• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4948-4967
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• 2017

On mobile devices, image sequences are widely used for multimedia applications such as computer vision, video enhancement, and augmented reality. However, the real-time processing of mobile devices is still a challenge because of constraints and demands for higher resolution images. Recently, heterogeneous computing methods that utilize both a central processing unit (CPU) and a graphics processing unit (GPU) have been researched to accelerate the image sequence processing. This paper deals with various optimizing techniques such as parallel processing by the CPU and GPU, distributed processing on the CPU, frame buffer object, and double buffering for parallel and/or distributed tasks. Using the optimizing techniques both individually and combined, several heterogeneous computing structures were implemented and their effectiveness were analyzed. The experimental results show that the heterogeneous computing facilitates executions up to 3.5 times faster than CPU-only processing.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.454-462
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• 2014

With the development of location aware technologies and mobile devices, location-based services have been studied. To provide location-based services, many researchers proposed methods for processing various query types with Mapreduce(MR). One of the proposed methods, is a Reverse k-nearest neighbor(RkNN) query processing method with MR. However, the existing methods spend too much cost to process the continuous RkNN query. In this paper, we propose an efficient continuous RkNN query processing method with MR to resolve the problems of the existing methods. The proposed method uses the 60-degree-pruning method. The proposed method does not need to reprocess the query for continuous query processing because the proposed method draws and monitors the monitoring area including the candidate objects of a RkNN query. In order to show the superiority of the proposed method, we compare it with the query processing performance of the existing method.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.57-63
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• 2019

During the last two decades, much joint research regarding vibration based methods has been done, leading to developing various algorithms and techniques. These algorithms and techniques can be divided into modal methods and signal methods. Although modal methods have been widely used for health monitoring and damage detection, signal methods due to higher efficiency have received considerable attention in various fields, including aerospace, mechanical and civil engineering. Signal-based methods are derived directly from the recorded responses through signal processing algorithms to detect damage. According to different signal processing techniques, signal-based methods can be divided into three categories including time domain methods, frequency domain methods, and time-frequency domain methods. The frequency domain methods are well-known and interest in using them has increased in recent years. To determine dynamic behaviours, to identify systems and to detect damages of bridges, different methods and algorithms have been proposed by researchers. In this study, a new algorithm to detect seismic damage in the bridge's piers is suggested. To evaluate the algorithm, an analytical model of a bridge with simple spans is used. Based on the algorithm, before and after damage, the bridge is excited by a sine force, and the piers' responses are measured. The dynamic specifications of the bridge are extracted by Power Spectral Density function. In addition, the Least Square Method is used to detect damage in the bridge's piers. The results indicate that the proposed algorithm can identify the seismic damage effectively. The algorithm is output-only method and measuring the excitation force is not needed. Moreover, the proposed approach does not need numerical models.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.338-357
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• 2016

The recent advent of increasingly affordable and powerful 3D scanning devices capable of capturing high resolution range data about real-world objects and environments has fueled research into effective 3D surface reconstruction techniques for rendering the raw point cloud data produced by many of these devices into a form that would make it usable in a variety of application domains. This paper, therefore, provides an overview of the existing literature on surface reconstruction from 3D point clouds. It explains some of the basic surface reconstruction concepts, describes the various factors used to evaluate surface reconstruction methods, highlights some commonly encountered issues in dealing with the raw 3D point cloud data and delineates the tradeoffs between data resolution/accuracy and processing speed. It also categorizes the various techniques for this task and briefly analyzes their empirical evaluation results demarcating their advantages and disadvantages. The paper concludes with a cross-comparison of methods which have been evaluated on the same benchmark data sets along with a discussion of the overall trends reported in the literature. The objective is to provide an overview of the state of the art on surface reconstruction from point cloud data in order to facilitate and inspire further research in this area.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.250-257
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• 2010

As the variant of skyline query processing, reverse skyline Queries have been studied. However, the existing methods for processing reverse skyline Queries have the limitation of service domains and spend high costs to provide various location-based services. In this paper, we propose a new reverse skyline Query processing method that efficiently processes a query with the objects in metric spaces. In addition, the proposed method also processes continuous reverse skyline queries efficiently. In order to show the superiority of the proposed scheme, we compare it with the previous reverse skyline 벼ery processing scheme in various environments. As a result, the proposed method achieves better performance than the existing method.

• Transactions of Materials Processing
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• v.24 no.1
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• pp.5-12
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• 2015

In the current study, fundamental deep drawing characteristics of Ti-6Al-4V alloy sheets were investigated to establish the effect of processing conditions on large size square deep drawn cups. To accomplish this study, FE-simulations (Abaqus) were performed to determine optimum blank size, friction coefficient, the gap between punch and die, etc. The simulated processing parameters were verified experimentally. Based on the FE-simulation results, deep drawing was performed with various blank holding loads and sample sizes. In order to improve the formability of Ti-6Al-4V sheet, various lubricant methods were evaluated. Tensile tests and thickness measurements were conducted on the formed sheets. Processing parameters including blank holding force, lubricants, and optimum blank size, were selected to achieve improved drawing quality. With the optimum processing condition, a $200mm{\times}200mm$ cup was deep drawn successfully.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.4
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• pp.561-567
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• 2021

The edible sargasso seaweed hijiki Sargassum fusiforme is known to have high concentration of arsenic, which is a threat to human health, particularly due to inorganic arsenic. In this study, various methods were used to remove inorganic arsenic from steamed hijiki concentrate. The highest concentration of arsenate [As(V)] in both raw and processed hijiki during steamed hijiki manufacturing process was within the range of 8.213-14.356 mg/kg, and it is a potential source of inorganic arsenic, which can result in re-contamination and cause environmental pollution. The removal efficiencies of the various removal methods were within the range of 57.3-83.4%, and 19.0% reduction was achieved using activated carbon and alginate bead. Further, activated carbon showed the best adsorption effect of inorganic arsenic. Therefore, we suggest that activated carbon is a suitable efficient method for removing inorganic arsenic and has low operational costs in field applicability.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.67-74
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• 2002

A study on image searching and management techniques is actively developed by user requirements for multimedia information that are existing as images, audios, texts data from various information processing devices. If we can automatically detect and segment changing scenes from real-time image sequences, we can improve an effectiveness of image searching systems. In this paper, we propose cut detection techniques based on image color distribution and we evaluated its performance on various real-time image sequences. Results of experiments show that the proposed method are robust on various image patterns than color histogram method using statistical informations of images. Also, these methods can be used for cut detection on real-time image sequences.

• Journal of Practical Agriculture & Fisheries Research
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• v.3 no.1
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• pp.102-115
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• 2001

Through out the last few decades, processing methods for ingredients of feed grains, such as grinding, flaking, extrusion, soaking, cracking etc., have been adopted in order to improve the nutrient digestibility in ruminants. Among feed grains, processing methods for whole corns have been the most frequently studied since corns are utilized as the thumb ingredients in formulating feeds. In these days, flaking of whole corns is the most incessantly used in formulation feeds, resulting in enhancing the performance of ruminants. Recently formulating non-forage feed for beef cattle, especially Holsteins, without processing whole corns is carrying out through various feed companies with expectations of whole corns acting like forages. However, it can not be ruled out that whole corns might possibly result in decreasing the productivity due to the depression of nutrient utilizations. Therefore, one must reevaluate the non-forage feeds as well as makes an effort to develop the rational and effective methodology in processing whole corns with the consideration of rumen eco-system.