• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.578-584
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• 2004

The CSVM(Current Support Vector Machine) that is a digital architecture performing all phases of recognition process including kernel computing, learning, and recall of SVM(Support Vector Machine) on a chip is proposed. Concurrent operation by parallel architecture of elements generates high speed and throughput. The classification problems of bio data having high dimension are solved fast and easily using the CSVM. Quadratic programming in original SVM learning algorithm is not suitable for hardware implementation, due to its complexity and large memory consumption. Hardware-friendly SVM learning algorithms, kernel adatron and kernel perceptron, are embedded on a chip. Experiments on fixed-point algorithm having quantization error are performed and their results are compared with floating-point algorithm. CSVM implemented on FPGA chip generates fast and accurate results on high dimensional cancer data.

• Journal of The Korean Astronomical Society
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• v.49 no.4
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• pp.157-162
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• 2016

High resolution reconstruction technology is developed to help enhance the spatial resolution of observational images for ground-based solar telescopes, such as speckle masking. Near real-time reconstruction performance is achieved on a high performance cluster using the Message Passing Interface (MPI). However, much time is spent in reconstructing solar subimages in such a speckle reconstruction. We design and implement a novel parallel method for speckle masking reconstruction of solar subimage on a shared memory machine using the OpenMP. Real tests are performed to verify the correctness of our codes. We present the details of several parallel reconstruction steps. The parallel implementation between various modules shows a great speed increase as compared to single thread serial implementation, and a speedup of about 2.5 is achieved in one subimage reconstruction. The timing result for reconstructing one subimage with 256×256 pixels shows a clear advantage with greater number of threads. This novel parallel method can be valuable in real-time reconstruction of solar images, especially after porting to a high performance cluster.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.901-915
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• 1999

Parallel computers are known to be excellent in performance per cost also satisfying scalability and high performance. However parallel machines have enjoyed limited success because of difficulty in parallel programming and non-portability between parallel machines. Recently, researchers have sought to develop data parallel language that provides machine independent programming systems. Data parallel language such as High Performance Fortran provides a basis to write a parallel program based on a global name space by partitioning data and computation, generating message-passing function. In this paper, we describe the Parallel Programming Translator(PPTran), source-to-source data parallel compiler, generating MPI SPMD parallel program from HPF input program through four phases such as data dependence analysis, partitioning data, partitioning computation, and code generation with explicit message-passing and verify the performance of PPTran

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.219-224
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• 2004

There have been many researches on machine tool vibration and chatter to obtain assessment procedure and more productivity. In this paper chatter limit is predicted on a universal machining center which used a parallel mechanism. The prediction method uses the combination of structural dynamic characteristics and cutting dynamics. So the dynamic characieristics were obtained by vibration experiments. We showed the unstable cutting conditions, and from them we could plot the unstable borderlines.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.88.1-88
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• 2001

The paper describes a new approach to the organization of an artificial brain for mobile multi-robot systems, where individual robots are not considered as independent entities, but rather forming together a universal parallel and distributed machine capable of processing both information and physical matter in distributed worlds. This spatial machine, operating without any central control, is driven on top by distributed mission scenarios in WAVE-WP language. The scenarios can be written on a variety of levels, and any mixture of them, supporting the needed system flexibility and freedom ...

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.580-585
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• 2014

This paper conducts a variety of experiments for "the extraction of Korean parallel sentences using Wikipedia data". We refer to various methods that were previously proposed for other languages. We use two approaches. The first one is to use translation probabilities that are extracted from the existing resources such as Sejong parallel corpus, and the second one is to use dictionaries such as Wiki dictionary consisting of Wikipedia titles and MRDs (machine readable dictionaries). Experimental results show that we obtained a significant improvement in system using Wikipedia data in comparison to one using only the existing resources. We finally achieve an outstanding performance, an F1-score of 57.6%. We additionally conduct experiments using a topic model. Although this experiment shows a relatively lower performance, an F1-score of 51.6%, it is expected to be worthy of further studies.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.74-87
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• 2000

PVM (parallel virtual machine) provides a programming environment that allows a collection of networked workstations to appear as a single parallel computational resource. The performance of parallel applications in this environment depends on the performance of data transfers between tasks. In this paper, we present a new Myrinet-based communication model of PVM that improves PVM communication performance over a high-speed Myrinet LAN. The proposed PVM communication model adopts a communication mechanism that allows any user-level process to directly access the network interface board without going through UDP/IP protocol stacks in the kernel. This mechanism provides faster data transfers between PVM tasks over the Myrinet since it avoids data copy overhead from kernel (user space) to user space (kernel) and reduces communication latency due to network protocol software layers. We implemented EPVM (Enhanced PVM), our updated version of the traditional PVM using UDP/IP, that is based on the proposed communication model over the Myrinet. Performance results show EPVM achieves communication speed-up of one to two over the traditional PVM.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.231-234
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• 2003

This paper describes the structure, operation, image processing, and decision making techniques of a color machine vision system designed for the automatic sorting of soybeans. The system consists of feeder, conveyor belt, line-scan camera, lights. ejector, and a PC Unlike manufactured goods, agricultural products including soybeans have quite uneven features. The criteria for sorting good and bad beans also vary depending on inspectors. We tackle these problem by letting the system learn the inspecting parameters from good samples selected manually by a machine user before running the system for sorting. Real-time processing has another importance In the design. Four parallel DSPs are employed to increase the processing speed. When the designed system was tested with real soybeans and the result was successful.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.1
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• pp.63-73
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• 1990

Low cost automatic welding machine is developed for the purpose of welding process automation of automobile parts with two dimensional welding joints. Developed gantry type machine is equipped with X, Y and roll axis stepping motors, and dirive units units are designed by two phase on drive scheme using shift registers. Control system is constructed by single board microcomputer of Z80A CPU, and also it is equipped with parallel input output ports and counter-timer chips. Linear and circular interpolation of welding head movement is accomplished by employing software digital differential analyzers. It has been shown that contour error of develped system is withi ${\pm}1.0mm$, meaning that the machine is suitable for CO2 arc welding process of automoble parts and is expected it's application to industry.