본 연구는 기존 문헌에서 제공된 곤충의 평균발육일과 그 표준편차 정보를 기반으로 피어슨의 비대칭 계수를 활용하여 발육완료시기분포의 방향성을 추정하였다. 우선 곤충의 온도의존적 발육특성을 통계적 방법으로 방향성을 추정하고, 곤충의 발육완료시기(일단위)를 평균값에 가까운 정수값을 최빈값으로 가정한 후, 왜곡의 크기를 추정한다. 본 제안에서는 적률생성함수(mgf: moment generate function)를 활용하여 평균과 표준편차를 기반으로 추정하여 3차적률함수인 왜도(skewness)를 추정하였다. 다음 단계로 대표값을 활용하여 분포의 방향성을 정하였으며, 3차적률을 통해 왜도의 크기를 구하고 이를 활용하여 왜곡분포를 추정하였다. 위의 알고리즘을 이용하여 추정한 곤충의 발육완료시기와 실제 곤충발육실험 데이터를 비교한 결과, 본 연구에서 제안한 알고리즘은 매우 높은 확률로 실제 곤충발육실험 데이터의 분포를 추정할 수 있었다.

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

This study focuses on a job-shop scheduling problem with the objective of minimizing total tardiness for the job orders that have different due dates and different process flows. We suggest the dispatching rule based scheduling algorithm to generate fast and efficient schedule. First, we show the delay schedule can be optimal for total tardiness measure in some cases. Based on this observation, we expand search space for selecting the job operation to explore the delay schedules. That means, not only all job operations waiting for process but also job operations not arrived at the machine yet are considered to be scheduled when a machine is available and it is need decision for the next operation to be processed. Assuming each job operation is assigned to the available machine, the expected total tardiness is estimated, and the job operation with the minimum expected total tardiness is selected to be processed in the machine. If this job is being processed in the other machine, then machine should wait until the job arrives at the machine. Simulation experiments are carried out to test the suggested algorithm and compare with the results of other well-known dispatching rules such as EDD, ATC and COVERT, etc. Results show that the proposed algorithm, MET, works better in terms of total tardiness of orders than existing rules without increasing the number of tardy jobs.

The incidence of stomach cancer has been found to be gradually decreasing; however, it remains one of the most frequently occurring malignant cancers in Korea. According to statistics of 2017, stomach cancer is the top cancer in men and the fourth most important cancer in women, necessitating methods for its early detection and treatment. Considerable research in the field of bioinformatics has been conducted in cancer studies, and bioinformatics approaches might help develop methods and models for its early prediction. We aimed to develop a classification method based on deep learning and demonstrate its application to gene expression data obtained from patients with stomach cancer. Data of 60,483 genes from 334 patients with stomach cancer in The Cancer Genome Atlas were evaluated by principal component analysis, heatmaps, and the convolutional neural network (CNN) algorithm. We combined the RNA-seq gene expression data with clinical data, searched candidate genes, and analyzed them using the CNN deep learning algorithm. We performed learning using the sample type and vital status of patients with stomach cancer and verified the results. We obtained an accuracy of 95.96% for sample type and 50.51% for vital status. Despite overfitting owing to the limited number of patients, relatively accurate results for sample type were obtained. This approach can be used to predict the prognosis of stomach cancer, which has many types and underlying causes.

2017년 12월 인천의 영흥도에서 발생한 급유선과 낚시어선의 충돌사고를 비롯하여 소형 어선의 충돌 사고가 잇따라 발생하고 있다. 해양수산부에서 이러한 소형 어선의 해양사고를 예방하기 위하여 5톤 미만의 어선원에 대한 교육·훈련 규정 마련 등 교육 강화 및 근로환경 개선 등 선박종사자의 안전역량 제고를 위해 노력하고 있으나, 여전히 소형 선박은 해양사고에 매우 취약한 실정이다. 본 연구에서는 소형선박의 충돌 사고를 예방하기 위하여 새로운 통신 기법인 차량용 무선통신(WAVE 통신)을 활용한 소형 선박을 위한 충돌 예방 알고리즘을 구축하고자 하였다. 충돌 예방 알고리즘은 DCPA/TCPA를 기반으로 구성되었으며, DCPA/TCPA의 기준 설정을 위하여 선행 연구 분석, 시뮬레이션 실험 및 설문조사를 실시하였다. 그 결과 DCPA ８(La + Lb), TCPA 2.5min의 기준을 적용하였다. 각각 다른 조우 상황의 3가지 사고 사례를 선별한 후 구성된 알고리즘을 적용하여 어느 시기에 경보가 발생하는지 확인하였다. 추후에 실선 적용을 통하여 문제점을 식별하고 알고리즘을 고도화한다면 소형 선박의 운항자가 충돌 상황을 사전에 인지하는데 정보를 제공할 수 있다.

본 논문에서는 바람, 파도, 조류 등의 큰 외란조건에서 선박계류시스템의 계류안정성 확보를 위한 동적제어기 설계를 연구하였다. 선박계류시스템의 비선형 동요를 억제하기 위해 슈퍼트위스팅 알고리즘(STA)을 포함한 슬라이딩 모드 제어(SMC) 기법이 적용되었다. 외란이나 파라미터의 불확실성에 대한 강인성의 장점에도 불구하고, 채터링은 슬라이딩 모드 제어기를 적용하는데 주요 단점이 되고 있다. 1차계 SMC는 정확히 제어 목표치에 수렴 하도록 정밀한 제어는 가능하나, 채터링과 같은 파괴적인 현상과 연계되어 적용에 주요한 장애가 된다. 대신에, STA는 큰 외란에도 불구하고 비교적 높은 정확도를 보이며 채터링 현상을 완전히 제거한다. 1차계 슬라이딩 모드 제어기의 채터링 문제를 피할 수 있는 STA기반의 SMC는 비선형 계류시스템의 동적제어를 위한 아주 효과적인 수단으로 판단된다. 아울러, STA로 제어된 선박계류시스템의 위치오차 궤적은 경계 구역 내에서 형성된다. 끝으로, 슬라이딩 표면과 위치궤적의 오차결과를 통해 STA의 이득제어 효과도 관측할 수 있다.

Triangulation is one of the fundamental problems in computational geometry and computer graphics community, and it has huge application areas such as 3D printing, computer-aided engineering, surface reconstruction, surface visualization, and so on. The Delaunay refinement algorithm is a well-known method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. In this paper, we propose a simple but efficient algorithm to triangulate Voronoi surfaces of Voronoi diagram of spheres in 3-dimensional Euclidean space. The proposed algorithm is based on the Ruppert’s Delaunay refinement algorithm, and we modified the algorithm to be applied to the triangulation of Voronoi surfaces in two ways. First, a new method to deciding the location of a newly added vertex on the surface in 3-dimensional space is proposed. Second, a new efficient but effective way of estimating approximation error between Voronoi surface and triangulation. Because the proposed algorithm generates a triangular mesh for Voronoi surfaces with guaranteed quality, users can control the level of quality of the resulting triangulation that their application problems require. We have implemented and tested the proposed algorithm for random non-intersecting spheres, and the experimental result shows the proposed algorithm produces quality triangulations on Voronoi surfaces satisfying the quality criterion.

이 논문에서는 다중 재난을 고려한 복합 구조제어 시스템의 최적 설계방법을 제시한다. 한 가지 유형의 위험에 대해 하나의 시스템이 설계되는 전형적인 구조제어 시스템과는 달리, 구조물의 지진 및 바람에 의한 진동응답을 저감하기 위해 능동 및 수동제어 시스템에 대한 동시 최적 설계방법을 제안하였다. 수치 예로서, 30층 빌딩 구조물에 설치된 30개의 점성 댐퍼와 복합형 질량 감쇠기에 대한 최적 설계문제를 보였다. 최적화 문제를 풀기 위해 자체적응 화음탐색(harmony search, HS)알 고리즘을 채택하였다. 화음탐색 알고리즘은 사람이 연주하는 악기의 튜닝 과정을 모방한 전역 최적화를 위한 메타 휴리스틱 진화 연산방법의 하나이다. 또한 전역 탐색 및 빠른 수렴을 위해 자가적응적이고 동적인 매개변수 조정 알고리즘을 도입하였다. 최적화 설계 결과, 능동 및 수동 시스템이 독립적으로 최적화된 표준적인 복합제어 시스템에 비해 제안한 동시 최적제어 시스템의 성능과 효율성이 우수함을 보였다.

PURPOSES : Thermal cracking (also called low-temperature cracking) is a serious stress for asphalt pavement, especially in eastern South Korea, the northern USA, and Canada. Thermal cracking occurs when the level of thermal stress exceeds the corresponding level of low temperature strength of the given asphalt materials. Therefore, computation of thermal stress is a key factor for understanding, quantifying, and evaluating the level of low-temperature cracking resistance of asphalt pavement. In this paper, two different approaches for computing thermal stress on asphalt binder were introduced: Hopkins and Hamming’s algorithm (1967) and the application of a simple power-law function. All the computed results were compared visually; then the findings and recommendations were discussed. METHODS: Thermal stress of the tested asphalt binder was computed based on the methodology introduced in previous literatures related to viscoelastic theory. To perform the numerical analysis, MATLABTM 2D matrix-correlation and Microsoft Excel visual basic code were developed and used for the function fitting and value-minimization processes, respectively. RESULTS : Different results from thermal stress were observed with application of different computation approaches. This variation of the data trends could be recognized not only visually but also statistically. CONCLUSIONS: It can be concluded that these two different computation approaches can successfully provide upper and lower limits (i.e. boundaries) for thermal stress prediction of a given asphalt binder. Based on these findings, more reliable and reasonable thermal stress results could be provided and finally, better pavement performance predictions could also be expected.

More than 6,000 power tiller accidents occurred in 2015, accounting for 50% of all agricultural machinery accidents. Despite this, educational institutions for farmers are only conducting theoretical education due to lack of training systems with guaranteed safety. This study developed an object motion tracking algorithm enabling trainees to control a power tiller driving simulator while wearing a HMD(head mounted display) in order to provide safe hands-on training equipment. A power tiller driving simulator was built using encoders, proximity sensors and displacement sensors to detect the locations of various operating devices such as steering clutch, and a computer model for this simulator was designed. Center coordinate synchronization of the driving simulator and the computer model was achieved with a tracker, and the motion of the power tiller driving simulator was tracked by computing position coordinates and rotation angles of the simulator. The maximum distance error was 23mm, and there was no difficulty maneuvering the driving simulator while wearing an HMD, even at maximum distance error. This motion tracking algorithm is expected to be applicable to the development of mixed reality based power tiller driving simulators for training, contributing to the reduction of power tiller accidents.

OLED Display fabrication system is one of the most complicated discrete processing systems in the world. As the glass size grows from 550×650mm to 1,500×1,850mm in recent years, the efficiency of Automated Material Handling System (AMHS) has become very important and OLED glass manufacturers are trying to improve the overall efficiency of AMHS. Aiming to meet the demand for high efficiency of transportation, various kind of approaches have been applied for improving dispatching rules and facility layout, while simultaneously considering the system parameters such as glass cassettes due date, waiting time, and stocker buffer status. However, these works did not suggest the operational policy and conditions of distribution systems, especially for handling unnecessary material flows such as detour. Based on this motivation, in this paper, we proposed an efficient algorithm for improving detour transportation in OLED FAB. Specifically, we considered an OLED FAB simplifying OLED production environment in a Korean company, where four stockers are constructed for the delivery of Lot in a bay and linked to processing equipments. We developed a simulation model using Automod and performed a numerical experiment using real operational data to test the performance of three operation policies under considerations. We showed that a competitive policy for assigning alternative stocker in case of detour was superior to the current dedicated policy using a specified stocker and other considered policies.

본 연구에서는 인명구조활동을 지원하기 위한 피난동선예측 알고리즘 개발의 첫 단계로 피난동선예측 알고리즘의 개념을 정립 하고 그 타당성을 수치적으로 명확히 제시하였다. 제안하는 알고리즘은 평상시 선박내 모니터링 시스템으로부터 지속적으로 승객이동 데이터를 취득, 분석, 정형화하고, 재난발생시 이 데이터와 예측 툴을 활용해 도출한 승선자의 피난동선예측 정보를 구조자에게 제공하여 인명피해를 최소화시키는 프로세스로 요약할 수 있다. 피난훈련을 통해 피난특성 데이터를 취득하였고 이를 기존 인명피난예측 툴에 입력하여 피난특성을 예측한 결과, 예측 툴의 구조적 원인으로 인해 가시거리가 충분히 확보되고 피난경로를 충분히 숙지한 상황에서의 피난 시나리오(SN1)에서만 신뢰할 만한 예측결과가 도출되었다. 본 연구에서 제안하는 알고리즘의 타당성을 확인하기 위해 타 분야의 예측툴을 사용하여 피난특성을 예측한 결과, 제안 알고리즘이 구현될 경우 평균피난시간예측값과 피난동선(지점경유)예측값이 각각 0.6 ~ 6.9%, 0.6 ~ 3.6% 범위의 오차에서 실측값과 매우 유사한 경향을 보였다. 향후 선내 모니터링 데이터를 분석하고 이를 활용한 예측성능이 우수한 피난동선예측 알고리즘을 개발할 계획이다.

This study applies optimization-based algorithm to develop combination classification methods. We propose a genetic algorithm-based combination classification method of multiple decision trees to improve predictive accuracy, optimize classification rules, and interpret classification results. The basic algorithm for decision tree has been constructed in a top-down recursive divide-and-conquer manner. Based on different split measures (attribute selection measures), different decision tree algorithms can be produced, and then multiple decision trees can be formed. We proposed the parallel combination model of multiple decision trees. On top of the combination model, multiple decision trees are parallel combined. Each decision tree produces its own classification rules according to training samples from which one can present the classification result using probability distribution of target class label. At the bottom, the classification result of each decision tree serves as the input for combination algorithm in producing classification result and rules for the combination model. Combination algorithm adopts weighted summation of the outputs of probability measurement levels from individual decision trees, while genetic algorithm optimizes connection weight matrix. Finally the target class label with the largest probability output value is selected as the decision result for combination classification methods. The proposed method is applied to the issues of customer credit rating assessment and customer response behaviour pattern recognition in CRM. From the simulation results it is concluded that the proposed method has higher predictive accuracy than single decision tree. Moreover, it retains good interpretability and optimizes classification rules.

The near real-time speckle masking reconstruction technique has been developed to accelerate the processing of solar images to achieve high resolutions for ground-based solar telescopes. However, the reconstruction of solar subimages in such a speckle reconstruction is very time-consuming. We design and implement a new parallel speckle masking reconstruction algorithm based on the Compute Unified Device Architecture (CUDA) on General Purpose Graphics Processing Units (GPGPU). Tests are performed to validate the correctness of our program on NVIDIA GPGPU. Details of several parallel reconstruction steps are presented, and the parallel implementation between various modules shows a significant speed increase compared to the previous serial implementations. In addition, we present a comparison of runtimes across serial programs, the OpenMP-based method, and the new parallel method. The new parallel method shows a clear advantage for large scale data processing, and a speedup of around 9 to 10 is achieved in reconstructing one solar subimage of 256×256 pixels. The speedup performance of the new parallel method exceeds that of OpenMP-based method overall. We conclude that the new parallel method would be of value, and contribute to real-time reconstruction of an entire solar image.