检索结果-内蒙古大学图书馆

Revolutionizing Wireless Rechargeable Sensor Networks: Speed Optimization-based Charging Scheduling Scheme (SOCSS) for efficient multi-node energy transfer

引用

Swarm and Evolutionary Computation 2025年 96卷

作者： Goyal, Riya Tomar, Abhinav Department of Computer Science and Engineering Netaji Subhas University of Technology New Delhi110078 India

Benefiting from the breakthrough of Wireless Energy Transfer (WET) technology, scheduling multiple Mobile Chargers (MCs) to charge sensor nodes can significantly prolong the lifetime of Wireless Rechargeable Sensor Networks (WRSNs). While previous studies have primarily focused on on-demand recharging within WRSNs, more consideration must be given to utilizing multi-node energy transfer with optimal charging locations to devise efficient charging schedules for requesting sensor nodes. Moreover, existing approaches assume a constant travel speed for MCs and utilize omnidirectional WET, leading to increased energy consumption for MCs and consequently affecting overall charging efficiency. To address these challenges, we propose a novel Speed Optimization-based Charging Scheduling Scheme (SOCSS) for multiple MCs in WRSNs. The initial phase of SOCSS involves clique-based network partitioning to identify minimum cliques and determine optimal charging locations to perform efficient multi-node energy transfer for sensor nodes. The subsequent phase encompasses scheduling and path planning, where the charging schedule is established using efficient Quantum-inspired Particle Swarm Optimization. By integrating speed optimization with the charging schedule, the energy consumption of the MCs is minimized, leading to cost-effective planning of the charging path for energy-constrained MCs. Extensive simulations are conducted to showcase the supremacy of SOCSS across a range of network parameters compared to prior art. In particular, SOCSS has achieved an impressive average reduction of 36.2% in the number of stopping points for MCs, a remarkable 38.9% decrease in the total travel distance, and a 15.7% reduction in the charging delay. © 2025 Elsevier B.V.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Task offloading of IOT device in fog-enabled architecture using deep reinforcement learning approach

引用

Pervasive and Mobile Computing 2025年 112卷

作者： Abhinav Tomar Megha Sharma Ashwarya Agarwal Aditya Nath Jha Jai Jaiswal Department of Computer Science and Engineering Netaji Subhas University of Technology New Delhi 110078 India

The rapid growth of IoT devices has strained traditional cloud-centric architectures, revealing limitations in latency, bandwidth, and reliability. Fog computing addresses these issues by decentralizing resources closer to data sources, but task offloading and resource allocation remain challenging due to dynamic workloads, heterogeneous resources, and strict QoS requirements. This study models task offloading as a multi-objective optimization problem, considering task priority, energy efficiency, latency, and deadlines. Using a Markov Decision Process (MDP), it applies three Deep Reinforcement Learning (DRL) algorithms — DQN, DDPG, and SAC — in a multi-agent fog computing setup. Unlike prior work focused on single-agent or isolated metrics, this approach captures inter-node dependencies to improve overall resource use. Simulations show SAC achieves a 97.3% task deadline success rate and improves resource efficiency by 10.1%, highlighting its effectiveness in managing dynamic fog environments. These results advance scalable, adaptive offloading strategies for future IoT systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of Leptospirosis Bacteria in Rodent Urine by Surface Plasmon Resonance Sensor Using Graphene

引用

Photonic Sensors 2021年第3期11卷 305-313页

作者： Surjeet Raikwar Y.K.Prajapati D.K.Srivastava J.B.Maurya J.P.Saini Department of Electronics and Communication Engineering Bundelkhand Institute of Engineering and TechnologyJhansiUttar Pradesh284128India Department of Electronics and Communication Engineering Motilal Nehru National Institute of Technology AllahabadPrayagrajUttar Pradesh211004India Netaji Subhas University of Technology DwarkaNew Delhi110078India

In this paper, a graphene-coated surface plasmon resonance sensor is designed for the examination of Rodent urine which is responsible for Leptospirosis bacteria. Rodent urine is considered as sensing medium. Graphene surface is activated by phosphate-buffered saline solution for better attachment of Leptospirosis bacteria on its surface. Oliguria and Polyuria are the Rodent urine with high and low concentrations of Leptospirosis bacteria, respectively. The transfer matrix method is used for the formulation of reflection intensity of p-polarized light. The reflectance curves for angular interrogation are plotted and the results are obtained in terms of sensitivity, detection accuracy, and quality factor. The significantly high sensitivity and detection accuracy for Oliguria distinguishes it from Polyuria having lower sensitivity.

关键词： Surface plasmon resonance sensor active metal layer Leptospirosis bacteria

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Project's Technical and Non-Technical Skill Extraction

A Novel Approach for Project's Technical and Non-Technical S...

引用

2019 International Conference on Computing, Power and Communication Technologies, GUCON 2019

作者： Bhatia, Kanika Chakraverty, Shampa Nagpal, Sushama Poddar, Anupam Lamba, Mohit Netaji Subhas University of Technology Department of Computer Engineering Sector-3 Dwarka New Delhi110078 India

ISBN: (纸本)9789353510985

Project-Oriented learning has been a popular approach for imparting practical knowledge among the students. But its high time that we focus not only on technical and practical knowledge but also on impersonal skills of the students. Integration of non-technical skills has become highly important to meet the industry expectations. Thus, projects need to be studied on both factors, so that students can focus not only developing technical skills but also learning managerial skills to work with their team members in a constructive manner. In this paper we have made a project-oriented skill extractor which not only extracts the technical skills but also the non-technical skills that are required for completion of a particular project. © 2019 Galgotias University.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

EDABTOS: Energy-delay aware binary task offloading strategy of IoT devices in a fog-enabled architecture

引用

Expert Systems with Applications 2025年 290卷

作者： Megha Sharma Abhinav Tomar Department of Computer Science and Engineering Netaji Subhas University of Technology New Delhi 110078 India

Fog computing addresses the low-latency computational demands of IoT applications by bringing resources closer to end users, reducing reliance on centralized cloud servers. However, traditional task offloading strategies struggle with resource heterogeneity, fluctuating workloads, and energy constraints, leading to suboptimal energy-latency trade-offs. To overcome these challenges, we propose EDABTOS (Energy-Delay Aware Binary Task Offloading Strategy), an adaptive approach leveraging Multi-Armed Bandit (MAB) methods. It dynamically optimizes task execution and resource allocation in fog-enabled IoT systems, improving upon ϵ -Greedy and Upper Confidence Bound (UCB) strategies for handling dynamic data transmission. Simulations show that EDABTOS achieves a 16.21 % latency reduction and 3.19 % energy efficiency improvement, outperforming conventional MAB techniques. These improvements align with and surpass recent advancements in intelligent task offloading, reinforcing EDABTOS as an effective strategy for real-world fog computing deployments. By validating its feasibility, this study contributes to the development of adaptive, energy-efficient task offloading mechanisms essential for next-generation IoT applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimizing Blood Bank Management with Cloud-Hosted Long Short-Term Memory Models for Inventory Forecasting and Utilization

Optimizing Blood Bank Management with Cloud-Hosted Long Shor...

引用

Electronics and Renewable Systems (ICEARS), International Conference on

作者： R. Aiyshwariya Devi Sree Southry S S. Rajanarayanan S. Chandra Sekaran Audithan Sivaraman S. Srinivasan Department of Artificial Intelligence and Data Science R.M.K. College of Engineering and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Sona College of Technology Salem Tamil Nadu India Department of Computer Science and Engineering Vinayaka Mission’s Research Foundation (DU) Vinayaka Mission’s Kirupananda Variyar Engineering College Salem Tamil Nadu India Department of Computer Science and Engineering P.S.V College of Engineering and Technology Krishnagiri Tamil Nadu India Department of Information Technology Netaji Subhas University of Technology (Govt of NCTDelhi) Jafferpur New Delhi India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

This research presents an innovative method for blood bank management using Cloud-based Long Short-Term Memory (LSTM) models for precise inventory forecasting and optimization. The objective of this research is to increase blood bank efficiency by utilizing LSTM models to accurately estimate demand, optimize inventory levels, and enhance overall resource utilization. The system uses cloud computing to provide real-time demand forecasting, minimizing blood waste and assuring a reliable supply for healthcare requirements. LSTM models use historical data to identify long-term trends and variations in blood demand, facilitating accurate inventory forecasting. This predictive system optimizes the allocation process, resulting in improve resource utilization and increased operational efficiency. In compared to traditional techniques, the proposed system provides a more scalable and flexible solution by using cloud technology to provide continuous monitoring and dynamic modifications of inventory levels. It provides a robust framework for management of blood supply and enhancing patient care for improved resource management. Future enhancements may include broadening the system to incorporate real-time multi-source data integration and investigating hybrid machine learning models to better optimize demand forecasts.

关键词： Cloud computing Computational modeling Demand forecasting Medical services Predictive models Real-time systems Resource management Blood Long short term memory Optimization

来源：评论

学校读者我要写书评

暂无评论

Extraction of technical and non-technical skills for optimal project-team allocation 1

引用

2nd International Conference on Machine Intelligence and Signal Processing, MISP 2019

作者： Bhatia, Kanika Chakraverty, Shampa Nagpal, Sushama Kumar, Amit Lamba, Mohit Poddar, Anupam Department of Computer Engineering Netaji Subhas University of Technology Sector-3 DwarkaNew Delhi110078 India

ISBN: (数字)9789811513664

ISBN: (纸本)9789811513657

Project portfolio management (PPM) is a crucial subject matter in academics that needs to be explored at skill level for both the projects and the students. Skill matching can play a major role in not only determining the requirements of the project but also utilizing the skills of the students. When it comes to skills one should focus on the technical skills but non-technical skills are equally important to be taken into account while performing matching. Non-technical skills are needed to be acquired by the student as a part of social and work ethics. In this paper, we have proposed a model which performs both skill extraction and skill matching of the projects to a team of students. The skill extraction involves both technical and non-technical skill extraction while for skill matching. Formal concept analysis (FCA) and project-oriented stable marriage algorithm have been employed. This model matches a project to a team of students while analyzing both technical and non-technical skills required for the project and of the student. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

An Intelligent Prediction Model of COVID-19 in India using Hybrid Epidemic Model

An Intelligent Prediction Model of COVID-19 in India using H...

引用

2020 International Conference on Smart Electronics and Communication, ICOSEC 2020

作者： Kumar, Manoj Bareja, Jatin Singh, Manjot Sharma, Rupanshu Delhi Technological University Department of Computer Science Engineering Delhi India Netaji Subhas Institute of Technology Manufacturing Process and Automation Engineering Delhi India

ISBN: (纸本)9781728154619

This article presents the current situation of COVID 19 spread in India and how it is impacted by various measures taken by the administration. Data source is taken (till 15th June 2020) from World Health organization (WHO) to study various trends and pattern. Hybrid epidemic susceptible-infected recovered model is used to make predictions at every stage of coronavirus. The basic reproduction number R0, is constructed using a logistic function. An improved or hybrid epidemic model is build based on various other factors to build a logistic infection rate to analyse the patterns and trend in the data. Secondly, ICU beds and ventilators available per 100, 000 inhabitants is also taken in account for critical. Also, the timeline for changing the stage of coronavirus is used from various reliable resources. Moreover, in comparison with the traditional SIR models, accuracy in the predictions has significantly increased with the R2 value of 96.8 percent for the future days in India.. © 2020 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Theoretical exploration of the volumetric and optical properties of 3-amino 1-propanol and isomeric butanol at 298.15 K-318.15 K: PFP theory, Graph theoretical approach, and FTIR studies

Chemical Thermodynamics and Thermal Analysis

引用

Chemical Thermodynamics and Thermal Analysis 2025年 18卷

作者： Verma, Sweety Kumari, Kavitha Min, Juwon Song, In–Hyoup Gahlyan, Suman Maken, Sanjeev Chemical Process Solution Research Center Korea Research Institute of Chemical Technology Daejeon 34114 South Korea Department of Chemistry Baba Mastnath University Rohtak 124001 India Department of Applied Sciences and Humanities Panipat Institute of Engineering and Technology Samalkha 132102 India Department of Chemistry Netaji Subhas University of Technology New Delhi 110078 India

Volumetric and optical properties for binary mixtures containing 3–amino-1–propanol (3AP) + isomeric butanol was measured in the temperature range (298.15–318.15) K. Excess molar volume (V_m^E) and deviation in refractive index (Δn_D) were computed using the estimated parameters. The Prigogine–Flory–Patterson (PFP) theory and Graph theoretical approach (GTA), were utilized to analyze the V_m^Edata at 298.15 K, respectively. Furthermore, the molecular species of various components are predicted to exist in both pure and mixed states by the GTA. The excess/deviation in properties was further interpreted in terms of intermolecular interactions. Theoretical and experimental results agree well. The temperature effect on measured properties was also discussed. For the theoretical determination of n_D various mixing rules were also used. Furthermore, FT–IR spectroscopy confirmed the formation of hydrogen bonding among the molecules in the components. © 2025 The Authors

关键词： 3–amino-1–propanol (3AP) Density FT-IR Graph theoretical approach Isomers of butanol Prigogine–Flory–Patterson theory

来源：评论

学校读者我要写书评

暂无评论

Gene Co expression analysis for identifying some regulatory genes in human lung cancer

Gene Co expression analysis for identifying some regulatory ...

引用

IEEE Electron Devices Kolkata Conference (EDKCON)

作者： Subir Hazra Amit Kumar Shaw Palash Das Anupam Ghosh Department of Information Technology Meghnad Saha Institute of Technology Kolkata India Department of Computer Science & Engineering Netaji Subhash Engineering College Kolkata India

ISBN: (纸本)9781665472067

Cancer occurs owing to significant variances in the gene expression level. Like all cancer lung cancer is the result of abnormalities in the regulatory systems of genes. It is evident that, gene expression systems can successfully frame phenotypes. Hence, it is important to analyze co expressed genes that could shed light on the fundamental principles governing the transcriptional regulatory processes influencing tumor formation and evolution. Oligonucleotide microarray and sequencing technology advancements have made it possible to quickly monitor the expression of genes in different tissues, providing a great mechanism in cancer research domain In the present article we have designed an algorithm which is focused on analyzing the gene correlation values of human lung expression and studying the gene correlation network. The algorithm effectively identifies some regulatory genes having significant association with lung cancer.

关键词： Sequential analysis Correlation Lung cancer Classification algorithms Gene expression Object recognition Prognostics and health management

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：