Emerging Trends in Engineering Research and Technology Vol. 4

Current Research on Forward Converter Based Switch Mode Power Supply with Modified Boost Converter as PFC

Naspuri Arun Raju — Thu, 11 Jun 2020 00:00:00 +0000

Due to modern era industrialization, the requirement of DC power is drastically increased. Enemy harmonics and bad power factor are the primary most concerns in power electronics. In mono-stage SMPS system, it is observed that percentage sharing of real power in apparent power is quite low and also observed that undesired harmonics are found enrich in source current.

This project deals with two stage SMPS system in which forward converter is used as step down converter and modified boost converter is used to increase the real power share in apparent power of source as well as to reduce the higher frequency currents in source current. Isolated converters are preferred to get reduced ground bounce as well as to isolate from high voltage circuit. To get rid of kilo-hertz currents in load, it is preferred to make the terminal capacitor voltage ripple free with the use of closed loop control system. Boost converter is adjusted to get rid of high stresses over a switch which further reduces switching losses to noticeable percentage. The settling time of terminal voltage was adjusted to a fraction of second without affecting the output DC’s smoothness.

Failure of FSSW on Mild Steel Plates Using En19 Taper Thread Tool

B. Srinivasulu, V. V. Prathibha Bharathi — Thu, 11 Jun 2020 00:00:00 +0000

FSSW is used a lot of vicinity which are from marine to aerospace industry. FSSW is effected with tool rotational speed, tool transverse speed, dwell time and tool plunge depth. One of them is weight. With the reference to the research work In this paper two flat plates of similar metals of MS of 1.2 mm thickness & 30.25mm specimen width are subjected to a solid state welding at 900rpm using the EN19 taper thread tool. The tensile-shear test results showed that the FSSW specimens are better than the specimens welded by the conventional FSSW process at 900-1300 tool rotational speeds with using taper thread tool pin profiles. By doing tensile test following ASTM B 557:2006 procedure the ultimate shear load obtained from the conventional friction stir spot welds is 1.960KN.

Distributed Detection in Cognitive Radio Networks: Recent Developments

Shweta Kumari — Thu, 11 Jun 2020 00:00:00 +0000

With the increase of wireless services and devices, and the need to maintain their QoS requirements, the demand for spectral bandwidth has increased in recent years. The traditional spectrum allocation techniques have led to inefﬁcient spectrum utilisation. In this project, we analyse a new paradigm called Dynamic Spectrum Access , using energy detection methods in case of real-valued and complex-valued signals. An energy efﬁcient detection is also proposed in a distributed cognitive network for the case of a single SU and N PUs, where N > 1. The cognitive radio network also has to pay a cost whenever a SU switches a channel. In this scenario, detection algorithms are also proposed absed on myopic approach.

Air Traffic Forecasting Using Time Series Models: New Perspectives

Manohar Dingari, D. Mallikarjuna Reddy, V. Sumalatha — Thu, 11 Jun 2020 00:00:00 +0000

In this chapter, Holt-Winters’ Additive model is fitted to the data regarding Domestic Air traffic in Air India flights. The investigation was done using dataset on number of passengers travelling by Air India domestic flights during January 2012 to November 2018. To prepare a tool to analyze the traffic flow monthly wise this helps Air India to revise their services. ARIMA model also has been fitted to the data, and compared with Holt-Winters’ Additive model. Finally, the results, findings and analysis proved that the Holt-Winters’ Additive model is superior to the ARIMA model for this data. This kind of analysis is very useful for forecasting the Air traffic.

A Novel Clone-based Reuse Method to Maintain Proficiency in Software Engineering Practice: An Overview

Kavitha Esther Rajakumari — Thu, 11 Jun 2020 00:00:00 +0000

The source code of an application paves way for a quality software product. Quality software in-turn helps in imposing software reuse. In this paper, pieces of similar codes also known as code clones or code duplications are considered as reusable software components. In general code clones are considered harmful in software engineering practice. They are considered to degrade the quality of software. Code clones are detected and removed without further processing. In this paper, a token- based CodeClone reuse method is proposed to detect type- 1 and type-4 clones. Positive effects of clones are analyzed and beneficial clones are extracted from the cluster of clones detected. The proposed method aids in the art of developing software thereby enforcing the concept of software reuse. The working principle of the proposed method is implemented using open source software as inputs. Beneficial clones are further stored in a database for future use. This database will be used while developing a software system, which indirectly leads to software component reuse. This clone-based software reuse is evaluated based on standard software reuse metrics and models. The primary objective of this proposed methodology is to meet the requirements, to encourage and to support small-scale organizations in terms of software reuse.i.e. quality products with minimum investment. Clone report is generated as it assists in knowing about the clone details within a software system.

Comprehensive Study on Removal Efficiency of Strychonomous Potatorum and Alum as Blended Coagulant for Treatment of Textile Effluent

N. Muralimohan, P. Sudha, T. Palanisamy — Thu, 11 Jun 2020 00:00:00 +0000

An explorative investigation was conducted for the viable utilization of Strychonomous potatorum seed powder and alum as a blended coagulant for the treatment of textile mill effluent. In this article, natural coagulant Strychonomous potatorum (SP) and conventional Coagulant Alum Al₂(SO₄)₃ of 10, 20, 40, 60 and 80 mg/L dosages were used. Different proportions of SP: Al₂(SO₄)₃ like 0:0 (P0), 10:90 (P1), 20:80 (P2), 30:70 (P3), 40:60 (P4), 50:50 (P5),60:40 (P6),70:30 (P7), 80:20 (P8) and 90:10 (P9) were used in Pre and post treated textile mill effluents. Formation of floc during coagulation process has been studied in the laboratory extent to ascertain the optimum dosage of blended coagulants and to estimate the percentage removal efficiency of major pollutants in textile mill effluent such as turbidity, TSS, TDS, COD and BOD. when compared with other dosage, from the observed results, the blended coagulant SP: Al₂(SO₄)₃ of 40:60 dosage ratio offers better removal efficiencies with respect to turbidity, TSS, TDS, COD and BOD and it has been suggested as an appropriate dosage for the treatment of textile mill effluent.

Monitoring and Identifying the Occurrence of Oil Spill in the Ocean Using Satellite Image for Disaster Mitigation: Advanced Study

Mukta Jagdish — Thu, 11 Jun 2020 00:00:00 +0000

In this approach a morphological closing techniques is used which solve the problem of oil spills detection in the ocean. As we know marine species face biggest issue of oil spill to solve this issue a morphological closing method is applied for Monitoring and identifying the occurrence of oil spill in the ocean using satellite image for disaster mitigation. This research work is carried out using SAR RADARSAT-2 image, which is capture from Gulf of Mexico. The work illustrate detection of oil spill in the ocean using satellite data with gray level masking, prepared with slick-relevant structure extracted by the algorithm with less time. In conclusion, morphological closing techniques can be used as a tool for monitoring and identifying the occurrence of oil spill and Synthetic aperture radar image serves as a good sensor for detection and surveying of oil spill. The performance shows the resulting grey level mask containing structure of the slick with levels of gray corresponding to less damp / most damped sea surface roughness.

A Prudence Introspection of Road Accident Prediction through Deep Learning

V. Priya, C. Priya — Thu, 11 Jun 2020 00:00:00 +0000

The research is based on the vehicle mishaps venture to gather and structure a dynamic, secure transportation lamentably vehicle crashes were unavoidable. The accident prediction related to the risky environment data collection and arrangements based on highest priority of reality of accidents. The social activity and roadway structures are useful in the progression of traffic security control approach. We accept that to secure the best possible setback decline impacts with constrained budgetary resources, it is fundamental that measures be set up on coherent and objective studies of the explanations behind mishaps and seriousness of wounds. A survey based on the different algorithms able to predict the road accident prevention methods. This paper exhibits a couple of models to predict the reality of harm that occurred in the midst of car accidents using three artificial intelligent approaches (AI). The proposed scheme contributes a neural system prepared utilizing decision trees and fluffy c implies clustering methodology for division.

Reverse Link Performance of CDMA Systems with RAKE Receiver and Multiple Access Interference Cancellation

Ayodeji. J. Bamisaye — Thu, 11 Jun 2020 00:00:00 +0000

All the subscribers in CDMA systems share the common channel. The limitation factor on the system’s capacity is not the bandwidth, but multiuser interference and the near far problem. In this chapter, we model CDMA system from the perspective of mobile radio channels corrupted by additive white noise generated by multipath and multiple access interferences. The system’s receiver is assisted using different combining diversity techniques such as Decorrelating Detector (DD), Minimum Mean Squared Error (MMSE) and Parallel Interference Cancellation (PIC). Performance analysis of the system with these detection techniques is presented. The chapter demonstrates that combining diversity techniques in the system’s receivers markedly improve the performance of CDMA systems.

A New Model for Population Analysis among Different States in India using Machine Learning Algorithm

Addepalli V. N. Krishna, M. Balamurugan — Thu, 11 Jun 2020 00:00:00 +0000

In this work Data from 2011 census is taken to identify the state which influences more in Population census among the different states identified. The data is considered from Madhya Pradesh, followed with Utter Pradesh, then to Bihar, Bengal and Orissa. Similarly other case studies are also done for Southern Indian states and North Eastern States. Genetic algorithm will be tried to find the optimal location for the given study. A fitting function is calculated for the population data of 2011 using Lagrange Interpolation technique. This fitting function is given as input to Genetic algorithm to find the optimal state which have maximum influence in the population growth among different states of India. The study also discussed various factors which influence population growth with respect to a place.

Modeling the Estimated Annual Peak Load for the Kingdom of Bahrain

Isa S. Qamber, Mohamed Y. AL-Hamad — Thu, 11 Jun 2020 00:00:00 +0000

It is important to develop an appropriate model for calculating the electricity demand projections demanded by decision makers. Specific models were derived to estimate future demand for electricity in the Kingdom of Bahrain in this study. The population and ambient temperature are considered as well as the time factor (year). The remote models were developed to describe the annual demand for electrical energy during the summer period. Estimated maximum annual electric demand values are obtained and evaluated according to the actual maximum load data for the Kingdom of Bahrain.

Inpainting by Modified Lattice Boltzmann Method and Exemplar Method for Object Removal in Colour Images

R. F. Liji, M. Sasikumar, P. Sreejaya — Thu, 11 Jun 2020 00:00:00 +0000

In this paper we use image inpainting technique in colour images. Inpainting is a technique in which, a missing area or pixels are replaced by adequate neighbouring pixels so that the resultant image obtained will look as no defect is there. In this paper we have removed an object from the colour image and the vacant pixels are filled with the help of the surrounding neighbouring pixels. Two techniques are used here for removing and inpainting an object from the still colour image, Modified Lattice Boltzmann Method and Exemplar Method. Existing Exemplar Method of inpainting is used to compare the results of Modified Lattice Boltzmann Method. The Lattice Boltzmann Equation from fluid dynamics it modified to use for inpainting. Peak Signal to Noise Ratio, Self-SIMilarity Index and execution time of the image is calculated for both inpainting techniques. From the objective analysis, it is found that the proposed Modified Lattice Boltzmann method of inpainting gives a better inpainted result.

A Forest Change Detection Using Auto Regressive Model-based Kernel Fuzzy Clustering: Advanced Study

Madhuri B. Mulik, V. Jayashree, P. N. Kulkarni — Thu, 11 Jun 2020 00:00:00 +0000

This chapter focuses on the use of satellite images for the forest change detection, forest cover management. In this chapter, the vegetation indices play a major role in extracting the useful information from the satellite images. Also analysis was done on the imagery data from the remote sensing satellites for detecting the changes in the forest over the year’s 2007-2017 using the pixel-based Bhattacharya distance. The indices from the satellite images are fed to the automatic segmentation model using the proposed Kernel Fuzzy Auto regressive (KFAR) model, which is the modified Kernel Fuzzy C-Means (KFCM) Clustering algorithm with the Conditional Autoregressive Value at Risk (CAVIAR). The forest change detection using the pixel-based Bhattacharya distance follows the segmentation and the experimentation reveals that the proposed method acquired the minimal Mean Square Error (MSE) and maximal accuracy of 0.0581 and 0.9211.

Exploring Optimum Solutions for Management of House Hold Data with Population Census in Indian Context

Addepalli V. N. Krishna — Thu, 11 Jun 2020 00:00:00 +0000

The study discusses the population census in identified states and its influence in neighborhood states. A fitting function will be generated from the identified data which will be processed using genetic algorithm to find the most probable state which influences population among the identified set.

In continuation to that we can consider the House hold data in different states as rows and different types of House Holds like Good, Livable and Dilapidated as columns as input to the GenAlgo function. The problem is initialized with a fitness function and mutation function relevant to the Household problem. The work starts with data frame that is passed back to fitfun and mutfun to enable them to take advantage of any additional data viable for them to perform their proposed functions. The idea here is to have put together a data frame containing the Good number of households and Livable households of the population to identify the best performers of states in development activities.

This work tries to map population growth with development activities like House hold data in finding a balance in growth among different states in India.