Reviewerly/exHarmony huggingface dataset:
Tourism Policing in a Fourth Wave World

This chapter provides an overview of how technology will change the face of tourism and tourism policing and security. Based on the philosophy of Alvin Toffler, the chapter offers an overview as to where we have come from and how changes in economic production will impact the way tourism security is done in the future.
Applying CI in Biology through PSO

Conventional computing methods face challenges dealing with real world problems, which are characterised by noisy or incomplete data. To find solutions for such problems, natural systems have evolved over the years and on analysis it has been found these contain many simple elements when working together to solve real life complex problems. Swarm Intelligence (SI) is one of the techniques which is inspired by nature and is a population based algorithm motivated by the collective behaviour of a group of social insects. Particle swarm optimization (PSO) is one of the techniques belonging to this group, used to solve some optimization problems. This chapter will discuss some of the problems existing in computational biology, their contemporary solution methods followed by the use of PSO to address those problems. Along with this several applications of PSO are discussed in few of the relevant fields are discussed having some future research directions on this field.
Activity

Whether an IT auditor is engaged in internal or external IT audit reporting, after formal audit results communication, IT audit follow-up is an engagement requirement. The IT auditor assigned responsibility for tracking and assessing audit area responses must have skills to confirm appropriate corrective actions deployment. The IT audit reporting process prepares an IT auditor for providing appropriate follow-up concerning resolved and unresolved audit issues. If the deployment of a corrective action does not occur, the assigned IT auditor should seek support from higher levels of audit area management for achieving recommendation implementation within a reasonable timeframe. Chapter 9 presents management's proposed actions, IT audit follow-up materiality, and IT audit follow-up criticality. Chapter 9 also addresses the management response assessment of corrective actions.
Class Imbalance in Facial Expression Recognition by GCN with Focal Loss

Dataset is important in facial expression recognition, but they may run into apparent imbalances caused by various collection scenes. This paper studies the class imbalance problem in the benchmark dataset for facial expression recognition. We focus on the design of focal loss function instead of cross entropy loss to solve the class imbalance. Graph convolutional network (GCN) is applied to achieve the facial expression recognition. Experimental results in Oulu-CASIA dataset and SFEW 2.0 dataset exhibit that the proposed programme improves the performances of facial expression recognition.
The Explanation Game: A Formal Framework for Interpretable Machine Learning

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions.
Sharing the Load: A Planning Checklist for Consortial Database Use

This paper provides a starting point for those who are planning to implement shared research databases in a consortium environment. For those who are well into the process, it provides a stopping-off place, a review tool for the next planning meeting or consortium retreat. The paper presents a checklist of planning concerns and accompanying discussion and illustration of the issues. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678, E-mail address: getinfo@hawortlipressinc.com]
Identification of Various Privacy and Trust Issues in Cloud Computing Environment

Cloud computing is a rising paradigm in today's world. In this, users can send his or her request to any CSP, i.e., cloud service provider, of their choice. In return, the CSP reverts him back with that particular service. Now, while communicating from various two locations, the data transferred is not passed through that much amount of security and privacy as expected. So, there are lots of parameters in the environment that are taken care of while sending, receiving or just passing data over the network. This chapter presents various security issues that are underlying in cloud computing. This chapter has illustrated various issues such as Trust, Encryption, Authenticity, Confidentiality and Multi Tenancy. Also, some of the proposed solutions have also been discussed later in the chapter.
Cost Estimation and Security Investment of Security Projects

This chapter aims at examining two main aspects in security: cost estimation and investment assessment. The characteristics of security projects are stressed and the importance of adopting management task is determined. In addition, the chapter examines the different cost-estimation models developed for security project and discusses the technical and managerial factors affecting the cost estimation and the management of projects. In addition, a review of research works directed toward security investment models is determined. In fact, most models have focused on determining the optimal security investment allocation based on budgetary, economic, and financial constraints. Recent models are interested to examine more specific security features when assessing the required investment (e.g., system vulnerabilities, attack types, risk factors, data privacy, and insurance). Finally, the chapter discusses future directions that could be investigated to make available useful models for cost estimation and investment on security projects.
Chapter Four. All Natural Types and Antitypes are Ontologically Real: Introducing Edwards’ Onto-Typology

No AccessChapter Four. All Natural Types and Antitypes are Ontologically Real: Introducing Edwards’ Onto-Typologyhttps://doi.org/10.13109/9783666517013.54SectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail About Previous chapter Next chapter FiguresReferencesRelatedDetails Download book coverNew Directions in Jonathan Edwards StudiesVolume 5 1. AuflageISBN: 978-3-525-51701-7 eISBN: 978-3-666-51701-3HistoryPublished online:October 2020 PDF download
This paper essentially present a method to assimilate satellite SSTs using canonical correlation analysis (CCA); a statistical technique that permits to construct an appropriate observation operator to project the state variables of a numerical model onto

This paper essentially present a method to assimilate satellite SSTs using canonical correlation analysis (CCA); a statistical technique that permits to construct an appropriate observation operator to project the state variables of a numerical model onto observed variables.In this case the method is used to correctly assimilate measurements (satellite skin sea surface temperatures) which are not included in the set of those simulated by the model (the temperature of the first model layer) but which are physically linked to them.Based on a previous paper of Pimentel et al (2018) a 1D model (GOTM) is used to simulate high-resolution temperature profiles from which it is possible to extract temperature at the model levels (the state variable of the model) and "observed" temperatures at the sub-skin level.The skin temperature C1
Neuronal Communication Genetic Algorithm-Based Inductive Learning

The development of powerful learning strategies in the medical domain constitutes a real challenge. Machine learning algorithms are used to extract high-level knowledge from medical datasets. Rule-based machine learning algorithms are easily interpreted by humans. To build a robust rule-based algorithm, a new hybrid metaheuristic was proposed for the classification of medical datasets. The hybrid approach uses neural communication and genetic algorithm-based inductive learning to build a robust model for disease prediction. The resulting classification models are characterized by good predictive accuracy and relatively small size. The results on 16 well-known medical datasets from the UCI machine learning repository shows the efficiency of the proposed approach compared to other states-of-the-art approaches.
Detection of Seam-Carving Image Based on Benford's Law for Forensic Applications

Seam-Carving is widely used for content-aware image resizing. To cope with the digital image forgery caused by Seam-Carving, a new detecting algorithm based on Benford's law is presented. The algorithm utilize the probabilities of the first digits of quantized DCT coefficients from individual AC modes to detect Seam-Carving images. The experimental result shows that the performance of proposed method is better than that of the method based on traditional Markov features and other existing methods.
Improving wireless and networking cybersecurity curriculum

This investigation expands previous work responding to the growing need to educate and train cyber professionals of wireless and networking devices by guiding cyber education curricular development in undergraduate and master's degree programs. In the haste to expand cyber curriculum, important considerations to improve student learning may be overlooked, resulting in less effective and satisfying experiences. Enhancing effectiveness of the learner experience may leverage not just what, but also how, content is delivered. The result integrates 'minds-on' with 'hands-on' learning. This paper is authored by cyber faculty at a university that recently expanded undergraduate and master's cybersecurity programs to cover wired and wireless cyber curriculum. This initiative supplemented theoretical education with development of hands-on 'experiential' learner experiences across the curriculum.
Integrated Nanophotonic Ising Sampler

We demonstrate an integrated silicon photonic Markov Chain Monte Carlo sampler capable of high-probability convergence to the ground state of various 4-spin Ising graphs. Robustness to getting trapped in local minima is enhanced by experimental system noise.
Students' Perception of the Integration of Mobile Devices as Learning Tools in Pre-Primary and Primary Teacher Training Degrees

University education is nowadays facing the need to rethink teaching processes carried out, to accommodate them to new understandings about how the human beings learn, also transcending the use, access and appropriation of a methodology adapted to changing times where, no doubt, mobile devices have a leading role. Besides their obvious communicative and playful function, teachers and learners must be aware of the pedagogical potential of these devices that can become allies in educational processes. This study analyzes the perception of university students, enrolled in the Pre-Primary and Primary Teacher Training Degrees at the University of Salamanca (Spain), about the use of mobile devices as tools to assist the learning process and as gadgets to practice and boost the learning process carried out in the classroom. Relevant outcomes have been extracted from the inspection of the data obtained through a survey to students, what has enabled us to draw interesting conclusions about the opinion of students about the inclusion of mobile devices as learning resources at tertiary level, that unravel the good disposition of the students polled towards the incorporation of these devices, both to university classes as well as to their future professional development.
Introductory mathematical programming for EC

tutorial Introductory mathematical programming for EC Share on Author: Ofer M. Shir Tel-Hai College & Migal Institute, ISRAEL Tel-Hai College & Migal Institute, ISRAELView Profile Authors Info & Claims GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference CompanionJuly 2020 Pages 547–560https://doi.org/10.1145/3377929.3389869Online:08 July 2020Publication History 0citation40DownloadsMetricsTotal Citations0Total Downloads40Last 12 Months12Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Location Tracking Prediction of Network Users Based on Online Learning Method With Python

Aiming at the problem that the precision and recall rate of traditional prediction methods are low and its low prediction efficiency, a Python-based trajectory tracking prediction method of online learning network user location is proposed. First, troubleshooting terminal programs of online learning network user by programming in Python (computer programming language) structure, the location trajectory data of online learning network user is spatially processed. In this way, features of time-related, spatial correlation, social relationship correlation, and user preference characteristics are extracted respectively to realize feature normalization processing. Second, on this basis, the cosine similarity is used to calculate the similarity of user behavior trajectory. According to K-MEANS (hard clustering algorithm), the time dimension is considered. Finally, the clustering result of users' behavior trajectory based on the sign-in data is compared with a preset threshold to predict the online user location trajectory. The experimental results show that the proposed method normalizes the user's trajectory, combines the time segment, and compares it with the preset threshold, which does not only improve the prediction efficiency but also obtains higher and more feasible precision and recall rate.
Fractionalization, polarization and banking stability in Africa

Abstract I examine the impact of diversity (ethnic and religious fractionalization and polarization) on banking stability in Sub-Saharan Africa (SSA). Using data from 1996 to 2014, I employ the system Generalized Method of Moments (sys-GMM) approach to examine this relationship. I find that countries in SSA are more polarized religiously than they are ethnically. The region is, however, more ethnically fractionalized than they are religiously. Further, I conjecture that banks in more heterogeneous societies will experience poor asset quality and lower stability. I however postulate that banks offset the risks from diversity at certain levels of net interest margin (NIM). I provide empirical evidence to support these conjectures. I find varying threshold NIM values for each diversity indicator depending on the stability measure used. Opening up the banking system to foreign entry can help offset the negative impact of diversity on banking stability. Policy implications are discussed.
Assembly, Space, and Things

Each day as one notices more people walking along sidewalks, head down peering into smart phones, the fear is that social interaction in public space is dead. However, the integration of human and non-human processes may connect our communities now in more ways than ever before. New urban design theory suggests that “the city” may not be understood as a whole, rather as an assembly of dynamic urban processes. At many bike share systems around the world only static maps with limited interaction experience. Urban interaction design and the Internet of Things, is changing this experience. The interdisciplinary methodology describes a symbiosis of people, space and things. The significance is the integrated urban interaction design process of: urban design theory using classification of urban experience; geospatial analysis at the street-scale of point addresses, and fabrication of a test-bed kiosk to test ambient sensors and user interaction. Connectivity experienced in the virtual space of social media may now enter back into the physical realm of public space.
The Explosion of Cryptocurrencies: A Black Hole Analogy

Using an analogy between finance and astrophysics, this study aims to investigate whether there exists a mechanism that can describe the explosive increase in the number of traded cryptocurrencies and the cryptocurrency market in general. In physics, the Schwarzschild radius indicates that black holes are constantly expanding because of their mass increase. Enriching this analogy, we consider the cryptocurrency market as a self-gravitational body whose mass is denoted by (1) the number of traded cryptocurrencies and (2) in terms of increasing market capitalization for a given number of traded cryptocurrencies. By analyzing weekly snapshot data of all traded cryptocurrencies from January 4, 2009, to June 14, 2020, we find evidence that the above-mentioned mechanism exists. The results clearly indicate the self-gravitational property of the cryptocurrency market, which is direct evidence toward the hypothesis that the changes in the traded cryptocurrencies are a positive function of the previous period’s number of traded cryptocurrencies.
Graphics and Image Data Representations

In this chapter, we discuss how images are stored, starting off with the simplest image data, one bit per pixel. Grayscale, 8-bit images are considered next, and we consider the problem of how to actually send images to a printer and what problems and solutions this entails. RGB 24-bit color images are then explored, looking at the three color planes as images in their own right, and capturing RGB information content via a three-dimensional histogram of colors is introduced. Returning to 8 bits, the concept of a color palette is discussed; but this then brings up the problem of just what colors shall be distinguished by inclusion in the palette. To this end, the problem of how to devise a color lookup table is considered, with the Median-Cut algorithm brought forward as one solution. Popular file formats, GIF, JPEG, PNG, TIFF, PDF, and so on are introduced. The GIF format is simple but representative, and for this reason it is set out in some detail. To wrap up the discussion the PTM (Polynomial Texture Mapping) technique and format is included, with the capability of virtually exploring the surfaces of cultural heritage precious objects.
Introduction

With the rapid development of information technology and the establishment of “human-oriented” new type communication fashion, future multimedia service emphasizes not only speed, bandwidth, quality of service sources, but also user feeling and satisfaction. Therefore, for multimedia content providers and network operators, promoting users’ feeling or even their viscosity is very important in the context of multimedia service explosion and heavy competition. In other words, only by continuously improving the recognition and viscosity of users, positioning network services and operational activities into the most valuable user groups, service providers and network operators can achieve the optimization of resource allocation and continuous growth of industry revenue in the fierce competition. Traditional time-consuming and power-intensive user scoring methods can no longer satisfy the multimedia content provider and network operator’s evaluation of user satisfaction. Instead, multimedia users’ quality of experience (QoE) is evaluated by using the collected big data. Therefore, how to objectively and effectively evaluate multimedia user QoE by considering various influencing factors has become a hot and difficult topic in current research.
Learning Rules

Over the last few decades, there has been an increasing need for input-output mapping models. While AI techniques, especially deep learning techniques are revolutionizing the business and technology worlds, there is an increasing need to address the problem of interpretability and to improve model transparency, performance, and safety. In this chapter, we concentrate on fuzzy rule-based models, where the interpretability of the system is clear. We propose a three-step method based on Łukasiewicz logic for the description of the rules and the fuzzy memberships to construct concise and highly comprehensible fuzzy rules. We apply a genetic algorithm to evolve the structure of the rules and then a gradient-based optimization to fine-tune the fuzzy membership functions. Using the squashing functions introduced in Chap. 7, we can approximate the operators and the memberships in the same way and we can efficiently calculate the derivatives of the membership functions. We also present applications of the model using the UCI machine learning database.
Updating Weights

Training a neural network is to update the weights to minimize a specified loss function and the gradient descent method has been employed. However, the number of weights exponentially grows, especially in a deep learning machine. In recent years, several methods updating weights have been developed to improve the speed of convergence and to find the best trajectory to reach the optimum of the employed loss function for a network. In this chapter, those methods for updating weights are explained.
Analysis of influence of ultra-hydrophilicity of oxidation titanium surface on blood compatibility based on density functional theory

Based on the density functional theory, it adopts the first-principles method to calculate the ultra-hydrophilicity of oxidation titanium surface under different oxygen vacancy concentrations. The calculation results show that under the practically feasible oxygen vacancy concentration range, with the increase of the oxygen vacancy concentration, the ultra-hydrophilicity of oxidation titanium surface is increased, and the semiconductor type of the oxidation titanium is transformed from p type to n type. When the oxidation titanium surface is in contact with blood, the n-type semiconductor and the features of the electron state occupying the bottom of conduction band of the oxidation titanium surface can suppress the transfer of charge from the fibrinogen in the blood to the oxidation titanium surface so to suppress the aggregation and activation of blood platelet, thus improve the ultra-hydrophilicity of oxidation titanium surface on blood compatibility.
Programming with R

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box–Muller and Metropolis–Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computing languages and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from www.statprogr.science. Worked examples - from real applications - hundreds of exercises, and downloadable code, datasets, and solutions make a complete package for anyone working in or learning practical data science.