Reviewerly/exHarmony huggingface dataset:
Brief Tour of Wavelet Theory

In this chapter, the main definitions of wavelet theory are given. To explain the basic ideas of the continuous wavelet transform, we describe a transition from Fourier analysis to wavelets. Mother functions and numerical techniques for implementing the wavelet transform are described. The problem of visualising the results is considered. Finally, features of the discrete wavelet transform are discussed.
Semantic Textual Similarity on Brazilian Portuguese: An approach based on language-mixture models

The literature describes the Semantic Textual Similarity (STS) area as a fundamental part of many Natural Language Processing (NLP) tasks.The STS approaches are dependent on the availability of lexical-semantic resources.There are several efforts to improve the lexicalsemantics resources for the English language, and the state-of-art report a large amount of application for this language.Brazilian Portuguese linguistics resources, when compared with English ones, do not have the same availability regarding relation and contents, generation a loss of precision in STS tasks.Therefore, the current work presents an approach that combines Brazilian Portuguese and English lexical-semantics ontology resources to reach all potential of both language linguistic relations, to generate a language-mixture model to measure STS.We evaluated the proposed approach with a well-known and respected Brazilian Portuguese STS dataset, which brought to light some considerations about mixture models and their relations with ontology language semantics.
Introduction

This chapter explains the background of the study and highlighted the issue and rationale of the study. The research objectives were formulated from the research background, problem statement, rationale of the study and the area to improve the study. The benefit, the significance of the study, scope and limitation also indicates in this chapter to ensure the objectives of the research conducted accordingly hence to predict the condition of Government building. The chapter also focuses on the literature overview on the building defects which related to the study.
Psychological and Pedagogical Characteristics of Elder Preschool Children

This article examines the importance of teaching a foreign language to preschool children. Particular attention is paid to the psychological and pedagogical characteristics of older preschool children in the study of a foreign language.
Trusting Artificial Intelligence in Cybersecurity Is a Double-Edged Sword

Applications of artificial intelligence (AI) for cybersecurity tasks are attracting greater attention from the private and the public sectors. Estimates indicate that the market for AI in cybersecurity will grow from US$1 billion in 2016 to a US$34.8 billion net worth by 2025. The latest national cybersecurity and defence strategies of several governments explicitly mention AI capabilities. At the same time, initiatives to define new standards and certification procedures to elicit users’ trust in AI are emerging on a global scale. However, trust in AI (both machine learning and neural networks) to deliver cybersecurity tasks is a doubleedged sword: it can improve substantially cybersecurity practices, but can also facilitate new forms of attacks to the AI applications themselves, which may pose severe security threats. We argue that trust in AI for cybersecurity is unwarranted and that, to reduce security risks, some form of control to ensure the deployment of ‘reliable AI’ for cybersecurity is necessary. To this end, we offer three recommendations focusing on the design, development and deployment of AI for cybersecurity.
Recognizing Driving Behavior and Road Anomaly Using Smartphone Sensors

Road traffic accidents are caused 1.25 million deaths per year worldwide. To improve road safety and reducing road accidents, a recognition method for driving events is introduced in this paper. The proposed method detected and classified both driving behaviors and road anomalies patterns based on smartphone sensors (accelerometer and gyroscope). k-Nearest Neighbor and Dynamic Time Warping algorithms were utilized for method evaluation. Experiments were conducted to evaluate k-nearest neighbor and dynamic time warping algorithms accuracy for road anomalies and driving behaviors detection, moreover, driving behaviors classification. Evaluation results showed that k-nearest neighbor algorithm detected road anomalies and driving behaviors with total accuracy 98.67%. Dynamic time warping algorithm classified (normal and abnormal) driving behaviors with total accuracy 96.75%.
Anthrophilia* Algorithm

Optimization nowadays is not a choice. We need a system of check and balance in any dynamic system. For this, we must have a general system of equations, some mathematical model, some much generalized yet fundamentally strong algorithm having large domain of applications. We need to understand all the visible constraints which presently cannot be ignored. Simultaneously, we must realize the demand of the situation and the limitations of the present algorithms. By algorithms, we mean those who definitely reach out to global optima in finite time. Such techniques are lagging in situations where the goal is to achieve states which are, in general, functions bounded by variable constraints (Krumke in Wireless networks 7(6):575–584, [1]). Hence, this is the time when we look for an algorithm which is multidimensional, recursive and is expected to reason fastest to the solution when several variable boundaries are on the line.
Analysis of the Application of Internet Information Technology in the Formative Evaluation of Spanish Teaching in Colleges and Universities

In Spanish teaching in colleges and universities, objective evaluation of students’ language learning is conducive to the improvement of students’ language learning ability. However, the current evaluation system used in Spanish teaching in colleges and universities has certain drawbacks, and it is difficult to make a comprehensive evaluation of the students’ language learning process. In view of this, Internet information technology is used in the formative evaluation of universities in Spain. This article puts forward the theory of formative evaluation and advocates the application of Internet information technology to the evaluation system. With the help of information technology, it realizes the diversification of evaluation subjects and promotes the continuous improvement of Spanish teaching evaluation.
Novel Technique for Control of Industrial Robots with Wearable and Contactless Technologies

This work ensures the usability of wearable and non-contact sensor technologies in the industrial field. In this study, it is aimed that operators can easily control industrial robots in real time without the need for a specialized programming environment. For this purpose, a new human robot interface, in which industrial robots can be controlled by hand movements, has been created. In this interface, Leap Motion Controller(LMC), which uses an IR Camera for the control of robot arm positioning and motion trajectories, and MYO armband, which detects wrist and hand movements with EMG sensors, is used for the control of Robot end effector (tool) actions. Robot movements are controlled by industrial communication after hand movements, classification and data processing stages with high accuracy. Various robotic processes such as holding, transporting and painting will be carried out easily and flexibly without the need for programming.
Implementation of Parallel Algorithms for Liquid Metal Solidification Molecular Dynamics Based on Big Data

With the advancement of science and technology and the popularization of the Internet, large amounts of data and information will be generated from people's daily work and life to the state of molecular motion trajectories. How to efficiently mine the hidden information of these massive data information is the key to scientific and social development, which requires big data analysis technology. The solidification process of metals is a very complex process, including both macroscopic and microscopic processes. Molecular dynamics can simulate the process of liquid metal solidification from a microscopic scale. In molecular dynamics simulation, the more particles the simulation system contains, the more accurate the data obtained. However, the molecular dynamics serial program runs slowly, and the number of simulated atoms is limited, which makes the simulation results far from the real situation. The rise of parallel computing provides conditions for large-scale molecular dynamics parallelization and promotes the rapid development of molecular dynamics parallelization. The purpose of this paper is to study the dynamic parallel algorithm of liquid metal solidification molecules based on big data. In this paper, through in-depth research on big data, analysis of the current research results of parallel computing of liquid metal solidification molecules, and combined with the current research status of liquid metal solidification molecules in my country, to discuss the research of liquid metal solidification molecular dynamics parallel algorithm under big data. Research shows that the spatial domain decomposition method is more general, and its communication cost is relatively small. It reflects that it can obtain relatively high parallel performance and computing efficiency in local communication, especially in large-scale simulation systems with a large number of atoms.
Research Progress in the Field of Image Completion

Image completion technology is a challenging research direction in the field of image restoration. The traditional image completion technology mainly fills the missing areas with missing values based on the information of the unmissed areas of the image. Traditional image completion can well complement images with a small missing area and relatively simple texture structure, but it does not work well for images with large missing areas or complex texture structures. With the continuous development of deep learning, the performance of image restoration has been significantly improved. The image completion method based on deep learning can learn the high-level features of the image, so that the result of the completion is more realistic. This article reviews the image completion technology, introduces the basic principles of typical methods and compares their advantages and disadvantages. Finally, we analyze the future research directions in this field and put forward prospects.
Selection of Renewable Energy Sources for Buildings

This chapter describes a general issue of selecting renewable energy sources (RES) and technical systems. To achieve the nearly zero-energy building (nZEB) standard, application of an RES (e.g., solar, wind, geothermal, hydropower, and biomass energy) is necessary. Each type of RES has specific characteristics and can be used to produce electricity and/or heat in certain systems. A short review of various systems using renewable energy sources is presented. To find the required and satisfactory solution that guaranties meeting the nZEB standard, an analysis must be carried out considering a number of aspects: local availability, structure and time-dependence of energy demand, building construction, economic conditions, legal regulations, and specific requirements. Finally, two examples of modernisation towards the nZEB standard are included.
A Literature Review on Image Encryption Techniques

Encryption is one of the techniques that ensure the security of images used in various domains like military intelligence, secure medical imaging services, intranet and internet communication, e-banking, social networking image communication like Facebook, WhatsApp, Twitter etc. All these images travel in a free and open network either during storage or communication; hence their security turns out to be a crucial necessity in the grounds of personal privacy and confidentiality. This article reviews and summarizes various image encryption techniques so as to promote development of advanced image encryption methods that facilitate increased versatility and security.
Coauthentication

This paper introduces and evaluates collaborative authentication, or coauthentication, a single-factor technique in which multiple registered devices work together to authenticate a user. Coauthentication provides security benefits similar to those of multi-factor techniques, such as mitigating theft of any one authentication secret, without some of the inconveniences of multi-factor techniques, such as having to enter passwords or biometrics. Coauthentication provides additional security benefits, including: preventing phishing, replay, and man-in-the-middle attacks; basing authentications on high-entropy secrets that can be generated and updated automatically; and availability protections against, for example, device misplacement and denial-of-service attacks. Coauthentication is amenable to many applications, including m-out-of-n, continuous, group, shared-device, and anonymous authentications. The principal security properties of coauthentication have been formally verified in ProVerif, and implementations have performed efficiently compared to password-based authentication.
The Fundamentals of Human-Computer Interaction

This chapter explains the overview of human-computer interaction (HCI); cognitive models, socio-organizational issues, and stakeholder requirements; HCI and hand gesture recognition; and the multifaceted applications of HCI. HCI is a sociotechnological discipline whose goal is to bring the power of computers and communication systems to people in ways and forms that are both accessible and useful in the effective manner. HCI plays an important role in identifying the environmental and social issues that can affect the use of systems, and provide techniques to ensure the design of the system will be usable, effective, and safe. HCI draws on computer science, computer and communications engineering, graphic design, management, psychology, and sociology as it tries to make computer and communications systems ever more usable in executing tasks. HCI is an important consideration for any business that uses computers in their everyday operation.
Research on Mobile Teaching Design of Higher Vocational Education under Ubiquitous Network Technology-Taking ‘Basic Piano Course’ as an Example

When designing the ‘Piano Basic Course’ teaching plan, the introduction of ubiquitous mobile thinking can improve the quality of piano education in higher vocational education. Based on this, this article discusses the advantages of using ubiquitous mobile mode in the teaching of basic piano courses, and elaborates on the teaching design of pre-class preparation, practice teaching design in class, teaching design after class, and teaching evaluation based on ubiquitous mobile technology. The design realizes an in-depth analysis of the ubiquitous and mobile design of piano teaching in higher vocational colleges, and aims to help the construction of higher vocational teaching systems.
The Cross-Cultural Analysis of Australia and Russia

The chapter examines the comparison of the cross-cultural analysis of the green country, Australia (NSW), and the northern country, Russia (Republic of Karelia). Based on the results of the analysis, it shows how a small business from Russia, Green Roofs, overcomes barriers in Australia through the application of blockchain technology. The authors hope that examples of development and thoughts about the driving sources of these transformations, chosen by taking into account the interests of the development of the Russian digital economy, can be interesting and useful for Russian enterprises, small businesses that have begun their digital transformations.
How Behavior Can Affect Performance

There has been a significant increase in studies about how behavior affects our daily lives. One question about behavior is how it can affect performance of individuals. Behavior is influenced by a variety of factors such as strategy and information. Previous studies have found significant differences in terms of voluntary information disclosures between firms the consistently netted positive performances. (Kashyap et al, 2020, p. 6) In 2004, Lo discovered a relation exists between risk and reward, and it is not very likely to be stable overtime. This study will seek to discover how behavior is influenced and how it affects net performance in a Trade Simulation data set. This is done through a Likert Scale analysis and three categorical groups of Information Condition, Strategy, and the Starting Sentiment of each participant in this study. Behavior was discovered to have an immediate impact on the net performance of the participants in this study.
Competent Asset Planning for Cloud Computing

Cloud Computing is being widely utilized in today’s world. The proposed system comes under the Iaas (Infrastructure as a service) which provides CPU and memory as a resource. As cloud computing is very popular, the users of cloud are also increasing accordingly and this has become the important issue for the cloud service providers in terms of load balancing. Each of the client requests has to be executed with proper allocation of assets. The major challenge is to understand how these requests are allocated to the user. Management of assets and allocation of assets has to be done proficiently so a s to increase the system utilization and also overall performance of the system else this becomes the serious issue for governing the cloud environment with multiple customers. In the proposed system dynamic load balancing concepts have been used which helps in fair allocation of resources to achieve high user satisfaction as well as proper asset utilization. This proposed model has a Controller and Balancers that gather and analyze the information. Status of the server is monitored and then appropriate load balancing techniques selected on the basis of system status as a achieve resource utilization.
Trust, Privacy, Issues in Cloud-Based Healthcare Services

In recent era individuals and organizations are migrating towards the cloud computing services to store and retrieve the data or services. However, they have less confidence on cloud as all the task are handled by the service provider without any involvement of the data owner. Cloud system provides features to the owner, to store their data on some remote locations and allow only authorized users to access the data according to the role, access capability or attribute they possess. Storing the personal health records on cloud server (third party) is a promising model for healthcare services to exchange information with the help of cloud provider. In this chapter, we highlight the various security issues and concerns such as trust, privacy and access control in cloud based healthcare system that needs to be known while storing the patient's information over a cloud system.
Generative Wavelet-Multilayer Perception Feature Fusion Method for Zero-Shot Learning

For zero-shot learning, a Generative WaveletMultilayer Perception Feature Fusion (GWMPFF) method is proposed. In GWMPFF, the Generative Adversarial Networks(GAN) is used to generate virtual samples from unseen classes to alleviate the domain shift problem. Considering that the sensitivity of wavelet transform to contour information and high-frequency details is consistent with the characteristics of semantic description, a WaveletMultilayer Perceptron Feature Fusion (WMPFF) model is proposed to transform visual samples into semantic descriptions for classification. Finally, experiments on the standard datasets SUN and CUB demonstrate that the proposed method outperforms the comparison methods.
Analysis of a Training Package for Law Enforcement to Conduct Open Source Research

Law enforcement officials (LEOs) in the UK conduct open source research (OSR) as part of their routine online investigations. OSR, in this instance, refers to publicly available information that is accessed via the Internet. As part of the research, identifying and tracing the electronic suspect (RITES) course provided by the UK's College of Policing, LEOs are introduced to the open source internet research tool (OSIRT); a free software tool designed to assist LEOs with OSR investigations. This article draws on analyses from questionnaires and observations from a RITES course; mapping them to Kirkpatrick's evaluation model. Results showed the positive impact the RITES course had in transferring knowledge back on-the-job, with LEOs applying knowledge learned to real-life investigative scenarios. Additionally, results showed OSIRT integrated both in the RITES course and into the LEOs investigative routine.
A Mutli-feature Correlation Filter Tracker with Different Hash Algorithm

The discriminative correlation filter (DCF) does not work well in complex tracking scenarios. In order to improve the accuracy of object tracking, a new correlation filter tracker is proposed. We use the different hash algorithm to screen candidate samples, reduce the number of negative samples and improve the speed and accuracy of object tracking; combine the HOG feature with color histogram feature to acquire a robust object appearance model; design an adaptive fusion function to fuse the two features to obtain a more discriminative feature and improve the discriminability of the filter. Experiments on OTB2015 show that the proposed tracker has good accuracy in complex tracking scenes such as fast motion, background clutter, illumination variation, scale variation, etc.
The Human-IoT Ecosystem

IoT devices offer a cheap and powerful approach to identifying real world states and situations and acting on this real world environment to change these states and the environment. Augmenting real world things with IoT technology enables the capture of real world context to support decision making and actions in the real world via powerful smart objects in a human- IoT ecosystem. Increasingly we will have to understand the Human-IoT or smart device ecosystem interaction in order to optimise and integrate the design of human and IoT systems. This chapter explores the design and categorisation of IoT devices in terms of their functionality and capability to support context to add to human perception. It then proposes how we can model the context information of both IoT devices and humans in a way that may help progress Human-IoT Ecosystem design using situation theory.
Cloud Networking

The cloud computingCloud networking environment is huge and consists of several computational resources dispersed across different geographical locations. Unfortunately, resources get tied up when networks are used. This chapter aims to show how networks evolved from the simple design of a flat network model to a software-defined networking model for the cloud. By the end of this chapter the reader should have an overall idea about enterprise networking, cloud networkingCloud networking , and how they best work together to achieve business goals.
Introduction

Software engineering has grown to be one of the most important disciplines with noticeable impact to business and everyday life. However, there are still several challenges posed when developing and maintaining software, which often result in lost time and effort. In this chapter, we discuss how current challenges can be confronted using mining techniques toward applying software reuse. We initially focus on defining the scope and purpose of this book given the current state of the practice in software engineering. After that, the underlying context of software reuse is discussed with respect to the areas of requirements mining, source code mining, and quality assessment. For each of these areas, we outline the contributions of the book, and finally we provide an overview of the different chapters.