• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.567-582
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• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.5
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• pp.428-434
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• 2016

A lot of drawings for pipe construction and installation are needed to construct plant process system on the offshore plant structures. Depending on their scale or complexity, the required number of drawings related pipes sometimes amounts to several hundreds of thousands. Most major shipyards, therefore, have their own system which can automatically depict pipes’ geometric, manufacturing, and BOM(Bill of Material) information on the drawings. However, as the complexity and absolute quantity in the isometric region on the drawings is increased, the information extraction from the customized DB and positioning at the typical locations does not get to be enough to avoid the overlap between geometric contours, labels, and symbols. For this reason, the novel methods to arrange additional annotations without overlaps are presented in the paper. This approach is expected to increase the readability and legibility of the drawing and prevent the human error, and finally decrease the time-consuming and tedious jobs which are unnecessarily required to designers.

• Journal of Semiconductor Engineering
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• v.2 no.3
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• pp.136-141
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• 2021

This paper analyzes the tree expansion for multiple-input multiple-output (MIMO) detection in the viewpoint of hardware implementation. The tree expansion is to calculate path metrics of child nodes performed in every visit to a node while traversing the detection tree. Accordingly, the tree-expansion unit (TEU), which is responsible for such a task, has been an essential component in a MIMO detector. Despite the paramount importance, the analyses on the TEUs in the literature are not thorough enough. Accordingly, we further investigate the hardware complexity of the TEUs to suggest a guideline for selection. In this paper, we focus on a pair of major ways to implement the TEU: 1) a full parallel realization; 2) a transformation of the formulae followed by common subexpression elimination (CSE). For a logical comparison, the numbers of multipliers and adders are first enumerated. To evaluate them in a more practical manner, the TEUs are implemented in a 65-nm CMOS process, and their propagation delays, gate counts, and power consumptions were measured explicitly. Considering the target specification of a MIMO system and the implementation results comprehensively, one can choose which architecture to adopt in realizing a detector.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2103-2118
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• 2024

Chinese herbal slices (CHS) automated recognition based on computer vision plays a critical role in the practical application of intelligent Chinese medicine. Due to the complexity and similarity of herbal images, identifying Chinese herbal slices is still a challenging task. Especially, easily-confused CHS have higher inter-class and intra-class complexity and similarity issues, the existing deep learning models are less adaptable to identify them efficiently. To comprehensively address these problems, a novel tiny easily-confused CHS dataset has been built firstly, which includes six pairs of twelve categories with about 2395 samples. Furthermore, we propose a ResNeSt-CHS model that combines multilevel perception fusion (MPF) and perceptive sparse fusion (PSF) blocks for efficiently recognizing easilyconfused CHS images. To verify the superiority of the ResNeSt-CHS and the effectiveness of our dataset, experiments have been employed, validating that the ResNeSt-CHS is optimal for easily-confused CHS recognition, with 2.1% improvement of the original ResNeSt model. Additionally, the results indicate that ResNeSt-CHS is applied on a relatively small-scale dataset yet high accuracy. This model has obtained state-of-the-art easily-confused CHS classification performance, with accuracy of 90.8%, far beyond other models (EfficientNet, Transformer, and ResNeSt, etc) in terms of evaluation criteria.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.37-43
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• 2020

In this paper, we propose an efficient AB² multiplication algorithm using SPB(shifted polynomial basis) over finite fields. Using the feature of the SPB, we split the equation for AB² multiplication into two parts. The two partitioned equations are executable at the same time, and we derive an algorithm that processes them in parallel. Then we propose an efficient semi-systolic AB² multiplier based on the proposed algorithm. The proposed multiplier has less area-time (AT) complexity than related multipliers. In detail, the proposed AB² multiplier saves about 94%, 87%, 86% and 83% of the AT complexity of the multipliers of Wei, Wang-Guo, Kim-Lee, Choi-Lee, respectively. Therefore, the proposed multiplier is suitable for VLSI implementation and can be easily adopted as the basic building block for various applications.

• Journal of KIISE
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• v.41 no.11
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• pp.935-942
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• 2014

Today, it is very important issue to high quality of software issue on huge scale of code and time-to-market. In the industrial fields still developers focuses on Code based development. Therefore we try to consider two points of views 1) improving the general developer the bad development habit, and 2) maintenance without design, documentation and code visualization. To solve these problems, we need to make the code visualization of code. In this paper, we suggest how to visualize the inner structure of code, and also how to proceed improvement of quality with constructing the Tool-Chain for visualizing Java code's inner structure. For our practical case, we applied Object Code with NIPA's SW Visualization, and then reduced code complexity through quantitatively analyzing and visualizing code based on setting the basic module unit, the class of object oriented code.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.57-66
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• 2014

This paper presents a low-complexity barrel distortion correction processor for wide-angle cameras. The proposed processor performs the barrel distortion correction jointly with the color demosaicking, so that the hardware complexity can be reduced significantly. In addition, to reduce the required memory bandwidth, an efficient memory interface is proposed by utilizing the spatial locality of the memory access in the correction process. The proposed processor is implemented with 35K logic gates in a $0.11-{\mu}m$ CMOS process and its correction speed is 150 Mpixels/s at the operating frequency of 606MHz, where the supported frame size is $2048{\times}2048$ and the required memory bandwidth is 1 read/cycle.

• Architectural research
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• v.4 no.1
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• pp.7-16
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• 2002

In order to examine theoretical underpinnings of preference for built forms, 129 subjects are asked to rate a series of 9 slides of residential houses depicting a wide range of architectural styles on a 5 point scale, for coherence, complexity, excitement, familiarity, and natural harmony, respectively. Based on Lee's (2002a, 2002b) two previous studies addressing the issue of aesthetic beauty evaluation for man-made creatures (e.g., residential housing scenes), this study summarizes several meaningful findings. As reported by all the subjects, first, both "desire to visit" and "desire to live in" turned out to be a good predictor of preference as the two measures are highly correlated in statistically significant levels (99.9%). People who desire to visit a spot are more likely to desire to live in it. Second, Pearson's correlations showed that coherence is the opposite end of complexity. The more likely a housing setting is hanging together, the less likely it looks to be complex. Overall, though, it is not clear that the two variables work directly in that way, as weighted on preference ratings. That is, coherence and complexity are likely to be totally two independent systems that affect the ratings of preference. Third, both excitement and environmental sensitivity (e.g., harmony of a house with its surrounding nature) most highly account for the preference for various housing scenes, while familiarity has only a little effect on preference ratings. Possibly, people like or dislike a visual thing, no matter how much they are familiar with it. Finally, this study suggested that design professionals could communicate effectively with their clients if sets of visual standards as an appropriate communication tool for better design are properly established.

• Journal of Information Technology Services
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• v.22 no.5
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• pp.71-86
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• 2023

Recently, various geographic information systems have been used based on spatial information of geographic information systems. Accordingly, it is essential to produce a large-scale map as a small-scale map for various uses of spatial information. However, maps currently being produced have inconsistencies between data due to production timing and limitations in expression, and productivity efficiency is greatly reduced due to errors in products or overlapping processes. In order to improve this, various efforts are being made, such as publishing research and reports for automating domestic mapping, but because there is no specific result, it relies on editors to make maps. This is mainly done by hand, so the time required for mapping is excessive, and quality control for each producer is different. In order to solve these problems, technology that can be automatically produced through computer programs is needed. Research has been conducted to apply the rule base to geometric generalization. The algorithm tolerance setting applied to rule-based modeling is a factor that greatly affects the result, and the level of the result changes accordingly. In this paper, we tried to study the effectiveness of mapping according to tolerance setting. To this end, the utility was verified by comparing it with a manually produced map. In addition, the original data and reduction rate were analyzed by applying generalization algorithms and tolerance values. Although there are some differences by region, it was confirmed that the complexity decreased on average. Through this, it is expected to contribute to the use of spatial information-based services by improving tolerances suitable for small-scale mapping regulations in order to secure spatial information data that guarantees consistency and accuracy.