無 / A multiple-star representation of a simple graph G assigns each vertex a union of stars in a host tree, such that vertices are adjacent if and only if their assigned sets intersect. The total star number S(G) is the minimum of the total number of stars used in any such representation of G. We obtain the maximum value of S(G) for m-edge connected graphs: m + 1, n-vertex graphs: [n² + 1)/ 4], and n-vertex outer-planar graphs: [3n /2-l]

Thesis (B.A.)--Haverford College, Dept. of Economics, 2007. / Includes bibliographical references.

L'alignement multiple de réseaux biologiques a pour objectif d'extraire des informations fonctionnelles des données haut-débit représentées sous forme de graphes. Ceci concerne, par exemple, les données d'interaction protéines-protéines, les données métaboliques ou même les données génomiques. Dans un premier temps nous proposons un formalisme précis, qui s'appuie sur les notions de graphe de données stratifié et de multigraphe d'alignement (MGA), et qui définit les alignements multiples locaux en autorisant notamment un réglage de la conservation de la topologie entre les réseaux. Nous présentons ensuite un algorithme de construction et partitionnement ''à la volée" du MGA, qui permet de traiter de façon efficace l'alignement de nombreux réseaux biologiques. Dans un second temps, nous étendons le formalisme pour parvenir à retrouver des alignements - que nous qualifions de ''partiels" - lorsqu'il y a des noeuds manquants sur certains réseaux. Nous détaillons les algorithmes associés, puis nous proposons différentes améliorations, et des variantes adaptées à des problèmes biologiques particuliers.

Interference from other adjacent users in wireless applications is a major problem in direct-sequence code-division multiple-access (DS-CDMA). This is also known as the near-far problem where a strong signal from one user interferes with other users. The current approach to deal with the near-far problem in DS-CDMA systems is to use strict transmitter power control. An alternative approach is to use near-far resistant receivers. The practical near-far resistance receiver structure is the adaptive decorrelating detectors since it avoids complex matrix inversion. The existing CDMA standard known as IS-95 uses a long signature code sequence. However for simplicity, the adaptive multi-user receiver uses short signature code sequence. The problem is that adaptive receivers lose near-far resistance as the number of users increases in the system. This thesis describes a novel method of multistage decision feedback cancellation (DFC) scheme immune from the near-far problem. The performance of the new DFC structure is constructed using three different adaptive algorithms: the least mean squared (LMS), the recursive least squared (RLS) and the linearly constraint constant modulus (LCCM) adaptive algorithms. It is found that LMS adaptive algorithm provides the best result considering its simple hardware complexity. It is also found that the LMS adaptive receiver along with the DFC structure provides a better bit synchronization capability to the over all system. Since the receiver is near-far resistant, the LMS adaptive receiver along with the decision feedback cancellation structure also performs better in the presence of Rayleigh fading. / Graduation date: 1998

IS-95, an interim standard proposed for future digital personal communications systems, uses two levels of encoding of digital data for error control and compatibility with code-division multiple access (CDMA) transmission. The data is first convolutionally encoded and the resulting symbols are interleaved and then groups are encoded as orthogonal Walsh sequences. Decoding these two separate encodings is traditionally done in separate sequential steps. By combining the decoding and applying feedback of the final decision of the second level of decoding to the first level decoder it is possible to reduce the error rate of the decoder. Each Walsh sequence encodes six non-adjacent symbols of the convolutional code. The receiver computes an estimate of the probability that each of the sixty-four possible Walsh sequences has been sent, and uses this estimate as an estimate for each of the convolution symbols which specified the Walsh sequence. Since the convolution symbols are non-adjacent, it is likely that the actual value of some of the earlier symbols will have been determined by the final decoder before later symbols specifying the same Walsh sequence are used by the convolution decoder. The knowledge of the values of these symbols can be used to adjust the probability estimates for that Walsh sequence, improving the likelihood that future convolutional symbols will be correctly decoded. Specific metrics for estimating probabilities that each convolutional symbol was sent were tested with and without the proposed feedback, and error rates were estimated based on extensive computer simulations. It was found that applying feedback does improve error rates. Analytical methods were also applied to help explain the effects. / Graduation date: 1996

A new method for multi-objective optimization of linear and mixed programs based on Lagrange multiplier methods is developed. The method resembles, but is distinct from, objective function weighting and goal programming methods. A subgradient optimization algorithm for selecting the multipliers is presented and analyzed. The method is illustrated by its application to a model for determining the weekly re-distribution of railroad cars from excess supply areas to excess demand areas, and to a model for balancing cost minimization against order completion requirements for a dynamic lot size model.

Multivariate statistics play an important role in performance analysis of wireless communication systems in correlated fading channels. This thesis presents a framework which can be used to derive easily computable mathematical representations for some multivariate statistical distributions, which are derivatives of the Gaussian distribution, and which have a particular correlation structure. The new multivariate distribution representations are given as single integral solutions of familiar mathematical functions which can be evaluated using common mathematical software packages. The new approach can be used to obtain single integral representations for the multivariate probability density function, cumulative distribution function, and joint moments of some widely used statistical distributions in wireless communication theory, under an assumed correlation structure. The remarkable advantage of the new representation is that the computational burden remains at numerical evaluation of a single integral, for a distribution with an arbitrary number of dimensions. The new representations are used to evaluate the performance of diversity combining schemes and multiple input multiple output systems, operating in correlated fading channels. The new framework gives some insights into some long existing open problems in multivariate statistical distributions. / Communications

Thesis (M.S.)--University of Delaware, 2006. / Principal faculty advisor: Cheng-Shun (Richard) Fang, Dept. of Health, Nutrition, and Exercise Sciences. Includes bibliographical references.

No description available.

Multiple Sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. Over 80% of MS patients are in the relapsing remitting stage. Symptoms range from fever, fatigue, emotional distress, tingling, numbness, optic neuritis, spasticity, muscle weakness, impaired coordination, to other abnormal neurological problems. Expression of symptoms is known as a relapse or exacerbation. The cause of relapses is unknown, but multiple factors seem to play a significant role. Possible factors that may influence MS onset and relapse consist of a genetic association, viruses, disruption of the blood-brain barrier, and stress. Stress has shown to have negative implications and may stimulate relapses. Thus, this study examined a possible stress intervention that most people already had available to them, companion animals. Companion animals have been shown to lower blood pressure, decrease heart rate, provide social support, and reduce stress. The main hypothesis was to evaluate whether or not pet ownership and/or attachment influenced the perceived stress level and number of negative life events experienced by MS patients in the relapsing remitting stage. Participants were given a questionnaire that consisted of 7 surveys. The questionnaire accessed quality of life, disease severity, number of negative life events, perceived stress level, level of depression, social support, and pet ownership and attachment level. Our sample population consisted of MS patients seen at the University of Texas Southwestern Neurology clinic from February 23rd to May 21st, 2004. One hundred and forty seven relapsing remitting MS patients were included in the study. Multiple linear regression was used to compare the relationship of stress and number of negative life events to pet ownership and attachment. Results revealed that pet ownership and attachment levels did not affect the stress level and number of negative life events of MS patients. No confounders were identified. Interaction terms with disease severity as the dependent variable, pet ownership and perceived stress level or negative life events as the independent variables were not significant. The type of pet owned did not influence the attachment level of the MS patient. In conclusion, the results of this study did not support the hypothesis.