{"title":"BER of Various Modulation Techniques Under Atmospheric Turbulences","authors":"Priyanka Bhardwaj, Aadi Jain, Manveen, Richita Kamal, Rishab Chittlangia","doi":"10.35940/ijeat.e2797.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2797.0610521","url":null,"abstract":"Noise in the communication channel is well\u0000established to be a threat to digital bit transmission, resulting in\u0000many mistakes at the bit level. Different modulation methods are\u0000studied in terms of BER, probability of error and SNR to better\u0000comprehend this. In the presence of specific levels of noise in the\u0000communication channel, this analysis yields an interesting\u0000conclusion that advises the employment of particular modulation\u0000methods. A comprehensive analysis of several modulation\u0000schemes has been considered. Those include On-Off Key\u0000modulation (OOK), Binary Phase Shift Key (BPSK), Quadrature\u0000Phase Shift Key (QPSK), Pulse Amplitude Modulation (PAM) and\u00008-Phase Shift Key (8-PSK). This analysis can aid in the selection\u0000of a modulation approach based on the channel condition.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85202363","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}
{"title":"Semantic Segmentation of Satellite Images using Deep Learning","authors":"Chandra Pal Kushwah, Kuruna Markam","doi":"10.35940/ijitee.h9186.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9186.0610821","url":null,"abstract":"Bidirectional in recent years, Deep learning performance in natural scene image processing has improved its use in remote sensing image analysis. In this paper, we used the semantic segmentation of remote sensing images for deep neural networks (DNN). To make it ideal for multi-target semantic segmentation of remote sensing image systems, we boost the Seg Net encoder-decoder CNN structures with index pooling & U-net. The findings reveal that the segmentation of various objects has its benefits and drawbacks for both models. Furthermore, we provide an integrated algorithm that incorporates two models. The test results indicate that the integrated algorithm proposed will take advantage of all multi-target segmentation models and obtain improved segmentation relative to two models.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88696291","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}
{"title":"Virtual Sketch using Open CV","authors":"Pranavi Srungavarapu, Eswar Pavan Maganti, Srilekkha Sakhamuri, Sai Pavan Kalyan Veerada, Anuradha Chinta","doi":"10.35940/ijitee.h9262.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9262.0610821","url":null,"abstract":"Virtual Sketch is in where we can draw by just capturing the motion of a colored marker with a camera. One colored object at the tip of the finger is mainly used as the marker. We are here now, using the techniques of computer vision in open cv to build this project. The required language for this project is python due to its more exhaustive libraries and easy to make use of the syntax and but understanding the basics as well as it can be implemented in any open cv supported languages The colour tracking and detection processes are used to achieve the goal of this project. The color marker here used is detected and mask is produced. The next steps of morphological operations on the mask produced those are Erosion and Dilation. Erosion makes the impurities present in the mask to get reduced and Dilation further regains the eroded main mask.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72641044","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}
{"title":"Transformer Less Self-Commutated PV Inverter","authors":"P. Maithili, J. Kanakaraj","doi":"10.35940/ijitee.g9037.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.g9037.0610821","url":null,"abstract":"The power demand is increased day by day and\u0000generation of electrical energy from non-renewable sources are\u0000not able to meet the demand. An alternate energy sources are the\u0000only solution to meet the power demand. The power generation\u0000from solar energy with photovoltaic effect is plays a major role.\u0000This Solar PV system has low efficiency. The power\u0000semiconductor devices and converter circuit along with inductive /\u0000magnetic circuit. The Inverter circuit have an influence on\u0000photovoltaic power generation to improve the level of output\u0000voltage along with efficiency. In this paper a new transformer less\u0000DC-AC converter is proposed, and it has high efficiency, requires\u0000less cost when compares with conventional inverter with\u0000transformer. Transformer less self-commutated photovoltaic\u0000inverter is reflected the advantages of central and string inverters.\u0000It gives high output power and low-cost converter. These\u0000transformer less DC-AC converter is connect with\u0000Boost/Buck-Boost converter for the better output. So, this\u0000proposed DC-AC converter topology is not required mechanical\u0000switching and it is lighter in size. The PV technology has low\u0000efficiency and utilize more cost for generation of power. The\u0000proposed transformer less PV inverter is the better choice to\u0000increase the usefulness and reduce the charge rate of this PV\u0000system.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91496978","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}
{"title":"Insurepp-Machine Learning Webapp","authors":"R. Singh, Avnesh Nigam, S. Winster","doi":"10.35940/ijeat.d2506.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.d2506.0610521","url":null,"abstract":"Nowadays, there are many companies which are\u0000collecting money in the name of insurance. For them, insurance\u0000has become a type of business. To reduce this thing, we have\u0000developed INSUREPP which can help in giving less amount and\u0000is very easy to use. You just need to click some pictures and upload\u0000it in the application. It will use various CNN models. It will check\u0000the harm, the seriousness of the harm, the region of the harm and\u0000will predict the results. We are making this project so that it takes\u0000less time in insurance claiming, as it can predict the cost of\u0000damage.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76347870","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}
{"title":"A Novel Approach of Image Fusion Techniques using Ant Colony Optimization","authors":"J. Kulkarni, R. Bichkar","doi":"10.35940/ijitee.h9241.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9241.0610821","url":null,"abstract":"Ant Colony Optimization (ACO) is a relatively high approach for finding a relatively strong solution to the problem of optimization. The ACO based image fusion technique is proposed. The objective function and distance matrix is designed for image fusion. ACO is used to fuse input images at the feature-level by learning the fusion parameters. It is used to select the fusion parameters according to the user-defined cost functions. This algorithm transforms the results into the initial pheromone distribution and seeks the optimal solution by using the features. As to relevant parameters for the ACO, three parameters (α, β, ρ ) have the greatest impact on convergence. If the values of α, β are appropriately increased, convergence can speed up. But if the gap between these two is too large, the precision of convergence will be negatively affected. Since the ACO is a random search algorithm, its computation speed is relatively slow.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"109 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83517024","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}
{"title":"Pothole Dection Syatem in Vehicle","authors":"K K Sabarikanth","doi":"10.35940/ijitee.h9249.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9249.0610821","url":null,"abstract":"In India major road accident is based on potholes. To identify this potholes and humps in roads may reduces the road accident and also reduces the damages in cars and bike. To identify the holes and humps or speed breakers, the ultra sonic sensor, display board and buzzer also used in it. Project is mainly used in the prototype model of the vehicle which has the capable to find holes and humps in the road. When the vehicle identify the holes and hump it started showing the distance of obstacles, once the distance of obstacles reduced to 10m range the buzzer gives the alarm signals to drives that obstacles is near to vehicle so that they can reduces the speed of the vehicle and go slow through the obstacles or they can change the path. The display board given near the dash board that drivers can easily view the board and buzzer is given inside the vehicles and ultrasonic sensors given in the front of the bumper so it act efficiently. Here the arduino board is used for the power supply and programs, so this project reduces the accident occurs in the road due to holes and humps.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86799529","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}
{"title":"Vehicular Security: Drowsy Driver Detection System","authors":"Pranavi Pendyala, Aviva Munshi, Anoushka Mehra","doi":"10.35940/ijeat.e2751.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2751.0610521","url":null,"abstract":"Detecting the driver's drowsiness in a consistent\u0000and confident manner is a difficult job because it necessitates\u0000careful observation of facial behaviour such as eye-closure,\u0000blinking, and yawning. It's much more difficult to deal with when\u0000they're wearing sunglasses or a scarf, as seen in the data\u0000collection for this competition. A drowsy person makes a variety\u0000of facial gestures, such as quick and repetitive blinking, shaking\u0000their heads, and yawning often. Drivers' drowsiness levels are\u0000commonly determined by assessing their abnormal behaviours\u0000using computerised, nonintrusive behavioural approaches. Using\u0000computer vision techniques to track a driver's sleepiness in a\u0000non-invasive manner. The aim of this paper is to calculate the\u0000current behaviour of the driver's eyes, which is visualised by the\u0000camera, so that we can check the driver's drowsiness. We present a\u0000drowsiness detection framework that uses Python, OpenCV, and\u0000Keras to notify the driver when he feels sleepy. We will use\u0000OpenCV to gather images from a webcam and feed them into a\u0000Deep Learning model that will classify whether the person's eyes\u0000are \"Open\" or \"Closed\" in this article.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89956751","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}
{"title":"Implementation of Digital Signage for Smart Facility System using IoT","authors":"Byeongtae Ahn","doi":"10.35940/ijitee.h9255.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9255.0610821","url":null,"abstract":"Recently, as wireless communication and smart phone spread and technology develop, there is an increasing demand for a system capable of real-time communication and business processing using online information anytime, anywhere in the offline field. In particular, changes in digital signage technology are developing in various ways due to the development of advanced convergence technologies. With the development of convergence technologies, digital signage has been constructed to provide information through a structured structure between each component in order to develop in a form that can deliver information in response to environmental changes rather than user input. This paper developed a system that outputs and services various contents together with industrial facility inspection and management by using wireless communication Bluetooth in a display device equipped with an operating system. This system is an Internet-of-Things-based system that simultaneously outputs various contents and a business management function that enables facility inspection.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90871080","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}
{"title":"Multi Objective Optimization of Machining Parameters in End Milling of AISI1020","authors":"Jignesh G. Parmar, K. Dave","doi":"10.35940/ijitee.h9225.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9225.0610821","url":null,"abstract":"In current research, artificial neural network (ANN) and Multi objective genetic algorithm (MOGA) have been used for the prediction and multi objective optimization of the end milling operation. Cutting speed, feed rate, depth of cut, material density and hardness have been considered as input variables. The predicted values and optimized results obtained through ANN and MOGA are compared with experimental results. A good correlation has been established between the ANN predicted values and experimental results with an average accuracy of 91.983% for material removal rate, 99.894% for tool life, 92.683% for machining time, 92.671% for tangential cutting force, 92.109% for power and 90.311% for torque. The MOGA approach has been proposed to obtain the cutting condition for optimization of each responses. The MOGA gives average accuracy of 96.801% for MRR, 99.653% for tool life, 86.833% for machining time, 93.74% for cutting force, 93.74% for power and 99.473% for torque. It concludes that ANN and MOGA are efficiently and effectively used for prediction and multi objective optimization of end milling operation for any selected materials before the experimental. Implementation of these techniques in industries before the experimentation is useful to reduce the lead time, experimental cost and power consumption also increase the productivity of the product.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"43 31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79645278","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}