• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1417-1422
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• 1991

In this paper we develop an analytic model for end-to-end communication protocols and study the window mechanism for flow control in store-and-forward computer networks. We develop a flow control model in which the parameters of the system are not dynamically adjusted to the stochastic fluctuation of the system load. Simulation results are presented and it is shown that the throughput-delay performance of a network can be improved by proper selection of the design parameter, such as timeout, the number of retransmission, etc.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.65-74
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• 2021

In this paper, we discussed the necessity and importance of introducing feature stores to establish a collaborative environment between data engineering work and data science work. We examined the technology trends of feature stores by analyzing the status of some major feature stores. Moreover, by introducing a feature store, we can reduce the cost of performing artificial intelligence (AI) projects and improve the performance and reliability of AI models and the convenience of model operation. The future task is to establish technical requirements for establishing a collaborative environment between data engineering work and data science work and develop a solution for providing a collaborative environment based on this.

• Journal of Distribution Science
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• v.12 no.4
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• pp.23-30
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• 2014

Purpose - The purpose of this study is to analyze the efficiency of retail businesses by dividing domestic retailers into discount stores, super supermarkets (SSMs), and department stores. It suggests retail-business investment strategies by using data environment analysis (DEA) to analyze how input elements such as store area, parking lot area, number of employees, and sales management expenses for the convenience of customers positively affect business performance measurements such as sales and visiting customers per day. Research Design, Data, and Methodology - The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU). The study included 19 companies (five discount store DMUs, ten SSM DMUs, and four department store DMUs). Because the business elements and sizes of retail store DMUs used in this analysis are different, average per-store input and output variables were used. Data were collected from "The Yearbook of Retail Industry in Korea (2012)." DEA analysis was used to determine differences in efficiency among discount stores, SSMs, and department stores in terms of the business elements of each retail business. It was also used to determine what business elements were excessively invested in by comparing and analyzing efficiency by business elements using SPSS software's ANOVA (Analysis of Variance). Results - The CCR and BCC efficiency analysis found that the efficiency of discount stores is low. We believe that the saturation state of discount stores is a major factor. The ANOVA analysis confirms the VRS hypothesis with a statistically significant difference among the three groups, based on an analysis confidence interval of 95%. CRS and SE were not found to be significantly different among the three groups. As for the post hoc test, which concretely shows differences by group, the Scheffe's multiple comparison analysis test found the average differences between group 1 (discount stores) and group 2 (SSM) to be statistically significant. Conclusions - The DEA efficiency analysis implies that investment in input elements, including store area, parking lot area, and sales management expenses, were excessive in the case of discount stores, while SSMs need to invest more in promotion activities such as gifts, events, and coupons for customer management. Department stores have found that small companies invest excessively in input elements. Department stores need to invest in differentiated shopping mall complexes. This study was limited in acquiring statistical data; various input variables which might have shown more secure customer management and promotional expenses could not be applied. As the study was limited in various aspects of the efficiency analyses because financial analyses of the companies and of causal relationships, including satisfaction and loyalty of visiting customers, were not done, these aspects will be examined in the next study.

• Journal of Distribution Research
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• v.17 no.3
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• pp.93-113
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• 2012

Early conflict research in channel and organization area have focused on the definition of conflict construct, its cause, consequence and identified conflict resolution management. Recent studies about conflict, however, have explored new assumption of complexity, a multidimensional conflict construct, contextual conflict management strategies, positive and negative conflict/consequence, and the conflict resolution strategy. Although many literatures exists on channel conflict resolution, little research has been done about relationship learning and performance from conflict resolution perspective. This study explores how channel members can achieve a relationship learning, as a conflict resolution mechanism, which enhance co-created value in marketing channel relationship. Therefore we propose that conflict resolution strategies(collaborating behavior and avoiding behavior) influence channel performance(effectiveness and efficiency) through relationship learning processes(learning via information exchange, joint interpretation and coordination, relationship-specific knowledge memory), in view of buyer-seller relationship. The research model is shown at

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.107-112
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• 2020

Recently, unstructured data is rapidly being produced based on web-based services. NoSQL systems and key value stores that process unstructured data as key and value pairs are widely used in various applications. In this paper, a study was conducted on a skip list used for in-memory data management in an LSM-tree based key value store. The skip list used in the key value store is an insertion-based skip list that does not allow overwriting and processes all changes only by inserting. This behavior can support Multi-Version Concurrency Control (MVCC), which can simultaneously process multiple read/write requests through snapshot isolation. However, since duplicate keys exist in the skip list, the performance significantly degrades due to unnecessary node visits during a list traverse. In particular, serious overhead occurs when a range query or scan operation that collectively searches a specific range of data occurs. This paper proposes a newly designed Stride SkipList to reduce this overhead. The stride skip list additionally maintains an indexing pointer for the last node of the same key to avoid unnecessary node visits. The proposed scheme is implemented using RocksDB's in-memory component, and the performance evaluation shows that the performance of SCAN operation improves by up to 350 times compared to the existing skip list for various workloads.

• Journal of Distribution Science
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• v.13 no.4
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• pp.65-76
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• 2015

Purpose - This article aims to present and test a model regarding franchisors' supporting activities that may positively influence franchisees' attitude toward the franchising headquarter and their own business performance. Moreover, the authors examine the moderating effect of competitive intensity between franchisee attitude and business performance. Most previous research focused on behavioral performance measurements such as satisfaction, trust, and commitment. There are few empirical studies that focus on financial performance data because it is difficult to determine a relational mechanism between behavioral and financial performance. Moreover, financial data is confidential and difficult to collect in many cases. However, this study measures financial performance (e.g., sales revenue per square meter) differently than most previous research, which is mostly focused on the behavioral performance measurements. Research design, data, and methodology - To test our hypotheses, we selected 137 franchisee managers who are running chains of one of the foremost bakery franchise brands in South Korea. This study carefully investigated the reliability, content validity, convergent validity, and discriminant validity of the proposed instrument by analyzing the data obtained from the samples. The data was analyzed using the AMOS structural equation modeling program. Results - The results indicated that: non-financial support activities (e.g., information exchange and communication) had a positive impact on the franchisee attitude toward the franchising headquarter. The franchisee attitude in turn had a positive effect on the headquarters' business performance. Furthermore, competitive intensity could enhance the relationship between franchisee attitude toward franchising headquarter and business performance in a local franchise market. However, financial support activities (e.g., rewards and promotional support) and training had no relationship with either franchisee attitude or business performance. Conclusions - This study provides some practical implications to franchisors in terms of franchise operation and store opening strategies. With respect to the franchise operation strategy, franchisors need to focus on non-financial rather than financial support. Most franchisees consider the necessity of financial support activities and not their sufficiency because these activities are specified in their franchise contract. In addition, it is important for franchisees to maintain a positive attitude for the franchise headquarters. The franchisees with a positive attitude for the franchisor can show a high degree of solidarity for various support activities, and it consequently determines franchisees' sales performance. In terms of franchise store opening strategy, this study suggests an additional criterion that can be considered in determining the location of direct and non-direct management stores (e.g., franchisees' stores). In this research, franchise stores located within high level of competitive intensity are shown to have a high relationship between franchisee attitudes of franchisor support activities and business performance compared to the franchisees located within low competitive intensity level. This result shows that opening non-direct franchise stores is more effective than direct stores in higher competitive market situations. Research contribution, implications, and further research directions are discussed at the end of the paper.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.655-666
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• 2007

Reasoners using typical Tableaux algorithm such as RacerPro, Pellet have a problem in Tableaux algorithm large ABox reasoning. Researches to solve these Problems are dealt with Instance Store of University of Manchester which uses Tableaux algorithm based reasoner and DBMS and KAON2 of University of Karlsruhe using Disjunctive Datalog approach. An evaluation experiment for present reasoners is the experiment of TBox reasoning in most of Tableaux algorithm based one. The most of benchmarking tests in reasoning systems haven't done with ABox reasoning based Tableaux Algorithm but done with TBox reasoning based Tableaux Algorithm. Especially, rarely reported benchmarking tests in reasoners have been issued nowadays. Therefore, this thesis evaluates systems with theory of each reasoners for large ABox reasoning that becomes issues recently with typical reasoners. The large AoBx reasoning engine will be analyzed using Instance Store and KAON2 of Manchester University for large ABox processing. At the analysing method, LUBM(Lehigh University BenchMark), benchmarking test method, and it's test system will be introduced. In conclusion, I recommend appropriate reasoner in various environment with experiment result and characteristic of algorithm used for each reasoner.

• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• Journal of the Korean Society of Costume
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• v.43
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• pp.125-142
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• 1999

This research was aimed to present a model of clothing products evaluation nd to classify the effect of extrinsic cues on clothing products evaluation. In order to accomplish following subjects were established. First it is to find the effect of extrinsic cues -price brand store - on perceived quality perceived risk perceived value and purchase intention of clothing products. Second it is to formulate a model of clothing products evaluation and find the relation among the variables such as extrinsic cues perceived quality perceived risk perceived value and purchase intention. This research was mainly divided into theoretical and empirical part. In the theoretical part previous theories and studies on clothing products cues clothing products evaluation perceived quality perceived risk and perceived value were examined to establish a research model and to present a theoretical frame for clothing products evaluation. In the empirical research a questionnaire was developed and statistical data were collected from during July 1997. The subjects were 862 women in the age of 20-35 living in Seoul and kyungki region. SAS and LISREL were used to analyze the collected data. frequency percentage factor analysis ANOVA duncan test correlation analysis regression analysis and LISREL were applied. The results of this research are as follows: First perceived quality consists of performance quality external quality and utility quality in a form of multi dimensional structural. Perceived risk is structured by social/resultant risk financial/fashionable risk and performance/management risk. Second this research proved that extrinsic cues are influenced by each individual variable and extrinsic cues interact with each other through the variable. The perceived quality is influenced most by price Among the perceived risk social/resultant risk by brand financial/fashionable risk by price and performance/management risk by store. respectively. Perceived value is inflenced by price and brand. Third in evaluating process consumer use extrinsic cues to first formulate perceived quality and perceived risk of clothing products and then formulate perceived value ot decide on purchase intention.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.321-326
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• 2021

Blockchain is increasing in value as a platform for safe transmission of capital transactions or secure data. In addition, blockchain has the potential as a new platform that can safely store large amounts of data such as videos, music, and photos, and safely manage transaction details and service usage specifications. Since it is not possible to store large-capacity media data in a block, research on the performance of storing sound source information in a block and retrieving the stored sound source data by using the distributed storage system (IPFS) and the hash information of the sound source signature data was conducted. In this paper, we propose a sound source signature indexing method using a bloom filter that can improve the search speed suggested by previous studies. As a result of the experiment, it was confirmed that improved search performance (O(1)) than the existing search performance (O(n)) can be achieved.