• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.585-592
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• 2013

CBIR is an effective tool to search and extract image contents in a large remote sensing image database queried by an operator or end user. However, as imaging principles are different by sensors, their visual representation thus varies among image modality type. Considering images of various modalities archived in the database, image modality difference has to be tackled for the successful CBIR implementation. However, this topic has been seldom dealt with and thus still poses a practical challenge. This study suggests a cross modality CBIR (termed as the CM-CBIR) method that transforms given query feature vector by a supervised procedure in order to link between modalities. This procedure leverages the skill of analyst in training steps after which the transformed query vector is created for the use of searching in target images with different modalities. Current initial results show the potential of the proposed CM-CBIR method by delivering the image content of interest from different modality images. Despite its retrieval capability is outperformed by that of same modality CBIR (abbreviated as the SM-CBIR), the lack of retrieval performance can be compensated by employing the user's relevancy feedback, a conventional technique for retrieval enhancement.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.321-324
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• 2005

In these days, the management and visualization of 3D geo-spatial information is regarded as one of an important issue in GiS and remote sensing fields. 3D GIS is considered with the database issues such as handling and managing of 3D geometry/topology attributes, whereas 3D visualization is basically concerned with 3D computer graphics. This study focused on the design and implementation for the OpenGL API-based rendering system for the complex types of 3D geo-spatial features. In this approach 3D features can be separately processed with the functions of authoring and manipulation of terrain segments, building segments, road segments, and other geo-based things with texture mapping. Using this implementation, it is possible to the generation of an integrated scene with these complex types of 3D features. This integrated rendering system based on the feature-based 3D-GIS model can be extended and effectively applied to urban environment analysis, 3D virtual simulation and fly-by navigation in urban planning. Furthermore, we expect that 3D-GIS visualization application based on OpenGL API can be easily extended into a real-time mobile 3D-GIS system, soon after the release of OpenGLIES which stands for OpenGL for embedded system, though this topic is beyond the scope of this implementation.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.336-340
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• 2008

Sentiment classification is a recent subdiscipline of text classification, which is concerned not with the topic but with opinion. In this paper, we present a Korean sentence and document classification system using effective sentiment features. Korean sentiment classification starts from constructing effective sentiment feature sets for positive and negative. The synonym information of a English word thesaurus is used to extract effective sentiment features and then the extracted English sentiment features are translated in Korean features by English-Korean dictionary. A sentence or a document is represented by using the extracted sentiment features and is classified and evaluated by SVM(Support Vector Machine).

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.178-190
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• 2021

Alzheimer's disease (AD) is an insidious and degenerative neurological disease. It is a new topic for AD patients to use magnetic resonance imaging (MRI) and computer technology and is gradually explored at present. Preprocessing and correlation analysis on MRI data are firstly made in this paper. Then kernel principal component analysis (KPCA) is used to extract features of brain gray matter images. Finally supervised classification schemes such as AdaBoost algorithm and support vector machine algorithm are used to classify the above features. Experimental results by means of AD program Alzheimer's Disease Neuroimaging Initiative (ADNI) database which contains brain structural MRI (sMRI) of 116 AD patients, 116 patients with mild cognitive impairment, and 117 normal controls show that the proposed method can effectively assist the diagnosis and analysis of AD. Compared with principal component analysis (PCA) method, all classification results on KPCA are improved by 2%-6% among which the best result can reach 84%. It indicates that KPCA algorithm for feature extraction is more abundant and complete than PCA.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_1
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• pp.693-698
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• 2021

As technology advances, there is increasing need for research in different fields where this technology is applied. On of the most researched topic in computer vision is Human activity recognition (HAR), which has widely been implemented in various fields which include healthcare, video surveillance and education. We therefore present in this paper a human activity recognition system based on scale and rotation while employing the Kinect depth sensors to obtain the human skeleton joints. In contrast to previous approaches that use joint angles, in this paper we propose that each limb has an angle with the X, Y, Z axes which we employ as feature vectors. The use of the joint angles makes our system scale invariant. We further calculate the body relative direction in the egocentric coordinates in order to provide the rotation invariance. For the system parameters, we employ 8 limbs with their corresponding angles each having the X, Y, Z axes from the coordinate system as feature vectors. The extracted features are finally trained and tested with the Long short term memory (LSTM) Network which gives us an average accuracy of 98.3%.

• The Journal of Information Systems
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• v.31 no.4
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• pp.47-73
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• 2022

Purpose The purpose of this study is to select the electronic architecture concept of the powertrain domain of the electronic platform to be applied to electric vehicles after 2025. Previously, the automotive electrical and electronic architecture was determined only by trend analysis, but the purpose was to determine the scenario based on the data and select it with clear evaluation indicators. Design/methodology/approach This study identified the function to be applied to the powertrain domain of next-generation electric vehicle, estimated the controller, defined the function feature list, organized the scenario candidates with the controller list and function feature list, and selected the final architecture scenario. Findings According to the research results, the powertrain domain of electric vehicles was selected as the architectural concept to apply the DCU (Domain Control Unit) and VCU (Vehicle Control Unit) integrated architecture to next-generation electric vehicles. Although it is disadvantageous or equivalent in terms of cost, it was found to be excellent in most indicators such as stability, security, and hardware demand.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.644-662
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• 2023

There are still outbreaks of COVID-19 across the world. Ships increase the risk of worldwide transmission of the virus. Close contact tracing remains as an effective method of reducing the risk of virus transmission. Therefore, close contact tracing in ship environments becomes a research topic. Exposure Notifications API (Application Programming Interface) can be used to determine the encountered location points of close contacts on ships. Location points of close contact are estimated by the encountered location points. Risky areas in ships can be calculated based on the encountered location points. The tracking of close contacts is possible with Bluetooth technology without the Internet. The Bluetooth signal can be used to judge the proximity among detecting devices by using the feature that Bluetooth has a strong signal at close range. This Bluetooth feature makes it possible to trace close contacts in ship environments. In this paper, we propose a method for close contact tracing and showing the risky area in a ship environment by combining beacon and Exposure Notification API using Bluetooth technology. This method does not require an Internet connection for tracing close contacts and can protect the personal information of close contacts.

• Journal of Fashion Business
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• v.27 no.6
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• pp.66-84
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• 2023

Handbags are a part of fashion and while their significance and value are increasing, research on this topic is lacking. This study defines handbags and categorizes the materials used for making handbags, sewing methods, expression techniques, and terminologies related to accessories. A total of 1,743 handbags that were released from the Spring 2020 to Fall 2023, Ready-to-Wear collections by 8 selected brands (Hermes, Dior, Fendi, Chanel, Louis Vuitton, Prada, Gucci, and Alexander McQueen), were analyzed. Out of these, 732 unique designs, excluding those with only color variations, were studied. The most common sewing methods were 'Cut, sewing, and edge painting', 'Cylinder arm sewing', 'Cut, edge painting, and sewing', and 'Inverted seam', in that order. Slim strap designs primarily used the 'Cut, sewing, and edge painting' method, whereas the body, especially with narrow and hard leather, was best suited for the 'Cylinder arm sewing machine'. For expression techniques, the most frequently used methods were 'Quilting', 'Metal Eyelet', 'Embossing', 'Printing', 'Punching', and 'Weaving', respectively. The characteristics of each brand's production methods, expression techniques, and accessories were as follows: First, the exposure of logos and monograms is prominent. Unlike clothing, handbags often prominently feature the brand's logo or monogram. Second, signature quilting is a prominent feature. Quilting effectively conveys the brand's signature style, providing cushioning, volume, and pattern effects. Third, sustainable development is a growing trend. Brands are increasingly applying eco-friendly and socially responsible designs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.591-609
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• 2024

In this study, preprocessings with all combinations were examined in terms of the effects on decreasing word number, shortening the duration of the process and the classification success in balanced and imbalanced datasets which were unbalanced in different ratios. The decreases in the word number and the processing time provided by preprocessings were interrelated. It was seen that more successful classifications were made with Turkish datasets and English datasets were affected more from the situation of whether the dataset is balanced or not. It was found out that the incorrect classifications, which are in the classes having few documents in highly imbalanced datasets, were made by assigning to the class close to the related class in terms of topic in Turkish datasets and to the class which have many documents in English datasets. In terms of average scores, the highest classification was obtained in Turkish datasets as follows: with not applying lowercase, applying stemming and removing stop words, and in English datasets as follows: with applying lowercase and stemming, removing stop words. Applying stemming was the most important preprocessing method which increases the success in Turkish datasets, whereas removing stop words in English datasets. The maximum scores revealed that feature selection, feature size and classifier are more effective than preprocessing in classification success. It was concluded that preprocessing is necessary for text classification because it shortens the processing time and can achieve high classification success, a preprocessing method does not have the same effect in all languages, and different preprocessing methods are more successful for different languages.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.13-27
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• 2014

Agile methodologies have gained recognition as efficient development processes through their quick delivery of software, even under time constraints. However, like other agile methods such as Scrum, Extreme Programming (XP) and The Dynamic Systems Development Method (DSDM), Feature Driven Development (FDD) has been criticized due to the unavailability of security elements in its twelve practices. In order to examine this matter more closely, we conducted a systematic literature review (SLR) and studied literature for the years 2001-2012. Our findings highlight that, in its current form, the FDD model partially supports the development of secure software. However, there is little research on this topic, as detailed information about the usage of secure software is rarely published. Thus, we have been able to conclude that the existing five phases of FDD have not been enough to develop secure software until recently. For this reason, security-based phase and practices in FDD need to be proposed.