Readers often encounter the need to explore a document only for a specific point of interest. We call the phenomena of approaching a narrative not for its entirety, but for a thread of a particular topic, thematic reading. Present reading tools and information retrieval techniques provide only limited assistance to readers in such a situation. Our research centers on this phenomenon. We conducted investigations on both human behavior and machine automation, with a goal of better meeting the requirements of thematic reading. To observe readers? behavior and understand their expectations, we implemented a reader?s interface with designs targeting the predicted needs of thematic readers. We conducted user studies using both the system and Microsoft Word. We proved that thematic reading is capable of achieving the goal of understanding a specific topic, at least to a degree that succeeds in topic-wise tasks. We also reached guidelines for designing future reading platforms in major aspects such as view, navigation, and contextual awareness. As for machine automation, we investigated the potential to automatically locate thematically relevant excerpts. This investigation was inspired by the editorial compilation of a textbook index. To increase the search performance, we proposed a two-step methodology which first expands the query with expansion and then filters the intermediate results by checking the term-occurrence proximity. For query expansion, we compared the query expansion with WordNet, morphological inflections, and both processes together. Our results show that in the context of our study, WordNet made almost no contribution to the enhancement of recall, while expansion with the inflectional variants turned out to be a successful and essential scheme. For the refinement section, the results show that the proximity check on the alternative phrases formed after inflectional expansion can effectively increase the precision of the previously acquired return results. We further tested a different scheme ? using sliding window ? of defining target and verification units in the methodology. Our findings show that the structural delimitations (sentences and chapters) outperformed sliding windows. The first scheme was able to achieve consistently desirable results, while the results from the second were inconclusive.

This study analyzes the relationship between the information search of internet users and the keywords advertising effects. According to the result of literature review, this study takes ¡§information search on the internet¡¨, four perceptual antecedents of keywords advertising including ¡§informativeness¡¨, ¡§irritation¡¨, ¡§entertainment¡¨ and ¡§credibility¡¨, ¡§advertising value¡¨ and ¡§advertising attitudes¡¨ as our dimensions to analyze the keywords advertising effects. This study adopts questionnaire survey method to collect sample information and the research targets are users who searched information on the internet and understood keywords advertising. This study finds that the higher degree of search of internet users, the greater the informativeness of keywords advertising they perceive, and the keyword advertising is more valuable thus, however, the search degree has no direct effect on keywords advertising. Moreover, informativeness, irritation, entertainment and credibility of keywords advertising all have effects upon the value of keywords advertising; irritation, entertainment and credibility of keywords advertising all have effects upon the attitudes toward keywords advertising. Finally, this study discovers that the value of keywords advertising has effect on the internet users¡¦ attitudes toward keywords advertising.

In this paper, in order to reduce the location update cost in wireless mobile networks, we propose a cooperative location update scheme. The proposed scheme first discovers the statistical relation between mobile stations according to their history of location update and paging. In order to reduce the total cost of mobility management, we propose integrating the cooperative location update scheme with the concurrent search scheme. We use analytical results and simulation results to justify the usage of the proposed approach.

With the state-of-the-art IC technology, we can share a variety of digital content stored in our mobile devices via wireless communications. When requests for digital content arrive, base stations have to search for at least one copy of the digital content. We extend the concurrent search approach to efficiently location digital content. In addition, we propose the opportunistic concurrent search scheme in which a base station could use a single channel to page a number of mobile stations simultaneously. We use computer simulations to evaluate the performance and justify the usage of the proposed schemes.

Multicasting in mobile ad hoc networks (MANETs) is an efficient method for group communications that has received considerable attention. However, developing a scalable, robust and efficient multicast method in MANETs is difficult owing to group membership management and the ability to maintain a multicast structure over a dynamic topology. This work presents a novel Robust Mesh-based Multicast Protocol (RMMP) that integrates the advantages of tree-based and mesh-based multicast protocols and reduces data recovery time when paths break. The proposed RMMP is performed in two ways. One is to construct a multicast structure using a binary tree, and the other is to provide a second-route discovery scheme. The former distributes transmission averagely among member nodes, and the latter reduces the number of articulation nodes to eliminate loss of data packets. Simulation results demonstrate that the RMMP is suitable for heavy traffic loads, and achieves a high delivery ratio. Furthermore, the RMMP is robust in recovering data transmission when paths break.

Taiwan is surrounded by ocean, we expect through the underwater survey could make us know more about the marine resources, history and culture and understand how to use the natural resource well. The purpose of this paper is to investigate the survey strategy for marine archaeology using modern underwater survey and identification instruments and techniques on Peng-Hu underwater cultural site survey. The survey process can be roughly divided into three stages, preliminary and comprehensive survey (PCS), double-check and localization survey (DLS), and precise and identification survey (PIS) respectively. The objective of PCS is not to miss any possible target. The major equipments of the underwater engineering including marine magnetometer, the subbottom profiler, and the side-scan sonar are deployed simultaneously. After the comparisons and analysis of the images from various instruments obtained from PCS and DLS, the PIS will obtain the direct photo viewing of the targets using remotely-operated vehicle (ROV) or divers. This strategy has been conducted firstly in Kaohsiung Sizihwan bay Marine Test Field and Kaohsiung Cross-Harbor Tunnels as the preliminary. Then move to Peng-Hu Sea Area for the underwater archaeology survey which is authorized by Acdemia Sinica from April 2008 to June 2009. From the result, the megnetometer can help sonar to identify the target more specifically, especially for the sediment. It brings better result than side-scan sonar and multi-beam echo sounder which can only search the target on seabed and can search broader area than subbottom profiler. Therefor, magnetomator is an essential equipment for underwater archology.

This thesis addresses a multi-agent search problem where several agents, equipped with sensors and communication devices, search an unknown area. Lack of information about the search space is modeled as an uncertainty density distribution. A sequential deploy and search (SDS) strategy is formulated where the agents are first deployed to maximize single step search effectiveness. To achieve an optimal deployment, a multi-center objective function defined using the Voronoi cells and the uncertainty distribution is optimized. It is shown that the critical points of this objective function are the centroids of the Voronoi cells. A proportional control law is proposed that makes the agents move to their respective “centroids”. Assuming agents to be first order dynamical systems and using LaSalle's invariance principle, it is shown that the closed-loop system converges globally asymptotically to the critical points. It is also shown that the sequential deploy and search strategy is spatially distributed with respect to the Delaunay graph corresponding to any given agent configuration. Next, a combined deploy and search (CDS) strategy is proposed where, instead of first deploying agents and then performing the search, the agents engage in search operation as they move toward the centroids. This strategy gives rise to shorter agent trajectories compared to the SDS strategy. Then the problem is formulated with practical constraints such as sensor range limits and limit on maximum speed of the agents. A few issues relating to implementation of the proposed search strategies are also addressed. Finally, the assumption of homogeneous agents is relaxed and agents equipped with sensors with heterogeneous capabilities are considered. A generalized Voronoi partitioning scheme is proposed and used to formulate a heterogeneous locational optimization problem. In this problem the agents are deployed in the search space optimizing the sensor effectiveness. As earlier, the two search strategies are proposed. Simulation experiments are carried out to validate the performance of the proposed search strategies. The simulation results indicate that both the proposed search strategies perform quite well even when the conditions deviated from the nominal. It is also shown that the combined deploy and search strategy leads to shorter and smoother trajectories than those of the sequential deploy and search strategy with the same parameters.

<p>With increasing size of sequence databases heuristic search approaches have become necessary. Hidden Markov models are the best performing search methods known today with respect to discriminative power, but are too time complex to be practical when searching in large sequence databases. In this report, heuristic algorithms that reduce the search space before searching with traditional search algorithms of hidden Markov models are presented and experimentally validated. The results of the validation show that the heuristic search algorithms will speed up the searches without decreasing their discriminative power.</p>

Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2004. / Includes bibliographical references (p. 37-38).

Thesis (M.S.)--University of Florida, 2002. / Title from title page of source document. Includes vita. Includes bibliographical references.