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A Geo-illustration Studies of Nagamangala, Mayasandra, Yediyur area of Chitradurga Schist belt, Dharwar Craton, Southern India
Get PDFIn recent times the Precambrian shields of the world have became nerve centers of global research aimed mainly at decipher the early history of the Earth. Various agencies like the Geological Survey of India (GSI), Ministry of Mines (MoM), Ministry of Earth Sciences (MoES), research institutes and universities of not only India but from the other countries also are involved in this task. As such the craton portion of Karnataka has been gaining lot of importance in recent years on account of its unique geo-illustration. The present study area covers southern extensions of the Chitradurga schist belt, which includes the parts of Nagamangala, Mayasandra and Yadiyur schist belts and associated gneissic terrain with enclaves of mafic and ultramafic rocks exposed around Nagamangala town. Both the Nagamangala and Mayasandra schist belts are correlated to the Sargur Group ( 3400 my) while the Yadiyur schist belt to Dharwar Super Group. The present area is better suited for above mentioned studies as in this area the various litho units belonging to two stratigraphic units are well exposed and lie almost side by side. The present study of the area around the parts of Nagamangala, Mayasandra and Yadiyur dykes of Chitradurga schist belts of Dharwar Craton and is situated in Mandya and Tumkur district of Karnataka State. Sampling has been done so as to include all the noted variations in the field characters and to have a good geographic coverage. Satellite imagery has helped in picking up a number of major and minor lineaments cutting across the schist belts and gneisses. The geological map produced here has been prepared on the basis of the detailed observations in the field using Geoinformatics tools. The representative samples have been examined using geological microscope and the rocks have been classified on the basis of their mineral assemblages and textural features. The extensive igneous activity undergone by the study area is represented by the numerous dykes. A detailed geological characterization of the environs in the Nagamangala, Mayasandra and Yadiyur area on the basis of field observations has tried to give not only an unified illustration of the geology of the area but also has commented on the possible modes of advancement of the different necessary components like topography, climate, rainfall, drainage, soil and lithology of the study area
Performance Optimization of Peak to Average Power Ratio in FBMC Waveforms
Get PDFHigh spectral efficiency and low computational complexity are the requirements of 5G wireless communication systems. They must also offer low PAPR (peak to average power ratio), low latency, and high throughput. In 5G it is not possible to realise all of these requirements through a single technique. One of the efforts is to look for a suitable technique for 5G. So, a suitable technique emerges whose name is Filter Bank Multicarrier (FBMC). But it has a high complexity, high Peak to Average Power (PAPR) and high out of band (OOB) leakage which results in inter-carrier interference and inter-channel interference. Also, due to high PAPR, mobile batteries are depleted more rapidly. So, a PAPR reduced method is needed. In this paper, a method of Pruned DFT Precoded FBMC to optimize the PAPR for different number of subcarriers. The performance evaluation in terms of bit error rate (BER) and spectral efficiency of OFDM, FBMC and Pruned DFT Precoded FBMC has been done in this paper. In DFT Precoded FBMC, a DFT spreading matrix is multiplied with FBMC waveform and transmit only some part especially half of the DFT precoded matrix and rest remain zero by us. Monte Carlo simulation with one tap equalizer is used to validate our results
Optimization of Detection Error Rate in Cooperative Sensing using ACO algorithm
Get PDFCognitive radio (CR) is the next generation communication technology that combined the use of radio technology and networking technology. One of the key elements of cognitive radio is Cooperative spectrum sensing which sensing results from a different node are combined either through hard decision fusion (HDF) scheme or through soft decision fusion(SDF) scheme at fusion center (FC). SDF has excellent performance, but a lot of overhead is required while HDF requires only one bit of overhead, but has the worst performance. There is a trade-off between overhead and accuracy in this conventional scheme. In this paper, ant colony optimization (ACO) based hybrid cooperative sensing framework is proposed which optimizes the weighting coefficient vector of sensing result from a different node. The novelty of this paper is to use the ACO algorithm as significant tools that evaluate the optimal values of sensing weight for cooperative sensing so that it minimizes the overall cooperative sensing error under min-max criteria. The performance of the proposed ACO based framework is thoroughly analyzed and compared with conventional HDF approaches i.e. AND, OR, majority as well as conventional SDF based approaches like equal gain combing (EGC), MRC, etc., through simulation. The experimental result shows the proposed framework outperforms with the conventional HDF scheme and it has a low overhead requirement compared to the conventional SDF scheme. Finally, analytical evaluation and validation for the performance of ACO algorithm in this framework is also examined and it gives the excellent convergence performance with lower computation time and less complexity which meet the real-time requirement of cooperative spectrum sensing
Solar Generation Prediction using Artificial Intelligence: A Review
Get PDFSolar energy generation is one of the most promising and fastest-growing renewable energy sources for the generation of useful energy worldwide. Forecasting of solar power is the most essential for the planning of grid operations, mainly in residential microgrids, to optimize and manage the energy produced in a dispatchable trend. Due to the inability of deterministic methods to accurately forecast solar power generation due to their dependency on natural inputs, Artificial Intelligence (AI) based techniques are required to be implemented. AI techniques clubbed with stochastic methods are considered to be highly effective for solar generation forecasting. In this review, various artificial intelligence-based supervised and unsupervised learning methods for solar energy generation prediction are analyzed. The use of weather and environmental inputs for supervised learning is also compared. The accuracy of prediction of solar generation using several AI, Machine Learning, and Neural Network-based techniques are also analyzed in the paper. The paper presents an overall picture of the use of Artificial-Intelligence based techniques in solar generation prediction in the world
Impact of Covid19 induced economic restrictions on some selected sectors of the Indian Economy
Get PDFThe deserted roads, empty public places and locked factories in all the major cities of the world depicts a hard to believe spectre that would have been unimaginable a few months ago. As mankind contemplates about the future within the confines of home, there seems to be a trade-off between saving lives and continuing with life. The spark of COVID 19 in the most populous country on the face of earth and its subsequent conflagration throughout the continents has only a few precedents in terms of scale and severity. Almost all the major and minor economies are engulfed by its impact. In a scenario where everyone depends upon everyone else, India, just like any other country, is also staring at an uncertain future. To gauge the full impact of Covid19 on the economy, it is better to analyse one sector at a time
A Comparative Analysis of Genetic Algorithm and Moth Flame Optimization Algorithm for Multi-Criteria Design Optimization of Wind Turbine Generator Bearing
Get PDFAs global climate change is affecting the meteorological conditions and instigating massive social suffering, the emanation of greenhouse gases is necessitated to be restricted through effective usage of renewable sources of energy as per the directions of the Paris treaty of 2015. Wind energy, a renowned renewable energy resource, is enabling countries to generate power in a relatively cost-effective way and causes a remarkably nominal carbon trail. A considerable extent of the functioning lifespan of wind turbines remains unexploited every year all over the globe because of mechanical malfunctions. The existing research strives to evaluate the relative competency of the Genetic Algorithm (GA) and the Moth Flame Optimization Algorithm (MFOA) for optimizing the wind turbine generator bearing design through enhancement of its static and dynamic load-bearing capacities. The design solutions attained by both of the algorithms validate a noteworthy growth of the optimization objectives when contrasted with the technical catalog standards. Moreover, the relative evaluation demonstrates the superior aptness of multi-criteria GA on multi-criteria MFOA for finding improved design resolutions
Applying the Customer Based Brand Equity Model in examining Brand Loyalty of Consumers towards Johnson and Johnson Baby Care Products: A PLS-SEM Approach
Get PDFThis research primarily discusses the effects of various dimensions of CBBE Model that leads to brand loyalty in baby care products segment of Johnson and Johnson. While the CBBE Model is a well-established model to measure the brand equity the paper focuses on validating the model through empirical research and understanding the mediating effects of the same. Data for the study was collected through structured questionnaire using 5 point Likert scale where the responses varied between strongly agree to strongly disagree. Sample size consisted of 300 respondents all of which were female and had been using the said brand. Data was analyzed using Partial Least Square (PLS) Structural Equation Modeling (SEM) and the findings of this research show that perceived quality and perceived trust leads to increased brand value which in turn leads to brand loyalty. The study offers strategic implications for the industry thereby helping the companies to focus their efforts on building trust and developing quality product
Municipal sewage sludge/Biomass co-pyrolysis in a batch reactor: Physico-Chemical analysis of the products
Get PDFMunicipal sewage sludge (MSS) was co-pyrolysed with sugarcane bagasse (SCB) (50 wt %) at 500 ⁰C in a batch reactor in the presence of nitrogen under atmospheric pressure to produce modified biooil. In comparison with only MSS pyrolysis, the yield of the biooil and gas improved by 100% and 14%, respectively. Furthermore, yield of char (residue) decreased by 42%. GC/MS analysis showed that the co-pyrolysis afforded a reduction of sulfur and nitrogen compound significantly. Physical characteristics demonstrated that MSS derived biooil exhibited alkaline nature, whereas, SCB shows acidic nature. Thus, pH of co-pyrolysis derived biooil increases. Moreover, water content is slightly increases. In contrast to this, density and viscosity marginally reduced. Such a property of biooil favors its use as a transport fuel. Thus, co-pyrolysis technique has a potential to modify the properties of biooil significantly
ANALYSIS AND DESIGN OF TURBINE BUILDING USING HIGH STRENGTH STEEL
Get PDFStructural steel is advantageous material in construction industry because of its constructability and high strength to mass ratio. Steel frame is composed of structural steel members of different shape and size, which is connected with each other to transfer loads and provide complete rigidity against heavy loads. Steel frame can be built in a couple of days rather than weeks, with 20% to 40% reduction in construction time compared to on site construction. Now a day’s in steel frame, structural components are used of medium strength steel grade E250 and E350. Grade E250 is used in general fabrication, storage tanks, structural member, etc. Grade E350 steel is utilized in projects where average strength is required without compromising weldability and ductility. Since rising price of materials requires reduction in weight of the structure, use of High Strength Steel (HSS) is increased and it fulfills the most of constructional requirements. The HSS is developed to provide the beneficial mechanical properties and excessive corrosion resistance than conventional grade steel. With the reduced weight, steel provides higher strength to the structure against heavy loads. In this research, E450 and E350 grade steels have been used to design the turbine building. Dead, Live, Wind, Seismic and Crane loads are applied to the turbine building as per IS 875:1987, IS 875:2015, IS 1893(1):2002, and IS 1893(4):2005, respectively and designed as per IS 800:2007 using Staad.pro software. Built-up, Indian, and Jindal sections are provided to the structural elements. After the comparison of results of E350 and E450 grade steels, it is concluded that by using HSS, the reduction in steel up to 15%. Structural member size decreases and hence overall weight of the turbine building is reduced. Reduction of steel results in overall construction cost