Determining Adaptability Performance of Artificial Neural Network-Based Thermal Control Logics for Envelope Conditions in Residential Buildings

This is the publisher's version, also available electronically from http://www.mdpi.com/1996-1073/6/7/3548This study examines the performance and adaptability of Artificial Neural Network (ANN)-based thermal control strategies for diverse thermal properties of building envelope conditions applied to residential buildings. The thermal performance using two non-ANN-based control logics and two predictive ANN-based control logics was numerically tested using simulation software after validation. The performance tests were conducted for a two-story single-family house for various envelope insulation levels and window-to-wall ratios on the envelopes. The percentages of the period within the targeted ranges for air temperature, humidity and PMV, and the magnitudes of the overshoots and undershoots outside of the targeted comfort range were analyzed for each control logic scheme. The results revealed that the two predictive control logics that employed thermal predictions of the ANN models achieved longer periods of thermal comfort than the non-ANN-based models in terms of the comfort periods and the reductions of the magnitudes of the overshoots and undershoots. The ANN-based models proved their adaptability through accurate control of the thermal conditions in buildings with various architectural variables. The ANN-based predictive control methods demonstrated their potential to create more comfortable thermal conditions in single-family homes compared to non-ANN based control logics

Association between use of hydrochlorothiazide and nonmelanoma skin cancer: Common data model cohort study in Asian population

Although hydrochlorothiazide (HCTZ) has been suggested to increase skin cancer risk in white Westerners, there is scant evidence for the same in Asians. We analyzed the association between the use of hydrochlorothiazide and non-melanoma in the Asian population using the common data model. METHODS: A retrospective multicenter observational study was conducted using a distributed research network to analyze the effect of HCTZ on skin cancer from 2004 to 2018. We performed Cox regression to evaluate the effects by comparing the use of HCTZ with other antihypertensive drugs. All analyses were re-evaluated using matched data using the propensity score matching (PSM). Then, the overall effects were evaluated by combining results with the meta-analysis. RESULTS: Positive associations were observed in the use of HCTZ with high cumulative dose for non-melanoma skin cancer (NMSC) in univariate analysis prior to the use of PSM. Some negative associations were observed in the use of low and medium cumulative doses. CONCLUSION: Although many findings in our study were inconclusive, there was a non-significant association of a dose-response pattern with estimates increasing in cumulative dose of HCTZ. In particular, a trend with a non-significant positive association was observed with the high cumulative dose of HCTZ

Analysis of Occupants’ Visual Perception to Refine Indoor Lighting Environment for Office Tasks

The combined effects of color temperature and illuminance in a small office on visual response and mood under various lighting conditions were examined in this study. Visual annoyance tests were conducted using a sample of 20 subjects in a full-scale mock-up test space. Computer and paper-based reading tasks were conducted for 500 lx and 750 lx illuminance levels under 3,000 K, 4,000 K and 6,500 K conditions. Two hypotheses were considered for the test in this study. The primary hypothesis was that visual perception is affected by the color temperatures of light sources. The secondary hypothesis was that better moods, such as relaxed and cozy feelings, are associated with low color temperatures given equal illuminance levels. The visual environment under the 3,000 K condition was characterized by glare and brightness, resulting in visual discomfort when target illuminance was higher than 500 lx. Occupants preferred 500 lx under the 6,500 K condition, and 500 lx and 750 lx under the 4,000 K condition, reporting better visual satisfaction when performing office tasks. Prediction models for visual comfort suggest that the less that subjects are visually bothered by light during tasks, the more visual comfort they feel. User satisfaction with light source color is critical for the prediction of visual comfort under different lighting conditions. Visual comfort was the most influential factor on mood. Lower color temperature was associated with better mood at lower illuminance levels, while higher color temperature was preferred at higher illuminance levels

Optimum Application of Thermal Factors to Artificial Neural Network Models for Improvement of Control Performance in Double Skin-Enveloped Buildings

This study proposes an artificial neural network (ANN)-based thermal control method for buildings with double skin envelopes that has rational relationships between the ANN model input and output. The relationship between the indoor air temperature and surrounding environmental factors was investigated based on field measurement data from an actual building. The results imply that the indoor temperature was not significantly influenced by vertical solar irradiance, but by the outdoor and cavity temperature. Accordingly, a new ANN model developed in this study excluded solar irradiance as an input variable for predicting the future indoor temperature. The structure and learning method of this new ANN model was optimized, followed by the performance tests of a variety of internal and external envelope opening strategies for the heating and cooling seasons. The performance tests revealed that the optimized ANN-based logic yielded better temperature conditions than the non-ANN based logic. This ANN-based logic increased overall comfortable periods and decreased the frequency of overshoots and undershoots out of the thermal comfort range. The ANN model proved that it has the potential to be successfully applied in the temperature control logic for double skin-enveloped buildings. The ANN model, which was proposed in this study, effectively predicted future indoor temperatures for the diverse opening strategies. The ANN-based logic optimally determined the operation of heating and cooling systems as well as opening conditions for the double skin envelopes

Data mining for detecting signals of adverse drug reaction of doxycycline using the Korea adverse event reporting system database

Background Doxycycline is one of the most prescribed antibiotics by dermatologists. However, the concern regarding adverse events of doxycyline has been rising. Objective To detect the adverse events of doxycycline using the Korea Adverse Events Reporting System (KAERS) database from January 2014 to December 2018 through a data mining method. Methods A signal was defined as one satisfying all three indices; a proportional reporting ratio, a reporting odds ratio, and an information component. We further checked whether the detected signals exist in drug labels in Korea and five developed countries, the United States, the United Kingdom, Germany, Canada, and Japan. Results A total of 3,365,186 adverse event-drug pairs were reported and of which 3,075 were associated with doxycycline. Among the thirty-seven signals, nineteen (malaise, ileus, confusion, malignant neoplasm, ectopic pregnancy, ovarian hyperstimulation, vaginal hemorrhage, bone necrosis, acne, rosacea, seborrheic dermatitis, folliculitis, skin ulceration, crusting, dry skin, paronychia, mottled skin, application site reaction, and application site edema) were not included on any of the drug labels of the six countries. Conclusion We identified nineteen new doxycycline signals that did not appear on drug labels in six countries. Further studies are warranted to evaluate the causality of the adverse events with doxycycline

Omega-3 and-6 Fatty Acid Intake and Colorectal Cancer Risk in Swedish Womens Lifestyle and Health Cohort

Purpose We aimed to assess the association between the dietary intake of fish-derived omega-3 polyunsaturated fatty acids and the risk of colorectal cancer among Swedish women. Materials and Methods A total of 48,233 women with information on dietary intake were included in the analysis. Participants were followed for incident colorectal cancer until 31 December 2012. Cox proportional hazard models were used to assess the association between baseline fatty acid intake and colorectal cancer risk. All analyses were stratified by colon and rectal cancers. Results During a median of 21.3 years of follow-up, a total of 344 colorectal cancer cases were ascertained. Although there was no overall association between omega-3 fatty acid intake and colorectal cancer risk, high intake of fish-derived docosahexaenoic acid was associated with reduced risk of rectal cancer (hazard ratios for the third and the highest quartiles were 0.59 (95% confidence interval [CI], 0.37 to 0.96) and 0.62 (95% CI, 0.39 to 0.98), respectively). Conclusion In conclusion, we found only limited support for an association between omega-3 polyunsaturated fatty acids and colorectal cancer in a large Swedish cohort of middle-aged women.Funding Agencies|Korea Research FoundationKorea Research Foundation [2017-R1A2B4009233]</p