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Recognition of disordered workpieces based on 3D Laser scanner and RS-CNN

Recognition of disordered workpieces based on 3D Laser scann...

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international symposium on distributed computing and applications to business, engineering and science (DCABES)

作者： Sikui He Bin Ye Huijun Li Yong Gao School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9781665454636

In industrial production, the disordered grasping operation of the robotic arm is mostly for grasping a single type of workpiece. Effective grasping is not easy when multiple overlapping workpieces are mixed together. The mutual occlusion between workpieces causes the loss of geometric shape information, which makes it difficult to obtain the precise grasping pose of each workpiece. In this paper, a 3D laser scanner is used to acquire the point cloud features of the workpiece. At first, the point clouds are filtered and segmented, and then they are input into the RS-CNN network for recognition and classification. According to the classification results, different models are used to register the point clouds in the scene. At last, the final pose of the workpiece to be grasped is obtained, which realizes the disorderly grasping of various workpieces.

关键词： Point cloud compression Visualization Three-dimensional displays Target recognition Shape Service robots Grasping

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Research Progress, Hot Spots and Prospects in the Field of Agricultural Innovation in China: - CiteSpace analysis based on 2258 articles 20

Research Progress, Hot Spots and Prospects in the Field of A...

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20th international symposium on distributed computing and applications for business engineering and science, DCABES 2021

作者： Zhu, Shuqi Lu, Qian Xiang, Yun School of Business Guilin University of Electronic Technology Guilin China Lingnan College Sun Yat-sen University Guilin China

ISBN: (纸本)9781665428897

Agricultural innovation is an important force driving the high-quality development of agriculture. Based on 2258 articles in China National Knowledge Infrastructure(CNKI) core journal database, and using Cite-Space software, we investigated the research progress, research hotspots and changes in the field of agricultural innovation in China from 2005 to 2020, trying to clarify the research trends and frontiers in the field of agricultural innovation. The results show that: The number of publications in the field of agricultural innovation in China presents an overall trend of 'increasing volatility in the early stage, a short-term decline in the medium-term, and a rapid rebound in the near term', but the cooperative research between authors and institutions is relatively weak;The hotspots of agricultural innovation research focus on technology Innovation, institutional innovation, innovation evaluation and modern agriculture, etc., and show phase characteristics;The evolution of research hot topics in the field of agricultural innovation in China reflects a strong background of the times. Therefore, in the future, interdisciplinary research will be a new hotspot and direction in the field of agricultural innovation. It is urgent to carry out systematic research on theories, methods, and applications, and strengthen the research on the integration of agricultural innovation and practice. © 2021 IEEE.

关键词： Agricultural technology

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Research on Detection Method of Abnormal Trajectory of Port Operation Vehicles 20

Research on Detection Method of Abnormal Trajectory of Port ...

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20th international symposium on distributed computing and applications for business engineering and science, DCABES 2021

作者： Li, Shuaihui Liu, Hongxing Yao, Hanbing School of Computer Science and Technology Wuhan University of Technology Wuhan China Hubei Provincial Key Laboratory of Transportation Internet of Things Technology Wuhan China

ISBN: (纸本)9781665428897

Port operation vehicles are mainly responsible for the transshipment of goods. If there is inadequate supervision in the process of transshipment it is easy to cause such behaviors as cargo leakage, cargo theft and illegal parking of drivers, which cause economic losses to the port. In order to discover such behaviors in time, the unsupervised anomaly detection algorithm Self-encoder-based Deep Feature Fusion Model(S-DFFM) is proposed to judge whether the trajectory of operation vehicles is abnormal or not. The method comprehensively characterizes the trajectory by fusing the shallow features of low-dimensional trajectory and the deep features of high-dimensional trajectory, which frees the trajectory from the limitation of spatial attributes. The experimental data adopts the real trajectory data of one month (7,547 trips) of operating vehicle trajectories of a port in Chongqing, and the experimental results show that S-DFFM can better represent the trajectory features, and the accuracy of trajectory abnormality detection using S-DFFM is as high as 96%. © 2021 IEEE.

关键词： Trajectories

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Research on Jamming Resource Allocation Based on Improved Pelican Optimization Algorithm

Research on Jamming Resource Allocation Based on Improved Pe...

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international symposium on distributed computing and applications to business, engineering and science (DCABES)

作者： Junwei Zhao Yian Liu Hailing Song Jiangnan University School of AI and Computer Science Wuxi China Naval Research Institute Beijing China

ISBN: (纸本)9781665454636

To get the best jamming effect of limited jamming resources in electronic warfare, this paper focuses on the problem of jamming resource allocation. An objective function of jamming resource allocation is built, which is based on the calculation by the probability formula of jammer pressing, and an improved Pelican Optimization Algorithm is designed. By simulating the pelican's natural behavior of approaching prey and searching the nearby area in the process of hunting, the algorithm creates the corresponding mathematical model, and obtains the global optimal allocation strategy by solving the model. The simulated results indicate that the probability of obtaining the optimal solution and optimal allocation strategy of the algorithm are better than the traditional Simulated Annealing Algorithm, whether it is the situation of “single jammer to single radar” or “multi-jammer to single-radar”.

关键词： Simulated annealing Radar Pressing Probability Linear programming Mathematical models Resource management

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Research on Demand Forecasting and Operation Model of Elderly Service Beds

Research on Demand Forecasting and Operation Model of Elderl...

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international symposium on distributed computing and applications to business, engineering and science (DCABES)

作者： Xinlong Li Zhirong Fan School of Information Science and Technology Fudan University Shanghai China

ISBN: (纸本)9781665454636

This paper predicts the number of elderly people over 65 years old in China by building a Logistic Model, and makes a reasonable prediction of the market demand scale of the number of elderly service beds per 1,000 users by GM(1,1) Grey Prediction Model. Then, we explore the operation mode from the government's perspective, and specifically explore the factors that may affect the operation of elderly service beds in the future through Analytic Hierarchy Process. We take the government subsidies, social employment, social contributions, operating income, and financing income as the main influencing factors, and give the proportion of each factor in the best mode, which provides a direction for the subsequent research on the operation mode of elderly service beds. Finally, this paper also gives some specific suggestions.

关键词： Computational modeling Government Sociology Transportation Transforms Predictive models Pensions

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Modification terms to the Black-Scholes model based on the functional volatility model 20

Modification terms to the Black-Scholes model based on the f...

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20th international symposium on distributed computing and applications for business engineering and science, DCABES 2021

作者： Lin, Xiaozheng Chen, Wei Wang, Meiqing Lai, Choi-Hong College of Mathematics and Computer Science Fuzhou University Fuzhou China University of Greenwich Department of Mathematics LondonSE10 9LS United Kingdom

ISBN: (纸本)9781665428897

The Black-Scholes model (B-S model) is a common used option pricing model, which assumes that the volatility and the interest rate are constants. However, the empirical analysis shows that the option prices obtained from the B-S model are quite different from the market prices. The traditional improve-ment to the B-S model is to replace the volatility constants or interest rate constants with variables. This paper proposes the concept of modification term of Black-Scholes model, which is different from the traditional methods. The errors of the B-S model may be calculated through the market data, and is fitted as a function of a functional implied volatility and the option gamma. The fitted function can be considered as the modification term of the Black-Scholes model. The functional implied volatility can be constructed by using the Gaussian semi-parametric implied volatility model proposed by Ref. [4]. Experimental results show that the modified model has a better predictive effect on option pricing. © 2021 IEEE.

关键词： Rate constants

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Active blanket jamming identification method based on rough set and decision tree

Active blanket jamming identification method based on rough ...

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international symposium on distributed computing and applications to business, engineering and science (DCABES)

作者： Jianghu Chen Yian Liu Hailing Song School of AI and Computer Science Jiangnan University Wuxi China Naval Research Institute Beijing China

ISBN: (纸本)9781665454636

Aiming at the classification or identification problem of active blanket jamming, a jamming identification method is proposed, which combines the upper approximation set, lower approximation set, border set theory of rough set and decision tree. The method first extracts the time-domain features of the signals, and divides the training set according to the degree of noise impact of the sample to train the decision tree respectively; then, the noise detection of the jamming signals is carried out by using the rough set theory; finally, the identification of three typical jamming patterns is realized through the decision tree. The comparison of simulation experiments shows that compared with the traditional method, this method has higher recognition accuracy, good real-time performance and noise robustness.

关键词： Training Rough sets Feature extraction Real-time systems Pattern recognition Noise robustness Decision trees

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Enhancing Smart City and IoT Solutions with Deep Residual Bi-LSTM Model

Enhancing Smart City and IoT Solutions with Deep Residual Bi...

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2023 international Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Madumidha, S. Chander Rao, S. Poorna Yadav, Sameer Hashmi, Syed Ghyasuddin Ahmad, Jorair Syed, Ziauddin Sri Krishna College of Technology Department of Information Technology Tamilnadu India Geethanjali College of Engineering and Technology Eee Department Telangana Hyderabad India University of Allahabad Department of Commerce and Business Administration Uttar Pradesh Prayagraj India College of Computer Science & Information Technology Jazan University Department of Information Technology & Security Jazan Saudi Arabia Information Technology & Security College of Computer Science and Information Technology Jazan University Jazan Saudi Arabia College of Computer Science and Information Technology Jazan University Department of Computer Science Jazan Saudi Arabia

ISBN: (纸本)9798350300857

There is a limitless supply of useful information and services made available by IoT devices connected to the internet. The Internet of Things (IoT) refers to the vast network of interconnected devices seen in a smart city. The scattered and dynamic natures of entities such as sensing, actuating devices, humans, and computing resources make it challenging to design applications in such large-scale IoT systems, despite the promise nature of the new breed of data and resources. In this research study, the proposed approach takes a coordinated look at the process of creating Internet of Things apps for use in Smart Cities. The proposed approach demonstrates the need for a distributed coordination model capable of monitoring such a vast number of independently operating parts while constructing Smart City IoT applications. Preprocessing, feature selection, and model performance evaluation are all used in the suggested method. Normalization and standardization are used during preprocessing. It uses entropy HOA for feature selection. The model's effectiveness is measured with Deep Residual Bi-LSTM. When compared to BiLSTM and Residual LSTM, two existing approaches, the suggested methodology performs admirably. © 2023 IEEE.

关键词： Standardization

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Personalized Privacy-Preserving Information Fusion in Mobile Crowdsensing 20

Personalized Privacy-Preserving Information Fusion in Mobile...

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20th IEEE international symposium on Parallel and distributed Processing with applications, 12th IEEE international Conference on Big Data and Cloud computing, 12th IEEE international Conference on Sustainable computing and Communications and 15th IEEE international Conference on Social computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2022

作者： Feng, Zheqi Peng, Tao Wang, Guojun Guan, Kejian Guangzhou University Shool of Computer Science and Cyber Engineering Guangzhou510006 China

ISBN: (纸本)9781665464970

In mobile crowdsensing (MCS), information fusion is necessary to obtain data aggregation results. In information fusion, most of the existing personalized mechanisms only consider meeting the personalized requirements of data collectors and rarely consider the potential personalized requirements of data users. Furthermore, how to provide personalized data aggregation results for data users with different data quality requirements has not been addressed. This paper proposes a personalized privacy-preserving information fusion (P3IF) mechanism based on the personalized sampling mechanism in the MCS. P3IF provides personalized data aggregation results for data users with different data quality requirements while ensuring personalized privacy protection for data collectors. Specifically, we design a personalized privacy-preserving information fusion scheme based on the personalized differential privacy mechanism. Considering on the privacy requirements of the data collectors, we conduct personalized privacy sampling on the raw data from the data collectors and obtain a subset of sensing data. According to the data quality requirements of data users and the quality of each data, the obtained subset is sampled for personalized data quality requirements, and the final data set is obtained. Simulation experiments verify the feasibility and effectiveness of P3IF. © 2022 IEEE.

关键词： Privacy-preserving techniques

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Improved BiLSTM Model For Online Food Safety Risk Prediction 20

Improved BiLSTM Model For Online Food Safety Risk Prediction

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20th international symposium on distributed computing and applications for business engineering and science, DCABES 2021

作者： Zhang, Zekai Li, Mao Sun, Jun Chen, Qidong School Of Artificial Intelligence and Computer Science Jiangnan University WuXi China

ISBN: (纸本)9781665428897

The prediction of security risk is a new problem in the field of modeling. The value of food safety risk is dynamic, non-linear and non-stationary. In order to improve the prediction accuracy of non-stationary sequences, this paper proposes an improved time series prediction model of bidirectional long short-term memory network based on NS-ADAM optimization algorithm. By using NS-ADAM optimization algorithm, the non-stationary series can be approximately regarded as stationary series in a fixed window length. Combined with the advantages of two-way long-term and short-term network model to strengthen the correlation between current data and historical data, the combined network model significantly improves the prediction accuracy of non-stationary time series. The experimental results show that compared with the traditional integrated moving average autoregressive model and the conventional long-term and short-term memory network model, the improved model has higher prediction accuracy and better fitting effect for non-stationary series. © 2021 IEEE.

关键词： Food safety

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