• Proceedings of the Korean Powder Metallurgy Institute Conference
• /
• 2006.09a
• /
• pp.323-324
• /
• 2006

The nanostructure control of $Si_3N_4$ ceramics can be achieved by using fine starting powder and retardation of grain growth. The spark plasma sintering technique is useful to retard the grain growth by rapid heating. In the present work, the change of microstructure was investigated with emphasis on the particle size of starting powder, the amount of sintering additive and the heating schedule. The rapid heating by spark plasma sintering gave the fine microstructure consisting of equiaxed grains with the same size as starting particles. The spark plasma sintering of $Si_3N_4$ fine powder was effective to control the microstrucutre on nano-meter level.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.6 no.6
• /
• pp.202-209
• /
• 1998

For development of SDI(Spark-ignited Direct Injection) engine, stratified mixture formation with adequate strength at spark plug was required in wide range of engine operating conditions. So, spray structure under high ambient pressure and spray distribution after impingement on piston bowl in motoring engine was visualized by using laser equipments. Also, incylinder bulk flow structure was measured by using PIV (Paiticle Image Velocimetry) system. Counter-rotating tumble port and bowl piston was found effective to conserve bulk motion directed to spark plug in compression stroke. In addition, mask attached near valve seat in intake port was proposed to attenuate conventional tumble component and enhance counter-rotating tumble component.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1265-1267
• /
• 2015

최근 IoT 기술의 등장으로 저전력 소형 컴퓨터인 라즈베리파이 클러스터가 IoT 데이터 처리를 위해 사용되고 있다. IoT 기술이 발전하면서 다양한 데이터가 생성되고 있으며 IoT 환경에서도 빅데이터 처리가 요구되고 있다. 빅데이터 처리 프레임워크에는 일반적으로 하둡이 사용되고 있으며 이를 대체하는 솔루션으로 Apache Spark가 등장했다. 본 논문에서는 PC와 라즈베리파이 클러스터에서의 성능을 Apache Spark를 통해 비교하였다. 본 실험을 위해 Yelp 데이터를 사용하며 데이터 로드 시간과 Spark SQL을 이용한 데이터 처리 시간을 통해 성능을 비교하였다.

• Journal of the Korean Society of Mechanical Technology
• /
• v.13 no.4
• /
• pp.101-108
• /
• 2011

On cold start operation of an SI engine, a catalyst shows poor performance before it reaches activation temperature. Therefore, fast warmup of the catalyst is very crucial to reduce harmful emissions. In this study, an appropriate control strategy is investigated to increase exhaust gas temperature through changes of spark timing. Combustion stability is also considered at the same time. Exhaust gas temperature and pressure of combustion chamber are measured to investigate the effects of spark timings on cold start and idle performance. Experiments showed that retarded spark timing promotes the combustion at the end of expansion stroke and increases exhaust gas temperature during cold start.

• Journal of information and communication convergence engineering
• /
• v.19 no.3
• /
• pp.155-160
• /
• 2021

Differential evolution is an efficient algorithm for solving continuous optimization problems. However, its performance deteriorates rapidly, and the runtime increases exponentially when differential evolution is applied for solving large-scale optimization problems. Hence, a novel cooperative coevolution differential evolution based on Spark (known as SparkDECC) is proposed. The divide-and-conquer strategy is used in SparkDECC. First, the large-scale problem is decomposed into several low-dimensional subproblems using the random grouping strategy. Subsequently, each subproblem can be addressed in a parallel manner by exploiting the parallel computation capability of the resilient distributed datasets model in Spark. Finally, the optimal solution of the entire problem is obtained using the cooperation mechanism. The experimental results on 13 high-benchmark functions show that the new algorithm performs well in terms of speedup and scalability. The effectiveness and applicability of the proposed algorithm are verified.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.543-544
• /
• 2020

최근 급증하는 클라우드 도입 정책에 비해 클라우드 취약점 진단 및 관리 기술은 상대적으로 미비하여 오픈소스로 사용되고 있는 클라우드 기술의 신규 취약점이 발생하고 있다. 본 논문에서는 Apache Spark를 활용한 쿠버네티스 클라우드 취악점 진단 시스템을 제안한다. 제안하는 시스템은 Apache Spark를 활용하여 쿠버네티스 클라우드를 구성할 때 작성되는 Object Spec의 데이터 중 취약점을 유발하는 값을 진단 및 분석, 대응이 가능하도록 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.33-34
• /
• 2023

성장하는 빅 데이터 시장과 빅 데이터 수의 기하급수적인 증가는 기존 컴퓨팅 환경에서 데이터 처리의 어려움을 야기한다. 특히 이미지 데이터 처리 속도는 데이터양이 많을수록 현저하게 느려진다. 이에 본 논문에서는 Apache Spark와 OpenCV를 활용한 분산 클러스터 컴퓨팅 환경의 대용량 이미지 머신러닝 시스템을 제안한다. 제안하는 시스템은 Apache Spark를 통해 분산 클러스터를 구성하며, OpenCV의 이미지 처리 알고리즘과 Spark MLlib의 머신러닝 알고리즘을 활용하여 작업을 수행한다. 제안하는 시스템을 통해 본 논문은 대용량 이미지 데이터 처리 및 머신러닝 작업 속도 향상 방법을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.382-385
• /
• 2023

Spark는 대용량의 데이터를 처리를 위해 분산된 데이터를 네트워크로 모은 다음, 데이터를 분할하는 작업인 Shuffle을 진행한다. 이때 Spark 클러스터의 어느 한 노드의 네트워크 전송 속도가 느릴 경우 병목 현상으로 인한 전체 처리 성능이 저하된다. 이에 본 논문에서는 네트워크 병목 현상을 예방하기 위한 클러스터 구성 방법을 제안한다. 본 논문에서 제안하는 노드 선택 시스템은 iperf 도구를 이용해 노드들의 대역폭을 측정하고 이에 따라 노드 선택 알고리즘을 통해 클러스터를 구성한다. 기존 Spark 클러스터와 본 논문이 제안하는 시스템으로 구성한 클러스터를 비교했을 때, 250MB 로그 파일을 제외하고 750MB 로그 파일부터는 네트워크 전송 속도가 낮은 노드를 가지고 있는 클러스터의 성능이 병목 현상으로 인해 느려졌다. 본 논문의 제안에 따라 노드들의 네트워크 전송 속도를 고려하여 클러스터를 구성하면 네트워크 전송 속도로 발생하는 병목 현상을 예방할 수 있다.

• Asia pacific journal of information systems
• /
• v.28 no.4
• /
• pp.308-319
• /
• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.

• Journal of Environmental Science International
• /
• v.15 no.6
• /
• pp.579-586
• /
• 2006

The purposes of this paper were to monitor the temperature rising courses and spark discharge of the modified granular activated carbon (GAC) by microwave (MW) irradiation and to evaluate absorption of benzene. The GAC coated on $SiO_2$, boron, talc, ferrite was named as the modified GAC. Thermal and spark discharge measurement of virgin GAC and modifed GAC has been carried out using a MW device operating at 2450 MHz under various energy conditions. The results of this paper as follows. First, the modified GAC is more efficient than the virgin GAC in temperature control. Temperature gradient of the modified GAC is more lower than that of virgin GAC. The temperature gradient of GAC was observed in the following order : virgin GAC, Mn-Zn ferrite/GAC, Ni-Zn ferrite,/GAC, $SiO_2/GAC$, Boron/GAC, Talc/GAC. Second, the spark discharge of the modified GAC was diminished, compared with that of virgin GAC. Because of its excellent electrical insulating properties, the coating material prevents the spark discharge. Finally, the benzene adsorption capacity of the modified GAC decreased due to diminishing of adsorption site by the coating material. Considering the temperature gradient and spark discharge of GAC, the GAC coated $SiO_2$ would be appropriate absorbent under irradiation of MW.