Reviewerly/exHarmony huggingface dataset:
An investigation into the impact of employee empowerment on organisational commitment: the case of Zajil International Telecom Company of Jordan

The aim of this study is investigating the impact of the main dimensions of employee empowerment (power, knowledge, self-determination and work-impact) on the basic types of organisational commitment (affective, normative and continuance) at Zajil International Telecom Company of Jordan. A sample of 220 employees (the whole technical and managerial staff) was withdrawn from a total population of 300 employees working at the Zajil International Telecom Company. A six-part questionnaire was developed, academically refereed, modified and then distributed. 217 questionnaires were correctly filled in and returned, that were later used for conducting validity, regression and correlation statistical testing using SPSS package. The main results of this study have plainly indicated that employee empowerment in terms of (power, knowledge, self-determination and work-impact) has a significant positive impact on the key types of organisational commitment (affective, continuance and normative). This result represents the originality of this study. It would be reasonable to state that the main objective of this study (determining to what extent that the employee's job title and nationality moderated the impact of employee empowerment on organisational commitment at Zajil International Telecom Company) was attained.
Biometric Authentication in Cloud Computing

The cloud clients are confronting serious issue of phony login and information robbery. So it is extremely important to confirm the cloud client that demands access to a record for giving protection and security. Distributed computing is turning into a hot pattern in IT businesses step by step. A considerable lot of the companies are utilizing cloud for putting away and keeping up their enormous information on cloud servers. In bygone day's passwords and pins are utilized for verifying information. Along these lines, Hackers can split these passwords and sticks and results in the uncertain information, so we need a safe system to shield the information from interlopers and programmers. For that reason, we are utilizing the idea of Biometric Authentication alongside information pressure and information encryption. The systems utilized for biometric confirmation in cloud faces execution issues like time complexities and space complexities.Symmetric Advanced Encryption Standard (AES) Algorithm is utilized for encoding the mystery esteem with biometric key
Opinion Analysis on Twitter Data and Detecting Spam Tweets

Social network sites are getting to be noticeably awesome through a great many clients. The data that is accumulated from the clients has square with favorable circumstances to their companions and spammers. Twitter is a standout amongst the most well-known informal organizations that, clients can send short printed messages in particular tweet. Opinion analysis is utilized as a part of different fields to reach to a last reaction. For the most part different internet business sites utilize this analysis to enhance their organizations. In this project we used an improvised opinion analysis which includes spam recognition. Looks into have demonstrated that this specific system is additionally subjected to spammer's attack more than other informal communities and more than six percent of tweets are spam. So, analyze of the spam tweets is imperative. In this research we firstly decide different components that are in charge of spam tweets and after that we distinguish them. Previous works in this field of spam tweets were completed by classification algorithms. Results appear, when this specific algorithm is set reasonably to the measure of exactness and accuracy of spam tweets location will enhance and false positive rate will decrease to the base of an incentive in correlation with the previous works.
German police get ‘ten-print’ fingerprint scanners

The German Federal Police have adopted ‘ten-print’ fingerprint scanners from JENETRIC as they beef up their border controls.
An efficient vote casting system with Aadhar verification through blockchain

In the recent past security for vote casting system plays a vital role in the autonomous constitutional authority of election. A democratic country like India highly depends on the fail proof voting system to elect the government. The many security systems have evolved to ensure the electronic voting system to avoid malpractice during election. This paper describes an electoral system for the Indian election on blockchain technology and Aadhaar verification. The proposed system provides optimal security for the voting system and preserves votes stored in the electronic voting machine (EVM). The technology behind blockchain and Aadhaar verification are used to simplify the process of the voting system. The Aadhaar number has to be fetched and verified with the database after entering every vote on the machine. The information has to be verified for the vote of an individual to be accepted by EVM and stored in block chain ledger. All the confidential information is recorded in cloud using Internet of Things (IoT) thus providing cyber security from all vulnerability. The experimental results has proved that the proposed system is efficient and accuracy for providing security for voting system.
A new reasoning-based approach for measuring the magnetic field emitted by portable computers

This paper explores a new reasoning-based approach for measuring the extremely low frequency magnetic field emitted by a portable computer. The introduced approach and the widely accepted TCO standard are compared each other and discussed. This comparison shows that the well-known magnetic field measurement TCO standard has important limitations and disadvantages. In fact, the new reasoning-based approach obtains measurement results of the extremely low frequency magnetic field which are closer to the working conditions of the portable computers' users. Accordingly, the introduced measurement methodology is more user-centric than the TCO standard measurement and should be employed in a future standardisation.
Bidirectional Recurrent Neural Network Language Model: Cross Entropy Churn Metrics for Defect Prediction Modelling

Software Defect Prediction (SDP) plays an active area in many research domain of Software Quality of Assurance (SQA). Many existing research studies are based on software traditional metric sets and defect prediction models are built in machine language to detect the bug for limited source code line. Inspired by the above existing system. In this paper, defect prediction is focused on predicting defects in source code. The aim of this dissertation is to enhance the quality of the software for precise prediction of defects. So, that it helps the developer to find the bug and fix the issue, to make better use of a resource which reduces the test effort, minimize the cost and improve the quality of software. A new approach is introduced to improve the prediction performance of Bidirectional RNNLM in Deep Neural Network. To build the defect prediction model a defect learner framework is proposed and first it need to build a Neural Language Model. Using this Language Model it helps to learn to deep semantic features in source code and it train &amp; test the model. Based on language model it combined with software traditional metric sets to measure the code and find the defect. The probability of language model and metric set Cross-Entropy with Abstract Syntax Tree (CE-AST) metric is used to evaluate the defect proneness and set as a metric label. For classification the metric label K-NN classifier is used. BPTT algorithm for learning RNN will provide additional improvement, it improves the predictions performance to find the dynamic error.
Active acquisition system of LBS-based logistics freight source information

In order to solve the bottleneck of logistics information exchange and meet the demand for getting freight source information in time, this paper proposes a solution of active acquisition system of logistics sources information based on LBS with Android mobile terminal. By using GPS/WIFI positioning technology to achieve the acquisition of the information of user's current location and through wireless network, the data are further sent to the spatialtemporal database of service terminal, where the spatial data and attribute data about logistics sources information are integrated and stored. Then these data are analysed and processed by use of the dynamic programming algorithm based on real-time logistics sources information. Finally the Baidu API is used to realise the visualisation of post-processing of logistics sources information so that the services in active acquisition of peripheral logistic information and optimal receiving route planning might be provided.
Decentralized Organizations

Bitcoin can be thought of as the first prototypical Decentralized Autonomous Organization (DAO). It created a network-based ecosystem of participants who contribute computational power toward a singular goal. In Bitcoin, the underlying protocol created a financial service that rewards miners for providing verification services, and this setup became a rudimentary decentralized organization. In this chapter, we will focus on more-complex organizations created on the blockchain with Aragon. Aragon is a decentralized application (DApp) that lets anyone create and manage different kinds of organizations (NGOs, non-profits, foundations) on the Ethereum blockchain. In the early days of Ethereum, creating a DAO and implementing even the most basic functions required complicated smart contracts and Solidity code. Aragon has simplified this process. It implements the basic features of an organization in a base template that gets deployed whenever a user instantiates a company. Most of the traditional features such as a cap table, voting abilities, fundraising, and accounting are offered in the Aragon template as a decentralized counterpart running on the blockchain. In addition, an Aragon company can be customized in a very granular fashion and extended with new modules that can be added to a company’s existing smart contracts. Aragon enables different organizations to control the level of trust built into them.
Physics-Based Estimates of the Maximum Magnitude of Induced Earthquakes in the Groningen Gas Field

&amp;lt;p&amp;gt;The induced seismicity in the Groningen gas field, The Netherlands, has led to intense public concerns and comprehensive investigations. One of the main challenges for assessing future seismic hazard in the Groningen gas field is to estimate the maximum possible earthquake magnitude (Mmax) that could be induced by gas extraction. Previous methods are strongly rooted in empirical and statistical approaches that are inherently limited by the scarcity of data. Here, we combine a physics-based dynamic rupture model based on the 3D theory of fracture mechanics with field-based and lab-based constraints to estimate Mmax in the Groningen gas field. If earthquakes in the reservoir have a rupture depth extension constrained by the reservoir thickness, the largest earthquakes should develop a large aspect ratio (longer horizontally than vertically). The model is thus an extension of the 3D theoretical rupture model on long faults with uniform stress and strength developed by Weng &amp;amp; Ampuero (2019), in which we have incorporated spatial heterogeneities, such as along-strike variable fault width, depth-dependent initial stresses and friction properties. The essential parameters that control rupture propagation and earthquake magnitude are the stored elastic energy and the fracture energy. Our method requires estimates of the stored elastic energy on reservoir faults as a result of the stresses induced by differential reservoir compaction during depletion. The fracture energy is constrained by laboratory experiments and theoretical frictional models. Coupling physics-based rupture models with field and lab observations provides an estimate of Mmax in the Groningen gas field and serves as a practical step toward physics-based seismic hazard assessment for other gas fields in the world.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Citation:&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Weng, H. and J. P. Ampuero (2019). &amp;quot;The Dynamics of Elongated Earthquake Ruptures.&amp;quot; Journal of Geophysical Research: Solid Earth.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;br&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/p&amp;gt;
Proposed frame-based expert system to construct student's knowledge model in intelligent tutoring systems

During the last decade, many of the Intelligent Tutoring Systems (ITS) have been developed in different domains. ITS deliver important learning gains outside classroom environments. Expert systems have been extensively used to implement ITS in education. Frames are widely used as a knowledge representation for the expert systems. This paper proposes and discusses the construction of student's knowledge model in ITS using a frame-based expert system that can adapt to the students’ cognitive characteristics.
A Research on the Factors that Impact the Effectiveness of Organizations in IT AND ITES in Coimbatore

Organization effectiveness determines how well an organization achieves its objectives with the given resources. In the present study the factors that influence organization effectiveness like organization culture, quality of work life, organization change and demographic factors have been considered for the study. The study was conducted in Coimbatore City as it is the second largest software producer in Tamil Nadu, contributing to around 8% of the total GDP. 400 respondents were selected randomly and questionnaires were collected from them. The collected data have been analyzed using regression analysis, and it is found that among all the demographic factors, gender and total workforce in the organization have influence on organization effectiveness. Organization culture, quality of work life and Organization change also play a part. Based on the findings, suggestions and conclusion have been given.
Design and Analysis of Multi - Heuristic Based Solution for Task Graph Scheduling Problem

Heuristic based strategies have always been of interest for researchers to achieve sub-optimal solutions for various NP-Complete problems. Human evolution based methods have been an inspiration for research since ages. One of the many evolutionary strategies based on the principle of genetic algorithm have been able to provide much sought after sub-optimal solutions for various NP-Complete problems. One of the most sought after NP-Complete problem is Task graph scheduling i.e. optimally execute the schedule of tasks on available parallel and distributed environment so as to achieve efficient utilization of available resources. Task scheduling is a multi-objective combinatorial optimization problem, with key parameters being reduced completion time and effective load balance on the available resources. Various algorithms have been proposed by various authors to achieve the above mentioned goal with the help of various heuristics like list scheduling, task duplication and critical path based. The algorithms proposed by various authors like Highest Level First Execution Time (HLFET), Modified Critical Path (MCP), Duplication Scheduling Heuristic (DSH), Linear Clustering (LC) and Dynamic Critical Path (DCP), belonging to each heuristic mentioned before will be taken under study. Previously these algorithms have been individually reported to be efficient in some certain restricted environment parameters with certain limitations; offering very preliminary improvement on the state of art of one single type of environment. Designers face difficulty in choosing the optimal algorithm for the generalized environment. This paper will identify the gaps in existing literature that forms the base of every research focusing in the direction of improvement of task graph scheduling algorithms. Further, this paper will propose a hybrid meta-heuristic i.e. Genetic Algorithm based task graph scheduling solution and perform a comparative study of aforementioned algorithms.
Random Number Generator

This chapter explains how to use Excel to take a random sample of people (or objects) from a sampling frame that contains the list of people (or objects) from which you want to take a random sample. You will learn how to use Excel to create frame numbers for generating random numbers, why a set of duplicate frame numbers is important, and the Excel commands needed to sort the duplicate frame numbers into a random sequence. In addition, you will learn how to print out your result so that all of the information fits entirely onto a single page of paper. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem for each chapter is presented in the Practice Test given in Appendix B along with the answers in Appendix C of this book.
Mathematical Modelling for Prediction and Classification of Neonatal Infections by using Rough Set

Human contagious diseases are basically affected newly born baby. Millions of death occur due to these diseases of our intention to give a prediction of such diseases. Study report analysis the symptom of this diseases with minimum attributes by using Rough set Technique and to predict the contagious diseases are using Time series model.
Formation of communicative skills of applicants of higher education in the process of studying the interfaculty discipline “generations X, Y, Z and the challenges of modernity

The need to form the communicative skills of applicants for higher education is determined by the requirements of the modern labor market, increasing requirements for the quality of education. Higher education institutions have all the potential to meet this challenge and cover the entire range of development of students communication skills and abilities in the learning process. The role of higher education institutions in training personnel to meet the needs of the labor market is not only to provide graduates with professional knowledge, skills and abilities, but also in the cross-cutting development of general, soft skills required for higher education applicants to adequately meet the challenges of today’s competitive world. We consider the formation of students’ communicative skills and abilities from the standpoint of the conceptual provisions of the competence-based approach in the modern educational paradigm. Pedagogical conditions and prospects for the formation of students communicative skills are associated with the development and implementation of appropriate activities in the educational process, reflecting the patterns, content, logic and structure of the development and improvement of students communicative potential. The study of the formation of students communication skills was based on the selection of significant indicators, which were measured using diagnostic techniques. The article reveals the possibilities of developing students communicative skills in the process of studying the interfaculty discipline «Generation X, Y, Z and the challenges of our time», taking into account innovative trends in modern higher education and with an emphasis on modeling situations that may arise in future professional activities in the system interaction of four generations.
A case-based reasoning system for software reuse

Developing and building multi-layered systems that meet users' needs and expectations is considered an essential issue that affects the overall quality of the product. In the software development life cycle (SDLC), software development teams need to apply several systematic activities at interrelated stages to produce a project that meets customer expectations. However, developers usually encounter enormous challenges while developing new projects. To eliminate these challenges and to develop better and reliable software, a new design approach that is based on systematic software reuse and CBR technique is discussed in this paper. A software design system that adopts the reusability approach in software engineering and the CBR technique was applied to provide solutions in the form of software patterns based on functionalities and features of similar past projects. The produced system will attempt to eliminate the challenges regarding time, effort, and financial constraints by reducing the effort needed in software development activities regarding requirement elicitation, analysis, and specification.
Practical quantum digital signature with a gigahertz BB84 quantum key distribution system: erratum

In this erratum the formulas (6) and (8) of Opt. Lett.44, 139 (2019) OPLEDP0146-959210.1364/OL.44.000139 have been updated.
Single Image Haze Removal using Contextual Regularization

Haze is a condition where our visibility gets affected due to particles, smoke, dust and moisture which are suspended in air. Haze reduces the visibility. A contextual regularization de-hazing algorithm is proposed which uses a single frame image for enhancing the foggy image using multilevel transmission mapping. Quantitative parameters such as MSE and PSNR are considered to assess the superiority of the proposed method. The proposed method is fast and free from noise when compared with other existing methods.
An agricultural data storage mechanism based on HBase

With the development of agricultural space-time localisation, sensor network and cloud computing, the amount of agricultural data is increasing rapidly and the data structure becomes more complicated and changeable. Currently, the widely used agricultural database is the relational database. This database handles a large amount of data with very limited throughput and is not suitable for organisation and management of distributed data. HBase is a non-relational database of distributed file storage built on Hadoop platform. HBase is suitable for unstructured data storage database and it can handle large volume of data with high scalability. To better store agricultural big data in HBase, we propose a special agricultural data buffer structure which stores data based on the data category and a two-level indexing memory organisation strategy on HBase. The method proposed saves more than a quarter of the time compared to traditional buffering methods. Experimental results show the higher efficiency of the agricultural data buffer structure and memory-organisation strategy.
Pointing by gaze, head, and foot in a head-mounted display

This paper presents a Fitts' law experiment and a clinical case study performed with a head-mounted display (HMD). The experiment compared gaze, foot, and head pointing. With the equipment setup we used, gaze was slower than the other pointing methods, especially in the lower visual field. Throughputs for gaze and foot pointing were lower than mouse and head pointing and their effective target widths were also higher. A follow-up case study included seven participants with movement disorders. Only two of the participants were able to calibrate for gaze tracking but all seven could use head pointing, although with throughput less than one-third of the non-clinical participants.