作者机构：
[Li, Longjin; Jia, Lei] Univ South China, Dept Elect Engn, Hengyang, Peoples R China.
会议名称：
25th International Conference on Electrical Machines and Systems (ICEMS)
会议时间：
NOV 29-DEC 02, 2022
会议地点：
Rajamangala Univ Technol Lanna, Chiang Mai, THAILAND
会议主办单位：
Rajamangala Univ Technol Lanna
会议论文集名称：
International Conference on Electrical Machines and Systems ICEMS
关键词：
Brushless doubly-fed generator;Pole-changing;Finite element
摘要：
In this paper, a nested-loop rotor brushless doubly-fed generator (BDFG) with improved stator single winding pole-changing design scheme is presented. The BDFG is simulated at 400 rpm and 600 rpm through finite element (FE) method. It is found that the improved stator single winding pole-changing design scheme is effective in reducing the machine harmonic contents and improving the PW generated voltage, CW current waveforms quality.
作者机构：
[Ouyang, Chunping; Tian, Wenlong; Liu, Yongbin; Liu, Qifei; Li, Jing; Geng, Yuqing] Univ South China, Sch Comp Sci & Technol, Hengyang, Peoples R China.;[Tian, Wenlong] Nanyang Technol Univ, Sch Phys & Math Sci, Singapore, Singapore.;[Ouyang, Chunping; Tian, Wenlong; Liu, Yongbin] Hunan Prov Base Sci & Technol Innovat Cooperat, Hengyang, Peoples R China.;[Li, Ruixuan] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China.;[Xiao, Weijun] Virginia Commonwealth Univ, Elect & Comp Engn, Richmond, VA 23284 USA.
会议名称：
IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC) / 9th International Conference on Big Data Computing, Applications and Technologies (BDCAT)
会议时间：
DEC 06-09, 2022
会议地点：
Vancouver, WA
会议主办单位：
[Geng, Yuqing;Tian, Wenlong;Ouyang, Chunping;Liu, Yongbin;Liu, Qifei;Li, Jing] Univ South China, Sch Comp Sci & Technol, Hengyang, Peoples R China.^[Tian, Wenlong] Nanyang Technol Univ, Sch Phys & Math Sci, Singapore, Singapore.^[Tian, Wenlong;Ouyang, Chunping;Liu, Yongbin] Hunan Prov Base Sci & Technol Innovat Cooperat, Hengyang, Peoples R China.^[Li, Ruixuan] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China.^[Xiao, Weijun] Virginia Commonwealth Univ, Elect & Comp Engn, Richmond, VA 23284 USA.^[Xu, Zhiyong] Suffolk Univ, Math & Comp Sci Dept, Boston, MA 02114 USA.
关键词：
Cloud Storage;Resemblance Detection;Context-Aware;Deduplication Ratio Prediction
摘要：
With the prevalence of cloud storage, people prefer to outsource their data to the cloud for flexibility and reliability. Undoubtedly, there are lots of redundancy among these data. However, high-end storage with deduplication costs heavy computation and increases the data management complexity. Potential customers need the redundancy proportion information of their outsourced data to decide whether high-end storage with deduplication is worthwhile. Thus, many researchers have previously attempted to predict the redundant ratio. However, existing mechanisms ignore the redundancy proportion among similar chunks containing many duplicate data. Although resemblance detection, detecting the duplicate parts among similar data, has become a hot issue, it is hardly applied to the conventional deduplication ratio estimation because of unacceptable calculation cost. Therefore, we analyze the limitations and challenges of deduplication ratio prediction in prediction scope and response time and further propose a novel prediction scheme. By leveraging the context-aware resemblance detection, and confidence interval theory, our method can achieve faster estimation speed with higher accuracy in deduplication ratio compared with the state-of-the-art work. Finally, the results show that our method can efficiently and effectively estimate the proportion of duplicate chunks and redundant data among similar chunks by conducting experiments on real workloads.
作者机构：
[He, Jianchong; Lu, Yao] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou, Peoples R China.;[Liang, Xiaowen] Guangzhou Med Univ, Affiliated Hosp 3, Guangzhou, Peoples R China.;[Wei, Jun] Percept Vis Med Technol Co Ltd, Guangzhou, Peoples R China.;[Wei, Jun; Chen, Zhiyi] Univ South China, Affiliated Hosp 1, Med Imaging Ctr, Hengyang, Peoples R China.
会议名称：
13th International Conference on Graphics and Image Processing (ICGIP)
会议时间：
AUG 18-20, 2021
会议地点：
Yunnan Univ, Kunming, PEOPLES R CHINA
会议主办单位：
Yunnan Univ
会议论文集名称：
Proceedings of SPIE
关键词：
Endometrium thickness;ultrasound image;multi-task learning;image process
摘要：
Endometrial receptivity assessment based on the ultrasound image is a common and non-invasive way in clinician practice. Clinicians consider that the thickness of the endometrium is one of the most important assessment markers, which can be calculated with the endometrial region in ultrasound images. Suffering from low contrast of the boundaries in ultrasound images, it's a challenge that makes accurate segmentation of endometrial for thickness calculation. An automated assessment framework with a multi-task learning segmentation network is proposed in this paper. The VGG-based U-net is trained with an auxiliary pattern classification task, the losses of different tasks are combined by weighted sum based on uncertainty in the training phase. Experiment shows that the network has a more accurate prediction than single-task learning and the framework does a better thickness calculation.
作者机构：
[Zhang, Liangfa] Univ South China, Hengyang, Peoples R China.
会议名称：
IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)
会议时间：
FEB 25-27, 2022
会议地点：
Changchun, PEOPLES R CHINA
会议主办单位：
[Zhang, Liangfa] Univ South China, Hengyang, Peoples R China.
关键词：
Face recognition;Pose variation;Deep learning
摘要：
Face recognition beneath pose changes, recently, is a very tough problem and key point in face recognition, a lot of research institutes have tried to figure out the best way to solve the tough problem by producing different method. Recently, as the success development of deep learning in many fields of computer vision, deep learning is also applied to this problem and obtains the state-of-the-art performance. This review is trying to analyze the basic idea and introduce the state-of-the-art algorithms in this field.
作者机构：
[Jiang, Shan; Wu, Huanhuan; Luo, Lingyun] School of Computer Science, University of South China, 28 West Changsheng Rd, Hunan, Hengyang;421001, China;[Jiang, Shan; Wu, Huanhuan; Luo, Lingyun] 421001, China
会议名称：
3rd Asia Service Sciences and Software Engineering Conference, ASSE 2022
作者机构：
[Liu, Chong; Yang, Mei] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.;[Shao, CP; Shao, Cuiping; Yang, Mei; Li, Huiyun] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.
会议名称：
21st IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom)
会议时间：
DEC 09-11, 2022
会议地点：
Wuhan, PEOPLES R CHINA
会议主办单位：
[Yang, Mei;Liu, Chong] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.^[Yang, Mei;Li, Huiyun;Shao, Cuiping] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.
会议论文集名称：
IEEE International Conference on Trust Security and Privacy in Computing and Communications
关键词：
Internet of Vehicles;Security certification;SM2 Digital signature;HF(2(233));FPGA
摘要：
The rapid development of the Internet of Vehicles (IoV) provides a strong technical guarantee for intelligent transportation, greatly facilitating people's daily travel. At the same time, its security problems are becoming increasingly prominent. Fortunately, the cryptographic integrated circuits (ICs) provide a security guarantee for the IoV access authentication, traffic management, data communication, etc., which is the core and cornerstone of the IoV cryptographic technology. However, the IoV has high requirements for timeliness, and its communication resources are precious, so its necessary to ensure that the overhead of the cryptographic module is small and the delay is low. In this paper, we adopt SM2 Elliptic Curve Public Key Digital Signature Algorithm-with fast operation speed and short signature data to implement cryptographic ICs. We design and optimize its hardware design to balance overhead and efficiency. Based on the Montgomery point multiplication algorithm in Lopez-Dahab (LD) projection coordinates, we have researched the core point multiplication operation in SM2 and optimized the time-consuming operation in finite fields, which improved the computational efficiency of SM2. Finally, we completed the hardware design of SM2 on GF(2(233)) domain and verified it on a Xilinx Kintex-7 FPGA development board. The experiment results show that the design occupies a total of 77,665 Slice LUTs and merely takes 2.57 mu s to complete a signature verification. The signature verification rate is 389,105 times/s. Compared with traditional solutions, our proposed method achieves less overhead and little latency.
摘要：
Sensing intrusion is a new threat to information security of automatic driving system, which employs digital noise like adversarial sample to show sensors fake information, aiming to mislead decision making and eventually achieve the hacker's illegal intention. Unfortunately, it is difficult for most traditional information security techniques to deal with this novel risk. Even if the methods like outlier detection can pick out the abnormal sensing data, they still hardly tell the samples containing adversarial noise. In this paper, a method based on semantic similarity check is proposed to address this issue. Scene semantic centroid is introduced to represent the core semantics of a category of driving scene. Correspondingly, each component of the centroid is used to depict the standard sensing semantics for each sensor in this kind of scene. On this basis, a straightforward algorithm is proposed to simultaneously detect both abnormal driving scene and the sensors that may be hacked. Considering the raw sensing semantic space is too high dimensional and too sparse to handle efficiently, a scene semantic autoencoder is developed to extract scene semantic centroid by semantic embedding. The experiments on Nuscenes dataset show that the proposed method is not only feasible to identify the suspicious intruded sensors, but also more effective and accurate than the traditional abnormal sensing data detection.
摘要：
The current mainstream knowledge tracking model is based on the neural network of deep learning, which has a certain improvement in performance. However, due to the difficulty of interpretability of the deep learning methods, and the previous literature did not involve the high-dimensional information between problems and knowledge points when their model used the answer record, there is a situation that the relevant information is not sufficiently extracted. In order to solve the above problems, a knowledge tracing model based on the graph attention network mechanism is proposed, which uses the graph attention network to reveal the potential graph structure between knowledge points in answer records, and aggregates the correlation degree through the attention mechanism, so that the input information of the model includes the relationship information between problems and knowledge points, which enhances the interpretability of the model and improves the prediction accuracy of the model. On the three commonly used public datasets, the proposed model can better reflect learners' mastery of knowledge points.
通讯机构：
[Fangcheng Cao] S;School of Chemistry and Chemical Engineering, University of South China, Hengyang 421001, Hunan, P. R. China
会议名称：
1st China-New Zealand Forum on Advanced Materials and Processing Technology (AMPT) / 5th International Forum on Advanced Materials and Processing Technoogies
会议时间：
MAY 28-29, 2021
会议地点：
Jiangsu Univ Sci & Technol, Zhenjiang, PEOPLES R CHINA
摘要：
Zeolites with unique framework structure have wide applications, such as ions’ exchangers, molecular sieves and catalysts. This work focused on the synthesis and characterization of zeolite by recycling coal fly ash as the starting material via hydrothermal method. The intermediate phases and final products were characterized by XRF, XRD, FT-IR, SEM and BET techniques. The effects of aging time on the crystallization/transformation of zeolite were discussed. The results showed that the alkali-activated coal fly ash after hydrothermal process could lead to the formation of zeolite Na-P1. Furthermore, the aging treatment benefited the formation of homogenous zeolite Na-P1 with smaller particle size, larger specific surface area, total pore volume and pore size.
作者机构：
[Zhou, Rui; He, Hongyu] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.;[Zhou, Rui; Zhang, Kangshuai; Peng, Lei] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.;[Shu, Hongfeng; Liu, Qi] Shenzhen SmartC Technol Dev Grp Co Ltd, Shenzhen 518038, Peoples R China.
会议名称：
IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
会议时间：
OCT 08-12, 2022
会议地点：
Macau, PEOPLES R CHINA
会议主办单位：
[Zhou, Rui;He, Hongyu] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.^[Zhou, Rui;Zhang, Kangshuai;Peng, Lei] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.^[Shu, Hongfeng;Liu, Qi] Shenzhen SmartC Technol Dev Grp Co Ltd, Shenzhen 518038, Peoples R China.
会议论文集名称：
IEEE International Conference on Intelligent Transportation Systems-ITSC
关键词：
5G RSU scheduling;5G RSU energy optimization;Working efficiency per unit energy consumption
摘要：
High energy consumption of roadside unit (RSU) is a great challenge to the deployment of 5G Vehicle-to-Infrastructure(V2I) communication network in large scale. Compared with letting all RSUs work all day, scheduling RSU according to actual V2I traffic load is no doubt an intuitive and ideal energy optimization solution. In this paper, an energy optimization model is proposed to maximize the working efficiency per unit energy consumption of RSU under the premise of meeting V2I communication needs. The periodic statistical features of the travel time and the amount of V2I communication traffic when vehicles passing through RSUs are introduced as the model inputs to endow the model with the adaptability to real-time traffic flow. Afterwards,the method of deep reinforcement learning is applied to solve the approximate optimal solutions. Experiment results demonstrate that the proposed method is feasible and effective, as it can adaptively adjust the duty RSUs with the change of traffic flow to reduce the overall energy consumption compared with other simplistic energy-saving methods that are usually used in practice.
摘要：
This work investigates a joint power allocation and transmission scheduling algorithm for underwater acoustic (UWA) networks to improve the throughput by leveraging the low sound speed in water. We consider a round-based UWA system where transmission links are active concurrently to send multiple signal blocks during each round. To mitigate the interference, a quasi-interference alignment (IA) method is proposed where the interference signals are aligned as much as possible while a low level of collisions between useful and interference signals is allowed. Specifically, the transmission starting time and transmission power are jointly optimized to maximize the total transmission capacity. Different from the conventional IA, the proposed mechanism intends to reduce the total reception time by tolerating slight collisions of useful signals while adapts the power allocation to compensate for the collisions, which could increase the transmission degrees of freedom (d.o.f.). To solve the optimization problem in a tractable way, we decompose the problem into two smaller sub-problems which optimize the transmission schedule and power allocation with a smaller feasible region. The simulation results show that, with an appropriate collision level, the proposed method could achieve decent throughput improvement, compared to the conventional IA and a benchmark method which solves the optimization problem by the genetic algorithm.
作者机构：
[Yan, Shiyu; Yang, Xiaohua; Li, Meng; Wen, Zhaoyu] Univ South China, Sch Comp Sci, Hengyang 421001, Peoples R China.
会议名称：
3rd International Conference on Electronics and Communication; Network and Computer Technology (ECNCT)
会议时间：
DEC 03-05, 2021
会议地点：
Xiamen, PEOPLES R CHINA
会议主办单位：
[Wen, Zhaoyu;Yang, Xiaohua;Yan, Shiyu;Li, Meng] Univ South China, Sch Comp Sci, Hengyang 421001, Peoples R China.
会议论文集名称：
Proceedings of SPIE
关键词：
metamorphic testing;metamorphic relation;likely metamorphic relation;GEP;neutron diffusion program
摘要：
The metamorphic test is a method to alleviate the unexpected value of the Oracle problem. The key point is the identification of the metamorphic relations. The identification of the metamorphic relations of scientific calculation programs is also a complex problem, and the likely of the metamorphic relation of the program can provide enlightening information for the identification of the metamorphic relations. The likely metamorphic relation can be regarded as the implicit expression of the input pattern and output pattern. This paper proposes an output pattern recognition technology based on the likely metamorphic relations of GEP. The technology is mainly aimed at the core neutron diffusion calculation program. The input pattern of the program, and then generate input data and run the program. Finally, in the corresponding output data results, through GEP data mining technology, the output pattern expressed in a variety of functional forms is obtained, which is further compared with analytical solutions and verified to be reliable likely metamorphic relations.
期刊：
E3S Web of Conferences,2022年356:01021-null ISSN：2267-1242
通讯作者：
Ai, Z.
作者机构：
Department of Building Environment and Energy, College of Civil Engineering, Hunan University, Changsha, Hunan, China;Department of Building Environment and Energy, College of Civil Engineering, University of South China, Hunan, China;National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha, Hunan, China;[Hu Y.] Department of Building Environment and Energy, College of Civil Engineering, Hunan University, Hunan, Changsha, China, Department of Building Environment and Energy, College of Civil Engineering, University of South China, Hunan, China;[Zhang G.; Ai Z.] Department of Building Environment and Energy, College of Civil Engineering, Hunan University, Hunan, Changsha, China, National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Hunan, Changsha, China
通讯机构：
[Ai, Z.] D;Department of Building Environment and Energy, Hunan, China
作者机构：
[Qiu, Xiaoping] School of Nuclear Science and Technology, University of South China, Hunan, Hengyang, China;[Bai, Penggang] Department of Radiation Oncology, Fujian Cancer Hospital, Fujian, Fuzhou, China;[Chen, Yanyu] School of Nuclear Science and Technology, University of South China, Hunan, Hengyang, China<&wdkj&>Department of Radiation Oncology, Fujian Cancer Hospital, Fujian, Fuzhou, China
会议名称：
2nd International Symposium on Artificial Intelligence for Medicine Sciences, ISAIMS 2021
