• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.765-774
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• 2013

In this paper, we present a cooperative compressed spectrum sensing scheme for correlated signals in decentralized wideband cognitive radio networks. Compressed sensing is a signal processing technique that can recover signals which are sampled below the Nyquist rate with high probability, and can solve the necessity of high-speed analog-to-digital converter problem for wideband spectrum sensing. In compressed sensing, one of the main issues is to design recovery algorithms which accurately recover original signals from compressed signals. In this paper, in order to achieve high recovery performance, we consider the multiple measurement vector model which has a sequence of compressed signals, and propose a cooperative sparse Bayesian recovery algorithm which models the temporal correlation of the input signals.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3
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• pp.191-199
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• 2010

Physical modeling is a synthesis method of high quality sound which is similar to real sound for musical instruments. However, since physical modeling requires a lot of parameters to synthesize sound of a musical instrument, it prevents real-time processing for the musical instrument which supports a large number of sounds simultaneously. To solve this problem, this paper proposes a single instruction multiple data (SIMD) parallel processor that supports real-time processing of sound synthesis of guitar, a representative plucked string musical instrument. To control six strings of guitar, we used a SIMD parallel processor which consists of six processing elements (PEs). Each PE supports modeling of the corresponding string. The proposed SIMD processor can generate synthesized sounds of six strings simultaneously when a parallel synthesis algorithm receives excitation signals and parameters of each string as an input. Experimental results using a sampling rate 44.1 kHz and 16 bits quantization indicate that synthesis sounds using the proposed parallel processor were very similar to original sound. In addition, the proposed parallel processor outperforms commercial TI's TMS320C6416 in terms of execution time (8.9x better) and energy efficiency (39.8x better).

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.2
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• pp.45-51
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• 2002

Recently the interest for the environment is increasing. So the criterion for the evaluation of the burner has changed. For efficient driving problem, if the thermal efficiency is higher and the oxygen in exhaust gas is lower, then burner is evaluated better. For environmental problem. burner must satisfy NOx limit, soot limit and CO limit. Generally the experienced operator judge of the combustion status of the burner by the color of flame. we don't still have any satisfactory solution against it. the relation of the combustion status and the color of the flame hasn't still been established. This paper is the study about the relation of the combustion status and the color of the flame. This paper describes development of real time flame diagnosis technique that evaluate and diagnose combustion state such as consistency of components in exhaust gas, stability of flame in quantitative sense. In this paper, it was proposed on the flame diagnosis technique of burner using image processing algorithm, the parameter extracted from the image of the flame was used as the input variables of the flame diagnostic system. at first, linear regression algorithm and multiple regression algorithm was used to obtain linear multi-nominal expression. Using the constructed inference algorithm, the amount of NOx and CO of the combustion gas was successfully inferred. the combustion control system will be realized sooner or later.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.596-601
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• 2011

In this paper, we propose a fast depth-image-based rendering method to generate a virtual view image in real-time using a graphic processor unit (GPU) for a 3D broadcasting system. Before the transmission, we encode the input 2D+depth video using the H.264 coding standard. At the receiver, we decode the received bitstream and generate a stereo video using a GPU which can compute in parallel. In this paper, we apply a simple and efficient hole filling method to reduce the decoder complexity and reduce hole filling errors. Besides, we design a vertical parallel structure for a forward mapping process to take advantage of the single instruction multiple thread structure of GPU. We also utilize high speed GPU memories to boost the computation speed. As a result, we can generate virtual view images 15 times faster than the case of CPU-based processing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.600-611
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• 1996

Recently, neural network-based speech recognition has been studied to utilize the adaptivity and learnability of neural network models. However, conventional neural network models have difficulty in the co-articulation processing and the boundary detection of similar phonmes of the Korean speech. Also, in case of using one phonotopic map, learning speed may dramatically increase and inaccuracies may be caused because homogeneous learning and recognition method should be applied for heterogenous data. Hence, in this paper, a neural net typewriter has been designed using a hierarchical self-organizing classifier(HSOC), and related algorithms are presented. This HSOC, during its learing stage, distributed phoneme data on hierarchically structured multiple phonotopic maps, using Kohonen's self-organizing feature maps(SOFM). Presented and experimented in this paper were the algorithms for deciding the number of maps, map sizes, the selection of phonemes and their placement per map, an approapriate learning and preprocessing method per map. If maps are divided according to a priorlinguistic knowledge, we would have difficulty in acquiring linguistic knowledge and how to alpply it(e.g., processing extended phonemes). Contrarily, our HSOC has an advantage that multiple phonotopic maps suitable for given input data are self-organizable. The resulting three korean phonotopic maps are optimally labelled and have their own optimal preprocessing schemes, and also confirm to the conventional linguistic knowledge.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.732-741
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• 2001

In the relational database systems the join operation is one of the most time-consuming query operations. Many parallel join algorithms have been developed 개 reduce the execution time Multiple hash join algorithm using allocation tree is one of the most efficient ones. However, it may have some delay on the processing each node of allocation tree, which is occurred in tuple-probing phase by the difference between one page reading time of outer relation and the processing time of already read one. This delay problem was solved by using the concept of synchronization of page execution time with we had proposed In this paper the effects of the performance improvements in each node of the allocation tree are extended to the whole allocation tree and the performance evaluation about that is processed. In addition we propose an efficient algorithm for multiple hash joins in limited number of processor environments according to the relationship between the number of input relations in the allocation tree and the number of processors allocated to the tree. Finally. we analyze the performance by building the analytical cost model and verify the validity of it by various performance comparison with previous method.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.521-526
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• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.277-286
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• 2020

Research on employee commitment to the organization is necessary for human resource management, and the result is applied in practice to improve organizational effectiveness. The aim of the present study is to explore factors affecting organizational commitment at the small and medium-sized enterprises (SMEs) in Vietnam. Besides, the relationship between organizational commitment and job performance is examined as well. The research was conducted on a sample consisting of 67 white-collar workers and 260 blue-collar workers at SMEs. A total of 327 valid complete questionnaires were input into SPSS 20 database for processing to provide evidence. The research model and hypotheses were tested using the technique of the hierarchical multiple regression analysis. The research resultsrevealed that income, reward and welfare, direct manager, working environment, coworker, and promotion opportunity tended to associate positively with organizational commitment. Besides, the finding also showed that, when the employee has a high organizational commitment, it would lead to high job performance. The main findings of this study provided some managerial implications for SMEs, in general, and managers, in particular. It implies that Vietnam's small and medium-sized enterprises should improve these six factors to retain employees as well as enhance their job performance.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.1
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• pp.44-50
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• 2015

This paper presents a high speed synchronous single inductor dual output boost converter using Type-III compensation for power management in smart devices. Maintaining multiple outputs from a single inductor is becoming very important because of inductor the sizes. The uses of high switching frequency, inductor and capacitor sizes are reduced. Owing to synchronous rectification this kind of converter is suitable for SoC. The phase is controlled in time sharing manner for each output. The controller used here is Type-III, which ensures quick settling time and high stability. The outputs are stable within $58{\mu}s$. The simulation results show that the proposed scheme achieves a better overall performance. The input voltage is 1.8V, switching frequency is 5MHz, and the inductor used is 600nH. The output voltages and powers are 2.6V& 3.3V and 147mW &, 230mW respectively.