Wireless sensor networks (WSNs) are expected to find extensive applicability and accelerating deployment in the future. However, the main challenge faced in WSN is its perishing lifetime. The process of clustering a network is a popular mechanism employed for the purpose of extending the lifespan of WSNs and thereby making efficient data transmission. The main aim of a clustering algorithm is to elect an optimal cluster head (CH). The recent research trend suggests meta‐heuristic algorithms for the selection of optimal CHs. Meta‐heuristic algorithms possess the advantages of being simple, flexible, derivation‐free, and avoids local optima. This research proposes a novel hybrid grey wolf optimiser‐based sunflower optimisation (HGWSFO) algorithm for optimal CH selection (CHS) under certain factor constraints such as energy spent and separation distance, such that the network lifetime is enhanced. Sunflower optimisation (SFO) is employed for a broader search (exploration) where the variation of the step‐size parameter brings the plant closer to the sun in search of global refinement, thus increasing the exploration efficiency. Grey wolf optimisation (GWO) is employed for a narrow search (exploitation), where the parameter coefficient vectors are deliberately required to emphasise exploitation. This balances the exploration‐exploitation trade‐off, prolongs the network lifetime, increases the energy efficiency, and enhances the performance of the network with respect to overall throughput, residual energy of nodes, dead nodes, alive nodes, network survivability index, and convergence rate. The superior characteristic of the suggested HGWSFO is validated by comparing its performance with various other existing CHS algorithms. The overall performance of the proposed HGWSFO is 28.58%, 31.53%, 48.8%, 49.67%, 54.95%, 70.76%, and 87.10%, better than that of GWO, SFO, particle swarm optimisation (PSO), improved PSO, low‐energy adaptive clustering hierarchy (LEACH), LEACH‐centralised, and direct transmission, respectively.
Background: Community-level surveys of potentially malignant and malignant oral lesions are helpful to accurately determine the prevalence and aid in planning population-based strategies for oral cancer prevention. Objectives: We aimed to assess the disease burden through a systematic oral cancer screening program in a defined semi-urban population in Ranipet district (Tamil Nadu, India). Materials and Methods: A multiphase community-based screening program was conducted by the Ragas Dental College and Hospital, Chennai, India, in partnership with Thirumalai Mission Trust Hospital in Ranipet district (Tamil Nadu, India) in a zone-wise manner from Aug 1, 2018 to Dec 31, 2019. Phase I consisted of screening of those who fulfilled the eligibility criteria; demographic data were collected by trained dentists, following which toluidine blue staining of suspected potentially malignant lesions was done. Subjects whose oral lesions stained positive were referred to a hospital where the staining procedure was repeated for confirmation, and then biopsy was done for all subjects by a trained dentist. The subjects were followed up, and appropriate referrals were initiated for all the subjects based on their diagnosis. Descriptive statistics were used to analyze the distribution of potentially malignant cases. Sensitivity, specificity, and predictive values were calculated for the clinical diagnosis using the histopathologic diagnosis as the gold standard. Results: A total of 1389 tobacco users (1012 [72.9%] men) and 3140 non-tobacco users were evaluated. Among them, 194 (14%) demonstrated clinical abnormalities in their oral mucosa; 157 required follow-up and were referred. Of the 157 referrals, 140 (89.2%) went for follow-up, and 84 (64%) of them required biopsies. Of the 74 eligible biopsies examined (7 dropped out and 3 biopsies were rejected due to inadequate tissue), 1 had definite malignancy (1.4%), 41 (55.4%) had potentially malignant oral disorders, and 32 (43.2%) had non-specific features. The overall sensitivity, specificity, positive predictive value, and negative predictive value for the clinical diagnosis made at the screening program were 88%, 25%, 61%, and 61%, respectively. Conclusion: Systematic visual oral screening restricted to high-risk individuals is a worthwhile initiative for the detection and control of oral cancer. Visual screening and early detection of premalignant oral disorders has the potential for early detection of potentially malignant and malignant oral lesions, and thus could play a pivotal role in disease control and improving patient outcomes. (Partial funding provided by the University Research Committee, The TN Dr. MGR Medical University, Guindy, Chennai; and the Thirumalai Charitable Trust, Ranipet, India)
Compared to conventional inverter (square wave) multi-level inverter offers quality power owing to different voltage levels utilization in average and high voltage. Besides it also reduces Total Harmonic Distortion in the distributed system and dv/dt across power switches. This advantage is transcendently appropriate for cascaded diode connected converter that can be worked to create more number of levels using asymmetrical voltage source because of their integrated arrangement. However, this benefit no longer exist because it requires many dc links (batteries or rectifiers) which is costlier. Substitute method of implementing single low voltage floating DC link is to recompense voltage distortion using Neutral-Point-Clamped (NPC) converter. This NPC output and controlled floating single DC-link voltage along with controlled PWM strategy reduces the THD. This improves the bandwidth and make simpler the current control scheme. These motivated the study and analyze the performance of a Diode Clamp based three phase nine level multilevel inverterusingnovel PWM approaches in MATLAB 2014b and PROTEUS for hardware development. Thus low power prototype is developed and its performance is shown.
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