Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchronization in Wireless Sensor Networks: Parameter Estimation, Performance Benchmarks, and Protocols

Wireless sensor networks are set to play a key role in a wide range of civilian and military applications, with tiny sensors connected through wireless links performing various sensing, computing, communication, and control tasks in highly distributed systems. This book presents a critical element in the deployment of wireless sensor networks: the process of synchronization. It summarizes the most important clock synchronization protocols proposed for wireless sensor networks with special emphasis placed on deriving efficient clock offset estimation schemes and performance benchmarks. Graduate students of electrical and computer engineering and computer science will find this a valuable resource, as will engineers who are interested in designing efficient clock synchronization algorithms and improving the performance of existing synchronization protocols.
Specific antecedents of employees’ knowledge sharing behavior

The purpose of this study is to examine the antecedents of specific human resource management (HRM) practices and trust on knowledge sharing (KS) behavior of employees. ,In the first phase, a questionnaire survey was used to collect the data from 350 randomly selected individuals working in banks. In the second phase, ten managerial-level employees were interviewed to triangulate the findings of the survey. ,The results revealed that employees viewed trust, recruitment and selection and performance appraisals have a positive relationship with KS behavior. However, training and development and incentives have no impact on KS. ,The value of this paper lies in the understanding gained about the interactive effects of KS and HR practices using the structural equation modeling technique. This paper will help in understanding the factors that can promote KS. This study will be helpful for employees, managers and policymakers. This study may help in highlighting the significant role of HR practices.
Stronger consistency and semantics for low-latency geo-replicated storage

Geo-replicated, distributed data stores that support complex online applications, such as social networks, strive to provide an always-on experience where operations always successfully complete with low latency. Today's systems sacrifice strong consistency and expressive semantics to achieve these goals, exposing inconsistencies to their clients and necessitating complex application logic. In this work, we identify and define a consistency model—causal consistency with convergent conflict handling, or causal+—that is the strongest achieved under these constraints. We explore the ramifications of and implementation techniques for causal+ consistency through the design and implementation of two storage systems, COPS and Eiger. COPS is a key-value store that provides causal+ consistency. A key contribution of COPS is its scalability, which can enforce causal dependencies between keys stored across an entire cluster, rather than a single server like previous systems. Eiger is a system that provides causal+ consistency for the rich column-family data model. The central approach in COPS and Eiger is tracking and explicitly checking that causal dependencies between keys are satisfied in the local cluster before exposing writes. Our work also provides stronger semantics, in the form of read- and write-only transactions, that allow programmers to consistently interact with data spread across many servers. COPS includes the first scalable read-only transactions that can optimistically complete in one round of local reads and take at most two non-blocking rounds of local reads. Eiger includes read-only transactions with the same properties that are more general—they are applicable to non-causal systems—and more fault-tolerant. Eiger also includes scalable write-only transactions that take three rounds of local non-blocking communication and do not block concurrent read-only transactions. We implemented COPS and Eiger and demonstrate their performance experimentally. The later of these systems, Eiger, achieves low latency, has throughput competitive with an eventually-consistent and non-transactional production system, and scales to large clusters almost linearly.
Analysis of Timeline Posts to a Language Teacher Organization Public Facebook Group.

Affordances of Facebook for enhancing communities of practice are often overlooked in studies highlighting the role of social networking in the English as a foreign language context of Korea. Taking this into account, the purpose behind this study is to determine the function a Korea-based language teacher organization Facebook group in terms of how the 3,197 members use the service as a personal learning environment for professional development, while also seeking to determine how the group supports the endeavors of those actively engaging with it. Data harvesting was undertaken using NodeXL Pro, and confined to a one-year period, with thematic content analysis then employed to group the 278 captured timeline posts into themes for analysis. Although most posts were disproportionately organizational, it is clear that professional development emerges amongst members as the largest concern. Further analysis came to illustrate the role of the group in the professional lives of members, seeing it arise as an affinity space, presenting access to professional development opportunities, content, and contacts, and providing a means for members to validate teaching material, showcase success, and access just-in-time support. Ultimately though, before becoming integral to any educator’s personal learning environment, the group could perform much better, and several means to this end are exposed.
Where to Spend our E-Journal Money? Defining a University Library's Core Collection Through Citation Analysis

This paper identifies core journals in the life sciences for Cornell University researchers by analyzing the frequency of Cornell-authored citations in Biosis Previews between 1996 and 2001. The distribution frequency of journals confirms Bradford's Law of Scatter or the 80/20 Rule. The top 240 journals, providing 80 percent of the citations, were analyzed by publisher type and institutional subscription price. In general, journals from society and associations received the highest number of citations and were priced considerably lower than commercial journals. The methodology described is a fast, low-cost, and scalable procedure that can be adapted to various subject databases, and may be used to provide guidance on which titles to purchase for electronic access.
Generalised associated discrete circuit model for switching devices

The paper describes a new switch model based on the associated discrete circuit (ADC) models. The switch model enables a switching circuit to be modelled by a constant admittance matrix, irrespective of its switching state. This feature allows a system with changing topology to be modelled efficiently and elegantly by one set of model equations, and a reduction of circuit formulation and computing time. The switch model is applied to the simulation of a half-bridge switched-mode circuit. Experimental results confirm the validity of the new switch model.
Reliability assessment of distribution networks incorporating regulator requirements, generic network equivalents and smart grid functionalities

This paper is part one of a two-part series discus sing how Regulator requirements for continuity of supply could be incorporated in the reliability analysis of existing electricity networks and future “smart grids”. The paper uses examples of overall and guaranteed standards of performance fro m the UK and Italy, specifying requirements that network operators should satisfy with respect to excessively long and /or too frequent supply interruptions. Besides the relevant Re gulator requirements, this paper presents input data, parametrs and models required for comprehensive reliability asses sment, while Part 2 paper presents scenarios and results for tes t network based on both analytical and probabilistic reliabil ity procedures.
HYBRID OF PARTICLE SWARM OPTIMIZATION WITH EVOLUTIONARY OPERATORS TO FRAGILE IMAGE WATERMARKING BASED DCT

Particle swarm optimization (PSO) is a new promising evolutionary algorithm for the optimization and search problem. One problem of PSO is its tendency to trap into local optima due to its mechanism in information sharing. This paper proposes a novel hybrid PSO, namely (HPSO) technique by merging both a mutation operator and natural selection to solve the problem of premature convergence. By introducing Cauchy mutation and evolutionary selection strategy based on roulette wheel selection, HPSO could greatly reduce the probability of trapping into local optimum. HPSO is proposed to improve the performance of fragile watermarking based DCT which results in enhancing both the quality of the watermarked image and the extracted watermark. After embedding watermark to the original image in the frequency domain, the conversion of real numbers of the modified coefficients in frequency domain to integer numbers in spatial domain produces some rounding errors problem. This problem results in completely different of the extracted watermark from the embedded watermark. The new developed PSO with evolutionary operators is carried out for correcting the rounding errors by training a translation map used to modify the inverse DCT (IDCT) coefficients from real to integer numbers. The experimental results show the superiority of the proposed algorithm comparing with the standard PSO for improving the performance of DCT fragile watermarking. Besides, it has been shown that the developed PSO is faster in convergence and the obtained results proved to have higher fitness than the other algorithm.
Understanding Mobile Human-Computer Interaction (Information Systems Series (ISS))

Taking a psychological perspective, this book examines the role of Human-Computer Interaction in the field of Information Systems research. The introductory section of the book covers the basic tenets of the HCI discipline, including how it developed and an overview of the various academic disciplines that contribute to HCI research. The second part of the book focuses on the application of HCI to Information Systems research, and reviews ways in which HCI techniques, methodologies and other research components have been used to date in the IS field. The third section of the book looks at the research areas where HCI has not yet been fully exploited in relation to IS, such as broadening user groups and user acceptance of technology. The final section of the book comprises of a set of guidelines for students to follow when undertaking an HCI based research project. * Offers a comprehensive insight into the social shaping of technology * Includes in depth analysis of HCI issues relating to mobile devices * Provides guidelines, technical tips and an overview of relevant data analysis techniques to help students develop their own research projects Table of Contents Contents Preface Part 1 What is HCI? Chapter 1 - Introduction to HCI Chapter 2 - Designing mobile systems for people Chapter 3 - Evaluation Chapter 4 - Principles of interface design Part 2 Application of HCI to mobile information systems research Chapter 5 - Gender differences and technology Chapter 6 - Age differences and technology Chapter 7 - Special needs and technology Chapter 8 - Social impact of mobile technology Part 3 Guidelines for designing mobile HCI-based information systems projects Chapter 9 - Guidelines Part 4 Future directions Chapter 10 - Different user groups Chapter 11 - Measurement techniques Chapter 12 - User acceptance of technology Index
Investigating the Intelligent Methods of Loss Minimization in Induction Motors

Induction motors are widely used in industry. Given the increasing demand for electric machines in different industries, optimization of these machines to achieve a high efficiency with low cost is of utmost importance. Loss-minimization in motor is done in three ways: 1) optimizing motor selection and design; 2) improving motor power supply waveforms; and 3) using appropriate controlling methods in drives. Often, inductive motors provide the maximum efficiency in their nominal load. In most applications it is necessary for a motor to work in light loads for a long time, e.g. in conveyors, elevators, etc. In these conditions, the machine load is not the nominal load, and a higher percentage of the input power is lost. So, in the case of variable load, the first and second methods cannot increase the efficiency; but the third method provides a large flexibility in decreasing motor losses. In this paper, the application of the third method in loss-minimization is reviewed. These motor losses are mostly related to the controlling strategy and basically occur in light-load conditions. There are various strategies to decrease this kind of losses, which are generally divided into two categories: classic methods and intelligent methods. In this paper, first the classic methods, including losses model control (LMC), flux control as a function of torque and search control (SC), are discussed. Then the intelligent methods, such as genetic algorithm, PSO, fuzzy logic and artificial neural network are investigated. This paper is presented while the last methods of efficiency improvement are being investigated and each method is described briefly.
An analog VLSI implementation of a feature extractor for real time optical character recognition

The architecture, the design, and the analog very large scale integration (VLSI) implementation of a feature extractor chip for optical character recognition (OCR) systems are described. The chip extracts a set of 112 feature values coded by current signals from a 32/spl times/24 digital pixel matrix, representing the input character. Such features are applied to a classifier (for example, a neural classifier) performing the recognition task. The measurements performed on that chip confirm its functionality. The chip can be used with a segmented and nonsegmented string of characters. A throughput of about 140 kChar/s is achieved for the segmented case, while a throughput of about 450 kChar/s is achieved for the nonsegmented case. The OCR architecture has been functionally validated. A set of numerical handwritten characters has been processed by the chip and the measured output features (after a normalization operation) have been used as input for neural network classifier; implemented by a software simulator which performs the recognition task. The resulting classification error rate (4.3%) has been successfully compared with those obtained by a high level model of this chip, and the results validate the entire architecture.
Pushing the envelope of sentiment analysis beyond words and polarities

Idioms are multi-word expressions which hold a literal and figurative meaning which is conventionally understood by native speakers. Their overall meaning, often, cannot be deduced from the literal meaning of their constituent words. Sentiment analysis, also referred to as opinion mining, aims to automatically extract and classify sentiments, opinions, and emotions expressed in text. The research in this thesis is motivated by the fact that idioms, which often express an affective stance towards an entity or an event, are not featured systematically in sentiment analysis. To estimate the degree to which the inclusion of idioms as features may improve the results of traditional sentiment analysis, we compared our results to two state-of-the-art sentiment analysis approaches. Firstly, we collected a set of idioms that are relevant to sentiment analysis, i.e. those that can be mapped to an emotion. These mappings were obtained using a crowdsourcing approach. Secondly, to evaluate the results of sentiment analysis, we assembled a corpus of sentences in which idioms are used in context. Each sentence was annotated with an emotion, which formed the basis for the gold standard used for the comparison against the baseline methods. The classification performance was improved by almost 20 percentage points. Given the positive findings from our initial experiments, the main limitation was the significant knowledge-engineering overhead involved in hand-crafting lexico-semantic resources used to support idiom-based features. To minimise the bottleneck associated with the acquisition of such resources, we scaled up our original approach by automating their engineering. Subsequently, these resources were used to replace the manually engineered counterparts of such features in the originally proposed method. The fully automated approach outperformed the two baseline methods by 7 and 9 percentage points. These improvements, however, were poorer in comparison to those achieved in the initial study. Nevertheless, we have demonstrated, not only can idiom-based features be automatically engineered, but they too, improve sentiment classification results, when such features are present. Taking a long-term view of the research in this thesis, we want to address the limitations of state-of-the-art sentiment analysis approaches by focusing on a full range of emotions, rather than sentiment polarity. However, there is no consensus among researchers on a standardised framework for classifying emotions. Proposing such a framework would be a major contribution to the field of sentiment analysis, as it would stimulate its evolution into fully-fledged emotion classification and allow for systematic comparison of independent studies. With this goal in mind, we investigated the utility of different classification frameworks for sentiment analysis. A comprehensive statistical analysis of our experimental results provided explicit evidence that, in relative terms, six basic emotions are best suited for sentiment analysis. However, we identified the major shortcoming of oversimplifying positive emotions.
Secure Encryption Via Deterministic Chaos

The evolutionary algorithms are applied to enhance the quality of recovered signal in chaotic secure communication system that is the core objective of this dissertation. The synchronization error between the transmitter and the receiver in communication systems is used to design the cost function. The parameters of chaotic dynamic model are estimated by evolutionary algorithms via minimizing the synchronization errors. By this way, the quality of recovered signal is increased when the synchronization error approaches to minimum value. The Pecora and Carroll method (PC method), Active-Passive Decomposition method (APD method) and Feedback method-three synchronization methods are used to achieve the synchronization of chaos communication. Differential evolution algorithm (DE) and Self-Organising Migrating Algorithm (SOMA) are used as the evolutionary algorithms to find the unknown parameters of receiver chaotic systems. The synchronizations of identical chaos are executed: Synchronization of three dimensional Lotka-Volterra systems via PC method, synchronization of four dimensional Qi systems via APD method, synchronization of four dimensional Liu systems via Feedback method. The powerful of EA on this problem are also proven via the synchronization of 5 and 6 dimensional chaotic systems. The application of EA is used for designing the control function in the synchronization between two difference chaotic systems. Based on the optimum results from evolutionary algorithms, the estimated values are used to reconstruct the receiver chaotic systems. The optimal quality of synchronization is achieved by using the estimated parameters. The synchronization between the transmitter and the receiver chaotic system is used to retrieve the transmitted information in Chaotic Masking Scheme (CMS). The quality of chaotic secure communication is enhanced with estimated parameters. It is possible to state that all simulations gave satisfactory results and thus evolutionary algorithms are successful in solving this difficult problem.
Automated essay evaluation and the computational paradigm: Machine scoring enters the classroom

Grading papers is a “tedious, repetitive, and time-consuming” undertaking, one that invites the sort of sympathies one might receive upon the “death of a pet” (Baker, 2014, p. 36). Perhaps, though, the only thing more distasteful for an English professor than having to grade hundreds of essays each semester is having to hand the job over to the likes of a mindless software program. Automated Essay Evaluation (AEE), the process of scoring essays by computer, was developed in the 1960s but has mostly aroused suspicion and derogation from the composition community. The parable of the blindfolded villagers describing the same elephant from different parts of its body serves as an apt metaphor for how rhetorical choices screen in or screen out different facts about AEE. Each research camp reports on a different facet of AEE, but it is possible for these multiple realities to describe the same beast. This dissertation seeks to: (1) describe the rhetorical contours of arguments for and against AEE, both currently and historically, exposing their limitations and motivations; (2) explore through a small study how differential frames of data analysis affect interpretations of AEE’s utility, namely how error analysis adds an emphasis on individual students rather than student-aggregates; and (3) sketch ways that attention to errors is instructive in understanding the pitfalls of both human and machine scoring of essays. Because human scoring—despite its drawbacks—is still the superior method, I end by suggesting that AEE would be best used when the economic choice is between machine scoring and feedback, or no scoring and feedback at all. The context of online learning in globally disadvantaged populations is one such example.
Force on current coils moving over a conducting sheet with application to magnetic levitation

The use of Fourier-transform techniques provides exact integral expressions for the forces on polygonal dc current coils moving over a conducting sheet. These expressions are applied to investigate magnetic levitation of proposed high-speed transportation. Extensive numerical data have been analyzed to determine the performance dependence of the system parameters such as velocity, coil shape, array configuration, clearance, and track thickness, conductivity and permeability. In terms of potential applications, a comparison between the superconducting repulsive and ferromagnetic attractive systems is given.
Nacre**Nacre, or mother-of-pearl, is one of nature's remarkable examples of a durable and break-resistant structure.: Durable, Secure and Energy-Efficient Non-Volatile Memory Utilizing Data Versioning

As we begin to utilize non-volatile memory (NVM) technologies as main memory elements, new challenges will emerge. While non-volatility is a desirable feature to save energy, it creates security vulnerabilities since data will persistent after system power-off. Data stored in NVMs can be secured using data encryption. However, side effects imposed by memory encryption result in excessive bit writes, which will drastically reduce NVM lifetimes and increase energy consumption. In this paper, we propose Nacre to bridge the gap between fully encrypted and unencrypted NVMs. Nacre exploits standard counter-mode encryption to maintain security. By tracking the different versions of the modified data in each memory writeback, Nacre attempts to limit the number of bit writes. Selective re-encryption is performed based on the history of the modified data in cache lines. We show that on average, Nacre improves memory lifetime by 53 percent (2.87x) as compared to state-of-the-art (full encryption) schemes. In addition, Nacre only increases energy consumption by 6 percent versus an unencrypted memory system.