• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.537-544
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• 2022

As the penetration of electric vehicles and development of new models, user experience factors are getting more important in designing connectivity systems for car infotainment services. The primary object of this study is to identify commonalities and differences by comparing user experience factors in the Korean and US electric vehicle markets. This study derived connectivity keywords by text mining the vehicle introduction on the market in each country, and performed centrality, cluster analysis and visualization mapping using the semantic network analysis. As a result, the Korean new electric vehicle connectivity service mainly focused on driving functions such as driving, parking assistance, and charging, while US focused on device connection, convenience function control, app use, entertainment viewing. Based on the analysis, this study presented the practical implications in marketing, system design, and HMI design.

• Design Convergence Study
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• v.15 no.6
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• pp.255-270
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• 2016

The purpose of this research is to establish the UX methodology knowledge optimized for small sized companies on the basis of theoretical and practical UX development process models. The 7 UX design process models were analyzed by the outcomes and attributes on each design stage from academic field. Then the interview and observation on 18 domestic companies were conducted to clarify the actual methods in use and the gab from the academic theories. The two different design model were unified as an product lifecycle coupled UX process (PLUS). The 100 theory-industry knowedge combined UX design methodologies were selected and aligned along with 6 design stages of PLUS process. Each method was decomposed as a template format that contains standardized attributes applicable for small companies under consideration of their resources, process and produced items. The result of this research is expected to be applied onto real industry and reduce the risk of small manufacturing companies to escalate the quality of UX in their productions.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.2
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• pp.93-114
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• 2023

In accordance with the educational paradigm that values self-directed creative education, school libraries and public libraries emphasize self-directed learning support through curriculum-linked programs as their main tasks. For self-directed learning, it is essential to provide learner-centered educational knowledge information, and there should be abundant textbook-linked references that can deepen and expand the curriculum reflected in textbooks. This study established KDC-linked information related to unit and cross-curricular learning topics through the analysis of elementary school textbooks and curriculum-linked books, restructured KDC system based on major subjects in the elementary school curriculum, and established a curriculum-linked subject information. Libraries can strengthen support for self-directed creative learning for elementary school students in an online environment by linking library content targeted for each user with elementary school education content focusing on learning topics in the curriculum.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.123-136
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• 2006

The prefetching technique is an effective way to reduce the latency caused memory access. However, excessively aggressive prefetch not only leads to cache pollution so as to cancel out the benefits of prefetch but also increase bus traffic leading to overall performance degradation. In this thesis, a prefetch filtering scheme is proposed which dynamically decides whether to commence prefetching by referring a filtering table to reduce the cache pollution due to unnecessary prefetches In this thesis, First, prefetch hashing table 1bitSC filtering scheme(PHT1bSC) has been shown to analyze the lock problem of the conventional scheme, this scheme such as conventional scheme used to be N:1 mapping, but it has the two state to 1bit value of each entries. A complete block address table filtering scheme(CBAT) has been introduced to be used as a reference for the comparative study. A prefetch block address lookup table scheme(PBALT) has been proposed as the main idea of this paper which exhibits the most exact filtering performance. This scheme has a length of the table the same as the PHT1bSC scheme, the contents of each entry have the fields the same as CBAT scheme recently, never referenced data block address has been 1:1 mapping a entry of the filter table. On commonly used prefetch schemes and general benchmarks and multimedia programs simulates change cache parameters. The PBALT scheme compared with no filtering has shown enhanced the greatest 22%, the cache miss ratio has been decreased by 7.9% by virtue of enhanced filtering accuracy compared with conventional PHT2bSC. The MADT of the proposed PBALT scheme has been decreased by 6.1% compared with conventional schemes to reduce the total execution time.

• Journal of IKEEE
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• v.17 no.4
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• pp.407-417
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• 2013

In this paper, a reconfigurable peripheral unit for LED lighting communication is presented. Embedded lighting devices require various communication protocols. Usually, serial communication protocols and lighting control communication protocols such as DALI, DMX512, UART, SPI, IrDA, etc. are used in lighting devices. When the requirements of communication protocols are satisfied with separate IPs, the cost and the power consumption can considerably increase. We propose a reconfigurable communication peripheral unit which uses analysis of signal formats of the protocols. The gate count of the reconfigurable peripheral unit uses only 57% of the gate count of the separate implementation. Also, in this paper, a mapping table based DALI-ZigBee interfacing method for flexible lighting network configurations is proposed. Using this method, various DALI-ZigBee network systems can be easily set up. An LED lighting system platform is implemented to verify the operation of the DALI-ZigBee interfacing method. The reconfigurable peripheral unit and the DALI-ZigBee interfacing method can be efficiently used to implement various wired/wireless lighting communication systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.96-105
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• 1998

The aim of this paper is to propose the method of WDHMM(Weighted DHMM), using the MLP-VQ for the improvement of speaker-independent connect-digit recognition system. MLP neural-network output distribution shows a probability distribution that presents the degree of similarity between each pattern by the non-linear mapping among the input patterns and learning patterns. MLP-VQ is proposed in this paper. It generates codewords by using the output node index which can reach the highest level within MLP neural-network output distribution. Different from the old VQ, the true characteristics of this new MLP-VQ lie in that the degree of similarity between present input patterns and each learned class pattern could be reflected for the recognition model. WDHMM is also proposed. It can use the MLP neural-network output distribution as the way of weighing the symbol generation probability of DHMMs. This newly-suggested method could shorten the time of HMM parameter estimation and recognition. The reason is that it is not necessary to regard symbol generation probability as multi-dimensional normal distribution, as opposed to the old SCHMM. This could also improve the recognition ability by 14.7% higher than DHMM, owing to the increase of small caculation amount. Because it can reflect phone class relations to the recognition model. The result of my research shows that speaker-independent connected-digit recognition, using MLP-VQ and WDHMM, is 84.22%.

• Composites Research
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• v.33 no.3
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• pp.108-114
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• 2020

Piecewise Integrated Composite (PIC) beam is composed of different stacking against loading type depending upon location. The aim of current study is to assign robust stacking sequences against external loading to every corresponding part of the PIC beam based on the value of stress triaxiality at generated reference points using the k-NN (k-Nearest Neighbor) classification, which is one of representative machine learning techniques, in order to excellent superior bending characteristics. The stress triaxiality at reference points is obtained by three-point bending analysis of the Al beam with training data categorizing the type of external loading, i.e., tension, compression or shear. Loading types of each plane of the beam were classified by independent plane scheme as well as total beam scheme. Also, loading fidelities were calibrated for each case with the variation of hyper-parameters. Most effective stacking sequences were mapped into the PIC beam based on the k-NN classification model with the highest loading fidelity. FE analysis result shows the PIC beam has superior external loading resistance and energy absorption compared to conventional beam.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.1
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• pp.33-37
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• 2022

Purpose ¹⁸F-Florbetaben (FBB) Readings are made by visually comparing the signal strengths of gray matter and white matter. We intend to evaluate the usefulness of image analysis by comparing quantified image analysis with readout. Materials and Methods Based on the reading results, 100 patients were divided into a negative scan and a positive scan, and 300 MBq of FBB was injected, and images were taken 90 minutes later for 20 minutes. The equipment was a Discovery 600 (GE Healthcare, MI, USA). Four regions of interest (lateral temporal lobes, frontal lobes, posterior cingulate & precuneus, and parietal lobes) were established based on the amyloid reading standard provided by the manufacturer. For image analysis, SUVratio (SUVr) was calculated by dividing each SUVmean by the cerebellum, and the average SUVr in the entire area was performed. Statistical analysis analyzed the cutoff derivation through ROC Curve, the difference between groups in Independent sample t-test, and the degree of agreement with the reading result through Kappa test. Results The average SUVr cutoff in the entire area was 1.23. Concordance with the read results using cutoff was 95/100 (95%) for negative and 92/100 (92%) for positive. As a result of the t-test, there was a statistically significant difference between the groups (P < 0.05), and the Kappa statistical result showed a high degree of agreement with 0.867 (P < 0.05). Conclusion The results of image analysis were statistically significant and showed a high degree of agreement with the reading results. In addition, FBB image analysis can be viewed by 3D mapping the area where amyloid is accumulated, location estimation is possible, and quantitative analysis results can be viewed in detail. If quantified FBB image analysis is used as an auxiliary indicator, it is thought to be helpful in reading.