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Improving Heart Disease Monitoring Through Intelligent Hybrid Inference Systems

Improving Heart Disease Monitoring Through Intelligent Hybri...

引用

electrical Electronics and computing Technologies (ICEECT), international conference on

作者： Janpreet Singh Dalwinder Singh School Of Computer Science and Engineering Lovely Professional University Phagwara India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

To detect early indications and control heart disease, appropriate monitoring methods are needed. This research introduces clever hybrid inference systems to improve heart disease monitoring. These technologies make precise, timely predictions using machine learning algorithms and expert knowledge, enabling early intervention and personalized treatment strategies. Intelligent hybrid inference systems use patient records, physiological measures, and medical literature to find patterns and insights. Deep learning and ensemble approaches are used to analyze data and identify complex heart disease risk factors. Clinical guidelines, medical protocols, and subject expertise are also integrated. This combination of data-driven algorithms and expert knowledge improves the inference process's interpretability and reliability, allowing healthcare practitioners to make informed predictions. Extensive tests and evaluations on real-world cardiac disease datasets test the proposed approach. Intelligent hybrid inference systems exceed standard methods in accuracy and prediction. The systems also adapt to varied patient populations and data characteristics. This research could change heart disease monitoring and management. Healthcare professionals can improve patient outcomes by using intelligent hybrid inference systems to diagnose cardiac disease early, estimate risk, and customize treatment approaches. This effort improves the lives of heart disease patients by using artificial intelligence and expert knowledge.

关键词： Heart Cardiac disease Medical services Inference algorithms Reliability Biomedical monitoring Monitoring Medical diagnostic imaging Standards Diseases

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Autolanding System of Shipborne UAV Based on Fusion of INS, CDGPS and Vision-Based Navigation

Autolanding System of Shipborne UAV Based on Fusion of INS, ...

引用

international conference on Guidance, Navigation and control, ICGNC 2020

作者： Tang, Daquan Kou, Kunhu Tang, Yidan Naval Aviation University Shandong Yantai264001 China Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China

ISBN: (纸本)9789811581540

To land on a moving ship automatically is very difficult for UAV. Vision based navigation is an effective and budget positioning method for UAV landing guidance. However, measurement noise statistics of vision based navigation vary with the distance from camera to object. This paper presents an integrated guidance method for UAV landing on a ship based on fusion of CDGPS, vision navigation and INS. The position of UAV relative to ship given by vision based navigation is integrated with the information of CDGPS, UAV INS and ship INS to improve the reliability of the landing guidance information. An adaptive Kalman filter is applied in the information fusion of the landing guidance system of which the period is as same as that of INS. Simulation results demonstrate that the position accuracy of our method is available for automatic carrier landing. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Stationary Vehicles Detection on Smart Highways and Roads using Spatio-temporal Tracking

Stationary Vehicles Detection on Smart Highways and Roads us...

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international conference on Developments in eSystems engineering (DESE)

作者： Wasiq Khan Jessica Kelly Ala Al-Kafri Natasa Kleanthous Umar Khayam Bilal Khan Faculty of Engineering & Technology Liverpool John Moores University Liverpool UK School of Computing Engineering and Digital Technologies Teesside University United Kingdom Electrical Engineering and Computer Science Khalifa University Abu Dhabi UAE COMSATS University Pakistan School of Computer Science & Eng California State University San Bernardino CA USA

Where traditional motorways contain hard shoulders to provide refuge for broken-down vehicles, smart motorways instead use live outer lane to ease congestion. The live lanes can be closed due to accidents or breakdowns which is communicated to other road users through overhead gantry signs. This can only occur if the traffic management control center is made aware of the stationary vehicle(s), through either notification via phone call or Motorway Incident Detection and automatic Signaling (MIDAS) induction loop technology. Alternatively, radar-based stopped vehicle detection is used to identify non-moving objects on the highway. However, this technology is unable to recognize objects or distinguish between congestion and break down etc., which leads to generate false alarms. For the first time, we propose a fully autonomous computer vision and deep learning-based solution to detect stationary vehicles on highways and local roads. We employ deep transfer learning to build a custom-trained vehicle detection model using a newly prepared dataset comprising over 105,000 annotated vehicle instances. DeepSort algorithm is employed for real-time vehicle tracking through associating instances between time series frames, followed by a rule-based algorithm to identify the current state of detected vehicles. Experimental outcomes show our approach as outperforming the state-of-the-art methods in terms of efficient and reliable detection of stationary vehicles (with 98.3% accuracy) as well as distinguish them from congestions when evaluated over video streams captured in realistic dynamic and diverse conditions.

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Multi-Agent Reinforcement Learning for Smart City Automated Traffic Light control

Multi-Agent Reinforcement Learning for Smart City Automated ...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Hakilo Sabit Department of Electrical and Electronic Engineering Auckland University of Technology Auckland New Zealand

Traffic congestion has emerged as a significant issue for road users, particularly in densely populated urban areas. Many individuals endure extended travel times while moving from one location to another, a direct result of the excessive traffic volume caused by ineffective traffic light control. Consequently, we propose the implementation of an automated traffic light control (TLC) system using Artificial Intelligence (AI) principles to manage two interconnected intersections within this case study. This framework is designed based on Multi-Agent Reinforcement Learning (MARL) with the Q-Learning (QL) algorithm, enabling the TLC system to assign appropriate green signal timing to each junction at both intersections. The primary objective is to alleviate traffic congestion at these intersections by minimizing vehicle wait times at red signals. The traffic model we have developed is implemented and simulated using the MATLAB simulator. We evaluate the system's performance using three distinct configurations with varying learning rates and record the results. The outcomes of our proposed model, presented using the designed methodology, effectively reduce weighted wait times and vehicle queue lengths through the QL algorithm.

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Arduino Board-Based Wireless controlled Seed Sowing Robot 3rd

Arduino Board-Based Wireless Controlled Seed Sowing Robot

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3rd international conference on Recent Trends in Advanced computing - Artificial Intelligence and Technologies, ICRTAC-AIT 2020

作者： Sugadev, M. Ravi, T. Kumar, Anugula Venkatesh Ilayaraja, T. Department of ECE Sathyabama Institute of Science and Technology Jeppiaar Nagar Sholinganallur Chennai600119 India

ISBN: (纸本)9789811664472

In this paper, circuit design, control algorithm and implementation of a prototype robot model, which can be utilized to sow seeds in agricultural fields are presented. In this design, a small driller unit makes a pit or hole on the field to sow the seeds. The depth of drilling is controlled remotely by Bluetooth protocol. To cover the seeds sowed by the robot with sand, a metal plate is fixed at the rear side of the robot. As the robot moves forward, the rear side plate keeps covering the seeds. To control the valve on the seed tank feed line at a desired rate, DC servomotor is employed. With the help of the control algorithm developed for the seed sowing robot, seed sowing depth and number of seeds per position can be altered as per the need of the user. This robot can manage to plant the seeds up to 2–5 cm depth. Bluetooth module attached to the microcontroller unit establishes communication of control signals between the robot and a smart mobile phone. Different tasks of the robot is controlled by an Android application installed on a smart phone. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Seed

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Loss Analysis of ANPC Inverters with Hybrid Si and WBG Devices 8th

Loss Analysis of ANPC Inverters with Hybrid Si and WBG Devic...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Zhang, Yifei Li, Kang Zhang, Li School of Electronic and Electrical Engineering University of Leeds LeedsLS29JT United Kingdom

ISBN: (纸本)9789819602247

High efficiency, high output waveform quality and low stress switching are among the principal requirements for the power converter design. This paper investigates the design and control of a 3-level Active Neutral Point Clamped (ANPC) grid-tied inverters to meet these requirements. A new PWM switching strategy is designed for power loss reduction in the control of ANPCs that use hybrid Si and WBG switching devices. The locations of switching devices made of different materials in the circuit are investigated, and the power losses and switching stresses under different PWM control strategies are compared. The power losses due to both conduction and switching for each switching device and the whole circuit are evaluated. Simulation results confirm that both the converter design and the PWM control strategy need to be optimized together for the best trade-off among different objectives, such as the power losses and the cost. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Hybrid power

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Complex-Valued Signal Capsule Network for automatic Modulation Classification

Complex-Valued Signal Capsule Network for Automatic Modulati...

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international conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Yang, Shuyuan Feng, Zhixi Wang, Nengguo Bu, Yunong Hu, Hao Luoyang471003 China Xidian University Shannxi China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Most current deep learning (DL) based AMC methods often require a large number of labeled samples to drive itself optimization study, so as to achieve a more superior performance. However, for many AMC tasks with a small amount of data, the AMC method based on deep learning still has many challenges, which makes the deep neural network model trained on a small dataset lack effective migration effect, leading to the failure to achieve better performance effect in the testing process. In this paper, we propose a novel AMC method based on Complex-valued Signal Capsule Network (CSCN). Compared with other DL based methods, the proposed CSCN can achieve a better performance under the condition of small dataset and low SNR on the well-known deepsig dataset RML2016.10a and RML2016.10b. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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computing State Invariants Using Point-Wise Integral Quadratic Constraints and the S-procedure

Computing State Invariants Using Point-Wise Integral Quadrat...

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2021 American control conference, ACC 2021

作者： Jaoude, Dany Abou Garoche, Pierre-Loic Farhood, Mazen Mechanical Engineering Department Enac the French National University of Civil Aviation Virginia Tech Kevin T. Crofton Department of Aerospace and Ocean Engineering United States

ISBN: (纸本)9781665441971

This paper deals with the problem of computing ellipsoidal state invariant sets for uncertain systems that consist of a nominal part and an uncertainty feedback operator. The set of allowable uncertainty operators is characterized using point-wise integral quadratic constraints (IQCs). The proposed solution methodology combines the S-procedure and the notion of point-wise IQCs in a novel way. The approach allows for a point-wise characterization of the disturbance inputs and involves solving a grid of convex optimization problems. The paper concludes with an illustrative example. © 2021 American automatic control Council.

关键词： Convex optimization

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A Pose control Algorithm for Elbow Models Based on Five-Axis Unsupported 3D Printing

A Pose Control Algorithm for Elbow Models Based on Five-Axis...

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2023 7th international conference on electrical, Mechanical and Computer engineering (ICEMCE)

作者： Jiachang Liu Fan Zhang Yiwen Tu Xiao Yang School of Electronical and Mechanical Engineering Wuhan University of Technology Wuhan Hubei China

Orthopedic emergency interventions necessitate swift brace production. Utilizing 3D printing technology, expedited fabrication of tailored braces becomes feasible. Nonetheless, the considerable number of suspended structures in elbow braces impedes efficient printing. The five-degree-of-freedom unsupported 3D printing technique, integrated with a rotating base plate, addresses this efficiency concern. Following a field 3D scan, the irregular elbow model's position and orientation must align with the printing mechanism for seamless execution. To tackle the challenge of optimal pose adaptation for the elbow model, a strategy grounded on 3D elbow model characteristics and printing device structural constraints was introduced. Given the non-uniformity of the 3D scanned model, the model's spatial pose attributes were determined by extracting the elbow model's central line, computing the inter-axis angles, and distinguishing between the major and minor axes. Considering the rotation angle restrictions of the printer's base plate and the coordinate placement of the model's foundation point, various aspects of the support model's pose, including its parallel base surface, spatial orientation, and proximity to the base plate, were meticulously calibrated to suit 3D printing requirements. Comparative simulation analyses and print tests confirm the efficacy of the elbow model's automatic adjustment method, advancing the cause of rapid 3D slicing devoid of external support.

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Edge computing and Computational Task Offloading Analysis – A review study

Edge Computing and Computational Task Offloading Analysis –...

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Emerging Trends in electrical, control, and Telecommunication engineering (ETECTE), international conference on

作者： Tanzeel Zaidi Samia Aziz Muhammad Usman Awais Azam Adeel Ashraf Cheema Sahar Ajmal Department of Computer Science National University of Computer and Emerging Sciences Chiniot - Faisalabad Pakistan

ISBN: (纸本)9781665492430

Delay constraints and energy consumption are becoming a barrier to running complex applications on mobile devices due to the rise of latency-sensitive applications. One of the fundamental technologies of Mobile Edge computing (MEC), which compensates for the limitations of mobile devices in terms of storage space, computing power, and battery efficiency, is computation offloading. The computation offloading methods in MEC networks are now the subject of extensive study for both the industry and academia, using a variety of valuable techniques and methodologies. This paper provides a detailed analysis of computing task offloading in a MEC environment. This study focuses on essential challenges related to numerous offloading goals, such as delay time, energy consumption reduction, income maximization, and system utility enhancement.

关键词： Industries Energy consumption Multi-access edge computing Quality of service Market research Mobile handsets Delays

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