• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.187-194
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• 2020

This paper proposes a website fingerprinting method using ensemble learning over a Tor network that guarantees client anonymity and personal information. We construct a training problem for website fingerprinting from the traffic packets collected in the Tor network, and compare the performance of the website fingerprinting system using tree-based ensemble models. A training feature vector is prepared from the general information, burst, cell sequence length, and cell order that are extracted from the traffic sequence, and the features of each website are represented with a fixed length. For experimental evaluation, we define four learning problems (Wang14, BW, CW_T, CW_H) according to the use of website fingerprinting, and compare the performance with the support vector machine model using CUMUL feature vectors. In the experimental evaluation, the proposed statistical-based training feature representation is superior to the CUMUL feature representation except for the BW case.

• Korea Trade Review
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• v.46 no.5
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• pp.99-113
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• 2021

This study aims to analyze the effect of product information quality and source credibility on product arousal in fresh food website. Despite fresh food websites are selling products with various feature, prior studies have focused on consumer behavior for fresh food website characteristics or specific products without considering the feature of the products. Consumers' attitudes, beliefs, and behaviors vary depending on the feature of the product. In other words, depending on the category of product, the decision making process that consumers purchase products can be differ. So, we classify products considering the feature of these products to examine the effect of information quality and source credibility on product arousal into experience goods and search goods. We surveyed 288 consumers having experience of purchase in fresh food website and verified the hypothesis through One-way ANOVA by classifying the information quality and the source credibility as high level and low level. As a result, there was a difference in product arousal according to the product information quality level and the source credibility level for each product category exposed to the fresh food website. In experience goods, source credibility have a more important effect on product arousal than product information quality, and in search goods, product information quality have a more important effect on product arousal than source credibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1916-1934
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• 2023

The phishing attack is a malicious emerging threat on the internet where the hackers try to access the user credentials such as login information or Internet banking details through pirated websites. Using that information, they get into the original website and try to modify or steal the information. The problem with traditional defense systems like firewalls is that they can only stop certain types of attacks because they rely on a fixed set of principles to do so. As a result, the model needs a client-side defense mechanism that can learn potential attack vectors to detect and prevent not only the known but also unknown types of assault. Feature selection plays a key role in machine learning by selecting only the required features by eliminating the irrelevant ones from the real-time dataset. The proposed model uses Hyperparameter Optimized Artificial Neural Networks (H-ANN) combined with a Hybrid Firefly and Grey Wolf Optimization algorithm (H-FFGWO) to detect and block phishing websites in Internet of Things(IoT) Applications. In this paper, the H-FFGWO is used for the feature selection from phishing datasets ISCX-URL, Open Phish, UCI machine-learning repository, Mendeley website dataset and Phish tank. The results showed that the proposed model had an accuracy of 98.07%, a recall of 98.04%, a precision of 98.43%, and an F1-Score of 98.24%.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.73-85
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• 2013

This study examines the online social capital of local press using the website and social media. Moreover, the paper respectively visualizes web feature as Web 1.0 and social feature analysis as Web 2.0 by applying correspondence analysis. For data, the study analyzes 10 representative local press in Yeungnam areas. To collect the data, two coders coded web features from the websites and we employed NodeXL, an open-source software tool, for social media data. The results reveal that local websites expend online social capital using social media account. Especially, the social features of local presses attach importance to Twitter as the main press keep the well-balance use among all platforms.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.45-58
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• 2018

As information and communication technologies (ICTs) become more advanced, consumers are able to experience retailing activities such as searching for products and services in online retail shops and for Internet-exclusive branded contents. Specifically, fashion retailers are facing the need to develop more novel experiential design than one another to maximize customers' experience in Internet websites and secure sustainable competency. Confirming methods of organic integration of experiential and visual features of both online and mobile channels is an important aspect of the study of extended consumers' interfaces of retail channels. Mehrabian and Russell's stimulus-organism-response (S-O-R) paradigm and Sugiyama and Andree's attention, interest, search, action, and share (AISAS) model were used for this research. Specifically, the present study considered the effect of e-commerce website features on consumers' emotional reactions (pleasure and arousal) and the consequent impact on online consumer behaviors (search, action, and share). Hence, plus the self-reported survey methods, each subject's psychophysiological indicators (i.e., pleasure and arousal) were measured to obtain more objective and reliable data and to redeem the results of the self-reported survey. Findings revealed the implications of the e-commerce website feature by comprehending the S-O-R paradigm and AISAS model and extending the understanding of the role of variables associated with comprehended frameworks based on psychophysiological data.

• Archives of design research
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• v.15 no.1
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• pp.135-142
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• 2002

To show the analytic approach to website sue, this paper discusses style's function that is immediately related to users emotional and aesthetic satisfaction. And we make an analysis of several websites based on various visual factors. Style provides emotion, a shared experience, context that makes the message arts function immediately apparent, and interests. It is a principle design feature that parallels cognitive function. Visual factors of website interface could be extracted from various aspects which are organization level, medial level, and formative level. Based on the extracted visual factors, we analyze the style which convey emotional idea. We select several sites which are opposite side in the image map with son-hard and warm-cool axis, and then make an analysis of them in two points which are organization and formative factors and communication means for emotional effect. To understand the systematic approach to website style could be helpful for figuring out the design problems and bringing out many solutions. It could be base for concrete guideline for website page design.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.119-128
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• 2016

This study is designed with an intention to understand CSR story strategies that the corporates use, focusing on analyzing the method of composition of Hyundai Motor Company's CSR website stories. When analyzing based on interactivity, ease of use, newest, and informativity, interactive dialogue feature was mostly lacking. It is not the most up-to-date data and lacks the newest. However, as sharing information feature was presented, information spread quickly. When applying Greimas' Actantial Model into the 'CSR News' that conveys the news about corporate philanthropic activities, it turned out that the CSR strategies were authenticity, consistency and flexibility. When doing CSR storytelling, a corporate should not only use pre-existing executives and staff members but should use new icons including civic organizations and the youth if possible, and perform its role as a supporter. At the same time, a corporate must build strategical storytelling to the new values and engage in systematic corporate philanthropic activities that meets the need of the time period.

• The Journal of Pediatrics of Korean Medicine
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• v.26 no.2
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• pp.53-61
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• 2012

Objectives To make comprehensive feature of clinical trials using herbal medicine and their results by today, then help a strategy for herbal medication-derived clinical studies in the future. Methods Through medical website (Pubmed EBSCO Medline), foreign clinical literatures about atopic dermatitis and herbal medicine were searched. And domestic clinical literatures about atopic dermatitis using internet website (OASIS) and hand-searching. Analysis was performed according to distribution mainly by subject, study design, number by year and its efficacy. Results and Conclusions Seventy-nine (Domestic literatures: Fifty, Foreign literatures: Twenty-nine) literatures were selected according to inclusion criteria of clinical study. 80% of domestic clinical literatures were observational studies, 50% of foreign were intervention. There were six adverse effect case studies, two follow-ups, one case report, four translational and four uncontrolled clinical trials in foreign literatures. And nineteen case reports, eighteen case series, two follow-up and five uncontrolled clinical studies in domestic. Six RCTs have established by four external herb therapy and two decoctions in Korea, showed positive effects. Three out of four external applications RCTs, four out of seven decoctions showed positive results in foreign studies. This study revealed the current status of atopic dermatitis clinical research using herbal drugs. To put clinical trials to use of herbal medicine in the treatment atopic dermatitis, scientific and objective-based studies should be needed.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.357-364
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• 2005

In this paper, we propose an accurate and fast keyword spotting system for searching user-specified keyword in Hangul document images by using two-level image-to-image matching. The system is composed of character segmentation, creating a query image, feature extraction, and matching procedure. Two different feature vectors are used in the matching procedure. An experiment using 1600 Hangul word images from 8 document images, downloaded from the website of Korea Information Science Society, demonstrates that the proposed system is superior to conventional image-based document retrieval systems.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.411-427
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• 2022

Digging historical and cultural information from seals in ancient books is of great significance. However, ancient Chinese seal samples are scarce and carving methods are diverse, and traditional digital image processing methods based on greyscale have difficulty achieving superior segmentation and recognition performance. Recently, some deep learning algorithms have been proposed to address this problem; however, current neural networks are difficult to train owing to the lack of datasets. To solve the afore-mentioned problems, we proposed an SEL-RefineMask which combines selector of feature pyramid network (SEL-FPN) with RefineMask to segment and recognize seals. We designed an SEL-FPN to intelligently select a specific layer which represents different scales in the FPN and reduces the number of anchor frames. We performed experiments on some instance segmentation networks as the baseline method, and the top-1 segmentation result of 64.93% is 5.73% higher than that of humans. The top-1 result of the SEL-RefineMask network reached 67.96% which surpassed the baseline results. After segmentation, a vision transformer was used to recognize the segmentation output, and the accuracy reached 91%. Furthermore, a dataset of seals in ancient Chinese books (SACB) for segmentation and small seal font (SSF) for recognition were established which are publicly available on the website.