Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcoding Cache For Smart Phones

In this paper, we present Transcoding Cache (TC), a new way for caching data in smart phone application using web service. Transcoding Cache adapts the cache data for better utilization of limited space. Without changing the cache algorithm, TC works by transcoding the cache data in the disk cache. Our experiments show that TC performs better than the normal cache system in term of miss ratio and data loaded through the network. In particular, we can reduce the data transmitted through the mobile network up to 15% comparing to the legacy cache system.
Signal processing methods for characterisation of ventricular repolarisation using the surface electrocardiogram

This thesis investigates the mechanisms underlying drug-induced arrhythmia and pro- poses a new approach for the automated analysis of the electrocardiogram (ECG). The current method of assessing the cardiac safety of new drugs in clinical trials is by the measurement and analysis of the QT interval. However, the sensitivity and specificity of the QT interval has been questioned and alternative biomarkers based on T-wave mor- phology have been proposed in the literature. The mechanisms underlying drug effects on T-wave morphology are not clearly understood. Therefore, a combined approach of for- ward cardiac modelling and inverse ECG analysis is adopted to investigate the effects of sotalol, a compound known to have pro-arrhythmic effects, on ventricular repolarisation. A computational model of sotalol and IKr, an ion channel that plays a critical role in ventricular repolarisation, was developed. This model was incorporated into a model of the human ventricular myocyte, and subsequently arranged in a 1-D fibre model of 200 cells. The model was used to assess the effect of sotalol on IKr, action potential duration and biomarkers of ventricular repolarisation derived from the simulated ECG. In parallel, an automated ECG analysis method based on machine learning, signal processing and time-frequency analysis is developed to identify a number of fiducial points in ECG waveforms so that timing intervals and a smooth T-wave segment can be extracted for morphology analysis. The approach is to train a hidden Markov model (HMM) using a data set of ECG waveforms and the corresponding expert annotations. The signal is first encoded using the undecimated wavelet transform (UWT). The UWT coefficients are used for R-peak detection, signal encoding for the HMM and a wavelet de-noising procedure. Using the Viterbi algorithm, the trained HMM is then applied to a subset of the ECG signal to infer the fiducial points for each heart beat. Furthermore, a method for deriving a confidence measure based on the trained HMM is implemented so that a level of confidence can be associated with the automated annotations. Finally, the T-wave segment is extracted from the de-noised ECG signal for morphology characterisation. This thesis contributes to the literature on automated characterisation of drug ef- fects on ventricular repolarisation in three different ways. Firstly, it investigates the mechanisms underlying the effects of drug inhibition of IKr on ventricular repolarisation as captured by the simulated ECG signal. Secondly, it shows how the combination of UWT encoding and HMM inference can be effectively used to segment 24-hour Holter ECG recordings. Evaluation of the segmentation algorithm on a clinical ECG data set demonstrates the ability of the algorithm to overcome problems associated with existing automated systems, and hence provide a more robust analysis of ECG signals. Finally, the thesis provides insight into the drug effects of sotalol on ventricular repolarisation as captured by biomarkers extracted from the surface ECG.
Domain-Specific Language Testing Framework

In this report we present a framework for the generation of tests using domain-specific models. These tests can be used to verify the correctness of the artifacts generated using the domain-specific model and systems that use these artifacts. By generating the tests instead of manually developing them, development time is reduced while usability is improved. The test generation process consists of three phases: generalization, generation and specification. In the generation phase the domain-specific model is transformed to an instance of a newly developed generic metamodel, to abstract away from language-specific features. In the generation phase, generic test cases are generated that achieve branch/condition coverage. In the specification phase the generic test cases are transformed to executable test code. By keeping the test cases generic, several types of tests can be generated using the same generic test case. We show that the developed framework supports a multitude of languages and resulting test types. We also discuss several areas where the framework can be extended with addition features. An important lesson learned during the research and development is that a DSL (testing) framework should be setup modular, extensible and small.
Planning and control of robotic juggling tasks

A new class of control algorithms “mirror algorithms” give rise to experimentally observedjuggling behavior in a simple robotic mechanism. The simplest of these algorithms (upon which all the others are founded) is provably correct with respect to a simplified model of the robot and its environment. This paper reviews the physical setup and underlying mathematical theory, discusses two significant extensions of the fundamental algorithm, provides data from our successful empirical verifications of these control strategies and briefly speculates upon the larger implications for the field of robotics. For more information: Kod*Lab Disciplines Electrical and Computer Engineering | Engineering | Systems Engineering Comments Copyright Massachusetts Institute of Technology. Reprinted from Robotics Research: The Fifth International Symposium 1990, pages 321-332. NOTE: At the time of publication, author Daniel Koditschek was affiliated with Yale University. Currently, he is a faculty member in the Department of Electrical and Systems Engineering at the University of Pennsylvania. This conference paper is available at ScholarlyCommons: http://repository.upenn. edu/ese_papers/674
The development of a compact point-defense phased array antenna

The design and construction of an S-band space-fed phased array antenna are presented. The antenna is a major unit of the MARS (Meliorated Advanced Radar System), an S-band, space-fed phased array, multifunction, mobile radar system designed for pointing defense. A prototype scaled-down MARS space-fed array antenna was designed an built with 254 radiation elements. The crucial objective of this program was to demonstrate the feasibility of producing a low-cost, high-performance, easy-to-maintain, electronically phased array antenna. The critical components have been well developed and tested. <<ETX>>
FORTRAN programming, a spiral approach

Imagine that you get such certain awesome experience and knowledge by only reading a book. How can? It seems to be greater when a book can be the best thing to discover. Books now will appear in printed and soft file collection. One of them is this book fortran programming a spiral approach. It is so usual with the printed books. However, many people sometimes have no space to bring the book for them; this is why they can't read the book wherever they want.
High performance integrated CMOS frequency-to-voltage converter

In this paper we present a new high performance frequency-to-voltage converter (FVC) dedicated for integrated CMOS mixed-signal (analog/digital) applications. The circuit is very fast and requires a very small silicon area for integration. The output voltage generated by this FVC does not present any AC ripples and is proportional to the period of a square wave form input signal. The time response of this FVC is very small and is approximately equal to eight cycles of the input signal within a precision of 0.4%. The circuit can operate theoretically up to 100 MHz and its operating frequency range can easily be changed.
Equating scores on “Lite” and long library user survey forms

Purpose – In 2009, in Performance Measurement and Metrics, the authors reported results of LibQUAL+® experiments at four universities in which the use of the LibQUAL+® Lite protocol was investigated. The purpose of this article is to briefly report related results for the first use of LibQUAL+® in Hebrew. The authors also take the opportunity to propose another method for equating scores across the LibQUAL+® Lite and the traditional LibQUAL+® protocols.Design/methodology/approach – Matrix sampling is a survey method which can be used to collect data on all survey items without requiring every participant to react to every survey question. Here, the authors investigate the features of data from one such survey, the LibQUAL+® Lite protocol, exploring the participation rates, completion times, and result comparisons across the two administration protocols – the traditional LibQUAL+® protocol and the LibQUAL+® Lite protocol – at an Israeli University and for the first time, in Hebrew.Findings – This experimen.
Resumptive Prolepsis: A study in indirect A'-dependencies

This dissertation investigates A’-dependencies where the dislocated constituent is not transformationally related to the position where it is interpreted. The analysis is carried out within the Principles & Parameters framework. The first two chapters address relative clauses. Based on a detailed examination of reconstruction, it is argued that German restrictive relatives should be given a Matching Analysis. Chapter three analyzes an alternative to long-distance relativization in German and Dutch where the relative pronoun is governed by the preposition von/van ‘of’ and a resumptive appears instead of a gap in the complement clause. The construction has the hallmarks of an indirect A’-dependency: The external head is interpreted inside the complement clause but cannot be transformationally related to that position. The paradox is resolved by postulating short A’-movement in the matrix clause, operator movement in the complement clause and an ellipsis operation that links the chains. Chapter four analyzes relative clauses in Zurich German. While local relativization is shown to be largely parallel to Standard German, long-distance relativization is reanalyzed in terms of Resumptive Prolepsis. This study is of interest to anyone interested in the syntax of relative clauses, reconstruction, resumption or in the syntax of Standard German, Zurich German and Dutch.
Proceedings of the 14th ACM symposium on Access control models and technologies

It is our great pleasure to welcome you to the 14th ACM Symposium on Access Control Models and Technologies (SACMAT 2009). This year's symposium continues its tradition of being the premier forum for presentation of research results on leading edge issues of access control, including models, systems, applications, and theory. The call for papers attracted 75 submissions from many countries around the world. Each submission was reviewed by at least three reviewers who are experts in the field. Furthermore, extensive online discussions took place in making the final selections for the symposium. The program committee selected 24 papers that cover a variety of topics, including role engineering, secure information sharing, security analysis and verification, trust and access control for systems and model extensions and meta-models. The program includes a panel on Usability Meets Access Control: Challenges and Research Opportunities and another on Spatio-Temporal Access Control: Challenges and Applications. Finally, the program includes a keynote speech by Frank Siebenlist from Argonne National Laboratory, USA on Challenges and Opportunities for Virtualized Security in the Clouds. We hope that these proceedings will serve as a valuable reference for security researchers and developers.
Modeling Spectrum Sensing and Optimal Time Interval Selection for Cognitive Radio System

Cognitive Radio (CR) is a promising technology for next-generation wireless networks in order to efficiently utilize the limited spectrum resources and satisfy the rapidly increasing demand for wireless applications and services. In cognitive radio technology, the wireless system is used to find a vacant band that cognitive radio user can use when its use doesn’t interrupts the primary user. During the mobility of secondary user has to move from one primary user system to another primary user system. So the user should check periodically whether the band is still vacant for channel selection and the optimal time interval between two successive checks for spectrum availability, we are using spectrum sensing and geo-location database scheme. We have to maximize the duration of spectrum availability checks while ensuring that the probability of the cognitive radio user disturbs the primary user (PU) should less than a specified threshold. Authenticating the PU signal in order to mitigate PU emulation attacks. Authenticating primary user’s signal in CRN integrates link signatures and cryptographic mechanisms. Keywords— cognitive radio, spectrum sensing, channel selection, Geo-location database, PU emulation attack.
A new neural network model based on nearest neighbor classifier

A new neural network model for pattern classification based on the nearest neighbor method is presented. In this model, the training patterns were mapped to hidden neurons, but one hidden neuron may represent one or more training patterns. At the recognition stage, the distance to the training patterns were calculated in parallel by the hidden neurons. Therefore, the nearest neighbor can be found efficiently. Some experimental results on recognition of printed and hand-written numerals are given to evaluate the proposed model. Comparisons with the backpropagation learning algorithm are included. <<ETX>>
Resource‐Constrained Modulo Scheduling

This chapter presents an unusual application of the RCPSP, namely an instruction scheduling problem for very long instruction word processors. The specific characteristics of these processors and the cyclic nature of the problem yields a modulo RCPSP with minimum and maximum time lags. New integer linear programming formulations are proposed and an efficient large neighborhood search technique is used to solve near-optimally large industrial problems in a few minutes.
Modelización de la combinación dinámica de estructuras léxicas.

En todo intento de formulacion de principios de organizacion de las estructuras lexicas y de caracterizacion de mecanismos de combinacion de estas estructuras subyace el fenomeno de la indeterminacion de la informacion. La modelizacion y el procesamiento de este fenomeno se han convertido en objetivos prioritarios de los enfoques computacionales de la semantica lexica. En esta comunicacion, se proponen precisamente algunos elementos organizadores de las estructuras lexicas que vehiculan un cierto grado de indeterminacion, asi como el analisis de herramientas composicionales que permitan controlar el proceso de construccion dinamica de la significacion a partir de estructuras indeterminadas. Este trabajo esta realizado, en particular, desde la perspectiva de una simulacion informatica del proceso de interpretacion de expresiones compuestas de tipo "nombre-adjetivo".
Software engineering: Theory and practice

A book that describes and applies Software Engineering methods according to the state of the art of the subject matter; it is integrated with a proper exemplification and evolves as each topic is introduced. The material is designed for undergraduates of the initial course of Software Engineering and/or professionals who wish to improve their techniques for the development of software systems.
Computationally efficient methods for polyphonic music transcription

Automatic music transcription is a music information retrieval (MIR) task which involves many different disciplines, such as audio signal processing, machine learning, computer science, psychoacoustics and music perception, music theory, and music cognition, The goal of automatic music transcription is to extract a human readable and interpretable representation, like a musical score, from an audio signal. To achieve this goal, it is necessary to estimate the pitches, onset times and durations of the notes, the tempo, the meter and the tonality of a musical piece. The most obvious application of automatic music transcription is to help a musician to write down the music notation of a performance from an audio recording, which is a time consuming task when it is done by hand. Besides this application, automatic music transcription can also be useful for other MIR tasks, like plagiarism detection, artist identification, genre classification, and composition assistance by changing the instrumentation, the arrangement or the loudness before resynthesizing new pieces. In general, music transcription methods can also provide information about the notes to symbolic music algorithms. This work addresses the automatic music transcription problem using different strategies. Novel efficient methods are proposed for onset detection (detection of the beginnings of musical events) and multiple fundamental frequency estimation (estimation of the pitches in a polyphonic mixture), using supervised learning and signal processing techniques. The main contributions of this work can be summarized in the following points: * An analytical and extensive review of the state of the art methods for onset detection and multiple fundamental frequency estimation. * The development of an efficient approach for onset detection and the construction of a public ground-truth data set for this task. * Two novel approaches for multiple pitch estimation of a priori known sounds using supervised learning methods. These algorithms were one of the first machine learning methods proposed for this task. * A simple iterative cancellation approach, mainly intended to transcribe piano music at a low computational cost. * Heuristic multiple fundamental frequency algorithms based on signal processing to analyze real music without any a priori knowledge. These methods, which are probably the main contribution of this work, experimentally reached the state of the art for this task with a very low computational burden.
Analisa Pengiriman Citra Terkompresi SPIHT dengan Teknik Spread Spectrum Direct Sequence (DS-SS)

In this information technology era, the demand for multimedia communications needs continue to increase. Website on the internet made it interesting by including a visualization of image or video that can be played. Image (image) as one of the multimedia component hold a very important role as a form of visual information. This image file has a capacity large enough, and to access it takes a long time, so it takes a data compression technique, with the aim to reduce the redundancy of the data contained in the image file, so that the image files can be stored or transmitted efficiently. In this case the image files will be compressed using the algorithm SPIHT (Set Partitioning In Hierarchical Trees), SPIHT image compression algorithm that is capable of achieving high compression ratios. By way of coding wavelet transforms coefficients gradually. Due to the compressed data stream is very vulnerable to channel interference. In the process of transmission technique was used Direct Sequence Spread Spectrum (DS-SS). Results obtained after simulation, reconstruction of the images measured by an objective assessment parameters based on the value Peak Signal to Noise Ratio. Objective assessment of efficient reconstruction image quality with the rate 2bpp (bit/pixel) 46,834 dB PSNR are values obtained Keywords: SPIHT, wavelet, DSSS, rate, PSNR
A Hierarchical Approach to Motion Analysis and Synthesis for Articulated Figures

Animating human-like characters is a recurring issue in computer graphics. Recently, capturing live motion has become one of the most promising technologies in character animation. Due to the success of this technology, realistic and highly detailed motion data are rapidly spread in computer graphics applications. Crafting animation with such data requires a rich set of specialized tools such as interactive editing, retargetting, blending, stitching, smoothing, enhancing, up-sampling, downsampling and so on. With those tools, animators combine motion clips together into animations of arbitrary length with great variety in character size, environment geometry, and scenario. A typical process of producing animation from live-captured data includes three major steps: The first step is to filter the raw input signal received from a motion capture system to obtain smoother, pleasing motion data. The next is to adapt the motion data to fit into a specific character or a virtual environment that may different from the live puppeteer or the environment, respectively, where the motion takes place. The motion segments thus obtained are combined into a seamless animation in the final step. In the thesis, we elaborate fundamental techniques that facilitate such tasks with proper consideration on orientation components and articulated structures. Specifically, three issues are addressed: We first present a general scheme of constructing spatial filters that perform smoothing and sharpening on orientation data. The next issue is to adapt an existing motion of a human-like character to have the desired features specified by a set of constraints. An efficient algorithm based on a hierarchical curve fitting technique and a fast inverse kinematics solver is provided. Finally, we present a multiresolution analysis scheme which decomposes a motion signal into a base level and a hierarchy of detail coefficients, followed by a synthesis scheme that produces a new motion by hierarchically combining detail coefficients of prescribed example motions.
On-line system for monitoring and forecasting Earth surface changes using sequences of remotely-sensed imagery

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study develops an on-line system for monitoring and forecasting ground surface changes by adaptively generating an appropriate synthetic time series at regular interval with recovering missing measurements for sequential images that are compiled at irregular time interval from Earth ground. The proposed system integrates an adaptive reconstruction technique and a classification algorithm. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. The classification algorithm segments each image frame by partitioning into physically meaningful regions whose statistics are expected to depend on the physical properties of the region. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series and monitoring of temporal variation in surface characteristics by observing statistical changes between contiguous image frames in the adaptive system.
System life cycle methods: an evaluation of their applicability

The authors examine the most frequently used methods for system development. Two development methodologies and over 15 techniques are examined for their applicability during different phases of the system development life cycle, for different types of systems, and for different levels of structure in the problem domain. The results obtained support the use of a contingency approach in the selection of methods for system development. <<ETX>>