• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4212-4226
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• 2019

In this paper, a design and implementation for direct deal distribution platform is proposed to bypass the complex traditional distribution structure of agricultural market, as one of the fields where distribution patterns have changed. In the case of domestic agricultural distribution, demand and supply are unstable since the sales market is excessively concentrated in the designated wholesale market. Besides sales must go through multiple stages of distribution leading to problems in freshness and stability of agricultural products and downward pressure on profit margins for producers. To solve the above mentioned issues, we propose a cloud service convergence direct deal distribution platform based on asynchronous-driven Node.js. The proposed platform can facilitate a variety of direct trading functions and also access to visualization information related to agricultural products, which may increase user confidence at an intermediary-free direct transactions platform. First, we describe the requirements of intermediary-free direct transactions of agricultural products and transaction entities. Next the database structure and transaction functions are designed and then implemented according to those requirements. Finally, an API based cloud convergence service structure is designed to provide the analyzed information to ensure a trustworthy system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.578-581
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• 2014

Blackhole attack, a kinds of attacks to routing function, can cause critical effects to network transmission function, Especially, on MANET(Mobile Ad-hoc Network) which it is not easy to prepare functions to respond malicious intrusion, transmission functions of entire networks could be degraded. In this paper, effects of blackhole attack to network transmission performance is analyzed on lattice structured MANET. Specially, performance is measured for various location of blackhole attack on lattice MANET, and compared with the performance of random structured MANET. This paper is done with computer simulation, VoIP(Voice over Internet Protocol) traffic is used in simulation. The results of this paper can be used for data to deal with blackhole attack.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.89-94
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• 2022

With the recent acceleration of an aging society, the use of wheelchairs is increasing, and wheelchair accidents are also increasing. However, despite this situation, the domestic wheelchair market is lacking in deveolpment of additional functions to prevent wheechair collisions and falls. Therefore, this paper aims to design and implement intelligent smart wheelchairs equipped with functions such as stair wheels and automatic illumination sensor headlights that allow wheelchairs to automatically avoid obstacles, notify interlocking applications when falls are detected. Accordingly, it is expected to increase the convenience of wheelchair users and prevent frequent wheelchair accidents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1755-1777
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• 2022

The development of wireless communication technology has led to the underutilization of radio spectra. To address this limitation, an intelligent cognitive radio network was developed. Specific emitter identification (SEI) is a key technology in this network. However, in realistic non-cooperative scenarios, the system may detect signal classes beyond those in the training database, and only a few labeled signal samples are available for network training, both of which deteriorate identification performance. To overcome these challenges, a meta-learning-based open-set identification system is proposed for SEI. First, the received signals were pre-processed using bi-spectral analysis and a Radon transform to obtain signal representation vectors, which were then fed into an open-set SEI network. This network consisted of a deep feature extractor and an intrinsic feature memorizer that can detect signals of unknown classes and classify signals of different known classes. The training loss functions and the procedures of the open-set SEI network were then designed for parameter optimization. Considering the few-shot problems of open-set SEI, meta-training loss functions and meta-training procedures that require only a few labeled signal samples were further developed for open-set SEI network training. The experimental results demonstrate that this approach outperforms other state-of-the-art SEI methods in open-set scenarios. In addition, excellent open-set SEI performance was achieved using at least 50 training signal samples, and effective operation in low signal-to-noise ratio (SNR) environments was demonstrated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.133-137
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• 2023

In this paper, we developed a 'comprehensive pet management application' that combines pet AI diagnosis, animal hospital search, smart household accounts, and community functions. The application can solve the inconvenience of users who have to use multiple functions as separate applications, and can easily use pet AI diagnosis services through photos, provides animal hospital information using crawling, finds nearby animal hospitals, and supports smart households that can scan receipts using OCR text extraction techniques. By using this application, information necessary for raising pets such as health and consumption details of pets can be managed in one system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.49-54
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• 2024

Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.223-245
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• 2007

Purpose: While empirical importance of dimensionality of perceived value is widely accepted, our understanding of experiential value dimensions in other retail channels and other cultures has not been explicitly tested. This study attempted to determine if the dimensions of experiential value scale (EVS) by Mathwick, Malhotra, and Rigdon (2001) identified in US catalog and Internet contexts could be applied in other international markets (South Korea) and in other retail channels (department store versus Internet shopping mall). Methodology/Approach: Two data sets, one from 220 department store shoppers and the other from 359 Internet shopping mall shoppers, were analyzed. Findings: Confirmatory factor analysis confirmed four different EVS dimensions by retail channels. Overall, entertainment and intrinsic enjoyment values were found to be more important in department store while economic and efficiency value dimensions were interpreted critical in Internet shopping mall context. Visual appeal aspect constitutes distinct value dimension in two channels. Practical Implications: One separate dimension of time efficiency in Internet shopping mall suggests that more efficient web design and functions that can save time and promote convenience are needed to better accommodate their customers. Internet has heavily relied on traditional attributes, such as factual information, price comparability, and brand name reliance. However, this study suggests that Internet shopping mall retailer should offer visual diversion and stimulation just as brick and mortar shopping malls do. Originality /Value of Paper: Although the research findings must be viewed as tentative because the results are from one country, they provide a rich basis for further understanding the dimensions of experiential value in other international markets and other retail channels. Category: Research Paper

• Journal of the Korean Dietetic Association
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• v.10 no.3
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• pp.284-292
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• 2004

The purpose of this study was to develop a manipulation system for nutrition counseling based on internet. This system offers convenient user interface and the synthetic counseling results with various utilities. This system consists of the general information of clients, the anthropometry data and the calculation of obesity and body index, the state of eating habits, calorie expenditure, clinical symptoms, the convenient method for analysis of nutrients, biochemical data and nutrition prescription. Having interoperability, these functions preserve the information of clients and manage the historical data. This system can insert, store, print out and generate the synthetic information of clients to provide a suitable and efficient nutrition counseling information. With accumulated client data, It does the nutrition education and counseling simultaneously. As it is developed based on internet, it provides friendly user interface. Also, Managing clients' information connected to database, it can provide a systematic and formal information. It is possible for the system to retrieve information and counsel in real time. It is expected that the nutrition counseling management system can improve the national health with animated nutrition counseling.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.267-273
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• 2011

The importance of networking capability is gaining more weight for enterprise business and high-speed Internet access with guaranteed security management is essential to companies. This paper presents a unified network security management solution to support high-speed Internet access, active security management, traffic classification and control. The presented system provides firewall, VPN, intrusion detection, contents filtering, traffic management, QoS management, and history log functions in unified manner implemented in a single appliance device located at the edge of enterprise networks. This will enable cost effective unified network security solution to companies.