Earticle

This research introduces an innovative approach in implementing Know Your Customer (KYC) on blockchain technology as a means of using data, hybrid robust m-estimation, and the iteratively reweighted less squares (IRLS) method to optimize CLV data. This approach aims to improve the accuracy and reliability of CLV predictions by ensuring the security and reliability of customer data. This tool can help companies manage and increase CLV more effectively, meeting data security and compliance standards. The R-squared validation test results are close to 1, so the model can explain data variations well. RMSE and MSE have small values, ??so the model has good performance in predicting the target value. With these achievements, this approach contributes to the development of better marketing strategies and business decisions in an increasingly complex and rapidly changing digital environment.

Animal pattern recognition from nighttime grayscale images is crucial for wildlife protection and ecological monitoring. Most of the current models suffer from a large parameter scale, making them unsuitable for deployment in resource-constrained environments. To address this challenge, this study proposes a multi-layer knowledge distillation approach based on the teacher Convnext model to improve the lightweight student model's classification performance effectively. Experimental results show that the parameters of the distilled CifarResNet20 model are only 0.27M, and the accuracy is 88.76%, which is superior to the traditional single-layer distillation and another tiny student model. The study confirms the efficiency and practical value of the proposed method in practical applications such as ecological monitoring.

반도체폐수 내 납 및 비소 분석의 정확도 향상을 위해 몇 가지 조건에서 전처리를 수행한 분석 결과를 비교하고 최적 분석법을 선정 하고 검증하였다. 우리나라에서는 물환경보전법에 의한 법적 규제가 이루어지고 있는데, 특정수질유해물질 폐수배출시설 적용기준인 0.01 mg/L을 고려할 때 낮은 정량한계 목표(납 0.002 mg/L, 비소 0.006 mg/L)로 분석 가능한 ICP-MS로 분석하는 것이 바람직하다. 한편 유기물 등의 간섭물질이 다량 존재하는 반도체폐수 내 금속류를 ICP-MS로 정량하기 위해서는 산 분해 전처리가 선행되어야 하는데, 일 반적으로 수행하고 있는 질산 등을 적용한 전처리 방법을 통해서는 반도체폐수 내 간섭물질의 적절한 제거가 되지 않아 분석의 재현성 및 정확도가 떨어지는 현상이 발생한다. 본 연구에서는 전처리 가열온도 및 과산화수소 적용 여부, 그리고 시약 적용량 등에 따른 분석 결과를 비교하였으며 검정분석법에 따른 분석 결과를 비교하였다. 분석 결과, 납과 비소 모두 검정곡선법(납 52.2~101.6%, 비소 49.8~122.4%)보다 내부표준법(납 72.6~120.2%, 비소 79.7~105.2%)에서의 회수율이 안정적으로 나타났으며 특히 비소 분석 결과에서 통 계적으로 유의한 차이를 보였다. 또한 질산만을 적용한 전처리보다 과산화수소를 함께 적용했을 때, 과산화수소 첨가량 및 가열 온도가 높아질수록 대체적으로 안정적인 회수율을 보였다. 상기 결과에 근거하여 선택된 전처리 조건에서 반복성 분석을 실시했을 때, RSD 5% 이내(0.61~2.15%)로 높은 정밀도를 나타냈다. 전처리 후 시료의 TOC 농도를 측정한 결과 75.9~82.3%의 감소율을 나타냈다. 선택된 분 석법으로 반도체폐수 내 납과 비소를 분석할 때 정확도 높은 결과 획득과 더불어 분석 시간 및 비용 절감이 가능할 것으로 기대된다.

This study aimed to optimize sample preparation and calibration method by comparing results with different pretreatment conditions and calibration methods for enhancing precision and accuracy. Considering the standard of specific toxic substance for wastewater discharge facilities, or 0.01 mg/L, it is desirable to analyze using ICP-MS that can be analyzed with a low LOQ (Lead 0.002 mg/ L, Arsenic 0.006 mg/L) for accurate analysis of trace elements. In this study, we compared the internal standard method with the external standard method. Acid digestion was performed in several conditions. The results showed that both Lead and Arsenic recovery was more stable in the internal standard method (72.6 to 120.2% for Lead, and 79.7 to 105.2% for Arsenic) than the external standard method (52.2 to 101.6% for Lead, and 49.8 to 122.4% for Arsenic), and there is a statistically significant difference between the groups. Compared to pretreatment method using nitric acid only, the method with hydrogen peroxide showed more stable recovery rate. Based on the results of the above, the repeatability analysis was performed under selected conditions, showing high precision within 5% of RSD. It is expected that the selected methods can be determined accurately and economically for Lead and Arsenic in semiconductor wastewater.

This study designed a model of the efficient production schemes and raw materials transportation optimization of current South Korean’s simple and monolithic distribution system of wood to build a SCM (supply chain management) as a basic level to establish a distribution of future by pellet production of raw materials costs and reduce transport costs, and specifically to forest of pallet to contribute to revitalizing the market. The result of each transportation costs after building the best transportation network from raw material supply area to demand area applying transport law was 964,600 thousands Won from 6 supply areas to 7 demand areas. And the result of each model’s analysis to get the pellet’s efficient production through production cost reduction showed that it reduced from 325,701 Won/t to 240,106 Won/t, results of existing efficient pellet for the production model 8,233 tons over 20,000 tons annual production capacity from the size of the expanded production capacity when the expansion. However, when the production size expanded to 50,000 Tons of the production, the effect was very small even though production cost decreased.

본 연구에서는 다중최적화기법을 이용하여 2가지 수문학적 과정을 통하여 유출량을 산정하는 수문모형의 모형 최적화를 시도하였으며, 수문모형으로는 융설량과 유출량을 동시에 산정할 수 있는 분포형 수문모형인 HL-RDHM을 이용하였다. 대상유역으로는 융설량 자료를 수집할 수 있는 미국 콜로라도의 Durango River 유역을 선정하였다. 다중최적화기법으로는 MOSCEM을 활용하였으며, 융설과 관련된 매개변수 5개와 유출에 관련된 매개변수 13개를 선정하여 매개변수 보정과 수문모형 최적화를 시도하였다. 모형 최적화를 위해 2004 – 2005년의 자료가 활용되었고, 2001 – 2004년 자료를 이용하여 검증하였다. 융설량과 유출량을 동시에 최적화함으로써 RMSE 기준으로, 3개의 SNOTEL 지점에서 초기해에 의한 모의치 보다 7% - 40%까지 RMSE 오차를 줄일 수 있었고, 유출구의 USGS 관측점에서 초기해에 비해 약 40% 값이 개선됨을 확인하였다.

In this study, the multi-objective optimization method is attemped to optimize the hydrological model to estimate the runoff through two hydrological processes. HL-RDHM, a distributed hydrological model that can simultaneously estimate the amount of snowfall and runoff, was used as the distributed hydrological model. The Durango River basin in Colorado, USA, was selected as the watershed. MOSCEM was used as a multi-objective optimization method and parameter calibration and hydrologic model optimization were tried by selecting 5 parameters related to snow melting and 13 parameters related to runoff. Data from 2004 to 2005 were used to optimize the model and verified using data from 2001 to 2004. By optimizing both the amount of snow and the amount of runoff, the RMSE error can be reduced from 7% to 40% of the simulation value based on the initial solution at three SNOTEL points based on the RMSE. The USGS observation point of the outflow is improved about 40%.

This study analyzed the appropriate placement method by floor for evacuating all occupants during the nighttime through evacuation simulation. The analysis results are as follows. First, when non-self evacuating patients were placed on the first floor, 266 patients and 6 workers were found to be evacuated after 460 seconds. This result shows that it is meaningful to place non-self evacuating patients on the lower floor with a time that is faster than 540 seconds, which is an evaluation criterion set using life Safety standards for human. This result is a time faster than the evaluation criteria of 540 seconds, which is set using the life safety standards, and it can be confirmed that it is meaningful to place non-self evacuating patients on the lower floor. Next, as a result of placing non-self evacuating patients from the first floor to the fourth floor, it was found that evacuation of all occupants required 460 seconds for the first floor, 834 seconds for the second floor, 1,508 seconds for the third floor, and 1,915 seconds for the fourth floor. These results indicate that the placement of non-self evacuating patients on the rest of the floors, except for the first floor, can lead to dangerous results in excess of 540 seconds, which is a flashover time. As a result, it is necessary to place non-self evacuating patients on a lower floor for safe evacuation. The study has limitations except for comparative analysis of changes in evacuation time due to changes in the number of workers at eldery care hospitals and situations in which fire-fighting facilities such as sprinkler facilities operated. It is necessary to study the evacuation time linked to the operation of the fire-fighting facilities and the evacuation time according to the change in the number of workers in the future.

The background of this study is to establish a systematic development process for SSD(Solid State Drive) which is being watched as the next generation auxiliary memory device and to make stable production. In order to do so, we select the two products that have been developed and classify and analyze all defects generated in each product by type and process of defects. The root cause of the fault and its background were reflected in the contradiction matrix of TRIZ's technical contradiction, and the improvements suggested in the 40 inventive principles were reflected in the test case design methodology of each process. Finally, this study suggests a process optimization method for systematic development.

In order to select the supporting points for large glass panels used for TFT-LCD monitors, an optimization method selecting the supporing points is presented. In this method we reduce the problem of 1 degree of freedom. ANSYS optimization module is used and optimization criterion is to minimize the maximum deflection.

This study, high-rise structure design of lateral loads, topics are slenderness ratio and stiffness. CTBUH said that high-rise structure is defined by slenderness ratio and later load resistance system. Selected analysis model is optimized by weight optimization method by taking the principle of virtual work. It's slenderness ratio is 5. Lateral load is proportional to structure's height. Stiffness method gives some analytical advantages to analysis the high-rise building rather than strength method. In generally analysis, lateral deflection controls structural limit state in the high-rise building design. And the lateral deflection can be easily find by stiffness method rather than strength method. We study for the weight optimization of the high-rise concrete structural model. We set up object function of weight and constraint function to obtain optimization member sizes. Because the lateral deformation constraint function can not be simply defined between correlation with object function. So, use principal of virtual work for lateral deformation constraint function to clear correlation with object function. This thesis suppose the slenderness ratio and many assumption. As a results from this study, we easily find member sizes, and lateral deformation at the limit state and strength with minimum weight. By structural analysis of deduction member sizes, demonstrate validity and usefulness of high-rise concrete structure optimization. Results of this thesis are as follows. First, Stiffness design is more effective than strength method. Cause, Strength method finds hard later deformation and takes more time than stiffness method. Enfin, Stiffness method is advantageous at High-rise structure design. Second, Existing constraint function isn't reflect geometrical shape for members. So, interaction between constraint and object function are indefinite. To solve this problem, We define between member shapes and lateral deformation to use principle of virtual work. In result, We find that it is relation of effect of lateral deformation and member shapes.

폐자동차 범퍼 파쇄물 재활용을 위하여 색채선별법을 도입하였다. 색채선별법은 기존의 비중, 입도 차이에 의한 선별이 어려운물질을 색상 차이를 이용한 카메라와 영상 분석기법으로 분리하는 선별법이다. 본 연구에서는 반응표면법 중 BBD (Box-Behnken Design)를 적용하여 실험을 계획하고 최적 조건을 도출하였다. 색채민감도, 피드투입량 및 입자크기의 영향을 분석하였으며, 회귀분석과 통계적인 방법에 기초하여 2차 반응 모델을 획득하였다. R 2 및 p-value는 각각 99.56%, < 0.001로 타당하였으며, 추정된 최적조건은 색채민감도 32%, 피드투입 200 kg/h, 입자크기 33 mm 조건에서 94.1%의 회수율이 나올 것으로 예측하였다. 실제 실험을통한 회수율은 93.8%로 나타나 해당 모델이 적절함을 확인하였다.

An color sorting technique was introduced to recycle End-of-life automobile shredded bumpers. The color sorting is a innovate method of separating the differences in the color of materials which are difficult to separate in gravity and size classification by using a camera and an image process technique. Experiments were planned and optimal conditions were derived by applying BBD (Box-Behnken Design) in the reaction surface method. The effects of color sensitivity, feed rate and sample size were analyzed, and a second-order reaction model was obtained based on the analysis of regression and statistical methods and R 2 and p-value were 99.56% and < 0.001. Optimum recovery was 94.1% under the conditions of color sensitivity, feed rate and particle size of 32%, 200 kg/h, and 33 mm respectively. The recovery of actual experiment was 93.8%. The experimental data agreed well with the predicted value and confirmed that the model was appropriate.

In this paper, a method of reducing the weight of vehicle wheels through topology optimization by finite element method is proposed. Recently, various environmental pollution caused by the operation of vehicles is gradually increasing, and this has a great correlation with the fuel efficiency of the vehicle. Therefore, it is required to reduce the weight of the vehicle to increase fuel efficiency. Among them, the vehicle's wheels are a key part of vehicle acceleration and braking, and passenger safety. Because the shape of the wheels is different, various effects such as reduced fuel economy and reduced airpower occur as well as aesthetic factors. The stiffness of the wheels plays an important role in transmitting the vehicle's power to the tires and braking. In this study, to reduce weight while satisfying the stiffness value, we propose to use topology optimization to design an arbitrary shape according to the number of spokes on the wheel.