The article describes the results of developing a minimum viable product for the automatic sorting of municipal solid waste. A neural network model for detecting municipal solid waste was developed for automatic waste...
The article describes the results of developing a minimum viable product for the automatic sorting of municipal solid waste. A neural network model for detecting municipal solid waste was developed for automatic waste sorting. This neural network model has trained on the TACO (trash annotations in context) dataset, which was augmented with collected data from the Internet. A brief theory of neural networks is given: what is the object detection and how it is performed, the quality parameters of neural networks (metrics), which were used to increase the quality of the neural network model. Based on the analysis of the obtained metrics (precision, recall, f1-score), the best parameters for the developed neural network model are selected. Particular attention is paid to the prospects of using the detection of objects (municipal solid waste) to reduce the area of old and suspend the formation of new waste disposal sites (landfills). The consequences of the formation of landfills for both the environment and animals, including humans, are given. The degree of importance of the presented material is high for scientists and engineers of the countries, where the percentage of recyclable waste does not reach even 10%, as well as for novice developers of neural network models.
— In competitive adversarial environments, it is often advantageous to obfuscate one’s strategies or capabilities. However, revealing one’s strategic intentions may shift the dynamics of the competition in complex ...
The Electrical engineering undergraduate program of the Escola Politécnica of the Universidade de São Paulo has created an alternative innovative curriculum path for its freshmen students in 2024. The Compet...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
The Electrical engineering undergraduate program of the Escola Politécnica of the Universidade de São Paulo has created an alternative innovative curriculum path for its freshmen students in 2024. The Competency-based Path emphasizes the development of competencies and skills for the unprecedented technological advancements that necessitate a holistic education for future electrical engineers, preparing them with practical skills for real-world challenges. The program was designed using an innovative methodology and centers around semester-long or year-long integrative projects. These projects bridge the gap between theory and practice, as students deal with real-world challenges while fostering social responsibility.
This paper incorporates a continuous-type network flexibility into chance constrained economic dispatch (CCED). In the proposed model, both power generations and line susceptances are continuous variables to minimize ...
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Multimodal information-based broad and deep learning model(MIBDL) for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion under...
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Multimodal information-based broad and deep learning model(MIBDL) for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using different processing methods of deep network and broad network, which obtains the features of depth and width dimensions. Moreover, random mapping in the initial broad learning network could cause information loss and its shallow layer network is difficult to cope with complex tasks. To address this problem, we use principal component analysis to generate the nodes of the broad learning, and the stacked broad learning network is adapted to make it easier for the existing broad learning networks to cope with complex tasks by creating deep variations of the existing network. To verify the effectiveness of the proposal, experiments completed on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-theart methods. According to the simulation experiments on the FABO database, by using the proposed method, the multimodal recognition rate is 17,54%, 1.24%, and 0.23% higher than those of the temporal normalized motion and appearance features(TN),the multi-channel CNN(MCCNN), and the hierarchical classification fusion strategy(HCFS), respectively.
Flow and storage volume regulation is essential for the adequate transport and management of energy resources in district heating systems. In this letter, we propose a novel and suitably tailored-decentralized-adaptiv...
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Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1...
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ISBN:
(纸本)9781665480468
Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1) multi-temporal, multi-dimension, multi-score, and heterogeneous road data acquisition, and (2) road distress detection. This paper then summarizes the UDTIRI competition, organized in conjunction with IEEE Bigdata 2022. More details on our competition are available at ***/view/udtiri-workshop/bigdata-2022.
The presence of constraints often leads to the formation of narrow and fragmented feasible regions within the search region, presenting significant challenges for optimization problem-solving. This paper introduces a ...
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ISBN:
(数字)9798331534318
ISBN:
(纸本)9798331534325
The presence of constraints often leads to the formation of narrow and fragmented feasible regions within the search region, presenting significant challenges for optimization problem-solving. This paper introduces a novel approach, Feasible Regions Identification based on Historical Solutions (FRIHS), designed to address these challenges. FRIHS leverages previously evaluated solutions to partition the search region into ε-feasible and ε-infeasible regions. Additionally, by analyzing the correlations among constraints, they are reformulated as auxiliary objectives, effectively transforming the constrained optimization problem into a constrained multi-objective optimization problem. The method employs the classical evolutionary algorithm Differential Evolution and the multi-objective method NSGA-III to search the most promising feasible regions. The effectiveness of FRIHS is evaluated through a comparative analysis with five advanced constraint-handling algorithms across a benchmark test suite. Experimental results indicate that the proposed approach demonstrates competitive performance on the test problems.
In this paper we obtain a numerically tractable test (sufficient condition) for the exponential stability of the unique positive equilibrium point of an ODE system. The result (Theorem 3.1) is based on Lyapunov theory...
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A fuzzy model for estimating the impact of the IT project environment on its implementation is developed, the inputs of which are environmental factors, financial, human resources and the output is the completion of t...
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ISBN:
(数字)9781728167602
ISBN:
(纸本)9781728167619
A fuzzy model for estimating the impact of the IT project environment on its implementation is developed, the inputs of which are environmental factors, financial, human resources and the output is the completion of the project, which allows timely response to uncertain and risky situations for the project. The proposed fuzzy model can be used to effectively manage projects of various directions and make changes to their implementation in order to complete project work in a timely and successful manner.
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