Air-to-air Missile is the main source of air confrontation, which plays an important role in air confrontation. The attack ability of air-to-air missile is one of the key factors of air combat. Establishing the models...
详细信息
ISBN:
(数字)9781510649965
ISBN:
(纸本)9781510649965;9781510649958
Air-to-air Missile is the main source of air confrontation, which plays an important role in air confrontation. The attack ability of air-to-air missile is one of the key factors of air combat. Establishing the models of motion and seeker tracking and introducing the greedy algorithm to improve the tracking ability, while regarding the third flight as attack target and establishing the model of motion and radiation. Simulating the infrared radiation characteristic of the target, calculating the attack region of missile and the optimization performance of algorithm It's concluded that attack region of the simulation matches the reality and the greedy algorithm can usefully improve the recognition efficiency of seeker.
Efficient and precise motif extraction is a central problem in the study of proteins functions and structures. This paper presents an efficient new geometric approach to the problem, based on the General Hough Transfo...
详细信息
ISBN:
(纸本)9783642411892;9783642411908
Efficient and precise motif extraction is a central problem in the study of proteins functions and structures. This paper presents an efficient new geometric approach to the problem, based on the General Hough Transform. The approach is both an extension and a variation of the Secondary Structure Co-Occurrences algorithm by Cantoni et al. [1-2]. The goal is to provide an effective and efficient implementation, suitable for HPC. The most significant contribution of this paper is the introduction of a heuristic greedy variant of the algorithm, which is able to reduce computational time by two orders of magnitude. A secondary effect of the new version is the capability to cope with uncertainty in the geometric description of the secondary structures.
More and more deep learning methods are applied in unmanned or assisted driving, and have achieved very excellent performance. This paper describes long short-term memory recurrent neural networks used in assisted dri...
详细信息
ISBN:
(纸本)9781538630969
More and more deep learning methods are applied in unmanned or assisted driving, and have achieved very excellent performance. This paper describes long short-term memory recurrent neural networks used in assisted driving, which can capture the long temporal dependencies of multiple vehicles sensors' data, supporting drivers' behavior analysis on vehicles. Some optimization methods, such as model compression, weight quantization, adaptive window segmentation, are applied to make the deep network faster and less power. Therefore, it can be easily deployed on smart-phones and other embedded devices due to its moderate energy consumption and low latency. The architecture was trained in a sequence-to-sequence prediction manner, and it explicitly learns to predict the driving patterns given the temporal context. The experiment is executed on the smart-phone. Experimental results for different parameters are also presented in the paper. At last, we reduce the model size to 77 KB, the processing time to 4.27 ms, and the power overhead is 7.7 mW, the percentage of improved performance by our optimizations is over 60%.
The echo state network (ESN) is a dynamic neural network, which simplifies the training process in the conventional neural network. Due to its powerful non-linear computing ability, it has been applied to predict the ...
详细信息
ISBN:
(数字)9783030042219
ISBN:
(纸本)9783030042219;9783030042202
The echo state network (ESN) is a dynamic neural network, which simplifies the training process in the conventional neural network. Due to its powerful non-linear computing ability, it has been applied to predict the time series. However, the parameters of the ESN need to be set experimentally, which can lead to instable performance and there is space to further improve its performance. In order to address this challenge, an improved fruit fly optimizationalgorithm (IFOA) is proposed in this work to optimize four key parameters of the ESN. Compared to the original fruit fly optimizationalgorithm (FOA), the proposed IFOA improves the optimization efficiency, where two novel particles are proposed in the fruit flies swarm, and the search process of the swarm is transformed from two-dimensional to three-dimensional space. The proposed approach is applied to financial data sets. Experimental results show that the proposed FOA-ESN and IFOA-ESN models are more effective (similar to 50% improvement) than others, and the IFOA-ESN can obtain the best prediction accuracy.
Radars which able to diagnose the state of living organisms, can find the widest application. The estimation method of respiration and heartbeat parameters of the man was offered. The mathematical modeling for algorit...
详细信息
ISBN:
(纸本)9789663354125
Radars which able to diagnose the state of living organisms, can find the widest application. The estimation method of respiration and heartbeat parameters of the man was offered. The mathematical modeling for algorithm optimization of obtaining the necessary signals and determination of their spectral characteristics are carried out.
Scene management technology is one of the key technologies of virtual reality and visualization. In this paper, we propose a new method based on adaptive binary tree (ABT) and scene graph, which is used to improve the...
详细信息
ISBN:
(纸本)9781538631546
Scene management technology is one of the key technologies of virtual reality and visualization. In this paper, we propose a new method based on adaptive binary tree (ABT) and scene graph, which is used to improve the real-time rendering of indoor and outdoor objects and enhance the organization efficiency of scenes structure. The generation algorithm of adaptive binary tree, the scoring standard of the splitting plane, the algorithm of search effective segmentation of plane and related algorithms are described in detail. Due to the characteristics of high accuracy of adaptive binary tree space subdivision and strong adaptability of scene graph, the paper proposes the new management model that combines adaptive binary tree space subdivision algorithm to scene graph, forming the strategy of scene management. It not only expands the range of application of scene organization, but also can help to improve the subsequent rendering efficiency. The experimental results have demonstrated that our method greatly shortens the three-dimensional scene organization time, and accelerates real-time rendering speed of complex scene.
Recently, Problem-based learning has been increasingly used, and with those practices, self and peer evaluation tasks have gained more importance. This method of learning assists learners in the acquisition of skills ...
详细信息
ISBN:
(数字)9781728109305
ISBN:
(纸本)9781728109305
Recently, Problem-based learning has been increasingly used, and with those practices, self and peer evaluation tasks have gained more importance. This method of learning assists learners in the acquisition of skills and competencies. In order to support self and peer evaluation tasks, there are some different software offers in the market. The ease use of them is demanded since these tasks are an important part of evaluation. With the literature emphasis on the importance of assessment and critical spirit, it arises the possibility to implement formulas to increase the efficiency on the methodology applied and satisfaction of students and teachers. This paper introduces formulation problems about marks weighting in self and peer evaluation. It presents the advantages and disadvantages of different solutions for the formulation and suggestions of adapting them among tools, feedback surveys, and teacher's methods of evaluation. It is also expected that the formulation, which was implemented in the software tool WEBAVALIA, has a great impact on feedback, improving user experience, and both efficiency and flexibility.
Scene space organizational structure and visibility culling plays a crucial role in the quality and efficiency of subsequent rendering. To improve the real-time rendering of indoor and outdoor objects and enhance the ...
详细信息
ISBN:
(纸本)9781538631546
Scene space organizational structure and visibility culling plays a crucial role in the quality and efficiency of subsequent rendering. To improve the real-time rendering of indoor and outdoor objects and enhance the organization efficiency of scenes, we propose an optimized scene management structure for fast visibility culling. We organize the scene into an adaptive binary tree (ABT) structure to make full use of the characteristics of high accuracy of ABT space subdivision and strong adaptability of scene graph. Based on its structure and the basic principle of view frustum culling (VW) algorithm, a double-layer visibility culling algorithm is proposed to further improve performance and to compensate for the existing low VFC efficiency. The results of experiments prove its high efficiency for handling complex scenes with large amount of triangles in high depth, accelerating real-time rendering speed of complex scene.
This article optimizes a continuous area cartogram algorithm published in The Professional Geographer by Dougenik, Chrisman, and Niemeyer (DCN) in 1985. The DCN algorithm simulates a rubber sheet and is an iterative a...
详细信息
This article optimizes a continuous area cartogram algorithm published in The Professional Geographer by Dougenik, Chrisman, and Niemeyer (DCN) in 1985. The DCN algorithm simulates a rubber sheet and is an iterative and approximate solution of cartogram construction. Although it remains popular because of its conceptual simplicity and cartographic quality, the DCN algorithm cannot completely preserve topology and its mathematical properties are inadequately explained. This article presents an optimization to the DCN algorithm, named Opti-DCN, with three improvements. First, it provides a mathematical condition for topology preservation. Second, new transformation equations that meet this condition are deduced from mathematics, which simultaneously optimize the global elasticity coefficient, a key parameter that greatly impacts the convergence rate of the rubber-sheet algorithm and the topological integrity of its generated cartograms. Last, the new algorithm simplifies the way of generating transforming forces in DCN and improves its efficiency of geometric transformation. Comparison shows that Opti-DCN is significantly faster to converge to equal-density cartograms and can mathematically and practically eliminate topological errors.
Industrial IoT (IIoT) in conjunction with UltraReliable Low-Latency Communications (URLLC) often struggles with data-rich, information-poor contexts. Blind Source Separation (BSS) is one of the key technologies which ...
详细信息
ISBN:
(纸本)9781728173078
Industrial IoT (IIoT) in conjunction with UltraReliable Low-Latency Communications (URLLC) often struggles with data-rich, information-poor contexts. Blind Source Separation (BSS) is one of the key technologies which can obtain the desired high-value information from all of the observed raw sensory data. As shown by recent studies, BSS can be both fast enough for low-latency requirements and sufficiently accurate to be a reliable method in large IoT deployments. Nonetheless, the trade-off between signal context usage and data recovery accuracy often affects the separation quality of BSS. In this paper, we propose for the first time a novel dual path convolutional neural network model, called Y-Net, for high accuracy BSS. Specifically, the separation quality is improved by the parallel perception and joint combination of both high- and low-level features of input signals, which we demonstrated through extensive numerical evaluations. In particular, Y-Net improves the Source-to-Distortion Ratio by 2.70 % to 35.32 % for different target signals, while the model size is only slightly increased, compared to other current solutions.
暂无评论