Reviewerly/exHarmony huggingface dataset:
An Empirical Research on Service-Oriented Architecture (SOA) for Data Exchange in BIGDATA Systems

Service-Oriented Architecture is a method for scheming dealing and organizing systems that represent ecofriendly business functionality. The objective of this study is to find out the critical success factors that need to implement SOA in BIG DATA systems. Our study aimed at classifying these erroneous performs in execution of SOA. The acceptance of SOA has interested creators to text its requests and applications. The analysed results would be very useful for researchers who would like to implement SOA with BIG DATA systems. SOA lead numerous advantages such as value-added flexibility and appropriate alignment among processes as well as reduced cost of integration and maintenance. Generally, BIG DATA anxieties large-volume, composite, rising figures groups with numerous, self-directed sources. BIG DATA claims where data gathering has grownup extremely and is elsewhere the aptitude of usually used software utensils to detention, accomplish and development within the rise [1]. The greatest essential task for the BIG DATA applications is to discover the large volumes of data and excerpt valuable material or information for upcoming actions. The main purpose of this study is to identify the important factors that are needed to implement SOA in BIG DATA systems. Zhang and Yang suggests a reengineering approach which will restructure the legacy systems that leads to SOA by considering of an organization. This paper also express various challenges of SOA and identify the problems that improve SOA based services for data exchange in BIG DATA systems.
Data Security of Smart Cities

The smart city is a new concept of urban development. It is about improving the life quality of city dwellers by making the city more adaptive and efficient, using new technologies that rely on an ecosystem of objects and services. The scope covering this new mode of city management includes: public infrastructures (buildings, street furniture, home automation, etc.), networks (water, electricity, gas, telecoms); transport (public transport, roads and smart cars, carpooling, so-called soft mobility—by bike, on foot, etc.); e-services and e-administrations. In recent years the concept of the smart city has become democratized, especially with the creation of several study groups and the establishment of more and more intelligent city in the world (New York, Paris, London…). However, with the emergence of the Internet of Things (IOT) continues to boost the development of smart cities, it also increases the need to address security issues. The purpose of this article is the description of the data exchange flows between each component of the smart city and the users, to identify the types of protocol of these exchanges and the associated IOT applications.
The Effect of Remittances on Economic Growth in Ethiopia: A Time Series Analysis (1980/81-2017/18)

For more than half a century, regardless of its increasing importance, the effect of remittances on economic growth has not adequately studied.In this study the empirical relationship between economic growth and remittances was investigated by using an ARDL bound approach to cointegration in Ethiopia during the period 1980/81-2017/18.According to the findings of this paper the estimated coefficients of the level of remittance inflows were found to influence the economic growth positively and significantly both in the long run and short run.Moreover in order to confirm the relationship and the impact of remittances inflows on economic growth co-integration and causality tests were conducted on the macroeconomic variables data collected.The outcome of co-integration test showed that there is a long-run equilibrium relationship between real GDP, remittance inflows, human capital, labor force, rate of inflation, gross capital formation and national saving.The result of causality test also shows that there is a unidirectional causality running from remittance inflows to GDP.
Accurate Annotation of Gaze Point for Wearable Eye Tracking Devices

As the cost of eye tracking devices decreases, wearable eye tracking devices are becoming more and more popular in head-mounted devices such as smart glasses and augmented reality helmets. Eye tracking enabled devices are believed to facilitate a better understanding of human behaviors and intentions, and will make the interaction between human and computing systems more natural and friendly. A challenging problem for wearable eye tracking devices is the accurate annotation of the gaze point in a real-world scenario, that is, to identity the real object where each gaze point is on and the accurate position of the gaze point relative to this object. We propose a framework for gaze point annotation in real-world scenarios and design a system to implement this framework by establishing an accurate mapping between the gaze point and its coordinates relative to a computer screen. Experimental results show our method is robust in real-world scenarios and can reach an error rate less than 1%, This demonstrates the effectiveness of the proposed framework.
Cognitive Structures

The ultimate goal of research into AI’s cognitive architectures is to model the human mind, eventually enabling to build human-level AI. Some criteria of cognitive architectures include understanding, free will, flexible behavior, real-time operation, rationality, large knowledge base, learning, development, linguistic abilities, self-awareness, and brain realization.
Comprehensive Scrutiny on the Concept of Group Work for English Language Teaching

In this literary review the researchers presented the concept of group work, types of group work, group work activities, forming and organizing groups, advantages and disadvantages of group work, the impact of teachers' and students' attitude towards group work activities, the teachers and students role in group work activity, factors affecting the implementation of group work activities in English language teaching (hereinafter referred as "ELT").And also the concept of speaking, group work activities used to teach speaking and functions of speaking in group work.The reader/learner will be benefitted from the article.
Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions

Mobile learning is viewed by many institutional leaders as the solution for a student cohort that is demanding an increasing flexibility in study options. These students are fitting study around other aspects of their lives including work and caring responsibilities, or they are studying at a geographical location far removed from the university campus. With ubiquitous connectivity available in many parts of the world and with the incremental improvements in design and affordability of mobile devices, many students are using mobile technologies to access course materials and activities. Even so, there are relatively few formal mobile learning initiatives underway and even fewer evaluations of those initiatives. This is significant because without a rigorous evaluation of mobile learning, it is impossible to determine whether it provides a viable and cost-effective way of accessing courses for both the student and the institution. This chapter examines the broad groupings of uses for mobile devices for learning, before considering the evaluation frameworks that are currently in use. The characteristics, affordances, and issues of these frameworks are briefly discussed. A project to develop a Mobile Learning Evaluation Framework is introduced, which will consider evaluation from four aspects: (1) pedagogical learning, (2) pedagogical teaching, (3) technical, and (4) organizational.
Agreement Technologies for Conflict Resolution

Recently, artificial intelligence, has emerged as a new source of scientific works in conflict resolution. The interest in conflict resolution lies in diverse reasons. One of the main reasons is that computational systems have gradually shifted towards a distributed paradigm where heterogeneous entities should include computational conflict resolution mechanisms, such as proposed by agreement technologies. This chapter gives an overview of these technologies, which are needed in order to ensure the accomplishment of the global system goal and to solve conflicts. Among agreement technologies, automated negotiation is proposed as one key mechanism in conflict resolution due to its analogous use in human conflict resolution. Automated negotiation consists of an automated exchange of proposals carried out by software agents on behalf of their users. Another key technology is argumentation, which provides a fruitful means of dealing with conflicts and knowledge inconsistencies. Agents can reach agreements by engaging in argumentation dialogues with their opponents in a discussion.
Conclusion and Future Work

In this book, we present our works on the analysis and recognition of time expressions and named entities. We summarize five intrinsic characteristics about time expressions and three ones about named entities. According to these characteristics, we propose three methods to recognize time expressions and named entities from unstructured text, namely SynTime, TOMN, and UGTO. When analyzing named entities, we find that the joint task of named entity recognition and classification cannot improve the performance of the subtask of named entity recognition.
ASR System for Isolated words using ANN with Back Propagation and Fuzzy based DWT

Speech is the primary means through which human beings interact. Speech has become a way for Man Machine Interaction (MMI). The Speech Recognition (SR) systems have been widely used in smart phones to initiate searches or to type certain text messages, and in control devices to perform switch on or off functions etc. This system comprises three blocks: Pre-processing, Feature Extraction and Classification. The input speech signal is pre-processed to remove the noise and to convert it into a digital form for feature extraction. The feature extraction is a significant process during SR systems design because the features extracted form the basis for accurate recognition of the speech. Only a few features of this signal may be selected for classification purposes. For final recognition of the spoken word or the input signal, various optimization algorithms as classifiers are used. This paper presents an extensive literature review on SR Systems. The authors have attempted to do a brief survey to identify the progress in this field. The survey provides the reader with well-known methods used by previous researchers. It also compares the performance metrics for two ASR techniques developed by the authors. The first technique uses Artificial Neural Network with Back Propagation while the second uses Fuzzy based Discrete Wavelet Transform. It was found that the fuzzy based DWT system provided better results in terms of the performance metrics like accuracy, sensitivity, specificity and word error rate. The paper concludes by providing the reader with a direction of future scope in this research area
Informatization of the Educational Space: Global Trends Overview

The authors of this article seek to answer the following questions: how does the sphere of education develop in the context of global information society and what are the key trends in the process of informatization of the educational space. Information resources and structures have become a tool for achieving a strategic advantage. The authenticity, credibility, as well as an adequate reflection of information realities represent the key challenges for the communication society.
Deep Reinforcement Learning Based Trajectory Planning for Hopping on Low-Gravity Asteroid Surface

In a small-body exploration mission, the rover may deviate from the expected target point due to the dispersion of delivery. This paper proposes a hopping trajectory planning method based on deep reinforcement learning to achieve a precision landing on a low-gravity surface. First, the dynamic model of the hopping rover is established. Then, the hopping scheme is proposed with the attitude angle and angular velocity as control variables. In order to rapidly solve the control variables, the deep reinforcement learning algorithm is utilized for the autonomous hopping trajectory planning. The landing process is divided into an approach and a deceleration stage, and two agents are trained according to the reward functions of the two stages. To achieve the expected attitude angle and angular velocity given by the agents’ outputs, the control torque is solved using sliding mode control method. Finally, the hopping trajectory planning method are verified in a landing mission on low-gravity surface. The results show that the rover can reach and stop at the target by intelligent hopping under various initial conditions.
An Evaluation of Software Development Practices among Small Firms in Developing Countries

For software development firms to be competitive they must assure the quality of the software product. This has led many firms to adopt software process improvement (SPI) programs such as the capability maturity model integration (CMMI). However, for small software firms, especially those in developing countries with limited resources, these programs are often too cumbersome and costly to implement. To address this issue, this paper proposes a simplified SPI model for small firms (SPM-S) comprised of 10 key software development practices; with fewer practices, the proposed model should be more accessible and less costly to implement. Using data collected in four developing countries in the English-speaking Caribbean from 112 developer/user dyads, the model is evaluated with respect to its impact on software quality. The findings show that the software development process coupled with supporting technology (e.g. project management tools) significantly impact software product quality. Implications for software process improvement in small firms and future research are discussed.
Introduction

In today’s world, software is the key element for the functionality of almost all engineered and automated systems. Due to this evolution, reliability and quality of software systems become crucial for the successful functioning of day-to-day operations.
Finding Automated (Bot, Sensor) or Semi-Automated (Cyborg) Social Media Accounts Using Network Analysis and NodeXL Basic

Various research findings suggest that humans often mistake social robot (‘bot) accounts for human in a microblogging context. The core research question here asks whether the use of social network analysis may help identify whether a social media account is fully automated, semi-automated, or fully human (embodied personhood)—in the contexts of Twitter and Wikipedia. Three hypotheses are considered: that automated social media account networks will have less diversity and less heterophily; that automated social media accounts will tend to have a botnet social structure, and that cyborg accounts will have select features of human- and robot- social media accounts. The findings suggest limited ability to differentiate the levels of automation in a social media account based solely on social network analysis alone in the face of a determined and semi-sophisticated adversary given the ease of network account sock-puppetry but does suggest some effective detection approaches in combination with other information streams.
Blockchain Innovation and Information Technology at GCC

Blockchain has become an epidemic and significant decision that organizations may make in the next few years, enabling institutions to integrate business functions, operations, and processes in a decentralized distributed ledger technology. This technology will transform the business world and economy in solving the limitations created by centralization and system inefficiency. Accordingly, with the high demand and complexity of growing economies such as the Gulf Cooperation Council GCC countries, the need for a typical solution technology is a game changer. This will lead GCC to a solid economic base. Blockchain technology can be applicable in many different fields such as Banking, education, Health, finance, government and trade. This article will address the literature review and methodology of Blockchain technology and innovation at the GCC, particularly in Saudi Arabia. Also, more research can be conducted in the future as the system may be integrated in these countries.
Cryptography

As society speeds, and in most cases is literally dragged, into the new information society, the kind of face-to-face and paper-traceable communication that characterized the non-digital communication before the information revolution—the kind of communication that guaranteed personal privacy and security—is increasingly becoming redefined into the new information society where faceless digital communication regimes are guaranteeing neither information and personal security nor personal privacy. Centuries-old and trusted global transactions and commercial systems that guaranteed business exchange and payment systems are being eroded and replaced with difficult to trust and easily counterfeitable electronic systems. The fight for personal privacy has never been any more fierce, and the integrity and confidentiality of data have become more urgent than ever before. The security and trust of digital transaction systems have become of critical importance as more and more organizations and businesses join the e-commerce train. Cryptography is being increasingly used to fight off this massive invasion of individual privacy and security, to guarantee data integrity and confidentiality, and to bring trust in global e-commerce. It guarantees authorization, authentication, integrity, confidentiality, and nonrepudiation in all communications and data exchanges in the new information society. This chapter focuses on this.
iPad and iPod in the Language Classrooms

The chapter examines how the use of emergent mobile technologies such as iPad and iPod in the classroom with young language learners can promote innovative learning environments and authentic oral language learning experiences. The chapter is based on a collaborative action research (CAR) project involving young French language learners in primary schools in a western province of Canada. Findings show that the affordances of mobile technologies support the creation of innovative learning environments and authentic oral language learning experiences through collaborative dialogue and peer-peer scaffolding among young language learners. The outcomes of the inquiry also demonstrate that the use of mobile devices such as iPad and iPod promotes the emergence of metacognitive reflection among learners, as well as a greater sense of agency and autonomy.
Social Media Fake Account Detection for Afan Oromo Language using Machine Learning

A social networking service serves as a platform to build social networks or social relations among people who, share interests, activities, backgrounds, or real life connections.A social network service is generally offered to participants who registers to this site with their unique representation (often a profile) and one's social links.Most social network services are web-based and provide means for users to interact over the Internet.(M.Smruthi, , February 2019).Online social networking sites became an important means in our daily life.Millions of users register and share personal information with others.Because of the fast expansion of social networks, public may exploit them for unprincipled and illegitimate activities.As a result of this, privacy threats and disclosing personal information have become the most important issues to the users of social networking sites.The intent of creating fake profiles have become an adversary effect and difficult to detect such identities/malicious content without appropriate research.The current research that have been developed for detecting malicious content, primarily considered the characteristics of user profile.Most of the existing techniques lack comprehensive evaluation.In this work we propose new model using machine learning and NLP (Natural Language Processing) techniques to enhance the accuracy rate in detecting the fake identities in online social networks.We would like to apply this approach to Facebook by extracting the features like Time, date of publication, language, and geo position.
A Deterministic Seeding Approach for k-means Clustering

In this work, a simple and efficient approach is proposed to initialize the k-means clustering algorithm. The complexity of this method is O(nk), where n is the number of data and k the number of clusters. Performance evaluation was done by applying this approach on various benchmark datasets and comparing with the related deterministic KKZ seed algorithm. Experimental results have demonstrated that this approach produces more consistent clustering results in term of average silhouette index.
GEA-net: Global embedded attention neural network for image classification

Recently, it is generally acknowledged that the receptive field size of visual cortical neurons are regulated by the stimulus in the neuroscience community. Thus, once the global receptive field is obtained, the network performance can be greatly improved. Unfortunately, the larger receptive field method has been rarely considered in constructing CNNs. Recent studies on network design have demonstrated that the key to improving model performance is channel attention. However, they usually neglect the location information. Hence, it is difficult to capture the long-term dependency of location information. In particular, the location information is important for generating spatially selective attention blocks. Therefore, in this paper, we propose a novel attention neural network termed “GEA” by embedding global context information into channel attention. Firstly, instead of channel attention, which is transformed from feature tensor to single feature vector via 2D pooling, our method decomposes the channel attention into two 1D feature encoding processes that aggregate features along two spatial directions. In particular, the long-term dependency can be captured by using one spatial direction as well as preserving accurate location information in the opposite direction. Then, we concatenate the results of the two directions, while carry out batch normalization and use relu activation function. In addition, the cross channel soft attention is used to adaptively select different spatial scales of the information. Finally, our method is simple and can be flexibly inserted into classic networks, such as ResNet and EfficientNet, with limited computational overhead. A large number of experiments show that our method is not only conducive to the classification of COCO and ImageNet, but also demonstrates promising performance for 3D features, such as Magnetic Resonance Imaging(MRI).
The Role of Affective Computing for Improving Situation Awareness in Unmanned Aerial Vehicle Operations

Unmanned aerial vehicles (UAVs), commonly known as drones, are a robotic form of military aircraft that are remotely operated by humans. Due to lack of situation awareness, such technology has led to the deaths of civilians through the inaccurate targeting of missile or gun attacks. This chapter presents the case for how a patented invention can be used to reduce civilian casualties through attaching an affect recognition sensor to a UAV that uses a database of strategies, tactics and commands to better instruct fighter pilots on how to respond while in combat so as to avoid misinterpreting civilians as combatants. The chapter discusses how this system, called VoisJet, can reduce many of the difficulties that come about for UAV pilots, including reducing cognitive load and opportunity for missing data. The chapter concludes that using UAVs fitted with VoisJet could allow for the reduction of the size of standing armies so that defence budgets are not overstretched outside of peacetime.