Miracle-dz/UniFAR-FTUs huggingface dataset:
WCET Optimizations and Architectural Support for Hard Real-Time Systems

WCET ANALYSIS AND OPTIMIZATIONS OF THE REAL-TIME APPLICATIONS ON MULTI-CORE PROCESSORS By Yiqiang Ding, Ph.D. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2012. Director: Dr. Wei Zhang, Associate Professor, Department of Electrical and Computer Engineering As time predictability is critical to hard real-time systems, it is not only necessary to accurately estimate the worst-case execution time (WCET) of the real-time tasks but also desirable to improve either the WCET of the tasks or time predictability of the system, because the real-time tasks with lower WCETs are easy to schedule and more likely to meat their deadlines. As a real-time system is an integration of software and hardware, the optimization can be achieved through two ways: software optimization and time-predictable architectural support. In terms of software optimization, we first propose a loop-based instruction prefetching approach to further improve the WCET comparing with simple prefetching techniques such as Next-N-Line prefetching which can enhance both the average-case performance and the worst-case performance. Our prefetching approach can exploit the program control-flow information to intelligently prefetch instructions that are most likely needed. Second, as inter-thread interferences in
Nature-Inspired Toolbox to Design and Optimize Systems

Nature-Inspired (NI) Toolbox is a Particle Swarm Optimization (PSO) based toolbox which is developed in the MATLAB environment. It has been released under General Public License and hosted at SourceForge.net (http://sourceforge.net/projects/nitool/). The purpose of this toolbox is to facilitate the users/designers in design and optimization of their systems. This chapter discusses the fundamental concepts of PSO algorithms in the initial sections, followed by discussions and illustrations of benchmark optimization functions. Various modules of the Graphical User Interface (GUI) of NI Toolbox are explained with necessary figures and snapshots. In the ending sections, simulations results present comparative performance of various PSO models with concluding remarks.
Data-supported optimization for maximum likelihood DOA estimation

We introduce a new conceptually simple and computationally effective solution to the maximum likelihood (ML) direction of arrival (DOA) estimation problem that consists of maximizing the likelihood function (LF) over a set of points derived from the data. Two different data-supported optimization (DSO) based techniques are formulated which use the data-supported grid points obtained by means of ESPRIT-like and root-MUSIC-like methods, respectively. The first technique is shown to be the method of choice in the short sample size case, whereas the second technique is applicable to situations where the number of snapshots is large. We show that the data-supported grid search of the LF provides the performance similar to that achieved by the genetic algorithm (GA), but at a significantly lower computational cost.
Automated inference of software development behaviors: design, implementation and validation of zorro for test-driven development

A recent focus of interest in software engineering research is on low-level software processes, which define how software developers or development teams should carry on development activities in short phases that last from several minutes to a few hours. Anecdotal evidence exists for the positive impact on quality and productivity of certain low-level software processes such as test-driven development and continuous integration. However, empirical research on low-level software processes often yields conflicting results. A significant threat to the validity of the empirical studies on low-level software processes is that they lack the ability to rigorously assess process conformance. That is to say, the degree to which developers follow the low-level software processes can not be evaluated. In order to improve the quality of empirical research on low-level software processes, I developed a technique called Software Development Stream Analysis (SDSA) that can infer development behaviors using automatically collected in-process software metrics. The collection of development activities is supported by Hackystat, a framework for automated software process and product metrics collection and analysis. SDSA abstracts the collected software metrics into a software development stream, a time-series data structure containing time-stamped development events. It then partitions the development stream into episodes, and then uses a rule-based system to infer low-level development behaviors exhibited in episodes. With the capabilities provided by Hackystat and SDSA, I developed the Zorro software system to study a specific low-level software process called Test-Driven Development (TDD). Experience reports have shown that TDD can greatly improve software quality with increased developer productivity, but empirical research findings on TDD are often mixed. An inability to rigorously assess process conformance is a possible explanation. Zorro can rigorously assess process conformance to a specific operational definition for TDD, and thus enable more controlled, comparable empirical studies.
Construcción y validación de instrumentos de recolección de datos para el período perioperatório de cirugía cardiaca

Este estudo teve como objetivo construir e validar instrumentos de coleta de dados para a identificacao de diagnosticos de enfermagem de pacientes adultos que se encontram no periodo perioperatorio de cirurgia cardiaca. Os instrumentos de coleta de dados propostos foram fundamentados no modelo conceitual de Wanda Horta. Para construcao dos instrumentos foi realizado um levantamento bibliografico com o objetivo de levantar sinais e sintomas importantes, que caracterizariam os diagnosticos de enfermagem. Para a validacao de aparencia e conteudo dos instrumentos de coleta de dados, elaboramos um questionario, que foi entregue a cinco enfermeiros convidados para realizar a validacao. Todos os profissionais solicitados para realizar a validacao expressaram que os instrumentos favorecem a formulacao dos diagnosticos de enfermagem e que os dados ou questoes sao suficientes para identificar alteracoes nas necessidades basicas.
Automatic image annotation using semi-supervised multi-instance multi-label learning algorithm

Automatic image annotation has emerged as an important research topic. From the perspective of machine learning, the annotation task fits both multi-instance and multi-label learning framework due to the fact that an image is composed of multiple regions, and is as-sociated with multiple keywords as well. In this paper, we propose a novel Semi-supervised multi-instance multi-label (SSMIML) learning framework, which aims at taking full advantage of both labeled and unlabeled data to address the annotation problem. Specifically, a reinforced diverse density algorithm is applied firstly to select the Instance prototypes (IPs) with respect to a given keyword from both positive and unlabeled bags. Then, the selected IPs are modeled using the Gaussian mixture model (GMM) in order to reflect the semantic class density distribution. Furthermore, based on the class distribution for a keyword, both positive and unlabeled bags are redefined using a novel feature mapping strategy. Thus, each bag can be represented by one fixed-length feature vector so that the manifold-ranking algorithm can be used subsequently to propagate the corresponding label from positive bags to unlabeled bags directly. Experiments on the Corel data set show that the proposed method outperforms most existing image annotation algorithms.
Synthetic cannabinoids : general considerations

Around 2008 synthetic cannabinoids were found to be present in and responsible for the psychoactive effects of herbal mixtures with names like ‘Spice’ or ‘K2’. In response to the increased popularity of these products, (inter)national organizations and governments started banning these cannabimimetics gradually. However, the lack of an uniform and international regulation makes it hard to control this issue. For the different types of synthetic cannabinoids the scientific knowledge in terms of pharmacokinetics and pharmacodynamics is limited. This also means that little is known on the health of users, both on short and long term. In the last years effort has been made to make detection of these products possible in different biological matrices. However, since the number of cannabimimetic compounds on the market appears to grow every month, both scientist and legislators run after a moving target.
Commonplace Tools for Studying Commonplace Interactions: Practitioners' Notes on Entry-Level Video Analysis

The advent of two technologies - inexpensive video recorders and digital video annotation software - is revolutionizing the study of human interaction. With palm-held camcorders, researchers can now easily collect video data in the field, where humans interact most naturally. More important, using free digital video annotation software, one can annotate and analyze video data on a laptop. In this methods review, we discuss our own experience with such tools in the study of gesture and language. We note points of general interest to researchers of other disciplines, and conclude with a discussion of new issues raised by the presence of readily available multimedia data.
Indoor Air Quality Monitoring Sensor for the Web of Things

Many Internet of Things platforms use dedicated software coupled with proprietary devices and interfaces, creating silo solutions with no interoperability. The Web of Things paradigm promotes using open Web standards to connect physical objects to the Internet through an application layer. In this paper, we propose a low-cost, indoor air quality monitoring sensor implementing a minimal servient building block recommended by the Web of Things Working Group of the World Wide Web Consortium. The proposed sensor runs a Web server on a low-power system-on-chip microcontroller, which provides temperature, relative humidity and carbon dioxide measurements to the Internet through a REST API. Any client on the Internet able to manage the HTTP protocol may access this sensor, making it compatible with any air quality monitoring platform that uses HTTP.
Frames change in language contact environments

Based on the empirical data of 97 fourth-graders from three districts of Braunschweig in Germany, this paper investigates the possibility of changing semantic frames in multilingual communities. The focus of study is the verb field of self-motion. In a free-sorting task involving 52 verbs, Turkish-speaking students, in particular, placed the verbs schleichen (‘to sneak’) and kommen (‘to come’) in the same group. When explaining the perceived similarity they also used the word schleichen (‘to sneak’), in a specific grammatical construction that is not found in Standard German. This paper suggests that semantic frames may change along with grammatical constructions when typologically distinct languages come into close contact.
Crack image segmentation based on improved DBC method

With the development of computer vision technology, crack detection based on digital image segmentation method arouses global attentions among researchers and transportation ministries. Since the crack always exhibits the random shape and complex texture, it is still a challenge to accomplish reliable crack detection results. Therefore, a novel crack image segmentation method based on fractal DBC (differential box counting) is introduced in this paper. The proposed method can estimate every pixel fractal feature based on neighborhood information which can consider the contribution from all possible direction in the related block. The block moves just one pixel every time so that it could cover all the pixels in the crack image. Unlike the classic DBC method which only describes fractal feature for the related region, this novel method can effectively achieve crack image segmentation according to the fractal feature of every pixel. The experiment proves the proposed method can achieve satisfactory results in crack detection.
Data Center Load Forecast Using Dependent Mixture Model

xi CHAPTER 1 : INTRODUCTION . 1 1.1 Background . 1 1.2 Datacenter overview . 3 1.3 Literature review . 3 1.4 Contributions . 6 1.5 Thesis outline . 6 CHAPTER 2 : THEORY . 7 2.1 Dependent mixture model . 9 2.1.1 Markov process . 10 2.1.2 Hidden Markov model . 13 2.1.3 Hidden Markov model elements . 14 2.1.4 Evaluating hidden Markov model parameters . 17 2.2 Data fitting and n-step ahead forecast . 26 2.2.1 Data fitting . 26 2.2.2 n-step ahead forecast . 27
Dilated Cardiomyopathy. New Therapeutic Approach

Inflammatory reaction has been associated with dilated cardiomyo pathy. In this context, cardiac autoantibodies and inflammatory cell infiltration have been studied during the last two decades towards the understanding of their origin and the underlying pathogenic mechanisms. Recent research has increasingly focused on the development of an etiological therapeutic approach. Immunoadsorption has shown to improve clinical, echocardiographic, haemodynamic and laboratory parameters in patients with inflammatory dilated cardiomyopathy. In this article we review recent literature concerning this subject, including classification, pathophysiological mechanisms and therapy.
Shakespeare and Early Modern Europe: A Critical Survey

ABSTRACT This survey examines the history of criticism on Shakespeare and early modern Europe. With major sociopolitical European events in mind, the article reviews scholarship on this topic from the early twentieth century to the present day. Particular emphasis is placed on studies of Shakespeare’s own treatment of European characters and settings. The related topics of the changing meaning of “Europe” of Shakespeare’s European afterlives are also briefly discussed.
An improved auditory feature based on instantaneous frequency and gammatone filters for underwater acoustic target recognition

Feature extraction based on Gammatone filterbank is more robust than that from Mel filterbank in underwater acoustic recognition. However, both conventional auditory features only represent the energy-based amplitude of the signal, and their performance decrease in low underwater SNR environments. Phase represented by instantaneous frequency (IF) may also contain some characteristics of the target. This paper proposes a novel fusion feature based on the outputs of Gammatone filters, in which an optimized algorithm of instantaneous frequency is given. Experiments employs Support Vector Machine (SVM) as the classifier and relative results indicate that significant performance gains can be obtained with instantaneous frequency information in low noise conditions.
Rôle des macrophytes dans la restauration des milieux lagunaires : successions écologiques

La prise de conscience des risques lies a la degradation de la qualite des milieux lagunaires vis-a-vis de l’eutrophisation a abouti a la mise en œuvre d’actions de gestion visant a reduire les apports en nutriments. Certaines lagunes sont aujourd’hui en phase de restauration, avec une amelioration notable de la qualite de l’eau liee notamment a la reduction des biomasses phytoplanctoniques. En revanche, la reponse des macrophytes benthiques semble plus complexe et non lineaire. A travers une approche complementaire basee sur l’analyse statistique des donnees d’observations acquises de 1998 a 2015 et sur des mesures in situ, cette these vise a identifier la dynamique temporelle et spatiale des macrophytes ainsi que leur role fonctionnel au cours du processus d'oligotrophisation. Au sein des lagunes mediterraneennes, la salinite et les teneurs en nutriments dans la colonne d'eau sont les principaux parametres qui structurent la distribution des macrophytes benthiques. L’analyse statistique menee sur 21 lagunes polyhalines et euhalines a permis d'illustrer les premieres etapes de restauration. La reduction des apports externes a conduit a un basculement rapide (3-4 ans) d’un systeme totalement domine par le phytoplancton vers un systeme domine par les macroalgues opportunistes et notamment les ulves. La reduction de la disponibilite en azote dans la colonne d'eau liee au developpement des ulves favoriserait le developpement des gracilaires (algue rouge) et des chaetomorphes (algue verte filamenteuse). Bien plus que la seule consequence de la restauration, la presence d'especes cles jouerait ainsi un role central dans la restauration en regulant les flux d'azote et de phosphore au sein du systeme et en creant les conditions favorables a l'apparition d'autres especes plus perennes. Bien que notre theorie decrive une tendance vers le retour des macrophytes perennes pour les trajectoires de re-oligotrophisation, nous n’avons pas encore pu documenter ce retour dans les lagunes apres une longue periode d’absence. Ceci, montre l’importance de prendre en compte, entre autres, l’importance des sources internes d’elements nutritifs et de la connectivite pour la recolonisation des angiospermes dans les lagunes.
An exploration of the challenges of sustainable and effective professional development for English as second language teachers in Sri Lanka

This study explores challenges of sustainable and effective professional development for English as Second Language (ESL) teachers in Sri Lanka. It aims to critically examine how the existing English teacher education system as a whole responds to the wider context of the crisis of sustainability in the quality of teaching and learning. It further aims to investigate perceptions of various stakeholders regarding issues, concerns and constraints of ESL teachers in order to explore approaches, strategies and changes needed to enhance effective and sustainable English teacher education within the system. In order to capture the complexity of the education system as a whole, ‘Systems Thinking’ paradigm has been adopted. It views the organizational behaviour and its respective environment as a complex whole of interrelating, interdependent parts rather than fragmented entities, which go beyond simple cause and effect relationships. A qualitative research approach has been used to investigate the experiences, opinions, presuppositions, and interpretations of stakeholders in this complex context. The multiple case studies conducted via fifty-seven informants represent the whole education system namely at the higher, middle and classroom management levels. The methods of data collection encompass focus groups, semi structured interviews and analysis of documents. Six key themes emerged from the analysis of data, namely policy and reforms; administration and management; implementation; structure; curriculum development; and working environment and resources. The research findings reveal the necessity for well-documented policies for English teacher education and the need for systemic management and administration with a shared vision, collaboration and personal mastery to establish tri-level development and effective networks. The lack of sufficient resources is found to be a key challenge in promoting sustainable and effective professional development practices island-wide. These findings are also the bases for recommendations and further research to cater for the socio-economic-political and global demands of post-colonial Sri Lanka.
An efficient procedure for Nakagami-m fading simulation

An efficient method for generating correlated Nakagami-m fading envelope samples is presented. The new method is compared to other methods used to generate Nakagami-m random variates. An accurate approximation to the inverse Nakagami-m cumulative distribution function, valid for all values of m, is derived. Uncertainties regarding the phase distribution and the autocorrelation of the Nakagami-m fading process are discussed. The fading envelope autocorrelation is determined by simulation and asymptotic analysis.
A Realization of Face Detection System Based on ARM Linux

In order to adapt to the requirements of intelligent video monitoring system, this paper presents an ARM-Linux based video monitoring system for face detection. In this system, an ARM processor with a Linux operating system was used, and the USB camera was used to capture data, and then the face detection was conducted in the ARM device. The OpenCV library was transplanted to Linux embedded system. The algorithm of face detection was realized by calling the OpenCV library. Specially, adaboost algorithm was chose as the face detection algorithm. Experimental results show that the face detection effect of the system is satisfactory and can meet the real time requirement of video surveillance.
Motion vector recovery for error concealment

This paper describes an error concealment algorithm to reduce the effect of channel errors in the bitstreams generated by motion compensated video coding algorithms such as MPEG. When channel errors are introduced during transmission and cannot be corrected properly, we can apply an error concealment technique to repair damaged portions of the picture by exploiting the spatial and temporal redundancies in the received and reconstructed video signal. In motion compensated video coding, if some bits are lost or received with errors, not only the current picture will be corrupted, but also errors will propagate to succeeding frames. In this paper, we analyze the effect of channel errors in MPEG-2 bitstreams, and propose an idea for recovering lost or erroneously received motion vectors. Extended luminance intensity value of the lost block is used for motion estimation at the decoder side. Simulation results show that the proposed algorithm achieves good performance in PSNR and provides good subjective image quality.
A Trusted Remote Attestation Model Based on Trusted Computing

Traditional security protocols can not be trusted in some application scenarios of high security level because the endpoints integrity is ignored. In this paper, we propose a novel trusted remote attestation model which combines the secure channel and the integrity measurement architecture of trusted computing. We design and implement a prototype system based on a mature security protocol, Transport Layer Security (TLS) protocol, integrated with integrity report provided by trusted platform module (TPM). The TLS protocol guarantees the security of data exchange process and the integrity report of TPM provides the evidence about the trustworthiness and the security state of the communication endpoints. Compared by traditional approaches, our method is more efficient and can be deployed in large scale systems easily.
Analytical model for adaptive noise cancellation in a speech signal

In this paper, I have presented an analytical modeling for adaptive noise cancellation in a speech signal which is contaminated by a noise or interference signal. I have derived a mathematical modeling for the elimination of noise signal which is present in the speech signal. I has been taken a noise signal as a reference input and another input which is a speech signal that is contaminated by noise signal. The reference noise signal is adaptively controlled by changing the weights of the adaptive filter if needed, to match with the noise component of the speech signal to nullify the effect of it which is present in the speech signal. After that, the clear speech signal will be listen at the output by the listener.