Search results

The purpose of this paper is to propose a model for a target searching problem in a two-dimensional region with time constraints. The proposed model facilitates the search operation by minimizing the mission time and fuel usage, and the search operation is performed by a set of agents divided into a number of groups.

The authors have applied optimization techniques, Cartesian product, inclusion–exclusion principle, cooperative strategy, Shapley value, fuzzy Shapley function and Choquet integral to model the problem.

The proposed technique optimizes the placement of base stations that minimizes the sortie length of the agents. The results show that the cooperative strategy outperforms the non-cooperative strategy. The Shapley values quantify the rewards of each group based on their contributions to the search operation, whereas the fuzzy Shapley values determine the rewards of each group based on their contributions and level of cooperation in the search operation.

The proposed model can be applied to model many real-time problems such as patrolling in international borders, urban areas, forests and managing rescue operations after natural calamities, etc. Therefore, defence organizations, police departments and other operation management sectors will be benefitted by applying the proposed approach.

To the best of the authors’ knowledge, determining the optimal locations of base stations in a region is not explored in the existing works on target searching problems with fuel constraints. The proposed approach to cooperatively search the targets in a region is new. Introducing the Shapley function and fuzzy Shapley function is a novel idea to quantify the rewards of each group based on their contributions and level of cooperation in the search operation. This paper addresses these unexplored areas.

Visual Distinctive Language (VDL)-based iconic tags are structured visual information annotation. They explicate the content and organization of tagged information by graphical and symbolic features in order to improve the vocabulary problems of textual tags. The purpose of this paper is to investigate how these special icons help in tagged-based user information searching.

A two-stage experiment was designed and conducted so as to follow and quantify the searching process in specific searching target case and no specific searching target case when using VDL-based iconic tags.

The experimental results manifested that VDL-based iconic tags enhanced the role of tag in information searching. They could make user better understand tag clusters, which, in turn, provide global structure of involved topics. Also, VDL-based iconic tags helped user to find out searching target more quickly with higher accuracy by taking advantages of visual representation of tag categories and symbolic signification of tag content.

This study is one of the first to verify how structured icons work in information searching and how user’s graphical cognition impacts on tag-based information searching process. The research findings are dedicated to the theory of VDL-based iconic tags, as well as to a new visualization method for search user interface design.

Limitations of traditional Boolean searching are claimed to be overcome by two alternative search systems: DR‐LINK, a linguistic search system, and TARGET, a relevance ranking system. This paper compares the system and search features of both and describes conceptual differences in system design. A series of test questions was developed to test the retrieval effectiveness of both search systems. A controlled dataset was used to measure the results. System features are compared and discussed. Relevance overlap and search capabilities are evaluated and results are presented.

This study aims to propose and evaluate a searching scheme for a bichromatic reverse k-nearest neighbor (BRkNN) that has objects and queries in spatial networks. In this proposed scheme, the author’s search for the BRkNN of the query using an influence zone for each object with a network Voronoi diagram (NVD).

The author’s analyze and evaluate the performance of the proposed searching scheme.

The contribution of this paper is that it confirmed that the proposed searching scheme gives shorter processing time than the conventional linear search.

A future direction of this study will involve making a searching scheme that reduces the processing time when objects move automatically on spatial networks.

In BRkNN, consider two groups in a convenience store, where several convenience stores, which are constructed in Groups A and B, operate in a given region. The author’s can use RNN is RkNN when k = 1 (RNN) effectively to set a new store considering the Euclidean and road distances among stores and the location relationship between Groups A and B.

In the proposed searching scheme, the author’s search for the BRkNN of the query for each object with an NVD using the influence zone, which is the region where an object in the spatial network recognizes the nearest neighbor for the query.

The purpose of this paper is to propose a model for a two-agent multi-target-searching scenario in a two-dimensional region, where some places of the region have limited resource capacity in terms of the number of agents that can simultaneously pass through those places and few places of the region are unreachable that expand with time. The proposed cooperative search model and Petri net model facilitate the search operation considering the constraints mentioned in the paper. The Petri net model graphically illustrates different scenarios and helps the agents to validate the strategies.

In this paper, the authors have applied an optimization approach to determine the optimal locations of base stations, a cooperative search model, inclusion–exclusion principle, Cartesian product to optimize the search operation and a Petri net model to validate the search technique.

The proposed approach finds the optimal locations of the base stations in the region. The proposed cooperative search model allows various constraints such as resource capacity, time-dependent unreachable places/obstacles, fuel capacities of the agents, two types of targets assigned to two agents and limited sortie lengths. On the other hand, a Petri net model graphically represents whether collisions/deadlocks between the two agents are possible or not for a particular combination of paths as well as effect of time-dependent unreachable places for different combination of paths are also illustrated.

The problem addressed in this paper is similar to various real-time problems such as rescue operations during/after flood, landslide, earthquake, accident, patrolling in urban areas, international borders, forests, etc. Thus, the proposed model can benefit various organizations and departments such as rescue operation authorities, defense organizations, police departments, etc.

To the best of the authors’ knowledge, the problem addressed in this paper has not been completely explored, and the proposed cooperative search model to conduct the search operation considering the above-mentioned constraints is new. To the best of the authors’ knowledge, no paper has modeled time-dependent unreachable places with the help of Petri net.

The purpose of this paper is to present a hybrid method of intelligent optimization algorithm and Receding Horizon Control. The method is applied to solve the problem of cooperative search of multi‐unmanned aerial vehicles (multi‐UAVs).

The intelligent optimization of Differential Evolution (DE) makes the complex problem of multi‐UAVs cooperative search a regular function optimization problem. To meet the real‐time requirement, the idea of Receding Horizon Control is applied. An Extended Search Map based on hormone information is used to describe the uncertain environment information.

Simulation results indicate effectiveness of the hybrid method in solving the problem of cooperative search for multi‐UAVs.

The paper presents an interesting hybrid method of DE and Receding Horizon Control for the problem of cooperative multi‐UAVs.

Finding specific information on the Web can be difficult and time‐consuming due to the Web’s tremendous size and the current speed of network connections. Information agents that search the Web on behalf of users are invaluable. Since information needs are diverse, there should be tools for users to build their own agents that specialize in finding the information they want. These tools should be usable by non‐programmers. This paper describes ARIS, a shell for constructing information agents without coding. Our approach is akin to expert system shells, where the user supplies the knowledge for each specialist agent, and a common engine utilizes the agents’ knowledge. An agent’s search is guided by knowledge about how Web sites in a given domain are typically structured. We also report on our experiences with two agents built using ARIS.

The purpose of this paper is to describe the experiences of developing an open source federated searching tool. It is hoped that it will generate interest not only in dbWiz, but in the many other open source projects either completed or in development at the Simon Fraser University Library and at other libraries around the world.

The methods used in this paper include reviewing of related literature, analysis of other federated search tools, and the observation and description of the development process at the Simon Fraser University Library.

The paper discusses the benefits and challenges faced in developing an open source federated searching tool for libraries. As a case study, it demonstrates the strength of the collaborative, open source development model. The paper also describes the key features required of any federated searching tool.

Federated searching is becoming an important new product for both academic and public libraries, with several commercial products to choose from. This paper describes the development of an open source federated search tool that provides a low‐cost, yet highly functional alternative for the wider library community.

This paper aims to present a distributed Bayesian approach with connectivity maintenance to manage a multi-agent network search for a target on a two-dimensional plane.

The Bayesian framework is used to compute the local probability density functions (PDFs) of the target and obtain the global PDF with the consensus algorithm. An inverse power iteration algorithm is introduced to estimate the algebraic connectivity λ₂ of the network. Based on the estimated λ₂, the authors design a potential field for the connectivity maintenance. Then, based on the detection probability function, the authors design a potential field for the search target. The authors combine the two potential fields and design a distributed gradient-based control for the agents.

The inverse power iteration algorithm can distributed estimate the algebraic connectivity by the agents. The agents can efficient search the target with connectivity maintenance with the designed distributed gradient-based search algorithm.

Previous study has paid little attention to the multi-agent search problem with connectivity maintenance. Our algorithm guarantees that the strongly connected graph of the multi-agent communication topology is always established while performing the distributed target search problem.

The purpose of this paper is to present a method to realize the flexible and lightweight integration of general web applications.

The information extraction and functionality emulation method are proposed to realize the web information integration for the general web applications. All the processes of web information searching, submitting and extraction are run at client‐side by end‐user programming like a real web service.

The implementation shows that the required programming techniques are within the abilities of general web users, and without needing to write too many programs.

A Java‐based class package was developed for web information searching/submitting/extraction, which users can integrate easily with the general web applications.