Reviewerly/exHarmony huggingface dataset:
CompModels: A Suite of Computer Model Test Functions for Bayesian Optimization

The CompModels package for R provides a suite of computer model test functions that can be used for computer model prediction/emulation, uncertainty quantification, and calibration, but in particular, the sequential optimization of computer models. The package is a mix of real-world physics problems, known mathematical functions, and black-box functions that have been converted into computer models with the goal of Bayesian (i.e., sequential) optimization in mind. Likewise, the package contains computer models that represent either the constrained or unconstrained optimization case, each with varying levels of difficulty. In this paper, we illustrate the use of the package with both real-world examples and black-box functions by solving constrained optimization problems via Bayesian optimization. Ultimately, the package is shown to provide users with a source of computer model test functions that are reproducible, shareable, and that can be used for benchmarking of novel optimization methods.
SEMANTIC CONSCIOUS LOOKING OVER ENCODED INFORMATION FOR DISTRIBUTED COMPUTING

Nowadays numbers of users outsource their data to the cloud. To give the security for data, the data should be encrypted before sending it to cloud because it becomes difficult for the hacker to hack the data which is in encrypted format. For example, it is hard to seek the catchphrases in encoded sets. Various plans are proposed to make mixed data open reliant on catchphrases. In any case, catchphrase based look for plans disregard the semantic depiction information of customer’s recuperation and can’t thoroughly meet with customers look desire. In this manner, how to design a content-based interest plan and make semantic chase continuously reasonable and context-aware is a hard test. Here the proposed system uses, two cloud servers, one is used to store the re-appropriated datasets and return the situated results to data customers. The other one is used to figure the scores between the reports and the query and send the scores to the essential server. To also improve the look viability, we utilize a tree-based document structure to deal with all the file record vectors. The multi-keyword situated look for over encoded cloud data is used as the basic edge to propose two secure plans. The examination results subject to this present reality datasets show that the arrangement is more gainful than past plans. More over it shows that the arrangements are secure under the known cipher text model and the background model.
Art as world and body transformation in philosophical and artistic cosmism. Article 2

The paper continues the description of the aesthetic system of Russian cosmism through the prism of the theme of world and body transformation. The synthetic idea of art, the idea of unity of science and art, the concept of culture of the future, which is key for the philosophy of cosmism, are considered. Fedorov's thesis which is formulated as: “Our life is an act of aesthetic creativity”, as well as his idea of man's creation of himself as a matter of art are also taken into consideration. Finally, the article shows Christian roots of the idea of transfigured corporeality developed by N.F. Fedorov and the cosmists of the 1920s.
Enhanced Research of Sentiment analysis Techniques in Social Media Content

Human involvement is potentially the richest amount of information found on social media. Information received from internet consumers reflects their views on subjects or goods. It's almost hard for us to wade through any of such data. The study of social media communication has grown to be a critically significant part of social media work. However, most sentiment analysis is currently done on the gross stage, rather than the fine granularity and doesn't conduct the nuances required. Sentiment research has gained prominence. As several search engines seek out opinionated data and classify it as such, some text interpretation problems are more complex than with conventional text analysis. This is unequivocal about the need to resolve these issues and has opened the doors to potential polysemantic processing research. However, with data increasing in volume, the automated data processing is required. As extensive research is conducted into various sentiment analysis methods, a survey of these Sentiment measurements is provided.
The Search for Relevance in Knowledge Management: An Ontological Perspective

The significance of and the role played by Knowledge Management (KM) is ever increasing in today’s business and organizational decision-making environment. This paper attempts to underline the importance of organizing knowledge not for its own sake, but for its efficient use in organizational decision making. The tremendous explosion of knowledge resources, both electronic and conventional, within the last few decades calls for an understanding of how knowledge is organized for management of data and information. This is so for the reason that they can be proficiently employed to create value and utility. This also calls for a search for ‘relevance’ in KM with regard to its situated nature in different contexts within which knowledge is situated, and that which nevertheless indirectly refers to its ontological scaffolding. We have devised two simple mathematical models of reference with regard to the design of the systems mostly intended for organizing knowledge in knowledge organizations for its most efficient utilization. The model specifies several unique scenarios aided by discovery of arguments related to its ontological framework within which knowledge is situated. Several contexts were drawn to draw inferences from the research study. The results bear relevance to knowledge managers who make important decisions for realization of organizational goals and objectives.
Creating Communities of Practice among Librarians in an Online Learning Environment

This poster applies the concept of an online community of practice in an effort to suggest how librarians can join together as a community to learn and to share ideas, strategies, and tools related to effective teaching and learning. It was presented at The Exchange an Association for Library Collections and Technical Services (ALCTS)/Library and Information Technology Association (LITA)/Library Leadership and Management (LLAMA) Collaboration held virtually on May 4, 6, & 8, 2020
New Sports Fitness Space Based on Big Data

With the economic and social development of our country and the improvement of people's living standards, our society is welcoming the arrival of the leisure era. This research mainly discusses the structure of a new type of physical fitness space based on big data. By establishing a sports big data platform, using the Internet and big data technology to manage and monitor urban outdoor fitness venues, national fitness activities, national fitness training and so on. According to the collected data, it can effectively solve the problem of government investment efficiency and allocation, and at the same time it is conducive to the government's procurement of public fitness facilities resources, and regional distribution supply, and promote the balanced development of urban outdoor fitness venues. Using Arc GIS spatial statistics and analysis tools as the main analysis method, from the evaluation and analysis of the number, distribution, radiation range, accessibility, and coupling of leisure sports facilities space, it summarizes the structural problems of urban leisure sports space supply. The population radiation rate in the inner and middle layers of city A is as high as 76%, but the population radiation rate in the outer layer is relatively low. This research has positive significance for the planning of sports and fitness space.
A Study on Sentence Segmentation in English to Chinese Translation of Petroleum Academic Papers from the Perspective of Cognitive Load

English petroleum academic papers have their special features: informative, large numbers of long sentences and complex structures. According to the principle of limited total amount of attention in the Cognitive Load Theory, when there are too many information chunks in a sentence, more cognitive resources are needed to process information, which will reduce the cognitive resources allocated to other tasks, such as memory storage, thus reducing the reading efficiency and increasing the difficulty for readers to understand the texts. Therefore, in the process of translating petroleum academic papers into Chinese, proper sentence segmentations are very important for the readers to improve their reading efficiency and understand the texts. Taking the English to Chinese translation of petroleum academic papers as an example, this paper studies sentence segmentation methods to improve the readability of Chinese versions of these texts from the perspective of cognitive load. The results show that adding function words, separating sense groups of a sentence and translating the non-finite verbs individually will effectively reduce the cognitive load of readers and improve the readability of the translations.
Handling Ambiguity Issues In The Process Of Finding Association Rules

Normally Association Rules Consider Only Items Enumerated In Transactions. Such Rules Are Termed As Positive Association Rules. In Case Of Negative Association Rules, They Too Consider The Same Items, But Also The Negated Items. While Performing Market-Basket Analysis, The Negative Association Rules Are Useful In To Identify Products That Conflict With Each Other Or Products That Complement Each Other. In This Paper The Two Main Issues In Generating Association Rules Are Addressed. One Is Minimizing Strong, Uninteresting Association Rules And The Other Is Identifying Misleading Association Rules With Strong Negative Correlation Between The Antecedents And Consequents. The Techniques Discussed In This Paper Are Found To Be More Effective And Precise. The Effectiveness Of The Mining Process Can Be Enhanced Significantly By Applying The Methods Discussed.
Analytical Study of Nanoplastic Encapsulation for Photo Voltaic Outdoor Lighting and the Protection of Offshore Wind Power Structures Nanotechnology

Plastic is a high-molecular-mass organic polymer made up of a variety of synthetic or semi-synthetic organic polymers. Plasticizers, flame retardants, antioxidants, acid scavengers, lubricants, pigments, antistatic agents, and slip compounds are some of the additives that can be used to make plastic from crude oil. Plastic has the inherent potential to be moulded or sculpted by applying extreme temperatures and pressure. Humans have discovered how to employ plastic for our socioeconomic progress throughout the last century. Today, plastic is used in a wide range of applications, including our daily activities. Plastics are known for being low-cost, tough, long-lasting, easy to manufacture, strong, electrically and thermally inert, and resistant to shock, mechanical vibration, and corrosion. Plastic has made a significant contribution to the world economy since it is very easy to make and export. Plastic is one of the most adaptable and commonly used materials in the world, revolutionising numerous industries by demonstrating that it is a good choice for packaging, food, textiles, building, and interior decorating. It is heartbreaking to see that half of the world is combating plastic pollution, which has a greater impact on natural habitat, aquatic animals, and human health. Plastic pollution has recently increased, posing a major threat to our environment that requires quick care or it would be too late for our mother earth. Microplastic has been found to cause cancer by promoting the creation of mutant cells, according to a paper issued by the World Health Organization.
НЕПРЕРЫВНОЕ ПРОФЕССИОНАЛЬНОЕ РАЗВИТИЕ РАБОЧИХ КАДРОВ РЕГИОНА В ФОРМАТЕ КЛАСТЕРНО-СЕТЕВОГО ВЗАИМОДЕЙСТВИЯ: УПРАВЛЕНЧЕСКИЙ АСПЕКТ

The paper states some regional peculiarities of the vocational education system in Tomsk Region. The authors justify the feasibility of a cluster-network approach in managing the continuous professional development of the region’s workforce to solve current problems and promising tasks of vocational education at the regional level and share their experience of its practical application. The research subject is described to indicate the key prospective areas of pedagogical and scientific research in the presented regional practice.
Availability and Utilization of Mobile Smartphones among Teachers and Students' in Colleges of Education in Yobe State, Nigeria

The study investigates the â€œAvailability and Utilization of Mobile smartphone among Teachers and students in Colleges of Education in Yobe state, Nigeriaâ€. The study was guided by two research objectives, two research questions and two null hypotheses which were tested at (0.05) level of significance. The population of the study was 614 teachers and 15103 students from three Colleges of Education in Yobe State. The design adopted for the study was descriptive survey research. Â A random sampling technique was used to determine the sample from the population. The sample has a population of 202 teachers and 4826 students. The sample size of 132 teachers and 357 students were obtained using Krejcie and Morgan Table for determining sample size. The instruments used for data collection was researcher self-constructed questionnaire titled Teachers Smartphone Availability Questionnaire and Students Smartphone Availability Questionnaires and was validated by three experts and pilot tested. The result of the pilot testing was analysed using Cronbach Alpha and yielded a reliability coefficient of 0.76 for teachers and 0.82 for students. Frequency count and percentage were used to analyze the descriptive statistics, mean and standard deviation were used to answer the research questions and paired sample test was also used to tested the null hypotheses at (0.05) level of significance. From the result, all twonull hypotheses were rejected. The summary of findings indicates that, smartphones are availability among students than among teachers in colleges of education in Yobe State. Educational utilization of smartphone is higher among students than among teachers in colleges of education in Yobe state. It was recommend that, Schools should send teachers for short term course in order to learn how to integrate smartphone in to teaching and learning.
Interactive Medical Chatbot for Assisting with COVID-related Queries

This chapter presents an overview of developing text-based conversational agents, especially chatbots, to cope with pandemic challenges in the era of COVID-19. In the chapter, the modus operandi of developing a healthcare bot is discussed in detail. The proposed chatbot not only detects whether the user is at risk of COVID-19 infection, but also answers all frequent types of users’ queries on COVID-19 satisfactorily. In addition, the proposed agent provides urgent information on hospitals and local medicine shops near to the suspected COVID-19 patients. In contrast to government-affiliated apps like Aarogya Setu, the proposed chatbot is integrated with an additional facilitator that provides the features for detecting symptoms and diseases of a suspected user at risk of COVID-19 infection. The contributions of our proposed conversational agent have been designed to answer any of the user’s queries on COVID-19 just like a search engine specialized in a specific COVID domain. The algorithm searches for the most appropriate answer by using the synonyms-matching technique to reach the nearest question cluster to which the user query belongs. Currently, the conversational agent provides information on hospitals and medicine shops only for the state of West Bengal in India, and a dataset has been prepared for each of the PIN codes in the state. Our conversational agent provides all the information related to COVID-19 to its users, unlike existing conversational agents, thereby assisting the user to stay informed and alert. We discuss how to employ the Rasa framework and parse texts of dialogue conversations in real-time to add a human-like flavor to make the conversations more interactive. The evaluation metrics applied at different module levels have shown satisfactory results.
An Implementation of Real-time Automatic Masked and Unmasked Face Recognition Using LBPH Algorithm

Face recognition is an important research in computer vision technology. Face recognition is biometric technologies which identify identities from their visual features of face images. There are many challenges to make a face recognition system like light illumination, pose variation, angle of face, distance between face and camera. But Due to COVID-19 one of the biggest challenge is added into the challenge list which is detect and recognize person face with facemask. Here the research is based on a real-time automatic masked and unmasked face recognition system. This is implementing using OpenCV, Haar Cascade and LBPH Algorithm which is able to detect and recognize a single person and multiple(two) person at a time with and without facemask . And also recognize multiple authorized persons when one-person ware facemask and another person didn’t ware facemask.
ES_Use: An Efficient Rating Prediction Method

In an online shop scenario, learning high-quality product embedding that captures various aspects of the product is important to improve the accuracy of user rating prediction. There is a lot of research about product embedding learning, for example, the side information which is the fusion of user feedback and the appearance of a product. However, because of the diversity of a product’s aspects, taking into account only its appearance as side information is not sufficient to accurately learn its embedding. In this paper, we present a matrix co-factorization method that employs information hidden in the so-called “also-viewed” or “also-bought” products, i.e., a list of products that have also been viewed or have also been bought by a user who has viewed a target product. To improve the accuracy of the rating prediction, our first step is to find out similar users. However, suppose the dataset is very large, e.g., if we have to deal with tens of millions of users’ data, the similarity calculation among users will be very time-consuming. For dealing with this problem, we use a compact binary sketch (i.e. ES, Even Sketch for user similarity estimation) to estimate user similarity. Our experiments demonstrate the superiority of our method in comparison with a state-of-the-art baseline in generating high-accuracy rating prediction.
Implementasi Network Automation Untuk Konfigurasi Jaringan Baru Dengan Netmiko

The internet is a necessity at this time, every activity we do every day always requires the internet starting from communicating, doing work, looking for information and other needs. PT. Maxindo Mitra Solusi is a company engaged in telecommunications (internet) services, installing network devices so that every customer can enjoy internet services. Each network device needs to be configured to be able to connect to the internet. Configuration of network devices is still done conventionally, where the device is configured one by one, it takes time and effort in advance of the risks that are usually done by humans. With the Network Development Life Cycle (NDLC) method to overcome the above problems. in the development of this system using the Python programming language and the use of the help of the Netmiko library. The testing system used is black box testing, white box testing and questionnaires. By using Network automation the installation of a new network becomes easier and faster. Network operators just need to run the program and each device will be configured automatically. More programs require relatively low resources and can reduce the risk of errors. Keywords : Internet, Network Development Life Cycle, Network Automation.
Methodological principles of organizing educational work of educational institutions in the digital reality

In this article we aim to problematize methodological principles of organizing educational work of educational institutions in the context of modern trends in a transforming society. The authors emphasize the inconsistency and multiplicity of conditions for mental and personal development of a person in the context of digital reality. The adoption of strategic documents that set the mandatory directions of educational activities at all levels of education requires an understanding of the existing traditions of teaching and education. The authors point to the insufficient elaboration of theoretical and methodological backgrounds of education of the digital society children - “digital natives”, insufficient analytics of the effectiveness and efficiency of the technologies and digital educational resources used. The article presents a fundamental vision of the organization of educational work: as a system and as a joint activity. The authors are convinced that for the organization of relatively socially controlled socialization of society members, for the transmission of culture and social norms, it is necessary to update the methodological principles of systematization, the environmental principle, the principle of value behavioral foundations, the principle of producibility, the principle of individual age characteristics inclusion and the principle of emotional involvement.
Visual Studio 2010-Based Medical Records Completeness Information System Design

This study aims to find out the design of information analysis system completeness of filling medical records sheets by using Microsoft Visual Studio.NET 2010 H ospital X. Research method used is qualitative method with descriptive approach, while the method of developing data collection techniques used is waterfall method. The results of the research conducted found problems that are standard operating procedures related to filling medical records that have been established but in the implementation has not gone well, The management of data analysis completeness of filling medical records sheet is still using manual, There are still unfilled and incomplete medical records . The advice given is to build an effective and integrated information system, Implement a complete information system filling medical records sheets, Give advice to doctors or health workers to always complete medical records. The research results conclude that the standard of operational procedures (SOP) related to the completeness of filling medical records already exists but the implementation has not gone well. Analysis of medical records is still done manually, as well as in the creation of a report recapitulating the completeness of medical records. By implementing a completeness analysis system following the SOP that has been established by the hospital and building the design of a computerized information system to facilitate the analysis of the completeness of medical records filling sheets in Hospital X.
Guest Editors' Words

This Special Issues brings ten invited papers, from the experts of the field across the globe, focusing on different aspects of computing systems design and techniques to cope with the increasing level of complexity and specialization in modern computing systems. The readers will be provided with an extensive literature review followed by valuable insights on the major trends on future computing systems design. In the following, we present a brief description of the papers appearing in this Special Issue.