The Clinch River (CR) and North Fork Holston River (NFHR) contain some of the most diverse freshwater mussel assemblages in the United States; however, both rivers are experiencing declines in mussel populations. The first component of this study used histological evaluations and water quality data to determine whether mussels were negatively impacted in the CR zone of decline (ZD) and to inform future management of freshwater mussels in the river. In the 91 kilometer (km) section from Carbo, Virginia (CRKM 431) downstream to Speers Ferry, Virginia (CRKM 340), referred to as the ZD, mussel density decreased >90% from 1979 to 2014 at key sites such as Semones Island (CRKM 378.3) and Pendleton Island (CRKM 364.2). Laboratory propagated mussels were placed in cages in the river for one year from June 2012 to May 2013 at four sites within the ZD and four sites in reaches where mussel populations remain stable or are increasing, a zone of stability (ZS). The survival, growth and histological results indicated that there are continuing impacts to mussels in the ZD. Research investigating impacts to the ZD and methods to improve water quality in this zone are needed. The laboratory component of this study examined sublethal effects of potassium (K⁺), chloride (Cl⁻), and un-ionized ammonia (NH₃-N) on mussel tissues at concentrations relevant to those found in the NFHR. Historical industrial activities at Saltville, Virginia, as well as continued pollution of the NFHR from chemical waste ponds at this location, are believed to be significant contributors to mussel declines. Contaminant seepages from the waste ponds that include Cl⁻, K⁺, and NH₃-N have been shown to be toxic to adult and juvenile mussels. A three-month laboratory study was conducted to assess impacts to organ tissues (gills, digestive glands, kidneys, and gonads) of adult Villosa iris exposed to environmentally relevant concentrations of K⁻ (4 and 8 mg/L), Cl⁻ (230 and 705 mg/L), and NH₃-N (0.014 and 0.15 mg/L) using histological evaluations. No detectable differences were observed among the histological endpoints from mussels held in treatments and control (p>0.05). The study design was modified and repeated using increased concentrations of K⁺ (8, 16, and 32 mg/L) and Cl⁻ (705, 1410, and 2820 mg/L) for a two-month exposure period. Due to issues with maintaining NH3-N in mussel holding chambers, the second study did not the second study did not include NH₃-N exposures. Control mussels in both studies had a higher abundance of lipofuscin in kidneys and degraded cytoplasm in the digestive gland diverticula compared to baseline mussels, indicating that captivity influenced mussel tissues. Future studies are needed to more thoroughly address these captivity effects. Both survival and histological data in the second test showed a significant negative effect of the increased concentrations of Cl⁻ and K⁻, which were representative of those found at some sites in the NFHR downstream of Saltville, Virginia. / Master of Science

The Upper Tennessee River drainage of Virginia and Tennessee, Green River drainage of Kentucky, and Cumberland River drainage of Kentucky and Tennessee are known for their freshwater mussel species diversity. These river systems harbor dense populations of freshwater mussels that have significant impacts on surrounding ecosystems; however, due to their sedentary lifestyles, freshwater mussels are particularly susceptible to many biotic and abiotic stressors. Managers strive to preserve the fragile ecosystems that include freshwater mussels and, hence, study the life-history strategies of endangered and common freshwater mussel species. The goals of this project were to inform management decision-making based on whether Leaunio ortmanni is endemic to the Green River drainage and a species distinct from Leaunio vanuxemensis based on molecular identification, estimation of genetic diversity, and morphometric analysis, and to screen for cryptic biodiversity of populations of the Cambarunio iris species complex in the Upper Tennessee, Cumberland, and Green River drainages. I used the mitochondrial DNA (mtDNA) gene from the first subunit of the NADH dehydrogenase (ND1) as a genetic marker for species-level assessment of L. ortmanni and L. vanuxemensis from the Green and Cumberland River drainages. Additional mtDNA sequences of L. ortmanni and L. vanuxemensis were added to increase sample sizes and coverage of historical distribution. A Bayesian phylogenetic analysis of mtDNA sequences did not result in monophyletic lineages for either species based on the ND1 marker. Haplotype networks of mtDNA sequences demonstrated that haplotype sharing is occurring between the two focal taxa, and also among additional taxa, all of which previously belonged to the genus Villosa. A total of eight nuclear DNA microsatellites were successfully genotyped for the two focal taxa. The nuclear DNA microsatellites showed a strong phylogeographic signal between L. ortmanni of the Green River drainage and L. vanuxemensis of the Cumberland River drainage. An assignment-test based analysis in program STRUCTURE and a phylogenetic tree constructed using Nei's D genetic distance indicated well-differentiated populations across the two drainages. Additionally, the nuclear DNA microsatellite analysis showed a recent loss of genetic diversity across all populations, including when populations were pooled together at the sub-basin level. Further delineation of the focal taxa was assessed using geometric morphometrics and decision tree and random forest analyses. Decision tree and random forest analyses identified periostracum color, nacre color, overall shape, and sex to be distinguishing factors for field identification of L. ortmanni and L. vanuxemensis. Geometric morphometrics comparing species, shape, and drainage showed clear differentiation in shell shape between L. ortmanni and L. vanuxemensis. This study was able to delineate these two taxa, showing that L. ortmanni and L. vanuxemensis are separate species, and that L. ortmanni warrants listing under the Endangered Species Act. Management actions should focus on broodstock collection and propagation strategies to increase genetic diversity within established populations. Additionally, propagation and augmentation should look to reintroduce populations of L. ortmanni into its historical geographic range in unoccupied sections of the mainstem Green River. In addition, I assessed genetic diversity and differentiation again using ND1 and eight nuclear DNA microsatellite loci, and morphological differences among different shell forms of C. iris in the Upper Tennessee, Cumberland, and Green river basins and of the sister species C. taeniatus in the Cumberland, and Green river basins. Additional mitochondrial DNA sequences of C. iris and C. taeniatus were added to increase sample sizes and coverage of historical distribution. Mitochondrial DNA analysis demonstrated haplotype sharing between taxa, but with many unique haplotypes occurring in the upper Tennessee River basin. Nuclear DNA microsatellite loci revealed low levels of genetic diversity within populations of C. iris within the Upper Tennessee River basin, but high levels of divergence from C. iris and C. taeniatus of the Green and Cumberland River basins. The nuclear DNA analysis showed high admixture within and among sampled populations of C. iris throughout the Upper Tennessee River Basin with minimal geographic structuring among sub-basins. Further, phenotypic diversity was assessed using geometric morphometrics and decision tree and random forest analysis. Decision-tree and random forest analysis identified maximum height from the umbo to the ventral margin, periostracum color, shell width, and ray coverage to be defining characteristics for field identification of the focal taxa. Geometric morphometrics showed high overlap of shell shape for the focal taxa regardless of locality. While cryptic biodiversity was not detected in the Upper Tennessee River Basin, on a larger geographic level, cryptic biodiversity was detected using the combination of the mtDNA, nuclear DNA, and morphological data, which showed that C. taeniatus and C. iris from the Green River drainage were distinct from populations of C. iris in the upper Tennessee River basin. / Master of Science / Worldwide, freshwater mussel species diversity is greatest in North America; however, both abundance and diversity have declined in Canada, the United States, Mexico and the countries of Central America. Among rivers of North America, the Ohio River and its large tributaries, which include the Green, Cumberland, and Tennessee River drainages, have been noted for their high levels of biodiversity of freshwater mussels. Freshwater mussels contribute many services to freshwater ecosystems, including nutrient recycling and storage, structural habitat, substrate and food web modification. Dense populations of freshwater mussels have significant impacts on the surrounding ecosystem; however, due to their sedentary lifestyles, freshwater mussels are particularly susceptible to many biotic and abiotic stressors. Examples of stressors include agricultural runoff, temperature fluctuations, and dams which can alter stream conditions into more lake-like conditions and therefore affect the distributions of host fish populations. These stressors put mussels at risk for extirpation, which in turn, reduces the ecological biodiversity of these river drainages. Like other freshwater mussel species, the rainbow mussel (Cambarunio iris) of the Upper Tennessee River drainage, Mountain Creekshell (Leaunio vanuxemensis) of the Cumberland and Tennessee River drainages, and Kentucky Creekshell (Leaunio ortmanni) of the Green River drainage are in danger of decline due to anthropogenic changes in biotic and abiotic factors. Habitat degradation and loss have been of particular concern to managers. Life-history strategies for these three species are still widely unknown, and due to the overlap in their distributions, both phylogenetic and morphological analyses are needed to distinguish between species and populations to determine the best approach for management and conservation. The lack of understanding of taxonomic relationships in combination with morphologically similar characters poses a threat to conservation of these three species. The phylogenetic species concept is defined as an irreducible group whose members are descended from a common ancestor and who all possess a combination of certain defining, or derived traits, whereas the biological species concept is defined as groups or populations that are reproductively isolated from each other, meaning individuals from different groups cannot breed with one another. The results of my study have led to a better understanding of the phylogenetic relationships and species status of individuals collected from different localities of L. ortmanni and L. vanuxemensis and C. iris collected from the Green and Cumberland River drainages and the Upper Tennessee River drainage. In addition, morphological analyses were conducted to identify which traits are best for external identification of these three look-alike species, so they can be more reliably identified in the field.

Yes / Multimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person.

Τα τελευταια χρόνια ειμαστε μαρτυρες ενός εντυπωσιακού παραδόξου στο χώρο της τεχνολογίας. Ενώ όλη η ανθρωπότητα αναζητά το κάτι παραπάνω σε υπολογιστική ισχύ, σε χώρο αποθήκευσης και σε ταχύτητα, μικρές αυτόνομες συσκευές έρχονται να κατακτήσουν όλο και περισσότερους τομείς της καθημερινότητάς μας. Μονάδες με την ικανότητα της επεξεργασίας και της αποθήκευσης δεδομένων, της αίσθησης του περιβάλλοντος αλλά και της επικοινωνίας μεταξύ τους, ενσωματώνονται σχεδόν σε όλους τους τομείς δραστηριοποίησης του ανθρώπου. Ο τρόπος αυτό-οργάνωσης αυτών των κόμβων - μονάδων στα πλαίσια μεγάλων ασύρματων δικτύων αισθητήρων, και η συλλογή δεδομένων από μια ευρεία περιοχή, τους δίνει τη δυνατότητα λήψης αποφάσεων, πολλές φορές κρίσιμων, ανάλογα με τις επικρατούμενες συνθήκες. Τα παραπάνω χαρακτηριστικά των δομικών στοιχείων των ασυρμάτων δικτύων αισθητήρων, σε συνδυασμό με τις υπηρεσίες της υψηλής και καθιερωμένης τεχνολογίας του συστήματος GPS (Global Positioning System) μπορούν να δημιουργήσουν έναν εκρηκτικό συνδυασμό και ερευνητικές ιδέες για ανάπτυξη αστικών εφαρμογών αυτοματισμού, στο πλαίσιο των λεγόμενων «έξυπνων πόλεων». Μέσα σε ένα απέραντο δίκτυο ασυρμάτων αισθητήρων, αποτελούμενο από χιλιάδες οντότητες, η ικανότητα του κάθε κόμβου να εντοπίζει την θέση του και να την μοιράζεται με τους υπόλοιπους, κερδίζει ολοένα και περισσότερο έδαφος ειδικά σε θέματα δρομολόγησης. Η χρήση της τεχνολογίας GPS από έναν κόμβο, αντικείμενο που μελετάμε στη παρούσα εργασία, μπορεί να οδηγήσει από την επιτυχή εφαρμογή του Geographical Routing σε ένα WSN, μέχρι την υλοποίηση απαιτητικών εφαρμογών για αντιγραφή κίνησης αλλά και δημιουργίας «έξυπνων αυτοκινητόδρομων» μέσα στους οποίους θα γίνεται αυτόματη πλοήγηση των κινητών υπό την επίβλεψη ενός μεγάλου WSN με κόμβους που συνεργάζονται με το σύστημα δορυφορικού εντοπισμού θέσης αλλά και μεταξύ τους. Όπως γίνεται άμεσα αντιληπτό, η παρούσα εργασία, που πραγματεύεται την σωστή συνεργασία και επικοινωνία ενός δικτύου ασυρμάτων αισθητήρων με την τεχνολογία GPS για την ιχνηλάτηση της πορείας ενός κινητού, μπορεί να δώσει μελλοντική τροφή για ενασχόληση σε πολλαπλά ερευνητικά επίπεδα. Η εργασία μας χωρίστηκε σε τρείς θεματικές ενότητες. Η πρώτη αφορά τον τομέα του WSN και του προγραμματισμού των κόμβων, για επικοινωνία με τους δορυφόρους, με τον υπολογιστή αλλά και μεταξύ τους, με τις απαραίτητες λειτουργικές εφαρμογές που κληθήκαμε να υλοποιήσουμε. Η δεύτερη αναφέρεται στην εργασία μας από την πλευρά του υπολογιστή, που λειτουργεί σαν συλλέκτης των δεδομένων του δικτύου, και τη σύνδεση του συστήματός μας με την πρότυπη εφαρμογή Google EarthTM για απεικόνιση σε πραγματικό χρόνο της τροχιάς που ακολουθεί ένα κινητό. Η τρίτη ενότητα περιλαμβάνει εκτέλεση πειραμάτων χρήσης του συστήματος που σχεδιάσαμε και παράθεση οπτικοποιημένων αποτελεσμάτων, για την εύκολη εξαγωγή χρήσιμων συμπερασμάτων όσον αφορά στη λειτουργικότητά του. / The last few years we witness a striking paradox in the field of technology. While all humanity is seeking for more computing power, more storage capabilities and more proccessing speed, small autonomous devices have appeared to occupy more and more areas of our lives in the daily routine. Units with the capabilities of data proccessing, data storage, enviromental sensing and communication with each other, are incorporated in almost all areas of human activity. The way in which these nodes are self-organized into large Wireless Sensor Networks and their ability to collect data from a wide area, enables them in taking decisions, critical ones sometimes, according to the prevailing conditions. The above characteristics of the components of wireless sensor networks, combined with the services of the established and standard technology of the GPS (Global Positioning System) can create ideas for research and development of urban applications of automation in the so-called “smart cities”. In a vast network of wireless sensors, consisting of thousands of entities, the ability of each node to detect its position and share it with others, is gaining more and more ground especially in routing topics. The use of GPS technology from a node, which is one of the subjects we study in this thesis, could lead from the successful implementation of the Geographical Routing, to the implementation of more demanding applications for motion replication but also to creating “smart highways” through which mobiles will execute an automatic navigation, supervised by a large WSN consisting of nodes cooperating with the satellite positioning system and with each other. As is readily apparent, the present thesis which is dealing with the good cooperation and communication of a wireless sensor network with the GPS technology in order to trace the path of a mobile, can provide room for future involvement in multiple levels of research. Our work was divided into three thematic sections. The first concerns the field of WSN and node programming so that they can be able to communicate with satellites, with the computer and with each other, by installing them with the necessary functional applications that we had to implement. The second section refers to our work on the computer side, which acts as a network data collector, and the link of our system with the standard Google EarthTM application to display the path of a mobile in real – time. The third section includes conducting experiments using the system we designed. The results are visualised and listed for an easy extraction of usefull conclusions regarding the functionality of our system.

The automatic recognition of individuals through the iris characteristics is an e±cient biometric technique that is widely studied and applied around the world. Many image processing stages are necessary to make possible the representation and the interpretation of the iris information. This work presents the state of the art in iris recognition systems where the most re- markable works and the di®erent techniques applied to perform each process- ing stage are quoted. The implementations of each processing stage using traditional techniques are presented and, afterwards, two innovator methods are proposed with the common objective of bringing bene¯t to the system. The ¯rst processing stage should be the localization of the iris region in an eye image. The ¯rst method proposed in this work presents an algorithm to achieve the iris localization through the utilization of the called Memetic Algorithms. The new method is compared to a classical method and the obtained results show advantages concerning e±ciency and processing time. In another processing stage there must be a pixels sampling from the iris region, from where the information used to di®erentiate the individuals is extracted. Traditionally, this sampling process is accomplished in an uni- form way along the whole iris region. It is proposed a pre-processing method which suggests a non uniform pixels sampling from the iris region with the objective of selecting the group of pixels which carry more information about the iris structure. The search for this group of pixels is done through Ge- netic Algorithms. The application of the new method improves the e±ciency of the system and also, allows the generation of smaller templates. In this work, a study on the called Active Shape Models is also accomplished and its application to perform the iris region segmentation is evaluated. To execute the simulations and the evaluation of the methods, it was used two public and free iris images database: UBIRIS database and MMU database. / O reconhecimento automático de pessoas utilizando-se características da íris é uma eficiente técnica biométrica que está sendo largamente estudada e aplicada em todo o mundo. Diversas etapas de processamento são necessárias para tornar possível a representação e a interpretação da informação contida na íris. Neste trabalho é apresentado o estado da arte de sistemas de reconhecimento de íris onde são citados os trabalhos de maior destaque e as diferentes técnicas empregadas em cada etapa de processamento. São apresentadas implementações de cada etapa de processamento utilizando técnicas tradicionais e, posteriormente, são propostos dois métodos inovadores que têm o objetivo comum de trazer benefícios ao sistema. A primeira etapa de processamento é a localização da região da íris na imagem. O primeiro método proposto neste trabalho apresenta um algoritmo para realizar a localização da íris utilizando os chamados Algoritmos Meméticos. O novo método é comparado a um método clássico e os resultadosnobtidos demonstram vantagens no que diz respeito à eficiência e ao tempo de processamento. Em uma outra etapa de processamento deve haver uma amostragem de pixels na região da íris, de onde são retiradas as informações utilizadas para diferenciar os indivíduos. Tradicionalmente, esta amostragem é realizada de maneira uniforme ao longo de toda a região da íris. É proposto um método de pré-processamento que sugere uma amostragem não uniforme de pixels na região da íris com o objetivo de selecionar o conjunto de pixels que carregam mais informações da estrutura da íris. A busca por esse conjunto de pixels é realizada utilizando-se Algoritmos Genéticos. A aplicação deste novo método aumenta a eficiência do sistema e ainda possibilita a geração de templates binários menores. Neste trabalho é realizado, ainda, um estudos dos chamados Active Shape Models e a sua aplicação para segmentar a região da íris é avaliada. Para a simulação e avaliação dos métodos, foram utilizados dois bancos de imagens de íris públicos e gratuitos: o banco de imagens UBIRIS e o banco de imagens MMU. / Doutor em Ciências

Biometric gateways are used to quickly and accurately identify people. Of the biometric characteristics, iris, face and fingerprints are commonly used. By combining them, better identification results can be achieved. The aim of this thesis is to create such a biometric gateway together with the control application. A combination of iris of both eyes and face is used, which is captured by cameras from three angles to increase accuracy. Neural networks are used to detect and extract face features. Iris recognition is realized using Daugman's algorithm.

The biometric techniques are well known and widespread nowadays. In this context biometry means automated person recognition using anatomic features. This work uses the iris as the anatomic feature. Iris recognition is taken as the most promising technique of all because of its non-invasiveness and low error rate. The inventor of iris recognition is John G. Daugman. His work underlies almost all current public works of this technology. This final thesis is concerned with biometry based on iris images. The principles of biometric methods based on iris images are described in the first part. The first practical part of this work is aimed at the proposal and realization of two methods which localize the iris inner boundary. The third part presents the proposal and realization of iris image processing in order to classifying persons. The last chapter is focus on evaluation of experimental results and there are also compared our results with several well-known methods.

Biometrics is a method of recognizing the identity of a person based on unique biological characteristics that are unique to each person. The methods of biometric identification is currently becoming increasingly widespread in various sectors. This work is focused on the identification of a person by iris images. The introductory section describes the principles of the well-known methods for biometric applications and the next part describes the design method and its implementation in Matlab. In the practical part, fast radial symmetry method is used for detection of pupil, from which it derives further image processing. Two dimensional discrete welvet transform is used here. The proposed algorithm is tested on databases CASIA-Iris- Interval and database IITD.

Le but de ce travail est de construire un système transportable flexible à cout minimum pouvant aider a la réalisation d'un compilateur pour le langage de commande réseau, qui sera utilise par le réseau CYCLADES

本研究的發問從研究者自身經驗以及大眾媒體內容出發，試圖瞭解成年女性學習芭蕾背後指涉出女性身體、芭蕾文化以及社會性別結構之間的何種關係，並從中探討女性身體在習舞的過程中，扮演何種角色。 對此，在理論的引用上，本研究以人類學的「體現」典範和美國女性主義政治哲學家Iris Marion Young的理論觀點，將女性身體視為一個知覺主體進行分析探討；在研究方法上，則採用「深度訪談法」以及研究者本身的「參與體驗」，以對成年女性的習舞身體經驗進行多方詮釋，從中瞭解該經驗所呈現、調和與轉化女性身體、芭蕾文化和社會性別結構的種種現象與關係。 本研究發現成年女性的芭蕾身體經驗共有三個特質：首先，成年女性在學習芭蕾的過程中，得以覺察自我身體感官，抒解身體壓力，並從社會角色回歸真實自我，對於身體的關注也不再僅集中在視覺觀感，同時也重視身體體驗。芭蕾的身體經驗成為成年女性擺脫社會角色，回歸身體知覺的「她方」國度。 再者，芭蕾身體經驗具有「轉化」的功能。此經驗一方面轉化了成年女性和日常生活的關係，改變成年女性在日常生活的姿態、生活行動的意義，讓成年女性有再詮釋個人與生活世界的能力。另外在「芭蕾學習文化」的部分，成年女性在日漸老化、退化身體的限制下，以親身體驗與實踐，重新定義學習芭蕾的年齡上限與可能性，也藉此展現女性身體的能力、自主與超越性。另外，在本研究也發現，成年女性的身體經驗讓過去象徵為男性凝視的芭蕾文化，轉變成女性自我體察與觀看，而重新定義芭蕾的觀看意義，此乃有別於過去女性主義的芭蕾研究結果。 最後，本研究發現女性身體乃是同時交織主客體面貌的多元身體，亦即女性身體在自我知覺以及社會性別結構之中來回游移，時為主體，時為客體，女性身體遂在自我和社會之間不斷變化其面貌。 女性身體有其能動性，但其也必須在社會性別結構之下扮演其角色，因此對於扮演主客體的女性身體的關注，可能不在於尋求身體的終極解放，而是女性身體如何在結構的限制之下，獲得更多的自主與選擇的可能。在本研究中，成年女性在芭蕾學習經驗中，回歸純然的身體知覺，即開啟女性身體自主的可能與契機。