Reviewerly/exHarmony huggingface dataset:
The Influence of Interpersonal Relations on the Formation of Intercultural Competence of Future Specialists of Socionomic Professions

The article provides a theoretical analysis of the problem of interpersonal relationships and interactions, which are considered in the context of the study as factors influencing the process of formation of intercultural competence of future professionals of socionomic professions. The authors conclude that the effectiveness of intercultural education directly depends not only on the formalized methods and tools used in the educational process in higher education, but also on psychological factors, motivation and encouragement, activity and belief of students in the need for intercultural competence and the formation of intercultural competence as important components of future professional activity, as well as the psychological components that accompany the implementation of the system of formation of intercultural competence, in particular such as interpersonal relationships and interactions; psychological climate, psychological atmosphere, general emotional state of future specialists of socionomic professions. Complementing the content of intercultural education with subjective interpersonal relationships between teachers and students, as well as with representatives of different ethnocultural communities and groups, allows us to characterize them as important factors in the process of forming intercultural competencies. Psychological attitude to intercultural education determines the motivation and activity of students, which involves internal approval of the need for this education, the formation of attitudes towards it as a professional necessity. Accordingly, learning activity is manifested in the form of psychological involvement in the process of intercultural education.
Interdisciplinary Integration as the Basis of a Complex Approach to the Doctors of Philosophy Training Program

The article is devoted to the analysis of interdisciplinary integration as a foundation for improving the effectiveness of scientific, theoretical and practical training of a new generation of teachers for professional and higher education. The key terms of the studied phenomenon – integration, integrative learning, integrative knowledge, «transferable skills» are considered. The four levels of integration possible in the learning process are described. Examples of foreign experience in the implementation of an integrated approach into the educational process in France, America, Finland, England are discussed, which can be used in the implementation of an integrated approach to the organization of the educational process in Ukrainian HEIs. The phenomenon of interdisciplinary integration is presented as a process of harmonizing the content of disciplines so that they reflect their singularity, continuity and holistic character of a professional activity, which leads to the strengthening of interdisciplinary links while maintaining theoretical and practical integrity of these disciplines. The results of implementing the integrated approach are described. As a result, future doctors of philosophy gain the ability to construct logical connections and ask research questions, find the necessary information, compare concepts and create integrative schemes for a holistic understanding of a phenomenon or a situation, transfer knowledge from one field to another and from one situation to a different one. Particular focus in the article is put on the questions of interdisciplinary integration in the system of future doctors of philosophy training.
Personas to understand occupant behavior and energy usage

Advanced occupant modelling facilitates understanding occupant behaviour by providing dynamic behaviour hypotheses. Most advanced models do not consider occupants' complex nature like adaptive knowledge, attitudes, available control, interactive behaviour, and available technology. This paper proposes a personabased approach to capture various occupant characteristics for building design, simulation, and automation. We demonstrate a method to integrate the personas in building performance simulations for thermal preference in an academic office context. The case study illustrates the ease and flexibility in applying personas for different use case scenarios for decision-making. The energy usage is 10% higher or 12% lower than the standard assumptions based on the personas revealing occupants' do matter in a design.
Data imputation with a diagnostic purpose in building: Application to an office setting

In a building system, diagnoses are calculated from symptoms resulting from a set of tests; each defined by a bunch of data, behavioral constraints and a set of possible explanations in case of anomaly. To make a test, data are required from different sensors. However, missing data is a common issue in buildings. Because a detection test relies on several variables and that all the data should be available along a given time horizon, performing tests could become an issue. In the literature, many techniques have been proposed to impute missing data. However, detection tests could detect non-existing anomalies with usual types of imputation: it is indeed necessary that the imputed data do not generate alarms. It is all the more important for diagnosis from first principle approach where detection of anomalies has a strong impact on the diagnosis. This paper discusses the issue of imputation with diagnostic purposes i.e generating data satisfying test constraints. The proposed imputation algorithm is based on a genetic algorithm which search iteratively for imputed data satisfying behavioral constraints while preserving as much as possible known statistical properties. The efficiency of the method is evaluated on measurements obtained from a real application: an office at G-SCOP laboratory with a large number of sensors and missing data. Key-words: imputation, missing values, genetic algorithm, building system, diagnosis, false alarms.
ANALYSIS OF FLAME RETARDANT POLYPROPYLENE FOR PLASTIC INJECTION MOLDING USING BROMINATED AROMATIC COMPOUND

Flame Retardant (FR) is a type of thermoplastic material that is resistant to fire. Application of FR on various types of plastic resins such as polypropylene (PP), Acrylonitrile butadiene styrene (ABS), and other types of plastic resins. This study discusses the analysis of Brominated Aromatic Compound as a mixture of Polypropylene to produce PP-FR types for plastic injection molding with the material formulation method to perform a flame retardant test on the results of the specimens that have been made. This study shows that PP material and Acrylonitrile butadiene styrene can bind scanning microscopes with ×15,000 and ×30,000 zoom. The extrusion process results did not experience cracks after going through a chamber test of -5 ◦C to 70 ◦C for 120 hours on the specimen. In addition, the results of the flame retardant test fire can die in under 2 seconds
ANALISIS KESALAHAN MAHASISWA CALON GURU MATEMATIKA DALAM MENYELESAIKAN PERSOALAN NUMERASI

The purpose of this study was to describe the errors of prospective mathematics teacher students in solving numeracy problems. This research is a qualitative descriptive research. The subjects in this study were prospective mathematics teacher students in the mathematics study program at Mahaputra Muhammad Yamin University, totaling 5 people. The conclusion of this study is the errors experienced by students when solving numeracy problems, namely errors in understanding questions, weakness in process skills, errors in process transformation, and errors in completion.
Differences in Psychological Well-Being and Commitment to Volunteer Activities According to the General Characteristics of Volunteers

The purpose of this study is to identify differences in psychological well-being and commitment to volunteer activities according to the general characteristics of volunteers.The study was conducted on 190 volunteers in Bucheon, Gyeonggi Province.Frequency analysis, reliability analysis, correlation analysis, t-test and one-way ANOVA were performed using the SPSS program.The study found that firstly, the psychological well-being of volunteers according to their gender was of no mean difference, and that the commitment of volunteer activities was of significant difference.Second, psychological well-being by age was found to have no significant differences among groups, volunteer activity was found to have the highest mean among those in their 40s, and the mean difference between groups was significant.Their, it was analyzed that the average difference in the loyal to volunteer activities according to the employment status was significant among groups.Fourth, the difference in the commitment to volunteer activities according to volunteer experience was found to have significant mean differences between groups.The results of this study may be used to enhance abilities of volunteers.
ACCURACY, READABILITY AND ACCEPTABILITY IN THE TRANSLATION OF ANDROID XIAOMI REDMI NOTE 4

Android translation(s) were translated by multiple people/agencies during multiple period of times, thus they are very prone to accuracy, readability and acceptability errors. Based on that reason, I conducted this research to (1) analyze and find out the accuracy of the translation in Xiaomi Redmi Note 4 smartphone, (2) readability of the translation of the smartphone, and (3) the acceptability of the translation. The result of this study showed that all of the accuracy, readability and acceptability of the original translation showed worse results than the modified translation. For accuracy, Goff-Kfouriâ€™s and Nababanâ€™s rubric both showed better result for the modified translation. For readability by the translators, the average of original translation got 2.3 (negative) and modified got 3.8 (positive); whereas the end-users rated 2.4 (negative) and 3.8 (positive) respectively. For acceptability, the average of original translation by the translators was rated 2.6 (negative) and the modified translation got 3.7 (barely positive); and by the end users, the rates were 2.7 (negative) and 3.7 (positive).
PLASMA APHERESIS PROCEDURE

The present study investigates to prepare single donor Plasma Apheresis product in the blood center with the help of Fresenius Cell Separator for use in patientwho require coagulation factors, covid patients, dengue patients etc. Apheresis is a medical procedure that involves removing whole blood from a donor or patient and separating the blood into individual components so that one particular component can be removed.Apheresis is a medical procedure that involves removing whole blood from a donor or patient and separating the blood into individual components so that one particular component can be removed. The remaining blood components then are re-infused back into the bloodstream of the patient or donor. Apheresis is also called pheresis or hemapheresis. The terminology used may also reflect the component of blood that is being removed, such as: • Plasma (plasmapheresis) • Platelets (plateletpheresis) • Leukocytes (leukapheresis or leukopheresis) • Lymphocytes (lymphopheresis or lymphapheresis) • Red blood cells (erythropheresis) Total plasma exchange (removal of plasma and replacement with fresh frozen plasma) can also be performed using the apheresis procedure. It is also used for the collection of stem cells from the peripheral blood. KEYWORDS: Plasma Apheresis, medical procedure, hemapheresis, Leukocytes
Performance Simulation of Identification System Based on Improved Neural Network Algorithm

After decades of development, neural network theory has made considerable progress in many research fields such as pattern recognition, automatic control, signal processing, decision support, and artificial intelligence. This article discusses the application of neural networks in pattern recognition and system recognition and proposes several new methods for recognizing system models and recognizing model parameters. In order to achieve high-precision control of smart structure actuators, a robust model must first be created. For various modeling tasks, many scientists have done a good job and proposed different modeling methods. There are three main ways to create a system model: one is a physical model based on the mechanism of the material itself, the other is an operator model based on experimental phenomena, and the third is an intelligent model based on computer intelligence. The problem of the recognition system stems from the fact that with the development of science and technology, the research methods of various disciplines have been further quantified. In industrial practice and scientific experiments, the purpose of observing and calculating the quantitative identification of complex objects that need to be studied is usual. According to its inherent laws, it is necessary to establish a mathematical model of the research object in order to make decisions such as analysis, design, prediction, and control. This article uses the neural network model to study the best improvement method of the dynamic process. The research results of this article represent the theoretical basis of future scientific research to a certain extent and have important research value.
Elliptic Curve Cryptography Based Homomorphic End-to-End Encryption Security in Cloud Computing

Cloud computing is turning into the principal computing model in the future because of its benefits, for example, high asset use rate and save significant expense of execution. The existing algorithms for security issues in cloud computing are basically advanced version of cryptography. Mainly cloud computing algorithm are concerning about data security and privacy preserving of user. To protect the privacy of data owner and data user the cryptographic data are shared and stored in cloud storage by applying HE-homomorphic encryption. According to environment of HE, this paper proposed a new hybrid algorithm by combining the two algorithms of cryptography i.e., AES and ECC with the concept of splitting algorithm. By the implementation of this hybrid algorithm, we will split any file into binary version and then after processing the cryptography technique. This hybrid algorithm provided higher protection against attacks over cloud storage and data sharing.
A Modified Moth-Flame Optimization Algorithm for Image Segmentation

As a renowned swarm-based approach, Moth-Flame Optimization (MFO) has been developed to address global optimization difficulties. It has been used to address a variety of advancement difficulties since its introduction. However, MFO may have difficulties in global optimal point and also suffer from slow convergence pace. In this paper, a modified MFO (m-MFO) is designed to address these issues by introducing a new parameter C and a weight W. The parameter C is utilized to boost exploration, whereas the weight W aids the algorithm in local search. The suggested approach is applied to the solution of 20 benchmark functions from both the unimodal and multimodal categories. Finally, the methodology is used to image segmentation using a multilayer thresholding approach. The comparison of the evaluated findings with alternative metaheuristic algorithms and convergence studies shows that the proposed m-MFO approach outperforms the basic MFO approach and several other methods.
Determination of permeability from well logging data based on the petrophysical invariant

The reliability of determining the permeability and porosity properties of oil and gas reservoirs depends on the informative value of the sets of petrophysical and geophysical well surveys and the efficiency of the methods for interpreting the obtained data. In order to determine the permeability from well logging data without using a correlation between permeability and porosity, the paper proposes the Kozeny–Carman equation, transformed on the basis of a petrophysical invariant (normalized effective porosity). The equation makes it possible to take into account the heterogeneity of the pore space of the intergranular reservoir with an appropriate petrophysical setting for the content of the main granulometric fractions.
Design of Knowledgebase for EES using Object - Relational Data Modeling

This work is focused on designing a knowledgebase for an Expert Education System (EES) that will help the learners to know where, what, how, and when is the required knowledge available in the knowledgebase.A three-layered architecture of a Knowledgebase is proposed, and have given some basic definitions for the concepts, knowledge units, and persistent objects.Definitions are given in FOL, frames, DL, and OR data models.Integrating these into a KB will serve as a backend for the EES.
SISTEM INFORMASI DESA SIALANG PANJANG KECAMATAN TEMBILAHAN HULU BERBASIS WEB

Until now, the Sialang Panjang Village Office does not yet have a special system to assist office staff in providing services to the community. However, there are several reasons why the Sialang Panjang Village Office wants a village system. These reasons include: they do not have a special program that is integrated into the database in terms of community population administration, besides the need for information for the local village community and the wider community is very large, many village communities do not know about village potential, village statistics, and the latest information. village. To overcome this, we need a software development process in the form of a Sialang Panjang Village Information System. The processes carried out are requirements analysis, system design, system implementation, system testing and system maintenance. The development method used is the waterfall method, while the analytical method used is the pieces method which can be a reference in building an information system for the village of Silang Panjang. UML (Unified Modeling Language) as a system modeling language, PHP (Hypertext Preprocessor) as a programming language and MySQL database. Then for system testing using black-box testing, white-box testing and questionnaires. With this village information system, it will be able to assist village office staff in providing services to the community and make it easier for the community to take care of population administration and obtain information.&#x0D; Keywords: Web-Based Information System, Village Service, Sialang Panjang Village
Petrogenesis and Tectonic Setting of the Gold-Bearing Magmatic Rocks of the North-Western Melfi Massif, Central Chad

This paper presents petrographic and geochemical data on magmatic rocks of the north-western Melfi massif (part of the Gera Massif at the center of Chad) in the Adamawa-Yadé domain. The study area consists of syenite and granite, all crosscut by minor dykes and quartz veins. Syenite and granite show porphyritic texture and are dominated by K-feldspar and plagioclase phenocrysts, biotite, a variable proportion of quartz, and often few amphiboles. These rocks are characterized by low Mg#, Ni and Co, high K2O, Na2O, LREE/HREE ratio, I-type geochemistry as well as positive Eu anomaly, suggesting an origin from partial melting of crustal rocks (here garnet-amphibolite) and metasomatized mantle-derived component with the input of sediments. The compositional evolution from syenites to granite raises the fractional crystallization process in their petrogenesis and involves the fractionation of amphibole, biotite, plagioclase, apatite, magnetite, and ilmenite. Studied samples are affected by the post-magmatic hydrothermal alteration with an assemblage made of epidote, biotite, sericite, and opaques minerals. In addition, they are characterized by considerable gold concentration (Au = 0.6-3.8 ppm) suggesting that the north-western part of the Melfi massif in the center of Chad is a preferential site of gold mineralization. The K-rich calc-alkaline to shoshonitic geochemistry and the pronounced Nb, Ta, and Ti negative anomalies of these rocks, combined with their high Nb/Ta (7.55-32.10), La/Nb (1.80-11.73), and La/Ta (21.53-376.60) ratios but low Rb (57.60-138.30 ppm) indicate that they are subduction-related or arc-related magmas belonging to the Great Central Gondwana Arc (GCGA) formed further to east-directed subduction direction.
intelligent automated monitoring system using video surveillance based recognition

The current pandemic situation makes it necessary to work in a contactless environment where human intervention is minimalized at most. Video surveillance is an important security asset for monitoring purposes at banks, department stores, highways, and crowded public places. With improved technology and a growing population, surveillance is becoming a key area in research. The best utilization of technology for surveillance is the focus area today. In recent times, object detection has come to the frontline as an important application in the field of Deep Learning. Unlike traditional methods, object detection in deep learning is characterized by its ability to learn features and depict the same. The proposed system aims at creating a platform that reduces/eliminates human intervention for monitoring purposes by using a CCTV camera assisted automated monitoring system. There is scope for automation, which would perform object detection and automatically open the door/gate when the same has been recognized. Here, CNN models are to be used for real-time object detection via the CCTV camera.
DETERMINASI MOTIVASI HIERARKI MASLOW DALAM MEMPENGARUHI KINERJA DOSEN

Fulfilling the performance of the tri dharma is not easy, especially in the field of research and community service. Lecturers are not only required to be scientific, but also to contribute energy, time and costs. Therefore, there needs to be a fulfillment of work spirit, so that lecturers always have reasons/motives in achieving the performance of the tri dharma. In fact, this research is to see the possibility of strengthening the performance of lecturers during the implementation of the tri dharma through the five motivational factors initiated by Maslow. In testing the phenomenon, a quantitative method is used, in order to obtain statistical conclusions in the form of estimated values. Furthermore, regression statistics were used as an analytical instrument. The research was conducted at Pamulang University with lecturers as the unit of analysis. The sampling technique uses simple randomness, where research questionnaires are distributed directly to respondents via google form. The results show that, Maslow's five motivational factors have a real/significant contribution to the achievement of performance. This explains that the fulfillment of various sources of work motivation can foster feelings of enthusiasm to achieve better performance. In fact, the most interesting thing from this finding is that lecturer motivation has unique characteristics, because the self-actualization motivation factor is the most dominant variable in the fulfillment of the tri dharma performance.