Large Thermoelectric Power Factor in TiS2 Crystal with Nearly Stoichiometric Composition

A TiS$_{2}$ crystal with a layered structure was found to have a large thermoelectric power factor.The in-plane power factor $S^{2}/ \rho$ at 300 K is 37.1~$\mu$W/K$^{2}$cm with resistivity ($\rho$) of 1.7 m$\Omega$cm and thermopower ($S$) of -251~$\mu$V/K, and this value is comparable to that of the best thermoelectric material, Bi$_{2}$Te$_{3}$ alloy. The electrical resistivity shows both metallic and highly anisotropic behaviors, suggesting that the electronic structure of this TiS$_{2}$ crystal has a quasi-two-dimensional nature. The large thermoelectric response can be ascribed to the large density of state just above the Fermi energy and inter-valley scattering. In spite of the large power factor, the figure of merit, $ZT$ of TiS$_{2}$ is 0.16 at 300 K, because of relatively large thermal conductivity, 68~mW/Kcm. However, most of this value comes from reducible lattice contribution. Thus, $ZT$ can be improved by reducing lattice thermal conductivity, e.g., by introducing a rattling unit into the inter-layer sites.Comment: 11 pages, 4 figures, to be published in Physical Review

The repertoire of ICE in prokaryotes underscores the unity, diversity, and ubiquity of conjugation

Horizontal gene transfer shapes the genomes of prokaryotes by allowing rapid acquisition of novel adaptive functions. Conjugation allows the broadest range and the highest gene transfer input per transfer event. While conjugative plasmids have been studied for decades, the number and diversity of integrative conjugative elements (ICE) in prokaryotes remained unknown. We defined a large set of protein profiles of the conjugation machinery to scan over 1,000 genomes of prokaryotes. We found 682 putative conjugative systems among all major phylogenetic clades and showed that ICEs are the most abundant conjugative elements in prokaryotes. Nearly half of the genomes contain a type IV secretion system (T4SS), with larger genomes encoding more conjugative systems. Surprisingly, almost half of the chromosomal T4SS lack co-localized relaxases and, consequently, might be devoted to protein transport instead of conjugation. This class of elements is preponderant among small genomes, is less commonly associated with integrases, and is rarer in plasmids. ICEs and conjugative plasmids in proteobacteria have different preferences for each type of T4SS, but all types exist in both chromosomes and plasmids. Mobilizable elements outnumber self-conjugative elements in both ICEs and plasmids, which suggests an extensive use of T4SS in trans. Our evolutionary analysis indicates that switch of plasmids to and from ICEs were frequent and that extant elements began to differentiate only relatively recently. According to the present results, ICEs are the most abundant conjugative elements in practically all prokaryotic clades and might be far more frequently domesticated into non-conjugative protein transport systems than previously thought. While conjugative plasmids and ICEs have different means of genomic stabilization, their mechanisms of mobility by conjugation show strikingly conserved patterns, arguing for a unitary view of conjugation in shaping the genomes of prokaryotes by horizontal gene transfer

Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

无线传感器网络，作为全球未来十大技术之一，集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术，可实时感知、采集、处理、传输网络分布区域内的各种信息数据，在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议，并针对大规模的无线传感器网络设计了一种树状路由协议，它根据节点地址信息来形成路由，从而简化了复杂繁冗的路由表查找和维护，节省了不必要的开销，提高了路由效率，实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR（AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2332007115216

Etude de nouveaux caractères biométriques de la main dans un contexte Télécom

Trade and e-commerce via mobile phones (m-commerce) is growing very strongly. To ensure the security of transactions, this thesis presents a study on the nature of the biometric palm in the context of telecom applications. In the first part of the work, a method for segmentation of the hand is presented. This method relies on a combination of the color information and shape of the hand. The color of the hand is determined by a multi-resolution approach after modeling neural networks. The shape of the hand is defined by an active shape model initialized and constrained by skin color. The combination of these approaches in near-real time provides better robustness to external disturbances, while improving the accuracy of detection. In a second phase, three bricks biometric hand recognition is presented. The first approach is to merge the information of convolutional shape and texture of the hand extracted with oriented Gabor filters. The second brick biometric extract the texture information from the palm of the hand in a circular Gabor filter. Two textures are compared by a robust edit distance for a better characterization of the palm. Finally, the third method of recognition is proposed. It establishes the palmar recognition through a non-linear estimation of the distribution of pixels of the palm that are derived from the concept of texture or normalized energy.Les échanges et le commerce électronique via la téléphonie mobile (m-commerce) se développent très fortement. Pour assurer la sécurité des transactions, cette thèse présente une étude sur le caractère biométrique de la paume de la main dans le contexte des applications télécoms. Dans la première partie du travail, une méthode de segmentation de la main est présentée. Cette méthode repose sur une combinaison des informations de couleurs et de formes de la main. La couleur de la main est déterminée par une approche multi-résolution après une modélisation par des réseaux de neurones. La forme de la main est définie par un modèle de forme actif initialisé et contraint par la couleur de peau. La combinaison de ces approches en quasi-temps réel permet une meilleure robustesse aux perturbations extérieures tout en améliorant la précision de la détection. Dans une seconde phase, trois briques de reconnaissance biométrique de la main sont présentées. La première approche consiste à fusionner par convolution les informations de forme et de texture de la main extrait par des filtres de Gabor orientés. La deuxième brique de reconnaissance biométrique extrait l'information de texture de la paume de la main par un filtre de Gabor circulaire. Deux textures sont comparées par une distance d'édition robuste permettant une meilleure caractérisation de la paume. Finalement, la troisième méthode de reconnaissance est proposée. Elle établit la reconnaissance palmaire grâce à une estimation non-linéaire de la distribution des pixels de la paume qui sont dérivés de la notion de texture ou de l'énergie normalisée

Etude de nouveaux caractères biométriques de la main dans un contexte Télécom

Les échanges et le commerce électronique via la téléphonie mobile (m-commerce) se développent très fortement. Pour assurer la sécurité des transactions, cette thèse présente une étude sur le caractère biométrique de la paume de la main dans le contexte des applications télécoms. Dans la première partie du travail, une méthode de segmentation de la main est présentée. Cette méthode repose sur une combinaison des informations de couleurs et de formes de la main. La couleur de la main est déterminée par une approche multi-résolution après une modélisation par des réseaux de neurones. La forme de la main est définie par un modèle de forme actif initialisé et contraint par la couleur de peau. La combinaison de ces approches en quasi-temps réel permet une meilleure robustesse aux perturbations extérieures tout en améliorant la précision de la détection. Dans une seconde phase, trois briques de reconnaissance biométrique de la main sont présentées. La première approche consiste à fusionner par convolution les informations de forme et de texture de la main extrait par des filtres de Gabor orientés. La deuxième brique de reconnaissance biométrique extrait l'information de texture de la paume de la main par un filtre de Gabor circulaire. Deux textures sont comparées par une distance d'édition robuste permettant une meilleure caractérisation de la paume. Finalement, la troisième méthode de reconnaissance est décrite. Elle établit la reconnaissance palmaire grâce à une estimation non-linéaire de la distribution des pixels de la paume qui sont dérivés de la notion de texture ou de l'énergie normalisée.Electronic commerce on mobile phone (m-commerce) is growing up very strongly. To ensure the security of transactions, this thesis presents a study of the biometric features of the palmprint in the context of telecom applications. In the first part of this work, a method for the segmentation of the hand is proposed. This method relies on a combination of the color and the shape of the hand. The color of the hand is defined by a multi resolution process that follows a modeling by neural networks. The shape is determined by an active shape model initialized and constrained by the skin color. The combination of these methods in near real time results in a better robustness to acquisition disturbances by increasing the accuracy of the detection. In the second part, three biometrics authentication methods are presented. The first method consists in a convolution-based merging process of the data about hand shape and palm texture extracted by an oriented Gabor filter. The second one extracts texture information by means of a circular Gabor filter. Two textures are compared by a normalized approximated string matching which is robust against translation, substitution, deletion and addition. Finally, the third biometrics authentication method is described. This method achieves the palmprint recognition thanks to a non-linear estimation of the distribution of palm pixels.CAEN-BU Sciences et STAPS (141182103) / SudocSudocFranceF

Les Objectifs de nutrition parentérale en réanimation néonatale sont mieux atteints avec des prescriptions de solutés standards qu'avec des prescriptions individualisées (une étude rétrospective)

AIX-MARSEILLE2-BU Méd/Odontol. (130552103) / SudocSudocFranceF

Contactless Hand Recognition Based on Distribution Estimation

International audienceMore and more research have been developed very recently for automatic hand recognition. This paper proposes a new method for contactless hand authentication in complex images with low cost devices. Our system uses skin color and hand shape information for hand detection process. Next, the palm is extracted and characterized by a bank of Gabor filters. Finally, the palm features are compared with a distribution estimation given an optimal discrimination. The experimental results present an error rate lower than 1.7% with a population of 49 people

Robust GrayScale Distribution Estimation for Contactless Palmprint Recognition

International audienceMore and more research have been developed very recently for automatic hand recognition. This paper proposes a new method for contactless hand authentication in complex images. Our system uses skin color and hand shape information for an accurate hand detection process. Then, the palm is extracted and characterized by a robust and normalized decomposition. During enrollment, a distribution estimation is used to defined the optimal discrimination of the palmprint features. Finally, some specific thresholds are defined to separate in test phase impostor and genuine users. The experimental results present an error rate of 1.5% with a population of 49 people

Hand detection for contactless biometrics identification

International audienceIn this paper, we present a new hand detection system based on a combination of skin color modelling and active shape model. Skin color distribution specified by a multiresolution neural network constrains active shape model evolutions on skin objects. We present the skin color detection performances of this near real time system on many color spaces and show that a combination of skin color and active shape model increase robustness and accuracy of hand detection in complex images

Contact less palmprint authentication using circular Gabor filter and approximated string matching

International audienceMore and more research have been developed very recently for automatic hand recognition. This paper proposes a new method for contactless hand authentication in complex images. Our system uses skin color and hand shape information for hand detection process. Next, the palm is extracted and characterized by circular Gabor filter. Finally, the palm features are matched by a new normalized approximated string matching. The experimental results present an error rate lower than 1.2% with a population of 49 people. We show that our method improves the performances of two palmprint methods 2D-Gabor and PPOC on our database