Showing papers by "Jawaharlal Nehru Technological University, Hyderabad published in 2022"

Design and performance analysis of a low-pull-in-voltage RF MEMS shunt switch for millimeter-wave therapy, IoT, and 5G applications

Abstract: Recent advancements in wireless communication systems utilize miniaturized devices based on microelectromechanical system technology for present and future 5G wireless applications. Nowadays, RF devices are utilizing frequencies up to 30 GHz with substantial signal propagation that leads to a slow data rate. On the other hand, there is a huge spectrum available in the millimeter-wave frequency range of 30–300 GHz. The millimeter-wave spectrum is attractive for the development of smart systems based on 5G technology. In this paper, a low-pull-in-voltage capacitive type RF MEMS switch is proposed to operate at frequencies above 30 GHz. The switch is proposed with a new iterative meandering technique where the span length of each section in the meanders differs relative to the first section. A low pull-in voltage of 1.8 V is achieved with a large capacitance ratio of 63. The switch exhibits low insertion loss of −0.24 dB at 41 GHz and possesses high isolation of −46.7 dB at 38 GHz. The design is validated by comparing the theoretical and simulated results, and the switch can be efficiently utilized for millimeter-wave applications.

A cogeneration cycle comparative analysis with parallel arrangement

Abstract: Refrigeration and power are the most desirable requirements in commercial places and offices. Goswami cycle is one of the solutions to generate power and refrigeration simultaneously with less pollution. In the Goswami cycle, the power and refrigeration streams are connected in series, the refrigeration output is limited in a series arrangement. In the present study, parallel streams are proposed to improve the performance of the cycle. In the Goswami cycle, the saturated vapour is enriched for power and refrigeration. In the present study, the saturated vapour is used for the power generation, the saturated liquid is flashed to the intermediate pressure, and the generated wet vapours are enriched for refrigeration processes. It is observed that power generation is increasing with an increase in dryness fraction and the fall in basic solution concentration, whereas the refrigeration effect is growing with the fall in dryness fraction and increase in basic solution concentration. The modified cycle is consistently generating higher output than the conventional cycle. The thermal efficiency of the Kalina flash cycle is 29.05% higher and the exergy efficiency is 5.61% lesser than the Goswami cycle.

Utility of Geomatics in Land Use Land Cover Change Detection and Accuracy Analysis

Abstract: Unprecedented growth and rapid urbanization resulted in remarkable changes in the land use and land cover patterns which altered the global environmental scenario and also affected ecosystem services. Continuous monitoring of land use and land cover changes is extremely important to systematically plan various infrastructure projects and their land requirements to meet demands from various sectors, especially in an urban context. Timely and reliable information on the spatial and temporal behavior of land use land cover patterns is, therefore, a prerequisite and realizing the potential of geospatial technologies in providing such information, a study has been taken up in the Hussain Sagar catchment area, a part of Hyderabad City. The present study includes land use land cover (LULC) classification of various satellite images taken at different periods for comparison and checking for their accuracy assessment. The results indicated a spectacular increase in settlements/built-up land to the tune of 50.34 km2 accounting for 48.38% of the proposed study area. Contrastingly, a significant shrinkage in the areal extent of vegetation, barren land, and water bodies has been noticed over the past one and half decades. It is noted from various sources and findings that the Kappa value greater than 0.75, is rated to be considerable. The results obtained from the present study indicated an overall classification accuracy of 87.33% with kappa value (K) = 0.84 which are found to be satisfactory and therefore the classified images can be used for further analysis.

Stimulus techniques and microelectrode recordings of subthalamic-nuclei neurons in Parkinson`s during functional-neurosurgery

Abstract: This study discusses the various procedures and issues involved in the acquisition of microelectrode recordings (MER) signals of subthalamic nucleus stimulations with induced deep brain stimulation electrodes very rigorously. Bellicose-invasive physiological detections through the methods of sub cortical physio logical detections, electrical induced stimulations and micro electrode recordings, stereo-tactic technique, macro-stimulation, stereo-tactic functional neurosurgical technique, stimulations such as macro and micro, induced stimuli with current and microelectrode recordings, impedance information monitoring, micro injections of test substances, evoked potentials, biomarkers/local field potentials, microelectrode fabrication methods and setups, sub cortical atlas-mapping with micro recording/microelectrode recording (M.E.R.). Thus, the study is very significant to the electrophysiological neurosurgical point of view and is very useful to the field of microelectrode recording and functional neurosurgery. This study is concerned with invasive physiological detection of deep brain structures with micro- or macro-electrodes prior to surgery followed by imaging techniques and their use in cortical and subcortical detection; detection relevant to the superficial cerebral cortex regions.

A Novel Approach to Detect Anomalies in Business Process Event Logs Using Deep Learning Algorithm

Abstract: Enterprises whose businesses are driven by web-based or cloud-based applications contain thousands of business processes involved. Due to the dynamic runtime environments and distributed nature of business processes and dependencies, there is possibility of noise and anomalies. Moreover, naturally, businesses are interested in finding anomalies in business processes and rectify them for improving quality of service (QoS). Especially, as part of process mining, anomaly detection has become an important research area in the contemporary era. Many anomaly detection methods came into existence based on machine learning techniques. There are attempts made using autoencoders for business process anomaly detection. However, from the literature, it is understood that there is need for a deep learning-based autoencoder with unsupervised learning approach for efficient detection of anomalies by analysing business process event logs. Towards this end, in this paper, we proposed a methodology and defined an algorithm known as deep learning encoder-based anomaly detection (DLE-AD) for enhancing the ability of anomaly detection. From the experiments, it is revealed that deep learning-based anomaly detection showed better performance over the traditional approaches. The proposed algorithm is evaluated against state of the art and found that it outperforms the existing methods.

Design and Implementation of a Self-charging System to Improve the Operating Range in Quad-Motor EV

Abstract: The current technological improvements are playing an important role in transportation industry and making it more advanced at each and every segments. At present the transportation industry is developing rapidly and its growth is increasing every year. Government is focusing on the environment friendly vehicle. For that electric vehicle (EV) is a game changer. For the past few decades electric vehicles and hybrid vehicles are improving rapidly in a vast manner. But also it carries some drawbacks as well. The drawbacks of electric vehicles are improving and changing day by day. There are many factors affecting the performance of the electric vehicles like battery efficiency, charging methods, and price. In our chapter we have developed a self-charging system for improving range of all-wheel drive electric vehicle by applying a method by which the vehicle get charged by itself when it’s in motion.

Significance of quadratic thermal radiation on the bioconvective flow of Ree-Eyring fluid through an inclined plate with viscous dissipation and chemical reaction: Non-Fourier heat flux model

Abstract: Ree-Eyring model is a pseudoplastic model, which portrays the shear diminishing fluid flows. In this paper, the significance of quadratic thermal radiation on the dissipative bioconvective flow of Ree-Eyring nanofluid by an inclined plate with a chemical reaction is investigated. The non-Fourier heat flux model is included in the energy equation. A combination of shooting and Runge–Kutta 4th order procedure is used to get the preferred outcomes. Features of fluid flow, including heat transfer rate, are discussed using the correlation coefficient. The escalation in the Brownian motion parameter leads to the decrement in the fluid concentration. Thermophoresis parameter ameliorates the fluid temperature, and the concentration of microorganisms minimises with larger Schmidt and Peclet numbers. The heat transfer rate consumes a generous, positive affiliation with the thermal relaxation parameter, and the increment in the rate of heat transfer is 0.00954. The skin friction coefficient decreases with the increase in magnetic field parameter, and the decrement in skin friction coefficient is −0.74692. Mass transfer rate increases with the increase in chemical reaction parameter, and the increment in mass transfer rate is 0.14542. Furthermore, the outcomes of this study are compared with earlier results.

Waste Management Data Analytics and Solution for Domestic Waste Management to Improve Soil Quality

Abstract: Solid waste management is crucial in India. In metropolitan India, nearly, 377 million population produces 62 million tons of municipal solid waste per annum, 70% is collected, 20% is treated, and 50% is neglected. With the current rate of increase in population, it will be incremental till 2025. Domestic house waste per person is also important parameter in metro cities. Exposed garbage every day results in contaminated land. Here, objective is to suggest an approach to develop an IoT-enabled waste management system to improve soil quality for agricultural activities and minimize human intervention helps to reduce human time and effort. Approach helps in control pollution and diseases caused due to environmental pollution. Here, we have performed data analytics using Weka tool and Microsoft Excel. We have used monthly-recycling-and-waste-collection-statistics data set for performing analytics and noticed contribution of curb waste maximum compare to other types of waste. There is a demand to provide technology for waste management.

Testing of Neighborhood Pattern-Sensitive Faults for Memory

Abstract: The important fundamental integrated circuits (ICs) in system ICs and electronic systems are semiconductor memories. With the increase in technology, the density, capacity of memory chips and cores increase rapidly. Due to this, the testing becomes a difficult issue. This results in an high testing cost. The invention of a deep-submicron form of technology improves the memory density to greater level that nobody could imagine. The greater number of faults and failure modes should be checked in order to maintain reliability and high quality of products in memories. By the growing density, due to the increase in coupling effect, the pattern-sensitive fault (PSF) becomes most important fault model to test in memories. The fault model occurs in random access memory (RAM). Neighborhood pattern-sensitive fault (NPSF) involves three or more number of cells in the memory. Those faults are identified as high quality and important fault models in the memory arrays. The methodology which exists now for NPSF fault detection is not suitable due to deficient in complete fault detection, and it takes longer test time. So, to improve the fault detection, a test method is developed which involves testing of 8 * 8 memory completely. With the help of the input series, the fault can be detected. The sequences which are used are Hamiltonian, binary and gray sequences.

Influence of Nano Filler (ZrO₂) on Optical and Thermal Studies of Potassium Doped Polyethylene Oxide Solid Polymer Electrolytes

Abstract: Solid polymer electrolyte films made with potassium doped Polyethylene oxide using ZrO 2 as nanofiller (70PEO-30KBF 4 -x ZrO 2 where x = 1, 2.5, 5, 7.5, & 10 wt% ­­ ) were prepared by solution casting technique. Optical and thermal properties of polymer electrolyte films were studied by using Optical absorption and DSC techniques. From Optical absorption spectra, it is observed that fundamental absorption edge is shifted towards the higher wavelength side (range 259- 297 nm) with increase of nano filler (ZrO­ 2 ) concentration (1-10 wt %). Optical band gap for all electronic transitions (p=1/2, 2, 2/3 and 1/3) are found to be increased as incorporation of nano filler (ZrO 2 ) which confirms the structural rearrangements takes place in polymer electrolyte films. Optical band gap for indirect allowed transitions (p=1/2) are found to be in the range of 1.93-3.34eV. Decrease in Urbach energy (4.8eV- 1.4eV) is associated with decrease in defect formation in host polymeric matrix (PEO-KBF 4 ) as a result of embedded nano filler (ZrO 2 ). DSC spectra analysis of polymer electrolytes has showed melting temperatures in the range 63.63-73.71°C and highest crystallinity is found to be 85 % (10 wt % ZrO­ 2 ). Enthalpy values are elevated with increase in nanofiller composition (ZrO 2 ) in the present polymer electrolyte films.Keywords: PEO based polymer electrolytes, Solid polymer electrolytes, Optical and Thermal studies.

Improvement of Soft Clays Using Stone Columns with and Without Encasement

Abstract: Engineering structures constructed on thick deposits of soft clay have problems of low bearing capacity, excessive total and differential settlement etc. To mitigate such problems, stone column technique seems to be a very suitable and favorable ground improvement technique for deep soft soil improvement. Further to prevent excessive bulging and squeezing of stone into soft soil, stone column can be encased with suitable geo-synthetics. Another advantage of encasement is having high load-carrying capacity and lesser settlement of composite foundation. This paper presents an experimental study of single granular piles with and without encasement in improving the bearing capacity and reducing the settlements. The main objectives are (a) to identify key considerations for the general use of encased stone columns and columns without encasement and (b) provide insights for design and construction. Laboratory experiments have been carried out with granular piles of size 6 cm. In laboratory setup, hydraulic pressure was used to apply the load to the soil granular pile system and the dial gauges were used to measure the settlements. To obtain the stiffness of the pile, a test was carried on piles with and without encasement, by loading only the pile material neglecting the confining effect of the surrounding soil as the soil is soft in nature. Study of the bearing capacity ratio, defined as ratio of the bearing capacity of treated soil with granular pile to the bearing capacity of untreated soil for a given settlement for the foundation, was conducted. Granular piles are made of stone and sand, and encasement of piles with leno-netted material. To cast the piles, casing pipes of the required diameter 6 cm were used.

Design of Fault Tolerant Single RAM-Based Parallel Real Fast Fourier Transform Architectures Using Error Correction Codes and Parseval Checks

Abstract: With the increase in demand for various features in electronic devices, development of these devices with less area and low power has become a prominant research area. This can be achieved by technology scaling, which makes the design simple and efficient at the cost of vulnerable to some faults. Soft errors are one such faults whose occurrence may disturb the operation of the device for an event, which may degrade the device reliability. Therefore, in most of the systems, preferably, there is a need for protection of vital elements. In many systems, the operation of several similar modules is observed, to process parallel data at a time. The Fast Fourier Transform (FFT) processor is one such thing in various diversified fields such as Digital communications, Bio-medical applications, Signal processing systems, etc. The Real Fast Fourier Transform (RFFT) is a type of memory-based FFT architecture. It can be optimized by its memory usage and processing element optimization. The single RAM-based RFFT architecture is of that kind. In this paper, the fault tolerant single RAM-based parallel RFFTs is proposed using a protection scheme that rely on conventional Error correction codes (ECC) and Parseval checks. This proposed architecure is implemented on virtex-6 and 7 devices using Xilinx ISE 14.2v tool. The results show that the proposed architecture performs better in terms of area and delay as compared to the existing ones.

Slope–Reinforcement Interactions: Effect of Strength Parameters

Abstract: Steepening of slopes for construction of rail/road embankments or for widening of other civil engineering structures is a necessity for development. Use of geosynthetics for steep slope construction or repair of failed slopes considering all aspects of design and environment could be a viable alternative to these problems. Designing geosynthetic reinforced slope with minimum length of geosynthetics leads to economy. 1.5H:1 V slope reinforced with a single layer has been analysed for three different sets of soil parameters and for three depths from the top of the embankment. Reinforcement length has been optimized from face and non-face ends of the slope. The paper presents the effect of soil parameters, angle of shearing resistance and cohesion on optimized length of reinforcement and saving in length of reinforcement.

Computational Fluid Dynamics (CFD) Modelling and Design for Computing the Internal Hydrodynamic Behaviour of Final Clarifier

Abstract: To obtain effluent low in suspended solids is critical for operation of the final clarifier tank in waste water treatment facilities. Flocculants solids tend to form sludge at the bottom of the tank and at peak flow rates; this sludge may fill the entire tank and overflow the weirs. Inadequate design of the tank may cause the suspended solids to be discharged into the effluent weir. CFD model was used to analyse the flow of a laboratory-based clarifier tank. This CFD model was further extended to analyse flow features in a full-scale clarifier tank. Design modification to the clarifier tank was analysed to optimise its performance in terms of limiting the carryover of suspended solids to the effluent weir.

Comparative Analysis of Machine Learning Approaches of Prediction of Diabetes Consequences in Pregnancy with Implications of Data Matrices

Abstract: Aruna Kumari, A. Santosh Kumar, HengeDiabetic retinopathy is a key reason of blindness in the working-age people. When treatment is more difficult, gestational diabetes occurs during pregnancy for some women, and it means glucose levels are too high when some pregnant women. This is developed due to hormones released from the placenta. Try to avoid eating simple carbohydrates food, take more vegetables for good health and it controls the blood sugar levels. Gestational diabetes generally passes away after the childbirth. If you are unrefined, it causes difficulties to your child, in the stage of premature birth and stillbirth. The danger of early childbirth due to diabetes mellitus, gestational is larger if mom develops diabetes before the 24th week of pregnancy, the risk for developing diabetes later in life. Sometimes it converts type 2 diabetes also in later stage of life. A well person 102.5 and 169.5 for a diabetes mellitus person, insulin’s moderate by the goal is certainly dissimilar, A normal human for 107 as well as diabetic mellitus person for 140, plasma glucose concentration two hours in an oral glucose acceptance test, triceps skin fold thickness in mm a non-diabetic person for 27 and 32 for a diabetic person. Blood pressure for a fit person 70 and 74.5 for a diabetic person. A fine person for 30.1 and 34.3 for a diabetic mellitus person for body mass index weight in kg/height in m $$^2$$ , age in years, consider number of times pregnant, calculate diabetes pedigree function. Then after apply some complexity on algorithms to increase the accuracy use hyperparameters on light gbm then after apply the grid search and add the K-neighbour’s to light gbm with voting classifier we got accuracy of 94.1%, the result was also very close to the best result found and this shows the right hyperparameters light gbm and grid search can be good and practical classification on medical history.

Intelligence Speech Has Collapsed and Talking Unconsciously Circumstance Using Diva Module

Abstract: This research work is based on the human mental condition state at their is unconscious due to some disorder at that state the human does not know what he is speaking or his speech will be collapsed due to some disorders. There is such a disorder that doctors can also delay identifying what the actual disorder is due to damage of speech nerves the disorders like Aphasia, dopamine deficiency, Parkinson's disease, etc. There is a solution for such disorders identification without communicating with the patient. DIVA module and Denoising. The signal using the UNICA algorithm to analyse the perfect report of the patient. The Directions into Velocities of Articulators (DIVA) model is an adaptive neural network model for controlling the movement of the analogue vocal tract to produce phrases, syllables, or phonemes. The Electroence Phalogram signal obtained from the human brain is used as the DIVA model's input signal. However, the effect of power frequency interference and other noise sources has caused the input signal to be non-stationary and instantaneously contain several multi-form waveforms. The DIVA model is affected by such a signal as it is fed into it. As a result, this paper uses and improves an adaptive sparse decomposition model for feature extraction of the general EEG signal structure based on the principle of sparse decomposition. Matching Pursuit algorithm is used to compute the best atom using a decomposition model for feature extraction of the general EEG signal structure. After that, the original EEG signal can be represented by atoms from an entire atomic library.

Principal Component Analysis of Different Economic Traits in Layer Chicken

Abstract: Background: Principal component analysis is a multivariate technique that transforms a number of possibly correlated variables into smaller number of uncorrelated variables leads to dimension reduction. Various economic traits of layer chicken are used for selection of parent birds which need to adjust for selection strategies to augment the genetic improvement. Methods: The data was collected from 2020-2021 which includes weekly body weight (g) from 0 day to 20th week and 40th week, Body weight (g) at first egg production, age at sexual maturity (days), weight of first egg (g), egg numbers at 40th week, egg weight at 40th week (g), egg numbers at 52nd week, egg weight at 52nd week (g). The least squares mean was estimated considering three different genetic groups of layer chicken (N=450, 150 each group). The main focus of this study was to identify the principal components for economic traits in layer chicken. Further varimax rotation method was applied for the transformation of components to approximate simple structure. Result: The genetic group Desi cross 1 performed better than Desi cross 2 followed by Punjab Red layer chicken. A total of three principal components were obtained which explained a total variance of 75.524%. Principal component 1 had high loads on body weight 10th week to 20th week (BW 10-BW 20) and BWSM and had a variance of 38.892%. Similarly, PC2 and PC3 explained variance of 27.072% and 9.560% respectively and had high loads on 1 week body weight to 9-week body weight (BW1-BW9) and age at sexual maturity, 40-week egg production, 52-week egg production respectively. From this study it was included that PCA can be used for selecting the economic traits for breeding purpose of layer chicken.