• Journal of KIISE
• /
• v.43 no.9
• /
• pp.963-973
• /
• 2016

Providing a semantic knowledge system using media ontologies requires not only conventional axiom reasoning but also knowledge extension based on various types of reasoning. In particular, spatio-temporal information can be used in a variety of artificial intelligence applications and the importance of spatio-temporal reasoning and expression is continuously increasing. In this paper, we append the LOD data related to the public address system to large-scale media ontologies in order to utilize spatial inference in reasoning. We propose an RDFS/Spatial inference system by utilizing distributed memory-based framework for reasoning about large-scale ontologies annotated with spatial information. In addition, we describe a distributed spatio-temporal SPARQL parallel query processing method designed for large scale ontology data annotated with spatio-temporal information. In order to evaluate the performance of our system, we conducted experiments using LUBM and BSBM data sets for ontology reasoning and query processing benchmark.

• Journal of Satellite, Information and Communications
• /
• v.7 no.2
• /
• pp.8-12
• /
• 2012

Area-based stereo matchng algorithms are widely used for image analysis for stereo vision. SAD (Sum of Absolute Difference) algorithm is one of well known area-based stereo matchng algorithms with the characteristics of data intensive computing application. Therefore, it requires very high computation capabilities and its processing speed becomes very slow with software realization. This paper proposes a fast SAD algorithm utilizing SSE (Streaming SIMD Extensions) instructions based on SIMD (Single Instruction Multiple Data) parallism. CPU supporing SSE instructions has 16 XMM registers with 128 bits. For the performance evaluation of the proposed scheme, we compare the processing speed between SAD with/without SSE instructions. The proposed scheme achieves four times performance improvement over the general SAD, which shows the possibility of the software realization of real time SAD algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.9
• /
• pp.72-80
• /
• 2019

In this task, the tool dynamometer design and manufacture, and the Ansys S/W structural analysis program for tool attachment that satisfies the cutting force measurement requirements of the tool dynamometer system are used to determine the cutting force generated by metal cutting using 3-axis static structural analysis and the LabVIEW system. The cutting power in a cutting process using a milling tool for processing metals provides useful information for understanding the processing, optimization, tool status monitoring, and tool design. Thus, various methods of measuring cutting power have been proposed. The device consists of a strain-gauge-based sensor fitted to a new design force sensing element, which is then placed in a force reduction. The force-sensing element is designed as a symmetrical cross beam with four arms of a rectangular parallel line. Furthermore, data duplication is eliminated by the appropriate setting the strain gauge attachment position and the construction of a suitable Wheatstone full-bridge circuit. This device is intended for use with rotating spindles such as milling tools. Verification and machining tests were performed to determine the static and dynamic characteristics of the tool dynamometer. The verification tests were performed by analyzing the difference between strain data measured by weight and that derived by theoretical calculations. Processing test was performed by attaching a tool dynamometer to the MCT to analyze data generated by the measuring equipment during machining. To maintain high productivity and precision, the system monitors and suppresses process disturbances such as chatter vibration, imbalances, overload, collision, forced vibration due to tool failure, and excessive tool wear; additionally, a tool dynamometer with a high signal-to-noise ratio is provided.

• The KIPS Transactions:PartD
• /
• v.8D no.5
• /
• pp.593-604
• /
• 2001

A database sharing system (DSS) refers to a system for high performance transaction processing. In the DSS, the processing nodes are coupled via a high speed network and share a common database at the disk level. Each node has a local memory and a separate copy of operating system. To reduce the number of disk accesses, the node caches data pages and index pages in its memory buffer. In general, B-tree index pages are accessed more often and thus cached at more processing nodes, than their corresponding data pages. There are also complicated operations in the B-tree such as Fetch, Fetch Next, Insertion and Deletion. Therefore, an efficient cache consistency scheme supporting high level concurrency is required. In this paper, we propose cache consistency schemes using identifiers of index pages and page_LSN of leaf page. The propose schemes can improve the system throughput by reducing the required message traffic between nodes and index re-traversal.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.2
• /
• pp.318-328
• /
• 2014

In this paper, as a way of performance improvement of business card recognition in the mobile environment, we suggested a hybrid OCR agent which combines data using a parallel processing sequence between various algorithms and different kinds of business card recognition engines which have learning data. We also suggested an Image Processing Method on mobile cameras which adapts to the changes of the lighting, exposing axis and the backgrounds of the cards which occur depending on the photographic conditions. In case a hybrid OCR agent is composed by the method suggested above, the average recognition rate of Korean business cards has improved from 90.69% to 95.5% compared to the cases where a single engine is used. By using the Image Processing Method, the image capacity has decreased to the average of 50%, and the recognition has improved from 83% to 92.48% showing 9.4% improvement.

• Journal of Digital Contents Society
• /
• v.19 no.4
• /
• pp.771-777
• /
• 2018

This study proposes a big data based risk analysis framework to analyze more comprehensive disaster risk and vulnerability. We introduce a distributed and parallel framework that allows large volumes of data to be processed in a short time by using open-source disaster risk assessment tool. A performance analysis of the proposed system presents that it achieves a more faster processing time than that of the existing system and it will be possible to respond promptly to precise prediction and contribute to providing guideline to disaster countermeasures. Proposed system is able to support accurate risk prediction and mitigate severe damage, therefore will be crucial to giving decision makers or experts to prepare for emergency or disaster situation, and minimizing large scale damage to a region.

• Journal of Korea Game Society
• /
• v.12 no.5
• /
• pp.67-78
• /
• 2012

Summed area table allows filtering of arbitrary-width box regions for every pixel in constant time per pixel. This characteristic makes it beneficial in image processing applications where the sum or average of the surrounding pixel intensity is required. Although calculating the summed area table of an image data is primarily a memory bound job consisting of row or column-wise summation, previous works had to endure excessive access to the high latency global memory in order to exploit data parallelism. In this paper, we propose an efficient algorithm for generating the summed area table in the GPGPU environment where the input is decomposed into square sub-images with intermediate data that are propagated between them. By doing so, the global memory access is almost halved compared to the previous methods making an efficient use of the available memory bandwidth. The results show a substantial increase in performance.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.2
• /
• pp.15-23
• /
• 2009

This paper presents a novel high-speed, low-complexity flexible 128/64-point $radix-2^4$ FFT/IFFT processor for the applications in high-throughput MIMO-OFDM systems. The high radix multi-path delay feed-back (MDF) FFT architecture provides a higher throughput rate and low hardware complexity by using a four-parallel data-path scheme. The proposed processor not only supports the operation of FFT/IFFT in 128-point and 64-point but can also provide a high data processing rate by using a four-parallel data-path scheme. Furthermore, the proposed design has a less hardware complexity compared with traditional 128/64-point FFT/IFFT processors. Our proposed processor has a high throughput rate of up to 560Msample/s at 140MHz while requiring much smaller hardware expenditure satisfying IEEE 802.11n standard requirements.

• Geophysics and Geophysical Exploration
• /
• v.5 no.3
• /
• pp.185-192
• /
• 2002

We made a study of 3-D migration which could precisely image data of GPR (Ground Penetrating Radar) applied to NDT (Non-Destructive Test) field for the inspection of structural safety. In this study, we obtained 3-D migrated images of important targets in structuresurvey (e.g. steel pipes, cracks) by using 3-D Kirchhoff prestack depth migration scheme developed for seismic data processing. For a concrete model consisting of steel pipe and void, the targets have been well defined with opposite amplitude according to the parameters of the targets. And migrated images using Parallel-Broadside array (XX configuration) have shown higher resolution than those using Perpendicular-Broadside array (YY configuration) when steel pipes had different sizes. Therefore, it is required to analyze the migrated image of XX configuration as well as that of general YY configuration in order to get more accurate information. As the last stage, we chose a model including two steel pipes which cross each other. The upper pipe has been resolved clearly but the lower has been imaged bigger than the model size due to the high conductivity of the upper steel.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.6
• /
• pp.1127-1137
• /
• 2022

Cryptographic analysis and decryption technology utilizing the parallel operation of GPU has been studied in the direction of shortening the computation time of the password analysis system. These studies focus on optimizing the code to improve the speed of cryptographic analysis operations on a single GPU or simply increasing the number of GPUs to enhance parallel operations. However, using a large number of GPUs without optimization for data transmission causes longer data transmission latency than using a single GPU and increases the overall computation time of the cryptographic analysis system. In this paper, we investigate GPUDirect RDMA and related technologies for high-performance data processing in deep learning or HPC research fields in GPU clustering environments. In addition, we present a method of designing a high-performance cryptanalysis system using the relevant technologies. Furthermore, based on the suggested system topology, we present a method of implementing a cryptanalysis system using password cracking and GPU reduction. Finally, the performance evaluation results are presented according to demonstration of high-performance technology is applied to the implemented cryptanalysis system, and the expected effects of the proposed system design are shown.