Reviewerly/exHarmony huggingface dataset:
Youtube as an Information Source of Floating Agriculture: Analysis of Bengali Language Contents Quality and Viewers’ Interaction

Bangladesh is physically low-lying and prone to flooding, making floating agriculture an appropriate method for dealing with floods and assisting farmers in coping. This YouTube content study was conducted to investigate the quality of information found on YouTube regarding floating agriculture in Bengali language, as well as viewers' interactions to such videos. The inquiry began with a search on https://www.youtube.com for the keyword ', ভাসমান কৃষি (Floating Agriculture),' which obtained 302 results. Following that, a total of 245 contents were discarded due to their inability to fulfill the inclusion criteria. Data on likes, dislikes, views, duration, comments, publisher type, and publishing year were retrieved from videos. The quality of contents was measured by a grading methodology that took into account two aspects: i) Comprehensive aspect; and ii) Floating agriculture aspect. The Kruskal-Wallis test was used to investigate multiple comparisons (P<0.05 considered as statistically significant). Viewers’ Sentiments, emotion, and intention towards the videos were analyzed from comments. A total of 26.32 % contents were of high quality, with the majority of videos released by independent publishers and the quantity of videos on an upward trend. According to floating agriculture video demographics, mean view (70816.60 ± 177319.129), mean like (818.56 ± 1992.700), mean duration (07:47 ± 06:48 min.), and mean comment (18.40 ± 38.537). The amount of views, likes, and duration varied statistically significantly in relation to different content quality categories. Comments analysis revealed that the majority of the viewers’ possessed positive sentiments and happy responses, whereas most of the comment was for feedback purposes. In conclusion, despite the fact that the number of high-quality videos on YouTube regarding floating agriculture was limited, viewers seem to be satisfied with those videos. This is the first paper that critically assessed the quality of floating agriculture -related YouTube videos as well as identified viewers’ interaction towards those videos. This report highlights the present scenario of YouTube content regarding floating agriculture which will help content creators to produce quality videos. Understanding the viewers’ interaction would set new dimensions in policy implications regarding effective information dissemination.
The Linz Zoocode project. Fourth report of activities (2021).&lt;br&gt;Nomenclatural availability. 3. Paper publication

This fourth report of activities of the Linz Zoocode Committee is devoted to a detailed survey of the problems raised by the current Rules of the Code regarding the nomenclatural availability of works published on paper, concerning their dates, material and administrative parameters of publication, and various other matters. It proposes a few changes (clarifications and simplifications) in these Rules.
Constructing Japanese Bullying Expression Dictionary for Automated Cyberbullying Detection on Twitter

Cyberbullying has become a serious problem with the spread of personal computers, smartphones and SNS. In this paper, for automated cyberbullying detection on Twitter, we construct a Japanese bullying expression dictionary, which registers bullying words and their degrees related to bullying. The words registered in the dictionary are those that appear in the collected bullying-related tweets, and the bullying degrees attached to the words are calculated using Semantic Orientation Using Pointwise Mutual Information (SO-PMI). We also construct models to automatically classify bullying and non-bullying tweets by extracting multiple features including those drawn from the bullying expression dictionary and combining them with multiple machine learning algorithms. We evaluate the classification performance of bullying and non-bullying tweets using the constructed models. The experimental results show that the bullying expression dictionary can contribute to cyberbullying detection in most of the machine learning algorithms and that the best model can achieve an [Formula: see text]-measure value exceeding 0.9. We further investigate whether the periods of constructing bullying expression dictionaries affect the classification performance. The experimental results indicate that in contrast to the period of dictionary construction, the number of registered words has more immediate impact on classification performance.
Identifying High-impact Bug Reports with Imbalance Distribution by Instance Fuzzy Entropy

Bug tracking systems, such as Bugzilla, contain bug reports collected from sources such as development teams, testing teams and end users. Developers often depend on bug reports to fix identified bugs. Frequently used bug reports are the so-called severe bug reports. Although severe bug reports can be manually detected within bug reports in bug tracking systems, they impose heavy burdens on management of bug tracking systems. Consequently, an automated mechanism to examine the severity of bug reports is desirable to augment productivity. Unfortunately, identifying the severity of bug reports from thousands of bug reports in a bug tracking system is not an easy feat, because of the problem of low-quality and imbalance distributions that could affect the performance of automated mechanisms. In this paper, we propose an approach, namely FER, to counter low-quality and imbalanced distributions of bug reports relative to their severity. First, FER approach gets high-quality bug reports based on instance fuzzy entropy. Then, FER approach weakens the imbalancedness degree of class distribution according to the high-quality bug reports to train classifiers to recognize the severity of bug reports. Several experiments are conducted on bug reports from three open source projects (Eclipse, Mozilla, GNOME) and they reveal that our approach is robust against the low-quality and imbalance distributions of bug reports, while identifying the severity of bug reports.
Education in virtual space of collective action in the conditions of pandemic of COVID-19: social-philosophical aspect

It is proved that one of the tasks of modern education is the maximum use of information and communication technologies. After all, these technologies are one of the means that allows to realize the tasks of education in the conditions of pandemic and war. Due to these possibilities, modern education in most cases has moved from real classrooms to virtual ones. Virtual space creates possibilities for overcoming of temporal and spatial borders in the acquisition of knowledge, promotes the formation of social groups, within which there is an exchange and capture that or other information, knowledge. Features of the formation of col­lective action are considered. Attention is paid to the conditions with which the world met in the XXI century – COVID-19. The aim of this article is to analyse the peculiarities of the formation of collective action in cyberspace in the context of the COVID-19 pandemic based on a survey. The theoretical and methodological component consists of general and special methods and approaches: systemic and sociological. The COVID-19 pandemic has forced society to become virtual, most life processes have moved from real life to cyberspace, such as education, and people have become more able to communicate on social networks. However, the links that arise in the virtual space of social networks are weaker, and not always the expected collective action of the social group can justify itself from the standpoint of the number of participants or the goal, it is not always adequately transferred from the virtual world to the real. This is due to the fact that in the virtual world, social connections are built on a horizontal basis and do not involve vertical relationships. And such relations do not have the features of the forma­tion of collective action, which are inherent in the real, material world. The study surveyed respondents of different ages. The results of the survey showed that the basis for the formation of collective action, and identity in social networks are dominated by values and moral and ethical attitudes within the group, which determine the peculiarity of collective action and society in these real conditions and determine the development of society. After all, 58.5% of respondents clearly stated that the social networks in which they are members have an impact on them. That is, the social network under these conditions is almost the main fac­tor in the formation of personality and self. Displace attention on possibility of grant of educational services in the conditions of pandemic and war, using vir­tual space. Taking for basis philosophy of studies during life, it is shown that the virtual world gives equal possibilities all wishing to get education or additional knowledge regardless of age.
Transgressive dimension of the information society in the context of sustainable development: philosophical and praxeological analysis

In the second half of the twentieth century in the socio-political, economic, cultural life of society began transgressive changes that opened new prospects for the development of society in general and man in particular. The main civilizational tendencies that prompted these changes and continue to be affirmed in the 21st century are: firstly, the tendency towards global social development; secondly, humanity’s acquisition of the ability to self-derail, which is associated with the development of nuclear technologies and global environmental problems; thirdly, the transition of humanity from industrial to scientific and information technologies. It was these trends that initiated the transition to a new type of organization of public life of people, which was called “information society”. Informationism is a strategy to focus on information technologies development, to create multiple ways of accumulation of knowledge and to provide increasingly complex information processing. However, when it comes to the formation of an information society, it is understood not only as a stage of technological development, but as a new stage of spiritual development of mankind. For the first time, the information society produces in the general social volume such features of social existence, which require new approaches to the formation of structural, functional and value components of the social organism. The education system within the framework of the new paradigm is designed to function as a direct generator of new social realities that produces social changes. Accordingly, the educational circuit, as the institutional functioning of a certain value system, should cover all spheres of life, become the core of sustainable social development in general.
Diversification-oriented accuracy prediction in recommender systems

Tremendous amount of data generated by e-commerce users on items (e.g., purchase or rating history), sets some key challenges for the online knowledge discovery scheme. Recommendation systems are an important element of the digital marketplace such as e-stores and service providers that use the generated information to discover preferred products of the consumers. Developing an effective recommender system that produces diverse suggestions without compromising the precision of the customised list is challenging for online systems. This paper aims at diversifying recommendation by integrating graph-based algorithm supported with significant nearest neighbour strategy for enhancing recommendation precision. The experimental efficacy on the 100K dataset of MovieLens shows that the proposed hybrid model has a strong coverage and superior efficiency in product recommendations.
Design of Integrated Energy Market Service System Based on Blockchain Smart Contract

There are some problems in the traditional integrated energy market, such as single transaction mode, difficulty in effective dispatch, and lack of targeted subject to provide integrated energy market services. Therefore, this paper designs an integrated energy market service system based on the blockchain smart contract. The participants in the integrated energy market are divided into integrated energy suppliers, integrated energy users and integrated energy service providers. The integrated energy service providers set up energy trading centres and energy dispatch centres according to the needs of integrated energy suppliers and integrated energy users, and provide energy trading and dispatch services for them by using the Digital Currency Electronic Payment (DCEP) of the central bank and the blockchain smart contract. “Antchain” platform is used to simulate the energy trading and dispatch process, and the verifiable simulation results are given. It is proved that the integrated energy market service system based on the blockchain intelligent contract designed in this paper can effectively realize the security and convenience of energy trading and the efficiency and intelligence of energy dispatch.
Using open source software securely

These days, open source software provides many of the building blocks for most new applications, and with good reason: it empowers developers and organisations to innovate more flexibly and build applications faster and more efficiently. However, its powerful benefits need to be understood in the context of mitigating security risks and, in particular, preventing vulnerabilities that might arise during the development process.
A Taxonomy of Quantum Computing Algorithms

Quantum computing exploits quantum-mechanical principles such as entanglement and superposition to offer significant computational advantages over conventional classical computing. Many complex and computationally challenging problems are expected to be solved by quantum computing in a number of fields, such as data science, industrial chemistry, smart energy, finance, secure communications, and many others. In order to understand the current status of quantum computing and identify its challenges, a systematic review of the existing literature will be valuable. An overview of quantum computing literature and its taxonomy is presented in this chapter. Further, the proposed taxonomy aims to identify research gaps by mapping various related studies. There is a detailed analysis of quantum technologies with the most current state of the art. Finally, the chapter presents a highlight of open challenges and future research directions.
Secrecy Capacity-Approaching Neural Communications for Gaussian Wiretap Channel

Recently, some researches are devoted to the topic of end-to-end learning a physical layer secure communication system based on autoencoder under Gaussian wiretap channel. However, in those works, the reliability and security of the encoder model were learned through necessary decoding outputs of not only legitimate receiver but also the eavesdropper. In fact, the assumption of known eavesdropper’s decoder or its output is not practical. To address this issue, in this paper we propose a dual mutual information neural estimation (MINE) based neural secure communications model. The security constraints of this method is constructed only with the input and output signal samples of the legal and eavesdropper channels and benefit that training the encoder is completely independent of the decoder. Moreover, since the design of secure coding does not rely on the eavesdropper’s decoding results, the security performance would not be affected by the eavesdropper’s decoding means. Numerical results show that the performance of our model is guaranteed whether the eavesdropper learns the decoder himself or uses the legal decoder.
A Cross-Modal Attention and Multi-task Learning Based Approach for Multi-modal Sentiment Analysis

With the rapid development of multimodal research, deep multimodal learning model can effectively improve the accuracy of sentiment classification, and provide important decision support for many applications, such as product reviews, emotion analysis, rumor detection et. Aiming at the problem of feature representation and feature fusion in multimodal sentiment analysis, a model based on multi-task learning and attention mechanism is proposed. Firstly, bi-directional LSTM unit is used to extract the intra-modality representation of single modality. Secondly, the attention mechanism is used to model inter-modality dynamics. Finally, we introduce multi-task learning by predicting sentiment and emotion simultaneously. Experimental results on CMU-MOSEI dataset shows that proposed model outperforms baselines in terms of accuracy and F1-score.
Matching Based Intelligent Edge Resource Allocation

With the rapid development of the Internet of Things, multi-access edge computing (MEC) has emerged as a key technique and intelligent edge resource allocation has become one of the important research issues in MEC. In this paper, we utilize advantages of matching game to integrate users’ needs and the position of edge computing nodes in IoT networks. The proposed GS-based two-sided matching approach simulates the competition and negotiation relationship between different user sets in IoT edge nodes, and provides feasible options based on the preference between different entities. Simulations show that it not only solves the problem of edge resource allocation in a semi-distributed manner, but also effectively improves SP’s revenue.
Simulation of Bloch Sphere for a Single Qubit

The Bloch sphere is a generalisation of the complex number z with |z|2 = 1 being represented in the complex plane as a point on the unit circle. The goal of the research is to create a simulation that can be used to visualise a Bloch sphere of a single quantum bit, also known as a Qbit. QISKIT (developed by IBM) is an open-source lab for education in the realm of quantum computing, and is used to test and validate this simulator. This study made use of both quantitative and qualitative methods of investigation.
Evaluating the Most Effective Solar Panel by ENTROPY and COPRAS Methods

The terms “sustainable development” and “sustainability” have become more popular because of the critical troubles faced through mankind such as growing humankind effect on ecology and the risk of energy source depletion. Solar energy is one of the most rapidly developing sources of sustainable energy available today. The solar panel is the foundation of a photovoltaic system. In this study, the COPRAS and ENTROPY methods have been applied to select the most effective solar panel (100W) for a solar farm design. The five various solar panel brands have been evaluated, and professionals' choices have been dependent on the most important characteristics of the solar panels. From the top panel firms worldwide, the solar panel data utilized in this chapter is obtained. The most effective panel selection has been analyzed to affect the solar panel property potency employing in scales, in conjunction with several competing solar panels from which corporations must choose the top requirements, using COPRAS and ENTROPY techniques.
Quantum Software Engineering and Technology

Quantum technology works with and relies on sub-atomic particles or physics that operates on the quantum level. Quantum computing has become a mature field, having diversified applications in supply chain and logistics, chemistry, economics and financial services, energy and agriculture, medicine and health, etc. In the recent years, companies have started to incorporate quantum software to benefit the research and the practitioner communities. Software engineering and programming practices need to be brought into the domain of quantum computing. Quantum algorithms provide the ability to analyze the data and offer simulations based on the data. A few of the quantum computing programming languages include QISKit, Q#, Cirq, and forest are used to write and run quantum programs. In this chapter, the authors provide an overall picture of the problems and challenges of developing quantum software and up-to-date software engineering processes, methods, techniques, practices, and principles for the development of quantum software to both researchers and practitioners.
Impediment of Infodemic on Disaster Policy Efficacy: Insights from Location Big Data

Infodemics impede the efficacy of business and public policies, particularly in disastrous times when high-quality information is in the greatest demand. This research proposes a multi-faceted conceptual framework to characterize an infodemic and then empirically assesses its impact on the core mitigation policy of a latest prominent disaster, the COVID-19 pandemic. Analyzing a half million records of COVID-related news media and social media, as well as .2 billion records of location data, via a multitude of methodologies, including text mining and spatio-temporal analytics, we uncover a number of interesting findings. First, the volume of the COVID information incurs an inverted-U-shaped impact on individuals’ compliance with the lockdown policy. That is, a smaller volume encourages the policy compliance, whereas an overwhelming volume discourages compliance, revealing negative ramifications of excessive information about a disaster. Second, novel information boosts policy compliance, signifying the value of offering original and distinctive, instead of redundant, information to the public during a disaster. Third, misinformation exhibits a U-shaped influence unexplored by the literature, deterring policy compliance until a larger amount surfaces, diminishing informational value, escalating public uncertainty. Overall, these findings demonstrate the power of information technology, such as media analytics and location sensing, in disaster management. They also illuminate the significance of strategic information management during disasters and the imperative need for cohesive efforts across governments, media, technology platforms, and the general public to curb future infodemics.
Video Extensometer with Telecentric Illumination System Based on Cmos Camera Under Tensile Testing of Structural Steel

Steel structures experience plastic deformation and damage during large earthquakes. The stress-strain (S-S) curve of structural steel can be used to develop a constitutive model to simulate its structural behavior. The S-S curve can be obtained by video extensometers, whose efficiency with a telecentric lens and telecentric illumination remains unclear. In this study, the basic properties of a telecentric lens and telecentric illumination system for video extensometers were investigated. Rigid-body motion and tensile testing were performed and the carrier of displacement of six gauge lengths was traced. Further, N images were obtained under a constant displacement/force and averaged to reduce the pseudo strain. Experimental results showed that the pseudo strain increases with the out-of-plane rigid displacement but remains unaffected by the in-plane rigid-body displacement. Tensile testing results showed an error difference of less than 10% for the Young’s modulus obtained from the video extensometer and strain gauge.
Does Utilizing Smart Contracts Induce a Financial Connectedness Between Ethereum and Non-Fungible Tokens?

The majority of NFTs utilize the platform of Ethereum blockchain to accommodate smart contract facilities. In this paper, we analyze if this technical dependence induces a financial linkage in the risk, return, and prices of these assets. As a robustness check, we also test the same relation between Bitcoin and NFTs. The results of the DCC-GARCH model reveal that NFTs have had high correlations with both Ether and Bitcoin across the years. Bootstrap causality tests suggest that most of the relations between NFTs-Ether and NFTs-Bitcoin occur either in negative or positive return components rather than symmetric causal nexus. Finally, the findings obtained from return and volatility spillovers indicate that the extent of risk and return contributions of Ether and Bitcoin to NFTs are very close. As results suggest, portfolios that contain NFTs, Ether and Bitcoin may be exposed to significant losses, especially in the following periods of bubble formations.