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An agricultural data storage mechanism based on HBase

International Journal of information and Communication technology 2019年第4期14卷 456-469页

作者： Li, Changyun Zhang, Qingqing He, Pinjie Wang, Zhibing Chen, Li College of Computer and Science Hunan University of Technology Zhuzhou412007 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory Zhuzhou412007 China Intelligent Perception and Networked Control Hunan Province Key Laboratory of College Zhuzhou412007 China

With the development of agricultural space-Time localisation, sensor network and cloud computing, the amount of agricultural data is increasing rapidly and the data structure becomes more complicated and changeable. Currently, the widely used agricultural database is the relational database. This database handles a large amount of data with very limited throughput and is not suitable for organisation and management of distributed data. HBase is a non-relational database of distributed file storage built on Hadoop platform. HBase is suitable for unstructured data storage database and it can handle large volume of data with high scalability. To better store agricultural big data in HBase, we propose a special agricultural data buffer structure which stores data based on the data category and a two-level indexing memory organisation strategy on HBase. The method proposed saves more than a quarter of the time compared to traditional buffering methods. Experimental results show the higher efficiency of the agricultural data buffer structure and memory-organisation strategy. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Big data

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Multi-stage hybrid multiobjective evolutionary algorithm for multi-type vehicle routing problem with simultaneous pickup and delivery and time windows

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Computers & Industrial Engineering 2025年

作者： Wenqiang Zhang Shun Li Miaolei Deng Yashuang Mu Peng Li Key Laboratory of Grain Information Processing and Control (Henan University of Technology) Ministry of Education China Henan Key Laboratory of Grain Storage Information Intelligent Perception and Decision Making Henan University of Technology China School of Artificial Intelligence and Big Data Henan University of Technology China College of Information Science and Engineering Henan University of Technology China Institute for Complexity Science Henan University of Technology China

The vehicle routing problem (VRP) is a fundamental and extensively studied problem in logistics and transportation. Despite its significance, real-world applications often require more complex variants to address specific operational constraints and objectives. To address these limitations, this paper introduces the multi-type vehicle routing problem with simultaneous pickup and delivery and time windows (MTVRPSPDTW). Although hybrid multiobjective algorithms have been successful in combination optimization problems in recent years, it is still challenging to improve the performance of the algorithms by combining them with different timing. We propose a multi-stage hybrid evolutionary multi-objective optimization with a multi-region sampling strategy (MS-HEMO-MRSS) to optimize both vehicle number and wait time of MTVRPSPDTW. The algorithm integrates a three-stage hybrid approach, combining a global search using the multi-region sampling strategy (MRSS) with a local search based on routing sequence differential evolution (RSDE). The initial stage employs MRSS to quickly position the population near the Pareto front from various directions. The second stage utilizes RSDE to accelerate convergence towards central and edge areas of the Pareto front. In the final stage, individuals on Pareto front are selected and RSDE is used again to guide them towards the edge regions to enhance distribution performance. Specialized encoding, decoding techniques, and genetic operators tailored for two vectors are introduced to optimize MTVRPSPDTW. Comparative experiments with traditional multiobjective evolutionary algorithms demonstrate significant convergence and notable distribution performances, highlighting the benefits of employing different optimization strategies at different evolutionary stages.

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Three-dimensional imaging of through-wall radar based on compressed sampling in the frequency domain

Three-dimensional imaging of through-wall radar based on com...

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2022 International Conference on Informatics, Networking and Computing, ICINC 2022

作者： Xu, Dongpo Liu, Yunqing Wang, Liang Li, Xiaolong Electronics and Information Engineering Changchun University of Science and Technology Changchun130022 China Intelligent Perception and Processing Technology Laboratory Beijing100124 China

ISBN: (纸本)9798350309690

Three-dimensional imaging of through-the-wall radar is an important branch in the field of covert target identification, and the commonly used technique is backward projection imaging, which compensates for the time delay information between the transceiver antennas and coherently superimposes the echo signals of each aperture in space to finally project a three-dimensional image. Because of its unique characteristics, the imaging algorithm is computationally huge and difficult to be applied in practical engineering. In this paper, we address this situation by focusing the image reconstruction problem in the framework of compressive sampling based on SFCW-MIMO radar, and propose a 3D imaging technique for through-wall radar with compressive sampling in the frequency domain. Through actual measurement data verification, it is proved that this method has faster image reconstruction speed and better imaging quality, which promotes the practical application of through-wall radar 3D imaging. © 2022 IEEE.

关键词： Image reconstruction

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Mimicking synaptic plasticity based on TiO 2 /MgO film resistive switching device

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Materials Science in Semiconductor processing 2025年 197卷

作者： Jinyan Pan Jing Li Ruotong He Qiao Huang Tiejun Li Lingsen Yan Yan Liu Hongyang He Yunlong Gao School of Ocean Information Engineering Jimei University Xiamen 361021 Fujian China Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing Jimei University Xiamen 361021 Fujian China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen University Xiamen 361102 Fujian China

The TiO 2 /MgO composite film was prepared via atomic layer deposition, exhibiting superior resistive switching (RS) performance compared to pure MgO film, including a higher resistance ratio (R off /R on ) and enhanced retention. The Ag/TiO 2 /MgO/ITO device exhibited gradual RS characteristics, making it suitable for neuromorphic applications. The device also displayed excellent multilevel RS properties analogous to synaptic plasticity. When a series of positive or negative scanning voltages with progressively increasing amplitudes were applied, the resistance of the device switched and remained at correspondingly higher or lower states, effectively mimicking synaptic potentiation or depression in an amplitude-dependent manner. Furthermore, long-term potentiation and depression behaviors were observed under the time-dependent stimulation. As the pulse voltage amplitude increased, fewer pulses were required to set the device to a specific state. Conversely, lower voltage necessitated more pulses to facilitate Ag ions migration and conductive filament formation. This dynamic mimics synaptic weight modulation, where the evaluation of filaments over time corresponds to synaptic adjustment. Therefore, applying higher or lower amplitude voltages for longer or shorter durations aligns with the observation, where varying stimuli to the presynaptic membrane modulate synaptic weight, thereby strengthening (and weakening) the synaptic signal. The pulse amplitude and duration thresholds modulate the RS behavior of the composite TiO 2 /MgO film effectively mimic the learning and forgetting processes of human brain memory.

关键词： Composite films

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An object classification method based on the improved bacterial foraging optimisation algorithm

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International Journal of Wireless and Mobile Computing 2017年第2期12卷 166-173页

作者： Zeng, Zhigao Guan, Lianghua Yi, Shengqiu Zhu, Yanhui Liu, Qiang Tong, Qi Zeng, Sanyou College of Computer and Communication Hunan University of Technology Hunan412007 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory Hunan China Department of Computer Science China University of GeoSciences Wuhan Hubei China

This paper proposes a new object classification method based on an improved bacterial foraging optimisation algorithm. Firstly, a dynamic step size is used instead of the fixed step size of the chemotaxis. Secondly, the fixed elimination-dispersal probability is replaced by the dynamic probability. Features are extracted to distinguish the objects, such as pedestrians, cars and pets. Ultimately, all the objects are classified using the improved bacterial foraging optimisation algorithm. The experimental results prove that the effectiveness of the object classification method proposed in this paper is better than that of other algorithms. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Optimization

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2-D shape completion with shape priors

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Chinese Science Bulletin 2013年第27期58卷 3430-3436页

作者： GUO Ge JIANG TingTing WANG YiZhou GAO Wen Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences National Engineering Laboratory for Video Technology Key Laboratory of Machine Perception School of EECS Peking University

We propose new techniques for 2-D shape/contour completion, which is one of the important research topics related to shape analysis and computer vision, e.g. the detection of incomplete objects due to occlusion and noises. The purpose of shape completion is to find the optimal curve segments that fill the missing contour parts, so as to acquire the best estimation of the original complete object shapes. Unlike the previous work using local smoothness or minimum curvature priors, we solve the problem under a Bayesian formulation taking advantage of global shape prior knowledge. With the priors, our methods are expert in recovering significant shape structures and dealing with large occlusion cases. There are two different priors adopted in this paper: (i) A generic prior model that prefers minimal global shape transformation (including non-rigid deformation and affine transformation with respect to a reference object shape) of the recovered complete shape; and (ii) a class-specific shape prior model learned from training examples of an object category, which prefers the reconstructed shape to follow the learned shape variation models of the category. Efficient contour completion algorithms are suggested corresponding to the two types of priors. Our experimental results demonstrate the advantage of the proposed shape completion approaches compared to the existing techniques, especially for objects with complex structure under severe occlusion.

关键词：形状结构计算机视觉贝叶斯公式电子相关最佳估计最小曲率先验知识仿射变换

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Star extraction by star sensors for daytime images affected by atmospheric turbulence

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Chinese Journal of Aeronautics 2025年

作者： Wanxiang GOU Yinhu ZHAN Chonghui LI Shuai TONG Yong ZHENG Yuan YANG Hanxu LI College of Geospatial Information Information Engineering University Zhengzhou 450000 China Key Laboratory of Smart Earth Beijing 100029 China Key Laboratory of Spatiotemporal Perception and Intelligent Processing Ministry of Natural Resources Zhengzhou 450000 China Collaborative Innovation Center of BDS Navigation Application Technology Henan Province Zhengzhou 450000 China

Daytime star images captured by dedicated near-space star sensors are characterized by short exposures, high noise, and low Signal-to-Noise Ratios (SNRs). Such imaging is also affected by atmospheric turbulence, causing optical phenomena, such as scintillation, distortion, and jitter. This causes difficulty in recording high-precision star images during the daytime. This study proposes an adaptive star point extraction method based on dynamically predicting stars’ positions. First, it predicts the approximate position of stars based on the star catalog, sensor attitude, observation time, and other information, improving the extraction accuracy. Second, it employs a regional SNR sorting method that adaptively selects star images with higher SNRs, suppressing the scintillation effect and enhancing the SNR of star images. Third, depending on the star’s motion trajectory characteristics on the image plane, it utilizes the centroid smoothing method for extraction, thus overcoming the impact of star drift. Field experiments demonstrate that the proposed method can effectively overcome star scintillation, drift, and irregular imaging caused by atmospheric turbulence, achieving a 100% success rate. Moreover, the extraction accuracy improves by more than 80% compared to traditional adaptive methods, attaining a value of 0.05 pixels (0.5’’), thereby meeting the requirements of daytime astronomical attitude determination and positioning.

关键词： Astronomical navigation Star sensor Daytime star image Atmospheric turbulence Star extraction Centroid accuracy

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Aerial Tracking based on Vision Transformer

Aerial Tracking based on Vision Transformer

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2022 International Conference on Electronic information Engineering and Computer Science, EIECS 2022

作者： Jiang, Siping Liu, Yunqing Wang, Liang Xu, Yulong Changchun University of Science and Technology College of Electronic and Information Engineering Jilin Province Changchun China Intelligent Perception and Processing Technology Laboratory Beijing China

ISBN: (纸本)9781510663312

In recent years, object tracking depends upon deep networks or complex architectures made great progress in accuracy, but less attention has been paid to tracking speed. On edge platforms with limited resources are used on UAVs, trackers are difficult to meet the requirements of real-time processing. To address the above problems, we proposed UAV object tracking based on vision transformer. Firstly, a lightweight neural network ResNet18 is used for feature extraction. Secondly, a transformer encoder is used to fully enhance fused features of the template features and the search features to improve feature expression, then, the enhanced features output from encoder are used for target prediction. Finally, further weighted fusion at decision level is used to obtain final tracking result, and a multi-supervised strategy is used. The proposed method achieves better results on three challenging large-scale tracking datasets, UAV123, LaSOT, and TrackingNet, reaching the success score(AUC) of 66.82, 64.26, and 81.2, respectively. In addition, our model tested speed on UAV123's test dataset, running at 116.2fps on NVIDIA 1660TI and 20.2fps on NVIDIA Jetson Xavier NX, which basically meets UAV's demand for real-time performance. © 2023 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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A parallel artificial immune model for optimization

A parallel artificial immune model for optimization

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2009 International Conference on Computational Intelligence and Security, CIS 2009

作者： Qi, Yutao Liu, Fang Jiao, Licheng School of Computer Science and Technology Key Laboratory of Intelligent Perception and Image Xidian University Xi'an China Inst. of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

ISBN: (纸本)9780769539317

This paper presents a parallel artificial immune model termed as tower master-slave model (TMSM) for solving optimising problems. Based on TMSM, the parallel immune memory clonal selection algorithm (PIMCSA) is also proposed. TMSM is a two level coarse-grained parallel artificial immune model with distributed immune response and distributed immune memory. In PIMCSA, vaccines are extracted and migrated between populations rather than individual migration as has been done in parallel genetic algorithms. It is a good balance between population diversity and the convergent speed. Experimental results on the numerical optimization and TSP problems show that PIMCSA achieves good performance in terms of both solution quality and computation time. © 2009 IEEE.

关键词： Genetic algorithms

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Degradation of AlGaN/GaN High Electron Mobility Transistors with Different AlGaN Layer Thicknesses under Strong Electric Field

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Chinese Physics Letters 2010年第2期27卷 243-245页

作者：杨凌马晶晶朱诚郝跃马晓华 Key Laboratory of Wide Band Gap Semiconductor Material and Device Institute of Microelectronics Xidian University Xi'an 710071 Key Laboratory of Intelligent Perception and Image Understanding (Ministry of Education) Institute of Intelligent Information Processing Xidian University Xi'an 710071 National Key Laboratory of Science and Technology on Antennas and Microwaves Xidian University Xi'an 710071

The degradation of AlGaN/GaN high electron mobility transistors （HEMTs） has a close relationship with a model of traps in AlGaN barriers as a result of high electric field. We mainly discuss the impacts of strong electrical field on the AlGaN barrier thickness of AlGaN/GaN HEMTs. It is found that the device with a thin AlGaN barrier layer is more easily degraded. We study the degradation of four parameters, i.e. the gate series resistance RGate, channel resistance R channel, gate current IG,off at VGS=-5 and VDS=0.1 V, and drain current ID,max at VGS=2 and VDS=5 V. In addition, the degradation mechanisms of the device electrical parameters are also investigated in detail.

关键词： Chinese climate network complex systems small world community

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