• Journal of Convergence for Information Technology
• /
• v.7 no.6
• /
• pp.259-265
• /
• 2017

This study reviewed the existing studies in order to set up a strategy that can achieve the trust and business performance of the franchisers, who are actually operating franchised business, breaking from the research trend centered around franchise headquarters and added the factors of the franchise headquarters' strategy for expanding franchises, including word-of-mouth communication and advertising & publicity and added the exercise of recruitment agency outsourcing, flagship store, recently utilized often as preceding variables to verify the causal relation between the trust of the franchiser and the business performance of the franchise. The implications of this study, it can be concluded that the government authority for the attraction of healthy franchises can continuously attract franchises and enter the market can continuously attract franchises by increasing the trust of the franchises, and powerfully investing and managing them for the effort through word-of-mouth marketing. It is expected that this study will be helpful in the establishment of a business strategy for forming a continuous relationship as well as the franchise head office's strategy for the recruitment of new franchises.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.9
• /
• pp.2093-2099
• /
• 2015

To prevent damage to the cargo, monitoring and remote management for reefer containers is necessary. The currently used remote monitoring service is the Power Cable Transmission(PCT) system, which is recommended by the International Maritime Organization(IMO). However, this system is not widely used because it requires a separate PCT infrastructure and is susceptible to data loss problems. To solve this problem, this study introduces the "IoT-based reefer container management system", The proposed system which is attached to reefer container collects and transmits data on the temperature, status and location of reefer container to middleware using RS-232 communication and WCDMA/GSM communication. Middleware is store the data received in the database and provide information to user in real time through the web and mobile program. At this time, users able to change setting temperature in real time from a distant place through the web program. This study tested by transit about shipment of strawberries to monitor and analyze and check the system's overall effectiveness.

• Journal of Information Management
• /
• v.43 no.4
• /
• pp.191-210
• /
• 2012

Scholarly science citation data is typically of large volume and consists of a variety of data. Moreover, the volume of data is increasing more and more. Therefore, there are some requirements to store and manage the data efficiently and Korea Institute of Science and Technology Information (KISTI) develops Korea Science Citation Database (KSCD) which manage and serve very large-volume of korea science technique information including citation data. However, current services based on KSCD are not enough for various users. Thus, it is important issue to offer a variety of services using KSCD. For example, if a user searches articles described by a specific author, then a user may want to find not only the articles cited by a certain author but also those articles that study similar topics. However, it is not always easy to provide these services with citation data. Therefore, this paper surveys studies about services using citation data in order to find approaches for better utilizing KSCD. Especially, this paper considers data mining techniques, because data mining is one of the main techniques to extracting semantic information from big data. Therefore, this paper discusses methods for utilizing large volume of KSCD based on data mining technique.

• Journal of KIISE
• /
• v.42 no.1
• /
• pp.54-67
• /
• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of KIISE:Information Networking
• /
• v.29 no.4
• /
• pp.412-427
• /
• 2002

This paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in mobile communication systems. In mobile communication systems, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the failure of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the failure of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a Neuro-Fuzzy Inference System (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme

• Information Systems Review
• /
• v.17 no.3
• /
• pp.95-111
• /
• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.5
• /
• pp.901-909
• /
• 2021

Since mobile devices have limited computational resources, it tends to use the cloud to compute or store data. As real-time becomes more important due to 5G, many studies have been conducted on edge clouds that computes at locations closer to users than central clouds. The farther the user's physical distance from the edge cloud connected to base station is, the slower the network transmits. So applications should be migrated and re-run to nearby edge cloud for smooth service use. We run applications in docker containers, which is independent of the host operating system and has a relatively light images size compared to the virtual machine. Existing migration studies have been experimented by using network simulators. It uses fixed values, so it is different from the results in the real-world environment. In addition, the method of migrating images through shared storage was used, which poses a risk of packet content exposure. In this paper, Containers are migrated with Secure CoPy(SCP) method, a data encryption transmission, by establishing an edge computing environment in a real-world environment. It compares migration time with Network File System, one of the shared storage methods, and analyzes network packets to verify safety.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.531-534
• /
• 2014

DLNA is an established industry standard which supports contents sharing among smart devices in home wired- and wireless-network environment and is well known in Korea as Allshare or Smartshare. The DLNA standard is implemented as built-in services in most of Android smart phones and tablets. In addition to the handheld devices, DLNA service can also be employed in speakers, printers, and so on. However, users have reported many interoperability issues between DLNA devices. Developers typically identify causes by analyzing the packet exchange information between devices. However, this approach costs them to put additional effort to filter relevant packets, to reconstruct packet exchange history and the protocol flow. Consequently, it ends up with increased development time. In this paper, we demonstrate a technique to automatically analyze and visualize the packet exchange history. We modified a router firmware to capture and store packets exchanged between DLNA devices, and then analyze and visualize the stored packet exchange history for developers. We believe that visualized packet exchange history can help developers to test the interoperability between DLNA devices with less effort, and ultimately to improve the productivity of developers.

• Natural Product Sciences
• /
• v.27 no.2
• /
• pp.86-98
• /
• 2021

This study was designed to characterize the effect of ginsenoside-Rg2 (Rg2), one of panaxatriol saponins isolated from Korean ginseng root, on the release of catecholamines (CA) in the perfused model of the rat adrenal medulla, and also to establish its mechanism of action. Rg2 (3~30 µM), administered into an adrenal vein for 90 min, depressed acetylcholine (ACh)-induced CA secretion in a dose- and time-dependent manner. Rg2 also time-dependently inhibited the CA secretion induced by 3-(m-chloro-phenyl-carbamoyl-oxy)-2-butynyltrimethyl ammonium chloride (McN-A-343), 1.1-dimethyl-4-phenyl piperazinium iodide (DMPP), and angiotensin II (Ang II). Also, during perfusion of Rg2, the CA secretion induced by high K⁺, veratridine, cyclopiazonic acid, methyl-1,4-dihydro-2,6-dimethyl-3-nitro-4-(2-trifluoro-methyl-phenyl)-pyridine-5-carboxylate (Bay-K-8644) depressed, respectively. In the simultaneous presence of Rg2 and N^ω-nitro-L-arginine methyl ester hydrochloride ʟ-NAME), the CA secretion induced by ACh, Ang II, Bay-K-8644 and veratridine was restored nearly to the extent of their corresponding control level, respectively, compared to those of inhibitory effects of Rg2-treatment alone. Virtually, NO release in adrenal medulla following perfusion of Rg2 was significantly enhanced in comparison to the corresponding spontaneous release. Also, in the coexistence of Rg2 and fimasartan, ACh-induced CA secretion was markedly diminished compared to the inhibitory effect of fimasartan-treated alone. Collectively, these results demonstrated that Rg2 suppressed the CA secretion induced by activation of cholinergic as well as angiotensinergic receptors from the perfused model of the rat adrenal gland. This Rg2-induced inhibitory effect seems to be exerted by reducing both influx of Na⁺ and Ca²⁺ through their ionic channels into the adrenomedullary cells as well as by suppressing Ca²⁺ release from the cytoplasmic calcium store, at least through the elevated NO release by activation of NO synthase, which is associated to the blockade of neuronal cholinergic and AT₁-receptors. Based on these results, the ingestion of Rg2 may be helpful to alleviate or prevent the cardiovascular diseases, via reduction of CA release in adrenal medulla and consequent decreased CA level in circulation.

• The Journal of Bigdata
• /
• v.7 no.2
• /
• pp.153-172
• /
• 2022

Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.