Miracle-dz/UniFAR-FTUs huggingface dataset:
Achieving ‘best value’ for the community by deployment of risk based cost estimation using Monte-Carlo Simulation to rate-payer-funded capital intensive road projects.

This paper presents the application and validation of a new tool developed by the first author for accurate risk-based estimation of project budgets. Typical capital intensive projects to which this tool can be applied include road reconstruction, road resheet and road rehabilitation projects. Quantitative risk analysis and stochastic modeling using Monte -Carlo simulation is embedded in the algorithms of the computer code. The tool forecasts a range of possible project costs and the probability of the occurrence of those costs by taking into account uncertainties and associated risks. Application of the tool to capital intensive road projects designed by the second author and constructed in 2011 & 2012 demonstrates its validity and utility. Comparisons of forecasted estimates using this tool with actual costs and with traditional deterministic methods of cost estimation (such as --point base-case estimates inclusive of contingency) provide valuable insights that can aid management in evaluating alternatives and in making informed decisions when estimating and allocating budgets to a portfolio of road projects.
A New Theory of Technology Usage

Benbasat and Barki (2007) suggest that the traditional perception-intention-usage framework has fulfilled its original purpose and has demonstrated its deficiencies in a number of important respects. Thus, they call for researchers to step outside its limited confines and move toward a new theory that takes into account the constantly changing context of IT. Answering the call, this paper presents a preliminary effort to develop the theory of technology usage (TTU), review its research base, and discuss how it can be applied to different contexts of IT. The current paper also emphasizes that IT should be categorized into productivity-oriented, pleasure-oriented, and dual-purposed, as it evolves from a single-user system in an organizational context to a multi-user system in a social and leisure setting. Moreover, a two-step procedure is devised for such trichotomization. The TTU incorporates the core concepts of the needs-based perspective on behaviors, and maps these concepts in a way that permits prediction and understanding of usage of these three IT categories. The paper is concluded with discussions of implications and directions for future research.
Implementation of Stereophonic Acoustic Echo Canceller on Intel IA-32 Processors with SIMD Capability

This paper presents an e(cid:14)cient implementation of a stereophonic acoustic echo canceller on Intel IA-32 processors with SIMD (single-instruction multiple-data) capability. An e(cid:14)cient data and task allocation overcomes a data alignment problem frequently encountered in a SIMD implementation without additional storage space. Compared with a scalar implementation, this implementation achieves more than four times faster execution speed.
Speech-enabled Systems for Language Learning

Levels of literacy and the variance in them, continue to be a problem in the world. These problems are ubiquitous in the sense that they change form from developing to developed regions, but do not seize to exist. For example, while teacher absenteeism is a fairly large problem in the developing world, student motivation can pose challenges in the developed world. Prior research has demonstrated that games can serve as an efficient medium in bridging these literacy gaps, generating student motivation (or engagement) not just in short term but also in the long term. This dissertation is dedicated to the investigation and application of spoken language technology to language acquisition contexts in the developed world. We explore the broader research question in two major contexts. Firstly, lack of proper English pronunciations is a major problem for immigrant population in developed countries like U.S. This poses various problems, including a barrier to entry into mainstream society. Therefore, the first part of the dissertation involves exploration of speech technologies merged with activity-based and arcade-based games to do pronunciation feedback for Hispanic children. This also involves using linguistic theory to determine computational criteria for intelligibility in speech and computational adaptations to reflect them. We also present results from a 3-month long evaluation of this system. Secondly, a large body of research has shown that the literacy gap between children is well-established before formal schooling begins, and predicts academic performance throughout primary, middle and secondary school. Therefore, in the second part of the dissertation we explore natural interactions for preschoolers that would engage them in game-like activities that involve short follow-up conversations. We explore the design and implementation of a conversational agent called Spot, that acts as a question-answering companion for preschool children. We present a month long study with 20 preschoolers with some insight on the potential, efficiency and usage of such a system. We end with a discussion on computational complexities in building Spot, and rules that it uses to work around speech recognition and natural language understanding errors.
Oracle Performance Tuning

This book is designed to enhance the skills of Oracle DBAs by giving them knowledge and examples of how to improve their system's performance. Readers will learn how to: understand how to use trace files, the alert log file, and event sets to assist with tuning; become familiar with the new features of Oracle9i. ; understand and be able to use utilities and dynamic performance views to assist with tuning; understand how to tune applications using index structures and how to perform SQL statement tuning. ; tune SQL statements efficiently; read alert logs and trace files; tune the shared pool; tune the buffer cache; use multiple buffer caches; tune a multi-threaded server; configure and tune the storage subsystem that Oracle is using, and use Oracle in a SAN environment.
Class-E CMOS RF Power Amplifier Using Voltage-Booster for Mobile Communication System

Efficiency enhancement techniques in switched Class-E power amplifier PA is usually obtained at the expense of the supply voltage. In cascode topology the supply voltage is limited by the breakdown voltage of the common-gate (CG) transistor. So voltage boosting technique is used at the CG to allow Radio Frequency (RF) swing at the gate to boost the biasing voltage above the supply voltage (VDD). This enables us to design the PA such that the cascode transistor has the same maximum drain-gate voltage. Consequently, larger signal swing will occurred at the output before encountering the breakdown. By using this combination, the gate of the NMOS is boosted above VDD and the power consumption is reduced. Simulation results using 0.13 m μ CMOS technology demonstrate 25.8 dBm output power with 38.8% Drain Efficiency at 2.4 GHz.
GEORGIA'S PROGRAM FOR AUTOMATED ACQUISITION AND ANALYSIS OF TRAFFIC COUNT DATA

THE ELECTRONIC COMPUTER PLAYS AN INCREASING ROLE IN THE DEVELOPMENT OF MODERN, LARGE-SCALE TRAFFIC COUNTING AND ANALYSIS PROGRAMS, DUE TO THE DIGITAL COMPOSITION OF TRAFFIC FLOW DATA. GEORGIA IS EXPERIMENTING WITH EXPANDED USE OF THE COMPUTER TO MONITOR AND CONTROL A SYSTEM OF AUTOMATICALLY COLLECTING DATA ACCUMULATED AT REMOTE CONTINUOUS-COUNT STATION LOCATIONS. THE AUTOMATIC TRAFFIC DATA TELEMETRY SYSTEM USES A CENTRALLY LOCATED COMPUTER CONNECTED BY TELEPHONE EQUIPMENT TO AN ELECTRICAL READ-OUT COMPUTER AT EACH REMOTE LOCATION. THESE LOCATIONS ARE AUTOMATICALLY POLLED ACCORDING TO A PREDETERMINED SCHEDULE. THROUGH THE EXECUTION OF A STORED COMPUTER PROGRAM, DATA ARE COLLECTED, EDITED AND RECORDED. AFTER A YEAR OF TESTING, THE SYSTEM IS PROVING TO BE SUPERIOR TO PREVIOUS METHODS OF COLLECTING CONTINUOUS-COUNT DATA. IN CONJUNCTION WITH THE INSTALLATION OF THE TELEMETRY SYSTEM, THE ENTIRE TRAFFIC COUNTING PROGRAM WAS REDESIGNED ACCORDING TO CURRENT STATISTICAL TECHNIQUES. THESE REVISIONS WERE NECESSARY FOR EXTRACTING THE DESIRED ADVANTAGE FROM A TRAFFIC COUNTING PROGRAM ORIENTED TOWARD MAXIMUM UTILIZATION OF THE COMPUTER.
Window Matching using Sparse Templates

This report describes a novel window matching technique. We perform window matching by transforming image data into sparse features, and apply a computationally efficient matching technique in the sparse feature space. The gain in execution time for the matching is roughly 10 times compared to full window matching techniques such as SSD, but the total execution time for the matching also involves an edge filtering step. Since the edge responses may be used for matching of several regions, the proposed matching technique is increasingly advantageous when the number of regions to keep track of increases, and when the size of the search window increases. The technique is used in a real-time ego-motion estimation system in the WITAS project. Ego-motion is estimated by tracking of a set of structure points, i.e. regions that do not have the aperture problem. Comparisons with SSD, with regard to speed and accuracy are made.
An associative approach to task switching

This thesis explores the behaviour of participants taking an associative approach to a task-cueing paradigm. Task-cueing is usually intended to explore controlled processing of task-sets. But small stimulus sets plausibly afford associative learning via simple and conditional discriminations. In six experiments participants were presented with typical task-cueing trials: a cue (coloured shape) followed by a digit (or in Experiment 5 a symbol) requiring one of two responses. In the standard Tasks condition (Monsell Experiment and Experiments 1-3), the participant was instructed to perform either an odd/even or a high/low task dependent on the cue. The second condition was intended to induce associative learning of cue + stimulus-response mappings. In general, the Tasks condition showed a large switch cost that reduced with preparation time, a small, constant congruency effect and a small perturbation when new stimuli were introduced. By contrast the CSR condition showed a small, reliable switch cost that did not reduce with preparation time, a large congruency effect that changed over time and a large perturbation when new stimuli were introduced. These differences may indicate automatic associative processing in the CSR condition and rule-based classification in the Tasks condition. Furthermore, an associative model based on the APECS learning algorithm (McLaren, 1993) provided an account of the CSR data. Experiment 3 showed that participants were able to deliberately change their approach to the experiment from using CSR instructions to using Tasks instructions, and to some extent vice versa. Experiments 4 & 5 explored the cause of the small switch cost in the CSR condition. Consideration of the aspects of the paradigm that produced the switch cost in the APECS model produced predictions, which were tested against behavioural data. Experiment 4 found that the resulting manipulation made participants more likely to induce task-sets. Experiment 5 used random symbols instead of numbers, removing the underlying task-sets. The results of this experiment broadly agreed with the predictions made using APECS. Chapter 6 considers an initial attempt to create a real-time version of APECS. It also finds that an associative model of a different class (AMAN, Harris & Livesey, 2010) can provide an account of some, but not all, of the phenomena found in the CSR condition. This thesis concludes that performance in the Tasks condition is suggestive of the use of cognitive control processes, whilst associatively based responding is available as a basis for performance in the CSR condition.
Identification et localisation des preoccupations fonctionnelles dans du code legataire java

Object oriented applications integrate various functional aspects. These aspects can be scattered everywhere in the code. There are various types of aspects: • aspects which represent business functionalities; • aspects related to non functional requirements or to design concerns such as robustness, distribution, and security. The code representing such aspects can be located in different class hierarchies. Researchers have been interested in the problem of the modularisation of these aspects and many approaches were proposed: oriented programming subjects, oriented programming Aspects and oriented programming view. These approaches offer techniques and tools for designing object oriented applications based on the composition of slices of various aspects. The main benefit of the separation of aspects is supporting reuse and maintenance. Consequently, it is well worth identifying and extracting aspects of legacy object oriented applications. Our work mainly focuses on functional aspects. Assuming that the code of a functional aspect or a feature has a functional cohesion (dependencies between elements), we suggest methods for identifying such features from the code. The idea is to identify, in the absence of any aspect oriented paradigm, the techniques used for implementing a feature in the code. Our approach consists of: identifying techniques used by developers to integrate a feature in the absence of aspect oriented techniques; • characterizing the patterns of these techniques; • and developing tools to identify these patterns. We present two approaches for the identification of the existing features in the object oriented code. The first one identifies various design patterns which integrates these features in the code. The second approach uses the formal concept analysis to identify the recurring features in the code. We experiment our approaches to identify functional features in different open source object oriented applications. The results show the efficiency of our approaches in identifying various functional features in the legacy object oriented, and can some times suggest refactoring. Keywords: Features, reengineerings, legacy object oriented code, refactoring, Galois lattices, Java.
Modeling and analyzing the software process and process breakdowns

In recent years, software process technology has emerged as a promising direction in the study of new methodologies for large-scale software development. Research into software processes has been focused in two directions. (1) Modeling of software processes which proposes formalisms for specifying software processes, called Software Process Models (SPMs); (2) Enactment of SPMs which guides developers through software development. However, such research does not address issues of analyzing, validating, and articulating SPMs that are created by a process formalism and executed during SPM enactment. Users must rely on their own skill and knowledge of process modeling to define a customized SPM. Even worse, to accommodate environmental changes during SPM enactment, they have to update an SPM without any automated support. This makes it very difficult to integrate SPM enactment into a software engineering environment. The Articulator system presented in this dissertation supports modeling and analyzing software processes, and recovering from process breakdown during SPM enactment. The Articulator incorporates an object-oriented representation of software processes and process breakdown using a process meta-model. This meta-model enables the static analysis of SPMs as to help users describe and validate their own software processes. Static analysis of SPMs includes: an SPM definition methodology, mechanisms for checking SPM definitions, and mechanisms for process visualization. This meta-model also enables the dynamic analysis of SPMs to help users estimate and adjust the dynamics of SPM enactment, recover from process breakdown during enactment, and evolve software processes through dynamic changes. Dynamic analysis of SPMs utilizes process simulation and articulation. As such, a number of case studies that utilize process modeling and analysis are discussed which cover both academic and industrial applications. Overall, the long-term goal of this research is to create a process-driven software engineering environment that integrates process modeling, analysis, and enactment with new or existing software tools. Such an environment would provide users with process-guided activity execution, resource management, and tool invocation. In the future, such an experiment can be undertaken to integrate the Articulator system with a commercial software engineering environment. (Copies available exclusively from Micrographics Department, Doheny Library, USC, Los Angeles, CA 90089-0182.)
Gene expression: an example of Statistical analysis of real-time PCR data

Real-time Polymerase Chain Reaction (RT-PCR) is one of the most sensitive and reliably quantitative methods for measuring gene expression levels. Despite this technique is broadly applied in biomedical sciences, data processing and statistical procedures for the analysis of RT-PCR data still present some lacks in reliability. In our work we analyze a data set from a genetic medicine experiment whose aim is to investigate the expression level of 225 genes in 2 types of cells which are possible candidates for tumour acceleration. In this experiment 2 biological replicates for 15 mice were considered, using 3 different experimental platforms. Our goal is to estimate a model which accounts for the complex design of a RT-PCR experiment, thus including sample effect, gene effect, treatment effect, card effect and interactions. The main interest is the interaction between gene and sample. With respect to standard techniques our model allows for a better estimation of the variance with less probability of non significant result in case of true differences.
Genetic Algorithms for Optimization of Wireless Devices

As a result of the evolution in communications technology, the number of wireless nodes is growing much more quickly than the number of wired nodes. Although they offer significant benefit, wireless communications systems pose challenging design problems due to the unpredictable nature of the channel. In spite of these challenges, end users are demanding the benefits of wireless connectivity with quality similar to that of wired connectivity, which requires the devices to be able to adapt to new situations in order to mitigate the detrimental effects of the wireless channel. This dissertation presents a three-layer self-awareness mechanism embedded in the management and control plane architecture of the devices used in a wireless communications network. The proposed mechanism consists of Monitoring, Situational-awareness and Adaptation functions.The dissertation focuses on the implementation of the Adaptation function, which is at the core of the self-awareness mechanism. Using an adaptive genetic algorithm (GA) as the underlying technology, the device is able to learn and apply the acquired knowledge to adapt its operational parameters when facing unknown situations. The self-adaptive capability embedded in the GA allows the evolution parameters to be adjusted according to the current point in the search. The 'knowledge' gained by each species is embodied in the makeup of the genetic information through the chromosomes.The genetic algorithm was tested in a multi-objective scenario that aims to find the weight distribution of a linear antenna array. The goal was to obtain patterns with low sidelobe levels, while maximizing the efficiency of the array. This is achieved by setting a desired effective radiation voltage (ERV). The results of the algorithm, which were compared to those obtained using simulated annealing, show that GA exhibits a more robust performance for different values of ERV. The capability of the algorithm to deal with possible sources of interference was also tested. The patterns obtained in this case showed attenuations of around 60 dB in the direction of the jammers, while maintaining the desired ERV value. While previous approaches to this problem have dealt with different issues, this is the first reported system that optimizes these parameters simultaneously.
Accès et Possession: Deux modalités d'expérience de consommation Le cas des visiteurs d'exposition et des collectionneurs d'œuvres d'art contemporain

Cette recherche propose un modele theorique qui distingue deux modalites d'experience de consommation appliquee au domaine de l'oeuvre d'art contemporain: a travers la possession d'une part, a travers l'acces a l'experience sans possession d'autre part, ainsi qu'une analyse des deux categories de consommateurs etudiees: les visiteurs et les collectionneurs. Ce modele est fonde a la fois sur des reflexions philosophiques -en ce qui concerne les modes d'existence "avoir ou etre"- et sur les analyses du desir du consommateur avant et apres l'experience de consommation, c'est-a-dire la valeur percue. Les resultats empiriques, a travers deux etudes qualitatives (entretiens profonds et notes personnelles, analyses du contenu et analyses intra-inter textuelles) et deux etudes quantitatives (questionnaires, analyse factorielles et modelisation avec equations structurelles) avec l'echantillon des visiteurs et des collectionneurs d'art contemporain, montrent que le desir du consommateur est different vis-a-vis de l'acces -la visite- et vis-a-vis de la possession. Ainsi la population desire-t-elle davantage d'evasion, de surprise, d'esthetique et de calme par la visite d'exposition d'art contemporain. Les valeurs percues apres la visite sont celles d'evasion, de stimulation et de philanthropie. A l'inverse, la population montre le desir de "garder des liens familiaux" par la possession d'oeuvres d'art contemporain. La valeur percue apres la possession est celle de contentement. Curieusement, les collectionneurs d'oeuvres d'art contemporain ne montrent pas un desir possessif plus fort que les visiteurs. Ils ont, en revanche, un desir philanthropique significativement plus marque alors que les visiteurs, de leur cote, montrent un desir d'intellectualite plus affirme que les collectionneurs.
Parallelizing Audio Feature Extraction Using an Automatically Partitioned Streaming Dataow Language.

We implement several versions of an audio feature extraction algorithm in a streaming data-parallel language, StreamIt. We attempt to use the StreamIt infrastructure for a performance study, but are disappointed by portability problems with StreamIt and a lack of optimizations for our target architectures in the StreamIt compiler; however, in certain cases, the compiler does produce noteworthy uniprocessor results.