Assessment of Occupational Radiation Exposure for Radiotherapy Healthcare Workers at Kenyatta National Hospital Using Thermoluminescence Dosimeter LiF:Mg,Ti

Kenyatta National Hospital (KNH) is the largest public referral hospital with a comprehensive cancer treatment facility in East and Central Africa. Occupational radiation monitoring is a significant technique for demonstrating compliance of radiation regulatory limits. The objective of the study was to carry out assessment of occupational radiation exposure among radiotherapy personnel at KNH using thermoluminescence dosimeter, TLD. KNH staff were monitored using dosimeter type TLD-100 made of LiF:Mg,Ti, on monthly basis. The reader system used for analysis was Harshaw 8800. The measurement established the average monthly accumulated occupational personnel dose for KNH to be 0.21 mSv and 0.29 mSv for Hp (10) and Hp (0.07) respectively. The accumulated dose results were within the maximum acceptable dose of 1.67 mSv/month and 41.6 mSv/month for Hp (10) and Hp (0.07) respectively. The investigation results were higher than the acceptable public limit of 0.08 mSv/month. Moreover, incidences were noted where the fetus dose limit 0.42 was also exceeded. Evaluation of statistical dose exposure among doctors, nurses and radiographers’ measurement results were within ±0.02 mSv. The study established the average KNH occupational radiation exposure levels for both Hp (10) and Hp (0.07) were within the ICRU recommendation, validating radiation protection safe practice. Data analysis of healthcare workers did not indicate exposure trend biased to any healthcare profession. Hence radiation risk cut across all professional categories. It is recommended that Radiation Monitoring program be reviewed to include non-clinical staff who access the facility. Radiation reporting should not be limited to one facility, but reflect cases where workers are involved in multiple multiple jobs.

Review on occupancy detection and prediction in building simulation

Energy simulation results for buildings have significantly deviated from actual consumption because of the uncertainty and randomness of occupant behavior.Such differences are mainly caused by the inaccurate estimation of occupancy in buildings.Therefore,the error between reality and prediction could be largely reduced by improving the accuracy level of occupancy prediction.Although various studies on occupancy have been conducted,there are still many differences in the approaches to detection,prediction,and validation.Reports published within this domain are reviewed in this article to discover the advantages and limitations of previous studies,and gaps in the research are identified for future investigation.Six methods of monitoring and their combinations are analyzed to provide effective guidance in choosing and applying a method.The advantages of deterministic schedules,stochastic schedules,and machine-learning methods for occupancy prediction are summarized and discussed to improve prediction accuracy in future work.Moreover,three applications of occupancy models—improving building simulation software,facilitating building operation control,and managing building energy use—are examined.This review provides theoretical guidance for building design and makes contributions to building energy conservation and thermal comfort through the implementation of intelligent control strategies based on occupancy monitoring and prediction.