Quality Assessment of Ambulatory Electrocardiogram Signals by Noise Detection using Optimal Binary Classification

In order to improve the diagnostic capability in Ambulatory Electrocardiogram signal and to reduce the noise signal impacts, there is a need for more robust models in place. In terms of improvising to the existing solutions, this article explores a novel binary classifier that learns from the features optimized by fusion of diversity assessment measures, which performs Quality Assessment of Ambulatory Electrocardiogram Signals (QAAES) by Noise Detection. The performance of the proposed model QAAES has been scaled by comparing it with contemporary models. Concerning performance analysis, the 10-fold cross-validation has been carried on a benchmark dataset. The results obtained from experiments carried on proposed and other contemporary models for cross-validation metrics have been compared to signify the sensitivity, specificity, and noise detection accuracy

Unmanned Aerial Vehicle Design for Smart City Application

Nowadays, Unmanned Aerial Vehicles (UAVs) or drones are also one of the applications to provide the required services and to gather information from the target location.  Because smart city applications effectively deal the drone interaction and enhance the human lifestyle with drones. Moreover, UAVs are generally utilized due to their privacy threats, lower cost, pose security, and versatility, which request dependable detection at lower altitudes. However, the less sensing module in the drone has earned the low sensing accuracy of location tracking. So, this paper aims to develop a novel Firefly-based Recurrent Neural Mechanism (FRNM) to enrich the sensing capacity of the drone vehicle. In addition, the sound of the research is medicine delivery through UAVs in emergencies. This UAV system is one of the most crucial features to delivering essential medical items aids by reaching properly correspondent patients.  Moreover, the client's needs are stored in the FRNM cloud then that stored data is trained to the UAV machine. Hereafter, based on the trained details, the drone can reach the destination and has delivered the requested medicine to the specific clients. The planned design is drawn in Network Simulator (NS2) environment, and the robustness of the projected replica is valued by calculating the chief parameters. Hereafter, the improvement score was valued by the comparison assessment. Hence, the FRNM has reported the finest performance by earning less location finding duration, running period, and error rate

EASR: Graph-based Framework for Energy Efficient Smart Routing in MANET using Availability Zones

Energy consumption in MobileAdhoc Network (MANET) is a topic of research from more than a decade. Althoughthere are multiple archival of literatures, that have proposed variousenergy-efficient algorithms for reducing the energy consumption to improveenergy efficiency. Establishing correct and reliable route is important designissue in MANET, but a more challenging goal is to provide energy efficientroute. But, it was observed that majority of such energy efficient routingprotocols just give symptomatic solution which addresses and mitigated theenergy issues overlooking various associated issues like quality of services.Moreover, in majority of research previous studies it is found that AODV andDSDV are highly in adoption rate among the researcher for solving energy issuesusing routing protocols. This manuscript after reviewing some of thesignificant literatures in past explored issues in existing AODV and DSDVand  proposes a novel energy efficientrouting protocols by incorporating a new actor called availability zone. Theproposed model shows better energy efficiency and QoS compared to AODV andDSDV

Low Latency Prefix Accumulation Driven Compound MAC Unit for Efficient FIR Filter Implementation

135–138This article presents hierarchical single compound adder-based MAC with assertion based error correction for speculation variations in the prefix addition for FIR filter design. The VLSI implementation of approximation in prefix adder results show a significant delay and complexity reductions, all this at the cost of latency measures when speculation fails during carry propagation, which is the main reason preventing the use of speculation in parallel-prefix adders in DSP applications. The speculative adder which is based on Han Carlson parallel prefix adder structure accomplishes better reduction in latency. Introducing a structured and efficient shift-add technique and explore latency reduction by incorporating approximation in addition. The improvements made in terms of reduction in latency and merits in performance by the proposed MAC unit are showed through the synthesis done by FPGA hardware. Results show that proposed method outpaces both formerly projected MAC designs using multiplication methods for attaining high speed

Low Latency Prefix Accumulation Driven Compound MAC Unit for Efficient FIR Filter Implementation

This article presents hierarchical single compound adder-based MAC with assertion based error correction for speculation variations in the prefix addition for FIR filter design. The VLSI implementation of approximation in prefix adder results show a significant delay and complexity reductions, all this at the cost of latency measures when speculation fails during carry propagation, which is the main reason preventing the use of speculation in parallel-prefix adders in DSP applications. The speculative adder which is based on Han Carlson parallel prefix adder structure accomplishes better reduction in latency. Introducing a structured and efficient shift-add technique and explore latency reduction by incorporating approximation in addition. The improvements made in terms of reduction in latency and merits in performance by the proposed MAC unit are showed through the synthesis done by FPGA hardware. Results show that proposed method outpaces both formerly projected MAC designs using multiplication methods for attaining high speed

Segmentation Methods for Severity Regurgitation: A Comparative Analysis

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