Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 130-144).

ICESat consisted of the Geoscience Laser Altimeter System (GLAS) and a commercial spacecraft bus. The stability of the GLAS to bus alignment was unknown and significant for GLAS pointing. Pointing control was performed by the bus, and variations of the GLAS alignment were effectively pointing control errors. There were four star trackers making measurements sensitive to this alignment, two on GLAS and two on the bus. Tracker pointing variations during samples from seven years of flight data were estimated using an alignment filter. The states of an alignment filter represent multiple independent attitudes, enabling the fusion of measurements from an arbitrary number of trackers and gyro units. The ICESat alignment filter states were equivalent to four tracker pointing vectors, expressed in both the body and celestial frames. Together with a star catalog, the four pointing vectors were equivalent to predictions of the tracker measurements. The stars provided nearly ideal reference points, but filter performance was improved by detecting and handling deterministic star errors. The primary result was evidence for relatively large pointing variations of the two GLAS trackers, on the order of fifty arcseconds, with both periodic orbital variations and trends on long time scales. There was also evidence of correlations between the variations of the two GLAS trackers, suggesting that they reflected GLAS to bus alignment variations. / text

With the rapid development of genome sequencing, an ever-increasing number of molecular biology analyses rely on the construction of an accurate multiple sequence alignment (MSA), such as motifs detection, phylogeny inference and structure prediction. Although many methods have been developed during the last two decades, most of them may perform poorly on some types of inputs, in particular when families of sequences fall below thirty percent similarity. Therefore, this thesis introduced two different effective approaches to improve the overall quality of multiple sequence alignment. First, by considering the similarity of the input sequences, we proposed an adaptive approach to compute better substitution matrices for each pair of sequences, and then apply the progressive alignment method to align them. For example, for inputs with high similarity, we consider the whole sequences and align them with global pair-Hidden Markov model, while for those with moderate low similarity, we may ignore the ank regions and use some local pair-Hidden Markov models to align them. To test the effectiveness of this approach, we have implemented a multiple sequence alignment tool called GLProbs and compared its performance with one dozen leading tools on three benchmark alignment databases, and GLProbs' alignments have the best scores in almost all testings. We have also evaluated the practicability of the alignments of GLProbs by applying the tool to three biological applications, namely phylogenetic tree reconstruction, protein secondary structure prediction and the detection of high risk members for cervical cancer in the HPV-E6 family, and the results are very encouraging. Second, based on our previous study, we proposed another new tool PnpProbs, which constructs better multiple sequence alignments by better handling of guide trees. It classifies input sequences into two types: normally related sequences and distantly related sequences. For normally related sequences, it uses an adaptive approach to construct the guide tree, and based on this guide tree, aligns the sequences progressively. To be more precise, it first estimates the input's discrepancy by computing the standard deviation of their percent identities, and based on this estimate, it chooses the best method to construct the guide tree. For distantly related sequences, PnpProbs abandons the guide tree; instead it uses the non-progressive sequence annealing method to construct the multiple sequence alignment. By combining the strength of the progressive and non-progressive methods, and with a better way to construct the guide tree, PnpProbs improves the quality of multiple sequence alignments significantly for not only general input sequences, but also those very distantly related. With those encouraging empirical results, our developed software tools have been appreciated by the community gradually. For example, GLProbs has been invited and incorporated into the JAva Bioinformatics Analysis Web Services system (JABAWS). / published_or_final_version / Computer Science / Master / Master of Philosophy

This thesis is a collection of four manuscripts linked by the aim of extending strategic alignment thought into the knowledge management domain by explicitly including the concept of knowledge strategy into the discussion of strategic alignment. In the first paper, a set of common knowledge strategy dimensions was synthesized and used to link two existing knowledge strategy typologies. The key finding of the study was that the two typologies operated at different strategic levels, allowing for the creation of portfolios of the lower order types under each higher order type. In the second paper, a model of strategic alignment between business, information system and knowledge strategy was presented and tested using survey data. It was found that the combination of aligned information and knowledge strategies with their associated business strategy resulted in higher performance for defenders, analyzers and prospectors and that the alignment of non-viable strategies led to worse performance than individual non-viable strategies alone. In the third paper, case studies provided examples of alignment and misalignment which were used to populate a framework linking alignment and performance. Four explanations for firms’ location in the model were provided, focusing on appropriate versus inappropriate alignment, conscious versus unconscious misalignment, antagonistic alignment versus misalignment, and strategic alignment versus misalignment. In the final paper, the Strategic Orientation of Knowledge-Based Enterprises (STROKE) instrument was developed to capture the orientation of knowledge strategy employment in firms. During the development process, a new statistic was developed to aid in the validation of card sorts during the scale development step of instrument creation. / Thesis (Ph.D, Management) -- Queen's University, 2009-04-12 16:39:28.315

Integrated liquid-chromatography mass-spectrometry(LC-MS) is becoming a widely used approach for quantifying the protein composition of complex samples.In the last few years,this technology has been used to compare complex biological samples across multiple conditions. One challenge in the analysis of an LC-MS experiment is the alignment of peptide features across samples. In this paper,we proposed a new method using the peptide internal information (both LC-MS and LC-MS/MS information) to align features from multiple LC-MS experiments.We defined Anchor points which are data elements that are highly confident we have identified and are shared by both samples. We chose one sample as template data set, find Anchor points in this sample, then apply alignment to modify another sample, find Anchors in modified sample, these Anchors should line up with one another. One advantage of our method is that it allows statistical assessment of alignment performance. Use anchor points to perform alignment between samples, and labeling an objective performance in LC-MS.

No description available.

Saarbrücken, Univ., Diss., 1999. / Computerdatei im Fernzugriff.

Bielefeld, University, Diss., 2001. / Dateiformat: tgz, Dateien im PS-Format.

Frankfurt (Main), University, Diss., 2003.

The rapid growth of data hungry wireless applications has boosted the demand for wireless communication systems with improved reliability, wider coverage, and higher throughput. The main challenges facing the design of such systems are the limited resources, such as bandwidth, restricted transmission power, etc., and the impairments of the wireless channels, including fading effects, interference, and noise. Multiple-input multiple-output (MIMO) communication has been shown to be one of the most promising emerging wireless technologies that can efficiently enhance link reliability, improve system coverage, and boost the data transmission rate. Consequently, MIMO is now extensively adopted by many mainstream wireless industry standards, including 3GPP WCDMA/HSDPA, LTE, EVDO, WiFi, and WiMAX. By deploying multiple antennas at both transmitter and receiver sides, MIMO techniques license a new dimension (spatial dimension) that can be applied in various ways for combating the impairments of wireless networks. Furthermore, this new dimension has introduced a new concept known as Interference Alignment that can efficiently deal with the interference presentin the wireless communication networks. In particular, IA is highly attractive in terms of providing more degrees of freedom compared to techniques such as TDMA/FDMA. With this in mind, this thesis will focus on studying and developing advanced techniques and algorithms for reducing interference in cellular communication networks. The contributions of the thesis are as follows. Initially, a review is provided to reiterate some basic concepts of wireless communications and discuss the challenges faced by the techniques that deal with interference mitigation. Next, Chapter 3 presents a novel IA based cancellation scheme that is proposed for combating the interfering signals present in the compounded MIMO broadcast channels, where the users experience a multi-source transmission from several base stations. After defining the interference channel (IC) interference and X-channel interference, the partial transmit beamforming matrices of the closed-form downlink scheme alleviate the corresponding types of interference. Applying the proposed scheme allows one to treat the multi-cell network as a set of single-cell MIMO network, which leads to the simultaneous BER performance enhancement and data rate increase. Moreover, a generalization scheme is given to assign the appropriate antenna configuration for achieving maximum DoF. Furthermore, Chapter 4 demonstrates a comprehensive analysis on the number of DoF achievable by exploiting the transmit beamforming technique. Additionally, the proposed scheme is able to provide the maximum data rate under a certain antenna setting or compute a transmitter-receiver configuration in order to meet the required number of DoF. Chapter 5 considers a modified IA scheme for the compounded MIMO network when different classes of users communicate in the overlapped area. Due to various antenna settings of each receiver, the effect of spatial correlation on the achievable data rate is investigated. Moreover, an algorithm is derived for calculating the antenna configuration for different users classes. Then, the proposed scheme is extended for the case of Large-scale MIMO, which in turn provides sufficient insights into the impact of the deployment of a large number of antennas. Finally, Chapter 6 presents an alternative design of the IA scheme with no symbol extension for the cellular MIMO network. Subsequently, a modified eigenvalue-based scheme is proposed to enhance the overall system performance. Finally, the achievable data rate is calculated under different CSI acquisition scenarios. Chapter 7 concludes the thesis and provides a list of potential future work directions for further investigation.