• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1142-1149
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• 2004

Motion Estimation(ME) has been developed to reduce temporal redundancy in digital video signals and increase data compression ratio. ME is an Important part of video encoding systems, since it can significantly affect the output quality of encoded sequences. However, ME requires high computational complexity, it is difficult to apply to real time video transmission. for this reason, motion estimation algorithms with low computational complexity are viable solutions. In this paper, we present an efficient method with low computational complexity based on spatial and temporal correlations of motion vectors. The proposed method uses temporally and spatially correlated motion information, the motion vector of the block with the same coordinate in the reference frame and the motion vectors of neighboring blocks around the current block in the current frame, to decide the search pattern and the location of search starting point adaptively. Experiments show that the image quality improvement of the proposed method over MVFAST (Motion Vector Field Adaptive Search Technique) and PMVFAST (Predictive Motion Vector Field Adaptive Search Technique) is 0.01～0.3(dB) better and the speedup improvement is about 1.12～l.33 times faster which resulted from lower computational complexity.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1056-1064
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• 2007

Biomolecular computing is a new computing paradigm that uses biomolecules such as DNA for information representation and processing. The huge number of molecules in a small volume and the innate massive parallelism inspired a novel computation method, and various computation models and molecular algorithms were developed for problem solving. In the meantime, the use of biomolecules for information processing supports the possibility of DNA computing as an application for biological problems. It has the potential as an analysis tool for biochemical information such as gene expression patterns. In this context, a DNA computing-based model of a biomolecular perceptron has been proposed and the result of its experimental implementation was presented previously. The weight encoding and weighted sum operation, which are the main components of a biomolecular perceptron, are based on the competitive hybridization reactions between the input molecules and weight-encoding probe molecules. However, thermodynamic symmetry in the competitive hybridizations is assumed, so there can be some error in the weight representation depending on the probe species in use. Here we suggest a generalized model of hybridization reactions considering the asymmetric thermodynamics in competitive hybridizations and present a weight encoding method for the reliable implementation of a biomolecular perceptron based on this model. We compare the accuracy of our weight encoding method with that of the previous one via computer simulations and present the condition of probe composition to satisfy the error limit.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.572-587
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• 2008

The Self-organizing Feature Map(SOFM) that is one of unsupervised neural networks is a very powerful tool for data clustering and visualization in high-dimensional data sets. Although the SOFM has been applied in many engineering problems, it needs to cluster similar weights into one class on the trained SOFM as a post-processing, which is manually performed in many cases. The traditional clustering algorithms, such as t-means, on the trained SOFM however do not yield satisfactory results, especially when clusters have arbitrary shapes. This paper proposes automatic clustering on trained SOFM, which can deal with arbitrary cluster shapes and be globally optimized by graph cuts. When using the graph cuts, the graph must have two additional vertices, called terminals, and weights between the terminals and vertices of the graph are generally set based on data manually obtained by users. The Proposed method automatically sets the weights based on mode-seeking on a distance matrix. Experimental results demonstrated the effectiveness of the proposed method in texture segmentation. In the experimental results, the proposed method improved precision rates compared with previous traditional clustering algorithm, as the method can deal with arbitrary cluster shapes based on the graph-theoretic clustering.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.625-635
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• 2008

Portable multimedia players have some different properties compared to general multimedia file server. Some of those properties are single user ownership, relatively low hardware performance, I/O burst by user special functions, and short software development cycles. Though suitable for processing multiple user requests at a time, the general multimedia file systems are not efficient for special user functions such as fast forwards/backwards. Soml' methods has been proposed to improve the performance and functionality, which the application programs give prediction hints to the file system. Unfortunately, they require the modification of all applications and recompilation. In this paper, we present a file system that efficiently supports user special functions in embedded multimedia systems using file block allocation, buffer-cache, and prefetch. A prefetch algorithm, SPRA (SPeed-based PRefetch Algorithm) predicts the next block using I/O patterns instead of hints from applications and it is resident in the file system, so doesn't affect application development process. From the experimental file system implementation and comparison with Linux readahead-based algorithms, the proposed system shows $4.29%{\sim}52.63%$ turnaround time and 1.01 to 3,09 times throughput in average.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.1-8
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• 2018

This paper describes new communication methods for transmitting torque commands between the vehicle controller that determines the amount of power generation in a range-extended electric vehicle and the engine controller that performs it. Generally, vehicles use CAN communication, but in this case, the hardware and software of the existing engine controller must be modified. For this reason, it is not easy to apply CAN communication to small and medium sized automotive reorganize companies. Therefore, this research presents a pin-pin communication method for applying the existing mass produced engine controller to range-extended electric vehicles. The pin-pin communication method converts the driver's demand torque control map inside an mass produced engine controller into a virtual accelerator opening position according to the target speed and target torque of the engine, and converts this to a voltage signal for the existing mass produced engine controller to recognize it. The virtual accelerator opening positions are mounted in the form of a control map in the vehicle controller through the reverse conversion process in an offline environment and are determined by the engine generating power requirements and engine optimal operating point algorithm. These algorithms and signal conversion circuits for engine torque transmission have been mounted on the vehicle controller to conduct the virtual accelerator opening position conversion process according to the engine target torque and to establish the virtual accelerator voltage signal using the signal converter.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.1-9
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• 2016

This paper was studied in two ways with respect to the information received from the video signal separation technique of PPI Scop radar device. The proposed technique consists in generating an image signal through the video signal separation and synthesis, symbol generation, the residual image signal generation process. This technology can greatly improve the operating convenience with improved ease of discrimination, screen readability for the operator in analyzing radar information. The first proposed method was constructed for high-speed FPGA-based information processing systems for high speed operation stability of the system. The second proposed method was implemented intelligent algorithms and a software algorithm function curve associated resources.This was required to meet the constraints on the radar information, analysis system. Existing radar systems have not the frame data analysis unit image. However, this study was designed to image data stored in the frame-by-frame analysis of radar images with express information MPEG4 video. Key research content is to highlight the key observations expresses the target, the object-specific monitoring information to the positive image processing algorithm and the function curve delays. For high-definition video, high-speed to implement data analysis and expressing a variety of information was applied to the ARM Processor Support in Pro ASIC3.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.716-730
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• 2008

In Service-Oriented Architecture (SOA), service providers develop and deploy reusable services on the repositories, and service consumers utilize blackbox form of services through their interfaces. Services are also highly evolvable and often heterogeneous. Due to these characteristics of the service, it is hard to manage the faults if faults occur on the services. Autonomic Computing (AC) is a way of designing systems which can manage themselves without direct human intervention. Applying the key disciplines of AC to service management is appealing since key technical issues for service management can be effectively resolved by AC. In this paper, we present a theoretical model, Symptom-Cause-Actuator (SCA), to enable autonomous service fault management in SOA. We derive SCA model from our rigorous observation on how physicians treat patients. In this paper, we first define a five-phase computing model and meta-model of SCA. And, we define a schema of SCA profile, which contains instances of symptoms, causes, actuators and their dependency values in a machine readable form. Then, we present detailed algorithms for the five phases that are used to manage faults the services. To show the applicability of our approach, we demonstrate the result of our case study for the domain of 'Flight Ticket Management Services'.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.253-260
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• 2009

Many algorithms for computer vision and pattern recognition have recently been implemented on GPU (graphic processing unit) for faster computational times. However, the implementation has two problems. First, the programmer should master the fundamentals of the graphics shading languages that require the prior knowledge on computer graphics. Second, in a job that needs much cooperation between CPU and GPU, which is usual in image processing and pattern recognition contrary to the graphic area, CPU should generate raw feature data for GPU processing as much as possible to effectively utilize GPU performance. This paper proposes more quick and efficient implementation of neural networks on both GPU and multi-core CPU. We use CUDA (compute unified device architecture) that can be easily programmed due to its simple C language-like style instead of GPU to solve the first problem. Moreover, OpenMP (Open Multi-Processing) is used to concurrently process multiple data with single instruction on multi-core CPU, which results in effectively utilizing the memories of GPU. In the experiments, we implemented neural networks-based text extraction system using the proposed architecture, and the computational times showed about 15 times faster than implementation on only GPU without OpenMP.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.137-148
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• 2012

Cloud service users request dedicated virtual computing resource from the cloud service provider to process jobs in independent environment from other users. To optimize this process with automated method, in this paper we proposed a framework for workflow scheduling in the cloud environment, in which the core component is the middleware called broker mediating the interaction between users and cloud service providers. To process jobs in on-demand and virtualized resources from cloud service providers, many papers propose scheduling algorithms that allocate jobs to virtual machines which are dedicated to one machine one job. With this method, the isolation of being processed jobs is guaranteed, but we can't use each resource to its fullest computing capacity with high efficiency in resource utilization. This paper therefore proposed a cost-efficient job scheduling algorithm which maximizes the utilization of managed resources with increasing the degree of multiprogramming to reduce the number of needed virtual machines; consequently we can save the cost for processing requests. We also consider the performance degradation in proposed scheme with thrashing and context switching. By evaluating the experimental results, we have shown that the proposed scheme has better cost-performance feature compared to an existing scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.9-21
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• 2004

In this paper, we proposed the image hiding method which decreases calculation amount by encrypt partial data using discrete wavelet transform and linear scale quantization which were adopted as the main technique for frequency transform in JPEG2000 standard. Also we used the chaotic system which has smaller calculation amount than other encryption algorithms and then dramatically decreased calculation amount. This method operates encryption process between quantization and entropy coding for preserving compression ratio of images and uses the subband selection method and the random changing method using the chaotic system. For ciphering the quantization index we use a novel image encryption algerian of cyclically shifted in the right or left direction and encrypts two quantization assignment method (Top-down/Reflection code), made change of data less. Also, suggested encryption method to JPEG2000 progressive transmission. The experiments have been performed with the proposed methods implemented in software for about 500 images. consequently, we are sure that the proposed are efficient image encryption methods to acquire the high encryption effect with small amount of encryption. It has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas. Also, because the proposed methods are performed in the application layer, they are expected to be a good solution for the end-to-end security problem, which is appearing as one of the important problems in the networks with both wired and wireless sections.