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Exploiting Chaotic Feature Vector for Dynamic Textures Recognition
( Yong Wang ),( Shiqiang Hu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.11
This paper investigates the description ability of chaotic feature vector to dynamic textures. First a chaotic feature and other features are calculated from each pixel intensity series. Then these features are combined to a chaotic feature vector. Therefore a video is modeled as a feature vector matrix. Next by the aid of bag of words framework, we explore the representation ability of the proposed chaotic feature vector. Finally we investigate recognition rate between different combinations of chaotic features. Experimental results show the merit of chaotic feature vector for pixel intensity series representation.
A real-time multiple vehicle tracking method for traffic congestion identification
( Xiaoyu Zhang ),( Shiqiang Hu ),( Huanlong Zhang ),( Xing Hu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.6
Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.
Chaotic Features for Traffic Video Classification
( Yong Wang ),( Shiqiang Hu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.8
This paper proposes a novel framework for traffic video classification based on chaotic features. First, each pixel intensity series in the video is modeled as a time series. Second, the chaos theory is employed to generate chaotic features. Each video is then represented by a feature vector matrix. Third, the mean shift clustering algorithm is used to cluster the feature vectors. Finally, the earth mover`s distance (EMD) is employed to obtain a distance matrix by comparing the similarity based on the segmentation results. The distance matrix is transformed into a matching matrix, which is evaluated in the classification task. Experimental results show good traffic video classification performance, with robustness to environmental conditions, such as occlusions and variable lighting.
Trajectory Planning with Collision Avoidance for Multiple Quadrotor UAVs Using DMPC
Yuhang Jiang,Shiqiang Hu,Christopher Damaren,Lingkun Luo,Bing Liu 한국항공우주학회 2023 International Journal of Aeronautical and Space Sc Vol.24 No.5
Trajectory planning with collision avoidance plays an important role for the safe application of multi-UAV systems in low altitude airspace. Although the synchronous DMPC algorithm had been widely applied in multi-agent systems due to its lower communication and computing cost, it generally suffers from the strict requirements. For example, the additional terminal conditions significantly reduce the maneuverability of the UAV in the fleet, whereas which ensure the stability of the algorithm and the feasibility of recursion. To remedy the raised issues, in this paper, a novel set of terminal conditions is proposed, which effectively reduces the conservativeness of the collision-free trajectories and satisfies the requirements of collision avoidance algorithms simultaneously. In this research, we also leverage the theoretical qualitative analysis, and thus providing initial guesses and related parameter settings for the algorithm. Finally, sufficient numerical simulations are proposed to verify the effectiveness and superiority of the proposed algorithm.
Yong Zhou,Lifang Hu,Lunwei Jiang,Shiqiang Liu 한국유전학회 2018 Genes & Genomics Vol.40 No.6
YTH domain-containing RNA-binding proteins are involved in post-transcriptional regulation and play important roles in the growth and development as well as abiotic stress responses of plants. However, YTH genes have not been previously studied in cucumber (Cucumis sativus). In this study, a total of five YTH genes (CsYTH1–CsYTH5) were identified in cucumber, which could be mapped on three out of the seven cucumber chromosomes. All CsYTH proteins had highly conserved C-terminal YTH domains, and two of them (CsYTH1 and CsYTH4) harbored extra CCCH and P/Q/N-rich domains. The phylogenesis, conserved motifs and exon–intron structure of YTH genes from cucumber, Arabidopsis and rice were also analyzed. The phylogenetically closely clustered YTHs shared similar gene structures and conserved motifs. An analysis of the cis-acting regulatory elements in the upstream region of these genes resulted in the identification of many cis-elements related to stress, hormone and development. Expression analysis based on the transcriptome data showed that some CsYTHs had development- or tissue-specific expression. In addition, their expression levels were altered under various stresses such as salt, drought, cold, and abscisic acid (ABA) treatments. These findings lay the foundation for the functional analysis of CsYTHs in the future.
Yun-Lai Zhou,Shiqiang Qin,Jia Hu,Yazhou Zhang,Juntao Kang 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.70 No.5
This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.