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arXiv 2022年

作者： Tong, Lyuyang National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence School of Computer Science Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan China Department of Computer Science City University of Hong Kong Hong Kong

Optimal experimental design is an essential subfield of statistics that maximizes the chances of experimental success. The D- and A-optimal design is a very challenging problem in the field of optimal design, namely minimizing the determinant and trace of the inverse Fisher information matrix. Due to the flexibility and ease of implementation, traditional evolutionary algorithms (EAs) are applied to deal with a small part of experimental optimization design problems without mathematical derivation and assumption. However, the current EAs remain the issues of determining the support point number, handling the infeasible weight solution, and the insufficient experiment. To address the above issues, this paper investigates differential evolution (DE) variants for finding D- and A-optimal designs on several different statistical models. The repair operation is proposed to automatically determine the support point by combining similar support points with their corresponding weights based on Euclidean distance and deleting the support point with less weight. Furthermore, the repair operation fixes the infeasible weight solution into the feasible weight solution. To enrich our optimal design experiments, we utilize the proposed DE variants to test the D- and A-optimal design problems on 12 statistical models. Compared with other competitor algorithms, simulation experiments show that LSHADE can achieve better performance on the D- and A-optimal design problems. Copyright © 2022, The Authors. All rights reserved.

关键词： Evolutionary algorithms

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KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

arXiv

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arXiv 2024年

作者： Tao, Wei Zhou, Yucheng Wang, Yanlin Zhang, Hongyu Wang, Haofen Zhang, Wenqiang Shanghai Engineering Research Center of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China School of Software Engineering Sun Yat-sen University Guangdong Zhuhai519082 China School of Big Data and Software Engineering Chongqing University Chongqing China College of Design and Innovation Tongji University Shanghai China Engineering Research Center of AI and Robotics Ministry of Education Academy for Engineering and Technology Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University 220 Handan Road Shanghai200433 China

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i.e., good-practice commits), while the rest do not. On the basis of our empirical study, we discover that training on good-practice commits significantly contributes to the commit message generation. Motivated by this finding, we propose a novel knowledge-aware denoising learning method called KADEL. Considering that good-practice commits constitute only a small proportion of the dataset, we align the remaining training samples with these good-practice commits. To achieve this, we propose a model that learns the commit knowledge by training on good-practice commits. This knowledge model enables supplementing more information for training samples that do not conform to good practice. However, since the supplementary information may contain noise or prediction errors, we propose a dynamic denoising training method. This method composes a distribution-aware confidence function and a dynamic distribution list, which enhances the effectiveness of the training process. Experimental results on the whole MCMD dataset demonstrate that our method overall achieves state-of-the-art performance compared with previous methods. © 2024, CC BY.

关键词： Sampling

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Uav Digital Twin Open-Source Framework: Case of Study Remote Sensing in the Andean Mountains

SSRN

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SSRN 2024年

作者： Valencia, Esteban Toapanta, Francisco Oña, Gabriel Carrillo, Andrey Aláez, Daniel Loyaga, Erick Chamorro, Willian Cruz, Patricio Abad, Jackeline Laboratory of UAS ATA Research Group Mechanical Engineering Department Escuela Politécnica Nacional Quito Ecuador Department of Statistics Computer Science and Mathematics Universidad Pública de Navarra Pamplona31006 Spain Institute of Smart Cities Universidad Pública de Navarra Pamplona31006 Spain

The increasing demand for Unmanned Aerial Vehicles (UAVs) in the aerospace industry emphasizes the need for accurate simulation environments, especially in difficult access regions, where reliability, high trustworthiness, and fail-proof designs are crucial. This study develops an opensource framework for a customized simulation environment for UAVs, using ROS- Gazebo tools combined with Ardupilot. The method comprises a realistic environment reconstruction based on free satellite information, ROS-Gazebo scheme for modeling and testing of the UAV platform and Ardupilot for the mission design and deployment. The methodology seeks to decrease the costs associated with monitoring missions and make more efficient operations in areas with risky and difficult *** order to evaluate the accuracy of the positioning of the UAV the method to simulate real missions, an experimental validation of the digital twin was conducted using real flight data logs from two self-built UAVs equipped with an open-source autopilot implemented on a Pixhawk Cube flight controller. One of the aircraft used to assess the performance of the proposed methodology was of the fixed-wing type. Its flight tests were conducted in the vicinity of the Antisana volcano (4500 masl), where wind gusts reach speeds between 9 and 12 m/s. Through these flight tests, the potential of the developed methodology was successfully validated, revealing maximum errors of 9% in the trajectory along the Z-axis (altitude). The other aircraft used was a quadcopter, and its flight tests took place in Carolina Park in the city of Quito (2800 masl), where wind gusts range between 5 and 7 m/s. These tests under less challenging conditions confirmed the potential of the method developed and allowed to test its versatility. For the quadcopter case an error of 8% in the trajectory along the Z-axis (altitude) was calculated. The results presented highlight the suitability of the proposed method for emulating complex missio

关键词： Fixed wings

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Fuzzy Sandwich Control of Some Nonlinear Systems with a Number of Stochastically Occurring Impulses 13

Fuzzy Sandwich Control of Some Nonlinear Systems with a Numb...

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13th International Conference on Information science and Technology, ICIST 2023

作者： Onasanya, Babatunde Oluwaseun Dai, Xiangguang Feng, Yuming Zhang, Wei School of Computer Science and Engineering Chongqing Three Gorges University Chongqing Wanzhou404100 China Department of Mathematics University of Ibadan Ibadan200284 Nigeria Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Chongqing Wanzhou404100 China Three Gorges Institute of Artificial Intelligence Chongqing Three Gorges University Chongqing Wanzhou404100 China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Chongqing Wanzhou404100 China

ISBN: (纸本)9798350313925

In this paper, rather than have a fixed constant matrix in the sandwich control of the nonlinear system, a fuzzy control matrix was used. In addition, simple inequalities that do not require additional computational time and skills in computer programming were used rather than the usual LMI. The result of this method is that the period T required in the control process is shorter and the control time is also reached much faster or reduced compared to the existing sandwich methods that used constant matrices. In other words, the control time of this method is shorter than the control time achieved when using constant matrices. Besides, this method also can be used to control more nonlinear chaotic systems such as Lorenz's, Rössler's and Chen's systems. Numerical simulations were used to demonstrate the effectiveness of this method. © 2023 IEEE.

关键词： Nonlinear systems

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Biomedical data and AI

引用

science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Detection of brain tumor and identification of tumor region using deep neural network on FMRI images 19

Detection of brain tumor and identification of tumor region ...

引用

19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Mashiat, Afsara Akhlaque, Reza Rifat Fariha, Fahmeda Hasan Reza, Tanzim Rahman, Md Anisur Parvez, Mohammad Zavid Brac University Software Engineering and HCI Research Group Department of Computer Science and Engineering Bangladesh Charles Sturt University School of Computing and Mathematics Australia

ISBN: (纸本)9780738124261

As brain is the most vital organ of the human body, the affects of brain related diseases can be severe. One of the most harmful diseases is brain tumor, which results in a very short life expectancy of the affected patient. Detection of brain tumor is a challenging task in the early stages. Still, with the help of modern technology and machine learning algorithms, it has become a matter of great interest for research. While detecting the brain tumor of an affected person, we are considering the fMRI data of the patient. Our aim is to identify whether the tumor is present in the patient's brain or not. We use a Convolutional Neural Network(CNN) that is good enough to generate high accuracy. We have used some deeper architecture design VGG16, VGG19, and Inception v3 for better accuracy. Three classification techniques are used namely binary classification, lobe based classification, and position based classification. The main contribution of our proposed work is that we have identified the specific region of the brain where the tumor is located. The region-based classification distinguishes our work from others that are applied on the same dataset. For binary classification, we found approximately 95% accuracy from all the three architectures. Furthermore, we found approximately 78% accuracy for lobe based classification and approximately 97% accuracy for position based classification. The experimental results indicate the superiority of our proposed method in terms of identifying the brain tumor. © 2020 IEEE.

关键词： Brain

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Comparative study for different types of mppt algorithms using direct control method 1

引用

2nd International Conference on Electrical and Electronics engineering, ICEEE 2021

作者： Shams, Immad Mohammed, Karam Khairullah Mekhilef, Saad Tey, Kok Soon Power Electronics and Renewable Energy Research Laboratory Department of Electrical Engineering Faculty of Engineering Kuala Lumpur50603 Malaysia Control and Mechatronics Engineering Department School of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru81310 Malaysia School of Software and Electrical Engineering Faculty of Science Engineering and Technology Swinburne University of Technology MelbourneVIC3122 Australia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

ISBN: (数字)9789811607493

ISBN: (纸本)9789811607486

Maximum power point tracking (MPPT) controllers achieve higher importance due to the high expansion rate of photovoltaic systems. The probability of partial shading conditions (PSCs) is also increased which drastically reduced the maximum power extraction capability from PV systems. In this paper, different types of MPPT algorithms using direct control method have been examined under the same test conditions. The current research trend on MPPT controllers has also been highlighted. This paper gives a brief description to engineers and practitioners working in the area of MPPT controllers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Controllers

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Hierarchical Graph Modeling for Multi-Scale Optimization of Power Systems

arXiv

引用

arXiv 2023年

作者： Cole, David L. Gangammanavar, Harsha Zavala, Victor M. Department of Chemical and Biological Engineering University of Wisconsin-Madison MadisonWI United States Operations Research and Engineering Management Southern Methodist University DallasTX United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States

Hierarchical optimization architectures are used in power systems to manage disturbances and phenomena that arise at multiple spatial and temporal scales. We present a graph modeling abstraction for representing such architectures and an implementation in the Julia package ***. We apply this framework to a tri-level hierarchical framework arising in wholesale market operations that involves day-ahead unit commitment, short-term unit commitment, and economic dispatch. We show that graph abstractions facilitate the construction, visualization, and solution of these complex problems. © 2023, CC BY.

关键词： Graph theory

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Optimization techniques for modeling with piecewise-linear functions

arXiv

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arXiv 2025年

作者： Dobrovoczki, Péter Kis, Tamás Engineering and Management Intelligence Research Laboratory HUN-REN Institute for Computer Science and Control Kende utca 13-17 Budapest1111 Hungary Department of Operations Research Institute of Mathematics Eötös Loránd University Pázmány Péter sétány 1/C Budapest1117 Hungary

In this paper we aim to construct piecewise-linear (PWL) approximations for functions of multiple variables and to build compact mixed-integer linear programming (MILP) formulations to represent the resulting PWL function. On the one hand, we describe a simple heuristic to iteratively construct a triangulation with a small number of triangles, while decreasing the error of the piecewise-linear approximation. On the other hand, we extend known techniques for modeling PWLs in MILPs more efficiently than state-of-the-art methods permit. The crux of our method is that the MILP model is a result of solving some hard combinatorial optimization problems, for which we present heuristic algorithms. The effectiveness of our techniques is demonstrated by a series of computational experiments including a short-term hydropower scheduling problem. Copyright © 2025, The Authors. All rights reserved.

关键词： Integer linear programming

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Detection of stress for visually impaired people using EEG signals based on time-frequency domain analysis 19

Detection of stress for visually impaired people using EEG s...

引用

19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Sultana, Samia Rahman, Md Anisur Zavid Parvez, Mohammad BRAC University Software Engineering and HCI Research Group Department of Computer Science and Engineering Bangladesh Charles Sturt University School of Computing and Mathematics Australia

ISBN: (纸本)9780738124261

Stress refers to body's physical, emotional and psychological reaction to any environmental change needing adjustment with major impact on human psychology. Stress is specially difficult to manage for visually impaired people (VIP) as they can become easily stressed in unknown situations. Electroencephalogram (EEG) signals can be used to detect stress as it basically represents the ongoing electrical signal changes in human brain. Literature shows that the stress detection techniques are mostly based on either time or frequency domain analysis. However, using either time or frequency domain analysis may not be sufficient to provide appropriate outcome for stress detection. Hence, in this paper a method is proposed using empirical mode decomposition (EMD) and short-term Fourier transform (STFT) are used to extract features considering spatio-temporal information from EEG signals. In the EMD, the signal is first decomposed into intrinsic mode functions (IMFs) representing a finite number of signals while maintaining the time domain and STFT is used to convert time domain to time-frequency domain. Support vector machine (SVM) is applied to classify the stress of VIP in unfamiliar indoor environments. The performance of the proposed method is compared with a state-of-the-art technique for stress detection. The experimental results demonstrate the superiority of the proposed technique over the existing technique. © 2020 IEEE.

关键词： Empirical mode decomposition

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