ALBERT

Description: Radiation safety is an integral part of targeted radionuclide therapy. The aim of this work was to study the external dose rate and retained body activity as functions of time in differentiated thyroid carcinoma patients receiving 131I therapy. Seventy patients were stratified into two groups: the ablation group (A) and the follow-up group (FU). The patients’ external dose rate was measured, and simultaneously, their retained body radiation activity was monitored at various time points. The equations of the external dose rate and the retained body activity, described as a function of hours post administration, were fitted. Additionally, the release time for patients was calculated. The reduction in activity in the group receiving a second or subsequent treatment was more rapid than the group receiving only the initial treatment. Most important, an expeditious method was established to indirectly evaluate the retained body activity of patients by measuring the external dose rate with a portable radiation survey meter. By this method, the calculated external dose rate limits are 19.2, 8.85, 5.08 and 2.32 μSv·h−1 at 1, 1.5, 2 and 3 m, respectively, according to a patient’s released threshold level of retained body activity 〈400 MBq. This study is beneficial for radiation safety decision-making.

Description: Sensors, Vol. 18, Pages 3095: Optimization-Based Wi-Fi Radio Map Construction for Indoor Positioning Using Only Smart Phones Sensors doi: 10.3390/s18093095 Authors: Jian Tan Xiangtao Fan Shenghua Wang Yingchao Ren Fingerprinting-based Wi-Fi indoor positioning has great potential for positioning in GPS-denied areas. However, establishing a fingerprinting map (also called a radio map) prior to positioning (site survey) is normally a labor-intensive task. This paper proposes a method for easy site survey without need for any extra hardware. The user can conduct the site survey adopting only a smart phone. The collected inertial-based readings are processed using the pedestrian dead-reckoning algorithms to generate a raw trajectory. Then a factor graph optimization method is proposed to re-estimate the trajectory by adding constraints originated from collected Wi-Fi fingerprints and landmark positions. The proposed method is verified through an experiment in a mall. The mean positioning error is 1.10 m and the maximum error is 2.25 m. This level of positioning accuracy is considered sufficient for radio map generation purposes. A classical baseline algorithm, the k-Nearest Neighbor (kNN) algorithm, is adopted to test the positioning performance of the radio map (RM), which also validates the quality of the constructed RM from the proposed method.

Description: Sensors, Vol. 18, Pages 3019: Target Recognition of SAR Images via Matching Attributed Scattering Centers with Binary Target Region Sensors doi: 10.3390/s18093019 Authors: Jian Tan Xiangtao Fan Shenghua Wang Yingchao Ren A target recognition method of synthetic aperture radar (SAR) images is proposed via matching attributed scattering centers (ASCs) to binary target regions. The ASCs extracted from the test image are predicted as binary regions. In detail, each ASC is first transformed to the image domain based on the ASC model. Afterwards, the resulting image is converted to a binary region segmented by a global threshold. All the predicted binary regions of individual ASCs from the test sample are mapped to the binary target regions of the corresponding templates. Then, the matched regions are evaluated by three scores which are combined as a similarity measure via the score-level fusion. In the classification stage, the target label of the test sample is determined according to the fused similarities. The proposed region matching method avoids the conventional ASC matching problem, which involves the assignment of ASC sets. In addition, the predicted regions are more robust than the point features. The Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset is used for performance evaluation in the experiments. According to the experimental results, the method in this study outperforms some traditional methods reported in the literature under several different operating conditions. Under the standard operating condition (SOC), the proposed method achieves very good performance, with an average recognition rate of 98.34%, which is higher than the traditional methods. Moreover, the robustness of the proposed method is also superior to the traditional methods under different extended operating conditions (EOCs), including configuration variants, large depression angle variation, noise contamination, and partial occlusion.