17 hasil untuk "Premkumar Chithaluru"
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Artikel Jurnal
Energy-efficient blockchain implementation for Cognitive Wireless Communication Networks (CWCNs)
Considering the computation resources available with sensor devices and the value and validity of Cognitive Wireless Communication Network (CWCN), traditional blockchain is not feasible for CWCN. Further, considering the security and privacy for CWCN that can directly impact human life (as in the…
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A Novel Approach to Integrating Uncertainty into a Push Re-Label Network Flow Algorithm for Pit Optimization
The standard optimization of open-pit mine design and production scheduling, which is impacted by a variety of factors, is an essential part of mining activities. The metal uncertainty, which is connected to supply uncertainty, is a crucial component in optimization. To address uncertainties…
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Improved Recurrent Neural Network Schema for Validating Digital Signatures in VANET
Vehicular ad hoc networks (VANETs) allow communication between stationary or moving vehicles with the assistance of wireless technology. Among various existing issues in smart VANETs, secure communication is the key challenge in VANETs with a 5G network. Smart vehicles must communicate with a broad…
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An Optimized Open Pit Mine Application for Limestone Quarry Production Scheduling to Maximize Net Present Value
This study involves a working limestone mine that supplies limestone to the cement factory. The two main goals of this paper are to (a) determine how long an operating mine can continue to provide the cement plant with the quality and quantity of materials it needs, and (b) explore the viability of…
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Hybrid deep learning framework for accurate classification of high dimensional genomic data
Abstract High-dimensional genomic datasets often contain redundant, noisy, and sparse features that make accurate classification challenging for conventional deep learning (DL) models. Existing approaches generally fail to maintain interpretability and stability when confronted with heterogeneous…
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An Evolutionary Technique for Building Neural Network Models for Predicting Metal Prices
In this research, a neural network (NN) model for metal price forecasting based on an evolutionary approach is proposed. Both the neural network model’s network parameters and network architecture are selected automatically. The time series metal price data set is used to construct a novel fitness…
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RETRACTED: Joshi et al. An Evolutionary Technique for Building Neural Network Models for Predicting Metal Prices. Mathematics 2023, 11, 1675
The journal and authors retract the article entitled “An Evolutionary Technique for Building Neural Network Models for Predicting Metal Prices” [...]
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Reconfigurable intelligent surface and UAV coordination for reliable THz wireless networks
Terahertz (THz) communication is a promising enabler for next-generation wireless networks because it can support ultra-high data rates. However, severe path loss, molecular absorption, and high sensitivity to blockage significantly limit coverage and reliability. To address these challenges, this…
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A scalable and secure federated learning authentication scheme for IoT
Abstract Secure and scalable authentication remains a fundamental challenge in Internet of Things (IoT) networks due to constrained device resources, dynamic topology, and the absence of centralized trust infrastructures. Conventional password-based and certificate-driven authentication schemes…
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A self-attention driven multi-scale object detection framework for adverse weather in smart cities
Abstract Detecting abandoned or small-scale objects under adverse weather conditions remains a significant challenge for maintaining road safety and urban security in smart cities. Existing detection systems often suffer performance degradation in the presence of fog, rain, snow, or sand, where…
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A Novel Large-Scale Stochastic Pushback Design Merged with a Minimum Cut Algorithm for Open Pit Mine Production Scheduling
Traditional optimization of open pit mine design is a crucial component of mining endeavors and is influenced by many variables. The critical factor in optimization is the geological uncertainty, which relates to the ore grade. To deal with uncertainties related to the block economic values of…
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Suspended Sediment Yield Forecasting with Single and Multi-Objective Optimization Using Hybrid Artificial Intelligence Models
Rivers play a major role within ecosystems and society, including for domestic, industrial, and agricultural uses, and in power generation. Forecasting of suspended sediment yield (SSY) is critical for design, management, planning, and disaster prevention in river basin systems. It is difficult to…
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Secure cloud computing: leveraging GNN and leader K-means for intrusion detection optimization
Abstract Over the past two decades, cloud computing has experienced exponential growth, becoming a critical resource for organizations and individuals alike. However, this rapid adoption has introduced significant security challenges, particularly in intrusion detection, where traditional systems…
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Optimizing internet of things security through blockchain enabled software defined networking
Abstract The Internet of Things (IoT) faces increasing security challenges, as traditional encryption-based methods often fail to prevent cyberattacks while maintaining reliable and cost-effective communication. To overcome these issues, this work introduces a security model that enhances existing…
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EDSSR: a secure and power-aware opportunistic routing scheme for WSNs
Abstract Motivated by the pivotal role of routing in Wireless Sensor Networks (WSNs) and the prevalent security vulnerabilities arising from existing protocols, this research tackles the inherent challenges of securing WSNs. Many current WSN routing protocols prioritize computational efficiency but…