Miracle-dz/UniFAR-FTUs huggingface dataset:
Use-centred design of medical and healthcare technology : A pilot study of field tests as a development tool

The purpose of the project has been to develop a process through which users, staff as well as patients, can be involved in field evaluations of medical and healthcare technology. Interviews with different stakeholders and the experiences from four case studies have led to the following conclusions. Users have the potential to act as active evaluators rather than passive subjects or participants only. However, user involvement in field evaluations must be supported by a formation of facilitators or 'door openers' to the healthcare organisation, moderators enhancing the dialogue between developers and users, and mentors for the users acting as evaluators.
Fuzzy-Q learning for autonomous robot systems

It is desirable for autonomous robot systems to posses the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Since Q-learning is normally used for optimizing a series of discrete actions, it may be undesirable when applied to a real environment which involves continuous states and actions. In this paper, we propose a new method of Q-learning that incorporates a fuzzy interpolation technique which is used to approximate a continuous state. Our learning method can estimate current state by its neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to react smoothly in a real environment. Simulation results involving an autonomous robot are given to show the validity of our method.
A case study of a multiobjective recombinative genetic algorithm with coevolutionary sharing

We present a multiobjective genetic algorithm that incorporates various genetic algorithm techniques that have been proven to be efficient and robust in their problem domain. More specifically, we integrate rank based selection, adaptive niching through coevolutionary sharing, elitist recombination, and non-dominated sorting into a multiobjective genetic algorithm called ERMOCS. As a proof of concept we test the algorithm on a softkill-scheduling problem.
THE CHALLENGES OF COLLABORATIVE LEARNING IN CLOUD AND A THREE LAYERED ARCHITECTURE TOWARDS THE SOLUTION

Cloud computing is the emerging technology providing IT as a utility through internet. The benefits of cloud computing are but not limited to service based, scalable, elastic, shared pool of resources, metered by use. Due to mentioned benefits the concept of cloud computing fits very well with the concept of m-learning which differs from other forms of e-learning, covers a wide range of possibilities opened up by the convergence of new mobile technologies, wireless communication structure and distance learning development. The concept of cloud computing like any other concept has not only benefits but also introduces myriad of security issues, such as transparency between cloud user and provider, lack of standards, security concerns related to identity, Service Level Agreements (SLA) inadequacy etc. Security concerns raised in cloud computing because of breaking the boundaries i.e. moving IT
Relativisation and Accessibility: A Corpus Analysis of Relative Clauses in Arabic Written Texts

ii Acknowledgement iv List of Tables x List of Figures xi List of Abbreviations xiii Description of Arabic Sounds xiv List of Texts Used xvi Chapter One: Introduction 1 1.1 Background to the Present Study 1 1.1.1 Related Studies 4 1.1.2 The Relativisation Strategies 8 1.2 This Study 10 1.2. 1 The Focus of this Study 10 1.2. 2 The Significance of the Study 12 1.2. 3 Organisation of the Thesis 13 Chapter Two: Relativisation and Accessibility 16 2.
Resource aware programming in sensor networks

This dissertation presents a platform for designing wireless sensor network applications that are data-intensive and must cope with variations in load and resource availability. Our thesis is that existing programming models and operating systems do not provide the right level of abstraction and primitives for resource management. Sensor network operating systems tend to expose a wide range of low-level primitives for resource management with little guidance in how to use them. To address these challenges, we explore resource awareness at two levels: at the node-level through a new OS called Pixie and at the network-level through a Body Sensor Network platform called Mercury. The first component of our solution, Pixie, is a new operating system for sensor networks that enables resource-aware programming, a model in which applications receive feedback on and have explicit control over resources. Pixie uses a dataflow programming model and is based on resource tickets, a core abstraction for representing resource availability and reservations. By giving the system visibility and fine-grained control over resource management, a broad range of policies can be implemented. To shield application programmers from the burden of managing these details, Pixie provides resource brokers, which mediate between low-level physical resources and higher-level application demands. The second component of our solution, Mercury, is a wearable sensor network platform for high-fidelity motion analysis studies. Mercury strives to manage resources across the network; it does so by receiving periodic resource availability messages from individual nodes running Pixie and then makes network-wide decisions regarding resource usage. Mercury is designed to overcome the core challenges of long battery lifetime and high data fidelity for long-term studies. This requires tuning sensor operation and data transfers based on energy consumption of each node and processing data under severe computational constraints. In addition, Mercury provides a high-level API allowing a range of policies to be implemented on top of the core functionality. This dissertation presents the architecture, implementation, and evaluation of Pixie and Mercury, and demonstrates that the node-level view through the Pixie OS and network-wide management through the Mercury platform is an effective way to build resource aware applications.
Feasibility of video codec algorithms for software-only playback

Software-only video codecs can provide good playback performance in desktop computers with a 486 or 68040 CPU running at 33 MHz without special hardware assistance. Typically, playback of compressed video can be categorized into three tasks: the actual decoding of the video stream, color conversion, and the transfer of decoded video data from system RAM to video RAM. By current standards, good playback performance is the decoding and display of video streams of 320 by 240 (or larger) compressed frames at 15 (or greater) frames-per- second. Software-only video codecs have evolved by modifying and tailoring existing compression methodologies to suit video playback in desktop computers. In this paper we examine the characteristics used to evaluate software-only video codec algorithms, namely: image fidelity (i.e., image quality), bandwidth (i.e., compression) ease-of-decoding (i.e., playback performance), memory consumption, compression to decompression asymmetry, scalability, and delay. We discuss the tradeoffs among these variables and the compromises that can be made to achieve low numerical complexity for software-only playback. Frame- differencing approaches are described since software-only video codecs typically employ them to enhance playback performance. To complement other papers that appear in this session of the Proceedings, we review methods derived from binary pattern image coding since these methods are amenable for software-only playback. In particular, we introduce a novel approach called pixel distribution image coding.
Life as it could be: Alife attempts to simulate evolution

Artificial life (Alife) explores natural life by attempting to create biological phenomena in computers and other nonliving media. Alife also strives to introduce a broader, more universal understanding of life (accessible to new kinds of manipulation and testing), than that defined by traditional biology. Looked at in this way, Alife represents the flip side of the empirical-analytic approach of most laboratory biologists, who start with a whole organism, deconstruct it into its component parts (for example organs, tissues, cells, genes, molecules, and so on), and then try to derive its fundamental principles. Most biologists would prefer to be able to simply reverse engineer life and synthesize real organisms, cookbook style, from their basic ingredients, but so far, this feat has eluded them. It is concluded that however it is viewed, Alife has not only spawned some fascinating varieties of digital life, but also an exciting new field of research. Moreover, Alife has engendered a rich and provocative body of thought, whether you're for or against it, with the potential for generating an endless number of new ideas.
Uncertainty models in information and database systems

Information systems have evolved to the point where it is desirable to capture the vagueness and uncertainty of data that occurs in actuality. Approaches have been taken using various fuzzy set concepts such as degree of membership, similarity relations and possibility distributions. This leads to the concept of generalized information systems which are typically char acterized by heterogeneous data representations, weakly typed data domains and the requirement for semantic knowledge during query interpretation. A generalized information system is more likely to have a direct representation for larger classes of information at the cost of more complex data management and query processing. In general the various fuzzy database approaches that have been developed are overviewed in the paper and characterized with respect to the concept of a generalized information system.
A Modified Monte-Carlo Simulation Technique for the Evaluation of Error Rate in Digital Communication Systems

Digital communication systems are frequently operated over nonlinear channels with memory. The analysis of the performance of these systems is difficult and no complete analytical treatment of the problem has been obtained before. Several recent efforts have been directed toward the computation of error probabilities via Monte-Carlo simulation using a complete system model. These simulations require excessively large sample sizes and are not practical for estimating very low values of error probabilities. This paper presents a modified Monte-Carlo simulation technique for estimating error probabilities in digital communication systems operating over nonlinear channels. An importance-sampling technique is used to modify the probability density function of the noise process in a way to make simulation possible. Theoretical results as well as realistic examples are presented, showing that the number of samples needed for simulation is reduced considerably.
Can I Have Your Attention? Implications of the Research on Distractions and Multitasking for Reference Librarians

The media have identified the past decade as “the age of distraction. ” People today find it harder to work on long, sustained tasks because distractions are eroding their attention spans, fostering a culture of discontinuity. Fields as diverse as psychology, business, education, human-computer interaction, and communication studies have produced a wealth of studies on interruptions, distractions, and multitasking—research that has important implications for reference librarians. The nature of our jobs invites interruptions by the public, requires familiarity with the latest technology, stimulates curiosity about a broad range of subjects, and demands adeptness at multitasking—all factors that can atomize attention.
An Adaptation of the FRBR Model to Legal Norms

FRBR (Functional Requirements for Bibliographic Records) is an entity- relationship model developed in 1998 by IFLA (International Federation of Library Associations and Institutions) as a new way to model bibliographic records. Its main feature is the recognition of four entities (Work, Expression, Manifestation, and Item) representing dierent levels of abstraction of a certain work. This paper proposes an adaptation of the FRBR model to the modelling of the several levels of abstraction of a legal norm.
PDroid: Detecting Privacy Leakage on Android

The prevalence of Android makes it face the severe security threats from malicious apps. Many Android malware can steal users’ sensitive data and leak them out. The data flow analysis is a popular technique used to detect privacy leakages by tracking the sensitive information flow statically. In practice, an effective data flow analysis should employ inter-procedure information tracking. However, the Android event-driven programming model brings a challenge to construct the call graph (CG) for a target app. This paper presents a method which employs the inter-procedural and context-sensitive data flow analysis to detect privacy leakage in Android apps. To make the analysis accurate, a flow-sensitive and points-to call target analysis is employed to construct and improve the call graph. A prototype system, called PDroid, has been implemented and applied to some real malware. The experiment shows that our method can effective detect the privacy leakages cross multiple method call instances.
Cutaneous whole nerve recordings used for correction of footdrop in hemiplegic man

One hemiplegic patient with a dropfoot was chronically implanted with a cuff on the sural nerve, and recordings were made regularly during a period of two years. The results showed that the human sural nerve responded in a similar way to mechanical inputs applied on the skin, as the tibial nerve did in cats (M.K. Haugland, et al., ibid., vol. 2, p. 18-28, 1994), indicating that previous experimental systems using natural sensory feedback for closed-loop FNS are possible to adapt to humans. During walking, the recorded nerve signal modulated strongly and gave a clearly detectable response at foot contact and a silent period when the foot was in the air through the swing phase of the walking cycle. A portable system was built that used the recorded signal to control a peroneal stimulator to correct for footdrop. There were two reasons for this: first, to show in a relatively simple system the possibility of solving the practical problems involved in recording nerve activity during stimulation and second, to remove the external heel switch used in existing systems for footdrop correction, thereby making it possible to use such systems without footwear and preparing it to be a totally implantable system. The method for removing artifacts, as developed in animal experiments, was adapted to provide usable nerve signals while stimulating the ankle dorsiflexor muscles.
An adaptive localization method for real-time security analysis

A new adaptive localization method for fast real-time AC security analysis using a modification of the fast decoupled power flow algorithm is presented. The method exploits the property that the impact of most contingencies encountered in security analysis is limited to localized regions of the network. Although it is intended mainly for contingency evaluation, the method is also suitable for contingency screening. On each iteration, a localized region is adaptively identified as the set of buses whose mismatches exceed specified tolerances. The sparse mismatch vectors for these buses are then efficiently processed by sparse vector methods to solve for the significant bus voltage magnitude and angle corrections required for security analysis. Reactive power limits on generators are enforced and all other appropriate automatic control adjustments are performed for the localized solutions. Test results on two practical systems show CPU time improvements over full AC solutions ranging from 3:1 to 5:1. <<ETX>>
An effective method for combining multiple features of image retrieval

We propose an image retrieval system using the Borda count method in combining multiple experts (CME). It combines color-, shape- and texture-based retrieval systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.
Methodology for computational fluid dynamics code verification/validation

The issues of verification, calibration, and validation of computational fluid dynamics (CFD) codes has been receiving increasing levels of attention in the research literature and in engineering technology. Both CFD researchers and users of CFD codes are asking more critical and detailed questions concerning the accuracy, range of applicability, reliability and robustness of CFD codes and their predictions. This is a welcomed trend because it demonstrates that CFD is maturing from a research tool to the world of impacting engineering hardware and system design. In this environment, the broad issue of code quality assurance becomes paramount. However, the philosophy and methodology of building confidence in CFD code predictions has proven to be more difficult than many expected. A wide variety of physical modeling errors and discretization errors are discussed. Here, discretization errors refer to all errors caused by conversion of the original partial differential equations to algebraic equations, and their solution. Boundary conditions for both the partial differential equations and the discretized equations will be discussed. Contrasts are drawn between the assumptions and actual use of numerical method consistency and stability. Comments are also made concerning the existence and uniqueness of solutions for both the partial differential equations and themore » discrete equations. Various techniques are suggested for the detection and estimation of errors caused by physical modeling and discretization of the partial differential equations. « less
A SELF-ADAPTIVE FRAMEWORK FOR FAILURE AVOIDANCE IN CONFIGURABLE SOFTWARE

Many software systems today are highly-configurable, meaning the user can customize their instance of the application, adding and removing features as needed. However, this configurability makes it harder to ensure that faults will not escape testing and manifest as failures in the field. This is because many failures are configuration-dependent; they will appear under certain combinations of features configurations, but not others. Once faults are found and reported in the field, there can be a long lag time (days, weeks or even months) until patches are created and released to fix them. In the meantime, users will continue to use these software systems and need to be able to workaround potential failures. This thesis presents a self-adaptive framework for avoiding configuration-dependent failures at runtime. The framework is built on top of an existing self-adaptive system, Rainbow, and is implemented as a distributed client-base, with a central controller for applying the failure avoidance reconfigurations to clients as needed. Over time as the system gains global information of failures that have occurred, it will not only adapt to new configurations, but it guards other clients from these potentially bad configurations as well. We have performed two evaluations to determine the feasibility of this framework in practice. We first evaluate a set of heuristic failure avoidance algorithms which forms the core of our adaptation, and compare these against an existing bounded brute force algorithm. We find that our heuristic algorithms are effective in avoiding most failures, but for a lower computational cost. Although we miss some workarounds found by the brute force algorithm, we also find new workarounds that are outside of the bounded search space suggesting that a heuristic approach may be better. We then implemented our framework on top of Rainbow and evaluate this on the Firefox web browser. In a study using four distributed instances of Firefox and a set of seeded faults based on real Firefox configuration bugs, we determine that we can workaround them all, and that once observed, we will no longer see the same failure again. We also see new native failures that we did not seed, and find workarounds for these as well. We conclude that our self-adaptive framework is feasible approach for avoiding configuration dependent failures at runtime. iv ACKNOWLEDGMENTS First off I want to thank my advisor, Professor Myra Cohen for her support and dedication during my research. Without her help my work …
The design of an instrumented surgical tool for the intestinal inspection

In the last few years, we have observed a fast development of modern science and technology. In the field of medical engineering, the same evolution is observed, and the Minimally Invasive Surgery (MIS) has became one of the most important research area. Medical endoscope is one typical medical instrument that complies with the requirement of MIS. This paper deals with the design of a new type of micro-robot for intestinal inspection. Because of the injuries caused by the colonoscope during the operation, and the long time spent at the hospital by the patient, we focus on a new type of intelligent colonoscope. The main purpose of this medical tool is to be in accordance with MS by minimizing the contact between the colonoscope and the interior boundary of the colon, and to make the progression of the colonoscope easier for the surgeon. Our current prototype, which is twice the size of the final tool, is electro-pneumatically driven. It is constituted by three metal bellows disposed 120 apart, and its position in the intestine is driven by three sensors positioned on the superior plate. Some experimental results are presented.
An improved calibration method for structured light projection measurement system

The accurate calibration for a 3D profile measurement system based on structured light projection is important to the precision measurement system; however, system calibration is always complicated and time-consuming. An improved fast method is proposed to calibrate the measurement system. First, LCD monitor, as a calibration plate, displays chessboard pattern designed by computer programming, and camera captures 1 image. Then LCD monitor displays white pattern, projector projects horizontal and vertical color-encoded fringes to the LCD monitor, and camera collects 2 images respectively. A Phase-shifting algorithm is used to establish a highly accurate correspondent relationship between camera pixels and projector pixels, and projector images are generated. Next, move the LCD monitor to other 8 places, get camera and projector images which are set for camera and projector calibration respectively using Zhang’s calibration method. Compared with ordinary techniques which use expensive equipments such as two or three orthogonal plates, LCD monitor is easy-to-use and flexible, and experiments show that calibration accuracy is improved by 5 times. In comparison with traditional projector calibration method, this method decreases the number of captured images from 8 to 2 in each place and increases the processing speed. Combining camera calibration and projector calibration, the complex calculation process of integrating traditional camera calibration and projector calibration can be simplified. Experiments have been performed based on the proposed technique and good results have been obtained.