few-sample training.

Small data challenges have emerged in many learning problems, since the success of deep neural networks often relies on the availability of a huge number of labeled data that is expensive to collect. We explore a highly challenging task, few-sample training, which uses a small number of labeled images of each category and corresponding textual descriptions to train a model for fine-grained visual categorization. In order to tackle overfitting caused by small data, in this paper, we propose two novel feature augmentation approaches, Semantic Gate Feature Augmentation (SGFA) and Semantic Boundary Feature Augmentation (SBFA). Instead of generating a new image instance, we propose to directly synthesize instance features by leveraging semantic information, and its main novelties are: (1) The SGFA method is proposed to reduce the overfitting of small data by adding random noise to different regions of the image's feature maps through a gating mechanism. (2) The SBFA approach is proposed to optimize the decision boundary of the classifier. Technically, the decision boundary of the image feature is estimated through the assistance of semantic information, and then feature augmentation is performed by sampling in this region. Experiments in fine-grained visual categorization benchmark demonstrate that our proposed approach can significantly improve the categorization performance.
Weakly Supervised Instance Attention for Multisource Fine-Grained Object Recognition

Multisource image analysis that leverages complementary spectral, spatial,and structural information benefits fine-grained object recognition that aimsto classify an object into one of many similar subcategories. However, formultisource tasks that involve relatively small objects, even the smallestregistration errors can introduce high uncertainty in the classificationprocess. We approach this problem from a weakly supervised learning perspectivein which the input images correspond to larger neighborhoods around theexpected object locations where an object with a given class label is presentin the neighborhood without any knowledge of its exact location. The proposedmethod uses a single-source deep instance attention model with parallelbranches for joint localization and classification of objects, and extends thismodel into a multisource setting where a reference source that is assumed tohave no location uncertainty is used to aid the fusion of multiple sources infour different levels: probability level, logit level, feature level, and pixellevel. We show that all levels of fusion provide higher accuracies compared tothe state-of-the-art, with the best performing method of feature-level fusionresulting in 53% accuracy for the recognition of 40 different types of trees,corresponding to an improvement of 5.7% over the best performing baseline whenRGB, multispectral, and LiDAR data are used. We also provide an in-depthcomparison by evaluating each model at various parameter complexity settings,where the increased model capacity results in a further improvement of 6.3%over the default capacity setting.
Gadget-Based Digital Literacy in Learning Writing Skills for Elementary School Students

Technological developments continue to influence all aspects of life in the world including education. Realizing this, the Ministry of Education and Culture designed the digital literacy movement as a tool to increase the ability to use digital technology in education, especially for teachers and students. Digital literacy can also be used as a tool to improve students' writing skills. However, students are less interested in learning to write. The main difficulty in writing is the inability of students to put their ideas or ideas into writing, this is natural because students rarely practice their writing skills directly. Teachers can apply gadget-based digital literacy in learning writing skills. This study aims to describe gadget-based digital literacy in learning writing skills. Through the literature study method, researchers found that the importance of digital literacy competency learning programs for students has a positive impact on understanding and skills in using digital media. Gadget-based digital literacy results in creative and innovative learning. The use of gadget-based digital literacy can improve students' writing skills.
Human activity recognition system

Understanding the activities of human from videos is demanding task in Computer Vision. Identifying the actions being accomplished by the human in the video sequence automatically and tagging their actions is the prime functionality of intelligent video systems. The goal of activity recognition is to identify the actions and objectives of one or more objects from a series of examination on the action of object and their environmental condition. The major applications of Human Activity Recognition vary from Content-based Video Analytics, Robotics, Human-Computer Interaction, Human fall detection, Ambient Intelligence, Visual Surveillance, Video Indexing etc. The Experimental Evaluation of various papers are observed efficiently with the various performance metrics like Precision, Recall, and Accuracy.