<p>System-on-Chip is increasingly built using ASIP(Application  Specific Instruction set Processor) due to the flexibility and efficiency obtained from ASIPs. NoGAP (Novel Generator of Accelerator and Processor framework) is an innovative approach for  ASIP design, which provides the advantage of both ADL (Architecture  Description Language) and HDL (Hardware Description Language) to the  designer.</p><p>For the processors designed using NoGAP, software tools need to be automatically generated, to aid the  designer in programming and verifying the processor. As part of the master thesis work, we have developed two generators namely Assembler generator and Cycle-Accurate Simulator generator for NoGAP using C++. The Assembler generator automatically generates an assembler, which is used to convert the assembly code written by a programmer into relocatable binary code. The Cycle-Accurate Simulator generator automatically generates a cycle-accurate simulator to model the behavior of the designed processor. Both these generators are static, and can be used to generate the tools for any processor created using NoGAP.</p><p>In this report, we have detailed the concepts behind the generators,and the implementation details of the generators. We have listed the results obtained from running assembler and cycle-accurate simulator on a test processor created using NoGAP.</p> / NoGAP

We propose and test a new adaptive conjoint analysis method that draws on recent polyhedral “interior-point” developments in mathematical programming. The method is designed to offer accurate estimates after relatively few questions in problems involving many parameters. Each respondent’s ques-tions are adapted based upon prior answers by that respondent. The method requires computer support but can operate in both Internet and off-line environments with no noticeable delay between questions. We use Monte Carlo simulations to compare the performance of the method against a broad array of relevant benchmarks. While no method dominates in all situations, polyhedral algorithms appear to hold significant potential when (a) metric profile comparisons are more accurate than the self-explicated importance measures used in benchmark methods, (b) when respondent wear out is a concern, and (c) when product development and/or marketing teams wish to screen many features quickly. We also test hybrid methods that combine polyhedral algorithms with existing conjoint analysis methods. We close with suggestions on how polyhedral methods can be used to address other marketing problems. / Sloan School of Management and the Center for Innovation in Product Development at MIT

This thesis develops models for accurate prediction of price changes on electronic stock exchanges by utilizing autoregressive and logistic methods. Prices on these electronic stock exchanges, also called ECNs, are solely determined by where orders have been placed into the order book, unlike traditional stock exchanges where prices are determined by an expert market maker. Identifying the significant variables and formulating the models will provide critical insight into the dynamics of prices on ECNs. Whereas previous research has relied on simulated data to test market strategies, this analysis will utilize actual ECN data. The models recognize patterns of asymmetry and movement of the shares in the order book to formulate accurate probabilities for possible future price changes. On traditional stock exchanges, price changes could only occur as quickly as human beings could enact them. On ECNs, computerized systems place orders on behalf of traders based on their preferences, resulting in price changes that reflect trader activity almost instantaneously. The quickness of this automation on ECNs forces the re-evaluation of commonly held beliefs about stock price dynamics. Previous strategies developed for trading on ECNs have relied mainly on price fluctuations to gain profits. This thesis uses the formulated models to design profitable strategies that use accurate prediction rather than price variability.

This thesis investigated the memory skills of young adults with and without language and learning disabilities (LLD) using the Deese-Roediger-McDermott word recall paradigm (Roediger & McDermott, 1995). Three types of word lists were presented: semantic lists consisted of words that are related to a non-presented critical item (CI) (e.g., bad) in meaning (good, rotten, harmful, worse); phonological lists included words related to the CI in sound (e.g., had, lad, bat, bag); and hybrid lists included words related to the CI in both meaning and sound (e.g., good, lad, rotten, bat). Individuals with diagnoses of LLD were classified as "true LLD" or "compensated LLD" based on language test scores and a discriminating composite score, while those without LLD were considered the "typical language" (TL) group. Hypotheses were made regarding veridical recall and memory intrusions, including intrusions of the non-presented critical item (CI). For veridical recall, the compensated LLD and TL groups were expected to have higher recall accuracy than the true LLD group. As for CI intrusions, two possible outcomes were considered: the true LLD group may recall more CIs due to inability to discriminate between presented and non-presented words (Kirchner & Klatzky, 1985); or they may recall fewer CIs due to difficulties forming traces of the gist of the word list (Weekes et al., 2005). Data from 30 participants (ages 18 to 25) -- 12 true LLD, 8 compensated LLD, and 10 TL -- were included in this thesis. Results indicated that the true LLD group showed a non-significant tendency to have lower recall accuracy scores than the other two groups, and a higher number of CI intrusions. List-type also affected accuracy and CI intrusions, as semantically-related lists increased recall accuracy and hybrid semantic-phonological lists increased CI intrusions. Possible conclusions from these data are presented along with recommendations for future research. / text

This work is on a method for face detection through analysis of photos. Accurate location of faces and point out the faces are implemented. In the first step, we use Cb and Cr channel to find where the skin color parts are on the photo, then remove noise which around the skin parts, finally, use morphology technique to detect face part exactly. Our result shows this approach can detect faces and establish a good technical based for future face recognition.

System-on-Chip is increasingly built using ASIP(Application  Specific Instruction set Processor) due to the flexibility and efficiency obtained from ASIPs. NoGAP (Novel Generator of Accelerator and Processor framework) is an innovative approach for  ASIP design, which provides the advantage of both ADL (Architecture  Description Language) and HDL (Hardware Description Language) to the  designer. For the processors designed using NoGAP, software tools need to be automatically generated, to aid the  designer in programming and verifying the processor. As part of the master thesis work, we have developed two generators namely Assembler generator and Cycle-Accurate Simulator generator for NoGAP using C++. The Assembler generator automatically generates an assembler, which is used to convert the assembly code written by a programmer into relocatable binary code. The Cycle-Accurate Simulator generator automatically generates a cycle-accurate simulator to model the behavior of the designed processor. Both these generators are static, and can be used to generate the tools for any processor created using NoGAP. In this report, we have detailed the concepts behind the generators,and the implementation details of the generators. We have listed the results obtained from running assembler and cycle-accurate simulator on a test processor created using NoGAP. / NoGAP

Dans le contexte des sciences archéologiques, des images tridimensionnelles issues de scanners tomodensitométriques sont segmentées en régions d’intérêt afin d’en faire une analyse. Ces objets virtuels sont souvent utilisés dans le but d’effectuer des mesures précises. Une partie de ces analyses nécessite d’extraire la surface des régions d’intérêt. Cette thèse se place dans ce cadre et vise à améliorer la précision de l’extraction de surface. Nous présentons dans ce document nos contributions : tout d’abord, l’algorithme du HMH pondéré dont l’objectif est de positionner précisément un point à l’interface entre deux matériaux. Appliquée à une extraction de surface, cette méthode pose des problèmes de topologie sur la surface résultante. Nous avons donc proposé deux autres méthodes : la méthode du HMH discret qui permet de raffiner la segmentation d’objet 3D, et la méthode du HMH surfacique qui permet une extraction de surface contrainte garantissant l’obtention d’une surface topologiquement correcte. Il est possible d’enchainer ces deux méthodes sur une image 3D pré-segmentée afin d’obtenir une extraction de surface précise des objets d’intérêt. Ces méthodes ont été évaluées sur des acquisitions simulées d’objets synthétiques et des acquisitions réelles d’artéfacts archéologiques. / In the context of archaeological sciences, 3D images produced by Computer Tomography scanners are segmented into regions of interest corresponding to virtual objects in order to make some scientific analysis. These virtual objects are often used for the purpose of performing accurate measurements. Some of these analysis require extracting the surface of the regions of interest. This PhD falls within this framework and aims to improve the accuracy of surface extraction. We present in this document our contributions : first of all, the weighted HMH algorithm whose objective is to position precisely a point at the interface between two materials. But, applied to surface extraction, this method often leads to topology problems on the resulting surface. So we proposed two other methods : The discrete HMH method which allows to refine the 3D object segmentation, and the surface HMH method which allows a constrained surface extraction ensuring a topologically correct surface. It is possible to link these two methods on a pre-segmented 3D image in order to obtain a precise surface extraction of the objects of interest These methods were evaluated on simulated CT-scan acquisitions of synthetic objects and real acquisitions of archaeological artefacts.

The diploma thesis focuses on programming in the Matlab for the Raspberry Pi 3 platform. For the purpose of the presentation, there are two applications designed for Raspberry Pi that are using available hardware, camera and servos. The first application serves as colour object detecting and accurate tracking by using camera calibration. The second application serves as a face detection and recognition. These applications are implemented by modern methods and knowledge of computer vision. Tracking of the objects and face recognition are verified by an experiment that reveals the accuracy of the used methods.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18223号 / 工博第3815号 / 新制||工||1585(附属図書館) / 31081 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 後藤 仁志, 教授 細田 尚, 准教授 KHAYYER Abbas / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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