• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.133-139
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• 2017

Vehicles have increasingly evolved and become intelligent with convergence of information and communications technologies (ICT). Vehicle communications (VC) has become one of the major necessities for intelligent vehicles. However, VC suffers from serious security problems that hinder its commercialization. Hence, the IEEE 1609 Wireless Access Vehicular Environment (WAVE) protocol defines a security service for VC. This service includes Advanced Encryption Standard-Counter with CBC-MAC (AES-CCM) for data encryption in VC. A high-speed AES-CCM crypto module is necessary, because VC requires a fast communication rate between vehicles. In this study, we propose and implement an efficient AES-CCM hardware architecture for high-speed VC. First, we propose a 32-bit substitution table (S_Box) to reduce the AES module latency. Second, we employ key box register files to save key expansion results. Third, we save the input and processed data to internal register files for secure encryption and to secure data from external attacks. Finally, we design a parallel architecture for both cipher block chaining message authentication code (CBC-MAC) and the counter module in AES-CCM to improve performance. For implementation of the field programmable gate array (FPGA) hardware, we use a Xilinx Virtex-5 FPGA chip. The entire operation of the AES-CCM module is validated by timing simulations in Xilinx ISE at a speed of 166.2 MHz.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.23-28
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• 2005

An airborne radar is an essential aviation electronic system of the helicopter to perform various missions in all-weather environments. This paper presents the results of the design and implementation of the airborne pulse doppler radar signal processor using high multi-DSP for the multi-function radar capability such as short-range, midium-range, and long-range depending on the mission of the vehicle. Particularly, the radar signal processor is developed using two DSP boards in parallel for the various radar signal processing algorithm. The key algorithms include LFM chirp waveform-based pulse compression, MTI clutter filter, MTD processor, adaptive CFAR, and clutter map. Especially airborne moving clutter Doppler spectrum compensation algorithm such as TACCAR is implemented for the multi-mode airborne radar system. The test results shows the good Doppler spectral separation for the clutter and the moving target in the flight test environment using helicopter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.31-42
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• 2020

During the 4th Industrial Revolution, service platforms utilizing diverse contents are emerging, and research on recommended systems that can be customized to users to provide quality service is being conducted. hybrid recommendation systems that provide high accuracy recommendations are being researched in various domains, and various filtering techniques, machine learning, and deep learning are being applied to recommended systems. However, in a recommended service environment where data must be analyzed and processed real time, the accuracy of the recommendation is important, but the computational speed is also very important. Due to high level of model complexity, a hybrid recommendation system or a Deep Learning-based recommendation system takes a long time to calculate. In this paper, a Cascade-hybrid recommended algorithm is proposed that can reduce the computational time while maintaining the accuracy of the recommendation. The proposed algorithm was designed to reduce the complexity of the model and minimize the computational speed while processing sequentially, rather than using existing weights or using a hybrid recommendation technique handled in parallel. Therefore, through the algorithms in this paper, contents can be analyzed and recommended effectively and real time through services such as SNS environments or shared economy platforms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.683-692
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• 1995

Many kinds of large scale multiprocessing and parallel-processing systems have recently been developed. The contention on the shared data caused by multiple processors may degrade system performance. So, processor synchronization has become one of the important issues in these systems. To solve the synchornization issues, a lot of software and hardware schemes based on spin lock have been proposed. Although software schemes are easy to implement, hardware schemes are preferred in many systems to gain optimized performance. This paper proposes an efficient processor synchronization scheme, called QCX,and describes its design considerations, hardware, algorithm, protocol. Also, in this paper, the performance of QCX has been evaluated with QOLB[5] and LBP[7] using a simulation. The simulation, with varying the number of processor and the contention on shared variables, measured the average execution times of a workload. The simulation results show that the performances of QCX is best when practicability is considered. QCX is more efficient than QOLB and LBP in two aspects. First, the hardware of QCX is more simple and cost-effective because the cache structure need not be changed. Secondly, QCX is more general because it uses a generic atomic instruction.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.331-333
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• 2015

Data is increasing explosively with the spread of networks and mobile devices and there are problems in effectively processing the rapidly increasing data using existing recommendation techniques. Therefore, researches are being conducted on how to solve the scalability problem of the collaborative filtering technique. In this paper applies MapReduce, which is a distributed parallel process framework, to the collaborative filtering technique to reduce the scalability problem and heighten accuracy. The proposed technique applies MapReduce and the index technique to a user-based collaborative filtering technique and as a method which improves neighbor numbers which are used in similarity calculations and neighbor suitability, scalability and accuracy improvement effects can be expected.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.1
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• pp.37-44
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• 2010

New features of motion compensation, such as variable block size and multiple reference frames are introduced in H.264/AVC. However, these new features induce significant implementation complexity increases. In this paper, an efficient architecture for spiral-type motion estimation is proposed. First, we propose a hardware-friendly spiral search order. Then, an efficient processing element (PE) architecture for ME is proposed to achieve the proposed search order. The improved PE enables one-pixel-move of the reference pixel data to top, bottom, right, and left by four ports for input and output. Moreover, the parallel calculation architecture to calculate all block size with the SAD of 4x4 is introduced in the proposed architecture. As the result of hardware implementation, the hardware cost is about 145k gates. Maximum clock frequency is 134 MHz in the case of FPGA (Xilinx Vertex5) implementation.

• Smart Structures and Systems
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• v.34 no.2
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• pp.117-127
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• 2024

A novel approach that the smart control of robotics can be realized by a fuzzy controller and an appropriate Runge-Kutta scheme in this paper. A recently proposed integral inequality is selected based on the free weight matrix, and the less conservative stability criterion is given in the form of linear matrix inequalities (LMIs). We demonstrate that this target information obtained through image processing is subjected to smart control with computer-vision robotic to Arduino, and the infrared beacon was utilized for the operation of practical illustrations. A fuzzy controller derived with a fuzzy Runge-Kutta type functions is injected into the system and then the system is stabilized asymptotically. In this study, a fuzzy controller and a fuzzy observer are proposed via the parallel distributed compensation technique to stabilize the system. This paper achieves the goal of real-time following of three vehicles and there are many areas where improvements were made. Finally, each information is transmitted to Arduino via I2C to follow the self-propelled vehicle. The proposed calculation is approved in reproductions and ongoing smart control tests.