654 research outputs found
Sort by
To Study The Effect of Electrode Rotational Speed and Machining Parameters On MRR and SR Using EDM
No full textIn this work an attempt has been made to compare the effect of rotating copper electrode for machining of
HCHCr D2 steel at different sets of rotation i.e. 60,100 and 200 rpm. e intent of the present study is to observe the effects of input parameters such as peak current, on time, duty cycle, rotational speed of electrode on the material removal rate (MRR) and
surface roughness (SR). It is observed that material removal rate of Cu electrode at lower RPM is higher at lower value of duty cycle and depends directly on values of current. e electrode wear rate is lower at higher RPM and increase with increase in current. Surface roughness holds a higher value at increased rotational speed and at greater values of duty cycle but lower at reduced duty cycle. e result shows that at higher speed of rotating electrode the MRR decrease whereas the surface roughness increases, at different levels of peak current and duty cycle. Percentage contribution of parameters like current, duty cycle and on time is calculated, on each set of RPM, through ANOVA and it's
found that current has the greatest effect on MRR followed by duty cycle and on time
Towards biological plausibility of electronic noses: A spiking neural network based approach for tea odour classification
No full textThe paper presents a novel encoding scheme for neuronal code generation for odour recognition using an electronic nose (EN). This scheme is based on channel encoding using multiple Gaussian receptive fields superimposed over the temporal EN responses. The encoded data is further applied to a spiking neural network (SNN) for pattern classification. Two forms of SNN, a back-propagation based SpikeProp and a dynamic evolving SNN are used to learn the encoded responses. The effects of information encoding on the performance of SNNs have been investigated. Statistical tests have been performed to determine the contribution of the SNN and the encoding scheme to overall odour discrimination. The approach has been implemented in odour classification of orthodox black tea (Kangra-Himachal Pradesh Region) thereby demonstrating a biomimetic approach for EN data analysis
Facial Synthesis of Nano Sized ZnO by Hydrothermal Method
No full textIn this contribution we are presenting a simple precipitation hydrothermal method to synthesize zinc
oxide (ZnO) nanoparticles using zinc nitrate and starch solution. The obtained precipitated compound was calcined and structurally characterized by Powder X-ray diffraction (XRD), Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and UV-Vis spectroscopic techniques. The powder X-ray data indicates that the calcined compound exhibits hexagonal (Wurtzite) structure with space group of P63mc (No. 186). Scanning electron micrographs show uniform spherical like morphology of ZnO. The SEM results reveal that the particle sizes were in the order of 30–50 nm and the average particle size is around 35 nm. The FT-IR result shows the existence of OH-, NO2-,CO, CO2 groups in unclaimed sample. The band gap was higher for synthesized ZnO particles than their bulk counterparts. The results indicate that starch is an attractive material that can be used as precipitation agent for preparing ZnO
Recent advancements in sensing techniques based on functional materials for organophosphate pesticides
No full textThe use of organophosphate pesticides (OPs) for pest control in agriculture has caused serious environmental problems throughout the world. OPs are highly toxic with the potential to cause neurological disorders in humans. As the application of OPs has greatly increased in various agriculture activities, it has become imperative to accurately monitor their concentration levels for the protection of ecological systems and food supplies. Although there are many conventional methods available for the detection of OPs, the development of portable sensors is necessary to facilitate routine analysis with more convenience. Some of these potent alternative techniques based on functional materials include fluorescence nanomaterials based sensors, molecular imprinted (MIP) sensors, electrochemical sensors, and biosensors. This review explores the basic features of these sensing approaches through evaluation of their performance. The discussion is extended further to describe the challenges and opportunities for these unique sensing techniques
An Artificial Neural Network Prediction Model for the Measurement of Effect of Temperature and Time on Germination of Seed
No full textThe climatologically phenomena like
temperature ,humidity ,light etc have a direct or indirect effect on the germination of seeds and seedling growth .Temperature greatly influences the germination rate of the seeds . In this paper we show connection between the temperature and seedling growth by performing image analysis and image processing on the gram seed images .The images were recorded by a high quality camera at various constant temperatures and particular time intervals. And the data collected from image processing is further used to develop an Artificial Neural Network (ANN) predictive model for the measurement of sprout length and germination rate at random temperatures
Influence of a PbS layer on the optical and electronic properties of ZnO@PbS core–shell nanorod thin films
No full textIn the present study, ZnO@PbS core–shell thin film based solar cells have been fabricated by the successive ionic layer absorption and reaction method (SILAR). The assembly consists of zinc oxide (ZnO) nanorods as the core and PbS as the shell, and the thickness of the PbS layer was controlled by varying the number of dipping cycles. The varied PbS layer thicknesses resulted in the shifting of the absorption of ZnO@PbS from the ultraviolet region to the visible region. The PbS layer suppressed the visible emission of ZnO and enhanced the charge separation at the interface. By introducing PbS layers, the charge generation and separation within the ZnO@PbS core–shell nanorod has been improved. The PbS shell on ZnO nanorods improved the short-circuit current (Jsc), open circuit voltage (Voc) and fill factor (FF) that resulted in an enhancement of the photovoltaic device efficiency. A maximum power conversion efficiency of 6.59% was achieved with ten layers of PbS in the ZnO@PbS@dye thin film based solar cell
Effect of multi-path fading model on T-ANT clustering protocol for WSN
No full textRouting the data efficiently in wireless sensor network (WSN) is the current area of research. Recently, many hybrid routing protocols have been proposed for WSNs. The key interest is on improving energy efficiency, network lifetime, deployment strategy, fault tolerance and latency. T-ANT clustering protocol is an efficient, scalable and robust data routing strategy. This protocol uses both hierarchical structure and biological inspiration. In this paper we investigate the effect of multi-path fading model on T-ANT clustering protocol and provide comparative study of results with the T-ANT protocol in isotropic model in a simulated environment on MATLAB platform. In particular, we are interested to investigate the effect of multi-path fading model on clustering fitness, cluster head election fitness and work load distribution among sensor nodes. The results show that T-ANT protocol in multi-path fading model performs little lower than the T-ANT protocol in isotropic model without affecting the clustering fitness properties
A Machine Vision System for Tool Positioning and Its Verification
No full textThis paper presents a machine vision–based precise tool positioning and verification system that may be used with milling and lathe machines, and so on. For many industrial applications, the accuracy required in machining operations is of the order of microns. The developed machine vision–based tool position verification process involves pixel calibration to compute and measure real-world minute dimensions. These measurements are based on two-dimensional spatial correlation of sequential images captured from the movement of the tool with a resolution of 250 µm. The captured sequential images are thresholded using a new bio-inspired technique named Negative Selection Algorithm, a model of Artificial Immune System. The developed system extracts the difference between the actual and target positions of the tool from the captured images through image processing and calculates the error. To compensate for the positional error, alignment commands are fed to the two-axis high precision motor. The maximum error observed was ±206 µm for 14.99999 mm movement
Modeling and Simulation Assessment of Solar Photovoltaic/Thermal Hybrid Liquid System Using TRNSYS
No full textThe PV/T hybrid system is a combined system consisting of PV panel behind which heat exchanger with fins are embedded. The PV/T system consists of PV panels with a battery bank, inverter etc., and the thermal system consists of a hot water storage tank, pump and differential thermostats. In the present work, the modeling and simulation of a Solar Photovoltaic/Thermal (PV/T) hybrid system is carried out for 5 kWp using TRNSYS for electrical energy and thermal energy for domestic hot water applications. The prominent parameters used for determining the electrical efficiency, thermal efficiency, overall thermal efficiency, electrical thermal efficiency and exergy efficiency are the solar radiation, voltage, current, ambient temperature, mass flow rate of water, area of the PV module etc. The simulated results of the Solar PV/T hybrid system are analyzed for the optimum water flow rate of 25 kg/hr. The electrical efficiency, thermal efficiency, overall thermal efficiency, equivalent thermal efficiency, exergy efficiency are found to be 10%, 34%, 60%, 35% and 13% respectively. The average tank temperature is found to be 50°C
Characterization and optoelectronics investigations of mixed donor ligand directed semiconductor ZnO nanoparticles
No full textThe optical properties of mixed donor ligand directed semiconductor ZnO nanoparticles are evaluated and imine linked receptor is used as capping agents. The ZnO nanoparticles are prepared using precipitation method. The ligand is synthesized using condensation reaction between 2-aminothiophenol and 2-thiophenecarboxaldehyde. The formation of ligand is confirmed with spectroscopic methods including NMR and mass spectroscopy. However, UV–Vis absorption, photoluminescence, X-ray diffraction, energy dispersive X-ray and FTIR spectroscopy techniques are used for characterization of the ligand coated ZnO nanoparticles. The capping with ligand resulted in the successful amendment of the surface of ZnO nanoparticles, as it particularly reduced the defects related visible emission known as green luminescence and hence resulted in improvement in the UV luminescence. The UV–Vis absorption spectra also showed blue shift in the UV region for the ligand based ZnO nanoparticles due to the effect of quantum confinement. The composite (ZnO-ligands) stability is confirmed theoretically with Density Functional Theory