Reviewerly/exHarmony huggingface dataset:
Introduction

Studies on Chinese aspect are carried out by two groups of people. The first group focuses on the functionalities of the aspectual markers 着 zhe0 ‘ZHE’, 了 le0 ‘LE’ and 过 guo4 ‘GUO’, and the other focuses on classification of situation types. However, very few studies are concerned with the relations between the aspectual markers and situation aspects. Among the limited studies on situation aspect of Chinese, there are still issues remaining. This thesis describes a theoretical framework for aspectual classification with the combination of an ontological view of human perceived events/situations and the ways of how different types of situation are described in Chinese language with a particular viewpoint. For example, some aspectual verbs, such as 开始 kai1shi3 ‘start’, 结束 jie2shu4 ‘end’, 继续 ji4xu4 ‘continue’, 停止 ting2zhi3 ‘stop’, 完成 wan2cheng2 ‘finish’ and so on, are such linguistic operators that are used to shift the view to a part of a situation. I will show that the aspectual markers着 zhe0 ‘ZHE’, 了 le0 ‘LE’ and 过 guo4 ‘GUO’ are also devices that can shift the viewpoint of situations. This chapter describes the scope, goals, methodology and other related issues of the study. It also describes the organization of the whole thesis.
Data Representation and Image Processing

Scanning probe microscopy data usually have the form of a matrix where the topography (height) or some other signal such as the phase in dynamic AFM is measured as a function of the lateral xy-position on the surface. Data representation is the task to map the heights (i.e. the output of the z-controller) to gray levels in an image in an optimal way. Image processing is used in order to enhance the image representation further, i.e. by removing image artifacts such as high-frequency noise, noise pixels or noise lines (Klapetek, Quantitative data processing in scanning probe microscopy, 2nd edn. Elsevier, Amsterdam, 2018, [1]; Eaton, Batziou, Artifacts and practical issues in atomic force microscopy. In: Santos N, Carvalho F (eds) Atomic force microscopy. Methods in molecular biology, vol. 1886. Humana Press, New York, 2019, [2]).
DEVELOPMENT OF A MEASUREMENT TOOL TO EVALUATE THE LEARNING EXPERIENCE IN AN E-LEARNING SYSTEM

The purpose of this study is to find ways to monitor and evaluate the user experience of learners as they use an e-learning system.To do this, we have identified several factors that allow us to measure this experience.We have designed an online measurement scale, presented as a self-administered questionnaire, specifically dedicated to e-learning platforms.With this tool, we can quickly isolate aspects that are perceived as critical, and that often require improvement actions.Finally, we tested our measurement tool over two sessions of an online course.The results of statistical analysis are very encouraging, showing that the learning platform used is considered simple by learners, flexible, secure and encouraging autonomy.The results also show that the platform has a deficit of social interaction (interactions between learners and their teachers, as well as between pairs), which should be remedied in order to improve learners' experience.
Modern Information Technology, Global Risk, and the Challenges of Crime in the Era of Late Modernity

The rapidity and efficient use of most communication technologies remain the driver of accelerated developments across the major societies of the world today. This is quite exciting when compared to what existed in the past. However, current happenings indicate that the contribution of these technologies to sporadic development of nations is fraught with recordable socio-economic risks whose effect is unprecedented and affecting the nature of trust required for social continuity in human environment. Consequently, this paper considers the nature of risks and vulnerabilities affecting e-connectivity from a modernist theoretical perspective and contextualized this in the double edged implication affecting the use of the Internet. The first section of this paper is devoted to review on the nature of affinity between the Internet and crime while the final section engages the empirical analysis of secondary data on the consequences of cyber-crime to the global economy.
Toward a Model for Ethical Cybersecurity Leadership

With no clear model for ethical cybersecurity leadership, the field of cybersecurity is largely unregulated. The advances in technology and the Internet of Things come at a price—security. Since there is a lack of regulation, no clear guidelines exist. Furthermore, there is a gap in the literature to identify a set of global ethical standards for cybersecurity leaders. This article proposes an international model of ethical standards with three ethical propositions to ensure the users of technology in today's global industry remain confident in the corporations entrusted with the users' information.
Introduction

Mobile image processing and computer vision applications are coming of age. There are many opportunities for building successful apps that may improve the way we capture, organize, edit, share, annotate, and retrieve images and videos using iOS-based mobile devices, such as iPhone and iPad. This chapter outlines the motivation for this book and provides an overview of relevant iOS apps, usage statistics, and additional insights into the age of mobile visual computing.
Blind Image Source Device Identification

This article describes how digital forensic techniques for source investigation and identification enable forensic analysts to map an image under question to its source device, in a completely blind way, with no a-priori information about the storage and processing. Such techniques operate based on blind image fingerprinting or machine learning based modelling using appropriate image features. Although researchers till date have succeeded to achieve extremely high accuracy, more than 99% with 10-12 candidate cameras, as far as source device prediction is concerned, the practical application of the existing techniques is still doubtful. This is due to the existence of some critical open challenges in this domain, such as exact device linking, open-set challenge, classifier overfitting and counter forensics. In this article, the authors identify those open challenges, with an insight into possible solution strategies.
METHODOLOGICAL FEATURES OF PROFESSIONALLY ORIENTED EDUCATION OF PHYSICAL ENGINEERING DISCIPLINES BASED ON STEM TECHNOLOGIES: ASPECT OF ONTOLOGICAL APPROACH

The article considers the urgency of the problem of interrelation of teaching physics and professionally-oriented disciplines based on STEM-technologies in the conditions of ontological approach in the process of training students in engineering and technical education according to the educational-professional program of speciality 272 “Air Transport”. Developed and proposed methods of teaching physics based on STEM-technologies, taking into account the definition of ontology aimed at forming STEM skills in subjects, due to the statement before educational institutions significantly improve the quality of students’ knowledge, the role of learning in shaping student’s thinking and cognitive abilities development of STEM education. It is determined that one of the innovative directions of modern education is the introduction of STEM education, which involves the integration of sciences aimed at the development of STEM technologies, innovative thinking and meeting the need for well-trained engineering and technical specialists. The methodical features of professionally-oriented teaching of physical engineering disciplines based on STEM technologies taking into account the ontological approach are substantiated. In the process of conducting a pedagogical experiment, theoretical and empirical research methods were used. In particular, the analysis of philosophical, psychological-pedagogical, educational-methodical literature, recommended textbooks and manuals on methods of teaching physics in the context of the development of STEM education was carried out. Observations, questionnaires, testing, surveys, interviews with scientists and students were conducted. These experimental results were comprehensively analyzed and processed, quantitative data using the methods of mathematical statistics. The results of a comparative experiment to identify the effectiveness of the proposed method of teaching physics in the context of STEM education showed that the level of physical knowledge, skills and abilities of students in control groups is lower than the corresponding level in experimental groups.
SVM Based Temporal Compression Techniques for Video Compression

Compression is an important role in multimedia communication. In this paper, the problems of compression, quality degradation, best matched video, and image are discussed. Block matching algorithms compress the image block by block, and it also operates in a temporal manner. Proposed method is a SVM based algorithm compression. It is the combination of intensity and motion estimation. The proposed technique’s compression gains of 92% accuracy with respective to static JPEG-LS, as it is applied in a frame basis. It achieves a good computation complexity and reduces it. An experimental result shows the better performance than existing methods. The method requires less best match points compared to existing methods. The quality of compression is improved when compared to the previous methods.
Digital Images

Up to now all signals have been one-dimensional. Images, however, are two-dimensional by nature. In this chapter we will extend our theory so that it also applies in higher dimensions. The key mathematical concept in this extension is called the tensor product, which also will help in obtaining efficient implementations of operations on images.
Chunk Meets Image

This study investigated the optimal conditions under which foreign language learning takes place using a smartphone. The authors proposed that two factors, chunking and imagery, would increase language learning. On the basis of previous findings, they formulated three hypotheses: (a) the use of images will have a positive effect on learning English sentences; (b) the use of chunks will have a positive effect on learning English sentences; and (c) the combined use of images and chunks will have a greater positive effect on learning English sentences than either feature alone. A total of 92 Korean seventh graders participated in this study. To examine the learning effect of chunking (i.e., sentence segmentation unit) and imagery (i.e., visual aid) in an experimental setting, they produced a smartphone learning application that incorporated the two methods. The authors measured learning effect with respect to lexical memory retention (i.e., word retrieval ability) and word order composition (i.e., ability to arrange words according to standard English syntax). The results show that the main effects of both chunking and imagery were significant and that the interaction effect between the two on lexical memory retention was also significant. The interaction effect was greater in the delayed effect measurement than in the immediate effect measurement. These findings suggest optimal conditions for designing a smartphone-based, self-learning application.
Sentiment classification using unlabelled data with emoticon classification

Sentiment analysis is the part of opinion mining used to discover the variations of user mood. Generally sentiment analysis deals with feature extraction and sentiment classification, most of the analysis is done by using text mining, mostly training classifiers on labelled data. Emoticon reactions become a major means of communication in social media, where they express the emotions and provide non-verbal communication. This paper propose a classifier making use of emoticons and unsupervised learning, namely K-means clustering, to provide sentiment analysis in an automated matter. The proposed method is trained using data with emoticon expressions collected from Facebook and evaluated on six different sentiment analysis datasets. Accuracy and ARI metrics are used for evaluation and findings are positive: the classifier outperforms K-means clustering and sentistrength2 algorithm in accuracy and training time is correlated to emoticons instead of text features, which is an order less.
The Topographic Representation of Time and its Link with Temporal Context and Perception

Neuronal tuning and topography are mechanisms widely used in the brain to represent not only sensory information but also abstract features like numerosity and time. In humans, temporal topography has been shown recently in a wide circuit of brain regions, from lateral occipital to inferior parietal and premotor regions. However, it remains unclear whether chronotopic maps are specific to vision, whether they map time in an absolute or relative fashion, and to what extent they reflect objective or subjective, perceived time and whether they are influenced by temporal context. Here we asked human participants to reproduce the durations of sounds in two, partially overlapping, temporal contexts while we recorded high-spatial resolution fMRI. Both model-based and data driven analysis approaches show the presence of auditory chronomaps in the auditory parabelt, intraparietal sulcus, and in the supplementary motor area (SMA). Most importantly, when the same physical duration is presented in different temporal contexts, and thus perceived differently, different neuronal units respond to it. Those units were also spatially shifted on the cortical surface according to the relative position of the perceived duration within each context. Finally, voxels did not change their preferences across contexts and their pattern of activity was more similar within rather than across them, suggesting a pivotal role of the context in shaping the maps. These results highlight two important properties of human chronomaps: their flexibility of representation due to perception and their dependency on temporal context.
Attitudes Towards Cloud Computing Adoption in Emerging Economies

Cloud computing is perceived to be the trend of the future as software and hardware turn into the new utility. This study aims to investigate the attitudes of IT professionals and decision makers in emerging economies towards cloud computing. The study also investigates the opportunities and concerns which IT professionals and decision makers have regarding adopting cloud computing in their organizations. This study was carried out in Jordan and the researchers used semi-structured interviews as a research methodology. The theoretical foundation for this research is found in the Diffusion of Innovation Theory. The findings suggest that IT professionals and decision makers in Jordan have positive attitudes towards cloud computing and the adoption rate is increasing at a rapid pace. Relative advantage in terms of cost reduction is a major adoption driver, while compatibility with organizations policies and culture is a major concern. The findings also suggest that government and small to medium-sized enterprises are the major adopters and large enterprises are lagging behind.
Cloud Computing as a Catalyst in STEM Education

The under representation of students in STEM disciplines creates big worries for the coming demands of STEM occupations. This requires new strategies to make curriculum interesting to enhance student's engagement in learning. Technology integration in curriculum makes more interesting and engaging, where students can learn with flexibility in time and place. This methodology creates and deepens interest in students towards learning with creativity and innovation. STEM students can work on authentic and real solutions within a technology-mediated learning environment, while inculcating higher order thinking skills. Technology-mediated environments support new ideas, real time collaboration and promotes peer learning. However, affordance as an adoption factor of technology in academics can be addressed by cloud computing technology. STEM education on cloud computing technology will gain access to its content rich features based on flexibility, accessibility, scalability, affordability, and reliability and enhanced agility. The cloud computing based STEM education infrastructure will inculcate development and experimentation skills in students. The present work (a) reviews scholarly work in cloud computing technology for simulations and prototypes for different STEM subjects, (b) outlines the benefits of using cloud computing technology for students pursuing STEM careers, and (c) presents the case studies of the successful implementation of cloud computing in STEM disciplines.
Analyzing Virtualization Vulnerabilities and Design a Secure Cloud Environment to Prevent From XSS Attack

Cloud virtualization has created an enormous impact on IT and networking worlds. A cloud environment is built on virtualization technology. Virtualization and its exclusive architecture have numerous features and advantages over non-conventional virtual machines. However, these new uniqueness create new vulnerabilities and attacks on a virtualization based cloud system. Cross Site Scripting (XSS) is among the top cloud vulnerabilities, according to recent studies. This exposure occurs when a user uses the input from a cloud environment application without properly looking into them. This allows an attacker to execute malicious scripts in cloud. The scripts execute harmful actions when a user visits the exploited cloud. Current approaches to mitigate this problem, especially on effective detection of XSS vulnerabilities in the application or prevention of real-time XSS attacks. To address this problem, the survey of different vulnerability attacks on cloud virtualization performed and also presents a concept for the removal of XSS vulnerabilities to secure the cloud environment.
A hybrid constraint handling techniques based on differential evolution algorithm for constrained optimization problems

Many practical engineering problems can be transformed into constrained optimization problems (COPs) , scholars prefer to use evolutionary algorithms (EA) to deal with COPS. Differential evolution (DE) algorithm has strong global search and convergence ability than other EA, however, when dealing with COPs, the search ability of DE algorithm is affected by parameter setting and constraint handling technology (CHT) is needed. In this paper, an improved differential evolution algorithm with a new hybrid CHT (IDE-HCHT) is used to deal with COPs, at the same time, the hybrid CHT replaces the selection step of the DE algorithm, and improves the processing efficiency of the algorithm. To verify its superiority, CEC2017 benchmark function is tested by the novel IDE-HCHT, and two other start-of-the-art algorithms, LSHADE44, UDE. The results show that the proposed method shows better competitive performance against the two algorithms.
Ontology-Based Smart Sound Digital Forensics Analysis for Web Services

The big data generated by today Web services makes very fastidious and time-consuming the investigators logs management and analysis tasks. This is due partly to the lack of an efficient web service dedicated log data representation. We introduce, in this paper, an extensible standard based semantic ontology representation of Web service log data to identify hidden information and extract eventual scenario of Cyber-attacks in the web logs. The proposed ontology supports the Web service specification and it satisfies the forensics and admissibility requirements. Through a friendly graphical user interface, the investigator can define validation rules and queries and execute them using a logical reasoner over the proposed ontology to get some comprehensive forensic report ready to present to the court. We also showed how the proposed ontology can facilitate the investigator analysis task, reduce required time, and enhance the forensics process comprehensiveness.
The Cyberethics, Cybersafety, and Cybersecurity at Schools

The 2006 Megan Meier case, where a teenage girl who was bullied on the Internet through e-mail and Myspace which was said to ultimately lead to her suicide, shed light on the cyber bullying issue in schools. This article uses a case study approach to describe how a number of school institutes were grappling with the loss of confidential information and protecting students on the WWW, each through a unique set of circumstances. It will reveal potential reactions of the institutions and possible ways to deal with the cyber threats. With experiences, school districts take measures to offer value education by improving students' knowledge and awareness of Cyberethics, Cybersafety, and Cybersecurity (C3) concepts to provide them with the means to protect themselves, and to enhance the safety and security of national infrastructure.
Cybersecurity Issues and Challenges in Industry 4.0

The convergence of information technology (IT) and operational technology (OT) and the associated paradigm shift toward fourth industrial revolution (aka Industry 4.0) in companies has brought tremendous changes in technology vision with innovative technologies such as robotics, big data, cloud computing, online monitoring, internet of things (IoT), cyber-physical systems (CPS), cognitive computing, and artificial intelligence (AI). However, this transition towards the fourth industrial revolution has many benefits in productivity, efficiency, revenues, customer experience, and profitability, but also imposes many challenges. One of the challenges is to manage and secure large amount of data generated from internet of things (IoT) devices that provide many entry points for hackers in the form of a threat to exploit new and existing vulnerabilities within the network. This chapter investigates various cybersecurity issues and challenges in Industry 4.0 with more focus on three industrial case studies.
Relational Probabilistic Graphical Models

This chapter introduces relational probabilistic graphical models (RPGMs), which combine the expressive power of predicate logic with the uncertain reasoning capabilities of probabilistic graphical models. First, a brief review of propositional and predicate logic is presented. We propose a taxonomy for the classification of RPGMs, and describe in detail two of the different relational-probabilistic formalisms: probabilistic relational models and Markov logic networks. Finally, the application of the two previous approaches is illustrated in two domains, student modeling for a virtual laboratory and visual object recognition based on symbol-relational grammars.
Indexed Search

The domain of Artificial Intelligence (AI) Search algorithms is a well-studied area. A variety of AI search algorithms have been developed in the past decades. Some of them are considered to be among the main AI search algorithms such as Best First Search, A*, Iterative Deepening Search, etc. The others use these main algorithms as a basis and include more heuristics to generate newer algorithms such as Iterative Deepening A* (IDA*), Branch and Bound Search, etc. the innovation of this research is a new approach to the AI search algorithms, we called it indexed search. The methods assigns integer indices to the states of the problem and instead of searching for the goal state, it searches for the index of the goal state. Once the index of a goal state found, we convert that index from decimal base to the base of the branching factor of the problem, and this new number is the solution path from goal to the start node. The new approach eliminates the Closed List which employed for most AI search algorithms to store the explored nodes. The new approach also generates a solution path faster than the respective versions of them and it also use less memory space.