Three kinds of air-cooling systems and their technical features have been described in this paper. Combined with the energy policy in our country, the perspective of air-cooling unit is discussed mainly in terms of co...
详细信息
Three kinds of air-cooling systems and their technical features have been described in this paper. Combined with the energy policy in our country, the perspective of air-cooling unit is discussed mainly in terms of coal-fired unit applied status, air cooling unit's development and our country's energy policy etc. And the matters needing attention and the needed taken measures in the conscientions improvement of air-cooling unit by the power enterprises are put forward.
The escalating challenges faced by the agricultural industry, characterized by labor shortages, and rising costs, underscore the imperative for innovative solutions. This study explores the transformative potential of...
The escalating challenges faced by the agricultural industry, characterized by labor shortages, and rising costs, underscore the imperative for innovative solutions. This study explores the transformative potential of Intelligent Harvesting Systems in revolutionizing fruit harvesting, with a focus on assessing feasibility and understanding implications within the fruit industry. The integration of cutting-edge technologies, specifically 5G communication and artificial intelligence (AI), plays a pivotal role in the design and evaluation of a control module for an agricultural picking robot. The feasibility assessment encompasses an in-depth exploration of the technological, economic, operational, and environmental. Experimental evaluations conducted in controlled environments and real-world settings showcase the system's high picking speed, accuracy, and adaptability to diverse produce sizes. The outcomes of this research not only align with the initial objectives of enhancing harvesting efficiency and reducing labor costs but also hold promise for a sustainable and resource-efficient agricultural future. The positive synergy between 5G communication and AI technology emerges as a driving force behind the system's exceptional performance. This study not only contributes to the immediate advancements in intelligent harvesting but also lays a robust foundation for continued innovation, setting the stage for further exploration and refinement in this dynamic field.
In developing nano-devices and nano-structures, traditional methodologies on MEMS meet the difficulty from the scale restriction. With the strategy of objects assembly, using AFM to handle nano-rods and other nano-obj...
详细信息
Implicit neural networks (INNs) are a class of learning models that use implicit algebraic equations as layers and have been shown to exhibit several notable benefits over traditional feedforward neural networks (FFNN...
详细信息
ISBN:
(数字)9781665467612
ISBN:
(纸本)9781665467629
Implicit neural networks (INNs) are a class of learning models that use implicit algebraic equations as layers and have been shown to exhibit several notable benefits over traditional feedforward neural networks (FFNNs). In this paper, we use interval reachability analysis to study robustness of INNs and compare them with FFNNs. We first introduce the notion of tight inclusion function and use it to provide the tightest rectangular over-approximation of the neural network’s input-output map. We also show that tight inclusion functions lead to sharper robustness guarantees than the well-studied robustness measures of Lipschitz constants. Like exact Lipschitz constants, tight inclusions functions are computationally challenging to obtain, and thus we develop a framework based upon mixed monotonicity and contraction theory to estimate the tight inclusion functions for INNs. We show that our approach performs at least as well as, and generally better than, state-ofthe-art interval-bound propagation methods for INNs. Finally, we design a novel optimization problem for training robust INNs and we provide empirical evidence that suitably-trained INNs can be more robust than comparably-trained FFNNs.
The Unscented Particle Filter and Cam Shift(Continuously adaptive mean shift) are two successful approaches for the object tracking in video surveillance systems. We focus on the tracking performance of both algorithm...
详细信息
The Unscented Particle Filter and Cam Shift(Continuously adaptive mean shift) are two successful approaches for the object tracking in video surveillance systems. We focus on the tracking performance of both algorithms and explore more intrinsic relationship between Cam Shift and Unscented Particle Filter(CAMSGUPF). Our proposed algorithm provides better sampling by shifting samples to their neighboring modes, passing over the degeneracy problem, and involves fewer particles to maintain multiple hypotheses. We used the Root Mean Square Error(RMSE) to compare our algorithm with traditional "Cam Shift guided particle filter". Experimental results prove that our proposed algorithm has better performance than traditional method according to the degree of applicability.
In video-based point cloud compression (V-PCC), one geometry video and one color video are generated from a dynamic point cloud. Then, the two videos are compressed independently using a state-of-the-art video coder. ...
详细信息
ISBN:
(纸本)9781665432894
In video-based point cloud compression (V-PCC), one geometry video and one color video are generated from a dynamic point cloud. Then, the two videos are compressed independently using a state-of-the-art video coder. In the Moving Picture Experts Group (MPEG) V-PCC test model, the quantization parameters for a given group of frames are constrained according to a fixed offset rule. For example, for the low-delay configuration, the difference between the quantization parameters of the first frame and the quantization parameters of the following frames in the same group is zero by default. We show that the rate-distortion performance of the V-PCC test model can be improved by lifting this constraint and considering the ratedistortion optimization problem as a multi-variable constrained combinatorial optimization problem where the variables are the quantization parameters of all frames. To solve the optimization problem, we use a variant of the differential evolution algorithm. Experimental results for the low-delay configuration show that our method can achieve a Bjøntegaard delta bitrate of up to -43.04% and more accurate rate control (average bitrate error to the target bitrate of 0.45% vs. 10.75%) compared to the state-of- the-art method, which optimizes the rate-distortion performance subject to the test model default offset rule. We also show that our optimization strategy can be used to improve the rate-distortion performance of two-dimensional video coders.
Hand-foot-mouth disease (HFMD) has gradually become prevalent in mainland China since the first official report in 2008. The incidence of HFMD is increasing among children mainly aged zero to five. Thus how to monitor...
Hand-foot-mouth disease (HFMD) has gradually become prevalent in mainland China since the first official report in 2008. The incidence of HFMD is increasing among children mainly aged zero to five. Thus how to monitor and prevent HFMD is becoming an important public health challenge. This study aims to build a forecasting framework of HFMD for two Chinese cities, Chengdu in Sichuan Province and Guangdong in Guangzhou Province based on LSTM, by utilizing clinical data of HFMD, meteorological factors, and Baidu index data. Our method achieves significant results
The identification of wind turbine abnormal data is the basis for subsequent wind power prediction and health assessment of wind turbine. This paper analyzes the characteristics of wind turbine abnormal data in detail...
详细信息
ISBN:
(纸本)9781665478977
The identification of wind turbine abnormal data is the basis for subsequent wind power prediction and health assessment of wind turbine. This paper analyzes the characteristics of wind turbine abnormal data in detail, and designs the MKIF (Mini batch K Means-Isolation Forest) algorithm to realize the identification of abnormal data of wind turbine. The MKIF algorithm introduces Mini batch K Means clustering into the partition process of the Isolation Forest search tree, and use Silhouette Coefficient to supervise the number and location of the split nodes of the tree. The MKIF anomaly score is defined to describe the degree of isolation of the data, which can effectively identify and eliminate abnormal data and use normal data to establish the main power band. Taking the actual operating data of two wind turbines as an example, the effectiveness of the MKIF abnormal data identification algorithm is verified.
Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of o...
详细信息
Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.
暂无评论