期刊：
2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI),2017年:1-7
通讯作者：
Wang, Guojun
作者机构：
[Dai, Yinglong] Cent South Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China.;[Xing, Xiaofei; Wang, Guojun] Guangzhou Univ, Sch Comp Sci & Educ Software, Guangzhou 510006, Guangdong, Peoples R China.;[Chen, Sihong] Hunan Univ Chinese Med, Hosp 1, Prevent Treatment Ctr, Changsha 410007, Hunan, Peoples R China.
会议名称：
IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation Conference (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
会议时间：
AUG 04-08, 2017
会议地点：
San Francisco, CA
会议主办单位：
[Dai, Yinglong] Cent South Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China.^[Wang, Guojun;Xing, Xiaofei] Guangzhou Univ, Sch Comp Sci & Educ Software, Guangzhou 510006, Guangdong, Peoples R China.^[Chen, Sihong] Hunan Univ Chinese Med, Hosp 1, Prevent Treatment Ctr, Changsha 410007, Hunan, Peoples R China.
关键词：
knowledge representation;deep learning;feature learning;traditional Chinese medicine;diagnosis
摘要：
Traditional Chinese medicine (TCM), which is built on a foundation of a long history of Chinese medical practice, provides a quite different approach with western medicine. It has formed a deep knowledge of medical science, theory, diagnostic methods, prescriptions and cures. Fully grasping the deep knowledge that mostly based on a great amount of experience is beyond anyone's capability. May we train a big electronic brain to assist diagnosis and healthcare suggestion from TCM approach? Thanks to the advances in deep learning that provides us a powerful method for fusing huge volume data into effective representations, we propose a framework of deep architectures that directly maps the heterogeneous high-dimensional sensory data into a common low-dimensional latent feature space, which is quite approaching the analysis of a TCM practitioner. The information process includes images, audios, text and other sensory data. We propose to use a hierarchically supervised training method to train the deep architectures and obtain the interpretable representations. It can facilitate the non-invasive, painless and inexpensive TCM diagnostic methods to check people's health state with a computer assistant.
作者机构：
[Li, Fuhai; Xie, Hongtu] Hunan Univ, Coll Elect & Informat Engn, Changsha, Hunan, Peoples R China.;[Shi, Shaoying; Xiao, Hui; Zhang, Lin; Xie, Hongtu; Wang, Guangxue] Air Force Early Warning Acad, Wuhan, Hubei, Peoples R China.;[Su, Jialin] PLA, Unit 63629, Beijing, Peoples R China.;[An, Daoxiang; Huang, Xiaotao; Zhou, Zhimin; Xie, Hongtu] Natl Univ Def Technol, Coll Elect Sci, Changsha, Hunan, Peoples R China.;[Wang, Guoqian] Hunan Inst Tradit Chinese Med, Changsha, Hunan, Peoples R China.
会议名称：
IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)
会议时间：
OCT 22-25, 2017
会议地点：
Xiamen, PEOPLES R CHINA
会议主办单位：
[Xie, Hongtu;Li, Fuhai] Hunan Univ, Coll Elect & Informat Engn, Changsha, Hunan, Peoples R China.^[Xie, Hongtu;Shi, Shaoying;Wang, Guangxue;Zhang, Lin;Xiao, Hui] Air Force Early Warning Acad, Wuhan, Hubei, Peoples R China.^[Su, Jialin] PLA, Unit 63629, Beijing, Peoples R China.^[Xie, Hongtu;An, Daoxiang;Huang, Xiaotao;Zhou, Zhimin] Natl Univ Def Technol, Coll Elect Sci, Changsha, Hunan, Peoples R China.^[Wang, Guoqian] Hunan Inst Tradit Chinese Med, Changsha, Hunan, Peoples R China.
关键词：
Airborne early warning radar;detection performance;evaluation and simulation;MATLAB
摘要：
Detection effectiveness of the airborne early warning radar is affected by its detection range as well as its detection probability. This paper presents a method for simulating and evaluating the detection effectiveness of the airborne early warning radar. Firstly, the detection model of the airborne early warning radar is designed. Secondly, based on the radar system parameter as well as the motion parameters of the airplane and target, the detection effectiveness of the early warning radar is simulated and displayed dynamically. Finally, the detection effectiveness of the early warning radar is validated based on the simulated data. The simulation results show that the proposed method can effectively simulate the detection effectiveness of the airborne early warning radar.
期刊：
2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017),2017年:959-966 ISSN：2158-9178
会议名称：
15th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) / 16th IEEE International Conference on Ubiquitous Computing and Communications (IUCC)
会议时间：
DEC 12-15, 2017
会议地点：
Guangzhou, PEOPLES R CHINA
会议主办单位：
[Dai, Yinglong] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China.^[Wang, Guojun;Xie, Dongqing;Chen, Shuhong] Guangzhou Univ, Sch Comp Sci & Educ Software, Guangzhou 510006, Guangdong, Peoples R China.^[Chen, Sihong] Hunan Univ Chinese Med, Hosp 1, Prevent Treatment Ctr, Changsha 410007, Hunan, Peoples R China.
会议论文集名称：
IEEE International Symposium on Parallel and Distributed Processing with Applications
关键词：
Deep Neural Networks;Simulation;Healthcare;Deep Reinforcement Learning;Closed Loop
摘要：
In this paper, we present a human body simulator for healthcare research. In this special environment, human body is regarded as a black-box system that generates different outputs corresponding to different external inputs. The inputs can be healthcare interventions, and the outputs can be phenotypes that reflect latent health states. The healthcare purpose is to find effective strategies that can make the human body transfer to a healthy state from any other unhealthy states. At first, we propose to use deep neural networks (DNNs) to model the human body system. After some analyses, we discover that the models of neural networks can reflect some real cases. Then, we implement a virtual human body simulator and a deep reinforcement learning (DRL) module. These two modules form a closed loop to do some healthcare experiments. The experiments compare different architectures of the body simulator and illustrate some attributes of the models.
关键词：
big data;steganography;carrier-free text steganography;multi-keywords;POS tagging
摘要：
Steganography has attracted more and more attentions in protecting information security. Previous studies achieved by modifying the carriers can't effectively resist the steganalysis methods and attacks. To address this problem, by combining big data with steganography, a novel multi-keywords carrier-free text steganography method based on part of speech tagging is proposed in this paper. In our method, the hidden tags are selected from all the Chinese character components of words. And the POS (Part of Speech) is used to hiding the number of keywords to enhance the hiding capacity. Meanwhile, the redundancy of hidden tags in extraction process is eliminated by ensuring the uniqueness of hidden tags in every stego-text. Also, the way of joint retrieval is used for hiding multi-keywords. The experimental results show that with appropriate hidden tags and large scale of big text data, the proposed method has good performance in the hiding capacity, the success rate of hiding, the extraction accuracy and the time efficiency.
作者机构：
[Xu, G. C.; Jiao, L. Y.] Gannan Med Univ, Ganzhou 341000, Peoples R China.;[Li, Y. C.; Wang, J. X.] Hunan Univ Tradit Chinese Med, Postgrad Sch, Changsha 410208, Hunan, Peoples R China.;[Li, Y. C.] Hunan Univ Tradit Chinese Med, Affiliated Hosp 1, Dept Neurol, Changsha 410007, Hunan, Peoples R China.
会议名称：
5th Chinese Congress on Gerontology and Health Industry (CCGI)
期刊：
Journal of the American College of Cardiology,2016年68(16, Supplement):C61-C61 ISSN：0735-1097
作者机构：
[Tuo, Qinhui; Fei, Qiu; Yang, Dongmei] Hunnan Univ Chinese Med, Changsha, Hunan, Peoples R China.
会议名称：
27th Great Wall Int Congress of Cardiol / 21st Annual Sci Meeting of the Int-Soc-of-Cardiovascular-Pharmacotherapy / World Heart Failure Congress / Int Congress of Cardiovascular Prevent and Rehabilitat
摘要：
To solve the adverse effects brought by resource node transfering the using right to local task and the difficult problem of resource load balancing, a two-phase pricing strategy based on QoS constraints is proposed in this paper. On the premise of guaranteeing the benefits of the resource provider in the cost price, this strategy balances the load of the resource provider by the profit price. The theoretical analysis proves the effectiveness of the pricing strategy, and the algorithm of the pricing strategy is designed in this paper. Resources node information in the real distributed systems is used as the performance parameters of experimental node in the simulation experiments, and the performance of the pricing strategy is tested in a large-scale grid mission. Experimental results show that, compared with the traditional pricing strategies, the two-phase pricing strategy based on QoS constraints has vastly superior performance on the benefits of the resource provider and the balance of resource utilization.
作者机构：
[Huang, Z. Q.] Gannan Med Univ, Coll Pharm, Ganzhou 341000, Peoples R China.;[Li, Y. C.; Wang, J. X.] Hunan Univ Tradit Chinese Med, Postgrad Sch, Changsha 410208, Hunan, Peoples R China.;[Li, Y. C.] Hunan Univ Tradit Chinese Med, Affiliated Hosp 1, Dept Neurol, Changsha 410007, Hunan, Peoples R China.
会议名称：
5th Chinese Congress on Gerontology and Health Industry (CCGI)
作者机构：
[Wang, Shan-Shan] Hunan Univ Chinese Med, Coll Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.;[Ge, Jin-Wen] Hunan Univ Chinese Med, Dept Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.;[Cheng, Shao-Wu] Hunan Univ Chinese Med, Dept Cytobiol & Mol Biotechnol, Changsha 410208, Hunan, Peoples R China.
会议名称：
International Conference on Biological Sciences and Technology (BST)
会议时间：
JAN 08-10, 2016
会议地点：
Guangzhou, PEOPLES R CHINA
会议主办单位：
[Wang, Shan-Shan] Hunan Univ Chinese Med, Coll Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.^[Ge, Jin-Wen] Hunan Univ Chinese Med, Dept Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.^[Cheng, Shao-Wu] Hunan Univ Chinese Med, Dept Cytobiol & Mol Biotechnol, Changsha 410208, Hunan, Peoples R China.
摘要：
Coagulation factor XII (FXII) is a multidomain serine protease that is the starter of intrinsic coagulation pathway. FXII deficiency and clinical hemostasis are not associated with bleeding, so investigators have not considered FXII important in physiology for a long time. In seeking explanation for FXII-independent physiologic hemostasis, investigators found FXII is an essential constitute of contact system that mediates procoagulation and proinflammatory via the intrinsic coagulation pathway or the Kallikrein-kinin system, respectively. Date obtained in infectious inflammation have revealed FXII mediated clotting that limited bacterial or toxin spread in early phases, and regulated fibrinolysis in later. Moreover, FXII mediated two noninfectious inflammation Hereditary angioedema (HAE) and non-specific allergy via bradykinin (BK) formation. In the coagulation, thrombosis not only is involved with coagulation, but is redefined as thrombo-inflammatory disorder. This paper reviews in detail the progresses in roles of FXII intersection between inflammation and coagulation.
作者机构：
[Ma Lijuan; Long Chunlin] Minzu Univ China, Coll Life & Environm Sci, Beijing 100081, Peoples R China.;[Yang Jun; Wang Zhi; Long Chunlin] Chinese Acad Sci, Kunming Inst Bot, Kunming 650201, Peoples R China.;[Wang Zhi] Hunan Univ Chinese Med, Coll Pharm, Changsha 410208, Hunan, Peoples R China.;[Ma Lijuan] Univ Macau, Inst Chinese Med Sci, Taipa, Macau, Peoples R China.
会议名称：
3rd International Conference on Advances in Energy and Environmental Science (ICAEES)
会议时间：
JUL 25-26, 2015
会议地点：
Zhuhai, PEOPLES R CHINA
会议主办单位：
[Long Chunlin;Ma Lijuan] Minzu Univ China, Coll Life & Environm Sci, Beijing 100081, Peoples R China.^[Long Chunlin;Yang Jun;Wang Zhi] Chinese Acad Sci, Kunming Inst Bot, Kunming 650201, Peoples R China.^[Wang Zhi] Hunan Univ Chinese Med, Coll Pharm, Changsha 410208, Hunan, Peoples R China.^[Ma Lijuan] Univ Macau, Inst Chinese Med Sci, Taipa, Macau, Peoples R China.
摘要：
It has become an action plan to develop biodiesel in China. The botanical and laboratory investigations together with literature surveys had been used to prospect potential plants for biodiesel development. Based on field surveys and collections of specimens and samples, 422 oil-bearing plant species had been documented from Yunnan, the richest province with plant species diversity in the country. The oil content, acid value, iodine value, saponification value, and fatty acid composition of plant samples had been tested and assessed. The results revealed that Camellia oleifera var. monosperma, Michelia sphaerantha, Euonymus tingens, Daphniphyllum paxianum, Trichosanthes rubriflos, Symplocos chinensis and Daphniphyllum macropodum might be selected as the potential plant species for biodiesel development in China.
作者：
Zhou, Y. D.;Mahdi, F.;Li, K. P.;Milasta, S.;Jekabsons, M. B.;...
作者机构：
[Mahdi, F.; Li, K. P.; Khan, I. A.; Zhou, Y. D.; Nagle, D. G.; Gao, J.] Univ Mississippi, Sch Pharm, Dept Biomol Sci, University, MS 38677 USA.;[Mahdi, F.; Li, K. P.; Khan, I. A.; Zhou, Y. D.; Nagle, D. G.; Gao, J.] Univ Mississippi, Sch Pharm, RIPS, University, MS 38677 USA.;[Li, K. P.] Guangdong Pharmaceut Univ, Dept Pharm, Guangzhou 510006, Guangdong, Peoples R China.;[Green, D. R.; Milasta, S.] St Jude Childrens Res Hosp, Dept Immunol, Memphis, TN 38105 USA.;[Jekabsons, M. B.] Univ Mississippi, Dept Biol, University, MS 38677 USA.
会议名称：
Annual Meeting of the American-Society-of-Pharmacognosy
期刊：
Journal of the American College of Cardiology,2015年66(16, Supplement):C105-C105 ISSN：0735-1097
作者机构：
[Ma, Xiaocong; Xu, Mingdong; Chen, Xia; Luo, Shuang; Zheng, Jinghui; Liang, Jian; Ning, Guilan; Wang, Tiehua; Wu, Fasheng; Jiang, Zuling] Guangxi Univ Chinese Med, Ruikang Hosp, Dept Cardiovasc Med, Nanning, Peoples R China.;[Jian, Weixiong] Hunan Univ Chinese Med, Natl Key Discipline Tradit Chinese Med Diagnost, Changsha, Hunan, Peoples R China.
会议名称：
26th Great Wall International Congress of Cardiology (GW-ICC) / Asia Pacific Heart Congress (APHC) / International Congress of Cardiovascular Prevention and Rehabilitation (ICCPR)
作者机构：
[Guan, Yihong; Luo, Yatao; Geng, Haibiao; Han, Yu] Kunming Univ Sci & Technol, Fac Sci, Kunming, Yunnan, Peoples R China.;[Guan, Maoying] Hunan Univ Chinese Med, Changsha, Hunan, Peoples R China.
会议名称：
International Conference on Biological Engineering and Biomedical (BEAB)
会议时间：
JAN 10-12, 2014
会议地点：
Yichang, PEOPLES R CHINA
会议主办单位：
[Han, Yu;Geng, Haibiao;Luo, Yatao;Guan, Yihong] Kunming Univ Sci & Technol, Fac Sci, Kunming, Yunnan, Peoples R China.^[Guan, Maoying] Hunan Univ Chinese Med, Changsha, Hunan, Peoples R China.
摘要：
After the study of brain MR images it is found that its gray distribution has a specific distribution pattern. The image's histogram is closely related to the distribution of brain tissue. The distribution pattern of the histogram can be abstracted into a series of curves. In this paper, an automatic segmentation method is proposed for magnetic resonance (MRI) brain images according to the abstract curves. In the end a more accurate segmentation method is obtained. The image segmentation method is divided into three steps as follows: First, the histogram of the image is calculated and also the histogram fuzzy is made. Then the fuzzy clustering algorithm is used to calculate the clustering center. Finally, the gray matter area's curve is calculated by the clustering center. The proposed algorithm in this paper is validated through a large number of simulated images and real MRI brain images.
作者：
Chen, Y.;Li, J.;Li, S. X.;Zhao, J.;Bernier, U. R.;...
作者机构：
[Chen, Y.] Hunan Inst Sci & Tech, Coll Chem & Chem Eng, Yueyang, Peoples R China.;[Chen, Y.; Li, J.; Li, S. X.; Wedge, D. E.] Hunan Univ Chinese Med, Sch Pharm, Changsha, Hunan, Peoples R China.;[Zhao, J.] Nat Ctr Nat Prod Res, Univ, MS USA.;[Becnel, J. J.; Bernier, U. R.] ARS, USDA, Ctr Med Agr & Vet Ent, Gainesville, FL USA.;[Wedge, D. E.; Cantrell, C. L.] ARS, Nat Prod Util Res Unit, USDA, Univ, MS USA.
会议名称：
55th Annual Meeting of the American-Society-of-Pharmacognosy (ASP)
作者机构：
[Wang, Jian; Zhang, Xiaoping; Lu, Jaming; Liang, Biyan] China Acad Chinese Med Sci, TCM Ctr AIDS Prevent & Treatment, Beijing, Peoples R China.;[Qi, Haixun] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China.;[Zhao, Yufeng] China Acad Chinese Med Sci, Inst Basic Res Clin Med, Beijing, Peoples R China.;[Xu, Liran] Henan Univ TCM, Affiliated Hosp 1, Dept Pulm Dis, Zhengzhou, Peoples R China.;[Deng, Xin] Guangxi Univ Chinese Med, Ruikang Hosp, Ctr AIDS Res, Nanning, Peoples R China.
会议名称：
IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE
会议时间：
DEC 09-12, 2014
会议地点：
Orlando, FL
会议主办单位：
[Zhang, Xiaoping;Wang, Jian;Liang, Biyan;Lu, Jaming] China Acad Chinese Med Sci, TCM Ctr AIDS Prevent & Treatment, Beijing, Peoples R China.^[Qi, Haixun] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China.^[Zhao, Yufeng] China Acad Chinese Med Sci, Inst Basic Res Clin Med, Beijing, Peoples R China.^[Xu, Liran] Henan Univ TCM, Affiliated Hosp 1, Dept Pulm Dis, Zhengzhou, Peoples R China.^[Deng, Xin] Guangxi Univ Chinese Med, Ruikang Hosp, Ctr AIDS Res, Nanning, Peoples R China.^[Li, Xiuhui] Beijing Youan Hosp, Integrated Tradit & Western Med Dept, Beijing, Peoples R China.^[Wang, Li] Yunnan Provin Acad TCM, Ctr AIDS Res, Kunming, Peoples R China.^[Tan, Xinghua] Guangzhou Eighth Peoples Hosp, TCM Dept, Guangzhou, Guangdong, Peoples R China.^[Mao, Yuxiang] Hebei Prov Hosp TCM, Hepatobiliary Dept, Shijiazhuang, Peoples R China.^[Zhang, Guoliang] Anhui Prov Hosp TCM, Infect Dept, Hefei, Peoples R China.^[Wang, Junwen] Hunan Prov Hosp TCM, Chinese Med Surg Dept, Changsha, Hunan, Peoples R China.^[Li, Xiaodong] Hubei Prov Hosp TCM, Hepatol Dept, Wuhan, Peoples R China.^[Wang, Yuguang] Beijing Ditan Hosp, Integrated Tradit & Western Med Dept, Beijing, Peoples R China.
关键词：
complex network;HIV/AIDS;traditional Chinese medical (TCM);symptom;herb
摘要：
Purpose: According to the theory of symptomatic treatment, to explore the characteristics of symptoms and the principles of TCM herbal treatment in HIV/AIDS population. Method: Extracting clinical case of HIV/AIDS for TCM herbal treatment gathered by pilot projects named the "National Free Treating HIV/AIDS with TCM Program" including 1695 patients with total 12,985 attendances from August 2004 to December 2010. Using complex network methods to explore the features of symptomatic treatment and using multi-layer network to show the relationship between symptoms and TCM herbs of prescription. Result: The main symptoms of HIV/AIDS are fatigue, anorexia, shortness of breath, chest tightness, pruritus, headache, muscle pain, abdominal distension, etc. And the main herbs are radix paeoniae alba, radix codonopsis, astragalus, atractylodes, tuckahoe, liquorice, rhizoma chuanxiong, dried tangerine peel, etc. Conclusion: From the relationship of prescription-symptom, it indicates that the treatment of HIV/AIDS starts from blood tonic, combined with spleen and stomach, digestion dredge, lung and focusing on modulating spleen.
