In automatic visual inspection, the object image subspace should be segmented and matched quickly so that the affine relationship can be built between the template image and the sample image. When the interference is ...In automatic visual inspection, the object image subspace should be segmented and matched quickly so that the affine relationship can be built between the template image and the sample image. When the interference is strong and the illumination is uneven, for example in an industrial application, this can make it difficult to obtain an objects subspace quickly and accurately in real-time. In this paper, a novel strategy is proposed to adopt discrete radial search paths instead of searching all points in an image. Therefore, the searching time can be substantially reduced. In order to reduce the influence coming from the industrial environment, the paper proposes another method that is local energy level set segmentation, which can locate the object subspace more efficiently and accurately. The detection of ＂crown caps＂ is presented as an example in this paper. Detection effects and computing time are compared between several detection methods, and the mechanisms of inspection have also been analyzed.展开更多
Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance,HCI,object-based video compression,etc.One of the most successful moving objec...Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance,HCI,object-based video compression,etc.One of the most successful moving object detection algorithms is based on Adaptive Gaussian Mixture Model(AGMM).Although AGMM-based object detection shows very good performance with respect to object detection accuracy,AGMM is very complex model requiring lots of floating-point arithmetic so that it should pay for expensive computational cost.Thus,direct implementation of the AGMM-based object detection for embedded DSPs without floating-point arithmetic HW support cannot satisfy the real-time processing requirement.This paper presents a novel real-time implementation of adaptive Gaussian mixture model-based moving object detection algorithm for fixed-point DSPs.In the proposed implementation,in addition to changes of data types into fixed-point ones,magnification of the Gaussian distribution technique is introduced so that the integer and fixed-point arithmetic can be easily and consistently utilized instead of real number and floating-point arithmetic in processing of AGMM algorithm.Experimental results shows that the proposed implementation have a high potential in real-time applications.展开更多
A conformal multi-resolution time-domain( CMRTD) method is presented for modeling curved objects. The effective dielectric constant and area weighting are used to derive the update equations of CMRTD. The backward sca...A conformal multi-resolution time-domain( CMRTD) method is presented for modeling curved objects. The effective dielectric constant and area weighting are used to derive the update equations of CMRTD. The backward scattering bistatic radar cross sections( RCS) of the dielectric cylinder and ellipsoid are used to validate the proposed method. The results show that the proposed conformal method is more accurate to deal with the complex curved objects in electromagnetic simulations.展开更多
In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm...In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation.展开更多
Recently, compressive tracking （CT） has been widely proposed for its efficiency, accuracy and robustness on many challenging sequences. Its appearance model employs non-adaptive random projections that preserve the ...Recently, compressive tracking （CT） has been widely proposed for its efficiency, accuracy and robustness on many challenging sequences. Its appearance model employs non-adaptive random projections that preserve the structure of the image feature space. A very sparse measurement matrix is used to extract features by multiplying it with the feature vector of the image patch. An adaptive Bayes classifier is trained using both positive samples and negative samples to separate the target from background. On the CT frame- work, however, some features used for classification have weak discriminative abilities, which reduces the accuracy of the strong classifier. In this paper, we present an online compressive feature selection algorithm（CFS） based on the CT framework. It selects the features which have the largest margin when using them to classify positive samples and negative samples. For features that are not selected, we define a random learning rate to update them slowly, It makes those weak classifiers preserve more target information, which relieves the drift when the appearance of the target changes heavily. Therefore, the classifier trained with those discriminative features couples its score in many challenging sequences, which leads to a more robust tracker. Numerous experiments show that our tracker could achieve superior result beyond many state-of-the-art trackers.展开更多
We propose a multi-objective Pareto-optimal technique using Genetic Algorithm (GA) for group communication, which determines a min-cost multicast tree satisfying end-to-end delay, jitter, packet loss rate and blocking...We propose a multi-objective Pareto-optimal technique using Genetic Algorithm (GA) for group communication, which determines a min-cost multicast tree satisfying end-to-end delay, jitter, packet loss rate and blocking probability constraints. The model incorporates a fuzzy-based selection technique for initialization of QoS parameter values at each instance of multicasting. The simulation results show that the proposed algorithm satisfies on-demand QoS requirements (like high availability, good load balancing and fault-tolerance) made by the hosts in varying topology and bursty data traffic in multimedia communication networks.展开更多
Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface（diffuser）.It has very important significance in indirect access to an object or dangerous object detection, ...Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface（diffuser）.It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well： this technology lays a good foundation for developing a practical system that can be used in real applications.展开更多
This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2(GHz) conditions to a set of new linear matrix inequality (LMI) constrain...This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2(GHz) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.展开更多
In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term ...In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.展开更多
文摘In automatic visual inspection, the object image subspace should be segmented and matched quickly so that the affine relationship can be built between the template image and the sample image. When the interference is strong and the illumination is uneven, for example in an industrial application, this can make it difficult to obtain an objects subspace quickly and accurately in real-time. In this paper, a novel strategy is proposed to adopt discrete radial search paths instead of searching all points in an image. Therefore, the searching time can be substantially reduced. In order to reduce the influence coming from the industrial environment, the paper proposes another method that is local energy level set segmentation, which can locate the object subspace more efficiently and accurately. The detection of ＂crown caps＂ is presented as an example in this paper. Detection effects and computing time are compared between several detection methods, and the mechanisms of inspection have also been analyzed.
基金supported by Soongsil University Research Fund and BK 21 of Korea
文摘Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance,HCI,object-based video compression,etc.One of the most successful moving object detection algorithms is based on Adaptive Gaussian Mixture Model(AGMM).Although AGMM-based object detection shows very good performance with respect to object detection accuracy,AGMM is very complex model requiring lots of floating-point arithmetic so that it should pay for expensive computational cost.Thus,direct implementation of the AGMM-based object detection for embedded DSPs without floating-point arithmetic HW support cannot satisfy the real-time processing requirement.This paper presents a novel real-time implementation of adaptive Gaussian mixture model-based moving object detection algorithm for fixed-point DSPs.In the proposed implementation,in addition to changes of data types into fixed-point ones,magnification of the Gaussian distribution technique is introduced so that the integer and fixed-point arithmetic can be easily and consistently utilized instead of real number and floating-point arithmetic in processing of AGMM algorithm.Experimental results shows that the proposed implementation have a high potential in real-time applications.
基金Supported by the National Natural Science Foundation of China(61172024)the Funding of Jiangsu Innovation Program for Graduate Education and the Fundamental Research Funds for the Central Universities(CXZZ12-0156)
文摘A conformal multi-resolution time-domain( CMRTD) method is presented for modeling curved objects. The effective dielectric constant and area weighting are used to derive the update equations of CMRTD. The backward scattering bistatic radar cross sections( RCS) of the dielectric cylinder and ellipsoid are used to validate the proposed method. The results show that the proposed conformal method is more accurate to deal with the complex curved objects in electromagnetic simulations.
基金supported by the National Natural Science Foundation of China(NNSFC)(the grant No.60274043)supported by the National High-tech Research&Development Project(863)(the grant No.2002AA412610)
文摘In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation.
文摘Recently, compressive tracking （CT） has been widely proposed for its efficiency, accuracy and robustness on many challenging sequences. Its appearance model employs non-adaptive random projections that preserve the structure of the image feature space. A very sparse measurement matrix is used to extract features by multiplying it with the feature vector of the image patch. An adaptive Bayes classifier is trained using both positive samples and negative samples to separate the target from background. On the CT frame- work, however, some features used for classification have weak discriminative abilities, which reduces the accuracy of the strong classifier. In this paper, we present an online compressive feature selection algorithm（CFS） based on the CT framework. It selects the features which have the largest margin when using them to classify positive samples and negative samples. For features that are not selected, we define a random learning rate to update them slowly, It makes those weak classifiers preserve more target information, which relieves the drift when the appearance of the target changes heavily. Therefore, the classifier trained with those discriminative features couples its score in many challenging sequences, which leads to a more robust tracker. Numerous experiments show that our tracker could achieve superior result beyond many state-of-the-art trackers.
文摘We propose a multi-objective Pareto-optimal technique using Genetic Algorithm (GA) for group communication, which determines a min-cost multicast tree satisfying end-to-end delay, jitter, packet loss rate and blocking probability constraints. The model incorporates a fuzzy-based selection technique for initialization of QoS parameter values at each instance of multicasting. The simulation results show that the proposed algorithm satisfies on-demand QoS requirements (like high availability, good load balancing and fault-tolerance) made by the hosts in varying topology and bursty data traffic in multimedia communication networks.
基金supported by the National Science and Technology Major Project of China(Grant No.AHJ2011Z001)the Major Research Project of Yili Normal University(Grant No.2016YSZD05)
文摘Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface（diffuser）.It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well： this technology lays a good foundation for developing a practical system that can be used in real applications.
基金Project supported by the National Natural Science Foundation of
China (No. 60374028) and the Scientific Research Foundation for
Returned Overseas Chinese Scholars Ministry of Education (No.
[2004]176)
文摘This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2(GHz) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.
基金Foundation item： Supported by the National Natural Science Foundation of China under Grant No. 51279033, and Heilongjiang Natural Science Foundation of China under Grant No. F201346
文摘In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.
