This study proposes a dynamic evaluation framework for diagnosing signal control adequacy using high-resolution Automated Traffic Signal Performance Measures (ATSPM) data. Traditional signal performance assessments have primarily relied on aggregated metrics, such as average delay and volume-to-capacity ratio, which are effective for evaluating overall operational efficiency but insufficient for capturing cycle-level control limitations and temporal variability. Although split failure-based measures, including the Split Failure Ratio (SFR), provide more direct insights into green time adequacy, most existing applications focus on the failure frequency within a fixed analysis period. To address this limitation, this study introduces a Dynamic Operational Strain (DOS) index that extends the split failure into a time-evolving state variable incorporating accumulation and recovery mechanisms. By modeling the recursive evolution of the operational strain, the proposed framework captures how often failures occur and how they persist or dissipate over time. Phase-level DOS measures are subsequently aggregated at the intersection level to derive a priority score reflecting structural control inadequacy. The framework is further applied to classify intersections using DOS–SFR quadrant analysis, enabling the identification of distinct operational patterns, such as persistent oversaturation, localized phase imbalance, intermittent strain accumulation, and stable control conditions. The results demonstrate that intersections with similar SFR values may exhibit substantially different temporal strain structures, highlighting the importance of a dynamic state-based evaluation. The proposed approach provides a diagnostic foundation for data-driven signal re-timing and future adaptive control strategies by shifting the signal performance assessment from static frequency-based measures to dynamic structural adequacy analysis.

With the rapid expansion of renewable energy deployment, power systems are increasingly exposed to issues such as higher output variability. Photovoltaic generation, as the most widely installed variable renewable energy source both domestically and internationally, exhibits significant fluctuations due to weather conditions. These characteristics lead to operational challenges including increased curtailment, higher reserve requirements, and even risks of large-scale outages. This study aimed to improve the accuracy of photovoltaic power generation forecasting by developing a data quality control procedure for meteorological data collected at a PV plant. The quality-controlled data were used as inputs to SVM and XGBoost, resulting in improved forecasting accuracy, with MAPE decreasing from 7–10% to 6.32% and 6.08%, respectively. The results demonstrate that meteorological data quality control significantly enhances PV forecasting performance and can contribute to distributed energy resource operation and curtailment mitigation strategies.

As renewable energy penetration continues to increase, the output variability and forecasting uncertainty of photovoltaic generation have emerged as major operational risks in power systems. This study establishes a sensor-based data quality control procedure to ensure the reliability of meteorological data collected at a PV plant. For temperature, humidity, and wind speed, a four stage QC process physical range check, persistence check, step change check, and median filtering was applied. Solar radiation, which exhibits strong temporal and distributional characteristics, was processed using a three-stage QC procedure consisting of physical range, step change, and frequency distribution checks. Using the quality-controlled meteorological data, PV generation forecasting was performed with SVM and XGBoost models. As a result, the MAPE values improved to 6.32% for SVM and 6.08% for XGBoost after QC application. The findings confirm that meteorological data quality control significantly enhances PV forecasting accuracy and can support future strategies for distributed energy resource management, curtailment mitigation, and power system risk reduction.

In the Republic of Korea, public health centers conduct vector mosquito control in accordance with infectious disease prevention laws. However, most public health centers have traditionally conducted periodic, uniform vector control across their respective regions without considering specific information on vector occurrence. In 2021, The Korea Diseases Control and Prevention Agency(KDCA) launched a control project to shift the paradigm toward mosquito control strategy based on mosquito surveillance data. In 2024, 18 local public health centers will participate in this project, which will progressively expanding so that it can be used countrywide. Local public health centers evaluate mosquito monitoring data using data gathered from Daily Mosquito Monitoring System(DMS), which enables them to pinpoint the best times and locations for vector control. Vector control activities carried out by local public health centers are computerized utilizing Vector Control Geographic Information System(VCGIS). Using the new control strategy with mosquito surveillance, the number of mosquito occurrences, number of control activities, and amount of insecticides have decreased compared to the periodic control activities. Based on mosquito surveillance data, it is anticipated that evidence-based mosquito vector control will offer a more efficient and effective means of mosquito control.

Humanities is originally a comprehensive discipline, and all disciplines must be formed under the foundation of humanities. To do so, humanities researchers should break their own castles, return to their original positions based on the humanistic reflection, and try various academic methods. Humanities should no longer be the recipient of the data and the user's role alone. But rather they are expected to play the role of the data curator, the leading role in data production and construction and use of a common platform, and the attempt to use the platform in various ways by the constant re-datafication make all relevant researchers enable collaboration. In addition, it is necessary to have the ability to solve problems through multi-fields, trans-fields, or cross-fields, which can be achieved not only by building basic knowledge in all fields of studies, but also by sharing interest, active participations, and diverse collaborations. We need to have critical and rational perspectives, and inclusive attitudes based on acceptance of differences, and all of these can be supported by our endeavors to solve structural problems.

This study suggested a new real-time traffic signal operation algorithm using combined data of travel time and occupancy rate. This study applied the travel time data to traffic signal control system, and developed the signal operation algorithm based on saturation degree that was calculated using the travel time data. This algorithm calculates a queue length using a delay model, and converts the queue length to the saturation degree. Moreover, it calculates signal timing variables using this combined saturation degree. This study conducted a microscopic simulation for effectiveness evaluation. We checked that the average intersection delay decreased by up to 27 percent. Moreover, we checked that this signal operation algorithm could respond to a traffic condition of oversaturation and loop detector error effectively and usefully. In korea, sectional traffic detection systems are being installed in various ITS projects, such as Advanced Transportation Management System(ATMS) and Urban Transportation Information System(UTIS). This study has important significance in the sense that it is new methodology to accept the sectional detection system in traffic signal control system.

Real-life time series characteristic data has significant amount of non-stationary components, especially periodic components in nature. Extracting such components has required many ad-hoc techniques with external parameters set by users in a case-by-case manner. In this study, we used Empirical Mode Decomposition Method from Hilbert-Huang Transform to extract them in a systematic manner with least number of ad-hoc parameters set by users. After the periodic components are removed, the remaining time-series data can be analyzed with traditional methods such as ARIMA model. Then we suggest a different way of setting control chart limits for characteristic data with periodic components in addition to ARIMA components.

기후 자료를 정확히 분석하고 미래 환경을 예측하기 위해서는 이들 자료에 대한 검증과 품질 관리 과정이 필요하다. 본 연구에서는 우리나라에서 구축한 기후 자료의 품질을 효과적으로 관리하기 위하여, 기후 자료의 시각화 도구를 개발하고, 이를 이용한 품질 관리 방안을 제시하였다. 본 연구에서 개발한 HTML5 기반의 시각화 도구를 이용하여, 인터넷 환경에서 다수의 전문가들이 효과적으로 기후 자료를 관리할 수 있게 되었다. 기후자료의 시각화 도구를 활용하여 기후자료의 품질 관리 업무에 적용한 결과, 다양한 종류의 품질 관리 검사를 효과적으로 수행할 수 있었다. 본 연구의 결과는 향후 기상청의 기후 자료 품질 관리 업무에 활용될 수 있을 것으로 예상된다.

성공적인 국제 Argo 사업을 통해 얻어진 고해상도의 수온 및 염분 프로파일들을 이용하여 준실시간으로 3차원 전지구 해양 상태의 재현이 가능해졌으며, 전지구 해양 자료 분석 연구에 대한 관심 또한 크게 증가하였다. 본 연구에서는 XBT와 Argo 자료의 계통 오차, 열염분 해수면 높이 및 인공위성 관측 자료와의 해수면 수지 불일치, 해양 열용량 변동 및 객관 분석장 개발 현황 등 최근의 자료 분석 연구의 주요 쟁점들에 관해 정리하였다. 특히 동아시아 해역에서의 지역 규모 해양 기후 변화 분석에 앞서 매우 신중한 해양 자료의 품질 관리 및 전구 규모의 해양 변동에 관한 이해가 필요하다는 것을 강조하였다.

This study was performed to investigate the eating habit, body image, and weight control behavior by BMI in Korean female high school students. Data on the 16, 574 subjects was obtained from the sixth Korea Youth Risk Behavior Web-based Survey (2010). Only 52.2% of the subjects had regular breakfast. The rate of skipping breakfast was higher in the underweight group than in the obese group, but the rate of skipping dinner was on the contrary to this. Underweight students had a higher intake frequency of fruits, fast food, instant noodle, and snacks than the obese groups. 3.5% of underweight students considered themselves to be overweight or obese. 53.4% of obese students considered themselves to be overweight. The experience of weight control increased according to BMI, but underweight students considered weight control as an effort to be slimmer. Meal restriction was used more frequently to control weight. The perceived stress level was higher in obese student, especially due to appearance. Therefore, an appropriate, integrated and personalized high school nutrition program should be established for proper body image perception and to develop the self-esteem of female high school students.

Monitoring autocorrelated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment throug

The study investigates the various Acceptance Control Charts (ACCs) based on the factors that include process independence, data weighting scheme, subgrouping, and use of control charts. USL - LSL 〉 6Σ that used in the good condition processes in the ACCs are designed by considering user's perspective, producer's perspective and both perspectives. ACCs developed from the research is efficiently applied by using the simple control limit unified with APL (Acceptable Process Level), RLP (Rejectable Process Level), Type I Error α, and Type II Error β. Sampling interval of subgroup examines i.i.d. (Identically and Independent Distributed) or auto-correlated processes. Three types of weight schemes according to the reliability of data include Shewhart, Moving Average(MA) and Exponentially Weighted Moving Average (EWMA) which are considered when designing ACCs. Two types of control charts by the purpose of improvement are also presented. Overall, α, β and APL for nonconforming proportion and RPL of claim proportion can be designed by practioners who emphasize productivity and claim defense cost.

The paper reviews the methodologies of confirmatory data analysis(CDA) and exploratory data analysis(EDA) in statistical quality control(SQC), design of experiment(DOE) and reliability engineering(RE). The study discusses the properties of flexibility, openness, resistance and reexpression for EDA.

Models are useful tools for understanding and improving biological control of arthropod pests by means of natural enemies. Thus, models can be applied to simulate various scenarios in order to identify optimal control strategies. Although simulations can never replace real experiments, they can often serve as guidelines for choosing relevant field experiments and thereby save a lot of laborious and costly field work. Whereas the processes underlying population dynamics (e.g. dispersal, functional response, mutual interference) can be studied under laboratory conditions, large-scaled experiments in the field or in greenhouses are unsuited for this purpose. Instead such experiments may provide information about the patterns (e.g. spatial distributions of prey and predators) generated by the underlying processes. A major purpose of modeling is to link the patterns to the processes that generate these patterns. Petri-dish and single plant experiments have clearly demonstrated the capacity of predacious mite Phytoseiulus persimilis to feed effectively on the two-spotted spider mite Tetranychus urticae. This quickly leads to reductions in the abundance of prey, followed by a decline in predator abundance and eventual extinction. However, when larger systems, consisting of many hundred plants, are infested with the two mite species, extinction of one or both species seems less likely at the system level, although it may still occur at the individual plant level. The qualitative difference between small and large systems with respect to persistence and extinction risks is attributed to the fact that mites move among plants, but to prove that dispersal per se plays a role for the overall dynamics is hard to demonstrate experimentally. To circumvent this problem, I developed a stochastic simulation model of a greenhouse system that explicitly incorporates within and between plant dynamics. The model is used for analyzing a series of experiments with biological control of spider mites in multi-plant systems. In these experiments, the number of plants as well as their connectivity and the numbers of introduced mites were varied in order to examine whether these factors affect e.g. the predator-prey ratio or the time to extinction of one or both species. In my presentation I will also demonstrate an interactive version of the model (called DynaMite). It allows the user to interfere in the system during a simulation so as to mimic the options a grower has in order to prevent losses and to maximize his profit. Such options include spraying with acaricides, releasing predators, and replanting in substitute of damaged plants. By choosing different control strategies, the user may gradually improve his skills according to the principle of learning by experience. The model can be freely downloaded from http://www1.bio.ku.dk/ansatte/beskrivelse/?id=43077

In this paper we present a newly improved telescope control software and a newly developed data analysis software package for effective use of the Solar Flare Telescope(SOFT) The telescope control software permits us to make not only auto tacking of the SOFT, but also quantitative measurement of the solar irradiation, allowing us to provide weather monitorings. In addition we introduce an IDL widget software package for both monochromatioc (MONO version) and polarimetric data (VMG version) analysis. The MONO version is capable of loading FITS files, changing colors and contrast, image processing, displaying plots, and saving displayed plots by selected formats The VMG version, on the other hand provides a calibration of polarimetric data and plots of reduced vector magnetic fields.

Regional air quality regulation is a system that allows the Minister of Environment to designate the local area as air quality control region where the concentrations of air pollutants are exceeding the environmental standards, and the local governments that administrate the regulated area have to develop and practise a plan for reducing the air pollutants. From the data observed yearly by the monitoring stations in 8 provincial cities with more than 0.5 million people was judged the compliance with air quality standards in each municipality for the period of 2003 to 2013. As the result of investigation on air pollutants concentrations of each city, it was found that there was no station that exceeds the ambient air quality standards of CO, SO2 and 24-hour NO2. But all municipalities exceeded the standards of 8-hour O3, annual and 24-hour PM10, and therefore 8 municipalities can be designated to be under the local air regulation. For the annual NO2 were the monitoring sites necessary requirements for designation of the air quality regulation region in Cheongju, Cheonan, Daejeon and Gwangju area. Incase of 1-hour O3, some of stations in Pohang, Cheongju, Cheonan and Changwon area were over the designation standards for the air quality control region.