Reviewerly/exHarmony huggingface dataset:
An Estimation for Bitcoin Price Volatility

According to public opinion cryptocurrencies, especially bitcoin, have been attention taking lately. This can be addressed to the innovative characteristics of blockchain (the basis of the entire digital currency system), namely, the decentralized structure, not using any intermediaries, being anonymous, fast and secure. Being a fluctuating investment tool, the cryptocurrency system exhibits unpredictable ups and downs that make it a speculative asset. This research tries to estimate the bitcoin price volatility using the GARCH model where four different over-the-counter-market data, such as the BITSTAMP, COINBASE, ITBIT, KRAKEN are employed. The results for these four over-the-counter- markets indicate high volatility. Professionals and individuals occupying with bitcoin should take this speculative structure into consideration.
Towards a Framework for Agent-Based Healthcare Monitoring

Currently, several countries have become aging societies and are moving towards aged societies. This results from low birth rate and the average life expectancy increasing in these countries. The subsequent concerns are about a lack of carers to look after those elderly people. Therefore, the need of technology-driven solutions to support elderly to live independently is increasing. This research intends to develop a conceptual framework supporting personalised healthcare for seniors. The agent-based, Semantic Web, and Internet of Things technology have been integrated to monitor elderly people’s vital signs when they are at home. In case of the presence of the vital sign abnormality, the carers and physicians will be notified in order to investigate the problem and provide help immediately. The result of this research is expected to provide assisted living facility for elderly people to stay independently as long as possible in their homes and to reduce the burden of carers.
Improving financial condition of small scale farmers through mobile based crop suggestion services

This Research discusses the problems faced by small scale farmers in Nathoke Village, Lahore, Pakistan and propose a solution to alleviate their problems. Research propose to integrate a small-service solution in an application, Meri Zameen already working and helping farmers in the fields in Punjab, Pakistan developed by Pakistan Information Technology Board. Agriculture Agents in Punjab inform farmers about modern techniques of farming and help them in acquiring them through this application and their experience. The research also puts the artiya, beyopari and fellow farmers, in light and shows how they play as a protagonist and antagonist in manipulating the decision making of farmers.
An Analysis of Concrete Test Weight with Different Water Cement Factors Using Histogram in Quality Management

Concrete is a product with the composition of binding medium in which there is an aggregate pigments or particles. The binder is formed by cement and water mixture. Cater cement factor affects the compressive strength result. In producing concrete, a quality control is needed to obtain performance or process variation. In order to obtain the quality, statistical analysis using histogram method in the form tables and graphs is needed. From the measurement analysis results of 30 concrete test objects with different cement water factors getting uneven and unpredictable distribution results. The greater the cement water factor, the more dispersed the distribution of the cement will be but the weight of the concrete will decrease.
Reversible Data Hiding

The chapter presents an application of reversible data hiding for the authentication of image travelling over a hostile and insecure communication channel. The reversible data resides in the image and tracks any changes done to it on a communication channel. The extraction of data and any modification to its structure reveals changes in the image. This allows the use of data hiding for forensic purpose. The reversible data hiding provides an additional advantage along with active forensics. The image regains original form after removal of the embedded data. However, reversible data hiding is an interplay between the image quality and watermarking capacity. The chapter presents the generic framework for data hiding and discusses its special case reversible data hiding. It presents capacity-behavior analysis of the difference expansion scheme. It performs in-depth analysis on the type of predictor and its impact on the capacity of the reversible data hiding scheme. Finally, the chapter presents a case study to showcase the use of reversible data hiding for image authentication.
Introduction to Artificial Goals and Challenges

This chapter introduces the literature on artificial grammar that forms the foundation for this study.
NON-PARAMETRIC APPROACH FOR PRELIMINARY PROCESSING OF EARTH REMOTE SENSING DATA

Researches described in the paper are aimed at studying the methods of data preprocessing from a sample of observations of a system characterized by input-output values of variables. We consider the data containing omissions and outliers. Algorithms for leveling outliers in a sample of observations, as well as algorithms for filling data gaps are presented. In addition, it is implemented a data repair algorithm that is able to recover lost values (outliers) after their exclusion. Our studies are useful in geographic information systems or in the analysis of information received from satellites during remote sensing of the earth.
Framework of cloud web services for processing remote sensing data

We consider a distributed network of cloud web services for processing satellite data, which provides data processing facilities for Earth remote sensing within SaaS model. In fact, this is a set of web services that implement the functional modules of the PlanetaMonitoring remote sensing data processing system.
Reassessing User-Friendliness of Evolving Graphical Interface Design from Social Perspective

The saturation of software in industries is too obvious a fact to be mentioned. Nearly every business in the world is dependent upon software industry. Organizations are keen toward enhancing the user experience of their software interface. Earlier, the software applications were command line driven where users had to remember and type commands to which system performed associated actions. But nowadays, virtually all applications are operated through graphical user interface (GUI). Users just drag mouse, click buttons, and apply combinations of keystrokes to accomplish a task. This is how GUIs have made the software friendlier to the users. The aim of the research is to find out how users become accustomed to features over time, how they interpret the meaning associated to the symbols in different contexts, and how semiotics plays a role here to provide affordance to the users, thereby helping them familiarize with the interface quickly.
An Economic and Public Policy view of Demonetization in India

The paper will look at the recent demonetization exercise that the government of India imposed on its people. The demonetization exercise was marketed from a Public Interest perspective as a way to eliminate corruption, increase the tax base and to fight terrorism. However, the Public Choice perspective brings out the political self-interest involved in the demonetization exercise. The role of foreign and domestic interest groups involved in pushing for demonetization will be explored. Insights from Austrian Economics will show why top down planning fails and results in more controls. Insights from Public Policy shows that the lasting impact of demonetization is an increased interest in digital payments.
Goal-based Ontology Creation for Natural Language Querying in SAP-ERP Platform

The omnipresence of mobile devices coupled with recent advances in automatic speech recognition capabilities has led to a growing demand for natural language querying (NLQ) interfaces to retrieve information from data repositories. Going beyond consumer tools like Siri and Cortana towards industry settings, natural language interaction has been observed to be the next generation user interface to business applications (such as ERP systems) after GUI and touch-based UIs on mobile. It enables business users to ask questions in natural language without needing to have any programming knowledge (such as ABAP or SQL) and knowledge about the data representation mechanisms (such as data schema). State of the art NLQ systems such as ATHENA represents the domain schema in the form of an ontology and performs interpretation using the ontology. The primary challenge in developing a NLQ system for querying data in SAP-ERP is its large ontology which results in an inefficient interpretation. We propose a Steiner tree based novel algorithm which generates a relatively smaller goal-oriented ontology which does not affect the NLQ interpretation. We investigate practical ways to address the problem of precise interpretation generation and introduce an algorithm for Lazy Inclusion. We present the effectiveness of the proposed techniques in the SAP-ERP domain with a set of benchmark natural language questions.
Mobile Number Portability Using a Reliable Cloud Database Appliance to Match Predictable Performance

The great interest for deploying applications in cloud infrastructures is rapidly growing due to its convenience and ease of use. Despite, the large number of different applications migrated to cloud, there are still applications that are not frequently met on cloud infrastructures. Applications defined as time critical or data-intensive are applications of this kind. The need of high resilience alongside with high performance lead these types of applications to run on mainframes, rather than on cloud infrastructures, as cloud is not able to satisfy them under strict Service Level Agreements (SLAs) and without predictable performance. To investigate further this area this paper aims to report on the research issues around time critical and data-intensive applications deployed on cloud and present Mobile Number Portability (MNP) Use Case migration to cloud with predictable performance.
Determining image sensor temperature using dark current

The state of the art method for fingerprinting digital cameras focuses on the non-uniform output of an array of photodiodes due to the distinct construction of the PN junction when excited by photons. This photo-response non-uniformity (PRNU) noise has shown to be effective but ignores knowledge of image sensor output under equilibrium states without excitation (dark current). The dark current response (DSN) traditionally has been deemed unsuitable as a source of fingerprinting as it is unstable across multiple variables including exposure time and temperature. As such it is currently ignored even though studies have shown it to be a viable method similar to that of PRNU. We hypothesize that DSN is not only a viable method for forensic identification but, through proper analysis of the thermal component, can lead to insights regarding the specific temperature at which an individual image under test was taken. We also show that digital filtering based on the discrete cosine transformation, rather than the state-of-the-art wavelet filtering, there is significant computational gain albeit with some performance degradation. This approach is beneficial for triage purposes.
Recursive General Secret Sharing Scheme Based on Authorized Subsets

The basic idea of secret sharing is that a dealer distributes a piece of information about a secret to each participant in such a way that authorized subsets of participants can reconstruct the secret but unauthorized subsets of participants cannot determine the secret.We propose a new secret sharing scheme realizing general access structures, which is based on authorized subsets.The proposed scheme is perfect and can reduce the number of shares distributed to one specified participant.In the implementation of secret sharing schemes for general access structures, an important issue is the number of shares distributed to each participant.We can apply the proposed scheme to the same access structure recursively.That is, the proposed scheme can reduce the number of shares distributed to another participant once again by applying the proposed scheme recursively.We apply the proposed scheme to all access structures on five participants in order to evaluate the efficiency of the proposed scheme.
Semantic Web Service for Global Apparel Business

Nowadays a substantial share of the production processes of the world's apparel business is taking place in developing countries. In the apparel business, supply chain coordination needs resource and information sharing between business partners. Semantic web service computing (SWSC) provides numerous opportunities and value-added service capabilities that global apparel business requires to exchange information between distributed business partners. The ability to dynamically discover and invoke a web service is an important aspect of semantic web service-based architectures. This chapter describes the main features of an ontology-based web service framework, known as CSIA (collaborative service integration architecture) for integrating distributed business information systems in a global supply chain. The CSIA framework uses a hybrid knowledge-based system, which consists of structural case-based reasoning (S-CBR), rule-based reasoning (RBR), and an ontology concept similarity assessment algorithm.
CA-KSE: a combinatorial algorithm for benchmarking in knowledge sharing environment

Purpose Over the past decade, the cost of product development has increased drastically, and this is due to the inability of most enterprises to locate suitable and optimal collaborators for knowledge sharing. Nevertheless, knowledge sharing is a mechanism that helps people find the best collaborators with relevant knowledge. Hence, a new approach for locating optimal collaborators with relevant knowledge is needed, which could help enterprise in reducing cost and time in a knowledge-sharing environment. The paper aims to discuss these issues. Design/methodology/approach One unique challenge in the domain of knowledge sharing is that collaborators do not possess the same number of events resident in the knowledge available for sharing. In this paper, the authors present a new approach for locating optimal collaborators in knowledge-sharing environment using the combinatorial algorithm (CA-KSE). Findings The proposed pattern-matching approach implemented in Java is considered efficient for solving the issue peculiar to collaboration in knowledge-sharing domain. The authors benchmarked the proposed approach with its semi-global pairwise alignment and global alignment counterparts through scores comparison and the receiver operating characteristic curve. The results obtained from the comparisons showed that CA-KSE is a perfect test having an area under curve of 0.9659, compared to the other approaches. Research limitations/implications The paper has proposed an efficient algorithm, which is considered better than related methods, for matching several collaborators (more than two) in KS environment. The method could be deployed in medical field for gene analysis, software organizations for distributed development and academics for knowledge sharing. Originality/value One sign of strength of this approach, compared to most sequence alignment approaches that can only match two collaborators at a time, is that it can match several collaborators at a faster rate.
Exploring the Opportunities and Challenges of Open Source Software and Its Economic Impact on the Cybersecurity Market

Organizations today face IT security challenges on many fronts. These include controlling user access to systems, resources, and data security issues that encompass secure storage, secure transmission, data authenticity and data integrity. These requirements are met by establishing the right policies, controls, and mechanisms that are put in place to effectively protect sensitive data. Therefore, this research aims to see if open source software has the potential to influence the cybersecurity market that is currently dominated by proprietary software. However, in order to accomplish such a task, certain conditions must be met. Such as understanding of the history behind open source software, the positive and negative influences it carries when dealing with this type of software. As well as compare and contrast current proprietary solutions with open source solutions, in order to grasp the potential economic impact of open source software leading onwards into the future. The ideal findings would be to outline the factors that are holding back open source software, and whether these factors are adjustable or correctable over time. Another aim is to highlight the potential financial benefit that comes from switching to or prioritizing OSS security solutions. As well as come up with any recommendations that would help aid businesses and organizations when it comes to obtaining suitable OSS security solutions.
The Scalability Analysis of a Parallel Tree Search Algorithm

Increasing the number of computational cores is a primary way of achieving high performance of contemporary supercomputers. However, developing parallel applications capable to harness the enormous amount of cores is a challenging task. Thus, studying the scalability of parallel algorithms (the growth order of the number of processors required to accommodate the growing amount of work, below we give a clear definition of the scalability investigated in our paper) is very important. In this paper we propose a parallel tree search algorithm aimed at distributed parallel computers. For this parallel algorithm, we perform a theoretical analysis of its scalability and show that the achieved scalability is close to the theoretical maximum.
A Comparison Study of Different Algorithms for Energy-Aware Placement of Virtual Machines

Cloud Computing services are essential to modern society. The increasing number of people and organisations using these types of services results in a higher demand in datacenters, which in turn, is raising energy consumption and carbon footprint. Reducing energy consumption has become a subject of interest to many researchers, who approach the problem with different optimisation processes and scheduling algorithms. This article shows an extensive vision of the steps followed by a datacenter, upon the arrival of a task or application by showing how it traverses along the processing time-line, and focusing on the energy-aware point of view of the datacenter. A crucial role is played by placement process of Virtual Machines (VM). Simulations using the CloudSim simulator were performed and results are reported to show a performance comparison of several selected algorithms, which focus in the VM placement problem, and considering two scenarios: empty and loaded datacenter. The results are evaluated in terms of energy consumption, quality of service and resource memory efficiency, among others.
The Possibility of the Generation of Literary Works by Abduction

This chapter will show the possibility of literary-work (poems, stories, novels, etc.) generation. First, the author introduces the research field, language-sense processing engineering (LSE). The key concept in LSE is language sense. The author defines “language sense” as affective or psychological aspects of language, to analyze and show several types of literary-work generation. For instance, the author analyzes the emotional and technical part of waka generation to generate new waka (Japanese poems). One feature that can be used for literary-work generation is “intertextuality” proposed by J. Kristeva. Below, the possibility of the automatic literary-work generation will be shown using a strategy to generate waka. In addition, several strategies to generate literary works will be shown to illustrate the possibility of automatic literary-work generation. In addition, the author will show the possibility of literary-work generation by abduction, which is rather intelligent generation.
Correlation image system 3D DANTEC as a modern system for measuring deformation

The work presents the possibilities created by the multi-camera 3D image correlation system. The experience is based on non-contact measurement of displacements and deformations. The measurement was used basically to estimate the deflection line of the bending beams and values of strains and displacements at various points of the cross-section. The measurement was carried out by tracking the displacements of the prepared surface of the sample. The results of the numerical analysis were also presented, which were compared with the experience carried out on the measurement stand.
A MRI View of Brain Tumor Outcome Prediction

On the one hand, cancer and tumor are one of the most feared terms in today’s society. It refers to an unstable growth of cells that potentially invade the surrounding tissues and may eventually lead to edema or even death. On the other hand, the term tumor is often misleading since people assume that it is the same as cancer, but this is not necessarily true. A cancer is a particularly threatening type of tumor. The word tumor simply refers to a mass, and in particular a brain tumor is a mass located in the patient’s brain that may seriously threaten his/her life. Thus, it is crucial to study which factors may influence the outcome of a brain tumor to improve the given treatment or even make the patient more contented. Therefore, this study presents a decision support system based on Magnetic Resonance Imaging (MRI) data or knowledge (if the data is presented in context) that allows for brain tumor outcome prediction. It describes an innovative approach to cater for brain illness where Logic Programming comes in support of a computational approach based on Case Based Reasoning. An attempt is made to predict whether a patient will die or survive with or without a tumor, where the data or knowledge may be of type unknown, incomplete or even self-contradictory.
Study on M-Learning Usage Among LIS Students With Special Reference to Alagappa University

Mobile learning comprises any kind of learning which is done on mobile and handheld gadgets either in or out of class, or learning which takes place “on the go” as part of class time, or outside. Although mobile learning is often taken to be synonymous with the use of mobile phones, it is increasingly associated with other devices such as tablet computers, portable games machines, e-books, and other devices which allow people to continue more traditional approaches to learning as they move through their daily lives. As such, it fits comfortably into definitions of blended learning. Educators and trainers are empowered since they can use the mobile technology to communicate with learners from anywhere and at any time. At the same time, educators and trainers can access learning resources from anytime and anywhere to plan and deliver their lessons.
An Intelligent Registration Management System for Freshmen

The registration management for freshmen is an important work in a university. The traditional registration mode is based on a paper form. The freshmen need to walk to each department to register and get passing stamp. It’s inefficient. In order to solve this problem, an intelligent registration management system based on the Internet is proposed in this paper. The functional structure, identity authentication and the data integration are also discussed. Through the intelligent registration management system, the freshmen can complete the registration procedures online. They don’t have to walk to all the departments, and there is no restriction on time and site. Finally, the efficiency of the registration management is improved.