본 연구는 서울시를 대상으로 여름철 지표온도(LST)에 영향을 미치는 공간적 요인을 분석하고, 지역별 영향력의 이질성을 파악하고자 하였다. 이를 위해 Landsat 8 위성영상을 활용하여 2024년 여름철 평균 지표온도를 산출하고, 자연환경, 도시구조, 인구활동, 토지이용 변수들을 250m 격자 단위로 구축하였다. 전역적 회귀분석(OLS)과 지리가중회귀분석(GWR)을 수행한 결과, GWR 모형이 더 높은 설명력(R2 = 0.878)과 낮은 AIC 값을 보여 공간적 적합도가 우수함을 확인하였다. 또한 Local R2 분포를 통해 모형의 설명력이 지역별로 상이함을 확인하였고, 변수별 회귀계수의 공간 분포를 통해 열환경 형성 요인의 비선형성과 공간 비정상성을 실증적으로 확인하였다. 본 연구는 서울시의 열환경 대응을 위한 지역 맞춤형 공간정책 수립에 기초자료를 제공하며, 도시열섬의 불균형 해소 및 열취약지역 관리 전략의 수립에 기여하고자 하였다.

2024년 기준으로 서울특별시의 자전거 이용률과 자전거 도로 인프라가 모두 증가하는 경향을 보이고 있는 반면 자전거 사고건수 및 자전거 사고로 인한 사망자수와 중상자수는 매년 감소하고 있는 추세를 보이고 있어 현행 자전거 관련 안전 정책이 어느 정도 실효성 이 있음을 시사한다. 그러나 중상 및 사망사고는 여전히 지속적으로 발생하고 있어 이에 대한 효과적인 정책이 필요한 상황이지만 현 재 국내 자전거 안전 정책은 사고 예방에만 집중되어 있어 사고의 특성을 종합적으로 반영하지 못한다는 큰 문제점이 있다. 이에 본 연구는 서울특별시 자전거 사고 데이터를 기반으로 자전거 도로 유형별로 서로 다른 값의 가중치를 부여하여 자전거 도로 자체의 특 성을 반영한 사고 심각도를 산출하고, 사고 심각도와 사고 건수를 각각 표준화하여 단위를 통일한 후 이를 통합한 종합적 사고 위험 도 점수를 도출하는 방법론을 사용하였다. 본 연구의 목적은 실제 서울특별시의 공유자전거 사고데이터를 활용하여 자전거 도로 유형 에 따라 사고 심각도와 사고 건수를 종합적으로 고려한 사고 위험도 지표를 개발하는 방법론을 제안하고, 이를 자전거 위험도 분석 및 도로 유형별 맞춤형 안전 대책 마련을 위한 정책적 근거로 제공할 수 있도록 그 기준을 검토하는 것이다. 데이터수집의 경우, 2021 년~2023년 3년간 서울특별시에서 발생한 자전거 교통사고 데이터와 자전거 교통사고가 발생하는 지점의 도로 유형, 경사, 노면상태 등 자전거 도로 인프라 자체적 특성과 자전거 사고 발생 시 기상상황 등 환경적 특성이 포함된 자전거 사고 발생 도로환경요인 데이터를 확보하였다 분석방법론의 경우, 자전거 교통사고에 영향을 미치는 다양한 요인들을 계층적으로 고려하기 위한 방법론인 Hierarchical Modeling을 적용하였으며, 3개의 계층으로 구성된 프레임워크를 구축하여 사고 심각도, 자전거 도로 유형별 사고 심각도를 반영한 공 간 위험도, 종합적 사고 위험도 점수를 체계적으로 도출하였다. Level 1에서는 사고 데이터를 기반으로 사고 심각도를 정량화하고, 도 로 유형에 따른 가중치를 적용하여 사고 심각도를 평가하였다. Level 2에서는 MCAR(Model for Conditional Autoregressive Effects) 모델 을 활용하여 시공간적 상관성을 반영하고, 이를 바탕으로 도로 유형별 사고 심각도를 조정하였다. Level 3에서는 Level 2에서 도출된 도로 유형별 사고 심각도 점수에 사고 발생 빈도를 반영하여 최종적인 종합 사고 위험도 점수를 산출하고, 안전 정책 적용이 시급한 지점을 도출하였다. 향후에는 머신러닝 기반의 예측 모델을 활용하여 도출된 종합적 사고 위험도 점수와 비교 분석할 예정이다.

Wireless sensor systems are primarily used for monitoring natural environments or industrial automation. The physical environment where these systems are installed is often unstable, making it difficult to replenish sensor energy immediately. Complex and harsh conditions can impact the network's structure, affecting monitoring performance. Wireless sensor systems consist of hundreds of sensors that collect data from hazardous environments and transmit information to a central system. However, due to the system's physical structure, information delays or losses may occur. This paper proposes a distance-based tree structure to address these issues in wireless sensor systems, and experimental results confirm its superior performance.

This paper reports the results of an experimental examination using X-rays to test annealing materials for lapped bearing steel (STB2), to confirm the validity of the weighted averaging analysis method. The distribution behavior for the sin diagram and the presence or absence of differences in the peak method, half-value breadth method, and centroid method were investigated. When lapping the annealed bearing steel (STB2) material, a residual stress state with a non-directional steep gradient appeared in the surface layer, and it was found that the weighted averaging analysis method was effective. If there is a steep stress gradient, the sin diagram is curved and the diffraction intensity distribution curve becomes asymmetric, resulting in a difference between the peak method, half-value breadth method, and centroid method. This phenomenon was evident when the stress gradient was more than 2~3 kg/mm2/μm. In this case, if the position of the diffraction line is determined using the centroid method and the weighted averaging analysis method is applied, the stress value on the surface and the stress gradient under the surface can be obtained more accurately. When the stress gradient becomes a problem, since the curvature of the sin diagram appears clearly in the region of sin > 0.5, it is necessary to increase the inclination angle  as much as possible. In the case of a lapping layer, a more accurate value can be obtained by considering  in the weighted averaging analysis method. In an isotropic biaxial residual stress state, the presence or absence of  can be determined as the presence or absence of strain for sin≈0.4.

We propose a method for developing an in-pipe inspection robot based on multiple inertial sensors. Estimating the position of underground pipelines where satellite signals do not reach remains challenging. High-precision inertial sensors and high-tech mobile robots can be solutions, but their high price limits their general use. We developed an in-pipe inspection robot by combining various low-cost sensors with a microcomputer-based RC car platform. First, we fabricated a multi-inertial sensors module by combining commercial grade low-cost MEMS inertial sensors. The sensor values measured by the multi-inertial sensor are transmitted to the main computer through the MCU, and the attitude angle of the vehicle is finally calculated through the inverse variance weighted average. The travel distance of the robot is estimated by using hall sensors and neodymium magnets attached to the inside of the wheels. Also, we measured the pipe diameter using multiple ultrasonic sensors. We verified the estimation accuracy of each sensor through experiments and consequently estimated the 3D trajectory of the in-pipe robot.

This study attempts a comparison between AHP(Analytic Hierarchy Process) in which the importance weight is structured by individual subjective values and regression model with importance weight based on statistical theory in determining the importance weight of casual model. The casual model is designed by for students’ satisfaction with university, and SERVQUAL modeling methodology is applied to derive factors affecting students’ satisfaction with university. By comparison of importance weights for regression model and AHP, the following characteristics are observed. 1) the lower the degree of satisfaction of the factor, the higher the importance weight of AHP, 2) the importance weight of AHP has tendency to decrease as the standard deviation(or p-value) increases. degree of decreases. the second sampling is conducted to double-check the above observations. This study empirically checks that the importance weight of AHP has a relationship with the mean and standard deviation(or p-value) of independence variables, but can not reveal how exactly the relationship is. Further research is needed to clarify the relationship with long-term perspective.

The ballasted flocculation effects of the mill scale and magnetite on activated sludge were investigated. Both ballasted flocculants (BF) could remarkably improve the sludge settleability in terms of zone settling velocity (ZSV) and sludge volume index (SVI). With the BF dosage of 0.2 to 2.0 g-BF/g-SS, the magnetite particles showed better efficiency on improving settling behavior of activated sludge than the mill scale due to higher surface area and hydrophobic property. The efficiency of SVI30 with magnetite injection was 2.5 to 11.3% higher than mill scale injection and that of the ZSV appreciated from 23.7% to 44.4% for magnetite injection. Averaged floc size of the BF sludge with magnetite dosage (0.5 g-BF/g-SS) was 2.3 times higher than that of the control sludge. Dewaterability of the sludge was also greatly improved by addition of the BF. The specific resistance to filtration (SRF) was reduced exponentially with increasing the dosage of BF. However, the BF’s particle size effect on the SRF looks to be marginal. Consequently, for improving the dewaterability, the BF played a physical role to remove the pore water of the biological flocs by intrusive attachment and a chemical role to induce aggregation of the flocs by charge neutralization.

Deep learning, which has recently shown excellent performance, has a problem that the amount of computation and required memory are large. Model compression is very useful because it saves memory and reduces storage size while maintaining model performance. Model compression methods reduce the number of edges by pruning weights that are deemed unnecessary in the calculation. Existing weight pruning methods using ADMM construct an optimization problem by a layer-by-layer addition of pre-defined removal-ratio constraints. Decomposing into two subproblems through the ADMM process, one can solve them through gradient descent and projection. However, the layer-by-layer removal ratios must be structurally specified, causing a sharp increase in training time due to a large number of parameters, and hardly feasible to use for large models that actually require weight pruning. Our proposed method performs weight pruning, producing similar performance, by setting a global removal ratio for the entire model without prior knowledge of structural characteristics in order to solve the shortcomings of the existing ADMM weight-pruning methods. To effectively avoid performance degradation, the method removes a relatively small number of previous layers in charge of feature extraction. Experiments show high-quality performance, not necessarily setting layer-by-layer removal ratios. Additionally, experiments increasing layers yield an insight for feature extraction in pruned layers. The experiment of the proposed method to the LeNet-5 model using MNIST data results in a higher compression ratio of 99.3% outperforming those of other existing algorithms. We also demonstrate the effectiveness of the proposed method in YOLOv4, an object detection model requiring substantial computation.

The effects of activated carbon originated Ballasted Flocculant (BF) on the settleability of activated sludge and the recovery of BF by Hydro-cyclone (HC) were analyzed experimentally. Two kinds of BF (M-I: 125-250 μm, M-II: 250-425 μm in dia.) and three kinds of activated sludges with different SS concentration (2,300-7,100 mg/L) were applied for this study. With the dosage variation of BF from 0.14 to 1.3 g-BF/g-SS, we could obtain 24-31% improvement in SV30 (Sludge Volume after 30min sedimentation) for the lowest SS concentration sludge (2,300 mg/L). Whereas the SV30 improvement was much higher as 44-48% for the highest SS concentration sludge (7,100 mg/L). The settling characteristics of the sludge with BF followed Vesilind model the best among three models (Vesilind, Takacs and Cho model). HC could effectively separate BF with the separation efficiency of 70-90% and over 95% separation efficiency could be obtained when the HC was applied twice.

The 37 indicators for performance evaluation of public sewage management agencies are divided into four major categories (agency manpower management ability, wastewater treatment plant operation and management, sludge and water reuse, service quality) in the first stage, and the necessity and score acquisition for the detailed indicators by each major category in the second stages. Priority was investigated through the Analytic Hierarchy Process (AHP) analysis technique for ease and relevance of company efforts. Also, based on the results of this analysis, integrated type weighting and relative importance were analyzed. As a result of the analysis, the weight and relative importance of the first stage classification were in the order of wastewater treatment plant operation and maintenance, operation agency manpower management ability, sludge and water reuse, and service quality. As a result of analyzing the weights and priorities of the detailed performance indicators in the second stage, it was found that operator’s career years, the percentage of certification holding rate in operators, compliance with the effluent water quality standards, training times for operators, and efforts to manage hazardous chemicals were important. Some of the indicators of operation agency performance evaluation may include indicators in which the performance of the company's efforts is underestimated or overestimated. In order to improve this, it is necessary to give weights in consideration of the necessity of the indicator, the relevance of the company's efforts, and the ease of obtaining scores.

본 연구는 태백산국립공원 백두대간 생태축 연결을 위한 평가항목 및 요인별 가중치 설정을 위해 공원관리와 생태계 조사, 생태환경계획과 관련된 분야별 전문가 대상의 설문조사를 토대로 계층화 분석을 실시하였다. 문헌연구와 담당자 면담조사로 생태축 연결을 위한 상위 평가지표 4개와 하위 평가지표 13개를 선정하였으며, 일관성 분석에 의한 유효 설문을 대상으로 항목별 가중치를 산정하였다. 분석결과, 상위평가 지표에서는 생태계 가치증진이 0.474로 가장 높고, 자연-인간 갈등완화(0.247), 지역주민의 참여(0.165), 경제적 측면(0.114) 순으로 나타났으며, 하위 평가지표에서는 생물이동경로(0.116), 경관생태적 패치 연결성(0.112), 기능적 서식지(0.099) 등이 중요 항목으로 추출되었다. 분야별 평가항목과 가중치 비교에 따르면 생태계조사 분야에서는 생물종 이동경로(0.116)을 가장 중시하는 반면, 공원관리 분야에서는 기능적 서식지가 0.110로 가장 중요한 항목으로 평가되었으며, 생태환경계획 분야에서는 지역의 보전 및 이용자원 분포현황이 0.123으로 가장 높게 나타났다. 본 연구결과는 태백산국립공원 일대의 생태축 연결에 필요한 조사항목의 선정이나 분야별 연결성 분석방향 설정에 기여할 것이다.

최근 미세먼지 농도가 높은 날이 늘면서 국민들의 관심도 증가하고 있다. 미세먼지의 분포는 공간적으로 상이하며 그 발생도 지역별로 다르게 기인하는데도 불구하고 미세먼지 저감을 위한 정책은 차별성 없이 이루어지고 있기 때문에 미세먼지의 공간적 이질성을 반영한 연구가 필요하다. 본 연구에서는 미세먼지 농도에 영향을 미치는 자연요소와 인문요소를 함께 고려하여 요인을 선정 후 OLS, GWR, GWRR기법을 이용하여 미세먼지 분포의 공간 패턴을 분석하였다. 연구결과는 다음과 같다. 첫째, OLS 분석 결과 자연요인의 경우 강수량과 대기정체일이 적을수록 그리고 주변고도가 낮을수록 미세먼지의 높은 농도의 기여율이 높았으며, 축사나 공업시설과 같은 인문요인의 경우 대부분 미세먼지와 양의 관계가 있음이 파악되었다. 둘째, GWRR 분석 결과 각 하위 지역별로 미세먼지의 분포에 영향을 주는 변수나 그 정도는 다르게 나타났다. 셋째, GWRR의 효용성 평가 결과 GWRR이 다른 두 모델에 비해 향상된 결과를 보였으며, 이는 미세먼지 뿐만 아니라 다양한 대기오염물질의 분석에도 적용이 가능함을 확인하였다.

Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston’s method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecasting because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston’s method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands’ interval separately, as in Croston’s method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.

베어링은 많은 회전체에서 사용되는 핵심부품으로, 예기치 않은 고장을 방지하기 위해 많은 연구가 집중되고 있다. 이때 중요한 것은 되도록 초기에 건전성 상태를 잘 나타내는 적절한 특징신호를 추출하는 것이다. 그러나 기존의 연구들은 주로 진단관점에서 특징신호를 추출하여 고장예지에는 적합하지 않은 측면이 있었다. 본 논문에서는 이러한 문제를 극복하기 위 해 베어링 고장 주파수의 에너지와 시간 사이의 상관계수 가중 합을 이용하여 베어링 수명 예측에 용이한 특징신호를 추출 하는 방법을 개발하였다. 그 결과 일반적으로 고장진단에서 많이 사용되고 있는 특징신호인 RMS에 비해서 결함 초기부터 단조로운 증가 경향의 특징신호를 추출함을 알 수 있었다. 이를 입증하기 위해서 NASA Ames에서 제공한 IMS bearing 진 동 데이터를 이용하였고 제시한 특징신호와 일반적인 RMS와 의 거동을 비교하여 유효성을 검증하였다.

PURPOSES: The purpose of this study is to analyze the characteristics of the weight values of evaluation items by traffic safety project type. METHODS: In general, a large-scale investment in projects such as the traffic safety project requires economic analyses to be performed in advance. However, there is an argument for considering special characteristics of the traffic safety project. Therefore, this study conducted characteristic analysis of the weight values of evaluation items. The analysis consisted of two steps. The first step was hypothesis verification using analysis of variance (ANOVA). In this process, the authors examined whether the weight of evaluation items is the same regardless of the traffic safety project type. Based on the first step's results, the authors proceeded to the second step. The objective of this step was to analyze how different the weight values are by traffic safety project type using an analytic hierarchy process. RESULTS: According to the ANOVA test results, the benefit to cost ratios have different weight values based on traffic safety project type at the 0.01 significance level. The policy evaluation items, such as the plans connection, resident opinion, and regional equity, also showed the same results except that the result for the related plans connection was statistically significant at the 0.05 level. Based on the first step's result, the AHP analysis in the second step showed that the traffic safety projects for vulnerable users and pedestrians have very low weight values in economic evaluation factors compared with other safety project types. The weight values for vulnerable users and pedestrians were 0.29 and 0.26, respectively, in economic evaluation items. On the other hand, the weight values for other safety project types were around 0.6. Among the policy evaluation items, resident opinion showed a higher weight value than other factors, such as connection and regional equity items. CONCLUSIONS: The social and economic impact of a traffic safety project varies by project type and project characteristics. Although the economic approach is overarching and a reasonable methodology is applied for large-scale projects, it should be noted that the safety issue, especially for transportation of vulnerable uses, requires a non-economical approach. Based on the analysis results, this study suggests that the priority of the projects should be determined by separating them into independent assessment groups depending on their characteristics.

This study aims to suggest the methodology to improve to estimate back-calculated fish growth parameters using weighted average. It is to contribute to correct errors in the calculation of back-calculated growth equation with unequal numbers of sample by age. If the numbers of sample were evenly collected by age, each back-calculated length at age was equal between arithmetic and weighted averages. However, most samples cannot be evenly collected by age in reality because of different catchability by fishing gear and limitation of environment condition. Therefore, the estimation of back-calculated length by weighted average method is essential to calculate growth parameters. There were some published growth equations from back-calculated length using a simple arithmetic average with different numbers of samples by age when searching for back-calculated growth equations from 91 relevant papers. In this study, the process of deriving growth equation was investigated and two different average calculations were applied to a fish growth equation, for example of Acheilognathus signifer. Growth parameters, such as L∞, k and t0, were estimated from two different back-calculated averages and the growth equations were compared with growth performance index. Based on the correction of back-calculated length using weighted average by age, the changes by female and male were -14.19% and -5.23% for L∞, and 59.28% and 18.91% for k, respectively. The corrected growth performance index by weighted average improved at 7.05% and 2.46% by female and male, respectively, compared to the arithmetic averages.

PURPOSES: This study aims to develop a rational procedure for estimating the pavement roughness index considering vehicle wandering. METHODS: The location analysis of the passing vehicle in the lane was performed by approximately 1.2 million vehicles for verification of the wandering distribution. According to verification result, the distribution follows the normal distribution pattern. The probability density function was estimated using each lane's wandering distribution model. Then the procedure for applying a weighted value into the lane profile was conducted using this function. RESULTS : The modified index, MRIw, with consideration towards applying the wandering weighted value application was computed then compared with MRI. It was found that the Coefficient of Variation for distribution of lateral roughness index in the lane was high in the case of a large difference between each index (i.e., MRIw and MRI) observed. CONCLUSIONS : This result confirms that the new procedure with consideration of the weight factor can successfully improve the lane representative characteristics of the roughness index.