Reviewerly/exHarmony huggingface dataset:
Comparison of the ant colony optimization algorithm and its two modifications

The ant optimization algorithm is one of the effective modern algorithms for finding ap-proximate solutions of the salesman problem and similar problems of finding routes on graphs. The first version of this metaheuristic optimization algorithm was proposed by Marco Dorigo in 1992 [1]. After some time, several modifications of this algorithm have been proposed in the literature. The aim of the study is to conduct a comparative analysis of the ant optimization algo-rithm (Ant Colony Optimization, ASO) [1] and its most successful modifications: Ant Colony System (ACS) [2] and Max-Min Ant System (MMAS) [3]. To do this, the system features of information exchange in the ant colony during the search for food are analyzed. A step-by-step algorithm that simulates the natural behavior of forage ants in finding the shortest path to deliver food to the anthill is presented. A software implementation of the three listed ant algorithms for solving the travelling salesman problem has been developed. Through the interface window, you can enter the number of cities, the number of ants, and the maximum number of iterations, fix the settings of the algorithm and select any of the three algorithms. The program randomly locates cities and selects the starting city for each ant. The software product is multi-threaded, i.e. during the calculations the interface is not blocked, which allows you to control the process of program execution, namely: start, pause, stop, resume work. The results of the program are: vis-ualization of the shortest route found, the length of this route and the smallest iteration number, which achieves the shortest route. Comparative analysis of the results allowed us to draw the following conclusions: 1) With well-chosen algorithm settings, iterative methods usually give a result close to optimal, however, the number of iterations required for this may differ significantly. 2) The study of the travelling salesman problem by ant algorithms is experimental rather than theoretical. The result very much depends on the parameters of the algorithm settings, but the theoretical study of these dependencies remains relevant and unresolved.
Reading In and Writing Out Text Data

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
Rapid Fabrication of Custom Microfluidic Devices for Research and Educational Applications

Microfluidic devices allow for the manipulation of fluids, particles, cells, micro-sized organs or organisms in channels ranging from the nano to submillimeter scales. A rapid increase in the use of this technology in the biological sciences has prompted a need for methods that are accessible to a wide range of research groups. Current fabrication standards, such as PDMS bonding, require expensive and time consuming lithographic and bonding techniques. A viable alternative is the use of equipment and materials that are easily affordable, require minimal expertise and allow for the rapid iteration of designs. In this work we describe a protocol for designing and producing PET-laminates (PETLs), microfluidic devices that are inexpensive, easy to fabricate, and consume significantly less time to generate than other approaches to microfluidics technology. They consist of thermally bonded film sheets, in which channels and other features are defined using a craft cutter. PETLs solve field-specific technical challenges while dramatically reducing obstacles to adoption. This approach facilitates the accessibility of microfluidics devices in both research and educational settings, providing a reliable platform for new methods of inquiry.
Early Detection Method for Money Fraudulent Activities on E-commerce Platform via Sentiment Analysis

Shopee is one of the prominent online shopping platforms in Malaysia. Nonetheless, countless scam cases were reported on the platform, particularly on money fraudulent activities. This study constructed a quantitative model through linear programming that assessed sentiments based on customers’ reviews. Reviews from three selected Shopee products (‘M3 Smart Health Watch’, ‘Sony Headset Wired Gaming Headphone’, and ‘20000mAh Pineng 100% Original Powerbank’) were analysed using the proposed model. The data were converted into measurable metrics to enable quantitative fraud detection. The model enabled the early detection of possible money fraudulent activities on Shopee products based on customers’ reviews. Resultantly, ‘M3 Smart Health Watch’ is an authentic Shopee product. In contrast, ‘Sony Headset Wired Gaming Headphone’ and ‘20000mAh Pineng 100% Original Powerbank’ are money fraud products sold by scammers. The proposed model utilises free and readily available software, thus extending its usability to other small business owners.
Role of Internet of Things and Artificial Intelligence in COVID-19 Pandemic Monitoring

Internet of Things (IoT) has become one of the important components in developing interconnected smart IoT devices. Data generated from the IoT devices increases rapidly due to the increase in the number of connected devices. The current COVID-19 outbreak condition has led to the need of the Healthcare IoT (H-IoT), which can provide an automatic solution for monitoring. Therefore, IoT data is extremely crucial to be analyzed. Artificial Intelligence (AI) has gained a lot of attentions for automatizing applications based on the big data generated from the IoT devices. This chapter presents the current development of AI applications for monitoring the pandemic. The role of IoT, data acquisition, preprocessing, and analysis is also described here. In depth, we elucidate few methods of data preprocessing using conventional techniques and Machine Learning (ML) algorithms, and data analysis using ML and Deep Learning (DL) algorithms. We list all techniques in handling data preprocessing and analysis, and the challenges of IoT and AI in the new way of living during pandemic which is also known as the era of new normal.
Analysis of Key Topics in Green Logistics Using LDA: Focusing on Keywords Before and After the COVID-19

Since the COVID-19 pandemic, the trend of green logistics has been accelerating in the logistics industry. The purpose of this study is to analyze the changes in social interest in green logistics before and after the COVID-19 pandemic, based on keywords extracted from news articles. To this end, two periods were selected, pre-pandemic (2018-2019) and postpandemic (2020-2021). Text analysis and topic modeling were conducted for the news articles related to green logistics in each period. In order to collect the news articles, the Big Kinds database was used, and key topics for each period were derived by applying the Latent Dirichlet Allocation (LDA) technique, a topic modeling methodology. The derived key topics were further classified into subtopics such as storage, unloading, packaging, transportation/distribution, and corporate strategy/policy in relation to logistics by functions. As a result of the study, it was confirmed that in the post-pandemic period, interest in green logistics increased in the media, and there was a change in the tendency of use of specific keywords and topics. In addition, with the emergence of new topics related to green storage, it was suggested that the green storage field could become a new business model for green logistics.
Development and Implementation of a Platform-based inter-cultural English Teaching and Learning Model: Focusing on Culture Project

The purpose of this study is to develop and implement a platform-based intercultural English teaching and learning model for a real time online class (‘English/American culture’) at a Korean university. According to the intercultural language learning theories, the intercultural competence makes learners better understand the target culture and improve language abilities. By incorporating inter-cultural projects into an English &amp; American culture course with an E-buddy project (of one Korean student and one American student as a team) on multiple online platforms, we encouraged Korean students to meet regularly with an American partner and do a collaborative culture project on a chosen topic in English. We analyzed the effects of the class with the inter-cultural project, by employing quantitative and qualitative methods: observations of classes and the culture project, a questionnaire, students’ reflection reports and interviews. The findings showed that students perceived it to be useful for an improvement of their speaking and listening skills. They were able to gain deeper insights into English/American culture and its society. In addition, the students developed certain degree of cross-cultural awareness and thereby came to a reappraisal of their own culture. In general, the students were positive about the course with the intercultural culture project in groups and found it beneficial for their language learning and intercultural understanding.
A Study on the Improvement Direction of Writing for Academic Purposes as Seen through Meta-analysis

This study was attempted to explore the problems in writing for academic purposes and to improve them. The data that is the basis of the study was based on the contents of a survey of university undergraduate students. The main contents of the investigation and analysis are as follows. First, there are problems and improvement directions for ‘reading text’. There are two important things to look at in this part. First, it is a reading methodology that can be accessed in the sense of communication. The other is an analysis of how to solve problems through ‘reading in two directions’. The second of the main contents of the survey and analysis is a study on evaluation criteria and regression. The purpose of this study was to identify the problems and analyze the causes in the method of helping learners understand the standards of feedback. In addition, problems that occur when rewriting is attempted in the process of rewriting are found and methods to improve them are presented. For this study, Cohen’s effect size category, which suggested a methodology for meta-analysis, was used and applied to the analysis.
Semisupervised Semantic Segmentation with Mutual Correction Learning

The semisupervised semantic segmentation method uses unlabeled data to effectively reduce the required labeled data, and the pseudo supervision performance is greatly influenced by pseudo labels. Therefore, we propose a semisupervised semantic segmentation method based on mutual correction learning, which effectively corrects the wrong convergence direction of pseudo supervision. The well-calibrated segmentation confidence maps are generated through the multiscale feature fusion attention mechanism module. More importantly, using internal knowledge, a mutual correction mechanism based on consistency regularization is proposed to correct the convergence direction of pseudo labels during cross pseudo supervision. The multiscale feature fusion attention mechanism module and mutual correction learning improve the accuracy of the entire learning process. Experiments show that the MIoU (mean intersection over union) reaches 75.32%, 77.80%, 78.95%, and 79.16% using 1/16, 1/8, 1/4, and 1/2 labeled data on PASCAL VOC 2012. The results show that the new approach achieves an advanced level.
Modernization of secondary vocational education in the context of the development of the national system of qualifications

In March 2021, the National Council for Professional Qualiﬁcations under the President of the Russian Federation approved the Strategy for the Development of the National Qualiﬁcations System of the Russian Federation until 2030. Almost at the same time, the List of initiatives for the socio-economic development of the Russian Federation until 2030 was approved, among which a special place belongs to the project “Professionalitet”, which involves a large-scale transformation of secondary vocational education. The coincidence of the priorities outlined by the documents became the basis for studying the possibilities of using the tools of the national qualiﬁcations system for the successful implementation of the “Professionalitet” project.An analysis of measures to reform secondary vocational education over the past ten to ﬁfteen years is given, the purpose of which is to ensure that the qualiﬁcations of graduates meet the requirements of the economy. The study of the data of monitoring studies, expert assessments led to the conclusion that as a result of the experiments there were some successful practices for the training of skilled workers and mid-level specialists, however, for the system as a whole, the eﬀects turned out to be more modest than expected.It is shown that, since the project “Professionalitet”, based on the experience of previous initiatives, should oﬀer a systematic solution to the problem of staﬀ shortages, it is inappropriate to consider its implementation outside the context of the development of the national qualiﬁcations system as a whole. As part of the experiment, a new approach to the training of working personnel should be developed, which implies more ﬂexible principles for the work of professional educational organizations, and the active involvement of business representatives in educational programs. This is possible if the state interacts with employers, the professional community, and educational organizations. Mechanisms for such interaction have been formed and continue to develop within the framework of the national qualiﬁcations system.On speciﬁc examples, it is considered how the tools of the national qualiﬁcations system can be used to determine the requirements for the results, content, terms of mastering the educational programs “Professionalitet”, assessing the quality of their implementation, ensuring the right of students to receive and conﬁrm qualiﬁcations that are understandable to employers and in demand on the labor market.
Cryptographic and Consensus Techniques Supporting Privacy and Security Management of Cryptocurrency Transactions

All cryptocurrency transactions are recorded in a digital, decentralized, and public ledger that is known as a blockchain. Privacy and security techniques are essential for the privacy and security management of cryptocurrency transactions. A system developer and a software engineer for a cryptocurrency blockchain system must well understand the knowledge of privacy and security techniques utilized in blockchain systems. This chapter includes blockchain structure for cryptocurrency, its privacy and security requirements, and security properties; cryptographic techniques and elliptic curve approaches; and consensus techniques. This chapter describes the general security aspects of a cryptocurrency blockchain system after analyzing the privacy and security requirements for cryptocurrency transactions. These security features efficiently support system developers and software engineers for the privacy and security managements and developments of cryptocurrency transactions.
Towards Efficient FHE Based cPIR Schemes and Their Parameter Selection

Private Information Retrieval (PIR) protocols enables fetching an arbitrary data from a server without revealing any information to the server about the data. In this paper, we construct three computational PIR (cPIR) protocols which we call P-cPIR and Recursive P-cPIR version I and II. We construct our cPIR protocols on a well known Fully Homomorphic Encryption scheme (FHE), BFVrns. For n = 220, 240, P-cPIR and Recursive P-cPIR version I provide at least ∼ 214 × computational improvement over other prominent cPIR protocols. Recursive P-cPIR version II proposes the same query and half response cost as OnionPIR (lower communication cost in total) and less than other protocols such as SealPIR, SHECS-PIR, XPIR. It also proposes at least ∼ 23 × less computational cost than other proposed protocols by stating the best performance in these protocols for both cases. We also provide a parameter selection method for the proposed cPIR protocols that takes the burden of parameter selection from the users and makes it more usable for real-life applications.
The fruit fly optimization algorithm based on normal cloud model

In order to overcome the demerits of fruit fly optimization algorithm (FOA), such as easily relapsing into local optimum and unstable results which are caused by strong dependence on the selection of algorithm parameters, The cloud model theory is introduced into the algorithm improvement, and the algorithm is optimized and improved from two aspects: the optimal step size of the algorithm and the optimal solution generation mechanism. Firstly, the conception of taste concentration introduced and adjusted adaptively for controlling search step to improve the global search ability and local optimization ability of the algorithm. Then, the randomness and fuzziness of smell concentration parameter is described by normal cloud model and adjusted to finish osphresis search operation automatically to improve the searching precision of the algorithm. Finally, The improved algorithm is used to the automatic test, compared and analyzed with the experiment of other FOA in reference literatures. The results of experiment show that the improved algorithm has better advantages of test efficiency and accuracy.
Copyright on digital platforms: shifting paradigms

Since the beginning of the Internet age, the Internet services providers have been incentivized to cooperate with copyright holders in exchange for (certain) legal immunity from the liabilities incurred by their users' infringements. Digital platforms play increasingly essential role in copyright protection and the shifting paradigms are gradually reflected in the legal reforms in different jurisdictions. However, the validity of the platform rules is increasingly being challenged in law enforcement or civil dispute cases for antitrust or other reasons. Indeed, a few large platforms have experimented with the out-of-court settlement mechanisms to resolve the disputes between the right holders and users. As the alternative option for the right holders, the platform alternative dispute resolution (ADR) mechanisms are increasingly recognized in law. Platform ADR mechanisms are in quick development but far from mature. No matter how the platform operators construct the ADR mechanisms, a few basic principles should be followed. In conclusion, the notice-and-takedown method is no long reflecting the reality of growing platform economy and its legal reform is inevitable. The reforms empower the platform operators, but unchecked power and reinforced private ordering are not in public interests. Therefore, success of the reforms depends on strengthening platform's legal obligations, intensifying the legal review of platform governance and improving platform ADR mechanisms
Preface

2021 3rd International Conference on Resources and Environmental Research (ICRER 2021) was originally scheduled to be held in Xiamen University of Technology, China during December 2-4, 2021, but it was switched to a virtual conference due to the unstable situation generated by the COVID-19 pandemic and the worldwide travel restrictions. The location of the organizer is No. 600, Ligong Road, Jimei District, Xiamen, China. This three-day conference focused on the research fields related to resources and environmental research and aimed to provide a forum for professors, researchers, scholars and industrial pioneers all over the world to share ideas, designs and experiments. ICRER 2021 attracted more than 45 participants from Thailand, Denmark, UK, Saudi Arabia, Malaysia, Portugal, Brazil, Indonesia, Spain, Australia, Republic of Kazakhstan, USA, Canada, and China. List of Committees are available in this pdf.
ORGANIZATION OF EDUCATIONAL WORK OF THE EDUCATIONAL INSTITUTION DURING QUARANTINE BY MEANS OF INFORMATION AND COMPUTER TECHNOLOGIES

The article analyzes the features of the educational process during quarantine and provides its theoretical justification. The methodological basis of the study are the general provisions of the theory of knowledge, the main provisions of the systems approach, the concept of informatization of education. It is proved that the need to organize distance learning at different levels of the educational process in modern realities has led to a more thorough approach in all world spheres. The tense epidemiological situation in our country and around the world has led to the fact that its subjects are divided in space. It is revealed that distance learning should: meet all the requirements for innovative education, be based on the use of information and communication technologies, modern multimedia interactive equipment; to ensure the effectiveness of basic educational programs; combine all the best qualities of virtual and traditional education. The theoretical bases of students' learning in the conditions of distance learning are highlighted. An experiment was conducted to analyze the state of awareness of Berdyansk students with online information resources about Covid_19, which was attended by 375 students of secondary school №7 in Berdyansk. The results of an experiment that showed the imperfection of the organization of preventive work in the city's schools are described. Therefore, the task of creating additional tools for informing students about Covid_19 is urgent. Describes the results of the analysis of popular site creation systems, which allowed to choose the GoogleSites system, due to its ease of use, flexibility, supported extensions for site development to inform students about Covid_19. This study is not final, so we plan to continue publications that will reveal in more detail the practical aspects of the development of this site. Key words: distance technologies, distance learning, distance education.