This study proposes a hierarchical optimization methodology for two-stage gear systems using Monte Carlo enhanced Genetic Algorithm (MCeGA). The approach integrates reliability-based design with genetic algorithms to overcome the inherent randomness of traditional GA methods. A two-phase optimization framework was developed. The system incorporates Unity engine for real-time 3D visualization and interactive design evaluation. Key design constraints including contact ratio, gear ratio, and meshing conditions were parameterized according to ISO 6336 and AGMA 2101 standards. The proposed framework enables application-specific optimal gear configurations through Pareto analysis and weighted optimization, providing engineers with practical design solutions for various industrial requirements.

Most engines for small vessels operating in coastal waters, such as fishing boats, are equipped with a reduction gear to reduce the engine's rotational speed. Small vessels are equipped with engines of fixed output and reduction gears of single reduction ratio only. This paper is a study on the development of a two-stage reducer capable of controlling the reduction ratio according to the light and full load conditions of a ship. Because the torque and rotational speed delivered to the propeller can be flexibly adjusted, the engine load can be maintained appropriately. In addition, because the engine room space is limited, the development of a two-stage reducer with an integrated power take off (PTO) was pursued to minimize the volume. Through this development, we were able to confirm a reduction in fuel consumption rate because we did not have to consume a lot of fuel to maintain maximum output. Reducing fuel consumption can result in reduced harmful exhaust emissions. Additionally, it can be expected that the frequency of failures that may occur due to overload can be reduced.

The operating parameters considered in this study include evaporating and condensing temperature, degree of subcooling and degree of superheating. in R744-R717 cascade refrigeration system and R744 two-stage compression refrigeration system with the range of low temperature -50℃∼-30℃. The coefficient of performance(COP) of R744-R717 cascade refrigeration system is about 16∼20% greater than that of R744 two-stage compression refrigeration system in the range of evaporation temperature of -50℃∼-30℃. R744 two-stage compression refrigeration system is unstable because its coefficient of performance changes significantly depending on the evaporating temperature and total compression work, and compression efficiency decreases. In this case, not efficient for long-term use. Whereas R744-R717 R744-R717 is a cascade refrigeration system using eco-friendly refrigerants. And this system is a high-efficiency refrigeration system that performs well even under various operating conditions. This is why it can be configured by selecting a refrigerant suitable for the high temperature side and the low temperature side.

With the recent surge in YouTube usage, there has been a proliferation of user-generated videos where individuals evaluate cosmetics. Consequently, many companies are increasingly utilizing evaluation videos for their product marketing and market research. However, a notable drawback is the manual classification of these product review videos incurring significant costs and time. Therefore, this paper proposes a deep learning-based cosmetics search algorithm to automate this task. The algorithm consists of two networks: One for detecting candidates in images using shape features such as circles, rectangles, etc and Another for filtering and categorizing these candidates. The reason for choosing a Two-Stage architecture over One-Stage is that, in videos containing background scenes, it is more robust to first detect cosmetic candidates before classifying them as specific objects. Although Two-Stage structures are generally known to outperform One-Stage structures in terms of model architecture, this study opts for Two-Stage to address issues related to the acquisition of training and validation data that arise when using One-Stage. Acquiring data for the algorithm that detects cosmetic candidates based on shape and the algorithm that classifies candidates into specific objects is cost-effective, ensuring the overall robustness of the algorithm.

In a group-testing method, instead of testing a sample, for example, blood individually, a batch of samples are pooled and tested simultaneously. If the pooled test is positive (or defective), each sample is tested individually. However, if negative (or good), the test is terminated at one pooled test because all samples in the batch are negative. This paper considers a queueing system with a two-stage group-testing policy. Samples arrive at the system according to a Poisson process. The system has a single server which starts a two-stage group test in a batch whenever the number of samples in the system reaches exactly a predetermined size. In the first stage, samples are pooled and tested simultaneously. If the pooled test is negative, the test is terminated. However, if positive, the samples are divided into two equally sized subgroups and each subgroup is applied to a group test in the second stage, respectively. The server performs pooled tests and individual tests sequentially. The testing time of a sample and a batch follow general distributions, respectively. In this paper, we derive the steady-state probability generating function of the system size at an arbitrary time, applying a bulk queuing model. In addition, we present queuing performance metrics such as the offered load, output rate, allowable input rate, and mean waiting time. In numerical examples with various prevalence rates, we show that the second-stage group-testing system can be more efficient than a one-stage group-testing system or an individual-testing system in terms of the allowable input rates and the waiting time. The two-stage group-testing system considered in this paper is very simple, so it is expected to be applicable in the field of COVID-19.

In this study, a two-stage electrostatic precipitator (ESP) was developed using a novel automatic dry cleaning device to reduce the ultrafine particles in subway stations. Collection efficiency was evaluated with a pilot scale ESP (1.2m× 1.2m) and the scale of the test duct was half of the subway air handling unit. The maximum collection efficiency for 0.3 μm particles was 96.9%. In addition, we studied a method of automatic dry cleaning for maintenance of the ESP. The cleaning efficiency was analyzed according to the cleaning flow rate for each particle loading amount to achieve a recovery rate over 90%. In addition, we derived the equation to estimate the reduction in collection efficiency according to the particle loading amount. It was confirmed that the performance of the contaminated ESP was restored to the initial state by the automatic dry cleaning in this study and that the electrical energy consumption was 5 times lower compared to utilizing conventional water cleaning.

Scientific and technological performances (e.g., patents and publications) made through R&D play a pivotal role for national economic growth. National governments encourage academia-industry cooperation and thereby pursue continuous development of science technology and innovation. Increasing R&D-related investments and manpower are crucial for national industrial development, but evidence of poor performance in business performance, efficiency, and effectiveness has recently been found in Korea. This study evaluates performance efficiency of the 6T sector (Information Technology, Bio Technology, Nano Technology, Space Technology, Environment Technology, Culture Technology), which is considered a high-potential promising industry for the next generation growth and currently occupies two thirds of the national R&D projects. The study measures the relative efficiency of R&D in a comparative perspective by employing the Data Envelopment Analysis (DEA) method. The result reveals overall low efficiency in basic R&D (0.2112), applied R&D (0.2083), development R&D (0.2638), and others (0.0641), confirming that economic performance and efficiency were relatively poor compared to production efficiency. Efficient R&D needs policy makers to create strategies that can increase overall efficiency by improving productivity performance and quality while increasing economic performance.

밀러 사이클은 흡입밸브 닫힘 시기 조정을 통해 압축비를 줄임으로써 NOx의 저감과 연료소비율 개선이 동시에 가능하다는 점 (밀러 효과)에서 디젤엔진에 매우 활발하게 채택되어지고 있다. 밀러 사이클은 흡입 밸브를 BDC 이전에 닫는 Early 밀러 방식과 BDC 이 후에 닫는 Late 밀러 방식으로 나눌 수 있다. 저속에서는 체적효율의 증가를 꾀할 수 있는 Late Miller가 유리한 반면, 중속, 고속에서는 IVC 이후 BDC 까지의 피스톤 하강 과정의 흡기의 팽창에 따른 내부 온도 감소 효과 높은 Early 밀러가 유리하다. 따라서 Early 밀러와 Late 밀러의 효과를 고려하여 운전 조건에 적합한 밀러 구현 방법을 채택할 필요가 있다. 본 연구에서는 4행정 엔진을 대상으로 2단 과급 시스 템의 적용하고 흡·배기 밸브 오버랩(valve overlap)의 감소를 통해 밀러 효과를 강화하는 과정과 밸브 조정 기구를 통한 밸브 조건의 변화 가 밀러 효과에 미치는 영향을 고찰하였다. 결과적으로 2단과급과 밀러사이클, 밸브 오버랩 감소와 흡입밸브 리프트 증가를 통해 연료소 비율과 최고연소온도 감소의 효과를 확인하였다.

The oriental fruit fly is a major polyphagous insect pest with a worldwide distribution. We investigated the development time, survivorship, longevity and fecundity of B. dorsalis at six different temperatures. We applied the computer programs – TWOSEX-MSChart and TIMING-MSChart - to analyze our data. We obtained the population parameters – adult preoviposition period (APOP), total preoviposition period (TPOP), oviposition days, eggs per reproductive female, first age of survival rate <50%, proportion of male and female individuals, propoortion of N-type individual, and life table parameters (net reproductive rate, intrinsic rate of increase, finite rate of increase, and mean generation time) - and population projection using two computer programs.

Age-stage two sex life table was constructed for a predatory lacewing, Chrysoperla carnea feeding on 3 different canola feeding aphids; mealy cabbage aphids, Brevicoryne brassicae (L.), mustard aphid, Lipaphis erysimi (Kaltenbach) and green peach aphid, Myzus persicae (Sulzer). The experiment was performed under laboratory conditions at 25± 1oC and 65 ± 1% RH. The immature development duration was shortest on M. persicae (17.3 days). While, C. carnea completed its immature developmental period in 21.1 days, which was longest among other, tested aphids. Similarly, survival of C. carnea was higher on feeding M. persicae and lowest on L. erysimi. Female egg laying of predator was also higher on M. persicae, followed by B. brassicae and L. erysimi. These results show that M. persicae favors the quick development and higher reproduction of C. carnea as compared to B. breassicae and L. erysimi. This information is useful in relation to mass rearing of C. carnea and in biological control of canola aphids by using C. carnea.

본 논문에서는 이단계 칼만필터를 활용한 구조물의 3 자유도 동적변위 계측 시스템을 소개한다. 개발 시스템은 센서 모듈, 베이스 모듈, 컴퓨테이션 모듈로 구성되어 있다. 센서 모듈은 100Hz 샘플주파수의 고정밀 가속도를 계측하는 포스피드백 가 속도계와 10Hz의 샘플주파수의 저정밀도의 속도, 변위를 계측하는 저가의 RTK-GNSS로 구성되어 있다. 계측된 데이터는 LAN 케이블을 통하여 컴퓨테이션 모듈로 전송되고, 컴퓨테이션 모듈에서 이단계 칼만필터를 활용하여 100Hz 샘플주파수의 고정밀 변위를 실시간으로 산정한다. 개발 시스템의 변위 계측 정밀도를 검증하기 위해 미국, 캘리포니아에 위치한 San Francisco-Oaklmand Bay bridge 에서 현장 실험을 수행하였으며, 실험 결과 1.68mm RMS 오차를 보임을 확인하였다.

The dynamic capabilities of sensing market signals, creating new opportunities and reconfiguring resources and capabilities to new opportunities in a rapidly changing economic environment determines the competitiveness of the enterprise to create added value and survival. This study conceptualized a two-stage performance measurement framework based on the casual model of resource (input)-process-performance (output). We have developed a ‘Process capability index’ that reflect the dynamic capabilities factors as a key intermediary product linking resource inputs and performance outputs in enterprise performance measurement. The process capability index consists of four elements : manpower (level of human resource), operation productivity, structure and risk management. The DEA (Data Envelopment Analysis) model was applied to the developed performance indicators to analyze the branch office performance of a telecom company. Process capability efficiency (stage 1) uses resource inputs to reach a certain level of process capabilities. In performance result efficiency (stage 2), the process capabilities are used to generate sales revenues and subscribers. The two-stage DEA model derives intermediate output values that optimize the individual stages simultaneously. Some branch offices in the telecom company have focused on process capability efficiency or some other branch offices focused on performance result efficiency. Positioning map using two-stage efficiency decomposition and benchmarking can help identify the sources of inefficiencies and visualize strategic directions for performance optimization. Applications of two-stage DEA in conjunction with the case study that are meaningfully used in performance measurement areas have been scarce. In particular, this paper has the contribution to present a new performance measurement model considering the organization theory, the dynamic capabilities.

2012년부터 강화된 총인의 농도를 준수하기 위해서는 응집에 의한 물리화학적 처리가 필수적인 후단공정이 되었으며, 현재 국내 하수처리시설 중 약 60%의 처리시설에서 총인처리시설이 설치되었다. 하지만 총인처리시설 운전에 따른 응집제 사용량이 증가하게 되었고, 이에 따라 약품 비용 및 슬러지 처리비 증가 등의 운영비가 상승하였다. 특히 분리막 공법(MBR)의 경우 막 투과수의 응집액 부족으로 인한 응집효율 저하 및 응집제의 과다 주입으로 인한 처리수질 악화 등의 문제가 발생하는 경우도 있다. 본 연구에서는 MBR 공법내에서 별도의 총인처리시설 필요 없이 생물학적 인제거를 극대화 하는 동시에 응집제 사용량을 최소화하면서 처리수의 인농도를 0.2 mg/L 이하로 유지할 수 있는 방안을 도출하고자 하였다.