•Analyzes the performance of ANN and ANFIS MPPT algorithms by stand alone PV system.•ISSBC with ANFIS can provide the overall efficiency higher than ANN.•CHBMLI integrate with SHE ANN modulation ...technique improve output voltage quality.•Simulation and hardware results show the ANFIS algorithm efficient than ANN algorithm.
This paper presents a unique combination of an interleaved soft switched boost converter (ISSBC) run by a set of two photovoltaic panel (PV) with a distributed MPPT, suitable to guarantee MPPT even under partial shadowed conditions, managed by an adaptive neuro fuzzy inference system trained by the training data derived from a particle swarm optimization (PSO–ANFIS) unit. The ISSBC is followed by a, single phase cascaded H bridge five-level inverter (CHI) driven by the individual DC outputs of the ISSBC, with selective harmonic elimination scheme to eliminate typically the seventh order harmonics. A comparison of different intelligent distributed maximum power point tracking (MPPT) algorithms for photovoltaic (PV) system under partial shadow conditions is carried out. The use of the ISSBC guarantees mitigation of ripple and it is meant to handle higher currents with minimal switching losses. Simulation was carried out in the Matlab Simulink environment and an experimental verification with a scaled down model validated the proposed scheme. It has been thus established, by both simulation and experimental verification, that the PSO–ANFIS model of distributed MPPT scheme of control outperforms other schemes of control for MPPT.
In recent years, natural fiber and its composites have attracted researchers due to environmental awareness. It is essential to identify new cellulose fibers for the potential polymer reinforcement. ...The current study deals with the investigation of natural cellulosic fibers extracted from the stem of Leucas aspera plants. The obtained fibers were treated with silane for effective use in composite applications. The physical, chemical, crystallinity, thermal stability, and morphological characteristics were analyzed for both untreated and silane-treated Leucas aspera fibers using chemical analysis, X-Ray diffraction test, fourier transform infrared spectroscopy, thermogravimetric analysis, and SEM images. The results showed that silane treatment removed excess lignin, wax and hemicellulose contents from Leucas aspera fibers and helped to increase its bonding characteristics with the matrix in composite applications leading to enhanced results compared to the untreated samples. There was a 2.1 times increase in crystalline index and better thermal stability with a char residue of 39%. To prove the applications' suitability, epoxy composites and friction composites in the form of brake pads were developed and analyzed for their mechanical performance as per ASTM and standard industrial practice. Increase in ultimate tensile strength was 56 MPa for silane-treated Leucas aspera fiber based epoxy composites while it was 43 MPa compared to its untreated samples. In brake pads, hardness was 93 for silane-treated LA fiber-based brake pads and 87 for the untreated.
Traditional screening of cervical cancer type classification majorly depends on the pathologist’s experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer ...prevention. In conjunction with precancer screening and treatment, colposcopy has played an essential role in lowering the incidence and mortality from cervical cancer over the last 50 years. However, due to the increase in workload, vision screening causes misdiagnosis and low diagnostic efficiency. Medical image processing using the convolutional neural network (CNN) model shows its superiority for the classification of cervical cancer type in the field of deep learning. This paper proposes two deep learning CNN architectures to detect cervical cancer using the colposcopy images; one is the VGG19 (TL) model, and the other is CYENET. In the CNN architecture, VGG19 is adopted as a transfer learning for the studies. A new model is developed and termed as the Colposcopy Ensemble Network (CYENET) to classify cervical cancers from colposcopy images automatically. The accuracy, specificity, and sensitivity are estimated for the developed model. The classification accuracy for VGG19 was 73.3%. Relatively satisfied results are obtained for VGG19 (TL). From the kappa score of the VGG19 model, we can interpret that it comes under the category of moderate classification. The experimental results show that the proposed CYENET exhibited high sensitivity, specificity, and kappa scores of 92.4%, 96.2%, and 88%, respectively. The classification accuracy of the CYENET model is improved as 92.3%, which is 19% higher than the VGG19 (TL) model.
Alzheimer's Disease (AD) is the most common cause of dementia globally. It steadily worsens from mild to severe, impairing one's ability to complete any work without assistance. It begins to outstrip ...due to the population ages and diagnosis timeline. For classifying cases, existing approaches incorporate medical history, neuropsychological testing, and Magnetic Resonance Imaging (MRI), but efficient procedures remain inconsistent due to lack of sensitivity and precision. The Convolutional Neural Network (CNN) is utilized to create a framework that can be used to detect specific Alzheimer's disease characteristics from MRI images. By considering four stages of dementia and conducting a particular diagnosis, the proposed model generates high-resolution disease probability maps from the local brain structure to a multilayer perceptron and provides accurate, intuitive visualizations of individual Alzheimer's disease risk. To avoid the problem of class imbalance, the samples should be evenly distributed among the classes. The obtained MRI image dataset from Kaggle has a major class imbalance problem. A DEMentia NETwork (DEMNET) is proposed to detect the dementia stages from MRI. The DEMNET achieves an accuracy of 95.23%, Area Under Curve (AUC) of 97% and Cohen's Kappa value of 0.93 from the Kaggle dataset, which is superior to existing methods. We also used the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to predict AD classes in order to assess the efficacy of the proposed model.
The objective of this research work is to study the impact of graphite forms used as solid lubricant additives on brake friction materials performance. Three composites were fabricated using the ...conventional process and were characterised for its physical, chemical, mechanical and thermal properties conforming to industrial standards. The thermal stability of the graphite particles and developed composites was measured in an air atmosphere using the thermogravimetric analyser. The tribological performances were studied using the Chase friction test machine as per IS-2742 Part-4 standard. The results indicated that the friction composite containing expandable graphite exhibited better thermal stability with good fade and recovery performances. This led to enhance wear resistance and stable friction due to its better heat dissipation and lubricity comparing with the other two composites. An empirical relationship for the friction and wear was developed based on Chase test results. The worn surface morphologies of the Chase tested composites were analysed using scanning electron microscopy to study the sensitivity of the friction–wear mechanisms to the graphite-type effect.
•Investigation on economic feasibility of PV/diesel system in various climatic zones.•HOMER is used to solve economic feasibility analysis.•By the sensitivity analysis, the net present cost is ...reduced.•Optimum climatic zone in Tamil Nadu, India is recommended.
With the increasing threat to environment and the fast depleting fossil fuel resources, hybrid power systems consisting of two or more renewable energy sources such as solar PV, wind, biomass, ocean thermal-with or without the back up of diesel generator have come to the forefront. These hybrid systems are normally integrated with battery banks for total reliability; such systems have brought about better quality of life in remote areas of developing economics. The remote areas in the state of Tamil Nadu in India possess excellent renewable energy sources. These areas fall under different climatic zones, are sparsely populated and are in the process of development. Though these areas are connected to the grid, Tamil Nadu grid is not stable; it is currently experiencing 40% short fall in generation. Thus grid power is available to these remote areas only for 10h a day and even when available, there are voltage frequency problems. This paper analyses the economic feasibility of installing and operating hybrid systems in these areas. The areas are divided into different climatic zones and the hybrid system economy is analyzed for each climatic zone on the basis of NPC (net present cost), consumption of diesel and renewable fraction for all climate zones. The analysis indicates that the interior climatic zone – the area would be the optimum climatic zone to install HPS PV/diesel. The sensitivity analysis proves that the NPC of such a system can be reduced. It is suggested that due to high initial cost, government subsidy is necessary to adopt the system on a large scale. Such a profit will encourage development of renewable energy utilization and bring about rapid development of these remote areas.
•An Eco-friendly electro-organic synthetic method for 2-(4,5-diphenyl-1H-imidazol-2-yl)phenol (DIP) using two electrode system.•DIP was synthesized in aqueous medium with good economical yield and ...showed excellent capacitance behaviour.•DIP as a monomer itself exhibited pseudocapacitive behaviour.•DIP showed 93.7% specific capacitance retention in the supercapacitor measurement.
An efficient cost-effective and eco-friendly electro-organic synthesis of 2-(4,5-diphenyl-1H-imidazol-2-yl)phenol (DIP) in aqueous medium and its application as an electrode material for supercapacitor are reported here. The as-synthesized derivative was characterized by various spectral and analytical techniques. The optical and physical properties were analyzed by PL studies and by XRD, SEM, BET, TG- DTA and DSC techniques. The electrochemical studies of the electroactive material, DIP were carried out using Cyclic Voltammetry (CV), Galvanostatic Charge – Discharge analysis (GCD) and Electrochemical Impedence Spectroscopy (EIS). DFT calculation of DIP was also performed to evaluate the bandgap energy theoretically. DIP as a monomer exhibited a good capacitive behavior with a specific capacitance of 325F/g at the scan rate of 5mV/s. The results revealed that DIP can be potentially used as a promising electrode material for high performance supercapacitor applications.
Enabling Strategic Decision-Making in Organizations through Dataplexbreaks down the role of data in strategic decision making, examining the organizational benefits but also utilising real-world ...examples of limitations and challenges and how these can be overcome.
Purpose
Metastatic spinal cord compression (MSCC) requires expeditious treatment. While there is no ambiguity in the literature about the urgency of care for patients with MSCC, the effect of timing ...of surgical intervention has not been investigated in detail. The objective of our study was to investigate whether or not the ‘timing of surgery’ is an important factor in survival and neurological outcome in patients with MSCC.
Methods
All patients with MSCC presenting to our unit from October 2005 to March 2010 were included in this study. Patients were divided into three groups—those who underwent surgery within 24 h (Group 1,
n
= 45), between 24 and 48 h (Group 2,
n
= 23) and after 48 h (Group 3,
n
= 53) from acute presentation of neurological symptoms. The outcome measures studied were neurological outcome (change in Frankel grade post-operatively), survival (survival rate and median survival in days), incidence of infection, length of stay and complications.
Results
Patients’ age, gender, revised Tokuhashi score, level of spinal metastasis and primary tumour type were not significantly different between the three groups. Greatest improvement in neurology was observed in Group 1, although not significantly when compared against Group 2 (24–48 h; (
p
= 0.09). When comparisons of neurological outcome were performed for all patients having surgery within 48 h (Groups 1 and 2) versus after 48 h (Group 3), the Frankel grade improvement was significant (
p
= 0.048) favouring surgery within 48 h of presentation. There was a negative correlation (−0.17) between the delay in surgery and the immediate neurological improvement, suggesting less improvement in those who had delayed surgery. There was no difference in length of hospital stay, incidence of infection, post-operative complications or survival between the groups.
Conclusions
Our results show that surgery should be performed sooner rather than later. Furthermore, earlier surgical treatment within 48 h in patients with MSCC resulted in significantly better neurological outcome. However, the timing of surgery did not influence length of hospital stay, complication rate or patient survival.
The current study deals with the mechanical and morphological properties of sisal/bagasse fibers reinforced epoxy composites. The composites were developed by the hand layup process in four different ...proportions of sisal/bagasse fibers. The produced composites were characterized for its mechanical characteristics, namely, tensile, flexural, impact, Shore D hardness compression tests, water absorption and biodegradation tests as per ASTM. Morphologies were studied using Scanning Electron Microscopy. It was inferred that composites with three layers of sisal fibers and a core layer of sisal fibers produced good properties.
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