• The Journal of Information Systems
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• v.14 no.3
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• pp.17-22
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• 2005

Location management is very important in location-based services to provide services to the mobile users like banking, city guides and many more. Ubiquitous and mobile devices are the source of data in location management and its significant operations are update and search method. Some studies to improve these were presented by using optimal sequential paging, location area scheme and hierarchical database scheme. In addition, not all location services have the same access methods on data and it lead to difficulties of providing services. A proposed location management of multi-agent architecture is presented in this study. It shows the coordination of the agents on the distributed database of location-based services. The proposal focuses on the location management of the mobile object presented in a hierarchical search and update. Also, it uses a nearest neighbor technique for efficient search method of mobile objects.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.1_2
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• pp.80-89
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• 2001

The development in the mobile computing systems have arisen new and previously unforeseen problems, such as problems in information management of mobile host, disconnection of mobile host and low bandwidths of wireless communications. Especially, location information management strategy of mobile host results in an increased overhead in mobile computing systems. Due to the mobility of the mobiles host, the changes in the mobile host's address depends on the mobile host's location, and is maintained by mapping physical address on virtual address, Since previously suggested several strategies for mapping method between physical address and virtual address did not tackle the increase of mobile host and distribution of location information, it was not able to support the scalability in mobile computing systems. Thus, to distribute the location inrormation, we propose an advanced n-depth LiST (Location information Search Tree) and the parallel location search and update strategy based on the advanced n-depth LiST. The advanced n-depth LiST is logically a hierarchical structure that clusters the location information server by ring structure and reduces the location information search and update cost by parallel seatch and updated method. The experiment shows that even though the distance of two MHs that communicate with each other is large, due to the strnctural distribution of location information, advanced n-depth LiST results in good performance. Moreover, despite the reduction in the location information search cost, there was no increase in the location information update cost.

• Journal of the Semiconductor & Display Technology
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• v.7 no.4
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• pp.57-62
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• 2008

Image retrieval is one of the most exciting and rapidly growing research issues in the field of multimedia technology. This paper proposes a new method that performs search the relevant images by using query-by-example. The proposed method for search and retrieval of images utilizes the location information where the image had been taken. The system associates the photo images with their corresponding GPS coordinates that are used as metadata for searching. Experimental results show that the proposed method demonstrates better performance improving up to 59% of average recall and 49% of average precision. Moreover, we learned from the experimental results geo-location information embedded within the image header is more effective and positive on the search and storage.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.79-88
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• 2015

The web search engines are exposed to the issue of uncertainty because of ambiguous queries, being input for retrieving the accurate results. Ambiguous queries constitute a significant fraction of such instances and pose real challenges to web search engines. Moreover, web search has created an interest for the researchers to deal with search by considering context in terms of location perspective. Our proposed disambiguation approach is designed to improve user experience by using context in terms of location relevance with the document relevance. The aim is that providing the user a comprehensive location perspective of a topic is informative than retrieving a result that only contains temporal or context information. The capacity to use this information in a location manner can be, from a user perspective, potentially useful for several tasks, including user query understanding or clustering based on location. In order to carry out the approach, we developed a Java based prototype to derive the contextual information from the web results based on the queries from the well-known datasets. Among those results, queries are further classified in order to perform search in a broad way. After the result provision to users and the selection made by them, feedback is recorded implicitly to improve the web search based on contextual information. The experiment results demonstrate the outstanding performance of our approach in terms of precision 75%, accuracy 73%; recall 81% and f-measure 78% when compared with generic temporal evaluation approach and furthermore achieved precision 86%, accuracy 71%; recall 67% and f-measure 75% when compared with web document clustering approach.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.437-444
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• 2012

In this paper, we propose a method for predicting a user's location based on their past movement patterns. There is no restriction on the length of past movement patterns when using this method to predict the current location. For this purpose, a modified search tree has been devised. The search tree is constructed in an effective manner while it additionally learns the movement patterns of a user one by one. In fact, the time complexity of the learning process for a movement pattern is linear. In this process, the search tree expands to take into consideration more details about the movement patterns when a pattern that conflicts with an existing trained pattern is found. In this manner, the search tree is trained to make an exact matching, as needed, for location prediction. In the experiments, the results showed that this method is highly accurate in comparison with more complex and sophisticated methods. Also, the accuracy deviation of users of this method is significantly lower than for any other methods. This means that this method is highly stable for the variations of behavioral patterns as compared to any other method. Finally, 1.47 locations were considered on average for making a prediction with this method. This shows that the prediction process is very efficient.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.243-258
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• 2011

With increasing interest in ubiquitous computing technology, an infrastructure for the short-distance wireless communication has been extended socially, bringing spotlight to the security system using the image or location. In case of existing security system, there have been issues such as the occurrences of blind spots, difficulty in recognizing multiple objects and storing of the unspecified objects. In order to solve this issue, zone-based location-estimation search system for the image have been suggested as an alternative based on the real-time location determination technology combined with image. This paper intends to suggest the search service for the image zone-based location-estimation. For this, it proposed the location determination algorism using IEEE 802.15.4/ZigBee's RSSI and for real-time image service, the RTP/RTCP protocol was applied. In order to combine the location and image, at the event of the entry of the specified target, the record of the time for image and the time of occurrence of the event on a global time standard, it has devised a time stamp, applying XML based meta data formation method based on the media's feature data based in connection with the location based data for the events of the object. Using the proposed meta data, the service mode which can search for the image from the point in time when the entry of the specified target was proposed.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.1-8
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• 2020

In this paper, we propose an optimal path search algorithm between each node and midpoint that applies the time weighting. Services for using a location of mid point usually provide a mid point location-based on the location of users. There is a problem that is not efficient in terms of time because a location-based search method is only considered for location. To solve the problem of the existing location-based search method, the proposed algorithm sets the weights between each node and midpoint by reflecting user's location information and required time. Then, by utilizing that, it is possible to search for an optimum path. In addition, to increase the efficiency of the search, it ensures high accuracy by setting weights adaptively to the information given. Experimental results show that the proposed algorithm is able to find the optimal path to the midpoint compared with the existing method.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.639-647
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• 2020

In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.135-138
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• 2020

This paper suggests a method of automatic clustering to search of relevant digital photos using geo-coded information. The provided scheme labels photo images with their corresponding global positioning system coordinates and date/time at the moment of capture, and the labels are used as clustering metadata of the images when they are in the use of retrieval. Experimental results show that geo-location information can improve the accuracy of image retrieval, and the information embedded within the images are effective and precise on the image clustering.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.