Pub Date : 2021-04-15DOI: 10.30780/ijtrs.v06.i05.003
Ankit Yadav, Riya Fagna, Aparna Vyas
- In this data age century with increment in the modern technology there is a development in the theory of multidimensional data to provide the higher directional sensitivity in imaging. A numeric image is a portrayal of a real image which is taken as a set of numbers that can be gathered and picked up by a digital computer. In order to decode the image into numbers it is divided into small segments called pixels (picture elements). Whenever there is a transmission of images or due to some environment factor there is an addition of noise to the images takes place that ultimately results in the reduction of originality of the image. It is very important to remove the noise from the images so that it is safeguard. Shearlets are a multiscale foundation which authorize efficient encoding of anisotropic feature in multivariate problem classes. In this paper, we have set forth the noise removal transform by hard thresholding for denoising. We can denoise the noisy image by wiping out the fine details, to enhance the quality of the images. This paper presents the denoising of a natural image based on wavelet and shearlet trans- form with hard thresholding techniques which is used to eliminate noise from the image. The images are corrupted with Gaussian, salt pepper and speckle noise. The multiscale and multi-directional outlook of shearlet transform are methodical in take care of edges of an image in denoising procedures. Shearlet comes out as a methodical transform for edges analysis and detection. Quantitative performance parameters such as PSNR, MSE are used to evaluated the denoised image effect. And hence came to the conclusion that the Shearlet Transform with hard thresholding in pyshear lab (python) is an methodical technique for enhancing the overall quality of the image.
{"title":"IMAGE DENOISING USING HARD THRESHOLD TECHNIQUES ON WAVELET TRANSFORM AND SHEARLET TRANSFORM","authors":"Ankit Yadav, Riya Fagna, Aparna Vyas","doi":"10.30780/ijtrs.v06.i05.003","DOIUrl":"https://doi.org/10.30780/ijtrs.v06.i05.003","url":null,"abstract":"- In this data age century with increment in the modern technology there is a development in the theory of multidimensional data to provide the higher directional sensitivity in imaging. A numeric image is a portrayal of a real image which is taken as a set of numbers that can be gathered and picked up by a digital computer. In order to decode the image into numbers it is divided into small segments called pixels (picture elements). Whenever there is a transmission of images or due to some environment factor there is an addition of noise to the images takes place that ultimately results in the reduction of originality of the image. It is very important to remove the noise from the images so that it is safeguard. Shearlets are a multiscale foundation which authorize efficient encoding of anisotropic feature in multivariate problem classes. In this paper, we have set forth the noise removal transform by hard thresholding for denoising. We can denoise the noisy image by wiping out the fine details, to enhance the quality of the images. This paper presents the denoising of a natural image based on wavelet and shearlet trans- form with hard thresholding techniques which is used to eliminate noise from the image. The images are corrupted with Gaussian, salt pepper and speckle noise. The multiscale and multi-directional outlook of shearlet transform are methodical in take care of edges of an image in denoising procedures. Shearlet comes out as a methodical transform for edges analysis and detection. Quantitative performance parameters such as PSNR, MSE are used to evaluated the denoised image effect. And hence came to the conclusion that the Shearlet Transform with hard thresholding in pyshear lab (python) is an methodical technique for enhancing the overall quality of the image.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121034187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-15DOI: 10.30780/ijtrs.v06.i05.001
Rachakonda Hrithik Sagar, Abhishek Bingi, Aashray Pola, K. S. R. Goud, Tuiba Ashraf, S. Sahana
The incidence of skin cancer is increasing by epidemic proportions. According to WHO, Skin Cancer is the world’s 6th most common cancer. It can be classified into Basal cell carcinoma, Squamous cell carcinoma and Melanoma among which Melanoma is more difficult to predict. By using this method, we can assist dermatologists to detect at an early stage as Computer Vision plays a vital role in diagnosis. In this paper, to detect skin cancer we are using machine learning-based algorithms. Traditionally classification algorithms are Convolutional neural networking which Consists of initialization, adding a convolutional layer, summing pooling layer, summing flattening layer, summing a dense layer, then compiling Convolutional neural networks and fitting the CNN model to a dataset. We used machine learning model architecture to determine if the skin images of the patients are harmful or harmless via using machine learning libraries provided in python. We have chosen this approach to be more precise and specific in recognizing about cancer and ultimately declining the mortality rate caused by it.
{"title":"MALIGNANT SKIN CANCER DETECTION USING CONVOLUTIONAL NEURAL NETWORKING","authors":"Rachakonda Hrithik Sagar, Abhishek Bingi, Aashray Pola, K. S. R. Goud, Tuiba Ashraf, S. Sahana","doi":"10.30780/ijtrs.v06.i05.001","DOIUrl":"https://doi.org/10.30780/ijtrs.v06.i05.001","url":null,"abstract":"The incidence of skin cancer is increasing by epidemic proportions. According to WHO, Skin Cancer is the world’s 6th most common cancer. It can be classified into Basal cell carcinoma, Squamous cell carcinoma and Melanoma among which Melanoma is more difficult to predict. By using this method, we can assist dermatologists to detect at an early stage as Computer Vision plays a vital role in diagnosis. In this paper, to detect skin cancer we are using machine learning-based algorithms. Traditionally classification algorithms are Convolutional neural networking which Consists of initialization, adding a convolutional layer, summing pooling layer, summing flattening layer, summing a dense layer, then compiling Convolutional neural networks and fitting the CNN model to a dataset. We used machine learning model architecture to determine if the skin images of the patients are harmful or harmless via using machine learning libraries provided in python. We have chosen this approach to be more precise and specific in recognizing about cancer and ultimately declining the mortality rate caused by it.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124287494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-15DOI: 10.30780/IJTRS.V05.I12.003
P. Pandit, Rohit Kumar, Manju M. Gupta
Power system stability is one of the most crucial issues which deals with the response of the system to the errors such as: Sudden load change, Short circuit, Prime mover failure, Excitation failure etc. To maintain the stability and the damping oscillation of power system. Recently, FACTS controllers have been proposed to enhance the transient or dynamic stability of the power systems, e.g.: SVC, TCSC, STATCOM. In this a fuzzy logic controller is proposed to apply a suitable control signal to STATCOM. To improve the fault clearing time and transient stability improvement within a particular duration. It is found that the fault clearing times of 0.10sec for generator (G1) under test are self-stable with respect to simulation time. Proposed method is implemented in a single machine infinite bus system and the results are compared with conventional energy function-based controllers.
{"title":"IMPROVEMENT OF TRANSIENT STABILITY BY USING FLSTATCOM","authors":"P. Pandit, Rohit Kumar, Manju M. Gupta","doi":"10.30780/IJTRS.V05.I12.003","DOIUrl":"https://doi.org/10.30780/IJTRS.V05.I12.003","url":null,"abstract":"Power system stability is one of the most crucial issues which deals with the response of the system to the errors such as: Sudden load change, Short circuit, Prime mover failure, Excitation failure etc. To maintain the stability and the damping oscillation of power system. Recently, FACTS controllers have been proposed to enhance the transient or dynamic stability of the power systems, e.g.: SVC, TCSC, STATCOM. In this a fuzzy logic controller is proposed to apply a suitable control signal to STATCOM. To improve the fault clearing time and transient stability improvement within a particular duration. It is found that the fault clearing times of 0.10sec for generator (G1) under test are self-stable with respect to simulation time. Proposed method is implemented in a single machine infinite bus system and the results are compared with conventional energy function-based controllers.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130707932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-15DOI: 10.30780/IJTRS.V05.I12.001
Garima Kunwar Sarangdevot, Bhumika Shrimali, R. Joshi
DOI Number: https://doi.org/10.30780/IJTRS.V05.I12.001 pg. 1 www.ijtrs.com www.ijtrs.org Paper Id: IJTRS-V5-I12-001 Volume V Issue XII, December 2020 @2017, IJTRS All Right Reserved INTELLIGENT CONTROL STRATEGY TO MITIGATE THE HARMONIC DISTORTION IN WIND ENERGY SYSTEM Garima Kunwar Sarangdevot, Bhumika shrimali, R.R. Joshi E-Mail Id: garima2471994@gmail.com M. Tech Student, Department of Electrical Engineering, CTAE, Udaipur, Rajasthan, India Professor, Department of Electrical Engineering, CTAE, Udaipur, Rajasthan, India AbstractWind energy technologies are improving even faster than other renewable resources in the 21st century, such as solar, geothermal, etc. In this article, the conventional converter is replaced by a multilevel converter. This simple scheme introduces a low frequency harmonic distortion substance of high intensity into the PMSG and therefore increases the total loses in it. The fuzzy logic is often used as a machine side converter control technique to maintain the constant DC voltage provided to GSC without any additional DC-DC converter. The initially designed Based Load Side Converter (LSC) has been used to minimize harmonics and professional and nonordinately deliver the reactive power to the load. The feasibility of the proposed system model and integrated control strategy are verified using MATLAB/Simulink simulations.
{"title":"INTELLIGENT CONTROL STRATEGY TO MITIGATE THE HARMONIC DISTORTION IN WIND ENERGY SYSTEM","authors":"Garima Kunwar Sarangdevot, Bhumika Shrimali, R. Joshi","doi":"10.30780/IJTRS.V05.I12.001","DOIUrl":"https://doi.org/10.30780/IJTRS.V05.I12.001","url":null,"abstract":"DOI Number: https://doi.org/10.30780/IJTRS.V05.I12.001 pg. 1 www.ijtrs.com www.ijtrs.org Paper Id: IJTRS-V5-I12-001 Volume V Issue XII, December 2020 @2017, IJTRS All Right Reserved INTELLIGENT CONTROL STRATEGY TO MITIGATE THE HARMONIC DISTORTION IN WIND ENERGY SYSTEM Garima Kunwar Sarangdevot, Bhumika shrimali, R.R. Joshi E-Mail Id: garima2471994@gmail.com M. Tech Student, Department of Electrical Engineering, CTAE, Udaipur, Rajasthan, India Professor, Department of Electrical Engineering, CTAE, Udaipur, Rajasthan, India AbstractWind energy technologies are improving even faster than other renewable resources in the 21st century, such as solar, geothermal, etc. In this article, the conventional converter is replaced by a multilevel converter. This simple scheme introduces a low frequency harmonic distortion substance of high intensity into the PMSG and therefore increases the total loses in it. The fuzzy logic is often used as a machine side converter control technique to maintain the constant DC voltage provided to GSC without any additional DC-DC converter. The initially designed Based Load Side Converter (LSC) has been used to minimize harmonics and professional and nonordinately deliver the reactive power to the load. The feasibility of the proposed system model and integrated control strategy are verified using MATLAB/Simulink simulations.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114426455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-15DOI: 10.30780/specialissue-icaccg2020/039
Sanskar Aggarwal
Heart disease is one of the most critical human diseases in the world and affects human life to a very large extent. An accurate and timely diagnosis of heart disease is important to treat and prevent a heart failure. Using machine learning techniques and the data procured by the health care industry, a disease can be detected, predicted and even cured. In this paper, the Naive Bayes, Linear Classifier, K-nearest Neighbour and Random Forest machine learning algorithms have been applied. The results of these four algorithms were compared on the basis of accuracy, specificity and sensitivity for prediction of disease.
{"title":"COMPARATIVE STUDY ON MACHINE LEARNING ALGORITHMS FOR HEART DISEASE PREDICTION","authors":"Sanskar Aggarwal","doi":"10.30780/specialissue-icaccg2020/039","DOIUrl":"https://doi.org/10.30780/specialissue-icaccg2020/039","url":null,"abstract":"Heart disease is one of the most critical human diseases in the world and affects human life to a very large extent. An accurate and timely diagnosis of heart disease is important to treat and prevent a heart failure. Using machine learning techniques and the data procured by the health care industry, a disease can be detected, predicted and even cured. In this paper, the Naive Bayes, Linear Classifier, K-nearest Neighbour and Random Forest machine learning algorithms have been applied. The results of these four algorithms were compared on the basis of accuracy, specificity and sensitivity for prediction of disease.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115967474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-15DOI: 10.30780/specialissue-icaccg2020/043
Sangeeta Rathi, S. Bamal
{"title":"DEEP LEARNING AND GLOBALLY GUIDED IMAGE FILTERING TECHNIQUE BASED IMAGE DEHAZING AND ENHANCEMENT","authors":"Sangeeta Rathi, S. Bamal","doi":"10.30780/specialissue-icaccg2020/043","DOIUrl":"https://doi.org/10.30780/specialissue-icaccg2020/043","url":null,"abstract":"","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116631801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-15DOI: 10.30780/specialissue-icaccg2020/026
Ansar Ali, T. Devi
In this work, CFD (Computational Fluid Dynamics) simulations have been conducted to investigate flow behavior of water in fully baffled stirred tank employed with Rushton impeller. The dimension of the inner rotating fluid zones in Multiple Reference Frame (MRF) impeller model plays an important role in accurately predicting the results on numerically based problems. Therefore, the aim of the paper is to develop CFD model, optimizing the dimensions of inner rotating fluid zone for MRF model (which is a numerical algorithm designed for modeling the rotating part i.e., impeller in stirred tank). Standard k–ε turbulence model which is a commonly used algorithm to model the turbulent fluid flow nature in the system is adopted. The velocity profile (radial and tangential velocity) are studied and compared with experimental results of Wu and Patterson (1989) and Rushton et al. (1950).Based on the comparison of correlation coefficient in the predictions of normalized mean velocities, zone 4 having diameter of 0.104 m and height of 0.032 m was found to be optimal for CFD modelling of stirred tank. The global flow parameters such as flow number predicted by CFD matched quite well with the data of Wu and Patterson (1989) and Rushton et al. (1950). The percentage deviation in the pumping number predictions at various radial locations show a percentage deviation less than 15% in comparison with experimental results.
本文采用CFD(计算流体力学)方法对全隔板搅拌槽内的流体流动特性进行了数值模拟。在多参照系叶轮模型中，内部旋转流体区的尺寸对数值问题的准确预测结果起着重要作用。因此，本文的目的是建立CFD模型，对MRF模型(为搅拌槽内旋转部件即叶轮建模而设计的数值算法)的内部旋转流体区尺寸进行优化。采用标准k -ε湍流模型，这是一种常用的模拟系统中湍流流体流动性质的算法。研究了速度剖面(径向和切向速度)，并与Wu and Patterson(1989)和Rushton et al.(1950)的实验结果进行了比较。通过对归一化平均速度预测的相关系数比较，发现直径为0.104 m、高度为0.032 m的区域4最适合搅拌槽CFD建模。CFD预测的流数等全局流动参数与Wu and Patterson(1989)和Rushton et al.(1950)的数据吻合较好。与实验结果相比，各径向位置泵送数预测的百分比偏差小于15%。
{"title":"CFD SIMULATION MODEL FOR MIXING TANK USING MULTIPLE REFERENCE FRAME (MRF) IMPELLER ROTATION","authors":"Ansar Ali, T. Devi","doi":"10.30780/specialissue-icaccg2020/026","DOIUrl":"https://doi.org/10.30780/specialissue-icaccg2020/026","url":null,"abstract":"In this work, CFD (Computational Fluid Dynamics) simulations have been conducted to investigate flow behavior of water in fully baffled stirred tank employed with Rushton impeller. The dimension of the inner rotating fluid zones in Multiple Reference Frame (MRF) impeller model plays an important role in accurately predicting the results on numerically based problems. Therefore, the aim of the paper is to develop CFD model, optimizing the dimensions of inner rotating fluid zone for MRF model (which is a numerical algorithm designed for modeling the rotating part i.e., impeller in stirred tank). Standard k–ε turbulence model which is a commonly used algorithm to model the turbulent fluid flow nature in the system is adopted. The velocity profile (radial and tangential velocity) are studied and compared with experimental results of Wu and Patterson (1989) and Rushton et al. (1950).Based on the comparison of correlation coefficient in the predictions of normalized mean velocities, zone 4 having diameter of 0.104 m and height of 0.032 m was found to be optimal for CFD modelling of stirred tank. The global flow parameters such as flow number predicted by CFD matched quite well with the data of Wu and Patterson (1989) and Rushton et al. (1950). The percentage deviation in the pumping number predictions at various radial locations show a percentage deviation less than 15% in comparison with experimental results.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123083791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-15DOI: 10.30780/specialissue-icaccg2020/007
Jaswinder Kaur, Neha Gupta
DOI Number: https://doi.org/10.30780/specialissue-ICACCG2020/007 pg.1 Paper Id: IJTRS-ICACCG2020-007 @2017, IJTRS All Right Reserved, www.ijtrs.com ARTIFICIAL NEURAL NETWORK: A REVIEW Jaswinder Kaur, Neha Gupta E-Mail Id: jasukaur@rediffmail.com, nehagupta@ansaluniversity.edu.in School of Engineering & Technology, Ansal University, Gurgaon, India AbstractIn this paper an introduction of Artificial Neural Network is presented. Learning Algorithms like Supervised Algorithms, Reinforcement Algorithms and Unsupervised Algorithms are discussed. Also, optimization methods like Gradient Descent, Newton Method, Conjugate Gradient Method, Quasi Newton and Levenberg Marquardt are presented.
DOI号:https://doi.org/10.30780/specialissue-ICACCG2020/007 pg.1论文Id: IJTRS- icaccg2020 -007 @2017, IJTRS All rights Reserved, www.ijtrs.com ARTIFICIAL NEURAL NETWORK: A REVIEW Jaswinder Kaur, Neha Gupta E-Mail Id: jasukaur@rediffmail.com, nehagupta@ansaluniversity.edu.in印度古尔冈安萨尔大学工程与技术学院摘要本文介绍了人工神经网络。讨论了有监督算法、强化算法和无监督算法等学习算法。给出了梯度下降法、牛顿法、共轭梯度法、拟牛顿法和Levenberg Marquardt法等优化方法。
{"title":"ARTIFICIAL NEURAL NETWORK: A REVIEW","authors":"Jaswinder Kaur, Neha Gupta","doi":"10.30780/specialissue-icaccg2020/007","DOIUrl":"https://doi.org/10.30780/specialissue-icaccg2020/007","url":null,"abstract":"DOI Number: https://doi.org/10.30780/specialissue-ICACCG2020/007 pg.1 Paper Id: IJTRS-ICACCG2020-007 @2017, IJTRS All Right Reserved, www.ijtrs.com ARTIFICIAL NEURAL NETWORK: A REVIEW Jaswinder Kaur, Neha Gupta E-Mail Id: jasukaur@rediffmail.com, nehagupta@ansaluniversity.edu.in School of Engineering & Technology, Ansal University, Gurgaon, India AbstractIn this paper an introduction of Artificial Neural Network is presented. Learning Algorithms like Supervised Algorithms, Reinforcement Algorithms and Unsupervised Algorithms are discussed. Also, optimization methods like Gradient Descent, Newton Method, Conjugate Gradient Method, Quasi Newton and Levenberg Marquardt are presented.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130885273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-30DOI: 10.18090/samriddhi.v12i01.5
S. Bajpai, M. Shamsi, M. Kamboj
River water is significant for every living organism. In Indian mythology, rivers are given the status of Goddesses and were worship. Modernization and urbanization have polluted the river water and degraded their status. Assessment of water quality and determination of pollution level has become a big necessity today. In view of the above, the present work envisages findings of various physicochemical characteristics (pH, hardness, chloride, alkalinity, etc.) examined for Gomti river water samples collected from three different locations of Lucknow. This study was meant to determine the recent status of river Gomti along the Lucknow stretch. Results of the study indicated that river water is highly contaminated and not suitable for recreational activities.
{"title":"PHYSIOCHEMICAL ANALYSIS OF GOMTI RIVER IN LUCKNOW CITY, UTTAR PRADESH","authors":"S. Bajpai, M. Shamsi, M. Kamboj","doi":"10.18090/samriddhi.v12i01.5","DOIUrl":"https://doi.org/10.18090/samriddhi.v12i01.5","url":null,"abstract":"River water is significant for every living organism. In Indian mythology, rivers are given the status of Goddesses and were worship. Modernization and urbanization have polluted the river water and degraded their status. Assessment of water quality and determination of pollution level has become a big necessity today. In view of the above, the present work envisages findings of various physicochemical characteristics (pH, hardness, chloride, alkalinity, etc.) examined for Gomti river water samples collected from three different locations of Lucknow. This study was meant to determine the recent status of river Gomti along the Lucknow stretch. Results of the study indicated that river water is highly contaminated and not suitable for recreational activities.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131900473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-15DOI: 10.30780/specialissue-icrdet-2019/006
V. Chhabra, S. Sharma
Abstract-The study of micro strip patch antennas has made great progress in recent years. Compared with conventional antennas, micro strip patch antennas have more advantages and better prospects. They are lighter in weight, low volume, low cost, low profile, smaller in dimension and ease of fabrication and conformity. Moreover, the micro strip patch antennas can provide dual and circular polarizations, dual-frequency operation, frequency agility, broad band-width, feed line flexibility, beam scanning omnidirectional patterning. In this paper we discuss the microstrip antenna, types of microstrip antenna, feeding techniques and application of microstrip patch antenna with their advantage and disadvantages over conventional microwave antennas. In this paper we will try to find the changes in the output of the Microstrip antenna when we change the input values. Analyzing rectangular Line-Fed Microstrip antenna using PCAAD 6.0 software.
{"title":"A PAPER ON PERFORMANCE ANALYSIS OF MICROSTRIP RECTANGULAR PATCH ANTENNA","authors":"V. Chhabra, S. Sharma","doi":"10.30780/specialissue-icrdet-2019/006","DOIUrl":"https://doi.org/10.30780/specialissue-icrdet-2019/006","url":null,"abstract":"Abstract-The study of micro strip patch antennas has made great progress in recent years. Compared with conventional antennas, micro strip patch antennas have more advantages and better prospects. They are lighter in weight, low volume, low cost, low profile, smaller in dimension and ease of fabrication and conformity. Moreover, the micro strip patch antennas can provide dual and circular polarizations, dual-frequency operation, frequency agility, broad band-width, feed line flexibility, beam scanning omnidirectional patterning. In this paper we discuss the microstrip antenna, types of microstrip antenna, feeding techniques and application of microstrip patch antenna with their advantage and disadvantages over conventional microwave antennas. In this paper we will try to find the changes in the output of the Microstrip antenna when we change the input values. Analyzing rectangular Line-Fed Microstrip antenna using PCAAD 6.0 software.","PeriodicalId":302312,"journal":{"name":"International Journal of Technical Research & Science","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114237186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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