会议名称：
12th International Conference on Position Sensitive Detectors
会议时间：
SEP 12-17, 2021
会议地点：
Birmingham, ENGLAND
会议主办单位：
[Pritchard, J. L.;Velthuis, J. J.;Beck, L.;Li, Y.;De Sio, C.;Ballisat, L.;Duan, J.;Shi, Y.;Hugtenburg, R. P.] Univ Bristol, Sch Phys, Bristol BS8 1TL, Avon, England.^[Velthuis, J. J.;Hugtenburg, R. P.] Swansea Univ Med Sch, Dept Med Phys, Swansea SA2 8QA, W Glam, Wales.^[Velthuis, J. J.] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.^[Hugtenburg, R. P.] Swansea Bay Univ Hlth Board, Dept Med Phys & Clin Engn, Swansea SA2 8QA, W Glam, Wales.
关键词：
Radiotherapy concepts;Solid state detectors;X-ray detectors;Image reconstruction in medical imaging
摘要：
A multileaf collimator (MLC) is an integral component in modern radiotherapy machines as it dynamically shapes the photon field used for patient treatment. Currently, the MLC leaves which collimate the treatment field are mechanically calibrated to +/- 1mm every 3 months and during pre-treatment calibration are calibrated to the mechanically set leaf positions. Leaf drift can occur between calibration dates and hence exceed the +/- 1mm tolerance. Pre-treatment verification, increases LINAC usage time so is seldom performed for each individual patient treatment, but instead for an acceptable sample of patients and/or treatment fractions. Independent real-time treatment verification is therefore desirable. We are developing a large area CMOS MAPS upstream of the patient to monitor MLC leaf positions for real-time treatment verification. CMOS MAPS are radiation hard for photon and electron irradiation, have high readout speeds and low attenuation which makes them an ideal upstream radiation detector for radiotherapy. Previously, we reported on leaf position reconstruction for single leaves using the Lassena, a 12 x 14 cm(2), three side buttable MAPS suitable for clinical deployment. Sobel operator based methods were used for edge reconstruction. It was shown that the correspondence between reconstructed and set leaf position was excellent and resolutions ranged between 60.6 +/- 8 and 109 +/- 12 mu m for a single central leaf with leaf extensions ranging from 1 to 35 mm using 0.3 sec of treatment beam time at 400MU/min. Here, we report on leaf edge reconstruction using updated methods for complex leaf configurations, as occur in clinical use. Results show that leaf positions can be reconstructed with resolutions of 62 +/- 6 mu m for single leaves and 86 +/- 16 mu m for adjacent leaves at the isocenter using 0.15 sec at 400 MU/min of treatment beam. These resolutions are significantly better than current calibration standards.
作者：
Yuanchao Chen;Dong Xie;Guojie Chen;Shiliang Dai;Suyao Liu
期刊：
E3S Web of Conferences,2022年356:05030-null ISSN：2267-1242
通讯作者：
Xie, D.
作者机构：
National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, University of South China, Hengyang 421001, China;School of Resource Environment and Safety Engineering, University of South China, Hengyang 421001, China;School of Civil Engineering, University of South China, Hengyang 421001, China;[Xie D.; Dai S.; Liu S.; Chen G.] National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, University of South China, Hengyang, 421001, China, School of Civil Engineering, University of South China, Hengyang, 421001, China;[Chen Y.] National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, University of South China, Hengyang, 421001, China, School of Resource Environment and Safety Engineering, University of South China, Hengyang, 421001, China
通讯机构：
[Xie, D.] N;National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, China
会议名称：
9th International Forum on Electrical Engineering and Automation (IFEEA)
会议时间：
NOV 04-06, 2022
会议地点：
ELECTR NETWORK
会议主办单位：
[Wang, Shoutao;Chen, Wenguang;Liu, Zhijian;Wei, Caiyi;Peng, Yuanyuan] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
关键词：
Printed circuit board;Bidirectional pulse power supply;Forward and reverse pulse duty cycle ratio;Current density;Frequency
摘要：
Printed circuit boards are the most important basic electronic components in the electronics industry, and copper plating technology is widely used in the field of printed circuit board manufacturing. Pulse plating is more efficient and environmentally friendly than DC plating, and the plating layer of pulse plating is more uniform and detailed. The effect of bidirectional pulse power supply parameters on the copper plating effect of printed circuit board surface was investigated by using a self-developed bidirectional pulse power supply. The experimental results show that the frequency, forward and reverse pulse duty cycle and current density of the bidirectional pulse power supply have certain effects on the copper plating effect.
作者机构：
[Xie, Fuqiang; Guo, Lei; Yang, Bin] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
会议名称：
8th International Conference on Hydraulic and Civil Engineering - Deep Space Intelligent Development and Utilization Forum (ICHCE)
会议时间：
NOV 25-27, 2022
会议地点：
Xian, PEOPLES R CHINA
会议主办单位：
[Guo, Lei;Xie, Fuqiang;Yang, Bin] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
关键词：
component;Deep learning;Lane detection;non-local attention;frame-similarity loss
摘要：
Lane detection plays an important role in autonomous driving. For video instance lane detection, both global spatial and temporal information is significantly important. However, the global spatial features and the temporal features are not been well exploited in recent studies. In this work, we address the video instance lane detection task by capturing global context based on non-local attention network. Specifically, we designed a twin non-local attention network to extract long-range dependencies along the spatial and temporal dimensions, respectively. Meanwhile, the global spatial and temporal features can be adaptively fused by gating mechanisms for better results. In addition, the frame-similarity loss is proposed to further exploit the information of adjacent frames. The experimental results on the video instance lane detection (VIL-100) dataset verify that our method achieves better results compared with other comparison methods. Ablation experiments further demonstrate the effectiveness of each sub-module.
作者机构：
[Dhelim, Sahraoui; Dhelim, S; Aung, Nyothiri; Kechadi, Tahar] Univ Coll Dublin, Dublin, Ireland.;[Zhu, Tao] Univ South China, Henyang, Peoples R China.;[Zerdoumi, Saber] United Nation Int Solar Energy Technol Transferri, Henyang, Peoples R China.;[Guerbouz, Tahar] Univ Ouargla, Ouargla, Algeria.
会议名称：
IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)
会议时间：
NOV 11-13, 2022
会议地点：
Beijing, PEOPLES R CHINA
会议主办单位：
[Aung, Nyothiri;Kechadi, Tahar;Dhelim, Sahraoui] Univ Coll Dublin, Dublin, Ireland.^[Zhu, Tao] Univ South China, Henyang, Peoples R China.^[Zerdoumi, Saber] United Nation Int Solar Energy Technol Transferri, Henyang, Peoples R China.^[Guerbouz, Tahar] Univ Ouargla, Ouargla, Algeria.
关键词：
blockchain;IoV;VANET;trust;security;privacy
摘要：
With the rapid development of the Internet of Things (IoT) and its potential integration with the traditional Vehicular Ad-Hoc Networks (VANETs), we have witnessed the emergence of the Internet of Vehicles (IoV), which promises to seamlessly integrate into smart transportation systems. However, the key characteristics of IoV, such as high-speed mobility and frequent disconnections make it difficult to manage its security and privacy. The Blockchain, as a distributed tamper-resistant ledge, has been proposed as an innovative solution that guarantees privacy-preserving yet secure schemes. In this paper, we review recent literature on the application of blockchain to IoV, in particular, and intelligent transportation systems in general.
作者机构：
[Zhang, XZ; Zhang, Xiaozhi; Zhou, Liu] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.;[Zhu, Minjie; Ouyang, Lijun; Ouyang, Yan; Xiong, Dongping; Ouyang, LJ] Univ South China, Sch Comp Software, Hengyang 421001, Peoples R China.
会议名称：
14th International Conference on Graphics and Image Processing (ICGIP)
会议时间：
OCT 21-23, 2022
会议地点：
ELECTR NETWORK
会议主办单位：
[Zhou, Liu;Zhang, Xiaozhi] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.^[Zhu, Minjie;Xiong, Dongping;Ouyang, Lijun;Ouyang, Yan] Univ South China, Sch Comp Software, Hengyang 421001, Peoples R China.
会议论文集名称：
Proceedings of SPIE
关键词：
Magnetic resonance imaging (MRI);fast MRI;deep learning;Non-Local;remote dependencies
摘要：
As an advanced medical imaging technology, magnetic resonance imaging (MRI) has great advantages and application potentials in medical clinical diagnosis. However, since the long scanning time and the artifacts caused by patient movements, the imaging results are always not satisfactory. Therefore, accelerating MRI and improving the imaging quality are the key problems. In this work, we propose a novel deep network that combines the U-net architecture with non-local attention blocks for MRI reconstruction. We employ the U-net to construct the basic network. The non-local attention is exploited to capture the remote dependencies in MRI images which calculates the weighted average of the remaining multiple location features as the value of the response location. The U-net has limitations in capturing long-term dependencies, however, the non-local attention can solve this problem well. Furthermore, we develop the residual module to better retain the detail information. The proposed model is compared with some recent leading MRI reconstruction methods, including the state-of-the-art deep learning-based methods. Compared with these methods, the proposed residual non-local attention network provides superior MRI reconstruction results and retains better perceptual image details.
会议名称：
22nd International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2021)
会议时间：
DEC 17-19, 2021
会议地点：
Sun Yat Sen Univ, Guangzhou, PEOPLES R CHINA
会议主办单位：
Sun Yat Sen Univ
会议论文集名称：
Lecture Notes in Computer Science
关键词：
Communication distance;Data locality;Executor allocation;Spark
摘要：
Data locality is a key factor influencing the performance of Spark systems. As the execution container of tasks, the executors started on which nodes can directly affect the locality level achieved by the tasks. This paper tries to improve the data locality by executor allocation in reduce stage for Spark framework. Firstly, we calculate the network distance matrix of executors and formulate an optimal executor allocation problem to minimize the total communication distance. Then, an approximation algorithm is proposed and the approximate factor is proved to be 2. Finally, we evaluate the performance of our algorithm in a practical Spark cluster by using several representative benchmarks: sort, pageRank and LDA. Experimental results show that the proposed algorithm can help to improve the data locality and application/job performance obviously.
作者机构：
[Zhou, Yimin; Zuo, Guoping] School of Nuclear Science and Technology, University of South China, China;[Wu, Rongrong] Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, China;[Bai, Penggang] Department of Radiation Oncology, Fujian Cancer Hospital, China
会议名称：
3rd International Symposium on Artificial Intelligence for Medical Sciences, ISAIMS 2022
作者机构：
[Yang, Kai; Wang, Xiangjiang] College of Mechanical Engineering, University of South China, Hu Nan, Hengyang;421001, China;[Yang, Kai; Wang, Xiangjiang] 421001, China
会议名称：
2022 International Conference on Mechatronics and Automation Technology, ICMAT 2022
期刊：
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS,2022年114(3, Supplement):S119-S119 ISSN：0360-3016
通讯作者：
Y. Zeng
作者机构：
[Fu, X. L.; Cai, X.; Zeng, Y.] Shanghai Jiao Tong Univ, Shanghai Chest Hosp, Dept Radiat Oncol, Shanghai, Peoples R China.;[Li, J.] Fujian Canc Hosp, Dept Radiat Oncol, Fuzhou, Peoples R China.;[Li, J.] Fujian Med Univ, Canc Hosp, Fuzhou, Peoples R China.;[Ye, J.] Nanjing Med Univ, Jiangsu Canc Hosp, Affiliated Canc Hosp, Nanjing, Peoples R China.;[Han, G.] Taizhou City Peoples Hosp, Zhenjiang, Jiangsu, Peoples R China.
通讯机构：
[Y. Zeng] D;Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
会议名称：
Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO)
会议时间：
OCT 23-26, 2022
会议地点：
ELECTR NETWORK
摘要：
Postoperative radiotherapy (PORT) is necessary in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) who have not received neoadjuvant chemoradiotherapy (NCRT). However, the optimal clinical target volume has under hot debate for decades. This clinical trial aims to estimate the optimal radiation volume of PORT for patients with LA-ESCC.
Patients confirmed LA-ESCC (pT3-4N0-3M0) after esophagectomy without NCRT were randomly assigned to either large-field irradiation (LFI, primary lesion and lymph node tumor bed plus elective nodal irradiation) arm or small-field irradiation (SFI, primary lesion and lymph node tumor bed alone) arm with a ratio of 1:1, stratified by T stage and number of lymph node metastasis (LN<3 vs LN≥3). The primary endpoint was disease-free survival (DFS); secondary endpoints included overall survival (OS), adverse events and first failure patterns. The log-rank test was used to estimate the survival differences. The Chi-square test was used to compare adverse events and failure patterns between groups.
In the intention-to-treat analysis, a total of 401 patients with LA-ESCC were randomly assigned to the LFI arm (n=210) and the SFI arm (n=191). With a median follow-up of 38.9 months, the DFS and OS rates of the whole population at 1-year and 3-year were 72.9% and 51.8%, 88.4% and 61.7%, respectively, which were close to patients who received NCRT. Patients in the two irradiation arms had similar DFS (LFI vs SFI, 46.6 vs 48.1 months; HR=0.92, 95% CI, 0.68-1.25; p=0.60). The difference of OS between the two arms did not reach significant (NR vs 73.5 months, HR=0.82, 95% CI, 0.59-1.14; p=0.26). The locoregional recurrence-free survival (HR=0.57, 95% CI 0.35-0.92; p=0.022) and the failure patterns (p=0.021) between two arms were significantly different. Locoregional failure occurred in 12.9% and 20.4% of patients in the LFI arm and SFI arm, respectively; The differences of distant diseases and distant metastasis-free survival of patients between the two arms had no significance. The most frequent toxicity was grade 2 esophagitis (LFI vs SFI, 22.9% vs 16.8%). Grade 3 acute adverse events occurred in 6.7% and 2.6% of patients in the LFI and SFI arms, respectively. No toxicity of grade 4 or 5 was recorded in this study.
Both postoperative irradiation fields are alternatives for LA-ESCC patients without NCRT with the promising survival outcomes comparable to CROSS study. Patients in the LFI arm achieved better locoregional control with a safety profile consistent with the SFI arm.
摘要：
Early warning of small civilian UAVs is a critical issue in the field of public security and is a challenging task in object detection. Video object detection methods based on deep convolution neural networks have attracted increasing attention over recent years. The object detection algorithm designed for static images can hardly be used directly in video object detection, due to motion blur, out-of-focus, etc. Traditional methods mainly apply temporal information to address this problem. In this paper, we proposed a method based on optical flow for UAV video object detection, employing optical flow information and the object appearance visual features in different stages. We establish a motion enhancement module to utilize motion features of moving objects while suppressing complex backgrounds. In addition, direction information is used to associate detection boxes of adjacent frames, improving the stability of the detection. The results of the experiments on the Anti-UAV2021 Challenge dataset show that the average precision of our model is 89.8%, significantly higher than that of FGFA, SELSA, and YOLOv5 models. The experimental results also demonstrate that the motion enhancement module and direction post-processing module can improve the recall rate of small UAVs under complex backgrounds.
作者机构：
[Wang, Chongjie; Wang, Qianwen; Wei, Caiyi; Chen, Wenguang] Univ South China, Hengyang, Peoples R China.
会议名称：
9th International Forum on Electrical Engineering and Automation (IFEEA)
会议时间：
NOV 04-06, 2022
会议地点：
ELECTR NETWORK
会议主办单位：
[Wei, Caiyi;Chen, Wenguang;Wang, Chongjie;Wang, Qianwen] Univ South China, Hengyang, Peoples R China.
关键词：
Interleaved parallel;Buck converters;Hall current sensor;sharing load
摘要：
There is no unified standard for the measurement and detection of Hall current sensors at presently. Manufacturer makes equipment for measurement and detection according to their own verification scheme. The High current detection standard device is the key device to verify the Hall current sensor, and its output current accuracy directly determines the measurement accuracy of the high-current Hall sensor. Therefore, a Hall high current sensor detection device scheme is proposed in this paper. The main circuit adopts a multi-phase Buck converter interleaved and parallel topology, which can not only reduce the total output current ripple, improve the output precision, but also reduce the current stress of each phase Buck converter. Aiming at the problem of current imbalance caused by parameter differences between components, the master-slave current sharing method is used to perform closed-loop feedback control to achieve current sharing between modules. Finally, the simulation results in PSIM show that the total output current of the four-phase Buck converter is 100A, and the output current ripple ratio is 0.1%.
摘要：
Nowadays, falling is a growing threat to the elderly. This paper combines millimeter wave radar technology, machine learning algorithm, wireless communication technique and cloud platform to realize a fall detection system. In this project, the millimeter wave radar is used to sample the human posture point cloud data, and we create a data set that consist of point of clouds of two different human poses. Random forest and BP neural network are used to train the fall detection model. The system will send the human posture point data to the trained model and realize the fall detection. Besides, the system will use 4G communication technology to transform the data to the web cloud platform. This web page serves as an warning function, which can report the acceleration, speed and other information. According to our experiments, the millimeter wave radar system that we built in this paper can effectively detect human point cloud, and can send human point cloud data packets to the recognition model to detect human falls. In machine learning part, both Random forest and BP neural network models show very strong robustness after repeated adjusting parameters. Random forest has the advantages of light weight and interpretability, which can reach 93% recognition accuracy. The recognition accuracy of BP neural network is even up to 95%, which is higher than other detection models in previous works. Besides, BP neural network model also has higher recall rate in the categories of human falls, which fully meets the requirements of this project.
作者机构：
[Shan, Wenyu; Chen, Cheng; Luo, Lingyun; Ding, Pingjian; Luo, Hanyu] Univ South China, Sch Comp Sci, Hengyang 421001, Hunan, Peoples R China.;[Luo, Lingyun] Hunan Med Big Data Int Sci & Technol Innovat Coop, Hengyang 421001, Peoples R China.
会议名称：
18th International Conference on Intelligent Computing (ICIC)
会议时间：
AUG 07-11, 2022
会议地点：
Xian, PEOPLES R CHINA
会议主办单位：
[Luo, Hanyu;Chen, Cheng;Shan, Wenyu;Ding, Pingjian;Luo, Lingyun] Univ South China, Sch Comp Sci, Hengyang 421001, Hunan, Peoples R China.^[Luo, Lingyun] Hunan Med Big Data Int Sci & Technol Innovat Coop, Hengyang 421001, Peoples R China.
摘要：
Enhancers are small segments of DNA that bind to proteins (transcription factors) and the transcription of a gene is strengthened after binding to the protein, thus playing an essential role in gene expression. Recently, machine learning-based methods have become a trend in identifying enhancers and their strength. In this study, we propose iEnhancer-BERT, a novel transfer learning method based on pre-trained DNA language model using the whole human genome. More specifically, iEnhancer-BERT consists of a BERT layer for feature extraction and a CNN layer for classification. We initialize our parameters of the BERT layer using a pre-trained DNA language model, and fine-tune it with transfer learning on the enhancer identification tasks. Unlike common fine-tuning strategies, we extract the output of all Transformer Encoder layers to form the feature vector. Experiments show that our method achieves state-of-the-art results in both enhancer identification tasks and strong enhancer identification tasks. The code and data are publicly available at https://github.com/lhy0322/iEnhancer-BERT.
