This paper presents a new pulmonary nodules computer-aided detection system in chest CT images utilizing the adaptive fuzzy C-Means (AFCM) technologies. Since rough segmentation of nodules tends to result in high false positive (FP), the main purpose of this study is to reduce the false-positive of candidate nodules via the clustering and classifying approaches. The proposed scheme consists of three phases: pulmonary nodule identification, training nodules clustering, and testing nodules classification. Firstly, the lung parenchyma is extracted through neighborhood connected technology and masking processing, and by appropriate thresholding processing, the candidate nodules are identified. Then, for improving the performance in the training phase, we utilize the AFCM technology. Finally, the category of each testing candidate nodule is determined by Mahalanobis distance. We validated our method on 35 volumes of chest CT, which is subdivided into 20 training part and 15 testing part, and an approximate false-positive of 2.8 per scan is obtained in our experiment. The preliminary results prove that our scheme is a promising tool for pulmonary nodule detection.
{"title":"A New Pulmonary Nodules Computer-Aided Detection System in Chest CT Images Based on Adaptive Fuzzy C-Means Technology","authors":"Jinke Wang, Yuanzhi Cheng","doi":"10.1109/IHMSC.2015.30","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.30","url":null,"abstract":"This paper presents a new pulmonary nodules computer-aided detection system in chest CT images utilizing the adaptive fuzzy C-Means (AFCM) technologies. Since rough segmentation of nodules tends to result in high false positive (FP), the main purpose of this study is to reduce the false-positive of candidate nodules via the clustering and classifying approaches. The proposed scheme consists of three phases: pulmonary nodule identification, training nodules clustering, and testing nodules classification. Firstly, the lung parenchyma is extracted through neighborhood connected technology and masking processing, and by appropriate thresholding processing, the candidate nodules are identified. Then, for improving the performance in the training phase, we utilize the AFCM technology. Finally, the category of each testing candidate nodule is determined by Mahalanobis distance. We validated our method on 35 volumes of chest CT, which is subdivided into 20 training part and 15 testing part, and an approximate false-positive of 2.8 per scan is obtained in our experiment. The preliminary results prove that our scheme is a promising tool for pulmonary nodule detection.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"41 1","pages":"514-517"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88176801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose an improved image fusion method of infrared image and SAR image based on the Contour let transform and sparse representation. For the method, it decompose the source image into the low frequency sub band coefficients and the high frequency sub band coefficients with the Contour let transform. The low frequency coefficients with lower sparseness are dealed with sparse representation, construct over complete dictionary, solve sparse coefficient over the trained dictionary, and choose the low frequency coefficients with the larger energy fusion rule. The high frequency sub band coefficients are fused by gradient maxim in. Different frequency coefficients are used to reconstruct the fused image by the inverse Contour let transform. Experimental results show that the proposed method is a feasible and effective image fusion method in term of visual quality and objective evaluation.
{"title":"An Improved Image Fusion Method of Infrared Image and SAR Image Based on Contourlet and Sparse Representation","authors":"Xiuxia Ji","doi":"10.1109/IHMSC.2015.11","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.11","url":null,"abstract":"In this paper, we propose an improved image fusion method of infrared image and SAR image based on the Contour let transform and sparse representation. For the method, it decompose the source image into the low frequency sub band coefficients and the high frequency sub band coefficients with the Contour let transform. The low frequency coefficients with lower sparseness are dealed with sparse representation, construct over complete dictionary, solve sparse coefficient over the trained dictionary, and choose the low frequency coefficients with the larger energy fusion rule. The high frequency sub band coefficients are fused by gradient maxim in. Different frequency coefficients are used to reconstruct the fused image by the inverse Contour let transform. Experimental results show that the proposed method is a feasible and effective image fusion method in term of visual quality and objective evaluation.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"7 1","pages":"282-285"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79707411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Underwater glider is a new type of autonomous underwater vehicle driven by gravity. In order to study the relationship between the motion parameters and control variable of the underwater glider, solve the fluctuation problem of pitching angle and attack angle in the process of attitude changing, simulation via the software Mat lab is performed based on the kinematic equations of underwater glider in vertical plane. The results show that the longer the cycle of bary center adjusting, the smaller the fluctuating extent of the pitching angle. It seems that this fluctuation of underwater glider is not affected by the variation of buoyancy adjusting, and the fluctuation of attack angle may be affected by the time center location difference between these two adjusting cycles.
{"title":"Motion Simulation of an Underwater Glider","authors":"Yu Ma, Xiaowei Liu, Ping Ou","doi":"10.1109/IHMSC.2015.141","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.141","url":null,"abstract":"Underwater glider is a new type of autonomous underwater vehicle driven by gravity. In order to study the relationship between the motion parameters and control variable of the underwater glider, solve the fluctuation problem of pitching angle and attack angle in the process of attitude changing, simulation via the software Mat lab is performed based on the kinematic equations of underwater glider in vertical plane. The results show that the longer the cycle of bary center adjusting, the smaller the fluctuating extent of the pitching angle. It seems that this fluctuation of underwater glider is not affected by the variation of buoyancy adjusting, and the fluctuation of attack angle may be affected by the time center location difference between these two adjusting cycles.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"32 1","pages":"539-542"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81086874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiarui Cui, Jiqiang Fu, Zhiyu Tao, Lu Tong, Guangda Hu, Yumeng Zhang, Xinzhe Li
This work discusses a problem of trajectory tracking of joint based on Kinect carema. First, an improved recursive algorithm for Skeleton location tracing based on Kalman filtering algorithms in discrete data linear filtering is presented. Then a trajectory tracking system of joint is designed based on Kinect camera which is consisted of human-computer interaction subsystem which track the trajectory of the hand and dual-axis motion control subsystem which track the collected trajectory of the human-computer interaction subsystem. For the communication between the two subsystems, a reliable protocol and the reasonable software flow on human-computer interaction and dual-axis motion control subsystem are developed. Finally, an experiment is given to validate the algorithm and the system.
{"title":"Trajectory Tracking of Joint Based on Kinect","authors":"Jiarui Cui, Jiqiang Fu, Zhiyu Tao, Lu Tong, Guangda Hu, Yumeng Zhang, Xinzhe Li","doi":"10.1109/IHMSC.2015.124","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.124","url":null,"abstract":"This work discusses a problem of trajectory tracking of joint based on Kinect carema. First, an improved recursive algorithm for Skeleton location tracing based on Kalman filtering algorithms in discrete data linear filtering is presented. Then a trajectory tracking system of joint is designed based on Kinect camera which is consisted of human-computer interaction subsystem which track the trajectory of the hand and dual-axis motion control subsystem which track the collected trajectory of the human-computer interaction subsystem. For the communication between the two subsystems, a reliable protocol and the reasonable software flow on human-computer interaction and dual-axis motion control subsystem are developed. Finally, an experiment is given to validate the algorithm and the system.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"72 1","pages":"330-333"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86278161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the problem of batch scheduling jobs on m parallel machines with time bound to minimize total weighted completion times. Each batching machine can processing to b jobs simultaneously as a batch. A polynomial-time optimal algorithm for identical job processing time model is presented whose details and proof are given.
{"title":"Batch Scheduling Problem and Algorithm on Parallel Machines with Time Bound","authors":"Haixia Li, Xiaoli Gao, Chuanguang Sun","doi":"10.1109/IHMSC.2015.108","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.108","url":null,"abstract":"We consider the problem of batch scheduling jobs on m parallel machines with time bound to minimize total weighted completion times. Each batching machine can processing to b jobs simultaneously as a batch. A polynomial-time optimal algorithm for identical job processing time model is presented whose details and proof are given.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"191 1","pages":"8-10"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77302416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the high volume, velocity and variety characteristics, remote sensing(RS) data has been regarded as a typical big data. Cloud computing is a powerful technology in big data era. The Huge computing power of cloud computing could be leveraged in RS image data processing. This paper proposed a preliminary private cloud for RS image processing. The two cornerstone components of the private cloud was private cloud storage engine(PCSE) and private cloud computing engine(PCCE). The PCSE was responsible for the data storage while the PCCE is responsible for data processing. The private cloud had been implemented and used in our RS image processing project. Experiments results illustrated that the private cloud was effective for RS image processing.
{"title":"A Preliminary Private Cloud for Remote Sensing Image Data Processing","authors":"Zhenju Li, Xuejun Li, Tao Liu","doi":"10.1109/IHMSC.2015.10","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.10","url":null,"abstract":"With the high volume, velocity and variety characteristics, remote sensing(RS) data has been regarded as a typical big data. Cloud computing is a powerful technology in big data era. The Huge computing power of cloud computing could be leveraged in RS image data processing. This paper proposed a preliminary private cloud for RS image processing. The two cornerstone components of the private cloud was private cloud storage engine(PCSE) and private cloud computing engine(PCCE). The PCSE was responsible for the data storage while the PCCE is responsible for data processing. The private cloud had been implemented and used in our RS image processing project. Experiments results illustrated that the private cloud was effective for RS image processing.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"21 1","pages":"185-187"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86491733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurate noise level estimation is a very important step for many image denoising and computer vision tasks. So far the key idea of most methods is to separate the noise-free image part from noisy images and then use the noise part to estimate noise level. But the noise part usually still contains some image content, which often causes biased estimation results, especially in the low noise situation. In this paper, we propose a novel noise level estimation method. This method first uses the DCT basis to approximate the noise-free image part, then uses the ?2 distribution to approximate the local noise variance. Contrary to the conventional idea that the noise residual approximation can not produce accurate estimates, we show that because of the good approximation capability of the DCT basis for natural image content and the ?2 distribution approximation used in the statistical inference, it is possible to achieve more accurate image noise estimation results than most sophisticated state-of-the-art methods especially at low noise level which is more meaningful. Experiments results confirm the advantages of the proposed approach.
{"title":"Accurate Image Noise Level Estimation through DCT Transformation and Approximation by Chi-Square Distribution","authors":"Lei Yang, Y. Wan","doi":"10.1109/IHMSC.2015.16","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.16","url":null,"abstract":"Accurate noise level estimation is a very important step for many image denoising and computer vision tasks. So far the key idea of most methods is to separate the noise-free image part from noisy images and then use the noise part to estimate noise level. But the noise part usually still contains some image content, which often causes biased estimation results, especially in the low noise situation. In this paper, we propose a novel noise level estimation method. This method first uses the DCT basis to approximate the noise-free image part, then uses the ?2 distribution to approximate the local noise variance. Contrary to the conventional idea that the noise residual approximation can not produce accurate estimates, we show that because of the good approximation capability of the DCT basis for natural image content and the ?2 distribution approximation used in the statistical inference, it is possible to achieve more accurate image noise estimation results than most sophisticated state-of-the-art methods especially at low noise level which is more meaningful. Experiments results confirm the advantages of the proposed approach.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"36 1","pages":"387-390"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81371257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Order to improve performances, feed forward control is widely applied to process control, especially for plant with nonlinearity and transport delay. However, the pre-set feed forward trajectory cannot adapt to uncertainty in plant due to its run-to-run discrepancy and material deteriorations. It needs to be adjusted online according to current plant dynamics. In this paper, online trimming is implemented by adding the output of a MPC (model predictive control) controller to feed forward trajectory. The model used in MPC controller is acquired through system identification. This scheme is applied to CZ crystal growth control for verification. The results show that it can effectively compensate the inaccuracy of temperature trajectory in CZ control system. The trimmed temperature trajectory matches plant dynamics quickly due to the prediction functionality in the MPC controller.
{"title":"Online Trimming of Feed Forward Trajectory by System Identification and Model Predictive Control","authors":"Yao-Bing Wei, Hongxin Li, Xiaoke Li","doi":"10.1109/IHMSC.2015.180","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.180","url":null,"abstract":"Order to improve performances, feed forward control is widely applied to process control, especially for plant with nonlinearity and transport delay. However, the pre-set feed forward trajectory cannot adapt to uncertainty in plant due to its run-to-run discrepancy and material deteriorations. It needs to be adjusted online according to current plant dynamics. In this paper, online trimming is implemented by adding the output of a MPC (model predictive control) controller to feed forward trajectory. The model used in MPC controller is acquired through system identification. This scheme is applied to CZ crystal growth control for verification. The results show that it can effectively compensate the inaccuracy of temperature trajectory in CZ control system. The trimmed temperature trajectory matches plant dynamics quickly due to the prediction functionality in the MPC controller.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"12 1","pages":"105-108"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82328645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to improve the intellectuality and human-machine interaction of high power semiconductor laser power supply, STM32F107VCT6 is used as master controller in the constant-current source system of semiconductor laser. By using the 10M/100M Ethernet interface based on STM32F107VCT6, the power supply can achieve network communication. A friendly human-machine interface is designed based on LABVIEW. At the same time, the power supply system provides automatic temperature control and protection for semiconductor laser. The result shows that the power supply can work in continuous wave (CW) and quasi-continuous wave (QCW) modes, whose maximum output current is 70A.
{"title":"Design of High Power Semiconductor Laser Power Supply Based on ARM","authors":"Haixia Xu, Bo Li, Youqing Wang","doi":"10.1109/IHMSC.2015.79","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.79","url":null,"abstract":"In order to improve the intellectuality and human-machine interaction of high power semiconductor laser power supply, STM32F107VCT6 is used as master controller in the constant-current source system of semiconductor laser. By using the 10M/100M Ethernet interface based on STM32F107VCT6, the power supply can achieve network communication. A friendly human-machine interface is designed based on LABVIEW. At the same time, the power supply system provides automatic temperature control and protection for semiconductor laser. The result shows that the power supply can work in continuous wave (CW) and quasi-continuous wave (QCW) modes, whose maximum output current is 70A.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"45 1","pages":"505-508"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74015607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper focuses on the joint study of membrane computing with job shop scheduling problem. We use membrane to conduct the whole process of computation, which can obtain all possible combinations of operations and machines by evolution rules and calculate the whole computing time by communication rules, complete the order of every artifacts, output the final result through communication rules and division rules. A 3*3 JSSP example is used to indicate the feasibility of the provided algorithm.
{"title":"Solving Job Shop Scheduling Problems by P System with Active Membranes","authors":"Laisheng Xiang, Jie Xue","doi":"10.1109/IHMSC.2015.272","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.272","url":null,"abstract":"This paper focuses on the joint study of membrane computing with job shop scheduling problem. We use membrane to conduct the whole process of computation, which can obtain all possible combinations of operations and machines by evolution rules and calculate the whole computing time by communication rules, complete the order of every artifacts, output the final result through communication rules and division rules. A 3*3 JSSP example is used to indicate the feasibility of the provided algorithm.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"18 1","pages":"242-245"},"PeriodicalIF":0.0,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73579139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：