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Understanding of the Biomechanics of Tendons and Ligaments and its Application in Designing Prosthetics

Understanding of the Biomechanics of Tendons and Ligaments a...

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international conference on Humanoid, Nanotechnology, Information Technology, communication and Control, Environment and Management (HNICEM)

作者： Daeuk Kim Maria Nessie Sobina C. Yu Earl Jewel M. Arel Mark Jefferson U. Lim Anthony Tan Velasquez William T. Lavadia Ryan Rhay P. Vicerra Department of Manufacturing Engineering and Management De La Salle University Manila Philippines

Biomechanics is a branch of physical science that investigates how forces and energy interact with a subject element. the mechanical behaviors of biological systems and subsystems are the core emphasis of its principles. One of the main areas of interest in biomechanics is the musculoskeletal system and the ligaments and tendons that make up one of its corresponding subsystems. the development of devices like prosthetics and rehabilitation that can aid in the healing and restoration of the body as well as imitate lost biological functions is therefore made possible by the study of biomechanics in relation to these systems and subsystems. these underlying concepts are all pertinent to one’s engineering education, particularly for individuals working in the biomedical sector.

关键词： Biomechanics Humanoid robots Biological systems Behavioral sciences Ligaments Information technology Engineering education

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Vehicle Tracking in Low Frame Rate Scenes using Instance Segmentation

Vehicle Tracking in Low Frame Rate Scenes using Instance Seg...

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international conference on Humanoid, Nanotechnology, Information Technology, communication and Control, Environment and Management (HNICEM)

作者： Allysa Kate Brillantes Edwin Sybingco Argel Bandala Robert Kerwin Billones Alexis Fillone Elmer Dadios Department of Electronics and Computer Engineering Malate Manila Philippines Intelligent Systems Laboratory Malate Manila Philippines Department of Manufacturing Engineering and Management Malate Manila Philippines Department of Civil Engineering Malate Manila Philippines

Multiple object tracking is a necessary component in traffic surveillance systems. It is a requirement for today’s embedded visual surveillance systems to process videos at low frame rates. this paper aims to track objects at different frame rates focusing on improving the tracking at low frame rates. In the proposed model, an instance segmentation model was used. the mask prediction, together with the IOU of previous tracks and new observations, was utilized for data association. the proposed method was evaluated using evaluation metrics such as HOTA, MOTA, and IDF1 and achieved better results in tracking objects at low frame rates.

关键词： Measurement Visualization Surveillance Humanoid robots Traffic control Prediction algorithms Object tracking

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uFindMe: A UWB-Based Robotic Package Finder

uFindMe: A UWB-Based Robotic Package Finder

引用

international conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Nicholas Cich Rishabh Singhal Ashutosh Dhekne School of Computer Science Georgia Tech Atlanta GA USA

ISBN: (数字)9798350366402

ISBN: (纸本)9798350366419

this paper explores the problem of seeking a wireless ultra-wideband radio-enabled physical package in a cluttered environment using a mobile robot. We enable a robot to navigate (using LiDAR and wheel odometry measurements) to a physical package by continuously calculating the distance from the package (using UWB-based wireless ranging). We assume no explicit support from the surrounding environment where the package is present and, therefore, intend to perform this package-seeking using sensors on the robot and a UWB-wireless radio installed inside the package. We expect such a system to be used for high-value packages or packages with perishable contents. the technical innovations in this paper stem from the robot utilizing its own movements and continuous distance measurements with the UWB inside the package to localize the package and then seek out an approach path for autonomous navigation using LiDAR. We demonstrate our end-to-end robotic system using real-world experiments with varying levels of clutter and navigational complexity.

关键词： Wireless communication Wireless sensor networks Technological innovation Laser radar Wheels Robot sensing systems Distance measurement Sensors Mobile robots Ultra wideband technology

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Innovative Detection of Brain Tumor using Conventional Neural networks Classifier and comparison with Support Vector Machine Classifier

Innovative Detection of Brain Tumor using Conventional Neura...

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international conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)

作者： M. Guru Karthik Reddy P. Jagadeesh P. Kiran Kumar Department of Electronics Communication and Engineering Saveetha University Chennai India Department of Computer Science and Engineering) Saveetha University) Chennai India

ISBN: (纸本)9781665460729

the proposed work aims to determine the accuracy in brain tumour detection using Support Vector Machine (SVM) and Conventional Neural networks (CNN) algorithm. Conventional Neural networks is applied to the Brain Tumor Dataset that consists of 37 records. Sample size is calculated using G power and determined as 10 per group for both algorithms with pretest power 80% and threshold value as 0.05. Conventional Neural networks have 98.66% provides high accuracy in predicting brain tumors compared with Support Vector Machine which have 93.48%. there is a significant difference of 0.0001 (p¡0.05, two tailed) between the groups. the work proves that Conventional Neural networks exhibit better accuracy than Support Vector Machine in predicting brain tumors.

关键词： Support vector machines Computer science Support vector machine classification Cerebrum Prediction algorithms Mathematics Biological neural networks

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An Efficient Algorithm for Plant Disease Detection Using Deep Convolutional networks

An Efficient Algorithm for Plant Disease Detection Using Dee...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Pratibha Nayar Shivank Chhibber Ashwani Kumar Dubey Dept of Electronics & Communication Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Noida Uttar Pradesh India

ISBN: (纸本)9781665487726

Plant diseases and pests are important factors in determining crop yield and quality. Plant diseases are not only a threat to food security on a global scale but can also have devastating consequences for farmers whose livelihood depend on healthy crops. the detection of plant diseases is of fundamental importance in practical agricultural production. It controls the growth and health of the plant and ensures the regular operation and successful harvest of agricultural plantations. the disease affecting the plants is determined by factors such as the climate. this paper examines an alternative approach to developing a disease detection model supported by leaf classification using deep convolutional networks. Growth in computer vision present a scope to broaden and boost the practice of precision crop protection and expand the market for computer vision applications in precision agriculture, a completely unique form of training and therefore the technique used allows for quick and direct implementation of the system in practice. the database used in this paper consists of 77,000 images of healthy and infected plant leaves. We were able to train a CNN model for classifying plant diseases that is, they are present or not, and then another model was trained with YOLOv7 to detect the disease. the trained classification model achieved an accuracy of 99.5% and the detection model was able to achieve mA $P$ , precision, recall of 0.65, 0.59and 0.65 respectively.

关键词： Training Computer vision Computational modeling Plants (biology) Neurons Crops Production

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A Privacy-Preserving Indoor Localization System based on Hierarchical Federated Learning

A Privacy-Preserving Indoor Localization System based on Hie...

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international conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Masood Jan Wafa Njima Xun Zhang ISEP Institut Supérieur d’Electronique de Paris Paris France

ISBN: (数字)9798350366402

ISBN: (纸本)9798350366419

Location information serves as the fundamental element for numerous Internet of things (IoT) applications. Traditional indoor localization techniques often produce significant errors and raise privacy concerns due to centralized data collection. In response, Machine Learning (ML) techniques offer promising solutions by capturing indoor environment variations. However, they typically require central data aggregation, leading to privacy, bandwidth, and server reliability issues. To overcome these challenges, in this paper, we propose a Federated Learning (FL)-based approach for dynamic indoor localization using a Deep Neural Network (DNN) model. Experimental results show that FL has the nearby performance to Centralized Model (CL) while keeping the data privacy, bandwidth efficiency and server reliability. this research demonstrates that our proposed FL approach provides a viable solution for privacy-enhanced indoor localization, paving the way for advancements in secure and efficient indoor localization systems.

关键词： Location awareness Data privacy Federated learning Spectral efficiency Artificial neural networks Data models Indoor environment Servers Internet of things Visible light communication

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Experimental Study of Temperature Impact on Fiber Optic Current Sensor Elements 21st

Experimental Study of Temperature Impact on Fiber Optic Curr...

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21st international conference on Next Generation Teletraffic and Wired/Wireless Advanced networks and systems, NEW2AN 2021 and 14th conference on Internet of things and Smart Spaces, ruSMART 2021

作者： Temkina, Valentina Medvedev, Andrei Mayzel, Alexey Sivolenko, Eduard Poletaeva, Ekaterina Dudnik, Iuliia Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Software-Defined Systems LLC St. Petersburg Russia Radiophysics and Electronics Yerevan State University Yerevan Armenia

ISBN: (纸本)9783030977764

Fiber optic current sensors must meet 0.2S accuracy class in various environmental conditions in order to achieve a competitive position in the digital measuring device market. However, a number of external factors still limit their use. One of these factors is temperature. In this paper, we studied the temperature impact on the operation of optical elements that make up a fiber optic current sensor. Each element responds differently to changes in ambient temperature. therefore, we considered each element of the optical scheme separately and experimentally investigated the evolution of the polarization state of light during heating and cooling of these elements. the study showed that the circulator is not affected by temperature, the modulator operates like a phase plate, and a parasitic polarization mode is excited in the delay line. the most affected by temperature are the quarter-wave plate and the sensitive spun fiber. It will lead to significant errors in the fiber optic current sensor measurements. therefore, to ensure the high-precision operation of the device, it is necessary to develop algorithms for compensating the temperature dependences. © 2022, Springer Nature Switzerland AG.

关键词： Temperature distribution

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Lightweight CNN for Everyday Human Sound Classification on Edge Devices

Lightweight CNN for Everyday Human Sound Classification on E...

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international conference on communication systems and Network Technologies (CSNT)

作者： Venkata Raghava Shashank Viswanathuni Sarada Puranapanda Bethi Pardhasaradhi Sagar Koorapati Linga Reddy Cenkeramaddi ICT Department University of Agder Norway CSE Department Indian Institute of Information Technology Design and Manufacturing Kurnool India ICT Dept. Manipal Academy of Higher Education Manipal Institute of Technology Bengaluru India Qualcomm Technologies CPU Design Group Austin TX

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

this study presents a lightweight Convolutional Neural Network (CNN) that recognizes everyday sounds on IoT edge devices. Audio signals encompassing daily activities are captured via a microphone and transformed into time-frequency images using Continuous Wavelet Transform (CWT). the proposed CNN is optimized for low computational requirements and performs better than established pre-trained models such as DenseNet, EfficientNet, InceptionNet, MobileNet, NASNet, ResNet, VGGNet, and Xception. the model achieves an overall validation accuracy of 84 % in a ten-fold cross-validation framework, with a compact model size of only 854KB and an inference time of 7.3 milliseconds (ms) on a Raspberry Pi. In comparison, EfficientNetV2B1, the second-best performer, achieves comparable accuracy but with a significantly larger size of 27.1 MB and an inference time of 119.99 ms. the model’s inference time was evaluated on various devices, including Raspberry Pi, NVIDIA A100, Tesla V100, and Intel Xeon Platinum, demonstrating its efficiency across different platforms. the dataset includes everyday human sounds, such as crying, applause, breathing, coughing, footsteps, laughter, brushing teeth, snoring, and drinking water. the efficiency and accuracy of the proposed CNN make it ideal for real-time sound recognition in smart home automation, health monitoring, and ambient assisted living, where low latency and resource efficiency are critical.

关键词： Time-frequency analysis Accuracy Continuous wavelet transforms Image edge detection Computational modeling Smart homes Real-time systems Sleep apnea Convolutional neural networks Water resources

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Multidimensional Direct Fractional Programming based Multicast Beamforming Design in Space-Ground Integration networks

Multidimensional Direct Fractional Programming based Multica...

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international conference on Wireless communications and Signal Processing (WCSP)

作者： Huizhen Qiu Hongming Zhang Mugen Peng School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665450867

this paper studies the multicast beamforming opti-mization design problem for space-ground integration network (SGIN). Firstly, a centralized processor (CP) is deployed for performing user scheduling and multicast beamforming in SGIN. then, the in-band interference induced rate distortion problem in SG IN is detailed. In order to tackle this problem, we propose a multidimensional direct fractional programming (MDFP) based beamforming design algorithm for both satellite and base stations (BSs) at the CP, where the corresponding sum rates are maximized by subjecting to the transmission power budget of satellite and ground BSs. Finally, simulation results are provided, showing that our proposed algorithm is capable of obtaining feasible solutions with multiple iterations.

关键词： Wireless communication Multicast algorithms Satellites Array signal processing Processor scheduling Simulation System performance

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Physical Layer Authentication Based on DOA and Rotational State

Physical Layer Authentication Based on DOA and Rotational St...

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international conference on Wireless communications and Signal Processing (WCSP)

作者： Weiyang Xu Lingling Tao Qinglin Xu School of Communication Engineering Chongqing University Chongqing China

ISBN: (纸本)9781665450867

this paper studies the physical layer security for the downlink of cellular networks. Specifically, a user equipment (UE) should identify whether the received signals is from a legal base station (BS) or a rogue BS. Toward this end, a new physical layer authentication (PLA) scheme is proposed using the inherent and unique characteristics of direction of arrival (DOA) of the received signal. Under a simple hypothesis test, the DOA and rotational state features of the end device are used in designing the decision metric. the probability of false alarm and detection are analyzed based on the developed decision metric and their closed-form expressions are derived, based on which the optimal threshold can be obtained. Simulation results show that compared with the existing method in the literature, the proposed scheme outperforms significantly in terms of detection accuracy.

关键词： Wireless communication Performance evaluation Direction-of-arrival estimation Law Simulation Authentication Programmable logic arrays

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