Reviewerly/exHarmony huggingface dataset:
Identification of Violent Response with Stretch Sensor Data from a Smart-Jacket using Naïve Bayes Algorithm

In this paper, a smart-jacket using stretch sensors, pressure sensors was built for purpose of generating body-movements data and in order to record different kinds of signals and the distribution of the same on the jacket. Every degree of motion, when exercised, generates voltage changes in the stretch sensors as it is its property to do so. This data is collected in a flora chip set, which is Arduino based. The collected data is processed, pruned and filtered for outliers. This paper concerns with a supervised learning algorithm called Naive Bayes, which is applied over independent datasets, meaning one set of observation has no direct relations to each other. The placement of sensor are on the shoulders and elbows and the responses from each are independent of each other. Using Naive Bayes, the date has been classified for the violent response and the normal action.
Using Spyder to Construct a Digits Recognition System

An experiment was carried out primarily to build a system that can recognize digits then optimize the system. In every country, people only use a small portion of entire words and language structures in daily life’s communication. Therefore, it is possible to build such a system on a software named spyder. The first stage was to program the software to enable it can sample the speech, next converted it into the form that could be recognized by the computer, then train it with a structure consisting of nodes and layers. It would output the trained result. In case the software confused some digits with similar pronunciation, the next stage was to improve it. This experiment successfully realized all the goals. It would be constructive to extend the speech database and add the number of speakers to test the system.
Asymptotic bounds for spherical codes

The set of all error-correcting codes $C$ over a fixed finite alphabet $\mathbf{F}$ of cardinality $q$ determines the set of code points in the unit square $[0,1]^2$ with coordinates $(R(C), \delta (C))$:= (relative transmission rate, relative minimal distance). The central problem of the theory of such codes consists in maximising simultaneously the transmission rate of the code and the relative minimum Hamming distance between two different code words. The classical approach to this problem explored in vast literature consists in inventing explicit constructions of "good codes" and comparing new classes of codes with earlier ones. Less classical approach studies the geometry of the whole set of code points $(R,\delta)$ (with $q$ fixed), at first independently of its computability properties, and only afterwards turning to the problems of computability, analogies with statistical physics etc. The main purpose of this article consists in extending this latter strategy to the domain of spherical codes. Bibliography: 14 titles.
Presentation System of Operating Histories to Support Choice and Operation of Tools for Beginners of Text Mining Software TETDM

Data analysis has been conducted in business operations in many fields. Analysis of text data like comments of questionnaires and reviews on the Web is also required. Most of the data analysis is conducted by using the software. The data analysts need to acquire knowledge of the software usage and mining operations. Some of the software provide instructions and tutorials about how to use. However, if the analysts are beginners of data analysis, the instructions and tutorials can not tell how to choose appropriate tools and how to operate the tools for their analysis purpose.
Perturbations of Atmospheric Surface Layer Characteristics During the Annular Solar Eclipse on 26 December 2019 Over a Semi-Arid Region Anantapur in Southern India

The annual solar eclipse (ASE) occurred on 26 December 2019, which was visible most of the South Indian subcontinents greater than 80% obscurity, particularly during the morning hours, and it played a crucial role significant change in the atmospheric dynamics. Ground-based measurements were used to investigate the fluctuations of air temperature, relative humidity, atmospheric pressure, wind speed and direction, UV-A radiation and turbulence parameters on solar eclipse day over a semi-arid region, Anantapur, in Southern India. The all Surface Layer (SL) meteorological parameters are abruptly changed on eclipse day (26 December 2019) as compared to the control day (27 December 2019). During eclipse day, the near-surface air temperature was significantly decreased (1.12 ℃), and relative humidity increased (14.63%) after 60 min of the beginning of the eclipse, which mainly due to cooling the surface. The atmospheric pressure was reduced by 0.9 hPa during the eclipse period, and the magnitude of the winds speed also reduced to 0.92 ms -1 due to the stabilization of Atmospheric Boundary Layer and cooling in the SL. The turbulence parameters include Sensible Heat Flux (SHF), Momentum Flux (MF), and Turbulent Kinetic Energy (TKE) are also reduced by 0.91 Wm -2 , 0.2 Nm -2 , and 0.37 m 2 s -2 , respectively during the eclipse day, which mainly due to eclipse cooling effect diminishing the turbulence in Atmospheric Surface Layer (ASL). The lowest values of friction velocity were observed (0.18ms -1 ) during the eclipse day, and the Monin–Obukhov stability parameter showed a variation in the atmospheric stability from weakly unstable to neutral conditions during the eclipse day. The vertical winds speed showed strong downdrafts during the eclipse and even after the eclipse due to subsidence of air. The investigation revealed that the ABL dynamic process and turbulence processes are affected due to cut off of solar radiation and make the SL cooling.
Animal Detection in Highly Cluttered Natural Scenes by using Faster R-CNN

With the increasing awareness of environmental protection, people are paying more and more attention to the protection of wild animals. Their survive-al is closely related to human beings. As progress in target detection has achieved unprecedented success in computer vision, we can more easily tar-get animals. Animal detection based on computer vision is an important branch of object recognition, which is applied to intelligent monitoring, smart driving, and environmental protection. At present, many animal detection methods have been proposed. However, animal detection is still a challenge due to the complexity of the background, the diversity of animal pos-es, and the obstruction of objects. An accurate algorithm is needed. In this paper, the fast Region-based Convolutional Neural Network (Faster R-CNN) is used. The proposed method was tested using the CAMERA_TRAP DATASET. The results show that the proposed animal detection method based on Faster R-CNN performs better in terms of detection accuracy when its performance is compared to conventional schemes
Investigating the Effect of Sensitivity and Severity Analysis on Fault Proneness in Open Source Software

Fault prone components in open source software leads to huge loss and inadvertent effects if not properly identified and rigorously tested. Most of the reported studies in the literature have applied design metrics alone, to identify such critical components. But in reality, some of the components' criticality level can be identified only by means of dynamic code analysis; as some of the components seem to be normal but still have higher level of impact on the other components. This leads to an insight on the need of a rigorous analysis based on how sensitive a component is and how severe will be the impact of it on other components in the system. To achieve this, an efficient mechanism of evaluating the criticality index of each component by means of sensitivity and severity analysis using the static design metrics and dynamic source code metrics has been proposed. Then, testing is conducted rigorously on these components using both unit testing and pair-wise integration testing.
Zero-Crossing Analysis of Lévy Walks and a DDoS Dataset for Real-Time Feature Extraction

A comparison between the probability similarities of a Distributed Denial-of-Service (DDoS) dataset and Lévy walks is presented. This effort validates Lévy walks as a model resembling DDoS probability features. In addition, a method, based on the Smirnov transform, for generating synthetic data with the statistical properties of Lévy-walks is demonstrated. The Smirnov transform is used to address a cybersecurity problem associated with the Internet-of-things (IoT). The synthetic Lévy-walk is merged with sections of distinct signals (uniform noise, Gaussian noise, and an ordinary sinusoid). Zero-crossing rate (ZCR) within a varying-size window is utilized to analyze both the composite signal and the DDoS dataset. ZCR identifies all the distinct sections in the composite signal and successfully detects the occurrence of the cyberattack. The ZCR value increases as the signal under analysis becomes more complex and produces steadier values as the varying window size increases. The ZCR computation directly in the time-domain is its most notorious advantage for real-time implementations.
Cloud Governance at the Local Communities

This chapter conceptualizes the plan of an autonomous community to cover the information technology needs by adopting cloud computing on a community level. Community cloud computing is a solution with many advantages that can help the community to cover sufficiently their technology needs or even generate income by renting virtual resources. This is a theoretical approach that can be used as a conceptual tool for small municipalities or other communities that intend to extend their technological and political autonomy.
Online learning and digital competence: Ukraine and the world

The article is devoted to strengthening the role and importance of online learning and digital competence of teachers and students in the context of globalization and accelerating scientific and technological progress. A comparative analysis of the development of ICT, relevant electronic devices and the introduction of open online courses in the world is done. The main difficulties, shortcomings and achievements in the process of accelerating the dynamics and scale of application of online and distance learning during the lockdown period caused by the coronavirus pandemic are defined. The examples of Ukraine and the European Union show a significant difference between the countries of the world in terms of the development of material and technical base of educational institutions, digital infrastructure, access to high-quality and high-speed Internet, readiness of teachers and students to study in new conditions. There is a significant gap between global scientific and technological development and digital competence of citizens. Based on the use of historical, logical, comparative methods, principles and laws of dialectics argues the need for a deeper and more systematic theoretical understanding of current trends in ICT, rapid improvement of digital competence, especially the teaching staff. The importance of introducing in-depth, systematic and systematic research in Ukraine to assess the available technical resources, quality and prospects of digital infrastructure, the level of digital competence of citizens, the dynamics of online training courses, the impact of the social environment on education. The subject of analysis and strategic decision-making in the field of national digital policy should be relevant social, political, economic and technological problems in the country, improving the legal framework, technical re-equipment of educational institutions of all levels, increasing motivation, especially teaching staff for self-improvement and digital competence.
Enhanced Book Recommendation System using Collaborative Filtering

Students from many universities often struggle with picking the best books and study material for their various subjects. Teachers are also not well informed about books to pick in many cases. This could lead to lack of knowledge of a particular subject or students not being prepared well enough for their exams. It is paramount for these students to have solid and best recommendations about the books they should be picking for their courses. The motive of building this book recommendation system is to provide these universities and kids with a system that helps them with identifying proper study material for various subjects and provide them with online links to the books wherever possible. Every child is special and all of them deserve the best chance of getting in depth knowledge of the subjects not only for their exams, but also for future reference. This will help them develop themselves and have a solid understanding of the subject by studying from the best books available for that particular subject on the market. This would enable smaller universities to develop their education systems and try to be on par with top universities around the state and the country. The system would take input from the user in the form of text search or syllabus images. The images would be scanned for keywords regarding the subjects included. These keywords would then be used to draw results from the database with the help of filtering algorithms. The text search would also follow the same rule. Results would be shown to the user with the help of filtering algorithms working on the books database.
Verification Key Replacement Method for Equivalent Network File Systems

We hold in mind the issue of key purpose for relaxed many-to-numerous correspondences. the inconvenience is energized by way of approach for approach for the growth of first rate scale exceeded on record structures associate parallel the the front to diverse restrict devices. Our works of art offices around th e slicing side net fashionable for such record structures, i.e., parallel machine record device (pNFS), which makes utilization of Kerberos to accumulate parallel session keys amongst clients and restriction devices. Our observe of the forefront Kerberos-based totally really definitely display wellknown that it has distinct controls: (I) a metadata server empowering key trade among the customers and the capability devices has large first rate weight that confines the versatility of the meeting; (ii) the collection does now not talented vide ahead of time spine chiller; (iii) the metadata server makes itself most of the people of the communicate keys which may be related the unique customers a d storing devices, and this essentially enacts key escrow. on this paper, we underwrite an association of established key ex trade indicates which may be deliberate to comply to the above inconveniences. We display that our indicates are composed for reducing u p to more or extensively much much less fifty four% of the long-lasting assignment handy of the metadata server and simultaneously supporting in advance puzzle and escrow-freeness. This calls for maximum straightforward a chunk a bit of raised computation overhead on the customer
Cloud Security in E-Commerce Applications

In this chapter, the authors focus on the most fundamental barrier in the e-commerce application's adoption: security. The most significant or important aspect to explore in cloud computing is how to keep the data secure in the most efficient way with cutting-edge technologies. Cloud computing has taken its place by providing its convenient services like on-demand service, pay-per-use, rapid elasticity, resource pooling, and other lucrative facilities. In this chapter, the authors will firstly describe the introduction related to cloud computing, major characteristics, types, and a few security concerns and issues in cloud computing. Furthermore, they discuss the introduction of e-commerce applications, how it is interlinked with cloud computing, and what the possible threats are. Moreover, what the possible solutions could be are discussed, so that we can secure data on both user side as well as on the server side. The authors suggest some existing solutions at the end of the chapter.
A Yes/No Answer Generator Based on Sentiment-Word Scores in Biomedical Question Answering

Background and Objective: Yes/no question answering (QA) in open-domain is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in the biomedical domain. Yes/no QA aims at answering yes/no questions, which are seeking for a clear “yes” or “no” answer. In this paper, we present a novel yes/no answer generator based on sentiment-word scores in biomedical QA. Methods: In the proposed method, we first use the Stanford CoreNLP for tokenization and part-of-speech tagging all relevant passages to a given yes/no question. We then assign a sentiment score based on SentiWordNet to each word of the passages. Finally, the decision on either the answers “yes” or “no” is based on the obtained sentiment-passages score: “yes” for a positive final sentiment-passages score and “no” for a negative one. Results: Experimental evaluations performed on BioASQ collections show that the proposed method is more effective as compared with the current state-of-the-art method, and significantly outperforms it by an average of 15.68% in terms of accuracy.
Applications of Keystroke Dynamics Biometrics in Online Learning Environments

The biometric authentication in the online learning environment (OLE) is still exploratory and, despite an increase in keystroke dynamics biometrics research, many challenges remain in designing this authentication system due to the fact that it is economical and easily integrated with existing computer security system in OLE. Existing research in keystroke dynamics tends to focus on finding how keystroke dynamics of users can support non-intrusive authentications of users in OLEs. However, there is little evidence that researchers have approached the issue of unauthenticated users to take the role of authenticated users and perform tasks in the OLE with the intent of building models based on the keystroke dynamics of users. In a nutshell, the aim of this chapter is to provide an overview of the existing applications of keystroke dynamics as biometric authentication in the OLE, keystroke dynamics framework being designed for the OLE, advantages and disadvantages of a keystroke dynamics biometrics approach, as well as offering suggestions and possible future research directions.
An Introduction to the Business Ontology

Based on the long-standing work of the Global University Alliance and its members, ontology is introduced for the business domain. This ‘business ontology' incorporates all the constructs that can be found in the most popular business standards and frameworks. The business ontology's research and development journey is detailed; in terms of the how the research and findings came about, including the underlying academic design science that is informed by practitioners' industrial experiences. It explains the value of ontology, from which the need for the business ontology can be justified and gives it presence in business practice. The paper concludes with a discussion on the ontology's present status and future potential.
Multi-Objective Scheduling Model for OpenStack-Based Cloud

Efficient and flexible resource management is a critical issue in cloud computing context. At first, we study the scheduling process of virtual machine in Open Stack cloud platform in detail. And then propose a new model considering multiple parameters such as memory, CPU utilization and current workload of the hosts. This work proposes for the use of machine learning classifier to classify whether host is overloaded or under loaded, focuses on PSO based VM scheduling strategy for VM placement in cloud infrastructure. Experimental results show that proposed algorithm outperforms default scheduler and it leads to efficient usage of underlying resources of hosts.
Semantic Interoperability-Enabled Architecture for Connected Health Services

With the increasing availability of connected health organisations, key medical information is expected to be accessible at the point of care. However, the high sensitivity of the clinical data and the large heterogeneity in health information systems pose a great interoperability challenge, including solutions that rely solely on the use of data exchange standards. Due to low adoption of these standards, such solutions will not sufficiently scale to achieve this objective. This chapter presents a service-based approach that utilises domain models combined with extensible problem models, enriched with domain terminology and knowledge services to enable autonomous data governance and semantic interoperability. The chapter addresses the resulting requirements, describes the proposed a solution and reports the results from the prototype of the approach.
Exploring Information Security Governance in Cloud Computing Organisation

The paper reveals factors impacting information security governance within the cloud computing technology implementation in organizations. Case study methodology was used and 15 semi-structured interviews were conducted with directors and information security professionals from 5 different types of organizations. The main component that were identified as playing a significant role in information security governance were: information security strategy, security policies and procedure, risk management and assessment program, compliance and standard, monitoring and auditing, business continuity and disaster recovery, asset management and access control and identity management. The results show that awareness through education and training of employees needs to be given very particular attention in cloud computing security. The paper does not include any end-user perspective in interviews and this end-user context is missing. Companies need to focus upon awareness through education and training of employees. Moreover, management and employee support is the critical component of the effective information security governance framework implementation. Also, organisations should develop their information security using a very precise and detailed planning process that ensures the right cloud computing acceptance by the users. The proposed information security governance framework offers organisations a holistic perspective for governing information security, and minimizes risk and cultivates an acceptable level of information security culture.
Object Interaction Detection Based on Convolutional Neural Network

Vision gives people a strong recognition ability, and people can easily see various objects. With the popularity of smart phones and the development of the Internet, pictures and videos have become an important way for people to record their lives and share information. They are created so fast that no one can search them all, but the wealth of information they contain is very important to people. Therefore, this article is based on the convolutional neural network to study the object interaction detection. First of all, this article discusses the basic concepts of convolutional neural networks, and conducts corresponding research on the convolution algorithm, and then studies the method of object interaction detection. After that, the performance of traditional neural network and convolutional neural network in object interaction detection is tested and researched. The test results show that the convolutional neural network is faster than the traditional neural network algorithm in the four types of performance of image generation speed, object feature extraction speed, object classification speed, and object detection accuracy.