The path search problem considers a simple model of communication networks as channel graphs: directed acyclic graphs with a single source and sink. We consider each vertex to represent a switching point, and each edge a single communication line. Under a probabilistic model where each edge may independently be free (available for use) or blocked (already in use) with some constant probability, we seek to efficiently search the graph: examine (on average) as few edges as possible before determining if a path of free edges exists from source to sink. We consider the difficulty of searching various graphs under different search models, and examine the computational complexity of calculating the search cost of arbitrary graphs.

Determining the identity and pose of occluded objects from noisy data is a critical step in interacting intelligently with an unstructured environment. Previous work has shown that local measurements of position and surface orientation may be used in a constrained search process to solve this problem, for the case of rigid objects, either two-dimensional or three-dimensional. This paper considers the more general problem of recognizing and locating objects that can vary in parameterized ways. We consider objects with rotational, translational, or scaling degrees of freedom, and objects that undergo stretching transformations. We show that the constrained search method can be extended to handle the recognition and localization of such generalized classes of object families.

Determining the identity and pose of occluded objects from noisy data is a critical part of a system's intelligent interaction with an unstructured environment. Previous work has shown that local measurements of the position and surface orientation of small patches of an object's surface may be used in a constrained search process to solve this problem for the case of rigid polygonal objects using two-dimensional sensory data, or rigid polyhedral objects using three-dimensional data. This note extends the recognition system to deal with the problem of recognizing and locating curved objects. The extension is done in two dimensions, and applies to the recognition of two-dimensional objects from two-dimensional data, or to the recognition of three-dimensional objects in stable positions from two- dimensional data.

This master’s thesis, conducted at Sectra Medical Systems AB, investigates the feasibility of integrating a search platform, built on modern search technology, into the complex architecture of existing products. This was done through the implementation and integration of a search platform prototype, called Sectra Enterprise Search. It was built upon the search engine library Lucene.NET, written in C# for the Microsoft .NET Framework. Lucene.NET originates from the Java library Lucene, which is highly regarded and widely used for similar purposes. During the development process a lot of requirements for the search platform were identified, including high availability, scalability and maintainability. Besides full text search for information in a variety of data sources, desirable features include autocompletion and highlighting. Sectra Enterprise Search was successfully integrated within the architecture of existing products. The architecture of the prototype consists of multiple layers, with the search engine functionality at the very bottom and a web service handling all incoming request at the top. To sum up, integrating a search platform based on modern search technology into the architecture of existing products infers full control of deployment, users searching in a more intuitive manner and reasonable search response times.

The most popular methods for solving the shortest-path problem in Artificial Intelligence are heuristic search algorithms. The main contributions of this research are new heuristic search algorithms that are either faster or scale up to larger problems than existing algorithms. Our contributions apply to both online and offline tasks. For online tasks, existing real-time heuristic search algorithms learn better informed heuristic values and in some cases eventually converge to a shortest path by repeatedly executing the action leading to a successor state with a minimum cost-to-goal estimate. In contrast, we claim that real-time heuristic search converges faster to a shortest path when it always selects an action leading to a state with a minimum f-value, where the f-value of a state is an estimate of the cost of a shortest path from start to goal via the state, just like in the offline A* search algorithm. We support this claim by implementing this new non-trivial action-selection rule in FALCONS and by showing empirically that FALCONS significantly reduces the number of actions to convergence of a state-of-the-art real-time search algorithm. For offline tasks, we improve on two existing ways of scaling up best-first search to larger problems. First, it is known that the WA* algorithm (a greedy variant of A*) solves larger problems when it is either diversified (i.e., when it performs expansions in parallel) or committed (i.e., when it chooses the state to expand next among a fixed-size subset of the set of generated but unexpanded states). We claim that WA* solves even larger problems when it is enhanced with both diversity and commitment. We support this claim with our MSC-KWA* algorithm. Second, it is known that breadth-first search solves larger problems when it prunes unpromising states, resulting in the beam search algorithm. We claim that beam search quickly solves even larger problems when it is enhanced with backtracking based on limited discrepancy search. We support this claim with our BULB algorithm. We show that both MSC-KWA* and BULB scale up to larger problems than several state-of-the-art offline search algorithms in three standard benchmark domains. Finally, we present an anytime variant of BULB and apply it to the multiple sequence alignment problem in biology.

For the sake of maintaining people¡¦s safety and property at sea, IMO adopted the International Convention on Maritime Search and Rescue in 1979 which regulates all Parties shall ensure that necessary arrangements are made for the provision of adequate search and rescue services for persons in distress at sea round their coasts. Furthermore, the 2nd paragraph of Article 98 of United Nations Convention on the Law of the Sea, 1982, says every coastal State shall promote the establishment, operation and maintenance of an adequate and effective search and rescue service regarding safety on and over the sea and, where circumstances so require, by way of mutual regional arrangements cooperate with neighbouring States for this purpose. Thus, for the humanitarian and live saving at sea as well as complying with the relevant international conventions, prosecution of search and rescue at sea is the privilege for the competent authority and relating originations of our government. Accurate computation of drifting and well-planned search and rescue activity cope with prompt search and rescue prosecution are the key elements for successful rescue at sea. Nowadays, Taiwan government faces some problems. One is no search and rescue information system as US, UK and Canada installed to calculate the drifting of people or ships in distress promptly. Second is lack of thorough ocean data. Even though the SAR information system which was purchasing from other country has been installed, the accuracy will be reduced due to the uncompleted surrounding ocean wind and current data. Therefore, the author study the Search and Rescue Optimal Planning System (SAROPS) of US coast guard in order to provide suggestions for the relevant rescue units in Taiwan when establishing the similar system to promote the Search and Rescue efficiency and adopt scientific planning methodology

Research in international business and strategy emphasizes the important role knowledge plays in foreign expansion, and multiple research perspectives have viewed a firm‘s knowledge as the key driver of competitive advantage. Thus, in today‘s business environment, the ability to learn and source knowledge across boundaries is important to both firm performance and strategic change. My dissertation examines the ―knowledge-seeking‖ motive for international expansion, which suggests that firms expand abroad to gain new technical capabilities and knowledge from diverse institutions, which allow firms to change in dynamic markets. I extend organizational learning, the resource-based view, and internationalization theory to examine empirically how internationalization influences strategic changes by affecting exploratory search. This research also challenges the standard assumptions about the positive benefits of exploration on change, suggesting that a curvilinear relationship exists. Further, I argue that innovation capabilities enhance the relationship between strategic change and firm performance. These questions are examined using longitudinal data on pharmaceutical firms. The findings from this analysis reveal that internationalization has a curvilinear relationship with exploratory search. In addition, speed of internationalization, rhythm of internationalization, and international experience moderate the relationship between internationalization and exploratory search. Exploratory search was found to have an inverted U-shaped relationship with strategic change, suggesting the high exploratory search may negatively affect the firm. The analysis also revealed innovation capabilities negatively moderated the relationship between strategic change and firm performance (ROA). This study provides important contributions to the fields of strategic management, international business, and organizational learning.

Events of significant impact as recent as hurricane Ike yielded a consistent disturbing truth: we lack sufficient numbers of competent search dog [Canis familiaris] teams. This study was conceived to provide information in identifying factors involved in training competent search dogs. Obedience training methods, age training was initiated, previous handler canine training experience, and handler perception and emotional attachment to their search dog were examined through a sixty-six question survey. Achievement of a national certification was used as a measure of performance success. Association between factors and performance success was evaluated through Chi-Square testing. Surveys were announced through the National Search Dog Alliance (NSDA) and were available online; 177 were fully completed by respondents and used in the data analysis. Seventy-two percent of nationally certified canine team respondents preferred positive reinforcement methods. Several statistically significant associations were detected: (a) female handlers preferred positive reinforcement training methods [x^2 = 8.504, d.f.=1, P = 0.004], (b) as dogs matured use of active training equipment increased [x^2 = 54.043, d.f.= 2, P < 0.001]., and (c) four hours or more time spent training each week had a higher proportion of national certifications [x^2 = 16.379, d.f. = 1, P less than 0.001]. The data also indicated a trend for handlers to have previous canine training experience equal to or greater than search dog training experience [x^2 = 118.36, d.f. = 9, P =0.05]. The results warrant further research on the effects of early training, the effects of training time investment, and the interaction between canine selection and handler understanding of canine learning theory.

Steel construction materials are very common use for factory and high building in nearly years. Generally speaking the steel construction material is refers has the fixed cross section the steel products. Like rolling H, the T section, the light channel steel, the angle steel and so on all are. But their order characteristic for depends on the length order, also can be different regarding the different length its unit weight price. Manages in not the easy situation in the present enterprise, saved the material cost already to change can it be that is often important, All company shall consider for its huge material storage. Regarding the company huge stock information bank system in, frequently the existence permits the material which how long year hasn't used, finally really very is big by the waste treatment regarding company's loss. So material cutting plane is an important work for those fabrication company. A good cutting plane is directly effect the used percentage, material cost, transportation cost, moving efficiency are also an important effects points, Therefore a good combination for cutting plan can obvious lower material cost, also good help for cutting efficiency, The research of Tabu search shall be use to steel construction material combination and becoming an good effective calculation method to reach three purpose as follow: 1.Considers the multi-objective of material fixed number of years, the spillage of material and the material cost, that material best arrangement combination solution or approximate best solution. 2.Develop algorithm for actuality using in materials combination so all fabrication company can use this method to reduce their cost. 3.Collection all remain material and make it together to save moving time. The result showed obtains the solution by the Tabu Search method to be possible the effective reduced material purchase quantity; also remainder centralism also has the very good improvement.

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