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A Method for Quantifying Data Utility in Privacy-Preserving Scenarios 2

A Method for Quantifying Data Utility in Privacy-Preserving ...

引用

2nd ieee International conference on Electrical, automation and Computer engineering, ICEACE 2024

作者： Du, Haofeng Liu, Jianxiong Aerospace Science & Industry Network Information Development Co. Ltd The 2nd Institute of China Aerospace Science & Industry Corporation Beijing China Development Co. Ltd Aerospace Science & Industry Network Information Beijing China

ISBN: (纸本)9798350368208

Data masking is a critical component in the realm of data security, playing a significant role in preventing the involuntary disclosure of private information within data and ensuring that data is used legally. However, data masking achieves security by obfuscating the information contained in the original data, which can lead to a decrease in data usability while safeguarding it. To mitigate the negative impacts of data masking, we have devised a novel quantitative method for assessing the usability of masked data, termed QM-ADUGN (Quantitative Method for Masked Data Usability with Generalization and Noise). This method targets two common masking techniques, data generalization and noise addition, and quantifies data usability from two perspectives: accuracy and complexity. We have also designed experiments to validate the effectiveness of this usability quantification method. The experimental results indicate that the Pearson correlation coefficient between the quantification results and the actual usability of the data exceeds 0.8 in various scenarios, demonstrating a very strong correlation. Therefore, this quantification method can effectively reflect the true usability of the data. © 2024 ieee.

关键词： Differential privacy

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Enhancing Cancer Prediction: Investigating ACO-Based Feature Selection with Logistic Regression, XGBoost, and LightGBM 2

Enhancing Cancer Prediction: Investigating ACO-Based Feature...

引用

2nd ieee International conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Chidurala, Ashwini Basani, Shashanka Mulastam, Pranavi Nerella, Sanjay Srivastav, Shashank Dwivedi, Anshu Kumar SR University School of Computer Science and Artificial Intelligence Warangal India Buddha Institute of Technology Gida Department of Computer Science and Engineering Gorakhpur India Bennett University School of Computer Science Engineering and Technology Greater Noida India

ISBN: (纸本)9798350368109

This report mainly concentrates on cancer prediction, particularly focusing on breast cancer prediction, which remains a significant challenge in healthcare. Improving patient outcomes requires early identification and machine learning approaches have enough opportunities in this area to improve the predicting capabilities. Feature selection plays a vital role in developing accurate predictive models, and this study investigates the effectiveness of Ant Colony Optimization (ACO) in enhancing feature selection for three commonly used machine learning algorithms: Logistic Regression, XGBoost, and LightGBM. The report begins with an introduction highlighting the importance of early cancer detection and the role of machine learning techniques in achieving the goal. Then presents a comprehensive literature review, summarizing previous research papers on cancer detection and classification using various machine learning approaches, with and without implementing ACO. The proposed methodology outlines the steps followed in the research process, from importing necessary libraries to evaluating the performance of machine learning models. © 2024 ieee.

关键词： Adversarial machine learning

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Slot-Based Object-Centric Reinforcement Learning Algorithm 14

Slot-Based Object-Centric Reinforcement Learning Algorithm

引用

14th ieee International conference on Cyber Technology in automation, Control, and Intelligent Systems, CYBER 2024

作者： Chen, Chao Wang, Fei Wang, Xinyao Northeastern University Faculty of Robot Science and Engineering China Northeastern University Faculty of Robot Science and Engineering Liaoning Shen Yang China Bussiness School Liaoning University China

ISBN: (纸本)9798331506056

With the development of reinforcement learning algorithms, it has become capable of handling a wide variety of complex tasks in simulated environments. However, applying reinforcement learning algorithms to real-world tasks still faces significant challenges. When facing vision-based tasks, these algorithms often embed images into a unified representation, which is effective for most simple tasks but inefficient when dealing with tasks involving interactions between multiple objects. This inefficiency arises from the lack of prior information about the world, neglecting the fundamental characteristic that the world is composed of multiple objects. This paper proposes an algorithm called SOCRL (Slot Based Object-Centric reinforcement learning), which enhances the efficiency of reinforcement learning algorithms in multi-object tasks by decoupling images into independent components. Experimental results demonstrate that our algorithm exhibits better generalization and higher sample efficiency compared to previous algorithms. © 2024 ieee.

关键词： Adversarial machine learning

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Research on Planting Planning Strategies Based on Optimization Genetic Algorithms under Multiple Constraints 2

Research on Planting Planning Strategies Based on Optimizati...

引用

2nd ieee International conference on Electrical, automation and Computer engineering, ICEACE 2024

作者： Li, Jianxin Gao, Dechao Qiu, Zeshan Wang, Lizan Xinjiang University of Political Science and Law School of Information Network Security Tumushuke China

ISBN: (纸本)9798350368208

This paper presents a study on planting planning strategies based on optimization genetic algorithms under multiple constraints. The research focuses on establishing a linear programming model with the decision variable of the acreage of crop p planted in seasons of year y on plot l, with the maximization of yield as the optimization objective. An optimized genetic algorithm is designed for solving this model. The optimization method introduces a multi-matrix encoding scheme tailored to enhance the decoding efficiency of chromosomes specific to the problem studied in this paper. Additionally, a repair scheme for infeasible solutions is devised to address the multi-constraint nature of the problem. Finally, two surplus disposal scenarios are considered for the solution, demonstrating that the designed optimization genetic algorithm effectively solves the model. The results show that the algorithm progressively converges to the optimal solution during iterations, reaching a stable state after a relatively low number of iterations. © 2024 ieee.

关键词： Genetic algorithms

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Boolean Matching Reversible Circuits: Algorithm and Complexity 24

Boolean Matching Reversible Circuits: Algorithm and Complexi...

引用

61st ACM/ieee Design automation conference, DAC 2024

作者： Chen, Tian-Fu Jiang, Jie-Hong Roland Graduate School of Advanced Technology National Taiwan University Taipei Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Center for Quantum Science and Engineering National Taiwan University Taipei Taiwan Physics Division National Center for Theoretical Sciences Taipei Taiwan

ISBN: (纸本)9798400706011

Boolean matching is an important problem in logic synthesis and verification. Despite being well-studied for conventional Boolean circuits, its treatment for reversible logic circuits remains largely, if not completely, missing. This work provides the first such study. Given two (black-box) reversible logic circuits that are promised to be matchable, we check their equivalences under various input/output negation and permutation conditions subject to the availability/unavailability of their inverse circuits. Notably, among other results, we show that the equivalence up to input negation and permutation is solvable in quantum polynomial time, while its classical complexity is exponential. This result is arguably the first demonstration of quantum exponential speedup in solving design automation problems. Also, as a negative result, we show that the equivalence up to both input and output negations is not solvable in quantum polynomial time unless UNIQUE-SAT is, which is unlikely. This work paves the theoretical foundation of Boolean matching reversible circuits for potential applications, e.g., in quantum circuit synthesis. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Polynomial approximation

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HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements Classification from Motor Imagery EEG 3

HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements C...

引用

3rd ieee International conference on Robotics, automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Hasan, Tasnimul Hossain, A.B.M. Aowlad Biswas, Shuvagata Tazrin, Farhana Khulna University of Engineering & Technology Department of Biomedical Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Electronics and Communication Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Computer Science and Engineering Khulna9203 Bangladesh

ISBN: (纸本)9798331534400

Motor imagery-based BCI plays a vital role in controlling hand movements by processing and recognizing features from EEG signals associated with the imagination of those movements. In this paper, we present a Kolmogorov-Arnold Networks (KAN) based framework in order to classify the left and right-hand movements along with the absence of movement's intention from the electroencephalogram (EEG) signal. The emergence of KAN is expected to be a breakthrough concept in the artificial intelligence paradigm considering its learnable activation functions mechanism and interpretability opportunities. Preprocessing of the collected raw EEG data has been accomplished with band-pass filtering of EEG components of five well-matched channels and corresponding power spectral density feature extraction. We have used 15282 samples with annotated classes from a publicly available dataset to train, validate, and test the classifier. A comparative analysis of the performance of KAN and conventional Multi-Layer Perceptron (MLP) networks has been conducted in order to investigate the effectiveness of the KAN for this classification task. The proposed framework attains 96.14% classification accuracy for 3057 blind test samples, which is found to be better than the conventional MLP neural network approach (76.64% accuracy) and compatible with the existing techniques. The finding of this research might be useful in hand movement-related applications for robotics, prosthetics, and neuro-rehabilitation supports. © 2024 ieee.

关键词： Multilayer neural networks

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Architecture Design and Application Research of Software-Defined Distribution Smart Terminal 4

Architecture Design and Application Research of Software-Def...

引用

4th International conference on Energy engineering and Power Systems, EEPS 2024

作者： Xiong, Haijun Lan, Saidi Li, Yahan Zhang, Yizhi Shenke Technology Group Co. Ltd. Shijiazhuang China North China Electric Power University Department of Computer Science Baoding China

ISBN: (纸本)9798350366914

The interconnection and interoperability between distribution network automation terminals can improve cross-domain and cross-application collaboration efficiency. Traditional terminals find it challenging to meet the demands of new distribution networks. This paper proposes a design scheme for distribution network automation terminals based on software-defined concepts. Combining the 'software-defined' idea, the concept of software-defined distribution network automation terminals is proposed. Based on the analysis of the general structure of distribution network automation terminals, the terminal system structure is divided into the device layer, control layer, and application layer. The southbound interface between the device layer and the sensor layer and the northbound interface between the application layer and the substation layer are defined. The functions and implementation schemes of each layer and interface are detailed. The software-defined implementation of distributed synchronous acquisition and fault diagnosis terminals is provided, and experiments verify the feasibility and advantages of the proposed scheme. © 2024 ieee.

关键词： Application programs

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Improving the Music Harmony Search Using a Differential Exploration Phase for Solving Bound Constrained Optimization Problems 7

Improving the Music Harmony Search Using a Differential Expl...

引用

7th ieee Information Technology, Networking, Electronic and automation Control conference, ITNEC 2024

作者： Sun, Sha Zhao, Ruihan Wang, Chenxi Tang, Zheng Tao, Sichen Hujiang College University of Shanghai for Science and Technology Shanghai200093 China School of Engineering and Design Technical University Munich Garching85748 Germany School of Mechanical Engineering Tongji University Shanghai200082 China Chemnitz University of Technology Faculty of Electrical Engineering and Information Technology ChemnitzD-09111 Germany University of Toyama Faculty of Engineering Toyama930-8555 Japan

ISBN: (纸本)9798350370782

Very frequently, when solving a complex optimization problem, one is confronted that it comes from an NP-hard class, which means high difficulty to get the optimal solution. As an approximate optimization technology, meta-heuristics are good substitutions for conventional mathematics-based deterministic technology because it can provide acceptable solutions in reasonable computational time. As one of the classical meta-heuristics technology, harmony search (HS), inspired by music composition process, shows effectiveness in solving NP-hard complex optimization problems in a variety of research and practical fields, while it has a unique iteration paradigm. However, in recent 2 decades of years, the theoretical test and researches on harmony search are not sufficiently conducted. In this paper, we propose an improved harmony search (iHS) with a differential exploration phase and test its effectiveness and efficiency on the 2024 congress of evolutionary computation (CEC2024) competition benchmark test suite. Comparing with various classical and new proposed meta-heuristics, The experimental results demonstrate that iHS possesses better performance which shows its considerable potentials to be adequately developed in the future. © 2024 ieee.

关键词： Constrained optimization

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Study on Seeding Weight Detection Device of Rice Seedling Production Line 7

Study on Seeding Weight Detection Device of Rice Seedling Pr...

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7th ieee Information Technology, Networking, Electronic and automation Control conference, ITNEC 2024

作者： Dong, Wenhao He, Jing Ji, Chuandong Cao, Xiaoman Zhang, Xiaoya School of Mechanical and Electrical Engineering Guangdong Polytechnic of Industry and Commerce Guangzhou China College of Engineering South China Agricultural University Guangzhou China

ISBN: (纸本)9798350370782

At present, it is mainly by manual labor to measure and adjust the sowing amount during the working of rice seedling raising production line. By manual monitoring method, the labor intensity of workers is high, and the workers cannot adjust the sowing amount timely. So the error rate of the sowing amount is high, and this restricts the production efficiency of industrialized seedling production line In order to solve this problem, an automatic weighing device for the sowing amount in seedling tray on rice seedling production line is developed. The weighing device combined dynamic transport of trays and static weighing method. An experiment was carried out with the weighing device, and the results of the experiment shows that the weight accuracy of the device is over 99.79% at low seeding rate (40g80g/ tray);The weighing accuracy is over 99.92% at large sowing rate (100g-120g/tray). The accuracy of the detection can meet the requirements of rice seedling production lines, and the detection device can effectively improve the automation and production efficiency of rice seedling production lines. © 2024 ieee.

关键词： seeding performance seeding quantity seeding quantity regulation seedling production line

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Iterative Risk Aware PRM Path Planning Algorithm for Autonomous Unknown Environments Exploration 10

Iterative Risk Aware PRM Path Planning Algorithm for Autonom...

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10th International conference on automation, Robotics, and Applications, ICARA 2024

作者： Bana, Fatemeh Rekabi Alsayed, Ahmad Krajnik, Tomas Arvin, Farshad Durham University dept. Computer Science Durham United Kingdom University of Manchester dept. Mechanical Engineering Manchester United Kingdom Artificial Intelligence Center Czech Technical University Prague Czech Republic

ISBN: (纸本)9798350394245

Autonomous area exploration is a critical application for various robotic systems, with micro-drones being particularly suited due to their high manoeuvrability and reliability. However, their limited operational time and computational power pose challenges for effective exploration. This paper introduces a risk-aware path-planning algorithm for micro-drones, pri-oritising energy efficiency by minimising travel distance. The algorithm, utilizing Monte-Carlo simulations and a risk-aware Probabilistic Roadmap (PRM) method, discretises the workspace and constructs a topological PRM graph to mitigate collisions. Simulation results demonstrate the algorithm's performance in unknown environments, approaching ideal exploration in known areas. Field experiments with Crazyflie micro-drones validate its practical implementation, enabling micro-drones to navigate unknown environments with an acceptable collision risk for efficient exploration in resource-constrained spaces. © 2024 ieee.

关键词： Drones

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