• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.943-949
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• 2010

This paper presents some improvements on VLSI implementation of lifting-based 9/7 wavelet transform by optimization hardware multiplication. The proposed solution requires less logic area and power consumption without performance loss compared to previous wavelet filter structure based on lifting scheme. This paper proposes a better approach to the hardware implementation using Lefevre algorithm based on extensions of Pattern search methods. To compare the proposed structure to the previous solutions on full multiplier blocks, we implemented them using Verilog HDL. For a hardware implementation of the two solutions, the logical synthesis on 0.18 um standard cells technology show that area, maximum delay and power consumption of the proposed architecture can be reduced up to 51%, 43% and 30%, respectively, compared to previous solutions for a 200 MHz target clock frequency. Our evaluation show that when design VLSI chip of lifting-based 9/7 wavelet filter, our solution is better suited for standard-cell application-specific integrated circuits than prior works on complete multiplier blocks.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.655-664
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• 2020

Free viewpoint image synthesis technology is one of the important technologies in the MPEG-I (Immersive) standard. RVS (Reference View Synthesizer) developed by MPEG-I and in use in MPEG group is a DIBR (Depth Information-Based Rendering) program that generates an image at a virtual (intermediate) viewpoint from multiple viewpoints' inputs. RVS uses the mesh surface method based on computer graphics, and outperforms the pixel-based ones by 2.5dB or more compared to the previous pixel method. Even though its OpenGL version provides 10 times speed up over the non OpenGL based one, it still shows a non-real-time processing speed, i.e., 0.75 fps on the two 2k resolution input images. In this paper, we analyze the internal of RVS implementation and modify its structure, achieving 34 times speed up, therefore, real-time performance (22-26 fps), through the 3 key improvements: 1) the reuse of OpenGL buffers and texture objects 2) the parallelization of file I/O and OpenGL execution 3) the parallelization of GPU shader program and buffer transfer.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.343-349
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• 2009

In this paper, it would be shown that individuals can have different responses to the same email based on their preferences through computing the distributions of user clusters' email responses from clustering results based on email users' preference information. This paper presents an approach that incorporates user preferences to construct an anti-spam mail system, which is different from the conventional content-based ones. We consider email category information derived from the email content as well as user preference information. We also build a user preference ontology to formally represent the important concepts and rules derived from a data mining process and then apply a rule optimization procedure to exclude unnecessary rules. Experimental results show that our user preference based system achieves good performance in terms of accuracy, the rules derived from the system and human comprehensibility.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.547-557
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• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.326-331
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• 2021

In this study, the preparation conditions for a TiO₂-based vanadium-based catalyst for oxidizing hydrogen sulfide at room temperature were optimized. Four types of commercial TiO₂ were used as a catalyst support and the performance evaluation of hydrogen sulfide oxidation at room temperature of V/TiO₂ by varying vanadium contents prepared using the impregnation method was performed. Among the types of TiO₂ tested, it was confirmed that the catalyst with the vanadium content of 5% and based on TiO₂(A) has the best hydrogen sulfide conversion rate of 58%. By comparing the physical and chemical properties of the catalyst, the specific surface area of the support and the species of dominant vanadium are the major factor in catalyst performance. In order to confirm the regeneration characteristics of the catalyst with reduced activity, heat treatment was performed at 400 ℃ for 2 h, and the amount of hydrogen sulfide oxidation decreased by 10% due to the partial deposition of sulfur in the regenerated catalyst, but it was confirmed that the initial performance was similar.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.181-192
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• 2022

Active vibration control system(AVCS) for helicopter enables to control the vibration generated from the main rotor and has the superb vibration reduction performance with low weight compared passive vibration reduction device. In this paper, FxLMS algorithm-based vibration control software of the light civil helicopter tansmits the control command calculated using the signals of the tachometer and accelerometers to the circular force generator(CFG) is developed and verified. According to the RTCA DO-178C/DO-331, the vibration control software is developed through the model based design technique, and real-time operation performance is evaluated in PILS(processor in-the loop simulation) and HILS(hardware in-the loop simulation) environments. In particular, the reliability of the software is improved through the LDRA-based verification coverage in the PIL environments. In order to AVCS to light civil helicopter(LCH), the dynamic response characteristic model is obtained through the ground/flight tests. AVCS configuration which exhibits the optimal performance is determined using system optimization analysis and flight test and obtain STC certification.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1307-1307
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• 2024

Recent research on heavy equipment has been conducted for the purposes of enhanced safety, productivity improvement, and carbon neutrality at construction sites. A sensor-based approach is being explored to monitor the location and movements of heavy equipment in real time. However, it poses significant challenges in terms of time and cost as multiple sensors should be installed on numerous heavy equipment at construction sites. In addition, there is a limitation in identifying the collaboration or interference between two or more heavy equipment. In light of this, a vision-based deep learning approach is being actively conducted to effectively respond to various working conditions and dynamic environments. To enhance the performance of a vision-based activity recognition model, it is essential to secure a sufficient amount of training datasets (i.e., video datasets collected from actual construction sites). However, due to safety and security issues at construction sites, there are limitations in adequately collecting training dataset under various situations and environmental conditions. In addition, the videos feature a sequence of multiple activities of heavy equipment, making it challenging to clearly distinguish the boundaries between preceding and subsequent activities. To address these challenges, this study proposed a domain adaptation in vision-based transfer learning for automated excavator activity recognition utilizing 3D ResNet (residual deep neural network). Particularly, this study aimed to identify the optimal depth of 3D ResNet (i.e., the number of layers of the feature extractor) suitable for domain adaptation via fine-tuning process. To achieve this, this study sought to evaluate the activity recognition performance of five 3D ResNet models with 18, 34, 50, 101, and 152 layers, which used two consecutive videos with multiple activities (5 mins, 33 secs and 10 mins, 6 secs) collected from actual construction sites. First, pretrained weights from large-scale datasets (i.e., Kinetic-700 and Moment in Time (MiT)) in other domains (e.g., humans, animals, natural phenomena) were utilized. Second, five 3D ResNet models were fine-tuned using a customized dataset (14,185 clips, 60,606 secs). As an evaluation index for activity recognition model, the F1 score showed 0.881, 0.689, 0.74, 0.684, and 0.569 for the five 3D ResNet models, with the 18-layer model performing the best. This result indicated that the activity recognition models with fewer layers could be advantageous in deriving the optimal weights for the target domain (i.e., excavator activities) when fine-tuning with a limited dataset. Consequently, this study identified the optimal depth of 3D ResNet that can maintain a reliable performance in dynamic and complex construction sites, even with a limited dataset. The proposed approach is expected to contribute to the development of decision-support systems capable of systematically managing enhanced safety, productivity improvement, and carbon neutrality in the construction industry.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.77-90
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• 2018

Software Defect Prediction (SDP) is a field of study that identifies defective modules. With insufficient local data, a company can exploit Cross-Project Defect Prediction (CPDP), a way to build a classifier using dataset collected from other companies. Most machine learning algorithms for SDP have used more than one parameter that significantly affects prediction performance depending on different values. The objective of this study is to propose a parameter selection technique to enhance the performance of CPDP. Using a Harmony Search algorithm (HS), our approach tunes parameters of cost-sensitive boosting, a method to tackle class imbalance causing the difficulty of prediction. According to distributional characteristics, parameter ranges and constraint rules between parameters are defined and applied to HS. The proposed approach is compared with three CPDP methods and a Within-Project Defect Prediction (WPDP) method over fifteen target projects. The experimental results indicate that the proposed model outperforms the other CPDP methods in the context of class imbalance. Unlike the previous researches showing high probability of false alarm or low probability of detection, our approach provides acceptable high PD and low PF while providing high overall performance. It also provides similar performance compared with WPDP.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.47-47
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• 2010

Over the past 20 years, constant progress in noise and vibration (NVH) engineering has enabled to constantly advance quality and comfort of operation and use of really any products - from automobiles to aircraft, to all kinds of industrial vehicles and machines - to the extend that for many products, supreme NVH performance has becomes part of its brand image in the market. At the same time, the product innovation agenda in the automotive, aircraft and really many other industries, has been extended very much in recent years by meeting ever more strict environmental regulations. Like in the automotive industry, the drive towards meeting emission and CO2 targets leads to very much accelerated adoption of new powertrain concepts (downsizing of ICE, hybrid-electrical...), and to new vehicle architectures and the application of new materials to reduce weight, which bring new challenges for not only maintaining but further improving NVH performance. This drives for innovation in NVH engineering, so as to succeed in meeting a product brand performance for NVH, while as the same time satisfying eco-constraints. Product innovation has also become increasingly dependent on the adoption of electronics and software, which drives for new solutions for NVH engineering that can be applied for NVH performance optimization of mechatronic products. Finally, relentless pressure to shorten time to market while maintaining overall product quality and reliability, mandates that the practice and solutions for NVH engineering can be optimally applied in all phases of product development. The presentation will first review the afore trends for product and process innovation, and discuss the challenges they represent for NVH engineering. Next, the presentation discusses new solutions for NVH engineering of products, so as to meet target brand values, while at the same time meeting ever more strict eco constraints, and this within a context of increasing adoption of electronics and controls to drive product innovation. NVH being very much defined by system level performance, these solutions implement the approach of "Model Based System Engineering" to increase the impact of system level analysis for NVH in all phases of product development: - At the Concept Phase, to be able to do business case analysis of new product concepts; to arrive at an optimized and robust product architecture (e.g. to hybrid powertrain lay-out, to optimize fuel economy); to enable target cascading, to subsystem and component level. - In Development Phase, to increase realism and productivity of simulation, so as to frontload virtual validation of components and subsystems and to further reduce reliance on physical testing. - During the final System Testing Phase, to enable subsystem testing by a combination of physical testing and simulation: using simulation models to simulate the final integration context when testing a subsystem, enabling to frontload subsystem testing before final system integration is possible. - To interconnect Mechanical, Electronical and Controls engineering, in all phases of development, by supporting model driven controls engineering (MIL, SIL, HIL). Finally, the presentation reviews examples of how LMS is implementing such new applications for NVH engineering with lead customers in Europe, Asia and US, with demonstrated benefits both in terms of shortening development cycles, and/or enabling a simulation based approach to reduce reliance on physical testing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5B
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• pp.500-511
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• 2003

To prevent performance degradation of TCP due to packet losses in the smooth handoff by the route optimization extension of Mobile IP protocol, a buffering of packets at a base station is needed. A buffering of packets at a base station recovers those packets dropped during handoff by forwarding buffered packets at the old base station to the mobile user. But, when the mobile user moves to a congested base station in a new foreign subnetwork, those buffered packets forwarded by the old base station are dropped and the wireless link utilization performance degrades due to increased congestion by those forwarded packets. In this paper, considering the case that a mobile user moves to a congested base station in a new foreign subnetwork, we propose an Implicit Priority Packet Forwarding to improve TCP performance in mobile networks. In the proposed scheme, the old base station marks a buffered packet as a priority packet during handoff. In addition, RED (Random Early Detection) at the new congested base station does not include priority packets in queue size and does not drop those packets randomly based on average queue size. Simulation results show that wireless link utilization performance of mobile hosts can be improved without modification to Mobile IP protocol by applying proposed Implicit Priority Packet Forwarding.