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.
The purpose of this study is to analyze information search activity in purchasing behavior of household electric goods. Qusetionare survey method was used in this research. The sample was taken from 302 housewives living in Seoul, from 9th of Nov. to 20th of Nov, in 1991. Used statical methods were Frequency, Percentage, Crosstab, Anova, and Regression Analysis. The major findings are summarized as follows : 1) Component elements of information search : The means of acquiring information is that friends, neighbors, sales are most. A cause of choosing information is the sequence of satisfaction after using, easiness of interaction. The time in choosing goods is more month. 2) Component element of information search as social economic status housewife : children numbers and means of acquiring information(P<.01), education and a cause of choosing information(P<.05), life cost per month and a cause of choosing information(P<.05), social economic status and a time information search are significant. 3) A perception of risk as searching information : Among searching content of information a price influence a perception of risk. 4) Content of searching information and satisfaction of purchasing experience : Best choice is significant as quality of goods, difference of quality is significant as safety and degree of offering information is significant as a brand. 5) Satisfaction of purchasing experience following practical use of information : Best choice is significant as viewing of an exhibit and opinion of user. Difference of quality is not significant as any vairable. Degree of offer information influence searching pamphlet, searching an advertisement and opinion of user. 6) A perception of risk following source of an information : A perception of risk is most influenced by pamphlet.
With the development of related technologies, Location-Based Services (LBS) are growing fast and being used in many ways. Past LBS studies have focused on adoption of LBS because of the fact that LBS users have privacy concerns regarding revealing their location information. Meanwhile, the number of LBS users and revenues from LBS are growing rapidly because users can get some benefits by revealing their location information. Little research has been done on how LBS affects consumers' information search behavior in product purchase. The purpose of this paper is examining the effect of LBS information filtering on buyers' uncertainty and their information search behavior. When consumers purchase a product, they try to reduce uncertainty by searching information. Generally, there are two types of uncertainties - knowledge uncertainty and choice uncertainty. Knowledge uncertainty refers to the lack of information on what kinds of alternatives are available in the market and/or their important attributes. Therefore, consumers having knowledge uncertainty will have difficulties in identifying what alternatives exist in the market to fulfil their needs. Choice uncertainty refers to the lack of information about consumers' own preferences and which alternative will fit in their needs. Therefore, consumers with choice uncertainty have difficulties selecting best product among available alternatives.. According to economics of information theory, consumers narrow the scope of information search when knowledge uncertainty is high. It is because consumers' information search cost is high when their knowledge uncertainty is high. If people do not know available alternatives and their attributes, it takes time and cognitive efforts for them to acquire information about available alternatives. Therefore, they will reduce search breadth. For people with high knowledge uncertainty, the information about products and their attributes is new and of high value for them. Therefore, they will conduct searches more in-depth because they have incentive to acquire more information. When people have high choice uncertainty, people tend to search information about more alternatives. It is because increased search breadth will improve their chances to find better alternative for them. On the other hand, since human's cognitive capacity is limited, the increased search breadth (more alternatives) will reduce the depth of information search for each alternative. Consumers with high choice uncertainty will spend less time and effort for each alternative because considering more alternatives will increase their utility. LBS provides users with the capability to screen alternatives based on the distance from them, which reduces information search costs. Therefore, it is expected that LBS will help users consider more alternatives even when they have high knowledge uncertainty. LBS provides distance information, which helps users choose alternatives appropriate for them. Therefore, users will perceive lower choice uncertainty when they use LBS. In order to test the hypotheses, we selected 80 students and assigned them to one of the two experiment groups. One group was asked to use LBS to search surrounding restaurants and the other group was asked to not use LBS to search nearby restaurants. The experimental tasks and measures items were validated in a pilot experiment. The final measurement items are shown in Appendix A. Each subject was asked to read one of the two scenarios - with or without LBS - and use a smartphone application to pick a restaurant. All behaviors on smartphone were recorded using a recording application. Search breadth was measured by the number of restaurants clicked by each subject. Search depths was measured by two metrics - the average number of sub-level pages each subject visited and the average time spent on each restaurant. The hypotheses were tested using SPSS and PLS. The results show that knowledge uncertainty reduces search breadth (H1a). However, there was no significant correlation between knowledge uncertainty and search depth (H1b). Choice uncertainty significantly reduces search depth (H2b), but no significant relationship was found between choice uncertainty and search breadth (H2a). LBS information filtering significantly reduces the buyers' choice uncertainty (H4) and reduces the negative relationship between knowledge uncertainty and search breadth (H3). This research provides some important implications for service providers. Service providers should use different strategies based on their service properties. For those service providers who are not well-known to consumers (high knowledge uncertainty) should encourage their customers to use LBS. This is because LBS would increase buyers' consideration sets when the knowledge uncertainty is high. Therefore, less known services have chances to be included in consumers' consideration sets with LBS. On the other hand, LBS information filtering decrease choice uncertainty and the near service providers are more likely to be selected than without LBS. Hence, service providers should analyze geographically approximate competitors' strength and try to reduce the gap so that they can have chances to be included in the consideration set.
Journal of Korea Spatial Information System Society
/
v.11
no.4
/
pp.85-88
/
2009
In multimedia database systems, the nearest neighbor Query occurs frequently and requires the processing cost higher than other spatial Queries do. It needs the measurement of search distance that the number of searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the nearest neighbor query. The circular location property of objects is considered to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of nearest neighbor queries be considered a circular location property of object where the search space consists of a circular domain and show its characteristics. The proposed method uses the circular minimum distance and the circular optimal distance, the search measurement for optimizing the processing cost of nearest neighbor queries.
KIPS Transactions on Computer and Communication Systems
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v.1
no.2
/
pp.79-86
/
2012
An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.
Journal of the Korean Society for Library and Information Science
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v.22
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pp.361-396
/
1992
The purpose of this study is to verify the correlations between the amount of the online searcher's search experience and their search effect. In order to achieve this purpose, the 28 online searchers working at the chosen libraries and information centers have participated in the study as subjects. The subjects have been classified into the two types of cognitive style by Group Embedded Figure Test. As the result of the GEFT, two groups have been identified: the 15 Field Independance ( FI ) searchers and the 13 Field Dependance ( FD ) searchers. The subject's search experience consists of the 3 elements: disciplinary, training, and working experience. In order to get the data of these empirical elements, a questionnaire have been sent to the 28 subjects. An online searching request form prepared by a practical user was sent to all subjects, who conducted searches of the oversea databases through Dialog to retrieve what was requested. The resultant outcomes were collected and sent back to the user to evaluate relevance and pertinence of the search effect by the individual. In this study, the search effect has been divide into relevance and pertinence. The relevance has been then subdivided into the 3 elements : the number of the relevant documents, recall ratio, and the cost per a relevant document. The relevance has been subdivided into the 3 elements: the number of the pertinent documents, utility ratio, and the cost per a pertinent document. The correlations between the 3 elements of the subject's experience and the 6 elements of the search effect has been analysed in the FI and in the FD searchers separately. At the standard of the 0.01 significance level, findings and conclusions made in the study are summarised as follows : 1. There are strong correlations between the amount of training and the recall ratio, the number of the pertinent documents, and the utility ratio on the part of FI searchers. 2. There are strong correlations between the amount of working experience and the number of the relevant documents, the recall ratio on the part of FD searchers. However, there is also a significant converse correlation between the amount of working experience and the search cost per a pertinent document on the part of FD searchers. 3. The amount of working experience has stronger correlations with the number of the pertinent documents and the utility ratio on the part of FD searchers than the amount of training. 4. There is a strong correlation between the amount of training and the pertinence on both part of FI and FD searchers.
Internet vendors are gradually realizing the importance of "locking-in" online customers in order to ensure profitability. Erection of switching barriers increases customers'lock-in and in turn may result in their willingness to pay price-premium for the same service. However, raising customer lock-in online is difficult because search costs are very low. Therefore, this study examines the effect of switching barriers (customer satisfaction, perceived value and relative advantage) on switching costs and the effect of switching costs on customer's willingness to pay more. Since switching costs and consequent relationships may depend upon the type of product therefore the research model in this study is examined for both search products and experience products. Data is collected through an online survey from two websites (one each for search product and experience product). The empirical results show the key role of switching costs in customers' willingness to pay more and the relationships among the four constructs. The theoretical and practical implications of this study are also discussed.
Journal of the Institute of Electronics Engineers of Korea TC
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v.44
no.3
s.357
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pp.61-67
/
2007
In Reed Solomon decoder, when there are more than 4 error symbols, we usually use Chien search machine to find those error positions. In this case, classical method requires complex and relatively slow digital circuitry to implement it. In this paper we propose New fast and cost effective Chien search machine design method using Galois Subfield transformation. Example is given to show the method is working well. This new design can be applied to the case where there are more than 5 symbol errors in the Reed-Solomon code word.
Journal of the Korea Society of Computer and Information
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v.15
no.1
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pp.83-90
/
2010
The number of searched nodes and the computation time in an index should be minimized for optimizing the processing cost of the nearest neighbor query. The Measurement of search distance considered a circular location property of objects is required to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of the nearest neighbor query be considered a circular location property of object where the search space consists of a circular domain and show its performance by experiments. The proposed method uses the circular minimum distance and the circular optimal distance which are the search measurements for optimizing the processing cost of the nearest neighbor query.
Fast IP address lookup in routers is essential to achieve packet forwarding in wire-speed. The longest prefix matching for IP address lookup is more complex than exact matching because of its dual dimensions, length and value. By thoroughly studying the current proposals for IP address lookup, we find out that the binary search could be a low-cost solution while providing high performance. Most of the existing binary search algorithms based on trie have simple data structures which can be easily implemented, but they have some problems because of empty internal nodes. The proposed algorithm is based on trie structure, but empty internal nodes are replaced by priority prefixes. The best-matching-prefix search in the proposed algorithm is more efficiently performed since search can be finished earlier when input is matched with a priority prefix. The performance evaluation results show that the constructed priority-trie has very good performance in the lookup speed and the scalability.
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