Reviewerly/exHarmony huggingface dataset:
Transported Immobility

This chapter takes inspiration from Roland Barthes’ concept of transported immobility to understand the contrary experience of living in a digital media blackout zone. By using Barthes’ protocol of attention to contingency in everyday life, I explore the Wi-Fi tethering experience in the Swedish forest, where I am tethered to a particular indoor and outdoor place and dependent on intermittent digital media connection. Such tethering fixes me to a place in the rural forest that enables Wi-Fi, provides access and a flow of communication in that moment of connection, and is a source of frustration as rural infrastructures and inclement weather routinely affect the experience. The chapter reflects on a double meaning of tethering: in the context of media there is the action of staying fixed in one place so your telecommunications devices can enable data movement, a fixity and flow in the media environment; and in the context of mobility, there is the tethering of a human, non-human, or object where there is the action of restricting or disabling movement, a regulation and constraint in everyday life. This tethering experience brings into relief assumptions we make about normative digital media experiences. These other stories of the media and its social and technical affordances compels us to review assumptions about digital society - this is a particular rural experience at the margins of socio-technical visions and dominant media theories. Such an experience signals the mirage of a digital society for particular rural citizens in a topography where media breakdown is a routine feature of daily life.
HIPAA Security and Privacy Rules Auditing in Extreme Programming Environments

Healthcare business is responsible of keeping patient data safe and secure by following the rules of the federal Health Insurance Portability and Accountability Act of 1996, (HIPAA). Agile software organizations that deal with healthcare software system face a number of challenges to demonstrate that their process activities conform to the rules of HIPAA. Such organizations must establish a software process life cycle and develop procedures, tools, and methodologies that can manage the HIPAA requirements during the different stages of system development, and also must provide evidences of HIPAA conformity. This paper proposes an auditing model for HIPAA security and privacy rules in XP environments. The design of the proposed model is based on an evaluation theory which takes as its input the work of Lopez ATAM, and the standards of common criteria (CC) concepts. The proposed auditing model has been assessed based on four case studies. The auditing result shows that the proposed model is capable of capturing the auditing evidences in most of the selected case studies.
Decision Making Under Multi Task Based on Priority for Each Task

In recent years, autonomous robots become to be desired to treat multi-task. A robot must decide a concrete action for plural objectives. Major researches try to realize this by weighted rewards. Weighted rewards can represent a human's intention easily. But weight of each task must change dynamically by a change of surrounding situation or of a robot status. Authors consider an independent learning for each task and selection of one concrete action from candidates of each learning. Authors propose a priority function to calculate priority for each task corresponding to surrounding situation or a robot status and propose a system which do decision making by using the priority function. Authors confirmed the usefulness of proposed method with simulation.
HASGS: Five Years of Reduced Augmented Evolution

The work presented here is based on the Hybrid Augmented Saxophone of Gestural Symbioses (HASGS) system with a focus on and its evolution over the last five years, and an emphasis on its functional structure and the repertoire. The HASGS system was intended to retain focus on the performance of the acoustic instrument, keeping gestures centralised within the habitual practice of the instrument, and reducing the use of external devices to control electronic parameters in mixed music. Taking a reduced approach, the technology chosen to prototype HASGS was developed in order to serve the aesthetic intentions of the pieces being written for it. This strategy proved to avoid an overload of solutions that could bring artefacts and superficial use of the augmentation processes, which sometimes occur on augmented instruments, specially prototyped for improvisational intentionality. Here, we discuss how the repertoire, hardware, and software of the system can be mutually affected by this approach. We understand this project as an empirically-based study which can both serve as a model for analysis, as well provide composers and performers with pathways and creative strategies for the development of augmentation processes.Â
Quantum Image Segmentation Algorithms

Quantum image segmentation has always been one of the difficult tasks in quantum image processing. This chapter introduce two quantum image segmentation algorithms. One is quantum edge detection algorithm; the other one is quantum image segmentation based on generalized Grover search algorithm.
Kinect Applications in Healthcare

Microsoft Kinect is one of the most popular inexpensive gadgets released in recent years. Kinect is equipped with a color camera, a depth camera, and a microphone array. The device allows users to interact with a computer via a natural user interface in terms of gestures or voice commands. The authors believe that the research and development on using Kinect technology in healthcare will gain more momentum. The demand of Kinect-based applications is high, due to Kinect's low cost and portability, and its accurate and robust motion detection capability. In this chapter, the authors survey the current applications of using the Kinect technology in healthcare. Furthermore, they outline a number of open research issues that could overcome the limitations of the current Kinect technology.
Elliptic Curves

Elliptic curves are one of the more elegant objects in algebra. A background of the underlying arithmetic of curves is necessary for cryptography, because they are used for (at least) three purposes: for factoring integers, for cryptography itself, and for key exchange. The arithmetic of elliptic curves parallels in many ways the arithmetic of integers modulo primes or composites, at least. In this chapter we present an introduction to elliptic curves as background for later chapters that use them for cryptographic purposes.
New Educational Models to Train Engineers and Executives On Eco Friendly Technologies, Products and Sustainability Policies

Several innovative educational methods have been recently used in teaching various “green” engineering and technology management subjects at the National Technical University of Athens. In this article, we will present their rationale and approach, assess their performance and acceptance by students and educators, and identify their resulting conclusions and recommendations.
A Next Generation of IT

A potential new generation computing environment is emerging which combines wiki technology with semantic web concepts. This has brought about the fusion of the wiki execution ecosystem, a semantic web for model-driven applications, and a high-level language as an extension to wiki text for accelerated development. Semantic MediaWiki provides this platform and a fragment of a health record, including allergy intolerance as structured in HL7 FHIR with terminology bindings to SNOMED CT and to HL7 terminologies was developed by the author in a short timeframe (approximately 10 hours). The system navigates around the health record and controls the entry of terms in the record from controlled ValueSets. All terminologies and ValueSets are integrated into the prototype.
Credit Card Fraud Detection: Advanced Real-time Application of Deep Sequential Models

In contemporary times, the rapid growth of e-commerce technologies has rendered it possible for people to select the most popular items in terms of recommended price, quality and quantity among various services, facilities, shops and stores from all around the world. Intriguingly enough, the ease of doing things has also made it easier for fraudsters to abuse this huge opportunity. As credit card has emerged to be the most popular mode of payment, the fraudulent activities using credit card payment technologies are fast increasing as a result. Therefore, it is inevitable for a financial institution to think of an automatic and fool-proof prevention mechanism to detect and prevent fraudulent activities. Although many works have been done in this area using traditional statistical and machine learning methods, they suffer from deficiencies as most of them have not taken the sequential nature of transactional data into account. In this paper, we propose an assembly model based on sequential modeling of data using deep recurrent neural networks and a novel selection mechanism based on an artificial neural network to detect fraudulent actions. As the experiments demonstrated, our suggested model outperforms the advanced models in all assessment criteria.
SAS Nonlinear Models or Artificial Higher Order Neural Network Nonlinear Models?

This chapter delivers general format of higher order neural networks (HONNs) for nonlinear data analysis and six different HONN models. Then, this chapter mathematically proves that HONN models could converge and have mean squared errors close to zero. Moreover, this chapter illustrates the learning algorithm with update formulas. HONN models are compared with SAS nonlinear (NLIN) models, and results show that HONN models are 3 to 12% better than SAS nonlinear models. Finally, this chapter shows how to use HONN models to find the best model, order, and coefficients without writing the regression expression, declaring parameter names, and supplying initial parameter values.
The Impact of Artificial Intelligence and Virtual Personal Assistants on Marketing

This chapter will review the state of the art in AI, with a particular focus on applications in marketing. Based on the current capabilities of AI in marketing, the authors explore the new rules of engagement. Rather than simply targeting consumers, the marketing effort will also be directed at the algorithms controlling the consumers' virtual personal assistants (VPAs). Rather than exploiting human desires and weaknesses, marketing will need to focus on meeting the user's actual needs. The level of customer satisfaction will be even more critical as marketing will need to focus on establishing and maintaining a reputation in competition with those of similar offerings in the marketplace. This chapter concludes with thoughts on the long-term implications, exploring the role of customer trust in the adoption of AI agents, the security requirements for agents, and the ethical implications of access to such agents.
Quantum contracts between Schrödinger and a cat

Viewing quantum information as economic commodity, we provide a fundamental viewpoint towards a quantum theory of contracts. In particular a generic quantum protocol of the principal-agent relation is formulated in a framework of quantum games, and quantum models of moral hazard problem and adverse selection are addressed. New infrastructures are about to be created by the development of quantum technology, which will have a revolutionary impact on people's economic activities. In other words, the time will come in the near future when people will conduct their economic activities on the complex Hilbert space. However, this kind of economic activity is not envisioned at all in conventional economics, so a new theory is literally needed. These problems include public and private interests of exchanging quantum commodity, market design and contracts, for example. In this article, We present a quantum contract theory based on this new fulcrum, and solve the problem of information asymmetry between principal and agent, which has long been a central issue in classical contract theory.
A Study on Network Security Problems and Information System Protection of Computers and Internet

The current society has entered a new era of information development, and computer technology has also entered a new stage, integrated into the lives of ordinary people, and began to gradually penetrate into every corner of society. It has brought great rapidity and convenience to people, and in the network environment, also the efficiency of information transmission has greatly met people's demand for information. However, the emergence of problems of network information security will have a huge negative impact on the network system. This paper focuses on the problems existing in the current security of network information, and gives the strategies to solve the problems.
Active Learning Approach for Spam Filtering

It is general to relate an optimization problem with bound constraints and a linear equality constraint with training a support vector machine (SVM). In this paper, the Support Vector Machine (SVM) model trained by the Active Learning algorithm is proposed for spam filtering. This experiment proceeds the data preprocessing, training of the SVM model, application of Active Learning (AL), evaluation of performances, and comparisons of results between random sampling and AL. The graphics clearly exhibit the result that the Active Learning method could use only a small size of the dataset to achieve efficient and accurate spam filtering work. This experiment assists in enhancing the efficiency of working and processing emails.
A Critical Overview of Net Zero Energy Buildings and Fuzzy Cognitive Maps

ZEBs (zero energy buildings) and more specifically “net Zero Energy Building” (nZEB) have become a prominent wording to describe the synergy of energy efficient building and renewable energy utilization to reach a balanced energy budget over a yearly cycle. The lack of a common and accepted definition or even a good understanding of ZEB makes the approach of this problem very challenging. In this paper there is an evaluation of the criteria in the definition framework and selection of the related options. Also a methodology is approached, to set nZEB definitions in a systematic way. Today's different ZEB technologies, challenges and problems are identified and analyzed. For the first time the overall operation of nZEB and its performance is investigated and modeled using FCMs and learning algorithms. A set of low energy buildings using extensive energy and environmental data are simulated for all four seasons of a year. Interesting results are obtained, presented and discussed. Useful conclusions are drawn and future research challenging topics are presented.
Real-time Sensing and Visualization of Electromagnetic Situation Based on Multi-source Information Fusion

Abstract It is of great significance for real-time sensing and visualization of electromagnetic situation to grasp the battlefield situation. The most important procedure is to deal with multi-source mass electromagnetic perception data and realize the point to space electromagnetic situation data refactoring. The basic idea of this paper is to estimate the electromagnetic field intensity of any concerned position by space domain fusion of multi-source data fusion after time domain fusion. Firstly, the Grubbs criteria is used in the pretreatment of single sensor data, and then the Bootstrap re-sampling methods is used for single sensor information fusion. This method can eliminate the vagueness and uncertainty of a mass of sensing data in a short period of time. Secondly, by the D-S evidence theory, the multi-sensor perceptual data combined with the wave propagation model and expert information are fused, and finally the prediction of space electromagnetic situation data is reconstructed. Finally, calculation examples of single sensor fusion and multi-sensor fusion are given to illustrate that the developed methods can increase the credibility of the reconstructed electromagnetic situation.
Visual Analysis on Chinese Smart Library Researches based on Citespace

The paper uses the bibliometric method to conduct visual analysis on Chinese smart library researches, presenting research status-quo, hot-spots, and trend by a data visualization software called Citespace. Taking 1938 Chinese journal papers from 1993 to 2020 of CNKI.net as data source, the authors select publication time and keywords to analyze the time distribution characteristics, keywords co-occurrence, clustering, and burst terms of these papers by Citespace. It is found that the volume of papers is in a state of rational and continuous development. The hot-spots focus on library construction, information technology, user smart service, and “smart” fields. The research on Chinese smart libraries has blossomed in many aspects. The research has its innovation, and its trend is flexibly adjusted to the background of the times and the development of national strategies.
Conclusion

Abstract The conclusion summarises the key findings of each chapter and reflects on the future research required in understanding the place of the humanities in higher education, from explorations of student perceptions of value, interrogations of new hybrid subjects such as the medical humanities and the creative industries, to better sharing knowledge concerning global changes to the value of education through engagement with diverse local contexts. The conclusion to ‘Value and the Humanities’ calls upon scholars to engage in articulations of value that reflect their disciplines. In the present moment, with the rise of populist thinking, this book concludes with the acknowledgement of the vital need for the reinvigoration of articulations of value.
Privacy Preserving String Matching for Cloud Computing

Cloud computing has become indispensable in providing highly reliable data services to users. But, there are major concerns about the privacy of the data stored on cloud servers. While encryption of data provides sufficient protection, it is challenging to support rich querying functionality, such as string matching, over the encrypted data. In this work, we present the first ever symmetric key based approach to support privacy preserving string matching in cloud computing. We describe an efficient and accurate indexing structure, the PASStree, which can execute a string pattern query in logarithmic time complexity over a set of data items. The PASStree provides strong privacy guarantees against attacks from a semi-honest adversary. We have comprehensively evaluated our scheme over large real-life data, such as Wikipedia and Enron documents, containing up to 100,000 keywords, and show that our algorithms achieve pattern search in less than a few milliseconds with 100% accuracy. Furthermore, we also describe a relevance ranking algorithm to return the most relevant documents to the user based on the pattern query. Our ranking algorithm achieves 90% + above precision in ranking the returned documents.
Introduction

This book deals with the digital audio watermarking copyright assurance. The watermarking data that will be utilized incorporates text messages, copyright audio, written by hand marks, and cell phone numbers. The purpose behind this is they are more instructive contrasted with pseudo irregular groupings. The watermarking data will be encoded before embedding it in the audio. DSSS algorithm is used to increase the security of this system. The embedding process of the watermark information is performed in the frequency domain rather than the spatial domain. The combination of DWT, SVD, and DFT methods will be utilized for this reason. The watermarks ought to be imperceptible and make insignificant contortion to the host audio. The main objective of this research is to propose a new algorithm that can embed and extract the watermarking information and fulfill the above prerequisites. The execution of the newly proposed algorithm will be surveyed by testing them utilizing a group of various audio file types and against various attacks.
Inducing Modular Rules for Classification

This chapter begins by considering a method of post-pruning decision rules generated via a decision tree, which has the property that the pruned rules will not generally fit together to form a tree. Rules of this kind are known as modular rules. When using modular rules to classify unseen test data a conflict resolution strategy is needed and several possibilities for this are discussed. The use of a decision tree as an intermediate representation for rules is identified as a source of overfitting. The Prism algorithm induces modular classification rules directly from a training set. Prism is described in detail, followed by a discussion of its performance as a classification algorithm relative to TDIDT.
Lingue e culture locali nei processi contemporanei di patrimonializzazione e di costruzione identitaria

In a solid tradition of studies, linguistics joins forces with the anthropological study of local cultures so as to identify and reflect on the cultural contexts that lead to the conservation or to the transformation of both linguistic and cultural facts. Such reflections especially focus on the way that local languages and cultures are turned into cultural heritage that support identity.In this light, and that of a specific case study, this essay analyses how local communities recall dialects and traditions as a way to create cultural heritage and maintain a relationship that is coherent, not corresponding with the past while attempting to construct a specific identity that can give them psychological stability and security within the global arena in which they also act.
Gain and Maintain Access

The gaining access phase in the ethical hacking process focuses on getting access to the individual host on a network based on the information collected during previous phases. Actual attacking starts in this phase, where an attacker will carry out password cracking/password sniffing attacks along with privilege escalation attacks to gain administrative privileges on the target host bypassing computer security. Once access is gained, maintaining that access on compromised hosts becomes important for an attacker in order to carry out future attacks. This chapter includes a study of tools and techniques like password cracking or social engineering attacks in order to gain the access on target machines based on the information collected during the previous phases. The chapter also introduces the tools and techniques used for escalating privileges by exploiting vulnerabilities, executing spyware/backdoor/key loggers/rootkits/trozans applications, etc. The chapter also explains the techniques used to maintain access in compromised hosts, to cover tracks/evidence, and methods to avoid detection. An attacker may use rootkits during this phase to hide his presence and maintain access to the compromised hosts. An attacker may hide files using rootkits/steganographic techniques, hide directories, hide attributes, use alternate data streams (ADS), place backdoors, and cover tracks by modifying/deleting log files. All these techniques are explained in this chapter.
Data Integrity in Mobile Cloud Computing

With the help of cloud computing Mobile Cloud Computing (MCC) overcomes the limitations of a mobile device such as security, performance and environment. But, security of the data stored in the cloud is a very challenging issue. Since the cloud cannot be fully trusted, data stored in the cloud is not fully secured. Integrity of the stored data is very important for the data owner. Therefore, it is a big problem to maintain the integrity of the data stored in the cloud environment. This chapter discusses existing schemes for data integrity in the mobile cloud environment. In this chapter a scheme has been proposed for enhancing data integrity in Mobile Cloud Environment. To make integrity checking fast the size of the data file is used. It has also been shown that how fast the integrity loss can be detected if the file size is considered. Finally, the proposed scheme is compared with some of the existing scheme.