• 한국정밀공학회지
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• 제12권11호
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• pp.140-147
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• 1995

This paper deals with conversion from the STL file to the Slice to the Slice cross-sectional information for Stereolithography. The STL file is widely used for Stereolithography, but it is very difficult to convert STL file into Slice file directly. Because it consists of an ordered list of triangular net without any topological information other than the orientation of each facet. So, The system is accomplished by data flow through several intermediate stages such as Reference. SL1. .SL2L. .SL3. and .SLC file. The data processing is performed in 5 steps: 1) Create a Reference file including common information. 2) Modify STL file within the effective range of SL machine. 3) Calculate a point of intersection between plane equation and line equation. 4) Sort z values in ascending order using quick sort algorithm. 5) Search the adjacent points and formulate a closed loop usingsingly linked linear list. The system is developed by using Borland C++ 3.1 compiler in the environment of Pentium PC, and verified to be satisfactory by making some prototypes of electric household appliances.

• 한국언어정보학회지:언어와정보
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• 제2권1호
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• pp.1-41
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• 1998

Evaluation of multilingual translation fundamentally involves measurement of meaning equivalences between the formally mapped discourses/texts of SL(source language) and TL(target language) both represented by a metalanguage called IL(interlingua). Unlike a usaal uni-directional MT(machine translation) model(e.g.:SL $\rightarrow$ analysis $\rightarrow$ transfer $\rightarrow$ generation $\rightarrow$ TL), a bi-directional(by 'negotiation') model(i.e.: SL $\rightarrow$ IL/S $\leftrightarrow$ IL $\leftrightarrow$ IL/T \leftarrow TL) is proposed here for the purpose of evaluating multilingual, not merely bilingual, translation. The IL, as conceived of in this study, is an English-based predicate logic represented in the framework of MRS(minimal recursion semantics), an MT-oriented off-shoot of HPSG(Head-driven Phrase Structure Grammar). In addition, a list of semantic and pragmatic checkpoints are set up, some being optional depending on the kind and use of the translation, so sa to have the evaluation of translation fine-grained by computing matching or mismatching of such checkpoints.

• ETRI Journal
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• 제44권5호
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권4호
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• pp.436-442
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• 2016

An electroencephalogram (EEG)-connectome processor to monitor and diagnose mental health is proposed. From 19-channel EEG signals, the proposed processor determines whether the mental state is healthy or unhealthy by extracting significant features from EEG signals and classifying them. Connectome approach is adopted for the best diagnosis accuracy, and synchronization likelihood (SL) is chosen as the connectome feature. Before computing SL, reconstruction optimizer (ReOpt) block compensates some parameters, resulting in improved accuracy. During SL calculation, a sparse matrix inscription (SMI) scheme is proposed to reduce the memory size to 1/24. From the calculated SL information, a small world feature extractor (SWFE) reduces the memory size to 1/29. Finally, using SLs or small word features, radial basis function (RBF) kernel-based support vector machine (SVM) diagnoses user's mental health condition. For RBF kernels, look-up-tables (LUTs) are used to replace the floating-point operations, decreasing the required operation by 54%. Consequently, The EEG-connectome processor improves the diagnosis accuracy from 89% to 95% in Alzheimer's disease case. The proposed processor occupies $3.8mm^2$ and consumes 1.71 mW with $0.18{\mu}m$ CMOS technology.

• 농약과학회지
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• 제7권4호
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• pp.280-287
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• 2003

주요 토양 처리용 농약 (10종 원제)의 지렁이에 대한 급성독성시험을 실시하여 노출을 고려한 위해성을 평가한 결과 paraquat dichloride와 pendimethalin은 지렁이에 대한 위해성이 무시할 수 있는 수준으로, benfuracarb, cadusafos, chlorpyrifos-methyl, endosulfan, isazofos, parathion 등 6종은 위해성이 낮은 것으로 그리고 imidacloprid와 phorate는 위해성이 높은 것으로 평가하고 번식독성시험이 필요한 것으로 판단되었다. 토양중 추정농도가 높은 22종 제품농약의 경우 인공토양을 이용한 독성시험 결과 dazomet 98% GR과 metam-sodium 25 % SL은 기준량 및 배량처리구에서 모두 치사하여 지렁이에 대한 영향이 높은 것으로, calcite 95% WP, calcium polysulfide 36% CF, chlorothalonil 75% WP, daminozide 85% WP, dichlonil 6.7% GR, etridiazole 25% EC, fosetyl-Al 80% WP, glyphosate 41% SL, hymexazo1 30% SL, iprodione 50% WP, machine oil 95% EC, mancozeb 75% WP, metam-sodium 25% SL, propineb 70% WP, terbuthylazine 80% WP, triazophos 40% EC는 지렁이에 대한 영향이 없는 것으로 나타났으나, thiophanate-methyl 70% WP, copper hydroxide 77% WP, dimethoate 46% EC, tolclofos-methyl 50% WP 및 propamocarb hydrochloride 67% SL 등 5 농약은 영향여부가 불분명하여 아만성독성시험을 수행한 결과 thiophanate-methy1 70% WP는 기준량 이상 처리시 지렁이에 치사 등 영향을 나타냈으나, copper hydroxide 77% WP, dimethoate 46% EC, tolclofos-methyl 50% WP 및 propamocarb hydrochloride 67% SL는 지렁이에 대한 영향이 낮은 것으로 조사되었다.

• 한국정밀공학회지
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• 제27권3호
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• pp.135-141
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• 2010

Researchers continue to explore possibilities for expanding additive manufacturing (AM) technologies into direct product manufacturing. One limitation is in the materials available for use in AM that can meet the needs of end-use applications. Stereolithography (SL) is an AM technology well known for its precision and high quality surface finish capabilities. SL builds parts by selectively crosslinking or solidifying photo-curable liquid resins, and the resin industry has been continuously developing new resins with improved performance characteristics. This paper introduces a unique SL machine that can fabricate parts out of multiple SL materials. The technology is based on using multiple vats positioned on a rotating vat carousel that contain different photo-curable materials. To change the material during the process, the build platform is raised out of the current vat, a new vat with a different material is rotated under the platform, and the platform is submerged into the new vat so that the new material can be used. This paper introduces a new vat exchange mechanism, cleaning process, recoating process, resin leveling mechanism and process planning technologies for the implementation of multiple material SL. An overview of the system framework is provided and the system integration and control software is described. In addition, several multiple material test parts are designed, fabricated, and described.

• 한국공작기계학회논문집
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• 제14권6호
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• pp.61-67
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• 2005

During stereolithography processes, one of the main sources of dimensional error of prototype is the distortion effect owing to the shrinkage of resin. In this study, the effects of dimension of specimen, such as length, width, and thickness, on the curl distortion is examined. During the SL processes, the variation of curl distortion ewer is measured according to the number of layers, Through this study, it is verified that there is a big difference of the distortion error in both direction and magnitude between before and after the supports are removed. It Is also observed that end profile of the test part and the upper side around the border are also distorted due to the shrinkage of the resin.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.493-497
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• 2002

In the part industry, pipe has required high accuracy in surface roughness and size. Especially, when producing the high frequency welding pipe, cutting process is very important as the finishing process that remove the hot welding bead. The objective of this paper is to investigate the hot machining high frequency welded pipe by simulation and experimental tests. To test the cutting process as hot machining, all cutting environment is reproduced in turning with heating system, and the test is accomplished by comparing with room temperature machining and hot machining in consideration of cutting force, tool wear and cutting temperature.

• Journal of Mechanical Science and Technology
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• 제16권8호
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• pp.1127-1134
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• 2002

The effects of pressure and temperature on the autoignition of propane and n-butane blends were investigated using a rapid compression machine (RCM) , which is widely used to examine the autoignition characteristics. The RCM was designed to be capable of varying the compression ratio between 5 and 20 and minimize the vortex formation on the cylinder wall using a wedge-shaped crevice. The initial temperature and pressure of the compressed gas were varied in range of 720∼900 K and 1.6∼ 1.8 MPa, respectively, by adjusting the ratio of the specific heat of the mixture by altering the ratio of the non-reactive components (N$_2$, Ar) under a constant effective equivalence ratio (ø$\_$f/= 1.0) The gas temperature after the compression stroke could be obtained from the measured time-pressure record. The results showed a two-stage ignition delay and a Negative Temperature Coefficient (NTC) behavior which were the unique characteristic of the alkane series fuels. As the propane concentration in the blend were increased from 20% and 40% propane, the autoignition delay time increased by approximately 41 % and 55% at 750 K. Numerical reduced kinetic modeling was performed using the Shell model, which introduced some important chemical ideas, represented by the generic species. Several rate coefficients were calibrated based on the experimental results to establish an autoignition model of the propane and n-butane blends. These coefficients can be used to predict the autoignition characteristics in LPG fueled Sl engines.

• 한국항해항만학회지
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• 제47권6호
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• pp.358-366
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• 2023

본 연구는 해양수산부의 '지능형 해상교통정보시스템' 서비스 중 '사고취약선박 모니터링 서비스'의 선박 충돌 경보를 개선하기 위한 것으로, 현재의 선박 충돌 경보는 대형 선박 위주의 데이터와 그 운항자에 기반한 설문조사 레이블을 가지고 지도 학습(SL)한 모델을 사용하고 있다. 이로 인해, 소형선박 데이터 및 운항자의 의견이 현재 충돌 지도학습 모델에 반영되지 않아, 소형선박 운항자가 느끼는 체감보다 먼 거리에서 경보가 제공되기 때문에 그 효과가 미비하다. 또한, 지도학습(SL) 방법은 레이블링 된 다수의 데이터가 필요하지만, 레이블링 과정에서 많은 자원과 시간이 필요하다. 본 논문은 이러한 한계를 극복하기 위해 준지도학습(SSL)의 알고리즘인 Label Propagation과 TabNet을 사용하여 레이블이 결정되지 않은 데이터를 활용하여 소형선박을 위한 충돌 경보의 분류 모델을 연구하였다. 충돌 경보의 분류 모델을 활용하여 소형선박 운항자를 대상으로 실해역 시험을 수행한 결과 운항자의 만족도가 증가하는 결과를 확인하였다.