Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mathematical Model of the Skype VoIP Congestion Control Algorithm

Voice over Internet Protocol (VoIP) is an Internet application of ever increasing importance. The purpose of this note is to derive a mathematical model of the Skype VoIP congestion control. The proposed model is in the form of a non linear hybrid automation, and has been validated through extensive experiments. The dynamics of the Skype sending rate, the stability of its equilibrium points and the efficiency in bandwidth utilization while avoiding network instability are analyzed. Results show that, under network congestion, the Skype sending rate is driven by the packet loss ratio and matches the available bandwidth with a steady state finite error.
Method and architecture for virtual desktop service

The present invention relates to a method and architecture that can efficiently provide virtual desktop services. The service architecture for a virtual desktop service according to the present invention includes a connection broker that performs authentication, management of a virtual machine, server monitoring, and protocol coordination. ; In order to provide an on-demand virtual desktop service, it is delivered to a specific virtual machine at a predetermined time in a streaming form to manage software resources executed on the specific virtual machine, and provision for the managed software resources. A resource pool for providing provision information according to a request of the connection broker; And a virtual machine infrastructure that supports hardware resources and generates virtual machines for operating the software of the user terminal and provides them as virtual desktops.
Data Driven Decision Support for Failure Prediction

Failure prediction and diagnosis is one of the principal areas in reliability engineering and system safety. Recent developments in the field of data mining opened new research orientation to failure prediction and diagnosis. In this thesis, the feasibility of data-driven decision support for failure prediction of the TWINSCAN machines of ASML is studied. Data-driven approaches focus on learning and classifying occurring faults from historical data without assuming a priori model ahead of time. Machine learning techniques such as classification, for instance are used to predict failures for which the dependent variables are unknown. One of the main tasks is to employ data mining technology and existing predictive modelling techniques on existing ASML event logs generated by TWINSCAN machines. The problems addressed in this project are related to several areas studied in data mining, including but not limited to mining data streams, predictive analytics, time-series prediction. An ensemble data-driven decision support system is proposed for predictive maintenance of ASML TWINSCAN machines. Several machine learning and statistical techniques are compared in terms of their predictive ability to find the best models. An ensemble decision support system is proposed by incorporating the best models based on the findings. The model encompasses existing and novel fault prediction techniques to predict future machine failures. The results showed that machine characteristics are instantaneous and the machine do not show early signs of failures. The results obtained by pattern mining suggests that failures could be predicted at least 15 minutes before their occurrence by employing rules with a confidence value of at least 0.25. The classification results showed that certain failures could be predicted on an average with a precision greater than 0.75 and a recall value of 0.39 with a prediction time that ranges from 1 hour to 24 hours before their occurrence.
Three Heuristic Rules for Sequencing Jobs to a Single Production Facility

This paper presents the experimental performance of three elementary rules for sequencing jobs through a single production facility. The problem is a variant of the "traveling salesman problem. " It is presented in terms of the job sequencing problem because of practical constraints on problem solving methods encountered in this situation. The objective of the sequencing decision is to minimize the facility downtime or setup time over a finite batch of jobs. The study consists of examining the performance of the three heuristic rules in terms of two criteria. The first is the optimal downtime obtained by the branch and bound algorithm. The second is the downtime which results from a random sequencing of jobs through the facility. The sampling procedure considers different values of the variance of between-job setup times, the number of jobs in the sequencing batch, and the form of the distribution of setup times.
A Query Language for Web Ontologies

In August 2002 the Joint United States/European Union ad hoc Agent Markup Language Committee announced the first release of the DAML Query Language (DQL) Abstract Specification. A revision of the specification followed in April 2003. This work analyses the current DQL specification and provides a (partial) implementation as a feasibility study. The prototype uses Description Logic reasoners for automated reasoning services over the DAML+OIL knowledge bases to compute the query answers. The queries are restricted to conjunctive queries that have a tree-like structure. The prototype successfully computes queries against knowledge bases in the Semantic Web. It shows that a query transformation into Description Logics queries is a feasible setting to provide a DQL service. However, further performance improvements are necessary before the prototype is usable in real world applications.
Four switch Three-Level Soft Switched Converter

A Three-level, constant-frequency, isolated converter which employs a coupled in conductor to achieve zero-voltage switching. Three level DC converter has been introduced hare. This converter consists of four switches, which give the two levels of the DC output i.e. 200V each. It will also give another level of DC output at inductor side which is 45V DC. We take the input 750V and it split three different levels of DC output. The entire model simulated using power system block set in MATLAB 2013.
PUZZLAR, A PROTOTYPE OF AN INTEGRATED PUZZLE GAME USING MULTIPLE MARKER AUGMENTED REALITY

Jigsaw puzzles are an old concept but many people still enjoy playing them. Living in an ever-evolving world, people and technology have become inseparable. One technology that is on the rise is Augmented Reality (AR), which combines the real world with virtual or computer-generated data. This research is based on developing a combination of jigsaw puzzles with AR (multiple marker-based) called Puzzlar, using FLARManager as an AR tool. The application also uses Adobe Flash (game design) and PHP. The uniqueness of the prototype program is in its use of 2D physical markers to represent 3D jigsaw puzzle pieces that are animated in the playing mode. In user acceptance testing (UAT), 70% of the testers were satisfied with the game play of Puzzlar. However, 30% of the testers thought that it could be improved.
Guidance and control for multi-stage rendezvous and docking operations in the presence of uncertainty

Rendezvous and docking missions have been a mainstay of space exploration from the Apollo program through present day operations with the International Space Station. There remains a growing interest in several mission types that not only rely on rendezvous and docking, but also rely on maneuvering spacecraft once docked. For example, there is active interest in orbital debris removal, on-orbit assembly, on-orbit refueling, and on-orbit servicing and repair missions. As these missions become more and more popular, the number of rendezvous and docking class operations will increase dramatically. Current methods focus on performing rendezvous and docking to very well-known targets and in very well-known conditions. Inherent to these new mission types, however, is an increasing element of uncertainty to which new guidance and control architectures will need to be robust. As guidance and control techniques become more robust, a corresponding tradeoff in performance can typically be experienced. This thesis attempts to address the uncertainties in rendezvous and docking operations while maintaining a probabilistically optimal level of performance. There are two main focuses in the thesis: spacecraft trajectory optimization and reference-tracking controller selection. With respect to trajectory optimization, the goal is to nd probabilistically optimal trajectories given large uncertainties in mission critical parameters, such as knowledge of an obstacle's position, while knowing that the trajectory is able to be replanned onboard the spacecraft when higher precision information is obtained. This baseline optimal trajectory and subsequently replanned trajectories are then followed by an optimally determined set of reference-tracking controllers. These controllers are selected and scheduled throughout the phases of the mission based on the probabilistically expected performance in the presence of noise and uncertain parameters. This process is explored through its implementation on a generic problem setup for rendezvous, docking, and joint maneuvering. Results specfic to this problem and associated analysis motivate the use of probabilistic planning in future space missions. Specically, the thesis shows that fuel and tracking performance can be improved if multi-stage missions are planned continuously through phase transitions and without the use of waypoints. Furthermore, under the presence of large uncertainties, the techniques in this thesis produce better expected fuel and tracking performance than traditional trajectory planning and controller selection methods.
A multivariable predictive control with internal model of a laminated windshield bending furnace

Laminated windshield bending furnaces have always been controlled manually. Previously, several attempts of automatic control have been tried unsuccessfully. This is essentially due to the fact that this kind of plants is a strongly coupled multivariable system, with nonlinearities and a large time delay. An other serious problem of the furnace to be controlled is the fact that it produces successively and periodically different types of windshields. So the plant is a time-varying system with periodic coefficients and disturbances. In this paper, an adequate combination of modern automatic control techniques, such as predictive control, the internal model of Morari and Smith predictor, have been used to obtain an original and efficient controller scheme for periodic plants. It has been tested on a real plant and has given satisfaction. An increase of the bending precision from 30% to 100% relatively to the manual control has been obtained. <<ETX>>
Kinematic Synthesis Using Reinforcement Learning

The presented research demonstrates the synthesis of two-dimensional kinematic mechanisms using feature-based reinforcement learning. As a running example the classic challenge of designing a straight-line mechanism is adopted: a mechanism capable of tracing a straight line as part of its trajectory. This paper presents a basic framework, consisting of elements such as mechanism representations, kinematic simulations and learning algorithms, as well as some of the resulting mechanisms and a comparison to prior art. Series of successful mechanisms have been synthesized for path generation of a straight line and figure-eight.
BINOMIAL CONFIDENCE INTERVALS FOR SMALL SAMPLE USABILITY STUDIES

James R. LewisIBM Human Factors GroupP. O. Box 1328Boca Raton, FL 33429-1328Tel: +1 (407) 443-1066Fax: +1 (407) 443-2778E-mail: JIMLEWIS@US.IBM. COMusability studies, sample size, usability measurementEfficiency is an important consideration in the design of industrial usability studies. One wayto reduce the cost of a usability study is to reduce its sample size. Small samples are notalways appropriate, but in this paper I will describe a way to use binomial confidenceintervals to determine rapidly if a usability defect rate exceeds a criterion. In these situations,relatively small samples are often adequate to meet the goals of a usability evaluator. I willalso discuss the risks of using small samples in these situations.
Texting During Class: Audience Response Systems

Librarians teach in many different environments. It is often difficult to gauge whether students are benefiting from training. Students often feel self-conscious or uncomfortable asking and answering questions in class. Audience response systems (ARS) make it easy for presenters to get immediate feedback from students who have the ability respond anonymously. Web-based ARS allow participants to engage with presenters using their smartphones, tablets, or computers. This column explores four web-based ARS that are available for free or have free options.
Implementing Remote Display on Commodity Operating Systems

Remote display provides a number of benefits, including ubiquitous access, thin-client computing, remote assistance and secure central management. In practice, it is crucial that remote display systems effectively support existing unmodified applications on commodity operating systems. However, commodity operating system environments have very different display architectures which impact how remote display can be implemented. This dissertation discusses the details of deploying remote display on commodity operating systems, including Linux(with X Window System) and Microsoft Windows. We focus on the implementation of a remote display system on Microsoft Windows and introduce several techniques, including kernel-user mode communication, a high throughput command channel, and efficient synchronization. With these techniques, we successfully implement an asynchronous remote display system on top of a synchronous local display system. Our work extends THINC, a virtual display architecture for remote display, from an X/Linux-only architecture to one across X/Linux and Windows. We present the detailed algorithm we used for supporting a portable command processing pipeline across multiple commodity operating systems. Our experiment results demonstrate that our approach can achieve similar remote display performance on both X/Linux and Windows.
Eyes-off physically grounded mobile interaction

This thesis explores the possibilities, challenges and future scope for eyes-off, physically grounded mobile interaction. We argue that for interactions with digital content in physical spaces, our focus should not be constantly and solely on the device we are using, but fused with an experience of the places themselves, and the people who inhabit them. Through the design, development and evaluation of a series of novel prototypes we show the benefits of a more eyes-off mobile interaction style. Consequently, we are able to outline several important design recommendations for future devices in this area. The four key contributing chapters of this thesis each investigate separate elements within this design space. We begin by evaluating the need for screen-primary feedback during content discovery, showing how a more exploratory experience can be supported via a less-visual interaction style. We then demonstrate how tactile feedback can improve the experience and the accuracy of the approach. In our novel tactile hierarchy design we add a further layer of haptic interaction, and show how people can be supported in finding and filtering content types, eyes-off. We then turn to explore interactions that shape the ways people interact with a physical space. Our novel group and solo navigation prototypes use haptic feedback for a new approach to pedestrian navigation. We demonstrate how variations in this feedback can support exploration, giving users autonomy in their navigation behaviour, but with an underlying reassurance that they will reach the goal. Our final contributing chapter turns to consider how these advanced interactions might be provided for people who do not have the expensive mobile devices that are usually required. We extend an existing telephone-based information service to support remote back-of-device inputs on low-end mobiles. We conclude by establishing the current boundaries of these techniques, and suggesting where their usage could lead in the future.
Document Clustering using Semantic Cliques Aggregation

The search engines are indispensable tools to find information amidst massive web pages and documents. A good search engine needs to retrieve information not only in a shorter time, but also relevant to the users’ queries. Most search engines provide short time retrieval to user queries; however, they provide a little guarantee of precision even to the highly detailed users’ queries. In such cases, documents clustering centered on the subject and contents might improve search results. This paper presents a novel method of document clustering, which uses semantic clique. First, we extracted the Features from the documents. Later, the associations between frequently co-occurring terms were defined, which were called as semantic cliques. Each connected component in the semantic clique represented a theme. The documents clustered based on the theme, for which we designed an aggregation algorithm. We evaluated the aggregation algorithm effectiveness using four kinds of datasets. The result showed that the semantic clique based document clustering algorithm performed significantly better than traditional clustering algorithms such as Principal Direction Divisive Partitioning (PDDP), k-means, Auto-Class, and Hierarchical Clustering (HAC). We found that the Semantic Clique Aggregation is a potential model to represent association rules in text and could be immensely useful for automatic document clustering.
Techniques for depth acquisition and enhancement of depth perception

Depth plays an essential role in computer graphics for the sorting of primitives. The related data representation, the depth map, is useful for many different applications. In this dissertation, we present solutions for creating depth maps with the goal of using these maps to enhance the depth perception in the original images. Regarding the generation of depth maps, we propose two solutions, a reconstruction method via near-light photometric stereo (PS) and a depth map design tool via user guidance. Additionally, we present several techniques for image enhancement of depth perception based on depth information. In the following, we give a short summary of the dissertation.
Pilot Validation of a Computal Seated Human Model Using an Instrumented Chair

Sitting-acquired deep tissue injuries (SADTI) are the most serious type of pressure ulcers. In order to investigate the ethiology of SADTI a new approach is under development. A musculo-skeletal model can predict forces at different seated positions and thereby find an optimum position where the risk of SADTI is minimized. This study focuses on validation of a musculo-skeletal model developed in the AnyBody Modeling System for predicting reaction forces on a wheelchair. A Wheelchair with forcemeasuring equipment was developed, an experiment was conducted, and the experimental results were compared with the predictions of the computational model. The results show that the model predicted changes in reaction forces due to changes in the chair posture well. It was concluded that the experimental approach is satisfactory and more experiments should be carried out to completely validate the computational model.
Fussy methods in expert systems for configuration and control (models, implementations and experiences)

Fuzzy methods are often discussed, and they may play an important role in the construction of knowledge-based systems. This paper discusses the main fields of knowledge-processing which are influenced by fuzzy methods, starting from set-theoretical considerations. The experiences of the authors in constructing expert systems in the fields of configuration and process control are comprehended and partially generalized. <<ETX>>
Bigram proximity matrix

A transformation of the text stream called a bigram proximity matrix (BPM) has been developed. The BPM is used to encode free‐form text so computational techniques can be applied to this type of information resource. For example, one could classify the encoded documents using k nearest neighbor (k‐NN) discrimination, group the documents according to their topic, search for latent topics, and more. The hope is that encoding text documents using the BPM will preserve the meaning better than the bag‐of‐words method commonly used in information retrieval and is easier to execute than other natural language processing applications. In this article, we provide a brief introduction to natural language processing and definitions for some of the concepts. Next, we define the BPM and give some examples of how it has been used. We then provide a weighted variant of the BPM and conclude with extensions to this type of document encoding. Copyright © 2010 John Wiley & Sons, Inc.
Development of a multi-objective goal programming model for the European apple industry

Within the European Union and throughout the world, apples are an important fruit crop and the EU apple industry sustains a healthy internal and external market. Consumers demand a high quality blemish-free product, which has inevitably dictated an intensive pattern o f pesticide use to control pests and diseases throughout the industry. As a consequence, apple orchards are often treated with a continuos dosage o f chemical sprays during their operational life, defending the crop against insect and fungal diseases. In turn, this pattern o f intensive agro-chemical management has created social, economic and environmental impacts with hundreds o f millions of people being exposed to pesticides each year, both on and off farm. However, against this, the economic benefit derived by the demand for pesticides for apples in the EU has led to the development o f a sector generating an approximate turnover o f six billion EURO, which clearly reflects social (employment) and economic gain. However, given the environmental problems associated with existing technologies, a collaborative European project was instigated to examine the improvements in environmental quality which might be gained through the introduction o f new apple varieties, bred for their resistance to the most significant apple diseases, scab and mildew. Since such new varieties would still need to meet market requirements and would also need to be capable o f delivering similar social and economic returns to the apple industry, assessing the likely success o f the new apple variety involved a complex, multi-dimensional decision problem. This study shows the development of a mathematical programming model constructed to provide a tool for overcoming this multi-dimensional problem. Specifically, a Goal Programming model was developed to allow the simultaneous appreciation o f Social, Environmental and Economic Goals within the EU apple industry. In constructing this model, this study was able to test the main hypothesis o f whether it was possible to simultaneously compare the social, economic and environmental components o f a whole industry when goals in each o f these sectors are measured in quite different units. However, the model also tests, mainly through the use o f sensitivity analysis, the likely social, economic and environmental impacts that the introduction o f a specific new apple variety would have for the EU apple industry. The conclusions show it is possible to successfully model such multi-dimensional problems and illustrates the bounds within which a new apple variety could create a Pareto improvement within the EU apple industry.