Reviewerly/exHarmony huggingface dataset:
Logic in Reality

In the middle of the twentieth Century, the Franco-Romanian thinker Stéphane Lupasco proposed a unique, non-propositional and thus non-truth functional logic applicable to changes in real processes and systems. It was developed by Basarab Nicolescuas a logic of the included third term and further by one of us (Brenner) as a logic of and in reality. Its grounding by Lupasco in quantum mechanics and physics provides a grounding for the science and accordingly the philosophy of science as well as natural philosophy. In this book, we will describe how this logic, which we designate as Logic in Reality (LIR) offers a way of bridging gaps between science and philosophy, joining in this the most recent development in theories of information, communication and systems. The grounding of LIR in the principles enunciated by Gödel, Pauli and Heisenberg is indicated. This Chapter will take the reader to further application of LIR to change, here and in the next Chap. 4.
Classification of Tropical Rain Forest East Kalimantan Using Image Processing and Backpropagation Neural Network Algorithm

Tropical Rain Forest located in East Kalimantan has a high level of biodiversity, with a high level of biodiversity in east kalimantan then it needs a method to classify the existing plants there. In the research, the researchers tried to classify 5 plants found in tropical rainforests, namely ShoreaBalangeran, Dryobalanopsbeccarii Dyer, Eusideroxylonzwageri, Duriokutejensis, Cerberamanghas. Classification is done by using backpropagation neural network algorithm combined with image processing, where the image used is the image of plant leaf. The result of this research is the classification of 5 species of this plant with precision value above 90% in order to become a supporter of botanical decision in determining the type of plant and become alternative reference to classify plants in tropical rain forest area.
Forensic archaeology and scene processing methods

Forensic archaeology is the application of archaeological theory and methods to medicolegal cases. This includes searching for and locating human remains, surveying, sampling, recording, and interpreting evidence, as well as the recovery and documentation of human remains and associated evidence. A location where remains are found is called a scene or recovery scene, and common types include surface, burial, submerged, and fire scenes. Processing a scene typically involves the search, recovery, and documentation of evidence, and is an inherently destructive process that permanently alters the context of the area and items located there. Documentation and preservation of contextual information is therefore critically important. Methods of locating a scene may include line searches, subsurface probing, thermal imaging, geophysical techniques, or cadaver dogs. Each has limitations, and certain approaches may only be appropriate in certain situations. The recovery process typically involves denuding the scene, establishing a datum, screening, excavating, and collecting evidence. Scenes can be mapped using a variety of approaches including triangulation, trilateration, azimuth, baseline, and grid. After collection, remains should be packaged in a way that preserves the quality of the evidence.
COMPUTER SIMULATION WITH ARGUMENTATION SCAFFOLDING FOR ELEMENTARY STUDENTS' COLLABORATIVE SCIENTIFIC EXPLANATION

In elementary science education, it has many potential benefits to engage students in scientific explanations through evaluating claims, evidence and reasonings.This study intends to develop a web-based platform that integrates such functions as science simulation and synchronous online discussion, embedded with argumentation scaffolding, so that elementary students could conduct simulated scientific experiments and construct scientific explanations collaboratively in an interactive online science learning environment.A modified argumentation scaffolding is designed based on Toulmin's framework and applied in this platform, which consists of six components: claim, evidence, reasoning, agreement, query, and rebuttal.Each component contains several semi-structured or structured text templates to provide guidelines for students' online practices in argumentation and explanation.An investigation will be made on whether this platform is useful in supporting students' collaborative construction of scientific explanations in simulated scientific experiments.
Security Architecture of Cloud Computing

Cloud computing is an innovation for dynamic resources to be used over the internet. Though cloud computing is cost effective and easy to use, security is often an area of concern. Sharing of sensitive information and running critical applications on public and/or shared cloud environments require high degree of security. Amount of data stored and processed is increasing enormously requiring cloud environments to resize to larger capacities. Cloud environments have both pros and cons concerning the security of data of the consumers using cloud services. This chapter discusses the main security issues faced by cloud computing environments. The main focus of this chapter is to describe the issues faced during building cross-domain collaborations over the internet and usage of cloud services and its security. This chapter also identifies the security at various levels of cloud computing and, based on cloud architecture, categorizes the security issues.
Regional growth inpainting strategy for depth image

The depth images acquired from depth sensors have inherent problems, such as missing depth values and noisy boundaries. In this paper, an inpainting strategy for depth image based on regional growth criterion is proposed. In terms of image inpainting sequence, based on Criminisi priority method, a new calculating method of confidence item is defined and the improved priority is used to weight the confidence items and data items. Compared with the inpainting results of Joint bilateral filter (JBF), JBFC (JBF based on Criminisi priority), and JBFW (JBF based on weighted pixel priority), the inpainting sequence and texture extension determined by weighted pixel priority are better. In terms of image inpainting field, Under the guidance of the weighted pixel priority, the adaptive neighborhood of the pixel to be inpainted is defined by region growth criterion which have higher similarity with the pixel to be inpainted than by traditional neighborhood. Experimental results show that the neighborhood constructed by region growth criterion is accurate and effective. Generally, the regional growth inpainting strategy can obtain higher inpainting accuracy while keeping the boundary information
Making Innovation Development Policies Work for MENA

This chapter analyzes the Middle Eastern North African economies' growth prospects and investigates the role of entrepreneurial activities in achieving sustainable economic growth and social development. It explores the existing macroeconomic, political and social characteristics of the region and brings the different literatures together to understand the policy implications of theory and practices. The chapter shows that entrepreneurial activities can cure a lot of problem in the region as long as supported by the central authorities, and the region has a strong potential to be used by the entrepreneurs.
Data Treatment

The rudimentary of data treatment was explained in this chapter. The difference between analogue and digital data was highlighted and explained. The methods for data treatment were described with examples. The different techniques for analyzing different types of data in environmental field work were illustrated. Special cases of data analysis in environmental studies were explained.
Optical Semantics

A discrete and digital representation of data can be replaced by a continuous one using optical tools. The optical computing can help to create the cognitive semantics and overcome the existing restrictions on the speed of calculations. Such a substitution is not absolute since optical transformations have a corpuscular-wave nature.
Special issue commemorating the 50th anniversary of “pattern recognition”

In recent years, collaborative representation-based classification (CRC) methods have shown impressive performance in many recognition tasks. However, when the training data have different distributions with the testing data, the performance of CRC will be degraded significantly. On the other hand, concatenating training data from different sources as a single data set will affect the performance of CRC, as the shift exists between the different source domains. To address these problems, in this paper, we propose a Jointly Discriminative projection and Dictionary learning for domain adaptive Collaborative Representation-based Classification method (JD2-CRC). As the distributions of different source domains may be dissimilar, the data from all domains are projected into a common feature subspace where the latent shared structures can be found. Then a compact dictionary is learned to represent the projected data well. To find the most suitable projection matrices and dictionary for CRC, we design the objective function of JD2-CRC,according to the classification rule of CRC in feature subspace, which minimizes the ratio of within-class reconstruction errors over between-class reconstruction errors. Different to traditional optimization methods, an effective optimization procedure is presented based on gradient descent. Thus, the obtained collaborative representations have a better discriminability and suit the classification rule of CRC well. The experimental results demonstrate that the proposed method can achieve superior performance against other state-of-the-art methods.
Application Overview Of Quantum Computing For Gas Turbine Design and Optimisation

Conceptual designs require optimization methods to identify the best fits in the system. The article investigates the application of quantum computation in gas turbine design and simulation problems with current technologies, approaches and potential capabilities. Quantum optimization algorithms and quantum annealers help in predicting overall efficiency and optimizing various operating parameters of the gas turbine. A comparison of both classical and quantum computers has been discussed briefly. The classical model challenges are mitigated with the use of quantum computation. A novel hybrid model for simulating gas turbines has been proposed which consists of a combination of both physics and machine learning to eliminate some critical problems faced. The review elaborates application of quantum computing based machine learning for design and optimization of a gas turbine. The overall states of the gas paths of gas turbines could be analyzed using the quantum computing model in the future.
A Comparative Web Usage Study of Users in Navigational Web Searching

This chapter highlighted the differences of users' behaviors between native English-speaking users and Chinese users as the biggest example of non-native English-speaking users. To do as such, the author of this chapter began by discussing the background of earlier web usage studies followed by a literature review on comparative studies that are on the basis of users with different language preferences. Afterwards, since earlier web log analyses are based on web transactions collected from mainly native users, the author of this chapter investigated the feasibility of generalization of former findings for navigational searching to the rest of the users by comparing two web log transactions from two groups of users with different localities in respect to the state-of-the-art in web searching.
The Storage and Retrieval Technologies of Quantum Images

Quantum image processing represents an emerging image processing technology by taking advantage of quantum computation. Quantum image processing faces the first question: How is an image stored in and retrieved from a quantum system? To solve the issue, the authors provide six quantum image representations, which can be divided into three categories. The first, second, and third categories store color information using amplitudes, phases, and basis states, respectively. Next, they design their circuits to implement the storage of quantum image. Then, retrieval methods are introduced. The storage and retrieval technologies of quantum image are the basis and premise condition to process quantum images.
Electronic Discovery (E-Discovery)

The objective of this chapter is to review the concept of electronic discovery(e-discovery) paying special attention to the legally established procedures for consideration as digital evidence, to the computer tools developed for obtaining them, as well as to the historical background that frame its origin. The authors review techniques and functionalities associated with advanced information systems and describe the possibilities and limits for the evaluation and exploitation of electronic discoveries in the cloud, in social networks, as well as in bring your own device (BYOD), big data, or business intelligence settings. It also includes a review of the reference frameworks, standards, and resources associated with the EDRM model (electronic discovery reference model).
The Effect of Accountability, Transparency and Stakeholder Participation on the Effectiveness of the Management of School Operational Assistance (BOS)

This study aims to analyze the effect of accountability, transparency and stakeholder participation on the effectiveness of the management of School Operational Assistance (BOS) funds at SMP Negeri 1 Lappariaja, Bone Regency. This study uses a quantitative approach with multiple linear regression analysis method and the number of samples in this study is 35. The research findings indicate that accountability has a positive and insignificant effect on the effectiveness of BOS fund management, transparency and stakeholder participation have a negative and insignificant effect on the effectiveness of BOS fund management at SMP Negeri 1 Lappariaja, Bone Regency.
Predicting a Model of Decision Making in All the Systems

“Great things in business are never done by one person, they ‘re done by a team of people”- Steve jobs . The solid foundation of any successful company is its people(employees). Participative decisionmaking is important concept.. People are dependent to one another. Nobody live without others help directly or indirectly .Participative decision making is the extent to which employers allow or encourage employees to share or participate in organizational decision making(probust 2005). The objective of this paper is to find out, why we implement participative decision making in all the organizations. It is a literature review paper. This study found how participative decision making improves organizational productivity, Jobsatisfaction, Organizational commitment, empowerment in various research studies.
Teaching the Earth: Pathways and Careers in Geoscience Education

There are many exciting careers in geoscience education that impact how people think and learn about the Earth. Geoscience education can equip citizens with the skills and knowledge needed to make informed decisions about the planet. The employment opportunities in this sector are growing and include positions in formal and informal education, policy, evaluation, and consulting fields. Geoscience education research is an emerging subdiscipline within the broader geosciences and is a field of study that is becoming more common for those with a strong interest in research and teaching, especially at the undergraduate level. The types of geoscience education positions vary widely and often require different skill sets and degree pathways. Here, we describe the various geoscience education positions one may target for a career, their projected salaries, the degree pathways to reach these positions, and next steps interested students should take to plan for such careers. Helpful resources and web-sites are provided to guide the reader to explore rewarding careers in geoscience education.
A De-swinging Scheme in Location Privacy Protection via Smart Contract

There are some problems such as behavior deception and service swing while utilizing distributed k-anonymity technology to construct an anonymous domain. If the malicious nodes submit a false location coordinate to take participate in the process of constructing, the coordinate of the honest node will be leaked, and the attacker will increase the reputation illegally. To tackle those problems, we propose a de-swinging scheme based on the smart contract for location privacy protection. Primarily, a de-swinging reputation evaluation method (DREM) is introduced, in which participants prefer to choose nodes with high reputations to complete the construction process of the anonymous domain. In this method, we design a penalty factor to curb malicious behavior. Besides, based on our proposed DREM, a cridible cloaking area is constructed to protect the location privacy of the request nodes. We utilize smart contract to calculate reputation automatically during the process of construction. Finally, the security analysis and simulation results indicate that our proposed scheme can effectively resist malicious attacks, detect malicious nodes quickly, encourage nodes to participate honestly in the construction of anonymous domain.
Methodological Support of the Work of Primary Schoolchildren with Information Presented in the Form of Diagrams

The article outlines a range of methodological problems that arise when teaching younger schoolchildren, the ability to use information presented in the form of diagrams. Modern textbooks of mathematics for elementary school and methodological recommendations to them related to the topic “Diagrams” of the section “Working with information” are analyzed. Since the development in younger schoolchildren of the skills of working with visual sign-symbolic means of graphical presentation of information is one of the requirements of the Federal State Educational Standard of Primary General Education for meta-subject learning outcomes, the author proposes methodological techniques and a system of assignments that allow to eliminate the current and potential difficulties of primary school students when mastering charts.
Transforming Cities

Chapter 5 explores the use of distributed ledger technologies in cities to help improve citizen-centric services: land registries, health care, welfare payments, identity, supply chains, and voting. McKinsey analysts predict that by 2020 the number of smart cities will reach 600 worldwide, and 5 years later almost 60% of the world's GDP will be produced in them. Digital technologies could become an engine of economic progress, and Blockchain could be one of those technologies. This connectivity, however, comes at a cost. How will cybersecurity evolve with Web 3.0 and 4.0 technologies to protect cities from cyber-attacks? This chapter introduces how Blockchains may be used to resolve a range of city-based challenges arising from broader global concerns like national population increases, urban density, anthropomorphic climate change, urban pollution and mobility, local and national citizen services, and infrastructure.
An integration of handcrafted features for violent event detection in videos

Activity recognition is a prominent and difficult research problem and a branch of machine learning. Currently, there is great interested in safety in private and public areas. Therefore surveillance cameras have been deployed to monitor suspicious activity. Consequently, many researchers have worked on developing automatic surveillance systems to detect violent events. However, violent events remain difficult to detect because of illumination issues, complex backgrounds, and scale variations in surveillance cameras. In this chapter, the authors use GHOG (Global Histograms of Oriented Gradients), HOFO (Histogram of Optical Flow Orientation), GIST handcrafted feature descriptors and integration of GHOG+HOFO+GIST descriptor to improve the performance of the proposed method. Finally, prominent features are used with a support vector machine classifier for violent event detection. Experimentation is conducted on the Hockey Fight dataset and Violent-Flows dataset with the proposed feature integration descriptors, showing promising results and illustrating that it is computationally efficient.
The Technological Pedagogical Content Knowledge of EFL Teachers (EFL TPACK)

Teaching is known to be one of the most stressful occupations ever since teachers are believed to suffer from different social and political discriminations leading many of them to feel frustrated. In the 21st century, the force of technological empowerment and ICT integration in schools has multiplied the stressful nature of the profession for teachers. To make the whole process of education more successful and to protect the wellbeing of teachers, empowering teachers to handle their job appropriately is a very crucial issue. TPACK (technological pedagogical content knowledge) is the knowledge of most value in today's world, and understanding this complex knowledge is the very first step on the path of successful ICT integration into the process of teaching. With that being said, this chapter aims at investigating the concept of TPACK in terms of education in general and language teaching in particular.
Copula model selection using image recognition

The choice of a copula model from limited data is a hard but important task. Motivated by the visual patterns that different copula models produce in smoothed density heatmaps, we consider copula model selection as an image recognition problem. We extract image features from heatmaps using the pre-trained AlexNet, and present workflows for model selection that combine image features with statistical information. We employ dimension reduction via Principal Component and Linear Discriminant Analyses, and use a Support Vector Machine classifier. Simulation studies show that the use of image data improves the accuracy of the copula model selection task, particularly in scenarios where sample sizes and correlations are low. This finding indicates that transfer learning can support statistical procedures of model selection.
Decentralization Neutralizers

Decentralization cannot evolve in a vacuum. As decentralized technology becomes increasingly available, its application, adaptation, and evolution depend on society’s acceptance and use of the technology. While improved decentralized incentive designs can accelerate adoption, design alone will not suffice in promoting the decentralization of business and society. Several factors call into question society’s engagement with decentralized technologies. Such factors can be seen as decentralization neutralizers. They are plentiful and undermine society’s engagement with emerging decentralized technologies and the solutions it may offer for society. The article discusses these decentralization neutralizers and points out possible solutions.
TMAC: an Active Defense Architecture adapted to Microkernel Operating System for Power ICS

Because of its obvious advantages in reliability, security and scalability, microkernel operating systems are becoming more and more popular within power industrial control terminals. However, the application of new technologies such as the Internet of Things has further expanded the exposure of terminal network attacks. In particular, with the development of new power systems dominated by new energy sources, the power grid is shifting from closed to open, and IoT terminals are gradually distributed in untrustworthy physical environments. Aiming at the micro-kernel operating system scenario of power industrial control terminal, this paper proposes active defense architecture named TMAC which integrates functional safety and information security of Power ICS, and describes related key technologies. Experiments show that TMAC can significantly guarantee the security of the microkernel operating system.