Sentiment analysis, which aims to extract information from textual data indicating people's ideas or attitudes about a particular problem, has developed into one of the most exciting study issues in natural langua...
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This paper describes the development of a random finite element model (RFEM) that allows holistic simulation of frozen soil behaviors, including the effects of phase transition and the consequent internal stress and v...
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Most educational laboratory equipment utilized in vibrations and control labs is heavy and bulky, limiting its use within lab spaces. Further, mechanical engineering students typically gain hands-on experience only in...
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Most educational laboratory equipment utilized in vibrations and control labs is heavy and bulky, limiting its use within lab spaces. Further, mechanical engineering students typically gain hands-on experience only in labs that are offered separately from fundamental courses, unlike other engineering programs. Thus, the extent of student learning from labs, given their limited time, remains a concern considering students’ learning opportunities. This study presents the design and development of two portable and low-cost lab equipment devices: a compliant mechanism with unbalanced rotating masses and a DC motor with beam control under disturbances. While the former is utilized to demonstrate fundamentals of vibrations, derivation of the mathematical model, simulation, and comparison of theory and experimental data, the latter can be used for demonstration of disturbance control. Virtual labs are developed for both mechanisms in MATLAB Simscape.
This paper introduces a prototype for a new approach to assistive robotics, integrating edge computing with Natural Language Processing (NLP) and computer vision to enhance the interaction between humans and robotic s...
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ISBN:
(数字)9798331544546
ISBN:
(纸本)9798331544553
This paper introduces a prototype for a new approach to assistive robotics, integrating edge computing with Natural Language Processing (NLP) and computer vision to enhance the interaction between humans and robotic systems. Our proof of concept demonstrates the feasibility of using large language models (LLMs) and vision systems in tandem for interpreting and executing complex commands conveyed through natural language. This integration aims to improve the intuitiveness and accessibility of assistive robotic systems, making them more adaptable to the nuanced needs of users with disabilities. By leveraging the capabilities of edge computing, our system has the potential to minimize latency and support offline capability, enhancing the autonomy and responsiveness of assistive robots. Experimental results from our implementation on a robotic arm show promising outcomes in terms of accurate intent interpretation and object manipulation based on verbal commands. This research lays the groundwork for future developments in assistive robotics, focusing on creating highly responsive, user-centric systems that can significantly improve the quality of life for individuals with disabilities. For video demonstrations and source code, please refer to: https://***/EnhancedArmEdgeNLP.
This research introduces an innovative approach to water conservation and personalized consumption management by combining Internet of Things (IoT) sensors with Deep Reinforcement Learning (DRL) methods. The suggested...
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ISBN:
(数字)9798350379297
ISBN:
(纸本)9798350379303
This research introduces an innovative approach to water conservation and personalized consumption management by combining Internet of Things (IoT) sensors with Deep Reinforcement Learning (DRL) methods. The suggested approach aims to give people more control over their water use in response to water shortages and the need for sustainable resource management. It installs IoT sensors on taps to track water use in real time. A DRL framework is fed data that these sensors have collected. The DRL algorithm develops individual consumption profiles for each user by factoring in past water use, environmental conditions, and personal tastes. Using this unique profile, water efficiency may be improved instantly. Users may easily enter their water conservation choices, budgets, and the system's user interface. Adjusting the water's flow rate by the user profiles learned by the DRL actively regulates water use while keeping people happy. The results of the experiments reveal that our method effectively reduces both water use and waste. Integrating IoT sensors with DRL methods provides a flexible and scalable answer for smart water management that economically benefits the environment and consumers.
作者：
Praful V. NandankarG.N.R. PrasadM. LakshminarayanaMr. Doddabasappa NG. SatishRamya MarananAssistant Professor
Department of Electrical Engineering Government College of Nagpur Maharashtra India Sr. Asst. Professor
Department of Master of Computer Application Chaitanya Bharathi Institute of Technology (A) Hyderabad India Assistant Professor
Department of Medical Electronics Engineering M S Ramaiah Institute of Technology Karnataka India Assistant Professor
School of Electrical and Electronic Engineering REVA University Bengaluru Karnataka India Associate Professor
Department of Electrical and Electronics Engineering Sree Dattha Institute of Engineering and Science Sheriguda Ibrahimpatnam Hyderabad Telangana India Assistant Professor
Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai India
Many people in metropolitan areas have experienced problems with energy and water shortages. Some people used modern technologies and advancements to theft water and power illegally. Because the planet absolutely need...
Many people in metropolitan areas have experienced problems with energy and water shortages. Some people used modern technologies and advancements to theft water and power illegally. Because the planet absolutely needs both water and power. Currently, the Internet of Things (IoT), smart meters, smart pipelines, and smart homes are being heavily integrated to replace traditional systems for detecting theft activities. This can be digitizing both the meter readings and the data that has been gathered. Wireless technology may be used to collect and analyze the data, which helps to reduce the need for physical labor. In this project, we suggested creating an IoT-based system for water and power theft detection. The proposed project aims to design a system to monitor the amount of power and water used by the people and indicates if water and electricity theft activities happen. This research study offers a user interface system to help people to monitor whether anyone is stealing their water or power. This study employs a hardware like voltage sensors, current sensors, flow sensors, and additionally, the Arduino IoT cloud to enable remote control and monitor the water and power usage.
In recent years, great progress has been made in forecasting human motion in crowded scenes. However, current methods are far from practical applications due to the unbearable high computation costs, especially for en...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
In recent years, great progress has been made in forecasting human motion in crowded scenes. However, current methods are far from practical applications due to the unbearable high computation costs, especially for encoding scene context. In addition, neglecting the partially detected trajectories makes the predicted outcome deviate from the real trajectory distribution. To handle the aforementioned concerns, we propose to represent the scene context and partially observed trajectories with sparse graphs. Customized for this special data structure, we design a hierarchical Graph Transformer Network model SparseGTN to predict multiple possible future trajectories of the target pedestrian by digesting the sparsely represented inputs. Our approach exhibits superiority over the state-of-the-art (SOTA) methods, utilizing a mere 3.42% of the number of floating point operations (FLOPs) and 0.53% of the number of model parameters. The code will be available online
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This paper presents a distributed model predictive control (DMPC) algorithm for a heterogeneous platoon using arbitrary communication topologies, provided each vehicle can communicate with a preceding vehicle in the p...
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ISBN:
(数字)9798331505929
ISBN:
(纸本)9798331505936
This paper presents a distributed model predictive control (DMPC) algorithm for a heterogeneous platoon using arbitrary communication topologies, provided each vehicle can communicate with a preceding vehicle in the platoon. The proposed DMPC algorithm can accommodate any spacing policy that is affine in a vehicle's velocity, which includes constant distance or constant time headway spacing policies. By analyzing the total cost for the entire platoon, a sufficient condition is derived to ensure platoon asymptotic stability. Simulation experiments with a platoon of 50 vehicles and hardware experiments with a platoon of four 1/10th-scale vehicles validate the algorithm and compare performance under different spacing policies and communication topologies. Code for the experiments and a video demonstration of the hardware experiment can be found at https://***/river-lab/dmpc_itsc_***.
作者：
Sara HelalNema SalemB.Sc.
Electrical and Computer Engineering Effat University Jeddah KSA Assistant Professor
Electrical and Computer Engineering Effat University Jeddah KSA
With the development and advent of Internet communications and multimedia technology, it is of high importance to secure the digital media, including audio, video, speech, and images. In fact, watermarking technique p...
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With the development and advent of Internet communications and multimedia technology, it is of high importance to secure the digital media, including audio, video, speech, and images. In fact, watermarking technique provides an efficient solution to this problem. However, for an effective watermarking of data, several important requirements need to be met, such as transparency, low computational cost, robustness, and security. In this work, a robust hybridized medical images watermarking approach based on Walsh Hadamard Transform ( WHT ) and singular value decomposition ( S VD ) is presented. Both of the host image and the watermark images were modified with singular values obtained by the ( S VD ) approach. The simulation results demonstrate that this proposed watermarking framework is highly robust and achieves high peak signal to noise ratio ( PS NR ) and high structure similarity index ( S S IM ).
The inspection of confined critical infrastructure such as attics or crawlspaces is challenging for human operators due to insufficient task space, limited visibility, and the presence of hazardous materials. This pap...
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ISBN:
(数字)9798331510954
ISBN:
(纸本)9798331510961
The inspection of confined critical infrastructure such as attics or crawlspaces is challenging for human operators due to insufficient task space, limited visibility, and the presence of hazardous materials. This paper introduces a prototype of PARIS (Precision Application Robot for Inaccessible Spaces): a use-inspired teleoperated mobile robot manipulator system that was conceived, developed, and tested for-and selected as a Phase I winner of-the U.S. Department of Energy's E-ROBOT Prize. To improve the thermal efficiency of buildings, the PARIS platform supports: 1) teleoperated mapping and navigation, enabling the human operator to explore compact spaces; 2) inspection and sensing, facilitating the identification and localization of under-insulated areas; and 3) air-sealing targeted gaps and cracks through which thermal energy is lost. The resulting versatile platform can also be tailored for targeted application of treatments and remediation in constrained spaces.
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