Karpagam Academy of Higher Education
Recent publications
Under the influence of cosmic improvement, photovoltaic (PV) container power capability decreases. In this case study, several passive and active chilling exploratory studies are carried out on a PV container to determine their effects on the energetic and warm depiction of a PVT scheme. All experiments are carried out on a cosmic person who poses as an expert while working with a wide range (regular-condensed) of energy from the sun’s capability. The temperature of the PV container rises as heat is generated along its course, resulting in a lower power delivered. The heat produced during the operation can be eliminated by attaching phase change material (PCM) to the PV committee afterward, which can retain the PV heat for a long time to increase overall effectiveness. Fins may be secondhand inside the PCM canister to improve the heat transmission. In research, it is noticed that as directly as PCM is melted entirely, the heat ancestry rate of PCM reduces that repeated leads to development in PV hotness. An oily acid was preferred as the PCM with a development change hotness. For the time being the investigation, research inspected two various sporadic warm requirement approaches utilizing a water distribution loop in the PV/T-PCM arrangement to boost the overall solar energy exercise effectiveness, and particularized contrasting were accomplished. The results showed that using PCM in a solar-powered battery can essentially reduce the PV committee’s hotness vacillation and improve photoelectric efficacy. Using the warm regulation method’s low hotness backdrop, excess heat may be extracted from the PCM in the solar panel. It was decided that an acceptable thermal management policy might improve the overall energy exercise percentage of the PV/T-PCM plan; however, more effect on the commerce research of the system that regulates organization is still needed. The research is developed to analyze a combination of solar Photovoltaic power systems using the PCM performance is analyzed.
Highly activated perovskite materials are desired for magnetic applications. Herein, we report the facile synthesis of LaMnxCo(1−x)O3 (x = 0, 0.05 and 0.1) via a hydrothermal method and investigated their structure stability along with its magnetic features. The as-synthesized and doped samples are crystallized into rhombohedral with the R3¯c space group. The clear reconstruction in microstructure is visible from spherical to nanorods after the addition of Mn and this is due to the lattice destruction when Co is replaced by Mn. The magnetically favourable oxidation state of the cobaltite is confirmed by the X-ray photoelectron spectra. It has been shows the mixed (Mn4+/3+) valence state for the doped samples and can be influenced for oxygen defective perovskite formation. Therefore, sustainable ferromagnetic order at low temperature is observed due to the existence of Co³⁺ at high spin state along with Co²⁺ state. The isothermal magnetization curve at room temperature reveals the paramagnetic state of the materials. From this work it can be validated that a dopant controlled defective structure can effectively activate the perovskite oxides properties and be able to fabricate similar perovskite system by adopting this process for future magnetic devices applications.
Volatile organic compounds pose an acute threat to the environment and human life. Formaldehyde, a well-known volatile organic compound known for its numerous commercial applications, has put forth the requirement for tracking down trace amounts of its presence in order to ensure healthier living. This work emphasizes the novel use of a non-toxic deep eutectic solvent medium (choline chloride and urea) for aiding the solid-state synthesis of pure and La-doped barium titanate. The prepared chemiresistive ceramics were verified for their gas sensing abilities towards a number of volatile organics, among which formaldehyde (100 ppm) showed amplified response of 118 in La-doped BTO modified gold interdigitated electrode. It also produced a rapid response-recovery rate of 12 sec/18 sec witnessing the extreme performance of La-doped BTO ceramic material. Additionally, the chemiresistive sensor was stable to humidity and had extended-shelf life.
The efficiency of photovoltaic (PV) modules is not linear to environmental circumstances, resulting in nonlinear PV curves. The nonlinear PV curve has only one point when the power is at its highest. Perturbation and observation (P&O) technique has been extensively used for Maximum Power Point Tracking (MPPT). However, tracking MPP takes longer with the lower step size approach. In the steady state, oscillations are observed be have higher with increasing step size operating point. As a result, new approaches for tracking this MPP with improved quick dynamic reaction, energy generation effectiveness, performance, and stability have been developed. This proposed study work obtains an intellectual solution for maximum power point tracking using a dual adaptive neuro-fuzzy inference system (ANFIS) controllers. The suggested Dual ANFIS MPPT approach identifies the best operating point of a PV system that is developed using a ZETA DC-DC converter as the PV array's and load's interface. MATLAB Simulation findings also include ZETA converter-based PV system that compares the suggested tracking behaviour to dual ANFIS MPPT technique with perturbs and observes MPPT algorithm the approach under dynamic response.
  • Vinodh P. VijayanVinodh P. Vijayan
  • I. JuvannaI. Juvanna
  • V. V R. Maheshwara RaoV. V R. Maheshwara Rao
  • [...]
  • S. JayachitraS. Jayachitra
To significantly minimize the effort required to seek in new environments, it is critical to choose an effective search strategy. In mobile robotics, random search is the main search method due to the lower processing capabilities of mobile robots, which result in the detection of only local features. If you are looking for random-walking techniques that emulate social insects self-organized behaviour, then Levy’s struggle approach is very popular. Robot searches are often ineffective since the suggested methodology is very restricted. This article offers an enhanced random walking technique in which each robot’s stride size is adjusted to minimize the amount of repeated searches. To find out if the suggested approach was successful and whether it performed as an intelligent exploratory strategy, simulation tests and experiments with real robots were undertaken. The research found that the suggested approach was more successful over a wider area.
  • Arun Kumar M.Arun Kumar M.
  • Arvind ChakrapaniArvind Chakrapani
Electrocardiograms (ECG) are extensively used for the diagnosis of cardiac arrhythmias. This paper investigates the use of machine learning classification algorithms for ECG analysis and arrhythmia detection. This is a crucial component of a conventional electronic health system, and it frequently necessitates ECG signal reduction for long-term data storage and remote transmission. Signal processing methods must be used to extract the function of the morphological properties of the ECG signal changing with time, which is difficult to discern in the typical visual depiction of the ECG signal. In biomedical research, signal processing and data analysis are commonly employed methodologies. This work proposes the use of an ECG arrhythmia classification method based on Fast Fourier Transform (FFT) for feature extraction and an improved AlexNet classifier to distinguish the difference between four types of arrhythmia conditions that were collected from records. The Convolutional Neural Network (CNN) algorithm’s results are compared to those of other algorithms, and the simulation results prove that the proposed technique is more effective for various parameters. The final results of the proposed system show that its ability to find deviations is 20% better than that of traditional systems.
Recent development in strategies to overcome the environmental adversities are focused mainly on lowering the carbon footprints and to decrease the global temperature rise. Bioprocesses based on microalgae are promising due to a large spectrum of possible products, like platform chemicals, proteins and higher value products that can directly impart a fall in the carbon emission. Another promising approach towards sustainability is the integrated bio refinery cultivation of microalgae for waste water treatment with simultaneous production of fuels (alcohol and biodiesel), high value chemicals (Astaxanthin, Lutein, polyunsaturated fatty acids (PUFA), monounsaturated fatty acids (MUFA)etc.), proteins etc, but the technology readiness level are rather low and therefore are not established. However, for sustainable, economical and feasible bioprocess strategies using microalgae intra and extracellular bio-components extraction and cell wall disruption techniques should be optimized whereas challenges like high energy consumption involving these stages in the process makes it futile. The efficiency of cell disruption techniques and product extraction varies within different microalgae and depends mainly on the growth conditions and cell wall composition. The current review describes the cell wall structure and its composition of green freshwater microalgae such as Botryococccus braunii, Scenedesmus obliquus, Desmodesmus sp., Chlamydomonas reinhardtii, Chlorella vulgaris, Haematococcus pluvialis and marine forms like Dunaliella salina and Nannocholoropsis gaditana. Further, it highlights the green cell lysis technologies to disrupt cell walls and the future perspectives and challenges of algae in integrated wastewater treatment, CO2 capture, and energy-efficient algal cell wall disruption for utilizing microalgae for fuel production is discussed.
Among the different metal oxide nanoparticles, zinc oxide nanoparticles have gained significant importance due to their antibacterial properties against clinically pathogenic bacteria during the organal development. In the present study, biogenic zinc oxide nanoparticles were synthesized using seed extract of Citrus limon by a simple, cost-effective, and green chemistry approach. The synthesized ZnO NPs were characterized by UV-Vis spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, Dynamic Light Scattering, and Scanning Electron Microscopy. Next, the antimicrobial activity of ZnO NPs was tested against clinically pathogenic bacteria, i.e., Pseudomonas fluorescens, Escherichia coli, Enterobacter aerogenes, and Bacillus subtilis. Followed by, ZnO NPs were evaluated for the development of caudal fin in Zebrafish. The UV-Vis spectram result showed a band at 380 nm and FTIR results confirmed the ZnO NPs. The average crystallite size of the ZnO NPs was 52.65 ± 0.5 nm by the Debye Scherrer equation and SEM showed spherical-shaped particles. A zone of inhibition around ZnO NPs applied to P. fluorescensm indicates resistance to ZnO NPs followed by B. subtilis. Among the four different bacterial pathogens, E. aerogenes was the most susceptible compared to the other three pathogens. The calculated sub-lethal concentration of ZnO NPs at 96 h was 153.8 mg/L with a 95% confidence limit ranging from 70.62 to 214.18 mg/L, which was used with partially amputated zebrafish caudal fin growth. A significant (p < 0.5) development (95%) in the amputated caudal fin was detected at 12 days post-amputation. Low concentrated ZnO NPs can reduce developmental malformation. Collectively, suggested results strongly proved that lemon seed-mediated synthesized ZnO NPs had a good pathogenic barrier for bacterial infection during the external organal development for the first time.
The present work was done to optimize the process parameters of the oil extraction from the algae species spirogyra by using n-hexane as the solvent using the Soxhlet apparatus. The response surface methodology (RSM) and artificial neural network (ANN) were employed to optimize the particle size of the algae powder, dryness level of the algae powder, solid to solvent ratio, reaction time, and extraction temperature of the oil extraction process. Also, the physiochemical properties of the extracted oil were investigated. The comparative evaluation was done between the RSM and ANN models to select the more precise and accurate model. The coefficient of determination, R 2 of 98.92%, and the mean absolute percentage deviation (MAPD) of 0.492% for ANN revealed that the current model created with a network topology of 3 : 11 : 1 with tansig (hyperbolic tangent sigmoid) transfer function in the input layer and purelin (pure linear) transfer function in the output layer trained with trainlm (Levenberg–Marquardt) algorithm found to provide the optimal solution with better accuracy in prediction of the output. The physicochemical properties investigated, such as heating value, flashpoint, density, viscosity, iodine number, acid value, saponification value, and cetane index, showed that the extracted oil from the algae spirogyra species can be used as an alternative fuel.
Ethnopharmacological relevance: Pien-Tze-Huang (PZH)—a traditional Chinese medicine (TCM) compound—has been employed to treat various liver inflammation and tumors for over 10 decades. Interestingly, most of the pharmacological effects had been validated and explored toward liver ailment along with pro-inflammatory conditions and cancer at the cellular and molecular level to date. Aim of the study: The present study aimed to investigate the therapeutic effect of PZH on autophagy and TGF-β1 signaling pathways in rats with liver fibrosis and hepatic stellate cell line (HSC). Materials and methods: Male SD rats with carbon tetrachloride (CCl4)-induced liver fibrosis were used as the animal model. Next, PZH treatment was given for 8 weeks. Afterward, the therapeutic effects of PZH were analyzed through a hepatic tissue structure by hematoxylin-eosin (H&E), Van Gieson (VG) staining, and transmission electron microscopy (TEM), activity of ALT and AST by enzyme-associated immunosorbent assay as well. Subsequently, mRNA and protein expression were examined by quantitative polymerase chain reaction (qPCR), Western blotting, and immunohistochemistry (IHC). Then, the cell vitality of PZH-treated HSC and the expression of key molecules prevailing to autophagy were studied in vitro. Meanwhile, SM16 (a novel small molecular inhibitor which inhibits TGFβ-induced Smad2 phosphorylation) was employed to confirm PZH’s effects on the proliferation and autophagy of HSC. Results: PZH pharmacologically exerted anti-hepatic fibrosis effects as demonstrated by protecting hepatocytes and improving hepatic function. The results revealed the reduced production of extracellular collagen by adjusting the balance of matrix metalloproteinase (MMP) 2, MMP9, and tissue inhibitor of matrix metalloproteinase 1 (TIMP1) in PZH-treated CCl4-induced liver fibrosis. Interestingly, PZH inhibited the activation of HSC by down-regulating TGF-β1 and phosphorylating Smad2. Furthermore, PZH down-regulated yeast Atg6 (Beclin-1) and microtubule-associated protein light chain 3 (LC3) toward suppressing HSC autophagy, and PZH exhibited similar effects to that of SM16. Conclusion: To conclude, PZH alleviated CCl4-induced liver fibrosis to reduce the production of extracellular collagen and inhibiting the activation of HSC. In addition, their pharmacological mechanisms related to autophagy and TGF-β1/Smad2 signaling pathways were revealed for the first time.
To study the static software defect detection system, based on the traditional static software defect detection system design, a new static software defect detection system design based on big data technology is proposed. The proposed method can optimize the distribution of test resources and improve the quality of software products by predicting the potential defect program modules and design the software and hardware of the static software defect detection system of big data technology. It is found that the traditional static software defect detection system design based on code source data takes a long time, averaging 65 h /day. However, the traditional static software defect detection system based on deep learning has a short detection time, averaging 35 h/day. In this article, the detection time of the static software defect detection system based on big data is shorter than that of the other two traditional system designs, with an average of 15 h/day. Because the system design adjusts the operating state of the system, it improves the accuracy of data operation. On the premise of data collection, the system inspection research is completed, which ensures the operational safety of software data, alleviates the contradiction between system and data to a high degree, improves the efficiency of system operation, reduces unnecessary operations, further shortens the time required for inspection, improves the system performance, and has higher research and operation value.
Zinc oxide, a well-known inorganic metal oxide in nanoparticle form, has outstanding antibacterial properties. In this work, the authors focus on determining ZnO nanoparticles’ structural, optical, and antibacterial activity. A simple soft chemical route synthesizes C-ZnO nanoparticles chemically, while the green synthesis method is used to prepare G-ZnO nanoparticles. Ocimum tenuiflorum leaf extract was used to prepare G-ZnO nanopowders. These samples are investigated and compared in terms of their structural, morphological, optical, and antibacterial properties. According to XRD investigations, the synthesized ZnO nanopowders possess a hexagonal structure. The particle size of G-ZnO is smaller than that of C-ZnO nanoparticles. The XPS result revealed the binding and interactions between molecules. The FTIR study confirmed the presence of molecules and their vibrations. UV-vis-DRS spectroscopy was used to investigate optical properties such as reflectance and band gap. The grain size of the G-ZnO nanopowders was decreased, and oxygen vacancy was produced. The antibacterial efficiency of plant extracts against two different bacterial strains, S. aureus (Gram-positive) and E.coli (Gram-negative), has been studied and reported.
This study used a simplified, automated spray pyrolysis setup with a perfume atomizer to prepare nitrogen (N) doped ZnO thin films. The deposited thin films were annealed at 300 ºC to 500 ºC under a nitrogen atmosphere. In the present work, detailed investigations are carried out on the effect of annealing on structural, optical, and surface morphological, photoluminescence, and electrical properties of p-type ZnO: N thin films. The effect of annealing temperature on the photocatalytic activity of N-doped ZnO thin films was studied, the degradation efficacy was and 91%. The XRD diffractograms depicted that all the prepared films have a wurtzite structure, high crystallinity, and C-axis orientation. The increased annealing temperature received a red shift in the band gap. A flake-like morphology was observed from SEM images. The p-type to n-type conductivity transformation is kept at the maximum applied annealing temperature of 500 ºC. A resistivity received ∼ 21.7 Ω cm was obtained for 400 ºC annealing temperature. Photocatalytic studies confirmed that higher degradation efficiency was exhibited for higher annealing temperatures. The present investigations reveal that the properties of p-ZnO: N thin films are highly suitable for optoelectronic applications.
e primary heat source from the sunlight is solar energy, which is used in photovoltaic panels, solar power plates, photovoltaic streetlights, and solar-based hybrid nanocomposites. A hybrid nano uid is traversing an expanding sheet in this investigation. Maxwell uid stream with two nanoparticles is going towards a trough with a parabolic form and is situated within the solar aircraft wing to investigate the phenomena of heat transfer rate. e term solar thermal radiation was introduced to describe heat transfer occurrence. e e ectiveness of heat transmission from airplane wings is assessed by taking into account unique phenomena such as magnetic eld and heat source. e bvp4c procedure was applied to quantitatively explain the energy and motion equations with MATLAB software. e copper (Cu) and graphene oxide (GO) nanosolid particles are mixed with sodium alginate (SA), a common liquid, to form the nanosolid particles. Numerous control variables are thoroughly examined, including temperature, shear stress, motion, friction component, and Nusselt number. e skin-friction coe cient upsurges with a growing magnetic impression. e upsurge in Deborah number reduces the skin-friction coe cient. e heat source impression declines the heat transport rate but upsurges the skin-friction coe cient. e skin-friction coe cient and heat transport rate increase with growing magnetic impression. When it comes to heat transfer analysis, hybrid nano uid e ciency is substantially superior to that of regular nano uid.
A hybrid material, Zeolitic imidazolate frameworks (ZIFs) characterize a kind of new and specialized sort of metal–organic frameworks (MOFs) with imidazole linkers and metal ions with standard aluminosilicate zeolite structure. Their intrinsic pore size, robust functions and high-quality thermal and chemical stability have ended in a huge range of capabilities for diverse ZIF substances. In this promptly increasing area, over the past few years, energetic research activities have emerged from package approaches to potential applications. Herein, a simple method for the preparation of Zeolitic imidazolate framework-8 (ZIF-8) nanocrystals (NCs) has been synthesized by a simple one-step chemical method with starting material such as 2-methylimidazole and Zinc nitrate hexahydrate in methanol solution. Structural, functional, surface morphological and electrochemical performances have been systematically investigated by various analytical techniques. Electrochemical test results show its specific capacitance up to 111.23 F g−1 at current density of 1 A g−1 in a 3 M KOH electrolyte. In particular, the compound exhibits good cyclic stability with 85.36% capacity retention after 5000 cycles at a given current density of 3 A g−1.
The number of cloud users and their respective workload increases everyday with the inherent benefits of cloud computing. On the other hand, it becomes critical for service providers to maintain Quality of Service (QoS) even under heavy workload conditions. In order to provide better computing services, cloud utilizes Virtual Machine (VM) migration techniques, which eases the process of providing the services to the user without any delay and with minimum energy consumption. The existing cloud computing services mainly rely on migration techniques; nevertheless, handling large VM migrations consumes more energy, which directly affects the VM performances. This necessitates the need to develop an effective VM migration strategy to perform the necessary migrations and avoid unnecessary migrations. Conventional migration techniques perform migration based on static parameters which attains less efficient results and lags in performance while handling the resource utilization. In this research work, a hybrid optimization algorithm is presented to handle VM migration in a cloud environment. Cuckoo search optimization algorithm and particle swarm optimization algorithm are combined to obtain the proposed hybrid optimization model. The major objective of this research work is to reduce energy consumption, computation time, and migration cost. Maximizing resource utilization is another objective of this research work. To validate the research objective, the performance of hybrid optimization model is verified through simulation analysis and compared with conventional algorithms like firefly optimization, whale optimization, hybrid whale optimization, and hybrid bee colony optimization in terms of energy consumption, migration cost, resource availability, and computation time.
Objectives The present investigation was aimed to analyze the antidepressant activity of methanol extract of Bacopa monnieri using albino rats. Methods Three doses of methanol extract (25, 50 and 100 mg/kg), and standard (imipramine hydrochloride, 25 mg/kg) were administered to albino rats. Methanol extract was subjected to use forced swimming test, tail suspension test and locomotor activities. Results At 25 mg/kg, 50 mg/kg and 100 mg/kg doses, immobility time decreased at 49.6%, 59.5% and 69.9%, respectively than control (p value <0.0001). Tail suspension test increased immobility time at higher doses of methanol extract. Locomotor activities were statistically significant at 25 mg/kg and 50 mg/kg (p value = 0.005), and non significant at 100 mg/kg (p value= 0.781) in experimental animal. The experimental animals treated with plant extract showed varying levels of monoamine oxidase - A (MAO-A) activity. MAO - A level of the control animal was 2.87 ± 0.021 ng/mL and it reduced in the experimental albino rats treated with imipramine hydrochloride (2.73 ± 0.09 ng/mL). The amount of MAO-A in the experimental animals treated with methanol extract at 25 mg/kg (p=0.01), and 50 mg/kg (p value = 0.0001) showed significant decrease in MAO-A activity in rats brain than control. Conclusions The present finding revealed antidepressant effect of methanol extract of B. monnieri in Albino rats.
Vibrio is heterotrophic ubiquitous marine bacteria that plays dual role as putative halobiont and potential pathogen. Environment and diseases are inextricable hence the role of vibrio as a potential pathogen in the natural environment must be comprehended. Hence the present study aims at investigating the pathogenicity of Vibrio owensii on the post larvae of Litopenaeus vannamei. V. owensii isolated from the marine natural habitat of the Palk Bay province in India was highly resistant to ampicillin, methicillin, tetracycline and vancomycin. The strain also lacked pathogenicity against the post larvae of L. vannamei due to the absence of major virulence factors viz. Chitinase, phospholipase and hemolytic activity. Presumably this is the first report on the occurrence of V. owensii in the Indian waters therefore there arises a need to carry out more serious research on the pathogenicity of this species on other commercial crustaceans reared in the Indian aquaculture settings in order to apprehend its role as potential pathogen or the contrary.
A significant handful of hollow ultra-high-performance fiber-reinforced (UHPFR) concrete beams have been tested for torsional strength. Various cross sections, wall thicknesses, and cross-section forms of UHPFRC hollow beams were tested in this study. An investigation of these materials is carried out to determine their failure mechanisms and their torque-twist and torque–strain curves. In addition, they are analyzed as well. The cracking and ultimate torques were calculated utilizing theoretical methodologies. Either with or without flange plates, significant fractures entering spirally in UHPFRC hollow beams led to the same failure. Despite the fact that cross-sectional dimensions had an impact on the ultimate torque, wall thickness and cross-sectional type had little influence on cracking torque. The cracking torque was well predicted by the American Concrete Institute code requirements, but the maximum torque was poorly predicted by the existing theoretical methodologies, according to an examination of actual and theoretical data. For hollow beams made of UHPFRC, the wall thickness should be estimated more precisely.
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316 members
Palaniswamy Muthusamy
  • Department of Microbiology
Vellingiri Senthil Kumar
  • Department of Physics
Marimuthu .S
  • Mechanical Engineering
Esakki Muthu
  • Department of Physics, faculty of arts and science
Coimbatore, India