Earticle

광기전공학 기술이 융합된 광학계의 발달은 광학계를 구성하는 부품의 표면이 비구면 또는 자유곡면으로 진화하고 있다. 본 논문에서는 광학식 자유곡면의 국부영역으로부터 직교하는 2방향의 곡률을 정의하여 전체 형상 을 복원하는 알고리즘을 제안하였다. 8.4 m 자유곡면 형상을 가진 반사거울에 구현된 알고리즘을 적용한 결과 형상 복원 최대오차 0.065 nm, 평균제곱근 오차 0.013 nm로 복원됨을 확인하였다. 프루브의 위치오차 발생에 대한 노이 즈 민감도를 해석한 결과, 2 mm 오차에 대해서도 형상복원 최대오차 30 nm, 제곱평균제곱근 오차 8.7 nm로 위치 오차에 매우 둔감한 알고리즘임을 확인하였다.

The demand for accurate freeform apsheric surface is increasing to satisfy the optical performance. In this paper, we develop the algorithm for opto-mechatronics convergence, that reconstruct the surface 3D profiles from the curvarure data along two orthogonal directions. A synthetic freeform surface with 8.4 m diameter was simulated for the testing. The simulation results show that the reconstruction error is 0.065 nm PV(Peak-to-valley) and 0.013 nm RMS(Root mean square) residual difference. Finally the sensitivity to noise is diagnosed for probe position error, the simulation results proving that the suggested method is robust to position error.

The mobile networks play a vital role in the information and communication technology. There are two kinds of mobility supported by mobile networks such as host mobility and network mobility. The enhancement of Quality of Service (QoS) in NEtwork MObility (NEMO) environment is more complex than host mobility environment. One of the complexities in NEMO environment is routing of packets. The routing algorithms play a significant role in enhancing QoS. This necessitates looking into the weaknesses of existing routing algorithms. Based on the weaknesses, we have already proposed a Delay-Sensitive Routing for NEMO (DSRNEMO) to enhance the QoS in NEMO environment with respect to delay parameter. The objectives of this paper are to derive a mathematical model for DSRNEMO and to simulate the operations of DSRNEMO. The outcome of the mathematical model and simulation results show that the DSRNEMO gives better results than the existing algorithm, NEMO. Ultimately, this paper contributes to enhance the QoS in mobile networks.

In the process of the rice germination, temperature control is the key. Due to the accelerating seed germination system belongs to a complex nonlinear, large time delay and multivariable, it is difficult to establish the exact mathematical relationship model. In order to solve this problem, in this paper, we established the model based on RBF neural network, and used genetic algorithm to optimize the parameters of the neural network. In order to realize the accurate control of temperature and ensure the quality of rice sprouting, Fuzzy-PID control method can adjusts the parameters of PID and effectively improve the uniform distribution of temperature in the germinating box. The 3D graphics of temperature distribution obtained by MATLAB can show effectiveness of the method. Finally, the control strategy and system model improving the rice budding rate and evenness of emergence, are verified by experimental verification.

This paper presents a new mathematical simulation using data validation through machine learning for the sustainable construction of smart concrete structures equipped with piezoelectric patches. The framework leverages the self-sensing characteristics of piezoelectric materials to meet the pressing demands for sustainable, intelligent, and resilient infrastructure. The dynamic electromechanical behavior of concrete elements under different working conditions and environmental influences is simulated based on a detailed mathematical model. These simulations are then validated by the use of machine learning algorithms that have been trained on experimental and synthetic data in order to improve the accuracy and robustness for future real-world applications. Simulation of the mathematics along with supervised learning models reveals how the system can support in detection of an anomaly and help make decisions proactively. The research also contributes towards smart infrastructure domain by offering a sustainable and globally conformable, scalable, and adaptive framework. When applied in combination, power of simulation and data-driven validation supports a revolution in civil engineering design and maintenance pipeline towards an efficient, long-lasting, and intelligent built world.

This study investigates the thermal post-buckling behavior of concrete eccentric annular sector plates reinforced with graphene oxide powders (GOPs). Employing the minimum total potential energy principle, the plates' stability and response under thermal loads are analyzed. The Haber-Schaim foundation model is utilized to account for the support conditions, while the transform differential quadrature method (TDQM) is applied to solve the governing differential equations efficiently. The integration of GOPs significantly enhances the mechanical properties and stability of the plates, making them suitable for advanced engineering applications. Numerical results demonstrate the critical thermal loads and post-buckling paths, providing valuable insights into the design and optimization of such reinforced structures. This study presents a machine learning algorithm designed to predict complex engineering phenomena using datasets derived from presented mathematical modeling. By leveraging advanced data analytics and machine learning techniques, the algorithm effectively captures and learns intricate patterns from the mathematical models, providing accurate and efficient predictions. The methodology involves generating comprehensive datasets from mathematical simulations, which are then used to train the machine learning model. The trained model is capable of predicting various engineering outcomes, such as stress, strain, and thermal responses, with high precision. This approach significantly reduces the computational time and resources required for traditional simulations, enabling rapid and reliable analysis. This comprehensive approach offers a robust framework for predicting the thermal post-buckling behavior of reinforced concrete plates, contributing to the development of resilient and efficient structural components in civil engineering.

This study presents a robust thermoeconomic framework for marine nuclear propulsion, utilizing the Nuclear Ship Savannah as a case study. To overcome data limitations, creative solutions are applied, including the application of artificial neural network approach to solve nonlinear coupled exergoeconomic equations and determine the thermodynamic properties of the flow within the Savannah's Nuclear Propulsion (SNP). Upon validating the proposed model, the study introduces innovative design modifications to enhance the thermal efficiencies of the SNP. Furthermore, single-objective optimization (SOO) and multi-objective optimization (MOO) are incorporated into the improved SNP (ISNP) to optimize system performance criteria, such as exergy efficiency (η_II), total capital cost rate (Ċ^I&O&M_tot), and total product exergy cost rate (Ċ_P). Afterwards, the ISNP optimization is executed using Henry Gas Solubility Optimization (HGSO) to determine the optimal non-dominated solutions, allowing for the evaluation of trade-offs in system performance. The final optimal design of the optimized ISNP (OISNP) is then selected through a multi-criteria decision-making process. Subsequently, a comprehensive comparative analysis is conducted on the SNP, ISNP, and OISNP models, considering energy, exergy, exergoeconomic, and environmental economics (4-E) viewpoints. The 4-E analysis reveals that the SNP exhibits an energy efficiency of 26.18 % and an exergy efficiency of 51.8 %, whereas the ISNP demonstrates enhanced performance with an energy efficiency of 28.42 % and an exergy efficiency of 55.50 %. The improvement lead to a 1.31 MW boost in propulsion power compared to the SNP, bringing it to 16.4 MW. This comparative evaluation underscores the significant improvements achieved through the modifications implemented in the SNP. Also, the OISNP demonstrates further advancements, achieving an exergy efficiency of 55.01 %, representing a 3.2 % improvement over the SNP, while its energy efficiency is recorded at 28.4 %, a 2.22 % increase compared to the SNP. Additionally, the propulsion power reaches 16 MW, marking a 1 MW increase over the SNP. Notably, the Ċ^I&O&M_tot,OISNP and Ċ_P,OISNP are reduced to $282.3/hour and $4290/hour, respectively, indicating substantial cost savings relative to both the ISNP and SNP models. Besides, the environmental analysis indicates that transitioning from a fossil fuel-powered MSP to an OISNP annually cuts fossil fuel consumption by 61,320 tons, generating $30.66 million in potential export revenue. This change reduces emissions by 193 kilotons (kt) of CO₂, 4.3 kt of NO_x, 3 kt of SO₂, and 0.92 kt of PM, while decreasing external costs by $6.132 million and potentially avoiding $9.65 million in annual carbon tax liabilities for the shipping industry. Furthermore, to evaluate the comparative statistical performance of the competing algorithms, a Wilcoxon rank sum test is conducted. The comparative results show that the HGSO algorithm outperforms the others, delivering both competitive and superior outcomes in solving complex optimization problems.

Estimating the construction period at the initial stage of the project and determining whether it is appropriate is very important for the developer's decision-making and the success of the construction company's business. Existing researchers have conducted various studies to calculate the appropriate construction period, but there is no study on the influencing factors and methodology for the construction period of beam-column PC apartment building frame construction. The purpose of this study is to calculate the PC member assembly time using the mathematical algorithm of PC member assembly. The results of this study can be used as basic data to calculate the construction date of the standard floor of PC construction.

본 연구는 알고리즘 기반의 수학활동이 유아의 수학적 문제해결력에 미치는 영향을 알아보고자 했다. 연구대상은 D지역의 I유치원 만 5세반 유아 42명으로 실험집단 유아 21명(남아 11명, 여아 10명), 비교집단 유아 21명(남아 11명, 여아 10명)이다. 연구절차는 알고리즘 기반의 유아수학활동 구성, 예비검사, 실험장소의 선정 및 실험자 교육 실시, 사전검사, 실험처치, 사후검사 순으로 진행되었다. 실험처치는 2017년 8월 21일부터 9월 29일까지 6주간 진행되었으며, 연구기간 중 실험집단 유아들에게는 알고리즘 기반의 수학활동을 매주 2-3회 적용하였다. 비교집단 유아들에게는 누리과정 중심 수학활동을 실시하였다. 수집된 자료는 SPSS 24.0을 사용하여 통계 처리하였다. 연구 결과, 유아의 수학적 문제해결력 전체는 실험진단과 비교집단 간의 유의미한 차이가 나타났으며 수학적 문제해결력의 하위영역 중 측정, 대수, 기하, 통계영역의 수학적 문제해결력을 향상 시켰다. 본 연구는 알고리즘 기반의 수학활동이 유아의 수학적 문제해결력 발달을 위한 새로운 교수학습 접근법을 제시함에 그 의의가 있다

The purpose of this study is to investigate the effects of Algorithm-based mathematic activities to young children's mathematical problem solving ability. The participants were 42 of five-year old children(experimental group 21, comparative group 21) at I kindergarten located in D city. the research proceeded in order that consisted of algorithm - based early childhood mathematical activity composition, preliminary test, selection of experiment site, implementation of experimenter education, pre - test, experimental treatment and post - test. The experiment was conducted from August 21 to September 29, 2017 for 6 weeks. The experiment group performed the mathematics activities through the algorithm-based, and the comparative group performed the mathematics activities in the Nuri course based on life topic. The results of this study is that, in the mathematical problem solving ability, there was a significant difference between the two groups. Second, mathematical problem solving ability of measurement, algebra, geometry, and statistical domain was improved among sub - areas of mathematical problem solving ability. Therefore, it has been shown that algorithmic mathematical activities are effective in improving the mathematical problem solving ability of young children. This study suggests that algorithm - based mathematical activities can be proposed as a new teaching and learning method for the development of mathematical problem solving ability of young children and it is a mathematical activity of unplugged learning which learns computer science without using computer. Is expected to be developed into a new type of mathematics education program for young children.

본 연구에서는 서로 상이한 최적화기법인 유전알고리듬과 수학적 프로그래밍기법을 이용하여 지오데식 돔 구조물을 최적화하고 그 결과를 분석하였다. 본 연구에서 도입한 유전알고리즘은 유전연산자인 선택, 교배, 돌연변이 이외에도 재생기법을 도입하여 최적해의 검색성능을 높였다. 그리고 수학적인 프로그래밍기법은 유한차분법을 이용하여 목적함수의 설계민감도를 계산하였으며 세 가지의 다른 검색기법을 이용하여 돔의 크기최적화를 수행하였다. 지오데식 돔의 중앙에 작용하는 집중하중에 저항하는 돔의 각 부재의 크기패턴을 자체 개발된 $ISADO-GA{\alpha}$와 ISADO-OPT를 이용하여 최적 설계하였다. 본 연구를 통하여 제시된 최적결과는 정해가 존재하지 않는 실제 구조물의 최적 값에 대한 유용한 정보를 제공할 뿐만이 아니라 향후 대공간구조의 새로운 구조시스템 개발의 밑거름이 될 것으로 판단된다.

This paper describes a comparative study of genetic algorithm and mathematical programming technique applied in the design optimization of geodesic dome. In particular, the genetic algorithm adopted in this study uses the so-called re-birthing technique together with the standard GA operations such as fitness, selection, crossover and mutation to accelerate the searching process. The finite difference method is used to calculate the design sensitivity required in mathematical programming techniques and three different techniques such as sequential linear programming (SLP), sequential quadratic programming(SQP) and modified feasible direction method(MFDM) are consistently used in the design optimization of geodesic dome. The optimum member sizes of geodesic dome against several external loads is evaluated by the codes $ISADO-GA{\alpha}$ and ISADO-OPT. From a numerical example, we found that both optimization techniques such as GA and mathematical programming technique are very effective to calculate the optimum member sizes of three dimensional discrete structures and it can provide a very useful information on the existing structural system and it also has a great potential to produce new structural system for large spatial structures.

At the initial deployment of B-ISDN, the heterogeneity of services and the bandwidth requirement make dimensioning of B-ISDN much more complicated than the dimensioning of homogeneous circuit or packet switched networks. Therefore B-ISDN must be extended gradually according to future telecommunication technology or service demands. In this paper, we propose a mathematical formulation for dimensioning problem of B-ISDN extension, considering the characteristics of ATM(Asynchronous Transfer Mode) such as various quality of services, the statistical multiplexing effects of VPCs(Virtual Path Connections) and the modularity of transmission links allocated when new B-ISDN nodes are given. The algorithm based on the simultaneous linear approximation technique and Lagrangian relaxation method and some numerical results are also presented.

For optimizing the operation plan when strike packages attack multiple targets, this article suggests a new mathematical model and a parallel hybrid genetic algorithm (PHGA) as a solution methodology. In the model, a package can assault multiple targets on a sortie and permitted the use of mixed munitions for a target. Furthermore, because the survival probability of a package depends on a flight route, it is formulated as a mixed integer programming which is synthesized the models for vehicle routing and weapon-target assignment. The hybrid strategy of the solution method (PHGA) is also implemented by the separation of functions of a GA and an exact solution method using ILOG CPLEX. The GA searches the flight routes of packages, and CPLEX assigns the munitions of a package to the targets on its way. The parallelism enhances the likelihood seeking the optimal solution via the collaboration among the HGAs.

At each iteration, the path is either extended by adding a new node, or contracted by deleting its terminal node. When the destination becomes the terminal node of the path, the algorithm terminate. In the process of finding the shortest path to given destination, the algorithm visits other node, there by obtaining a shortest path from the origin to them. We show here that when the auction algorithm is applied to this equivalent program with some special rules for choosing the initial object prices and the person submitting a bid at each iteration, one obtains the generic form of the $\varepsilon$-relaxation method. Thus, the two methods are mathematically equivalent

In order to improve the efficiency of a main transformer in a train, the optimal operation of a cooling system is necessary. For the development of optimal control algorithms of a cooling system, mathematical models of a main transformer cooling system were developed. These include static and dynamic models of a main transformer, an oil pump, an oil cooler, and a blower. Static models were used to find optimal oil temperatures of the inlet and the outlet of a transformer. Dynamic models were used to predict transient performances of control algorithms of a blower and an oil pump. Simulation results showed good predictions of the static and the dynamic behavior of a main transformer cooling system. Therefore, mathematical models developed in this study may be effectively used for the development of control algorithms of a main transformer cooling system.

본 논문에서는 파일롯 채널(pilot chanel)이 존재하는 직접확산 코드분할 다중접속 방식(DS-CDMA)에서 탐색 창을 갖는 이중도웰 직렬 동기획득 방식에 대한 수학적 모델을 제시하고, 이에 대한 성능을 분석하였다. 성능 분석을 위한 유도된 수학적 모델들은 부호 검출 함수, 오보 함수, 부호 miss함수, 그리고 평균 동기 획득 시간 등이었다. 또한 유도된 식을 IS-95 순방향 링크에 적용하여 수학적 모델에 의한 평균 동기획득 시간을 계산하였고, 이것을 기존의 동기획득 알고리듬과 비교하였다. 그리고 탐색 창을 갖는 이중드웰 직렬 동기 획득 방식에 대하여, 적분 시간과 탐색 창의 크기가 평균 동기획득 시간에 미치는 영향도 분석하였다. 성능분석을 위해 사용된 채널 모델은 북미의 PCS 채널 모델인 JTC 채널로 설정하였다. 성능 분석 결과, 탐색 창을 갖는 이중드웰 직렬 동기획득 방식이 평균 동기획득 시간에서 기존의 동기획득 알고리듬보다 약 17%~25% 정도 단축됨을 보였다.

In this paper, we present a mathematical modeling and perform a performance analysis of double-dwell serial search algorithm, which has a search window concept, for pilot channel in DS-CDMA(Direct Sequence Code Division Multiple Access). We derive a code detection function, a false alarm function, a code miss function, and a mean code acquisition time for the performance analysis. We calculate the mean code acquisition time of the mathematical model in IS-95 forward link and compare it with that of the conventional search methods. The performance of the code acquisition system is also evaluated to investigate the effect of dwell times and search window size. The JTC channel model, which is a PCS channel model in North America, is used for the analysis. The numerical result shows that the mean code acquisition time of the double-dwell serial search algorithm with a search window is reduced by about 17%~25% than those of the conventional ones.

In this paper, we propose a new termination rule for the iterative restoration of degraded images, by which the number of iterations can be dramatically reduced. This rule uses a parameter, called noise suppression factor (NSF), to appropriately teminate the iteration process, reduces a lot the computational load, and avoids the amplification of noise for the better quality. We also propose a method using the morphological filters, when applied to the resulting image, that will significantly reduce the ringing effect which would otherwise exist in the boundary of the image. Simulation with the blurred lena image with gaussian noise showns that the proposed termination rule combined with the morphological filtering gives the restored image with much improved quality.

Minimum-cost linear network flow problems could be transformed with equal to assignment problems. Traditional method to solve the linear network flow problems are improved source-cost by transform the simple cycle flow. Auction algorithm could be applied to same element using the initial target price and dispersion calculation. Also, each elements are obtained by $\varepsilon$-relaxation methods. In this paper we proposed; 1)minimum-cost flow problem, 2)minimum-cost flow problem by the mathematical equivalent and 3) extraction $\varepsilon$-relaxation & expand transfer problem with minimum-cost flow. It can be applicant to PCB design by above mentioned.

최소비용 선형 망 흐름 문제가 동등한 할당 문제로 변환될 수 있으며, 또한 선형 망 흐름 문제를 해결하기 위한 전통적 방법은 단순 싸이클 흐름을 변환시킴으로서 원시 비용을 개선하는 방법이다. Auction 알고리즘이 각각의 반복에서 분산계산을 제시하는 개체와 초기의 대상 가격을 선택하기 위하여 몇 개의 특별한 법칙과 함께 동일한 문제에 적용이 될 때, 개체는 ${\varepsilon}$-이완법의 형태에서 획득할 수 있다. 본 논문은 할당 문제를 해결하기 위한 방법으로 최소비용 흐름 문제를 일반화 시켜, 전형적인 반복에 최소비용 흐름 문제, 수학적 등가에 의한 최소비용 흐름 문제를 연구하였고, 최소비용 흐름 측면에서 수송문제의 확장과 ${\varepsilon}$-이완법을 도출하여 이를 PCB 설계에 응용하고자 하였다.