• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.539-548
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• 2015

In this paper, shared memory feature was developed in multi-core system with different OS for different processor-specific bus, while conducting an experiment on shared memory feature between the two processors based on embedded Linux system. For the purpose of developing shared memory in dual bus structure, memory controller was used, while managing shared memory segment through list data structure. For AMP multi-core test, Linux OS was installed in 2 processor cores. In addition, it verified the creation and use of shared memory by using kernel module implemented to test shared memory.

• Korean Institute of Interior Design Journal
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• v.27 no.2
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• pp.77-85
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• 2018

The number of household living alone including young single adults has gradually increased. The purpose of this study is to examine the demand on housing options, additional space, shared space, community facilities, housing service for young adults living alone including college students. A total of 180 questionnaire were collected and analyzed. For housing location, commuting distance is the most important feature and amenities are the second important feature. For additional space, there is a significant difference between male and female single residents. Female residents want to install dress room most while male adults want to have a study room. For the shared house option, single adults concerns housing fee and living cost most. However, female adults concern safety and security issues much more than male ones do. The degree of preference to community facilities varies between male and female single residents. The findings suggest more differentiated approaches are needed for alternative housing options for male and female residents.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.778-785
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• 2009

This paper presents a Gabor texture feature extraction method for classification of discolored Metal pad images using GPU(Graphics Processing Unit). The proposed algorithm extracts the texture information using Gabor filters and constructs a pattern map using the extracted information. Finally, the golden pad images are classified by utilizing the feature vectors which are extracted from the constructed pattern map. In order to evaluate the performance of the Gabor texture feature extraction algorithm based on GPU, a sequential processing and parallel processing using OpenMP in CPU of this algorithm were adopted. Also, the proposed algorithm was implemented by using Global memory and Shared memory in GPU. The experimental results were demonstrated that the method using Shared memory in GPU provides the best performance. For evaluating the effectiveness of extracted Gabor texture features, an experimental validation has been conducted on a database of 20 Metal pad images and the experiment has shown no mis-classification.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.641-647
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• 2002

In this paper, we propose the reduction method of the number of parameters in the segmental-feature HMM using trend quantization method. The proposed method shares the trend information of the polynomial trajectories by quantization. The trajectory is obtained by the sequence of feature vectors of speech signals and can be divided by trend and location information. The trend indicates the variation of consequent frame features, while the location points to the positional difference of the trajectories. Since the trend occupies the large portion of SFHMM, if the trend is shared, the number of parameters maybe decreases. To exploit the proposed system the experiments are performed on TIMIT corpus. The experimental results show that the performance of the proposed system is roughly similar to that of previous system. Therefore, the proposed system can be considered one of parameter reduction method.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.2
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• pp.234-243
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• 2011

Mindmap is effective method to analyze informations. And, through mindmap, students can be able to grow their ability of logical reconstruction. In Modern society, people have been developing IT technology and variety of portable devices. So, Educational environments have been being changed accordingly, too. In this study, we have implemented mindmap application that based on android to share the group member's thinking. To effective sharing, we have used mindmap technique and photo attachment feature. In this study, expert evaluation has been carried out by elementary current teachers. In result of this expert evaluation, we have obtained positive feedback at sharing function, input technique and information display. Also, teachers have gave feedbacks that they are willing to use this application in class, if classroom environment is possible.

• Korean Journal of Computational Design and Engineering
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• v.11 no.3
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• pp.164-171
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• 2006

As collaborative design and configuration design are of increasing importance in product development, it becomes essential to exchange the feature and parametric CAD models among participants. A history-based parametric method has been proposed and implemented. But each translator which exchanges the feature and parametric information tends to be heavy because to implement duplicated functions such as the identification of the selected geometries, mapping between features which have different attributes. Furthermore. because the history-based parametric translator uses the procedural model as the neutral format, which is the XML macro file, the history-based parametric translators need a geometric modeling kernel to generate an internal explicit geometric model. To ease the problem, we implemented a shared integration platform, the TransCAD. The TransCAD separates translators from the XML macro files. The translators for various CAD systems need to communicate with only the TransCAD. To support the communication with the TransCAD, we exposed the functions of the TransCAD by using the Automation APIs, which is developed by Microsoft. The Automation APIs of the TransCAD consist of the part modeling functions, the data extraction functions, and the utility functions. Each translator uses these functions to translate a parametric CAD model from the sending CAD system into the XML format, or from the in format into the model of the receiving CAD system This paper introduces what the TransCAD is and how it works for the exchange of the feature and parametric models.

• Korean Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.177-188
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• 1996

An approach to providing computational support with an expert shell is discussed with the scope of an industrial wire harness design, especially at a manufacturing stage. Key issues include the development of an architecture that supports a frequent design change among engineers associated with different parts of the wiring design process and the development of hierarchical representations that capture the different characteristics (e.g., connectivity, configuration) of the harnesses. The abstraction of design information results in features, while the abstraction of drawing elements leads to the definition of objects. These abstractions are essential for efficient transactions among people and computer tools in a domain that involves numerous interacting constraints. In this paper the strategy for the problem decomposition, the definition of features, and the ways in which features are shared by various operations and design changes, are discussed. We conclude with a discussion of some of the issues raised by the project and the steps underway to address them.

• Journal of Korea Multimedia Society
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• v.15 no.5
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• pp.606-614
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• 2012

Face detection using AdaBoost algorithm is one of the fastest and the most robust face detection algorithm so many improvements or extensions of this method have been proposed. However, almost all previous approaches deal with only frontal face and suffer from limited discriminant capability for inclined face because these methods apply the same features for both frontal and inclined face. Also conventional approaches for detecting inclined face which apply frontal face detecting method to inclined input image or make different detectors for each angle require heavy computational complexity and show low detection rate. In order to overcome this problem, a method for detecting inclined face using JointBoost is proposed in this paper. The computational and sample complexity is reduced by finding common features that can be shared across the classes. Simulation results show that the detection rate of the proposed method is at least 2% higher than that of the conventional AdaBoost method under the learning condition with the same iteration number. Also the proposed method not only detects the existence of a face but also gives information about the inclined direction of the detected face.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• Korean Journal of Cognitive Science
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• v.27 no.3
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• pp.355-376
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• 2016

We used holes defined by color similarity (Experiment 1) and binocular disparity (Experiment 2) to study how the inner contour of an object (i.e., boundary of a hole in it) is encoded in visual working memory. Many studies in VWM have shown that an object's boundary properties can be integrated with its surface properties via their shared spatial location, yielding an object-based encoding benefit. However, encoding of the hole contours has rarely been tested. We presented objects (squares or circles) containing a bar under a change detection paradigm, and relevant features to be remembered were the color of objects and the orientation of bars (or holes). If the contour of a hole belongs to the surrounding object rather than to the hole itself, the object-based feature binding hypothesis predicts that the shape of it can be integrated with color of an outer object, via their shared spatial location. Thus, in the hole display, change detection performance was expected to better than in the conjunction display where orientation and color features to be remembered were assigned to different parts of a conjunction object, and comparable to that in a single bar display where both orientation and color were assigned into a single bar. However, the results revealed that performance in the hole display did not differ from that in the conjunction display. This suggests that the shape of holes is not automatically encoded together with the surface properties of the outer object via object-based feature binding, but encoded independently from the surrounding object.