检索结果-内蒙古大学图书馆

Energy conservation: Virtual energy audit of an industrial plant

Materials Today: Proceedings 2023年 72卷 1882-1889页

作者： Joshi, Atharva Khandelwal, Niyati Suryavanshi, Yash Broota, Sumir Kurulekar, Maya Dhaneshwar, Pranav LY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune 411048 India TY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune 411048 India Department of Engineering Science Vishwakarma University MS Pune 411048 India Department of Mechanical Engineering Vishwakarma University MS Pune 411048 India

Energy consumed by manufacturing industries constitutes a large part of the total energy consumption of the world. In India, almost 50% of the total energy consumption is done by Industries. Energy bills are usually a major contributor to the operating expenses of a company. Industries can profit from the opportunities coming out of energy saving by the implementation of effective energy management using appropriate tools. An industrial plant layout is usually designed within several constraints, mainly operational. The objectives were decided by the company to study and identify energy gaps in the industrial plant and suggest suitable solutions to reduce energy consumption all while reducing the average working temperature inside the plant from 38 °C to an ideal value below 30 °C, preferably without installing an air conditioning system. The study was divided into two parts;Primarily, Data collection and observations of the plant operations and then Building Energy Modelling and simulation. The base model with existing conditions was modelled, simulated and validated with historical energy consumption data and temperature readings taken inside the plant. The proposed solutions include limited modifications in the existing set up considering the operational constraints. The simulations run with proposed modifications indicate a maximum of 11 % savings in energy consumed by lighting and potential to reduce temperature to 33.23 °C from 38 °C. The effect of ambient factors according to the geographical location such as sun exposure, wind directions, humidity were also taken into consideration. © 2023

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

SMARTGOV: Strategic Management of Assets for Resilient and Transparent Government Operations 9

SMARTGOV: Strategic Management of Assets for Resilient and T...

引用

9th International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2024

作者： Chauhan, Naman Atri, Pranshul Tomar, Riya Kumar, Aman Chauhan, Chhavi Kumar, Kaitala Charan Sophiya, E. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Chennai India School of Computer Science University of Petroleum and Energy Studies Dehradun India Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Mechanical Engineering Chennai India

ISBN: (纸本)9798350350845

In this age, we introduce an application that aims to revolutionize the management of government buildings. With a commitment, to supporting Digital India initiative, proposed project addresses the changing needs of governance and public service delivery. This application serves a purpose;it provides authorities with an easy-To-use platform for efficient building management while also empowering the public with real-Time information and a streamlined channel for expressing concerns. We leverage technologies like GPS camera Lite, Google Maps, Automatic fire detection using CNN with a mAP of 98.61% and Cloud Firestore to seamlessly integrate our application with Android Studio and Kotlin ensuring an optimal user experience. Our motivation behind this initiative stems from the need to contribute to our nation's progress by promoting governance and aligning with India's aspirations for Digital India. By fostering communication, transparency and accountability our application becomes a tool, in building an empowered and prosperous India. Proposed Work outlines the features, technological framework and societal benefits of our solution that resonates with both government requirements and public aspirations. © 2024 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Impact of different voltage source models on antenna current and input impedance within the boundary element method formalism 24

Impact of different voltage source models on antenna current...

引用

24th International Conference on Applied Electromagnetics and Communications, ICECOM 2023

作者： Susnjara, Anna Poljak, Dragan University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Department of Electronics and Computer Science Split Croatia

ISBN: (纸本)9798350313017

This paper investigates the differences in dipole current and input impedance due to different source models in the framework of boundary element formalism. The half-wavelength and full-wavelength dipole antennas are placed in free space and above a lossy medium. Antenna current and input impedance are obtained by numerically solving the Pocklington's integro-differential equation via Galerkin-Bubnov Indirect Boundary Element Method (GB-IBEM). Two different feeding structures are used as excitation sources, a delta gap source model usually used under GB-IBEM formalism and a magnetic frill source model. Different segment numbers are also used. The results indicate that the current magnitude in case of half-wavelength dipole antenna varies to a relatively great extent depending on the applied voltage generator model. Input impedance does not vary due to different source models, however, its value changes greatly with segment number. © 2023 IEEE.

关键词： Boundary element method

来源：评论

学校读者我要写书评

暂无评论

IoT-Driven Mushroom Farm Automation Using Neural Turing Machines (NTM) 4

IoT-Driven Mushroom Farm Automation Using Neural Turing Mach...

引用

4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Manoj Kumar, S. Monica, C.L. Sunith Babu, L. Manikandan, V. Subramani, Dinesh Malik, Subhash Madanapalle Institute of Technology & Science Department of Mechanical Engineering Angallu India V.R.Siddhartha Engineering College Department of Environmental Science Vijayawada India M. S. Ramaiah Institute of Technology Department of Mechanical Engineering Bengaluru India Department of Computer Science and Engineering Bengaluru India Department of Artificial Intelligence and Data Science Erode India Maharishi Markendeshwar Engineering College Department of Mechanical Engineering Mullana India

ISBN: (纸本)9798350352931

Mushroom cultivation leads global agriculture due to its impact on worldwide trade. One of the main challenges in this area is optimal weather, especially temperature and humidity. Unfortunately, traditional farming's inability to achieve these conditions often leads to low yields. The recommended procedure involves collecting sensor data, constructing the model, and training it. Preprocessing includes spectral smoothing, normalization, and reflectance calibration. Sensors measure motion, temperature, light, and soil moisture. Photo feature extraction uses edge detection to identify objects. The model is trained using NTM. The suggested NTM-based model beats top-tier models like Random Forest (RF) and Support Vector Machine (SVM) with 92.35 percent accuracy. This increasing accuracy shows the model's mushroom production optimization. This proposed uses sensor data and current image processing techniques to improve mushroom farming conditions. NTM-based mushroom cultivation is more efficient and yields more than conventional methods. © 2024 IEEE.

关键词： Soil moisture

来源：评论

学校读者我要写书评

暂无评论

A Transfer-Learning-based Strategy for Autonomous Driving: Leveraging Driver Experience for Vision-Based Control 20

A Transfer-Learning-based Strategy for Autonomous Driving: L...

引用

20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Babaahmadi, Amirreza Masoumi, Fatemeh Sadat Ayati, Moosa Amirpour, Mehrimah University of Tehran School of Mechanical Engineering Tehran Iran Allameh Tabataba'i University Faculty of Mathematics Statistics and Computer Science Tehran Iran Alzahra University Faculty of Engineering Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350383942

This paper explores the utilization of a novel transformer-based architecture for end-to-end learning in predicting steering angles in self-driving scenarios while leveraging a novel robust image processing pipeline to handle diverse environmental situations. Our approach relies solely on visual perception as the input to generate control commands. We trained and evaluated our methodology using a proprietary dataset from a self-driving car simulator consisting of image frames paired with their corresponding steering angles. The presented methodology is robust against overfitting, and it shows superior performance in terms of Mean Squared Error (MSE) and Mean Absolute Error (MAE) compared to previous methods. © 2024 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Feedback-based safe gradient flow for optimal regulation of virtual power plants 14

Feedback-based safe gradient flow for optimal regulation of ...

引用

14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Colot, Antonin Cornélusse, Bertrand Cortés, Jorge Dall'Anese, Emiliano Department of Electrical Engineering and Computer Science University of Liège Belgium Department of Mechanical and Aerospace Engineering University of California San Diego United States Department of Electrical and Computer Engineering Boston University United States

ISBN: (纸本)9781837242689

This paper considers the problem of controlling distributed energy resources (DERs) in a distribution network (DN);the paper focuses on the voltage regulation task and on the concept of virtual power plant (VPP). For the latter, we envision an aggregation of DERs as a VPP that tracks power setpoints at the point of common coupling to provide ancillary services to the bulk power system. We propose a feedback-based controller that pursues solutions to a time-varying AC optimal power flow problem. This controller ensures voltage constraints are met in real time, assuming no voltage measurement errors. The feedback from the system mitigates the controller sensitivity to model uncertainties and eliminates the need for measurements of uncontrollable loads at every node. The feedback-based controller is tested on the IEEE37-node system with delta and wye-connected devices in a strongly unbalanced configuration. © The Institution of engineering & Technology 2024.

关键词： Virtual Power Plants

来源：评论

学校读者我要写书评

暂无评论

Multi-robot Task Allocation in E-Commerce Warehouses: A Comparative Analysis of Distance Minimization and Priority-Based Approaches 21st

Multi-robot Task Allocation in E-Commerce Warehouses: A Comp...

引用

21st ISME International conference on Advances in mechanical engineering, ISME 2023

作者： Singhal, Rahul Goyal, Pranjay Agarwal, Shreya Makkar, Mohit Kumar, Pushpendra Department of Mechanical-Mechatronics Engineering LNMIIT Rajasthan Jaipur302031 India Department of Computer Science and Engineering LNMIIT Rajasthan Jaipur302031 India Department of Mechanical Engineering Graphic Era University Uttarakhand Dehradun248002 India

ISBN: (纸本)9789819736508

This paper presents a methodology for warehouse management with multiple robots for the efficient picking and dropping of consignments. Task allocation is a critical challenge in this process, as it requires determining a collision-free path for all robots based on warehouse management preferences. Two task allocation preferences are considered: (1) minimizing the total distance traveled by all robots to reduce power consumption and improve overall efficiency and (2) prioritizing task allocation by assigning tasks to the nearest available robot for faster delivery. The proposed approach uses the A* algorithm to determine the shortest path for each robot and evaluates the overall lower cost with the Kuhn-Munkres algorithm. Simulation results show the effectiveness of the methodology in achieving efficient task allocation and reducing the overall distance traveled. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Machine learning-based approaches for the diagnosis and detection of brain stroke 2nd

Machine learning-based approaches for the diagnosis and dete...

引用

2nd International Conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Panchal, Trupti Ramasubramanian, Sugayaalini Kumar, Yogesh Department of Mechanical Engineering Pandit Deendayal Energy University Gujarat Gandhinagar India Department of Computer Science and Engineering Pandit Deendayal Energy University Gujarat Gandhinagar India

ISBN: (纸本)9781032738659

This paper presents an in-depth analysis on brain stroke prediction using machine learning based approaches for prediction and classification. We take on a wide range of data sources, including demographic data, medical records, lifestyle conditions, and clinical measures for a prediction model. We managed to determine significant patterns and risk factors related to stroke owing to the dataset utilised in this study. Feature selection techniques are utilised to identify the most relevant predictors, enhancing the efficiency and interpretability of the model. In addition, we study alternative data preparation methods, such as managing missing values, outlier identification, and feature scaling, to ensure data quality and model resilience. © 2025 The Author(s).

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Anomaly detection for sustainable automotive manufacturing

Anomaly detection for sustainable automotive manufacturing

引用

2024 Low-Cost Digital Solutions for Industrial Automation, LoDiSA 2024

作者： Smallwood, Eleanor Burke, Richard Barnes, Andrew P. Department of Mechanical Engineering University of Bath Bath United Kingdom Department of Computer Science University of Bath Bath United Kingdom

ISBN: (纸本)9781837242672

The automotive sector provides society with the means to move people and goods, however the increasing need for climate change mitigation places responsibility on automotive manufacturers to develop low-carbon technologies to meet these needs. These rapid technological developments are prone to high costs, skill gaps, and sub-optimal energy-intensive practices, particularly within the testing environments for automotive components. Automated safety thresholds are in place to detect large fluctuations in real-time data, whilst the detection of other, more nuanced faults is manual, but these have the risk of undermining vehicle development. As such, this process is resource intensive, such as the personnel time and energy consumed to rerun tests containing faults, and the financial costs associated with these. Here we show the ability of unsupervised, data-driven machine learning based anomaly detection methods to identify anomalous time-periods within an automotive test, including faults in either the test component or in the test facility equipment, without the need for training data. We compare the performance of three clustering algorithms - k-means, agglomerative clustering, and DBSCAN - based on their run time and ability to create defined anomalous clusters of the two anomalies. K-means was able to identify the two anomalies with eight total clusters in half the time of agglomerative clustering. DBSCAN clustered the data in half the time of k-means however was unable to create defined anomalous clusters. These results illustrate the potential for unsupervised data-driven anomaly detection to operate within automotive manufacturer testing environments. These methods provide a low-cost digital solution to the resource demands associated with the traditional processes used by automotive manufacturers when developing sustainable transport options. © This is an open access article published by the IET under the Creative Commons Attribution License (http://creativeco

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Resume Ranking System Using Machine Learning 3rd

A Novel Approach for Resume Ranking System Using Machine Lea...

引用

3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Rajesh, B. Vignesh, G. Ram Sai Chamakura, Sai Kumar Karthik, N. Vani, V. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal609609 India Department of Mechanical Engineering National Institute of Technology Karaikal Puducherry609609 India

ISBN: (纸本)9789819783540

Nowadays, many job ads are attracting a vast number of applications in less time on the internet. Screening and sorting these resumes manually is a very time-consuming process and costs a huge amount of money for recruiting organizations. This research paper suggests an automated method for matching resumes to open vacancies. To identify the most accurate machine learning approach, it investigates several of them, including Random Forest, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Tree, Logistic Regression, Naïve Baye’s Classifier. Based on the findings of this research, Random Forest produces more accurate results for a given dataset. By using this automatic resume categorization method, the recruiting process will be revolutionized in terms of cost, time, and justice. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：