International Journal of Innovative Technology and Exploring Engineering - Regular Issue
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Published By Blue Eyes Intelligence Engineering And Sciences Engineering And Sciences Publication - BEIESP

2278-3075
Updated Saturday, 27 November 2021

Author(s):  
Abishek R ◽  
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Dr. D. Vaishali ◽  
Adhitya Narayan R ◽  
Vignesh Sundar M ◽  
...  

IoT has become an integrated part of our lives changing ways in which we operate our everyday appliances. In addition to making our home appliances smart, it has become a common trend for companies to adopt industry 4.0, which uses various sensors to monitor the equipment, machinery, and the work environment. We often come across multiple brands which make smart appliances but each brand comes with its separate mobile application for the appliance's operation. This requires us to switch between Apps to control these appliances if we at all remember which App controls which appliance. We intend to solve these two major inconveniences by creating a single mobile application that can control all these appliances using Augmented Reality technology. All we have to do is point our camera at the appliance that we need to operate and the App will display control options in real-time AR. This paper produces five important contributions: 1) An AR-based mobile application to control IoT devices and monitor the environment. 2) Implementing the mobile application using Unity 3D engine and Vuforia SDK. 3) Integrating a commercially available IoT device with the mobile application. 4) Integrating custom-made hardware IoT device with mobile application. 5) Integrating this combination to make our industries and homes smarter Keywords:


Author(s):  
Maria Mohammad Yousef ◽  

Generally, medical dataset classification has become one of the biggest problems in data mining research. Every database has a given number of features but it is observed that some of these features can be redundant and can be harmful as well as disrupt the process of classification and this problem is known as a high dimensionality problem. Dimensionality reduction in data preprocessing is critical for increasing the performance of machine learning algorithms. Besides the contribution of feature subset selection in dimensionality reduction gives a significant improvement in classification accuracy. In this paper, we proposed a new hybrid feature selection approach based on (GA assisted by KNN) to deal with issues of high dimensionality in biomedical data classification. The proposed method first applies the combination between GA and KNN for feature selection to find the optimal subset of features where the classification accuracy of the k-Nearest Neighbor (kNN) method is used as the fitness function for GA. After selecting the best-suggested subset of features, Support Vector Machine (SVM) are used as the classifiers. The proposed method experiments on five medical datasets of the UCI Machine Learning Repository. It is noted that the suggested technique performs admirably on these databases, achieving higher classification accuracy while using fewer features.


Author(s):  
Monika Rybczak ◽  
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Dawid Trzcińśki ◽  
Natalia Wenta ◽  
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...  

The article contains an overview of articles related to the description of control process visualization. It provides short information on how to visualize the production line based on two programming environments: Factory IO and Inventor together with Matlab/Simulink. The analysis of these two environments concerns control of a virtual 3D object from a real PLC. Both virtual production line projects are based on control from the S7-1214 DC/DC/DC controller. Currently, there is a need to validate the program code or control process which has been done using several commercially available programs.


Author(s):  
Sandhya Vidyashankar ◽  
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Rakshit Vahi ◽  
Yash Karkhanis ◽  
Gowri Srinivasa ◽  
...  

We present an automated, visual question answering based companion – VisQuelle - to facilitate elementary learning of word-object associations. In particular, we attempt to harness the power of machine learning models for object recognition and the understanding of combined processing of images and text data from visual-question answering to provide variety and nuance in the images associated with letters or words presented to the elementary learner. We incorporate elements such as gamification to motivate the learner by recording scores, errors, etc., to track the learner’s progress. Translation is also provided to reinforce word-object associations in the user’s native tongue, if the learner is using VisQuelle to learn a second language.


Author(s):  
Dr. P. Mari Selvam ◽  
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Dr. A. Gomathi ◽  

The corona virus which causes a highly infectious of Corona virus disease (COVID-19) that has affected more than 4 lakh people in around the world. Since it has been increased during the pandemic period online shopping usage, rural, urban and globally. In the current scenario many youngster’s changing the attitude has purchased to online shopping because social distancing and self-quarantine efforts. Hence the online shopping promoters like Amazon, flip kart, Reliance digital and other agencies are for the time being too given the importance its available fulfilment and logistics facility to serve the basic needs such as household products, packaged food, health care, hygiene, personal safety and other high priority products. It is for the time being going to taking orders for lower-priority to high priority products. In this study to analyze the impact of online buying behaviour increased in after pandemic period.


Author(s):  
Dr. R. Kiran Kumar ◽  
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K. Arunabhaskar ◽  
Dr. CH. Mani Mala ◽  
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...  

Automatic evaluation of retinal vessels acts a significant part in diagnosis of several ocular and systemic diseases. Eye diseases must be diagnosed early to avoid severe infection and vision loss. The method of segmentation and classification of the retinal blood vessel identification is most difficult tasks in computerized fundus imaging now a days. To solve this problem in this paper, to locate retinal vessel in the retinal vessel, Adaptive Regularized Kernel Based Fuzzy Clustering Means (ARKFCM) algorithm-based segmentation is used. For retinal vessel prediction purpose in this paper a PIGEON optimization-based learning rate modified Generative Adversarial Networks (GAN) algorithm is introduced. Additionally, to improve the proposed classification performance input image is transformed with the aid of Discrete Wavelet Transform (DWT). The DWT applied Low Low (LL) image and segmented images are cascaded. The cascade images are used for training and testing. The proposed system has validated with the help of DRIVE and STARE publically available datasets. They are studied by applying a Convolutional Neural Network, an instantly trained neural network for predicting retinal vessel. In the end, the system is checked for system efficiency using the results of modeling based on MATLAB. The scheme guarantees an accuracy of 92.77% on DRIVE dataset and 98.85% on STARE dataset with a minimum average classification error of 2.57%. Further, we recommended to physician for implement the real time clinical application; this scheme is highly beneficial for doctors for identifying retinal blood vessels.


Author(s):  
Ahmed Hashem El Fiky ◽  

The COVID-19 will take place for the first time in December 2019 in Wuhan, China. After that, the virus spread all over the world, with over 4.7 million confirmed cases and over 315000 deaths as of the time of writing this report. Radiologists can employ machine learning algorithms developed on radiography pictures as a decision support mechanism to help them speed up the diagnostic process. The goal of this study is to conduct a quantitative evaluation of six off-the-shelf convolutional neural networks (CNNs) for COVID-19 X-ray image analysis. Due to the limited amount of images available for analysis, the CNN transfer learning approach was used. We also developed a simple CNN architecture with a modest number of parameters that does a good job of differentiating COVID-19 from regular X-rays. in this paper, we are used large dataset which contained CXR images of normal patients and patients with COVID-19. the number of CXR images for normal patients are 10,192 image and the number of CXR images for COVID-19 patients are 3,616 images. The results of experiments show the effectiveness and robustness of Deep-COVID-19 and pretrained models like VGG16, VGG19, and MobileNets. Our proposed Model Deep-COVID-19 achieved over 94.5% accuracy.


Author(s):  
Abdullah Lala ◽  
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Toshif Patel ◽  
Ravi Karkar ◽  
Dr. Jigar Sevalia ◽  
...  

In modern construction, there is a trend to go deeper below the grade level in terms of basements which can be utilized for parking, shopping malls or a combination of both. In such cases, dynamic soil properties have a significant effect of activating dynamic soil structure interaction phenomenon during earthquake. Here in present study an effort is made to study the behavior of a building by varying five and three number of basements considering dynamic soil structure interaction. Issues like influence zone to be considered for dynamic soil structure interaction, behavior of building with basements under different water level conditions for two different types of layered soil and their comparison with fixed based structure for a real-life structure is dealt with. It is observed that dynamic soil structure interaction can significantly change the behavior and also the failure pattern of the building and hence it is recommended to perform dynamic soil structure interaction for building with multiple basements.


Author(s):  
Muppla Jagadeesh ◽  
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Mr.P Ajay Kumar Reddy ◽  
Dr.S.Nanda Kishor ◽  
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...  

Resolving the problems of individuals with Visual, Hearing, and Vocal Impairment through a solitary serving framework could be a tough task. Various current investigations focus on the resolution of the problems of 1 of them on top of challenges however not all. The work centers around chase down a noteworthy procedure that guides the externally weakened by permitting them to listen to what's self-addressed as text and it's accomplished by the tactic that catches the image through a camera and converts the content accessible as voice signals. This planned framework provides a path to people with Hearing weakening to image scan that is in morphology by discourse to message modification procedure and that we, in addition, provides a route to the vocally disabled to handle their voice by the guide of text to voice transformation strategy. each one of those 3 arrangements was regulated to be in an exceedingly solitary exceptional framework. each one of those exercises consists of the employment of Raspberry Pi. The outwardly barred individual's unit of measurement is helped by the cycle whereby the image to text and text to discourse is given by the Tesseract OCR (online character acknowledgment). The deaf individuals assist with the cycle of associate application that creates them grasp what the individual says is also shown attributable to the message. Vocally hindered individuals can pass on their message by text. Therefore totally different individuals will hear the message in an exceeding speaker.


Author(s):  
Ankita Yadav ◽  
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Mohammad Arif ◽  

This research is conducted in order to deal with the main problem of traffic congestion and road accidents that is basically caused because of the improper parking management. . Hence, it is important that cities have a well-managed parking system. In the past various researches has been done to design a suitable smart paring algorithm. However, each research had their own pros and cons. Our research leads to a smart algorithm that is secure and is convenient enough to develop a system that can be manage the available slots and can notify the users about the available parking slot beforehand to the client. The result analysis clearly shows that the algorithm proposed and designed is more accurate than other algorithms used in the past. The proposed algorithm is designed using ACO, decision tree, and GPS mapping. The idea of working on this research was to provide a solution that is cost effective, helps people on large scale and maintains the laws and order.


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