Reviewerly/exHarmony huggingface dataset:
Performance comparison and impact of weather conditions on different photovoltaic modules in two different cities

&lt;span&gt;This work is based on a comparative study of the impact of meteorological conditions as well as the assessment of the production performance of two identical photovoltaic stations installed in two Moroccan cities, the stations are based on three different technologies. The measures of one year of operation from January 2017 to December 2017 were evaluated. The annual average performance ratios were found to be 82.42%, 79.99% and 78.74% in Beni Mellal, and 85.29%, 84.61% and 70.41% in El Jadida for the polycrystalline (pc-Si), monocrystalline (mc-Si), and amorphous (a-Si) respectively. The photovoltaic efficiency was calculated at 12.24%, 11.89%, and 11.71% in Beni Mellal; and 12.59%, 12.49%, and 10.42% in El Jadida by the same order. Statistical analysis was carried out to establish the correlation with photovoltaic (PV) production showed that after irradiation, the temperature is the most influencing meteorological factor for PV production, revealing a degradation in the performance ratio of 2.5%, 2%, and 1% for each increase of 8 °C in temperature for monocrystalline, polycrystalline and amorphous technologies respectively at Beni Mellal. While at El Jadida the reduction in the performance ratio is evaluated by 5.5%, 5.2%, and 3% for each 8 °C increase in temperature for the same order.&lt;/span&gt;
Image Caption and Medical Report Generation Based on Deep Learning: a Review and Algorithm Analysis

Algorithms based on deep learning have been widely applied in automatic image captioning and medical report generation. As one of the most important applications in image captioning, medical report generation has been proved to be essential and effective in smart health and diagnosing. Due to the contraction of rapidly increasing need of radiology diagnosis and lack of report writing experience in most medical institutes, it is vital to work out an automatic medical report generation method. However, as the researchers followed the timeline of paper archives of image captioning, it comes out that there still exist a few problems in generating medical reports, which leads to the gap between the algorithm and medical practice. This study will (1) be a concise review of image captioning methods and medical report generation; (2) analyze the reasons of the phenomenon mentioned above with a case study; (3) give a forecast of medical report generation works.
How to Avoid the Pseudo Environment of Users’ Knowledge Contribution?—Taking the Online Question and Answer Platform as an Example

Information dissemination is based on human will, and it is purposeful and artificial.There is a certain subjectivity in the knowledge contribution of users of online question-and-answer platform, which builds a pseudo environment.
Mining the Frequent Patterns of Named Entities for Long Document Classification

Nowadays, a large amount of information is stored as text, and numerous text mining techniques have been developed for various applications, such as event detection, news topic classification, public opinion detection, and sentiment analysis. Although significant progress has been achieved for short text classification, document-level text classification requires further exploration. Long documents always contain irrelevant noisy information that shelters the prominence of indicative features, limiting the interpretability of classification results. To alleviate this problem, a model called MIPELD (mining the frequent pattern of a named entity for long document classification) for long document classification is demonstrated, which mines the frequent patterns of named entities as features. Discovered patterns allow semantic generalization among documents and provide clues for verifying the results. Experiments on several datasets resulted in good accuracy and marco-F1 values, meeting the requirements for practical application. Further analysis validated the effectiveness of MIPELD in mining interpretable information in text classification.
Evaluasi Usability Aplikasi EDMODO dengan SUS dan Thematic Analysis

The Covid pandemic that occurred in 2020 prompted the Indonesian government to issue policies related to distance education (PJJ), to avoid the spread of disease. This sudden appeal caused tertiary institutions and students who were not ready to be ready and accustomed to the situation. To do PJJ at X University, which is located in Jambi province, use EDMODO as an application to do PJJ. The use of EDMODO as a PJJ media has been going on for almost 2 semesters, but the effectiveness of teaching via EDMODO has not been studied for its success, so an analysis is needed related to the application of EDMODO as a PJJ application. The author uses a system usability scale to analyze the educational usability level of this application. From the calculation results, the average value of SUS is 71,2. However, there is a possibility of decreasing educational usability in this application. So, it is recommended that this application be developed again.
Detection of Shot Transition in Sports Video Based on Associative Memory Neural Network

Users must quickly and effectively classify, browse, and retrieve videos due to the explosive growth of video data. A variety of shots make up the video data stream. The most important technology in video retrieval is shot detection, which can fundamentally solve many problems, resulting in improved detection effects and even directly affecting video retrieval performance. This paper investigates the shot transition detection algorithm in digital video live broadcasts based on sporting events. To solve the problem of shot transition detection using a single training sample, an AMNN (Associative Memory Neural Network) model with online learning ability is proposed. Experiments on a large football video data set show that this algorithm detects shear and gradual change better than existing algorithms and meets the application requirements of sports video retrieval in most cases.
Pedagogical potential of the success situation in the teacher professional and creative self-realization

Introduction and problem statement. The article combines scientific and pedagogical ideas on the success situation as a way to organize the creative activity of the teacher's personality and a form of his professional self-realization. Nowadays, self-realization as a process of revealing intentions and talents of an individual takes place in conditions of fierce competition and high demands of business, labor market. Therefore, besides the main professional profile, the teacher needs to master many related professional and personal competencies, hard and soft skills, correlating desires, goals and opportunities. Methodology. As the scientific literature analysis result, the author deduces three meaningful interpretations of success as: 1) an activity characteristics; 2) an experience of joy; 3) a motive; and does not reduce it to the attributes of material prosperity and other quantitative indicators. Here, success is a prerequisite for personal development and creative self-realization. Based on the above, the success situation is stated as the leading condition for creative self-realization. Methods. The paper presents the author's classification of success situations by types of joy in educational and pedagogical activity. At teaching creative professions, the success situation can be developed in a set of techniques: removing clamps (through exercises to restore breathing); exercises for gradually increasing difficulties; accounting the physical condition and emotional well-being of a dancer/actor; evaluating not the result, but the physical effort and emotional costs to achieve a successful result; optimistic attitude for the future. Results. The article emphasizes that the success achievement contains both the external manifestations of social prestige and material wealth, and the individual internal reserves. The study shows that success, in addition to the activity result and its evaluation, contains a motive, meaning, purpose and means to achieve it; which are accompanied with feelings of joy by those who study, and pedagogical techniques to create a situation of success serve as the basis for the teacher professional competence and creative self-realization.
A Roadmap for Boosting Model Generalizability for Predicting Hospital Encounters for Asthma

In the United States, ~9% of people have asthma. Each year, asthma incurs high health care cost and many hospital encounters covering 1.8 million emergency room visits and 439,000 hospitalizations. A small percentage of patients with asthma use most health care resources. To improve outcomes and cut resource use, many health care systems use predictive models to prospectively find high-risk patients and enroll them in care management for preventive care. For maximal benefit from costly care management with limited service capacity, only patients at the highest risk should be enrolled. However, prior models built by others miss >50% of true highest-risk patients and mislabel many low-risk patients as high risk, leading to suboptimal care and wasted resources. To address this issue, 3 site-specific models were recently built to predict hospital encounters for asthma, gaining up to >11% better performance. However, these models do not generalize well across sites and patient subgroups, creating 2 gaps before translating these models into clinical use. This paper points out these 2 gaps and outlines 2 corresponding solutions: (1) a new machine learning technique to create cross-site generalizable predictive models to accurately find high-risk patients and (2) a new machine learning technique to automatically raise model performance for poorly performing subgroups while maintaining model performance on other subgroups. This gives a roadmap for future research.
The Concept of Using Educational Computer Games in Teaching Legal Disciplines: A View from Russia

The use of educational computer games in the context of the coronavirus pandemic is becoming increasingly popular in the educational process when studying a variety of disciplines. And if practical steps have been taken in this direction in technical, pedagogical, and some other sciences, then there is a doctrinal and practical gap in the teaching of legal disciplines that needs to be filled. The purpose of the study is to argue the prospects for the use of educational computer games at law faculties, which makes it possible to more effectively assess students’ knowledge, as well as increase their motivation to actively participate in the educational process. In the course of the study, methodology involved the theoretical and practical experience of developing educational computer games in various academic disciplines was summarized, the scientific literature and the existing practice of their use were analyzed, and the possible effect of introducing educational computer games into the educational process at law faculties after the development and implementation of such games in practice, including the first-generation educational computer game developed by the authors, was modeled. The research findings indicate formulation of a doctrinal concept of the use of educational computer games, identifies three of their generations, and shows the features of the development and application of each of them, including the author’s experience in developing a training computer game by right of the first generation. The authors analyzed the technical problems associated with the development of educational computer games and suggested ways to solve them. The authors’ proposals can be used by universities in any country to interact with game design studios to develop educational games.
Websites of libraries of SB RAS scientific institutions: lines of optimization

The purpose of the article is to present recommendations for optimizing websites / pages of libraries of scientific institutions of the Siberian Branch of the Russian Academy of Sciences (SB RAS). Recommendations have been formulated based on the results of the content analysis of websites of SB RAS scientific institutions’ libraries, carried out in 2021. The tool of the analysis was the content assessment checklist developed specifically for this study, based on the literature review and the author’s own experience. The checklist contains 50 questions divided into five sections: site information, web page design and functions, content and web services.Websites / pages of 44 libraries of scientific-research institutions of Barnaul, Biysk, Irkutsk, Kemerovo, Krasnoyarsk, Novosibirsk, Omsk, Tomsk, Ulan-Ude, Yakutsk were studied; also an online survey was conducted of the staff of SB RAS scientific-research institutions’ libraries, concerning management and maintenance of websites / pages.As a result of the analysis, it has been revealed that not all scientific institutions have links to their libraries on the main pages, libraries are presented mainly in the form of the webpage of the institute’s website, are not very well structured and organized. As a rule library sites do not use adaptive design, navigation tools are not everywhere available, users do not receive comprehensive information about information resources and library services, and virtual services are not developed.Evaluation of the web content has made it possible to identify trends and problems in the state of scientific institutions libraries’ web sites.
NATURE- AND BIO-INSPIRED OPTIMIZATION: THE GOOD, THE BAD, THE UGLY AND THE HOPEFUL

Nowadays, optimization has become an important issue for industrial systems and product development. From an engineering perspective, optimization implies adjusting or fine tuning the design of the system considering performance factors. Unfortunately, in many real-world problems there are no mathematical techniques capable of solving them within reasonable times. Consequently, optimization is done manually in many practical cases. Over the last decades many meta-heuristic optimization techniques have been inspired by natural phenomena and behavioral patterns observed in animals. As such, nature- and bio-inspired optimization allows optimizing a problem without requiring special knowledge about it, but only the fitness function to optimize and mechanisms to create possible solutions. Bio-inspired optimization techniques generate new candidate solutions intelligently in search for the best one for the problem. Although they do not guarantee to obtain the optimum solution, they can autonomously achieve good results within reasonable time, having been successfully used in manifold real-world problems. There are so many bio-inspired optimization proposals in the literature that it could be overwhelming to choose one. This research area is expanding every year, with more bio-inspired techniques, and tools devised to use them in real applications. However, not all bio-inspired solvers are interesting. Many proposals are mathematically similar to well-established meta-heuristics, so they could render equally similar results. Furthermore, the performance of many of them has not been rigorously confirmed by experimentation. This article elaborates on recent applications (the good), the lack of innovation of new metaphor-based algorithms (the bad), poor methodological practices (the ugly) and the exciting future of opportunities and challenges (the hopeful) of this research area. Nature- and bio-inspired optimization can be great alternatives to optimize complex processes in many real-world industrial problems. But above all, the use of bio-inspired solvers requires a global understanding on the current status of this area. Providing such an overarching view to the audience from a multi-faceted perspective is the ultimate purpose of this manuscript. Keywords: Bio-inspired optimization, Nature-inspired optimization, Optimization, Evolutionary Algorithm
Human Sentiment Analysis on Social Media through Naïve Bayes Classifier

Deciphering feelings and thoughts from a succession of words is one of the most complex and demanding undertakings.Recognizing sentiments and emotions is one of the most effective ways of expressing feelings and sentiments by writing text.It requires more interest from researchers in advancement than face or voice-based systems.Text based emotion analysis has sparked the attention of many individual researchers to continue their research into distinguishing unique emotions from natural language.The emotion recognition from text field is used in a range of applications, such as recommendation systems, cultural content services that recommend music based on a user's current emotional state, mood tracking, emotion retrieval from suicide notes, capturing emotions in multimedia tagging, detecting objectionable phrases in chats, and so on.In today's informationrich culture, smart sociotechnical systems are gaining traction, with various technologies being employed to gather data from such systems and analyze that data for useful insights into our daily activities.Recent advancements in health monitoring and communications technologies, among other noteworthy achievements, have helped sentiment identification.The trend in artificial intelligence (AI) research in recent years has been to incorporate AI techniques into daily living objects.It is well understood that AI systems will be beneficial to the majority of humans.Emotions are a collection of mental states brought on by a variety of feelings, ideas, and behaviors.People continually communicate emotional cues during the communication process; emotional awareness is vital in human interaction and in many facets of daily life.The seven emotional states (disgust, neutral, happy, sad, angry, astonished, and bored) are extensively described in this study in order to incorporate user text emotions through social media platforms using Correlation based Naive Bayes Classifier and achieve an accuracy rate of 99.99%.
Data Processing Model for Compliance with International Medical Research Data Processing Rules

In addition to traditional clinical research, advances in information communication technologies facilitates new medical research using internet of things devices and other cutting-edge technologies. Such medical research also simplifies the collection of data on research subjects in their daily lives internationally. In this context, medical research is increasingly required to comply with rules protecting patients' personal data. This study proposes a model to enable researchers and other stakeholders including ethics committees in such international medical research to easily verify whether the planned processing of patient data complies with relevant legal and ethical rules. The model proposed in this study consists of (1) how patient information is processed, (2) the rules that are relevant to the processing, and (3) the analysis of whether the processing complies with the rules. This study suggests that the model should describe the aspects of data processing that are subject to many rules, such as the location of the processing, categories of data, purposes of the processing, and the storage period. Thus, using the information described in the model as a guide, stakeholders can determine which national and international legal/ethical rules apply to the planned processing. Then, they can use the model to verify and document whether the processing complies with the specific regulatory rules. The use of the model in this study enables stakeholders in medical research to comply with the rules related to patient data more effectively than without using the model.
Hierarchical Gaussian Markov Random Field for Image Denoising

In this study, Bayesian image denoising, in which the prior distribution is assumed to be a Gaussian Markov random field (GMRF), is considered. Recently, an effective algorithm for Bayesian image denoising with a standard GMRF prior has been proposed, which can help implement the overall procedure and optimize its parameters in O(n)-time, where n is the size of the image. A new GMRF-type prior, referred to as a hierarchical GMRF (HGMRF) prior, is proposed, which is obtained by applying a hierarchical Bayesian approach to the standard GMRF prior; in addition, an effective denoising algorithm based on the HGMRF prior is proposed. The proposed HGMRF method can help implement the overall procedure and optimize its parameters in O(n)-time, as well as the previous GMRF method. The restoration quality of the proposed method is found to be significantly higher than that of the previous GMRF method as well as that of a non-local means filter in several cases. Furthermore, numerical evidence implies that the proposed HGMRF prior is more suitable for the image prior than the standard GMRF prior.
Patentability of Solutions in the Field of Bioprint Technologies: A Comparative Law Aspect

The paper is devoted to the issues of advisability of introducing amendments to the civil legislation in connection with the development of additive technologies or the possibility of effective application of the existing rules of law to the regulation of «innovative» civil relations. Digitization of objects of the material world associated with the creation of their digital prototypes constitutes a revolutionary element of 3D printing technology. A three-dimensional digital model (CAD file) can be easily modified, distributed and embodied in the form of a physical object by printing it on a 3D printer. This gives rise to new risks of infringement of exclusive rights to objects of patent law. In a foreign doctrine, a discussion has started regarding the possibility of qualifying the creation and circulation of digital models of patented products (inventions) as a direct infringement or indirect infringement of exclusive rights. The paper concluded that Russian patent law was not ready for the challenge generated by the development of 3D printing technology, since it was not aware of the concept of indirect infringement of the exclusive right. In Russian law enforcement practice, the concept of direct patent infringement is interpreted in a restrictive manner. The question of admissibility of patenting technical solutions in the field of bioprinting has been studied. It is concluded that in Russian law there are no fundamental obstacles to patenting technical solutions in the field of bioprinting technologies. Russian legislation provides for the possibility of patenting «natural products», as well as methods and means of treatment, which distinguishes the Russian approach from the American or European one. If the risk of genetic instability of pluripotent cells is leveled, the technology for creating bioprinted human organs will comply with the requirements of civil law. In particular, it will meet the requirements for the compliance of patented technical solutions with the public interest, the principles of humanity and morality.
Application of Improved ViBe Algorithm in Vehicle Detection

Background modeling technology, as the mainstream algorithm of vehicle detection, is widely used in the field of intelligent transportation. In ViBe algorithm, the "ghost" phenomenon in the model initialization stage, the update mechanism in the background model update stage and the flicker point interference caused by leaf disturbance, camera jitter and other factors in road scenes are improved. According to the similarity of road gray distribution, a judgment strategy of pixel gray value is introduced to solve the "ghost" phenomenon caused by foreground objects in the image when ViBe algorithm is modeling the first frame. The fixed update strategy in ViBe algorithm is changed to an adaptive update strategy to better adapt to the changes of road scenes. At the same time, the scintillation point determination mechanism is introduced to solve the leaf disturbance and camera jitter problems. The algorithm was verified by the standard data set Cnt 2014, and the results show that the detection effect is better than the classical algorithm.