Дисертації з теми "Mood detection"

Nous introduisons et développons dans cette thèse un nouveau type de méthodes Volumes Finis d'ordre très élevé pour les systèmes hyperboliques de lois de conservations. Appelée MOOD pour Multidimensional Optimal Order Detection, elle permet de réaliser des simulations très précises en dimensions deux et trois sur maillages non-structurés. La conception d'une telle méthode est rendue délicate par l'apparition de singularités dans la solution (chocs, discontinuités de contact) pour lesquelles des phenomènes parasites (oscillations, création de valeurs non physiques. . . ) sont générés par l'approximation d'ordre élevé. L'originalité de cette thèse réside dans le traitement de ces problèmes. A l'opposé des méthodes classiques qui essaient de contrôler ces phénomènes indésirables par une limitation a priori, nous proposons une approche de traitement a posteriori basée sur une décrémentation locale de l'ordre du schéma. Nous montrons en particulier que ce concept permet très simplement d'obtenir des propriétés qui sont habituellement difficiles à prouver dans le cadre multi-dimensionel non-structuré (préservation de la positité par exemple). La robustesse et la qualité de la méthode MOOD ont été prouvées sur de nombreux tests numériques en 2D et 3D. Une amélioration significative des ressources informatiques (CPU et stockage mémoire) nécessaires à l'obtention de résultats équivalents aux méthodes actuelles a été démontrée
We introduce and develop in this thesis a new type of very high-order Finite Volume methods for hyperbolic systems of conservation laws. This method, named MOOD for Multidimensional Optimal Order Detection, provides very accurate simulations for two- and three-dimensional unstructured meshes. The design of such a method is made delicate by the emergence of solution singularities (shocks, contact discontinuities) for which spurious phenomena (oscillations, non-physical values creation, etc. ) are generated by the high-order approximation. The originality of this work lies in a new treatment for theses problems. Contrary to classical methods which try to control such undesirable phenomena through an a priori limitation, we propose an a posteriori treatment approach based on a local scheme order decrementing. In particular, we show that this concept easily provides properties that are usually difficult to prove in a multidimensional unstructured framework (positivity-preserving for instance). The robustness and quality of the MOOD method have been numerically proved through numerous test cases in 2D and 3D, and a significant reduction of computational resources (CPU and memory storage) needed to get state-of-the-art results has been shown

The primary aim of this research was to examine the influence of temporary mood states on factual and interpersonal skepticism. Based on recent affect-cognition theorising and research on credibility judgment, 7 studies predicted that negative moods increase and positive moods decrease skepticism, because of the information-processing consequences of these affective states. First, three studies examined the influence of mood on factual skepticism toward urban myths and legends (Study 1) and novel and familiar general knowledge claims (Studies 2-3). Contrary to predictions, Study 1 found that sad participants were less skeptical than happy participants towards urban legends, possibly due to the negative valence of the claims. Because the feeling of familiarity has been shown to be an important determinant of truth, Studies 2-3 examined the influence of mood and familiarity on skepticism. Consistent with information processing theories of mood, happy participants were more likely than sad participants to give credence to familiar general knowledge claims (Study 2), even when given explicit feedback about their actual truth or falsity during initial exposure to claims (Study 3). The remainder of this thesis extended these findings to interpersonal judgments. Studies 4-5 found that sad participants were more skeptical of the genuineness of facial expressions of emotion compared to happy participants. Studies 6-7 examined whether sad participants might also show greater lie detection accuracy. In Study 6, happy, sad and neutral-mood participants judged the credibility of targets honestly or deceptively describing their emotional reaction to an affectively-laden film, but no evidence was found of mood induced differences in deception detection accuracy. However, in Study 7, sad participants were more skeptical than happy participants about the veracity of videotaped individuals honestly or deceptively denying their involvement in a mock crime (a theft), and showed greater accuracy at discerning lies from truths. This dissertation contributes to the affect-cognition literature by demonstrating that not only may sad moods lead people to be more skeptical, but they may also confer an advantage at detecting deception. The implications of these findings for everyday credibility judgment and for contemporary theories of affect and cognition are considered.

Peronospora tabacina Adam. is the causal agent of blue mold or downy mildew of tobacco. The pathogen is a fungus-like organism and is a member of the Oomycota. P. tabacina is an obligate parasite restricted to the genus Nicotiana spp. Identification of the pathogen is difficult since symptoms and signs generally occur 6-12 days post inoculation. The spread of the pathogen occurs through aerial long distance dispersal of inoculum and severe epidemics occur yearly in tobacco growing areas of the world. One objective of this work was to develop a real-time Taq Man assay for the detection and quantification of P. tabacina. Optimization of the assay was established at a final concentration of 450nM of primers and 125nM of probe. The assay was useful for detection of the pathogen down to a lower limit of 1fg of DNA. The pathogen could be detected after 4 days post inoculation. The real-time PCR assay was useful for the specific detection of P. tabacina in field samples, artificially inoculated leaves, roots, and systemically infected tobacco seedlings and could be used as a tool for regulatory agencies interested in the detection of the pathogen. A second objective was to examine the genetic structure of the pathogen in North America, Central America, the Caribbean and Europe and determine the direction of migration of the pathogen. The intergenic spacer Igs2 region of the nuclear ribosomal DNA (rDNA) and the Ras-related protein (Ypt1) gene, and the mitochondrial cytochrome c oxidase subunit 2 (cox2 gene) were used. Populations of P. tabacina were characterized by high nuclear diversity, low population division and a possible mixed sexual and asexual reproductive system. Large population size, the mechanism of dispersal, mutation rate and genetic diversity indicate that this pathogen is a high evolutionary risk plant pathogen. An isolation with migration (IM) model was used to study genetic diversity in the U.S./Central America and the Caribbean (CCAM) and the European subpopulations. Results support migration from the CCAM region, Florida and Texas into the northern part of the U.S. including North Carolina. These data validate previous migration reports of the pathogen by the North American Plant Disease Forecasting Center at NCSU. In Europe estimates for the migration of the pathogen from North Central to Western Europe and both these regions to Lebanon support migration reports for the first introductions of the pathogen into Europe. Mitochondrial sequences of P tabacina and Hyaloperonspora parasitica genome were generated using bioinforrmatics approaches and PCR methodology. One quarter of the mitochondrial genome of P. tabacina has been annotated and compared with that of Phytophthora infestans and Hyaloperonospora parasitica. Similarities in direction, arrangement and number of genes and regions have been found. Results from this research will be useful in understanding the evolutionary history of the Oomycetes as well as future population genetics research to investigate how these organisms adapt, survive and attack plants in a changing environment.

Objective: To determine the accuracy and appropriateness of screening measures for detecting low mood and cognitive impairment in acute stroke patients, by determination of their sensitivity, specificity and reliability. Methods: 114 English-speaking acute stroke patients completed a depression screening measure from the Mood Assessment Care Pathway (MACP), a battery of mood assessment measures and the Structured Clinical Interview for DSM-IV Axis 1 Disorders (SCID). Participants without significant physical or language impairment additionally completed the Middlesex Elderly Assessment of Mental State (MEAMS), an oral paradigm of the Trail Making Test (OTMT) and detailed neuropsychological assessment with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Rule Shift Card Test (BADS) and the Verbal Fluency Test (phonemic task). Results: 106 participants completed all of the mood assessment procedures. Sensitivity of the individual MACP measures was generally high for the detection of major and minor depression. Specificity varied widely between the measures ranging from 18% to 85% but was generally within acceptable levels (greater than 60%). A revised version of the MACP was proposed using optimal cut-off scores. The MACP-revised gave 100% sensitivity and 77% specificity for the detection of major depression and 81% sensitivity and 65% specificity for minor depression. Reliability as assessed by the Kappa coefficient was found to be generally low for either version of the MACP and the individual measures. 91 participants were assessed using the MEAMS. Convergent validity of the MEAMS with full assessment measures was not supported (r < .40). Overall, sensitivity of the MEAMS subtests and the overall MEAMS for the detection of impairment in any of the cognitive domains was generally low, except for the overall MEAMS with Immediate and Delayed Memory Impairment. Specificity was generally higher, but there were only two instances where subtests achieved acceptable levels of both sensitivity and specificity. The overall MEAMS failed to achieve acceptable levels of agreement for any of the cognitive domains assessed. 89 participants were assessed using the OTMT. Sensitivity of the OTMT-B for the detection of impairment in any of the cognitive domains was generally low (less than 60%). Specificity was generally higher (greater than 76%), but there were no instances where acceptable levels of sensitivity and specificity were both achieved. Agreement with full assessment measures was generally poor for any of the cognitive domains assessed. Conclusions: The overall MACP-revised was an acceptably valid screening battery for the assessment of major and minor depression in acute stroke patients and demonstrated a useful way of compiling mood screening batteries which allow the assessment of mood impairment for all stroke patients. Neither the MEAMS nor the OTMT were recommended as a measure for screening for cognitive problems after a stroke due to their low sensitivity. However, further investigation of the psychometric properties of the RBANS was indicated, as the current findings suggest that it can be successfully used to assess acute stroke patients for cognitive impairment.

Minimoons, Earth’s temporarily-captured orbiters, are excellent candidates for asteroidmining technology demonstrations and general asteroid studies because of their relativelylong stay in the vicinity of Earth. In this thesis, microsatellite compatible surveillancetechnologies are discussed and the suitability of various locations in the Earth-Moon systemfor minimoon surveillance is examined. This is done to acquire knowledge on whichtype of an orbit a minimoon-surveying-microsatellite could be placed on.The instantaneous visible fraction of the minimoon steady-state population is the figureof merit when comparing surveillance systems and locations. The visible fraction is estimatedby simulating the distribution of visible minimoons in the sky-plane. The objectsin the simulated sky-plane are synthetic minimoons, which are generated in large numbersaccording to the geocentric 6-dimensional-residence-time-distribution of minimoons, andthus, the bin values of the sky-plane distribution can be thought of as instantaneous probabilitiesfor containing a detectable minimoon within certain ecliptic latitude-longituderange.The visible fractions are estimated for various locations with given surveillance systemperformance. Multiple microsatellite compatible surveillance technology configurationsare examined as well as the e↵ect of limiting magnitude and maximum angular velocity.Minimoons are faint and fast moving objects and thus the use of synthetic tracking algorithmis beneficial and considered. Only visual band surveillance systems with aperturesizes less than 0.30 m and minimoons with diameter sizes larger than 0.50 m are consideredin the simulations.
Minimånar, jordens temporärt fångade satelliter, är utmärkta kandidater för demonstra-tioner av asteroidbrytningteknologi och för allmänna asteroidstudier på grund av deras relativt långa vistelse i närheten av jorden. I den här avhandlingen, diskuteras mikrosatellit kompatibla övervakningsteknologier och därtill undersökes lämpligheten av olika platser i jord-måne-systemet för övervakning av minimånar. Det här görs för att ska↵a kunskap om vilken typ av omloppsbana en mikrosatellit för minimåneövervakning kunde placeras på.Den momentana synliga fraktionen av den jämviktstillstånd minimånepopulationen är den merit som används vid jämförelse av övervakningssystem och platser i rymden. Den synliga fraktionen uppskattas genom att simulera fördelningen av synliga minimånar i skyplanet. Föremålen i det simulerade skyplanet är syntetiska minimånar, vilka genereras i stort antal enligt den geocentriska 6-dimensionella-uppehållstid-distributionen av minimånarna, och sålunda kan värdena i den diskretiserade skyplanfördelningen betraktas som momentana sannolikheter för att innehålla en observerbar minimåne inom det specifiserade ecliptiska latitudinella-longitudinella området.De synliga fraktionerna beräknas för olika platser med det givna övervakningssystemets parametrar. Flera mikrosatellit-kompatibla övervakningsteknologikonfigurationer undersöks, såväl som e↵ekterna av begränsande magnitud och maximal vinkelhastighet. Minimånar är dunkla och snabba rörliga föremål, och således är användningen av synthetic tracking fördelaktig och övervägd. Endast övervakningssystem som fungerar i visuellt bandmed en bländarstorlek mindre än 0,30 m och minimånar med en diameter större än 0,50m beaktas i simuleringarna.

For 500 years transient light phenomena (TLP) have been observed on the lunar surface by ground-based observers. The actual physical reason for most of these events is today still unknown. Current plans of NASA and SpaceX to send astronauts back to the Moon and already successful deep-space CubeSat mission will allow in the future research nanosatellite missions to the cislunar space. This thesis presents a new hardware and software concept for a future payload on such a nanosatellite. The main task was to develop and implement a high-performance image processing algorithm which task is to detect short brightening flashes on the lunar surface. Based on a review of historic reported phenomena, possible explanation theories for these phenomena and currently active and planed ground- or space-based observatories possible reference scenarios were analyzed. From the presented scenarios one, the detection of brightening events was chosen and requirements for this scenario stated. Afterwards, possible detectors, processing computers and image processing algorithms were researched and compared regarding the specified requirements. This analysis of available algorithm was used to develop a new high-performance detection algorithm to detect transient brightening events on the Moon. The implementation of this algorithm running on the processor and the internal GPU of a MacMini achieved a framerate of 55 FPS by processing images with a resolution of 4.2 megapixel. Its functionality and performance was verified on the remote telescope operated by the Chair of Space Technology of the University of Würzburg. Furthermore, the developed algorithm was also successfully ported on the Nvidia Jetson Nano and its performance compared with a FPGA based image processing algorithm. The results were used to chose a FPGA as the main processing computer of the payload. This concept uses two backside illuminated CMOS image sensor connected to a single FPGA. On the FPGA the developed image processing algorithm should be implemented. Further work is required to realize the proposed concept in building the actual hardware and porting the developed algorithm onto this platform.

The first transiting planetesimal orbiting a white dwarf was recently detected in K2 data of WD 1145+017 and has been followed up intensively. The multiple, long and variable transits suggest the transiting objects are dust clouds, probably produced by a disintegrating asteroid. In addition, the system contains circumstellar gas, evident by broad absorption lines, mostly in the u' band, and a dust disc, indicated by an infrared excess. Here we present the first detection of a change in colour of WD 1145+017 during transits, using simultaneous multiband fast-photometry ULTRACAM measurements over the u'g'r'i' bands. The observations reveal what appears to be 'bluing' during transits; transits are deeper in the redder bands, with a u' - r' colour difference of up to similar to-0.05 mag. We explore various possible explanations for the bluing, including limb darkening or peculiar dust properties. 'Spectral' photometry obtained by integrating over bandpasses in the spectroscopic data in and out of transit, compared to the photometric data, shows that the observed colour difference is most likely the result of reduced circumstellar absorption in the spectrum during transits. This indicates that the transiting objects and the gas share the same line of sight and that the gas covers the white dwarf only partially, as would be expected if the gas, the transiting debris and the dust emitting the infrared excess are part of the same general disc structure (although possibly at different radii). In addition, we present the results of a week-long monitoring campaign of the system using a global network of telescopes.

Manufacturers of cast metal parts are interested in the development of a feedback control system for use with the Precision Sand-Casting (PSC) process. As industry demands the ability to cast more complex geometries, there are a variety of challenges that engineers have to address. Certain characteristics of the mold, such as thick-to-thin transitions, extensive horizontal or flat surfaces, and sharp corners increase the likelihood of generating defective casts due to the turbulent metal-flow during fills. Consequently, it is critical that turbulent flow behavior within the mold be minimized as much as possible. One way to enhance the quality of the fill process is to adjust the flow rate of the molten metal as it fills these critical regions of the mold. Existing systems attempt to predict the position of the metal level based on elapsed time from the beginning of the fill stage. Unfortunately, variability in several aspects of the fill process makes it very difficult to consistently predict the position of the metal front. A better approach would be to embed a sensor that can detect the melt through a lift-off distance and determine the position of the metal-front. The information from this sensor can then be used to adjust the flow rate of the aluminum as the mold is filled. This thesis presents the design of a novel non-invasive sensor monitoring system. When deployed on the factory floor, the sensing system will provide all necessary information to allow process engineers to adjust the metal flow-rate within the mold and thereby reduce the amount of scrap being produced. Moreover, the system will exhibit additional value in the research and development of future mold designs.

Septins are a highly conserved family of eukaryotic proteins having significant homology within and among species. In the budding yeast, Saccharomyces cerevisiae, a septin-based hierarchy of proteins is required to localize chitin in the bud neck prior to septum formation. However, this process has not been clarified in a filamentous, conidiogenous fungus capable of yeast growth, such as Wangiella dermatitidis, a polymorphic agent of human phaeohyphomycosis. Prior studies of this melanized mold showed that some chitin synthase mutants (wdchsa??) have defects in yeast septum formation, suggesting that the septins of W. dermatitidis might functionally associate with some of its chitin synthases (WdChsp). To test this hypothesis, four vegetative septin homologs of S. cerevisiae were cloned from W. dermatitidis and designated WdCDC3, WdCDC10, WdCDC11, and WdCDC12. Of the four, only WdCDC3 functionally complemented completely a strain of S. cerevisiae with a ts mutation in the corresponding gene, although WdCDC12 did so partially. Functional characterizations by mutagenesis of the four W. dermatitidis septin genes revealed that resulting mutants (wdcdca??) each had unique defects in yeast growth and morphology, indicating that each septin carried out a distinct function. Furthermore, when a wdcdc10a?? mutation was introduced into five different wdchsa?? strains, weak genetic interactions were detected between WdCDC10 and WdCHS3 and WdCHS4, and a strong interaction between WdCDC10 and WdCHS5. Cytological studies showed that WdChs5p was mislocalized in some septin mutants, including wdcdc10a??. These results confirmed that in W. dermatitidis septins are important for proper cellular morphogenesis, cytokinesis, and especially septum formation through associations with some chitin synthases.

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The white mold disease, caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary, responsible for large losses in soybean (Glycine max (L.) Merrill). The pathogen has more than 400 hosts and presents the formation of a resistance structure (sclerotia), difficulting the disease control, thus increasing the importance of the pathogen in Brazilian agriculture. The seeds are the main spreading disease means, a quickly and correct presence detection of the pathogen is important to control the white mold, especially for non-infested areas by the pathogen. In this study, 57 S. sclerotiorum isolates were morphological and pathologically characterized to assess variations within the specie. Also was developed a method to detect the pathogen directly from seed-soak liquor of infected soybean seeds, through PCR. The proposed method was compared to the traditional recommended methods. The pathogen isolates showed some morphological variations among themselves, as the number and weight of the formed sclerotia. Pathologically, were observed two and seven pathogenic levels second, respectively, the soybean inoculation on the stem and on the detached trifoliate leaves. By the detection method, it was possible to detect one seed artificially contaminated in the sample with 400 total seeds. In naturally contaminated seeds, was possible to detected the pathogen presence in a sample that, according to the method of incubation on paper roll and on Neon-S medium, respectively, presented 1 and 3 seeds contaminated in four hundred seeds. The proposed methodology is promising for the detection of S. sclerotiorum, however, requires optimization because many false negative results were obtained, mainly due to substances released by the seeds that inhibited the PCR reaction. The use of filter in the samples has presented as a possible tool to overcome the PCR inhibitors. For the optimization of the method, increase the size of seed samples, use of filters, others techniques such as nested PCR, Real-Time PCR and DNA probes can help overcome these difficulties.
O Mofo branco, doença causada pelo fungo Sclerotinia sclerotiorum (Lib.) de Bary, vem causando grandes prejuízos na cultura da soja (Glycine max (L.) Merrill) e, por apresentar mais de 400 hospedeiros e a formação de uma estrutura de resistência (escleródios), o seu controle torna-se difícil, aumentando a importância do patógeno para a agricultura brasileira. As sementes são o principal meio de disseminação da doença, detectar rápido e corretamente a presença do patógeno nas mesmas é importante no controle do Mofo branco, principalmente, para não infestar áreas isentas do patógeno. No presente trabalho, 57 isolados de S. sclerotiorum foram caracterizados morfológica e patologicamente para avaliar variações dentro da espécie. Também se desenvolveu uma metodologia de detecção do patógeno em sementes de soja embebidas, através de PCR diretamente do líquido de embebição das mesmas. Comparou-se a metodologia proposta com as tradicionais recomendadas para o patógeno. Os isolados do patógeno apresentaram algumas variações morfológicas entre si, como quantidade e peso dos escleródios formados. Patologicamente, foram verificados dois e sete níveis de patogenicidade segundo, respectivamente, a inoculação dos isolados na haste e em trifólios destacados de plantas de soja. Diretamente a partir do líquido de embebição das sementes, foi possível detectar uma semente artificialmente contaminada em 400 sementes totais. Em sementes naturalmente contaminadas, detectou-se a presença do patógeno em amostra que, segundo o método de incubação em rolo de papel e em Neon-S apresentava, respectivamente, 1 e 3 sementes contaminadas em quatrocentas totais. A metodologia proposta é promissora para a detecção de S. sclerotiorum, no entanto, necessita de otimização, pois muitos resultados falsos-negativos foram obtidos, principalmente devido a substâncias liberadas pelas próprias sementes que inibiram a reação de PCR. A utilização de um filtro nas amostras apresentou-se como uma possível ferramenta para driblar os inibidores de PCR. Para a otimização do método, técnicas como Nested-PCR, Real-Time PCR, utilização de sondas de DNA, aumento no tamanho de amostras de sementes e a utilização dos filtros podem ajudar a superar essas dificuldades.

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Sclerotinia sclerotiorum infect many plants, including crops of great economic importance as soybeans (Glycine max) and oilseed rape (Brassica sp.), responsible for great losses. The plant disease control is the most important practical objective of plant pathology, but the correct and rapid diagnosis are essential to define strategies for the diseases management. Molecular techniques are able to amplify specific fragments from small amounts of genetic material and powerful tools widely used in various areas, including the phytopathological diagnosis. Several techniques have been studied and designed for the amplification of nucleic acids, including the LAMP (Loop-mediated isothermal amplification), which has high specificity, sensitivity and is fast. The aim of this study was to develop and optimize a specific molecular test for S. sclerotiorum by LAMP, as well as its validation to oilseed pare and soybean seeds samples. A set of six primers was designed and evaluated for S. sclerotiorum sensitivity and specificity detection. The composition of the LAMP reaction was enhanced for real-time (SS-qLAMP) and direct analysis (SS-cLAMP). The DNA from 57 isolates of S. sclerotiorum, DNA from several other plant pathogens and DNA from different cultures was tested. The DNA of all isolates of S. sclerotiorum were detected but no the other DNA samples. When testing the limit of detection of reactions, a single copy detections was suggested. By SS-qLAMP two curves were generated which can be used to estimate the amount of mycelium and DNA of S. sclerotiorum present in the samples analyzed. Bothe developed tests (SS-qLAMP and SS-cLAMP) can be applied to several purposes, such as detection of the pathogen in plant, spore traps, soil and seeds samples. Using seed samples with different contamination level, the test was optimized for canola and soybean seeds, SS-qLAMP(Canola) and SS-qLAMP(Soybean), respectively, detecting the presence of the pathogen in samples up to 0.13% and 0.03% naturally contaminated for canola and soybean, respectively, and was able to detect contamination in samples not contaminated according incubation-based methods. The time require for the test was 4h and 30 minutes and 2 hours and 50 minutes for canola and soybeans, respectively, with no needs of large space for samples incubation, specialized analysts and able to analyzed many samples simultaneously. The proposed method SS-qLAMP was well-validated according the ISTA (International Seed Testing Association) rules to oilseed-rape and soybean seed samples. x
Sclerotinia sclerotiorum é um fungo que pode atacar diversas espécies vegetais, incluído culturas de grande importância econômica como soja (Glycine max) e canola (Brassica sp.), causando grandes prejuízos para as mesmas. O controle de doenças de plantas é o mais importante objetivo prático da Fitopatologia, mas, a correta e rápida diagnose da doença são pré-requisitos indispensáveis para definir as medidas para o manejo das mesmas. Técnicas moleculares capazes de amplificar fragmentos específicos a partir de pequenas quantidades de material genético são poderosas ferramentas amplamente utilizadas em diversas áreas, incluindo o diagnóstico fitopatológico. Diversas técnicas têm sido estudadas e criadas para a amplificação de ácidos nucleicos, entre elas a LAMP (Amplificação isotérmica mediada por “loops”), que apresenta alta especificidade, sensibilidade e é rápida. O objetivo do presente estudo foi desenvolver e otimizar um teste molecular específico para S. sclerotiorum a base de LAMP, com obtenção de resultados em tempo real e quantitativos (qLAMP) e análise visual direta de resultados (cLAMP), assim como a validação do mesmo para ser utilizado na análise de amostras de sementes de canola e soja. Um conjunto de seis primers foi desenhado e avaliado quanto a sensibilidade e especificidade de detecção de S. sclerotiorum. A composição da reação de LAMP foi otimizada quanto a concentração de diversos componentes tanto para a análise em tempo real como direta, compondo, respectivamente as reações de SS-qLAMP e SS-cLAMP, conforme necessário. Testou-se o DNA de 57 isolados de S. sclerotiorum, o DNA de diversos outros fitopatógenos e o DNA de diversas culturas. O DNA de todos os isolados de S. sclerotiorum foram detectados mas não o de outros fitopatógenos e de plantas. Ao testar o limite de detecção das reações, não houve um limite de detecção, sugerindo que a presença de qualquer molécula de DNA alvo seria detectada. Pelo método quantitativo foi possível gerar duas curvas pelas quais pode-se estimar a quantidade de micélio e de DNA de S. sclerotiorum presente na amostra analisada. Desenvolveu-se um teste específico para S. sclerotiorum a base de LAMP, denominada SS-LAMP que pode ser aplicado em diversos casos, como a detecção do patógeno em amostras de plantas, armadilhas de esporos, de solo e sementes. Otimizou-se o teste SS-LAMP para sementes de canola e soja, SS-qLAMP(Canola) e SS-qLAMP(Soja), respectivamente, detectando-se a presença do patógeno em amostras com até 0,13% e 0,03% de contaminação natural, para canola e soja, respectivamente, além da detecção em amostras que os métodos tradicionais não detectaram. O tempo total do método foi de 4h e 30 minutos para canola e 2h e 50 minutos para soja, sem a necessidade de amplo espaço para incubação das amostras, pessoal especializado para análise e com a possibilidade de diversas amostras serem analisadas concomitantemente. Assim validou-se o método proposto SS-qLAMP(Soja) segundo as regras da ISTA (International Seed Testing Association – Associação Internacional de Análise de Sementes).

Abstract: The interest of major space agencies in the world for vision sensors in their mission designs has been increasing over the years. Indeed, cameras offer an efficient solution to address the ever-increasing requirements in performance. In addition, these sensors are multipurpose, lightweight, proven and a low-cost technology. Several researchers in vision sensing for space application currently focuse on the navigation system for autonomous pin-point planetary landing and for sample and return missions to small bodies. In fact, without a Global Positioning System (GPS) or radio beacon around celestial bodies, high-accuracy navigation around them is a complex task. Most of the navigation systems are based only on accurate initialization of the states and on the integration of the acceleration and the angular rate measurements from an Inertial Measurement Unit (IMU). This strategy can track very accurately sudden motions of short duration, but their estimate diverges in time and leads normally to high landing error. In order to improve navigation accuracy, many authors have proposed to fuse those IMU measurements with vision measurements using state estimators, such as Kalman filters. The first proposed vision-based navigation approach relies on feature tracking between sequences of images taken in real time during orbiting and/or landing operations. In that case, image features are image pixels that have a high probability of being recognized between images taken from different camera locations. By detecting and tracking these features through a sequence of images, the relative motion of the spacecraft can be determined. This technique, referred to as Terrain-Relative Relative Navigation (TRRN), relies on relatively simple, robust and well-developed image processing techniques. It allows the determination of the relative motion (velocity) of the spacecraft. Despite the fact that this technology has been demonstrated with space qualified hardware, its gain in accuracy remains limited since the spacecraft absolute position is not observable from the vision measurements. The vision-based navigation techniques currently studied consist in identifying features and in mapping them into an on-board cartographic database indexed by an absolute coordinate system, thereby providing absolute position determination. This technique, referred to as Terrain-Relative Absolute Navigation (TRAN), relies on very complex Image Processing Software (IPS) having an obvious lack of robustness. In fact, these software depend often on the spacecraft attitude and position, they are sensitive to illumination conditions (the elevation and azimuth of the Sun when the geo-referenced database is built must be similar to the ones present during mission), they are greatly influenced by the image noise and finally they hardly manage multiple varieties of terrain seen during the same mission (the spacecraft can fly over plain zone as well as mountainous regions, the images may contain old craters with noisy rims as well as young crater with clean rims and so on). At this moment, no real-time hardware-in-the-loop experiment has been conducted to demonstrate the applicability of this technology to space mission. The main objective of the current study is to develop autonomous vision-based navigation algorithms that provide absolute position and surface-relative velocity during the proximity operations of a planetary mission (orbiting phase and landing phase) using a combined approach of TRRN and TRAN technologies. The contributions of the study are: (1) reference mission definition, (2) advancements in the TRAN theory (image processing as well as state estimation) and (3) practical implementation of vision-based navigation.
Résumé: L’intérêt des principales agences spatiales envers les technologies basées sur la vision artificielle ne cesse de croître. En effet, les caméras offrent une solution efficace pour répondre aux exigences de performance, toujours plus élevées, des missions spatiales. De surcroît, ces capteurs sont multi-usages, légers, éprouvés et peu coûteux. Plusieurs chercheurs dans le domaine de la vision artificielle se concentrent actuellement sur les systèmes autonomes pour l’atterrissage de précision sur des planètes et sur les missions d’échantillonnage sur des astéroïdes. En effet, sans système de positionnement global « Global Positioning System (GPS) » ou de balises radio autour de ces corps célestes, la navigation de précision est une tâche très complexe. La plupart des systèmes de navigation sont basés seulement sur l’intégration des mesures provenant d’une centrale inertielle. Cette stratégie peut être utilisée pour suivre les mouvements du véhicule spatial seulement sur une courte durée, car les données estimées divergent rapidement. Dans le but d’améliorer la précision de la navigation, plusieurs auteurs ont proposé de fusionner les mesures provenant de la centrale inertielle avec des mesures d’images du terrain. Les premiers algorithmes de navigation utilisant l’imagerie du terrain qui ont été proposés reposent sur l’extraction et le suivi de traits caractéristiques dans une séquence d’images prises en temps réel pendant les phases d’orbite et/ou d’atterrissage de la mission. Dans ce cas, les traits caractéristiques de l’image correspondent à des pixels ayant une forte probabilité d’être reconnus entre des images prises avec différentes positions de caméra. En détectant et en suivant ces traits caractéristiques, le déplacement relatif du véhicule (la vitesse) peut être déterminé. Ces techniques, nommées navigation relative, utilisent des algorithmes de traitement d’images robustes, faciles à implémenter et bien développés. Bien que cette technologie a été éprouvée sur du matériel de qualité spatiale, le gain en précision demeure limité étant donné que la position absolue du véhicule n’est pas observable dans les mesures extraites de l’image. Les techniques de navigation basées sur la vision artificielle actuellement étudiées consistent à identifier des traits caractéristiques dans l’image pour les apparier avec ceux contenus dans une base de données géo-référencées de manière à fournir une mesure de position absolue au filtre de navigation. Cependant, cette technique, nommée navigation absolue, implique l’utilisation d’algorithmes de traitement d’images très complexes souffrant pour le moment des problèmes de robustesse. En effet, ces algorithmes dépendent souvent de la position et de l’attitude du véhicule. Ils sont très sensibles aux conditions d’illuminations (l’élévation et l’azimut du Soleil présents lorsque la base de données géo-référencée est construite doit être similaire à ceux observés pendant la mission). Ils sont grandement influencés par le bruit dans l’image et enfin ils supportent mal les multiples variétés de terrain rencontrées pendant la même mission (le véhicule peut survoler autant des zones de plaine que des régions montagneuses, les images peuvent contenir des vieux cratères avec des contours flous aussi bien que des cratères jeunes avec des contours bien définis, etc.). De plus, actuellement, aucune expérimentation en temps réel et sur du matériel de qualité spatiale n’a été réalisée pour démontrer l’applicabilité de cette technologie pour les missions spatiales. Par conséquent, l’objectif principal de ce projet de recherche est de développer un système de navigation autonome par imagerie du terrain qui fournit la position absolue et la vitesse relative au terrain d’un véhicule spatial pendant les opérations à basse altitude sur une planète. Les contributions de ce travail sont : (1) la définition d’une mission de référence, (2) l’avancement de la théorie de la navigation par imagerie du terrain (algorithmes de traitement d’images et estimation d’états) et (3) implémentation pratique de cette technologie.

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Esta dissertação apresenta uma estratégia de controle para sistemas de geração fotovoltaicos, de único estágio, trifásicos, conectados à rede elétrica de distribuição. São desenvolvidos modelos matemáticos para representar as características dinâmicas dos painéis fotovoltaicos, do conversor fonte de tensão (VSC -“Voltage Source Converter”) e da rede de distribuição. A modelagem do sistema de geração disperso (SGD) é feita no sistema de coordenadas síncrono (dq), fornecendo um sistema de equações diferenciais que pode ser usado para descrever o comportamento dinâmico do sistema quando as tensões da rede estão equilibradas ou desequilibradas. O conversor é controlado no modo de corrente, através da estratégia de modulação vetorial (Space Vector Modulation - SVM). São projetadas duas malhas de controle em cascata para controlar o conversor estático. A malha interna controla a corrente injetada na rede enquanto que a externa controla a tensão no barramento CC do conversor. O controle da tensão CC permite rastrear o ponto de máxima potência do painel PV além de controlar a quantidade de potência ativa injetada na rede CA. Um método ativo de detecção de ilhamento baseado na injeção de corrente de sequência negativa é incorporado ao sistema de controle. Resultados de simulações digitais obtidos com o programa ATP (Alternative Transient Program ) são utilizados para validar os modelos matemáticos e as estratégias de controle. Finalmente, um protótipo experimental de pequena escala é montado em laboratório. Todo o sistema de controle do protótipo experimental foi implementado no DSP TMS320F28212. Os resultados obtidos demonstram o funcionamento do sistema e podem ser usados para validar a estratégia de controle utilizada.
This dissertation presents a control strategy for a single-stage, three-phase, photovoltaic systems to be connected to a distribution network. Mathematical models are developed to represent the dynamic characteristics of the photovoltaic panels, the voltage-source converter (VSC) and the distribution network. The modeling of the dispersed generation system (DGS) is done in the synchronous reference frame (dq), providing a system of differential equations that describes the dynamic behavior of the system when the network voltages are balanced or unbalanced. The converter is controlled in current mode through the space vector modulation (SVM) strategy. Two control loops are designed to control the static converter. The inner loop controls the injected current into the network while the external loop controls the converter DC bus voltage. The DC voltage regulator allows to track the PV maximum power point and to control the active power injected into the AC grid. An active islanding detection method based on negative-sequence current injection is incorporated into the control system. Digital simulations results obtained with Alternative Transients Program (ATP) is used to validate the mathematical models and the control strategies. Finally, a small-scale experimental prototype is implemented in the laboratory. The whole control system of the experimental prototype was programmed in DSP TMS320F2812 of Texas Instruments. The results demonstrate that the operation of the system can be used to validate the applied control strategy.

碩士
國立成功大學
資訊工程學系
104
In mental health disorder, Unipolar Depression (UD) and Bipolar Disorder (BD) have become the most common mental illness. A large portion of the BD patients is misdiagnosed as UD on initial presentation. As speech is the most natural way to express emotion, this thesis focus on tracking emotion profile of speech to build a short-term mood disorder detector for diagnosis assistance. This thesis proposes an approach to short-term detection of mood disorder based on the elicited speech responses. At first, eliciting emotional videos are used to elicit the patients’ emotions. Speech responses of the patients are collected through the interviews by a clinician after watching each of six emotional video clips. As Deep Scattering Spectrum (DSS) can obtain more detailed energy distributions in frequency domain than the Low Level Descriptors (LLDs), this study combines LLDs and DSS as the speech features. A domain adaptation method combining hierarchical spectral clustering (HSC) algorithm and denoising autoencoder is proposed to adapt the emotion database to the mood disorder database to alleviate the data bias problem in the emotion space. The autoencoders is then adopted to extract the bottleneck features for dimensionality reduction. Hidden Markov model (HMM) is applied to characterize the trajectory of emotion profiles. Finally, HMM-based verification is used to improve the detection performance of mood disorders. This study collected the elicited emotional speech data from 15 BDs, 15 UDs and 15 healthy controls. Five-fold cross validation scheme was employed for evaluation. Experimental results show that the proposed method achieved a detection accuracy of 73.33%, improving by 18%, compared to the SVM-based method. In the future, the patient’s personality, response context and facial images can be considered for obtaining a better performance.

碩士
國立成功大學
資訊工程學系
104
In a rapidly changing social environment, emotions are more and more difficult to handle for human beings. Sometimes people do not even know that they have negative emotions. As a result, the accumulation of negative emotions become a mental illness. Thus, it is essential to develop an emotion tracking system to help users manage their emotions. In current study, an extended subjective self-report method is generally used for measuring emotions. Even though it is commonly accepted that the emotion perceived by the listener is close to the intended emotion conveyed by the speaker, several research indicated that there still remains a mismatch between them. In addition, the individuals with different personalities generally have different expressed emotions. Based on this investigation, this thesis proposes an emotion conversion model which characterizes the relationship between the perceived emotion and the expressed emotion of the user for a specific personality. Emotion conversion from perceived to expressed emotions is applied based on the personality traits of the user. This thesis considers mood swing as a long-term accumulation of emotions. A database containing user’s long-term speech data and mood annotation is collected. This database is used for constructing the temporal relationships between emotion and mood. In order to reflect the real mood from people, an SVM-based emotion model is developed to generate multiple probabilistic class labels. Moreover, a Gaussian distribution is built to generate noisy data since there is a difference between expressed and perceived emotions. The input is the expressed emotion value contaminated by the generated noise and the target is the expressed emotion for denoising autoencoder (DAE) training. Finally, for modeling the temporal fluctuation of emotions, a long short-term memory (LSTM)-based mood model is constructed for mood detection. In mood detection experiments, the mood database was provided by 10 participants. There were 104 positive moods and 96 negative moods. Leave-one-speaker-out cross validation was employed for evaluation. Experimental results show that the proposed method achieved a detection accuracy of 64.5%, which improves 5%, comparing to the HMM-based method. In the future, the tracking of the dialog content and blog of the users can be applied to obtain a better performance.

碩士
國立臺灣大學
資訊工程學研究所
93
Movie is one of the most important entertainments in the history of mankind. With the development of content digitalization, more and more movie viewers would like to choose parts of movies according to their favorites. But as interests of viewers are various, it''s difficult to deal with their requirements by only one principle. In this thesis, we develop modules for detecting video tempo and music mood, and present three applications about movie analysis. Music mood is categorized to high-tension and low-tension using timbre, intensity and rhythm, and each shot of video is given a tempo value by shot length and motion activity. After applying these two modules we recognize mood of music and develop three applications: music event detection, emotional event detection, and Original Sound Tracks (OST) visualization. Subjective tests show that the mean opinion scores of the experimental results are good.

碩士
國立交通大學
資訊管理研究所
99
Nowadays, there is much music in our daily life, but it is hard to find suitable ones as we would like to make use of them. For example, if we try to find romantic music for wedding, relieved music for therapy, where we can find it? Moreover, music mood only is judged by human experts in present. Although these experts develop many digital music libraries websites such as Allmusic.com to store music by moods, there has not been any efficiency system to classify music mood in automatic classifier so far. In fact, music is everywhere, not only human produces them but also Mother Nature generates them as well. Therefore, how can we deal with such great amount of music information? In this thesis, we regard predicting music mood as our goal. With the digital music library - Allmusic.com already classified music mood, we extracted English song lyrics in it. We calculate every token’s Log Likelihood Ratio after tokenization, removing stop-words and porter stemming. Further, we select out feature tokens as our classifying rule. Finally, we put them into LibSVM to build model, which tries to predict music mood of new added in data. Findings show that the accuracy only depends on lyrics is not good enough, only 50% predicting correct. Besides, we find mood Happy, Fiery and Drama are easy to detect, it perhaps that their emotional terms are clear. On the other hand, mood Wry, Literate, Ironic and Silly are hard to detect.

碩士
國立成功大學
資訊工程學系
103
Facial expression is a direct and natural way for affective expression. In the field of affective computing, recognition of facial expression is an important and popular research topic. In mood disorder diagnosis, a high percentage of bipolar disorder (BD) patients are initially misdiagnosed as having unipolar depression (UD). This misdiagnosis carries significant negative consequences for the treatment of the BD patients. Therefore, it is crucial to establish an accurate distinction between BD and UD in order to make an accurate and early diagnosis, leading to improvements in treatment and course of illness. The research goal of this thesis is to collect the facial expression of the patients with mood disorder when they were watching video clips for emotion elicitation. The features extracted from the elicited facial expressions are used for the detection of BD and UD. This thesis focuses on detecting the difference in facial expressions among the BD patients, UD patients and healthy people responding to emotional stimuli. In this study, first, the subjects are elicited by emotional video clips, and the videos with facial expression of the subjects are recorded. The corresponding facial action unit (AU) profiles are obtained using the support vector machines (SVMs) as the facial features. The Modulation Spectrum (MS) characterizing the fluctuation of AU profile sequence over a video segment are further extracted. Finally, a two-layer SVM is constructed for mood disorder detection based on the extracted MSs of the elicited facial expressions in the video segments of the subject. In order to evaluate the proposed method, the video segments from 24 subjects, 8 for BD, 8 for UD and the remaining 8 subjects for the control group were collected at CHI-MEI Hospital, Tainan, Taiwan. K-fold (K=8) cross validation method was performed for evaluation and the detection accuracy achieved 68.3% for mood disorder detection. Compared with the well-known classifiers, such as Gaussian Model and deep neural network (DNN), the experimental results confirmed that our proposed method can achieve the best performance. Furthermore, the AU profiles and MS features are also beneficial to improve mood disorder detection performance.

碩士
國立交通大學
工學院聲音與音樂創意科技碩士學位學程
98
As the technology of artificial intelligence and machine learning develops, people are pursuing some applications to interact with computers in a more humanized and personalized way. In the recent years, affective computing for the content-based information retrieval is a very popular research of both image and sound signals. Using emotions as an index for Music Information Retrieval is also a challenge issue for researchers. Music is always plays an important role in people’s everyday life, whether they had been experienced professional music education or not, all the different kinds of music exactly could arouse and transmit the different emotional responses of human. Although the emotion is a subjective feeling, the same music might bring different emotions to different persons, but in general, there is still a trend of peoples’ emotional responses. Most of the state of art research about music emotion classification or prediction assumes the music is always in a constant emotion or it is in a constant emotion at each possible part. The idea of the system proposed in this paper based on human’s listening processing, the emotion response at an instant of time are primary influenced by the features that you heard in the past few seconds, and the emotion responses will be displayed by the moving dot and it’s trajectory on the Thayer’s emotion plane, this will enhances the listening experiences of listener, finally the trajectory could also be clues for evaluate the average emotion or mood of the music.

碩士
國立成功大學
資訊工程學系
103
Mood disorders, including unipolar depression (UD) and bipolar disorder (BD), are reported to be the most common mental illness in recent years. In diagnostic evaluation on the outpatients with mood disorder, a high percentage of BD patients are initially misdiagnosed as having UD. This results in significant negative consequences for the treatment of the BD patients. Therefore, it is crucial to establish an accurate distinction between BD and UD in order to make an accurate and early diagnosis, leading to improvements in treatment and course of illness. Given that speech is the most natural way for emotion expression, recognition of emotions in speech could be effectively applied to mood disorder detection. As current research focused on long-term monitoring of the mood disorders, short-term detection which could be used in early detection and intervention and thus reduce the severity of symptoms is desirable. This thesis proposes an approach to short-term detection of mood disorder based on the elicited speech responses. At first, eliciting emotional videos were used to elicit the patients’ emotions. Speech responses of the patients were collected through the interviews by a clinician after watching each of six emotional video clips. The support vector machine (SVM)-based classifier was adopted to obtain emotion profiles for each speech responses. In order to deal with the data bias problem, hierarchical spectral clustering algorithm were employed to adapt the eNTERFACE emotion database to fit the collected mood disorder database. The adapted eNTERFACE emotion data were then fed to the trained autoencoder to reconstruct the eNTERFACE emotion data for SVM-based emotion classifier construction. Finally, based on the emotion profiles generated from the SVM-based emotion classifier, a latent affective structure model (LASM) is proposed to characterize the structural relationship among the speech responses to six emotional videos for mood disorder detection. For system performance evaluation, speech responses were collected from 24 subjects, including 8 UD, 8 BD and 8 healthy people (control group) to construct the CHI-MEI mood database. Eight-fold cross validation was adopted for the following evaluation. Performance evaluation on the LASM-based approaches using autoencoder with different numbers of neurons and layers were conducted. The experimental results show that the proposed LASM-based method achieved 67%, improving by 9% accuracy compared with the commonly used classifiers like SVM and DNN. In future work, it will be helpful to improve system performance by integrating the proposed method with lexical and visual information. Furthermore, the individuality of the patient is also an important factor to be considered in mood disorder detection.

Thesis (M.A.)--York University, 2007. Graduate Programme in Psychology.
Typescript. Includes bibliographical references (leaves 51-63). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR32009

Clinical depression is a common mood disorder that may last for long periods, vary in severity, and could impair an individual’s ability to cope with daily life. Depression affects 350 million people worldwide and is therefore considered a burden not only on a personal and social level, but also on an economic one. Depression is the fourth most significant cause of suffering and disability worldwide and it is predicted to be the leading cause in 2020. Although treatment of depression disorders has proven to be effective in most cases, misdiagnosing depressed patients is a common barrier. Not only because depression manifests itself in different ways, but also because clinical interviews and self-reported history are currently the only ways of diagnosis, which risks a range of subjective biases either from the patient report or the clinical judgment. While automatic affective state recognition has become an active research area in the past decade, methods for mood disorder detection, such as depression, are still in their infancy. Using the advancements of affective sensing techniques, the long-term goal is to develop an objective multimodal system that supports clinicians during the diagnosis and monitoring of clinical depression. This dissertation aims to investigate the most promising characteristics of depression that can be “heard” and “seen” by a computer system for the task of detecting depression objectively. Using audio-video recordings of a clinically validated Australian depression dataset, several experiments are conducted to characterise depression-related patterns from verbal and nonverbal cues. Of particular interest in this dissertation is the exploration of speech style, speech prosody, eye activity, and head pose modalities. Statistical analysis and automatic classification of extracted cues are investigated. In addition, multimodal fusion methods of these modalities are examined to increase the accuracy and confidence level of detecting depression. These investigations result in a proposed system that detects depression in a binary manner (e.g. depressed vs. non-depressed) using temporal depression behavioural cues. The proposed system: (1) uses audio-video recordings to investigate verbal and nonverbal modalities, (2) extracts functional features from verbal and nonverbal modalities over the entire subjects’ segments, (3) pre- and post-normalises the extracted features, (4) selects features using the T-test, (5) classifies depression in a binary manner (i.e. severely depressed vs. healthy controls), and finally (6) fuses the individual modalities. The proposed system was validated for scalability and usability using generalisation experiments. Close studies were made of American and German depression datasets individually, and then also in combination with the Australian one. Applying the proposed system to the three datasets showed remarkably high classification results - up to a 95% average recall for the individual sets and 86% for the three combined. Strong implications are that the proposed system has the ability to generalise to different datasets recorded under quite different conditions such as collection procedure and task, depression diagnosis testing and scale, as well as cultural and language background. High performance was found consistently in speech prosody and eye activity in both individual and combined datasets, with head pose features a little less remarkable. Strong indications are that the extracted features are robust to large variations in recording conditions. Furthermore, once the modalities were combined, the classification results improved substantially. Therefore, the modalities are shown both to correlate and complement each other, working in tandem as an innovative system for diagnoses of depression across large variations of population and procedure.

碩士
國立高雄科技大學
電機工程系
107
In the continuous improvement of semiconductor manufacturing process and continuous improvement of quality yield, automated production can no longer meet the high quality requirements of customers; in advanced manufacturing processes, automation equipment needs to have information self-perception, self-decision, self-execution and other functions to achieve wisdom for the Smart Factory modernization needs. In the early 1990s, when semiconductor packaging automation started, the company invested billions of dollars to purchase automated sealing equipment and entered the generation of automated production. The equipment in the 1990s did not have the concept of FDC (Fault Detection and Classification) and function. Although the manufacturing process has PLC (Programmable Logic Controller) automatic control production, and the corresponding recipe (Recipe) and SPC (Statistical Process Control) production chart can record the production quality for different processes, but each device belongs to “Individual automation equipment”. If you upload the data of the sensing components that affect the quality of each device to the cloud, you can optimize the current automated production process of the stand-alone machine by using the sophisticated technology of modern developed cloud technology and big data analysis. In this study, based on the voltage values of the pressure sensor of the device under the same servo control position and condition before the injection molding, and upload the data obtained by the extraction device to the cloud for data collection; The data collects, analyzes, classifies, manages, and plans a health management system, allowing the device to acquire self-awareness, self-decision, and self-execution into intelligent devices and tries to add the data returned by a large number of devices to the Convolutional Neural Network(CNN) training the system that can determine what kind of abnormality the abnormality diagram belongs to and in order to guide the maintenance personnel to repair and reduce inspection.

碩士
國立交通大學
工學院聲音與音樂創意科技碩士學位學程
104
This paper proposes a sequential framework that progressively extracts the features of music and characterizes music-induced emotions in a predetermined emotion plane. To build-up the emotion plane, 200 Western pop music clips, including four categories of emotion-predefined music with each group of 50 clips are used to train the system. Five feature sets, including onset intensity, timbre, sound volume, mode, and dissonance are extracted from WAV file to represent the characteristics of a music sample. Support vector machine (SVM) algorithm is used to demarcate the boundaries of “Exuberance”, “Contentment”, “Anxious”, and “Depression” on the Thayer’s emotion plane for trained music data. A graphic interface of emotion arousal locus on two-dimensional model of mood is established in Android System to represent the tracking of dynamic emotional transition caused by music. This system enables user to choose playing clips in mobile device based on identifying music emotions. Furthermore, the graphic interface of emotion can also reveal the emotional distribution of user’s music clips in data bank. The experimental results show the exploiting of human-machine interaction system by the efforts of mathematical analysis, feature extraction and algorithm, classifier training in music data processing. This interactive music selection system provides innovative music tracks playing sequence. With various music genre of different regions in the world, such as the Middle East music, religious music, a customized music emotions coordinate plane based on specified training music samples can be created to show the diversity of music culture.

碩士
國立屏東科技大學
生物機電工程系所
96
This study aims to develop a system to detect and separate contaminated flask plantlet by machine vision and x-y-z robot arm. The system consists of input, detection, pick-up, output, and central control unit. The detection function is conducted by four CCD cameras with a 4-channel monochrome frame grabber, which fitted to the format of tray type collection (20 flasks in 4×5 format) of flask plantlet. Thus detection unit takes four images of flasks at one time, and totally takes five times to finish one tray of flask plantlet. Once the contaminated flask plantlet was detected, its relative coordinate was labeled and passed to pick-up unit (an x-y-z robot arm). Therefore the contaminated flask plantlet will be removed and the others of non-contaminated plantlets will be delivered to outlet. The whole process was integrated by the central control unit which consists of motion control card, Digital I/O card, conveyers, sensors, and personal computer etc. The separation strategy is performed by Linear Discriminant Analysis (LDA). Experiment results showed that one tray inspection takes one minutes and 40 seconds. The classification rate reached 90% when 27 features of infrared bands (700~870nm) were used in LDA.

碩士
國立屏東科技大學
機械工程系
94
There are many cycles for sub-culture the Phalaenopsis seedlings in flask during the whole process of tissue culture. During this manual operation process, the contaminants sometimes will contaminate the seedlings in flask due to environment and improper operations. In order to prevent the miss-judges resulted from personnel and to increase the detection efficiency, this study developed a machine vision system that equipped with multispectral image, input unit, output unit and central control unit. The detection program was also developed by C language. Seedlings of Phalaenopsis in flask from the 2nd to 7th day after seedlings were sub-cultured in flask at last stage, were tested in tray-input format. Two shooting strategies: strategy A (one CCD on one flask) and strategy B (two CCD on one flask) were compared to find the detection accuracy. Results showed that strategy A could have the highest accuracy of 87% when the 3rd day samples were tested. The position accuracy set by step motor could have 100% accuracy. On the other hand, in strategy B the best detection accuracy was 78%, and the step motor had 100% accuracy.

碩士
南臺科技大學
電機工程系
105
Simulation of plastic injection molding by mold flow analysis, can reduce the number of test mode, shorten the mold design and development time and reduce production costs. With the progress of injection molding technology, bio-detection electrode chip base design widely used plastic injection process, not only increase the convenience of replacement, and significantly reduce the cost of manufacturing products. Therefore, the introduction of mold flow analysis technology in the bio-detection electrode chip multi-material injection molding (Multi-Component Molding) process analysis, multi-material injection molding is a diversified plastic model products, one of the advanced technology, a variety of materials or The colors are molded on the same product. In this study, the raw material electrode is used as the analysis element to explore how to make the maximum quantity of the product at the lowest cost and the shortest time, but still reach the best quality of the measurement level. The electrode piece is divided into the main body of the electrode The effect of molding parameters on the warpage of the modified model was studied by using the MCM process to analyze and import the Taguchi experiment. (Temperature, material temperature, flow rate, cooling time, packing pressure, holding time and runner design) were discussed. The trend of warpage of electrode plate under different molding conditions was discussed. Calculate the experimental prediction data, and find out the optimal conditions for each control change, determine the best combination of process parameters. Key words: Mold flow analysis, electrode piece, Taguchi method, warping, multi-material injection molding

Septins are a highly conserved family of eukaryotic proteins having significant homology within and among species. In the budding yeast, Saccharomyces cerevisiae, a septin-based hierarchy of proteins is required to localize chitin in the bud neck prior to septum formation. However, this process has not been clarified in a filamentous, conidiogenous fungus capable of yeast growth, such as Wangiella dermatitidis, a polymorphic agent of human phaeohyphomycosis. Prior studies of this melanized mold showed that some chitin synthase mutants (wdchsΔ) have defects in yeast septum formation, suggesting that the septins of W. dermatitidis might functionally associate with some of its chitin synthases (WdChsp). To test this hypothesis, four vegetative septin homologs of S. cerevisiae were cloned from W. dermatitidis and designated WdCDC3, WdCDC10, WdCDC11, and WdCDC12. Of the four, only WdCDC3 functionally complemented completely a strain of S. cerevisiae with a ts mutation in the corresponding gene, although WdCDC12 did so partially. Functional characterizations by mutagenesis of the four W. dermatitidis septin genes revealed that resulting mutants (wdcdc[delta]) each had unique defects in yeast growth and morphology, indicating that each septin carried out a distinct function. Furthermore, when a wdcdc10[delta] mutation was introduced into five different wdchs[delta] strains, weak genetic interactions were detected between WdCDC10 and WdCHS3 and WdCHS4, and a strong interaction between and WdCHS5. Cytological studies showed that WdChs5p was mislocalized in some septin mutants, including wdcdc10[delta]. These results confirmed that in W. dermatitidis septins are important for proper cellular morphogenesis, cytokinesis, and especially septum formation through associations with some chitin synthases.
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