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The Current Status, Hotspots, and Trends of Artificial Intelligence Research in Africa-A Bibliometric Analysis Based on CiteSpace from 2003 to 2023 24

The Current Status, Hotspots, and Trends of Artificial Intel...

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5th International Conference on computer science and Management Technology, ICCSMT 2024

作者： Dong, Miao Wu, Yuliang Zhang, Peipei Mubeen, Afzal School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Center for West African Studies University of Electronic Science and Technology of China Sichuan Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9798400709999

Based on the CiteSpace bibliometric method, 273 research papers from the Web of science Core Database from 2003 to 2023 were analyzed. This study delves into external characteristics such as publication volume, participating countries, research institutions, and authorship to uncover the key issues and evolving trends in the field of artificial intelligence (AI) research in Africa. The research shows that the number of AI studies in Africa has seen an"explosive" growth in recent years, with AI solutions being applied on a large scale. The development of AI in Africa primarily revolves around addressing practical needs in areas such as agriculture, food security, disease, and education, leading to significant achievements. However, challenges remain, including a lack of widespread international collaboration, a small core research community, and issues related to the localization of data and technology application. Looking ahead, strengthening international cooperation, enhancing local research and innovation capabilities, and addressing challenges related to data and technology application will be key to the continued growth of AI research in Africa. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Bibliographies

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A Low-Cost Flexible Wrist ECG Sensor for Wearable Devices Application 5

A Low-Cost Flexible Wrist ECG Sensor for Wearable Devices Ap...

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5th IEEE International Flexible Electronics Technology Conference, IFETC 2023

作者： Kim, Taeil Yi, Qian Hassanpoor, Sina Esfandyarpour, Rahim Baylor University Department of Mechanical Engineering TX76798 United States University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States

ISBN: (纸本)9798350332094

A low-cost flexible wrist electrocardiogram (ECG) sensor is fabricated on flexible Au-coated PET film. The circular electrode of ECG sensor is covered with Ag/AgCl. The diameter of circular electrodes is varied to find an optimized diameter which provides ECG signals including PQRST peaks with minimum intrusiveness for the user. The effects of applying artificial sweat between electrodes and skin, placing electrodes in different positions, and using a third electrode connected to the ground on wrist ECG signals are studied to find the best condition to obtain stable wrist ECG signal with minimum intrusiveness. © 2023 IEEE.

关键词： Electrocardiograms

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A hybrid optimization approach for securing cloud-based e-health systems

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Multimedia Tools and Applications 2025年第16期84卷 16525-16560页

作者： Altherwi, Abdulhadi Ahmad, Mohammad Tauheed Alam, Md. Moddassir Mirza, Hidayath Sultana, Nazia Pasha, Amjad Ali Sultana, Nishat Khan, Asif Irshad Alam, Md Mottahir Azim, Rezaul Department of Industrial Engineering College of Engineering and Computer Science Jazan University PO Box. 706 Jazan45142 Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia Department of Health Information Management and Technology College of Applied Medical Sciences University of Hafr Al-Batin Hafr Al-Batin Saudi Arabia Department of Electrical and Electronic Engineering College of Engineering and Computer Science Jazan University Jazan45142 Saudi Arabia Government Medical College Siddipet Ensanpalli Siddipet District Telangana502114 India Aerospace Engineering Department King Abdulaziz University Jeddah21589 Saudi Arabia Department of Business Administration Applied College Jazan University P. O. Box 706 Jazan45142 Saudi Arabia Department of Computer Science Aligarh Muslim University Uttar Pradesh Aligarh202002 India Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz Jeddah21589 Saudi Arabia Department of Physics University of Chittagong Chattogram4331 Bangladesh

In modern healthcare, cloud-based e-health technology offers substantial benefits but faces significant security challenges. Sensitive patient data is vulnerable to cyber threats during transmission and storage, potentially enabling unethical collaboration between healthcare professionals and cloud storage providers. This paper aims to develop a robust security framework that safeguards patient privacy and prevents unauthorized access to sensitive medical information in remote patient health monitoring systems. The study presents an Artificial Hybrid Optimization with an Attribute-Based Encryption (AHO-ABE) model. The model leverages cryptographic techniques and hybrid optimization to enhance data security. Specifically, whale optimization (WO) is used for efficient key generation, while sheep flock optimization (SFO) is employed for continuous network surveillance. Experimental results demonstrate that the AHO-ABE model significantly enhances data security, outperforming existing RPM-MEC, AID, AI-HCS, and IoT-HMS approaches. The model exhibits superior resilience against unauthorized access and data breaches, achieving a 5 ms execution time, 850 kbps throughput, 0.121 mJ energy usage, and 4 s latency. Combining cryptographic techniques with hybrid optimization algorithms, the AHO-ABE model provides a robust framework for safeguarding sensitive medical information. This approach ensures the integrity and confidentiality of patient data in remote healthcare settings, offering an effective solution against high-performance cyber attacks. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Diagnosis

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mechanically durable,super-repellent 3D printed microcell/nanoparticle surfaces

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Nano Research 2022年第6期15卷 5678-5686页

作者： Sajad Haghanifar Anthony J Galante Mehdi Zarei Jun Chen Susheng Tan Paul W Leu Department of Industrial Engineering University of PittsburghPittsburghPA 15261USA Department of Mechanical Engineering and Materials Science University of PittsburghPittsburghPA 15261USA Department of Electrical and Computer Engineering and Peterson Institute of NanoScience and Engineering University of PittsburghPittsburghPA 15261USA Department of Chemical Engineering University of PittsburghPittsburghPA 15261USA

Three-dimensional(3D)printed re-entrant micropillars have demonstrated high static contact angles for an unprecedented variety of liquids,but have yet to achieve this with low contact angle hysteresis and excellent abrasion *** report on the demonstration of 3D printed microcell/nanoparticle structures that exhibit high static contact angle,low contact angle hysteresis,and high mechanical *** and microcells both exhibit high static contact angles with water and ethylene glycol(EG),but suffer from high contact angle hysteresis,indicative of rose petal *** modeling results indicate that micropillars are able to achieve higher static contact angle and breakthrough pressure simultaneously compared with ***,simulations also indicate that micropillars have higher maximum equivalent stress at their bases,so that they are more prone to mechanical *** address contact angle hysteresis and mechanical durability issues by the creation of 3D printed microcell/nanoparticle arrays that demonstrate super-repellency and retain their super-repellency after 100 cycles of mechanical abrasion with a Scotch-Brite abrasive pad under a pressure of 1.2 *** use of interconnected microcell structures as opposed to micropillars addresses mechanical durability *** contact angle hysteresis is realized by coating 3D printed structures with low surface energy nanoparticles,which lowers the solid–liquid contact area *** results demonstrate new 3D printed structures with mechanical durability and super-repellency through the use of microcell structures integrated with fluorinated nanoparticles.

关键词： superomniphobicity three-dimensional(3D)printing surface evolver mechanical durability microcell re-entrant micropillar

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Swarm Characteristics Classification Using Neural Networks

arXiv

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arXiv 2024年

作者： Peltier, Donald W Kaminer, Isaac Clark, Abram Orescanin, Marko Department of Mechanical & Aerospace Engineering Department of Physics Department of Computer Science

Understanding the characteristics of swarming autonomous agents is critical for defense and security applications. This article presents a study on using supervised neural network time series classification (NN TSC) to predict key attributes and tactics of swarming autonomous agents for military contexts. Specifically, NN TSC is applied to infer two binary attributes - communication and proportional navigation - which combine to define four mutually exclusive swarm tactics. We identify a gap in literature on using NNs for swarm classification and demonstrate the effectiveness of NN TSC in rapidly deducing intelligence about attacking swarms to inform counter-maneuvers. Through simulated swarm-vs-swarm engagements, we evaluate NN TSC performance in terms of observation window requirements, noise robustness, and scalability to swarm size. Key findings show NNs can predict swarm behaviors with 97% accuracy using short observation windows of 20 time steps, while also demonstrating graceful degradation down to 80% accuracy under 50% noise, as well as excellent scalability to swarm sizes from 10 to 100 agents. These capabilities are promising for real-time decision-making support in defense scenarios by rapidly inferring insights about swarm behavior. © 2024, CC BY.

关键词： Scalability

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Digital Twins for Photorealistic Event-Based Structural Dynamics 41st

Digital Twins for Photorealistic Event-Based Structural Dyna...

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41st IMAC, A Conference and Exposition on Structural Dynamics, 2023

作者： Davis, Allison Walker, Edward Chen, Marcus Felipe, Moises Mascareñas, David Moreu, Fernando Cattaneo, Alessandro Department of Electrical Engineering and Computer Science College of Engineering and Applied Science University of Wyoming LaramieWY United States Department of Mechanical Engineering George R. Brown School of Engineering Rice University HoustonTX United States Department of Electrical and Computer Engineering College of Engineering University of Washington SeattleWA United States Los Alamos National Laboratory Los AlamosNM United States Department of Civil Construction and Environmental Engineering University of New Mexico AlbuquerqueNM United States

ISBN: (纸本)9783031349096

Digital twins are virtual representations of real-world structures that can be used for modeling and simulation. Because of digital twins’ ability to simulate complex structural behaviors, they also have potential for structural health monitoring (SHM) applications. Video-based SHM techniques are advantageous due to the lower installation/maintenance costs, analysis in high-spatial resolution, and its non-contact monitoring features. Both digital twins and video-based techniques hold particular interest in the fields of non-destructive evaluation, damage identification, and modal analysis. An effective use of these techniques for SHM applications still poses several challenges. Neural radiance fields (NeRFs) are an emerging and promising type of neural network that can render photorealistic novel views of a complex scene using a sparse data set of 2D images. Originally, NeRF was designed to capture static scenes, but recent work has extended its capability to capture dynamic scenes which has implications for medium and long-term SHM. However, to date, most NeRFs use frame-based images and videos as input data. Frame-based video monitoring approaches result in redundant information derived from the fact that, for structural dynamics monitoring, only a small number of active pixels record the actual dynamical changes in the structure, resulting in intensive computational loads for data processing and storage. A promising alternative is event-based imaging, which only records pixel-wise changes on the illumination of a scene. Event-based imaging creates a sparse set of data, while accurately capturing the dynamics. The work proposes a method to extract the dynamics of a structure using a generated digital twin. Using Unreal Engine 5, digital twins of rigid and non-rigid structures were generated. The digital twin model was then used along with an event-based camera simulator to generate event-based data. A frequency analysis framework was then developed to extract the

关键词： Cameras

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Development of Programmable Embroidery Pressure Sensors

Development of Programmable Embroidery Pressure Sensors

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IEEE International Conference on Connected Health: Applications, Systems and engineering Technologies (CHASE)

作者： Faisal Rehman Xian Li Ye Sun Department of Mechanical and Aerospace Engineering Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

ISBN: (数字)9798350345018

ISBN: (纸本)9798350345025

This paper presents a new class of programmable embroidered pressure sensors on cloth for textile electronics leveraging interdigitated capacitor designs. Our work demonstrates the fabrication procedure for programmable embroidered capacitive and resistive sensors through the integration of conductive yarns into fabric substrates, thus engendering flexible pressure sensors. The experimental findings heightened sensitivity and rapid response to applied force in the developed sensors, showcasing their potential for various applications in wearable technology and smart textiles.

关键词： Pressure sensors Smart textiles Electric potential Sensitivity Force Capacitive sensors Sensors

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Framework for a Case Study Based Course in Safety and Mission Assurance for Space Systems

Framework for a Case Study Based Course in Safety and Missio...

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2024 Systems and Information engineering Design Symposium, SIEDS 2024

作者： Bosch, Liz M. McGurn, Joshua B. Babiceanu, Radu Embry-Riddle Aeronautical University Aerospace Engineering Department Daytona BeachFL32114 United States Embry-Riddle Aeronautical University Electrical Engineering and Computer Science Department Daytona BeachFL32114 United States

ISBN: (纸本)9798350385144

The feasibility of sending humans to the Moon or Mars depends primarily on one question: is it safe enough? There are few to no courses offered in engineering curricula that address Safety and Mission Assurance (SandMA) for space systems, and there is a lack of instruction of safety culture-where ethics plays a significant role-in current engineering educational strategies. This produces a gap between a student's knowledge of SandMA and the knowledge required to perform effectively and safely within the workforce. This research proposes a course framework to bridge that gap and improve the strategies with which engineering courses are taught. The framework discussed in this paper provides a learner-centered pedagogical approach to promote motivation, a key aspect of decision-making. If case studies of real human spaceflight accidents, incidents, and close calls are used in the classroom to teach SandMA concepts, students can connect to the event, making them aware of how integrity, ethics, and safety culture play a role in the engineering decision-making aspect of human spaceflight. Connection to the course material can then produce the proper motivations that will then influence the student's decision-making process when they work in the industry. In addition, the framework addresses the usage of case studies to promote conceptual understanding, critical thinking, and problem-solving. By showing both the efficiency of case studies in teaching engineering concepts and the ability of case studies to promote ethical decision making and behavior, this approach is projected to foster students with integrity, accountability, and responsibility. The authors recommend aerospace and systems engineering programs implement courses with a similar framework in their curricula. © 2024 IEEE.

关键词： Decision making

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Time optimal trajectory planning of robot based on honey badger algorithm 3

Time optimal trajectory planning of robot based on honey bad...

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3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Liu, Xiaogang Gao, Wenbo Li, Yongzeng Wei, Li School of Mechanical and Automotive Engineering Guangxi University of Science and Technology Liuzhou545006 China School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin541004 China School of Automotive Engineering Guilin University of Aerospace Technology Guilin541004 China

ISBN: (纸本)9781510668522

Aiming at a point-To-point trajectory planning problem for industrial robots, we propose a method for time optimal optimization of trajectories in the robot joint space by employing the honey badger algorithm. Interpolation points at each joint are first acquired using robotic kinematics;Then, to enable the robot to smoothly complete the work task, a 4-5-4 piecewise polynomial is employed to interpolate its trajectory;Finally, we use the honey badger algorithm to optimize the interpolation time of the segmented polynomials to achieve the goal of optimal trajectory planning for the robot's time. The simulation through MATLAB software to obtain the change information of angular displacement, angular velocity and angular acceleration of each joint of the robot, under the restriction conditions that meet the kinematic parameters of the robot, the robot's motion time is shortened by 43.17% compared to that before optimization, which verifies the effectiveness of the honey badger algorithm in the optimization of robotic tracks. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Industrial robots

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A Deployable Edge Computing Solution for Machine Condition Monitoring

A Deployable Edge Computing Solution for Machine Condition M...

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IEEE Instrumentation and Measurement Technology Conference

作者： Xijia Zhao Peng Wang Department of Electrical and Computer Engineering University of Kentucky Lexington USA Department of Electrical and Computer Engineering Department of Mechanical and Aerospace Engineering University of Kentucky Lexington USA

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Machine condition monitoring and predictive maintenance are critical components of smart manufacturing. The realization of machine predictive maintenance relies on synthetic integration of advanced sensing, Internet of Things (IoT), cloud computing, and Artificial Intelligence (AI)-enabled data analytics for machine condition diagnosis and prognosis. One challenge that hurdles the manufacturing shop floor from implementing predictive maintenance is its outdated hardware and limited internet bandwidth, which prevents the floor from transmitting all collected data to the cloud for centralized data analytics. One promising solution is edge-cloud computing and decision-making architecture. In such an infrastructure, collected sensing data will be first processed on edge to directly obtain machine diagnosis results (e.g., normal vs. abnormal), and only extracted features or selected raw data will be transmitted to the cloud for further analytics (e.g., remaining life prognosis). To improve the affordability and applicability of edge computing, this study proposed a novel and deployable edge device that adopts a feature-based Tiny Machine Learning (Tiny ML) model to achieve vibration data processing and machine condition monitoring while maintaining the modeling generalizability and computing efficiency. It integrates a Microelectromechanical Systems (MEMS) accelerometer for vibration data sampling (up to 20 kHz) and a microcontroller for edge computing and communication to the cloud. The integral IoT system, which involves the edge device, cloud services, and wireless communication between the edge and cloud is presented, emphasizing its plug-and-play capability. In this framework, MQTT protocol is adopted for communication among edge, cloud, and end users, allowing processed signal information and machine diagnosis results to be published to end users in real-time. Extensive experiments have been conducted in the context of industrial motor condition monitoring and faul

关键词： Condition monitoring Vibrations Cloud computing Computational modeling Data models Real-time systems Sensors

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