Pub Date : 2021-06-30DOI: 10.35940/ijitee.h9241.0610821
J. Kulkarni, R. Bichkar
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.
{"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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2751.0610521
Pranavi Pendyala, Aviva Munshi, Anoushka Mehra
Detecting the driver's drowsiness in a consistent and confident manner is a difficult job because it necessitates careful observation of facial behaviour such as eye-closure, blinking, and yawning. It's much more difficult to deal with when they're wearing sunglasses or a scarf, as seen in the data collection for this competition. A drowsy person makes a variety of facial gestures, such as quick and repetitive blinking, shaking their heads, and yawning often. Drivers' drowsiness levels are commonly determined by assessing their abnormal behaviours using computerised, nonintrusive behavioural approaches. Using computer vision techniques to track a driver's sleepiness in a non-invasive manner. The aim of this paper is to calculate the current behaviour of the driver's eyes, which is visualised by the camera, so that we can check the driver's drowsiness. We present a drowsiness detection framework that uses Python, OpenCV, and Keras to notify the driver when he feels sleepy. We will use OpenCV to gather images from a webcam and feed them into a Deep Learning model that will classify whether the person's eyes are "Open" or "Closed" in this article.
{"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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2609.0610521
Hemu Farooq, Anuj Jain, V. K. Sharma
Sleep is utterly regarded as compulsory component for a person’s prosperity and is an exceedingly important element for wellbeing of a healthy person. It is a condition in which an individual is physically and mentally at rest. The conception of sleep is considered extremely peculiar and is a topic of discussion and researchers all over the world has been attracted by this concept. Sleep analysis and its stages is analyzed to be useful in sleep research and sleep medicine area. By properly analyzing the sleep scoring system and its different stages has proven helpful for diagnosing sleep disorders. As it’s seen, sleep stage classification by manual process is a hectic procedure as it takes sufficient time for sleep experts to perform data analysis. Besides, mistakes and irregularities in between classification of same data can be recurrent. Therefore, the use of automatic scoring system in order to support reliable classification is highly in greater use. The scheduled work provides an insight to use the automatic scheme which is based on real time EMG signals and Artificial neural network. EMG is an electro neurological diagnostic tool which evaluates and records the electrical activity generated by muscle cells. The sleep scoring analysis can be applied by recording Electroencephalogram (EEG), Electromyogram (EMG), and Electrooculogram (EOG) based on epoch and this method is termed as PSG test or polysomnography test. The epoch measured has length segments for a period of 30 seconds. The standard database of EMG records was gathered from various hospitals in sleep laboratory which gives the different stages of sleep. These are Waking, Non-REM1 (stage-1), NonREM2 (stage-2), Non-REM3 (stage-3), REM. The collection of data was done for the period of 30 second known as epoch, for seven hours. The dataset obtained from the biological signal was managed so that necessary data is to be extracted from degenerated signal utilized for the purpose of study. As a matter of fact, it is known electrical signals are distributed throughout the body and is needed to be removed. These unwanted signals are termed as artifacts and they are removed with the help of filters. In this proposed work, the signal is filtered by making use of low-pass filter called Butterworth. The withdrawn characteristics were instructed and categorized by utilizing Artificial Neural Network (ANN). ANN, on the other hand is highly complicated network and utilizing same in the field of biomedical when contracted with electrical signals, acquired from human body is itself a novel. The precision obtained by the help of the procedure was discovered to be satisfactory and hence the process is very useful in clinics of sleep, especially helpful for neuro-scientists for discovering the disturbance in sleep.
{"title":"A Proposal for Sleep Scoring Analysis Designed by Computer Assisted using Physiological Signals","authors":"Hemu Farooq, Anuj Jain, V. K. Sharma","doi":"10.35940/ijeat.e2609.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2609.0610521","url":null,"abstract":"Sleep is utterly regarded as compulsory component\u0000for a person’s prosperity and is an exceedingly important element\u0000for wellbeing of a healthy person. It is a condition in which an\u0000individual is physically and mentally at rest. The conception of\u0000sleep is considered extremely peculiar and is a topic of discussion\u0000and researchers all over the world has been attracted by this\u0000concept. Sleep analysis and its stages is analyzed to be useful in\u0000sleep research and sleep medicine area. By properly analyzing\u0000the sleep scoring system and its different stages has proven\u0000helpful for diagnosing sleep disorders. As it’s seen, sleep stage\u0000classification by manual process is a hectic procedure as it takes\u0000sufficient time for sleep experts to perform data analysis. Besides,\u0000mistakes and irregularities in between classification of same data\u0000can be recurrent. Therefore, the use of automatic scoring system\u0000in order to support reliable classification is highly in greater use.\u0000The scheduled work provides an insight to use the automatic\u0000scheme which is based on real time EMG signals and Artificial\u0000neural network. EMG is an electro neurological diagnostic tool\u0000which evaluates and records the electrical activity generated by\u0000muscle cells. The sleep scoring analysis can be applied by\u0000recording Electroencephalogram (EEG), Electromyogram\u0000(EMG), and Electrooculogram (EOG) based on epoch and this\u0000method is termed as PSG test or polysomnography test. The\u0000epoch measured has length segments for a period of 30 seconds.\u0000The standard database of EMG records was gathered from\u0000various hospitals in sleep laboratory which gives the different\u0000stages of sleep. These are Waking, Non-REM1 (stage-1), NonREM2 (stage-2), Non-REM3 (stage-3), REM. The collection of\u0000data was done for the period of 30 second known as epoch, for\u0000seven hours. The dataset obtained from the biological signal was\u0000managed so that necessary data is to be extracted from\u0000degenerated signal utilized for the purpose of study. As a matter\u0000of fact, it is known electrical signals are distributed throughout\u0000the body and is needed to be removed. These unwanted signals\u0000are termed as artifacts and they are removed with the help of\u0000filters. In this proposed work, the signal is filtered by making use\u0000of low-pass filter called Butterworth. The withdrawn\u0000characteristics were instructed and categorized by utilizing\u0000Artificial Neural Network (ANN). ANN, on the other hand is\u0000highly complicated network and utilizing same in the field of\u0000biomedical when contracted with electrical signals, acquired\u0000from human body is itself a novel. The precision obtained by the\u0000help of the procedure was discovered to be satisfactory and hence\u0000the process is very useful in clinics of sleep, especially helpful for\u0000neuro-scientists for discovering the disturbance in sleep.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74904029","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}
The main aim of this project is to understand and apply the separate approach to classify fraudulent transactions in a database using the Isolation forest algorithm and LOF algorithm instead of the generic Random Forest approach. The model will be able to identify transactions with greater accuracy and we will work towards a more optimal solution by comparing both approaches. The problem of detecting credit card fraud involves modelling past credit card purchases with the perception of those that turned out to be fraud. Then, this model is used to determine whether or not a new transaction is fraudulent. The objective of the project here is to identify 100% of the fraudulent transactions while mitigating the incorrect classifications offraud.
{"title":"Anomaly Detection Algorithms in Financial Data","authors":"Abhisu Jain, Mayank Arora, Anoushka Mehra, Aviva Munshi","doi":"10.35940/ijeat.e2598.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2598.0610521","url":null,"abstract":"The main aim of this project is to understand and apply\u0000the separate approach to classify fraudulent transactions in a\u0000database using the Isolation forest algorithm and LOF algorithm\u0000instead of the generic Random Forest approach. The model will be\u0000able to identify transactions with greater accuracy and we will\u0000work towards a more optimal solution by comparing both\u0000approaches. The problem of detecting credit card fraud involves\u0000modelling past credit card purchases with the perception of those\u0000that turned out to be fraud. Then, this model is used to determine\u0000whether or not a new transaction is fraudulent. The objective of\u0000the project here is to identify 100% of the fraudulent transactions\u0000while mitigating the incorrect classifications offraud.","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":"75856285","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 : 2021-06-30DOI: 10.35940/ijeat.d2497.0610521
S. Santhanam, Thiruvalar Selvan Palavesam
In this proposal new trapezoidal patch microstrip feed antenna array with ground defected by square shape is designed for detailed antenna parameter study in terms of return loss, VSWR, gain and radiation pattern for S band applications from 2 to 3 GHz. The bandwidth and radiation properties of four radiating element arranged in 2 x 2 array has been improved by defecting half of the ground by etching square shape opposite to the vertical feed point. 30 x 70 x 1.6 mm dimension structure has been fabricated in FR4 substrate for low cost applications and performance analyzed in three different planes. With comparison of four element array with full ground, the proposed array with defected ground has proved the improvement in behavior with return loss of -34.687 dB and ideally fit with VSWR of 1.038. Parametric study with feed length and substrate thickness has also been performed optimized decision of structure dimension. This study reveals that by reducing the substrate thickness and increasing the feed length, we can improve the performance of loss reduction. The front view has been simulated with full ground and defected ground for comparison and the compared results shows that the loss reduction of -22 dB has been achieved with VSWR value of 1.03 from 2.28 for defected ground structure. The designed structure has been simulated with CST software and the comparison of simulated results has conform that the proposed structure can be used for S band application like airport surveillance radars with wide bandwidth of 120 MHz and gain of 3.52 dBi. Comparison has been made between the proposed antenna array and the antennas available in literature with respect to bandwidth gain, reflection coefficient and defection type for better understanding.
本文设计了一种具有方形接地缺陷的梯形贴片微带馈电天线阵列，对2 ~ 3ghz S波段应用时的回波损耗、驻波比、增益和辐射方向图进行了详细的天线参数研究。通过在垂直馈电点的对面蚀刻方形来破坏一半的地面，提高了布置在2 × 2阵列中的四辐射元件的带宽和辐射性能。在FR4衬底上制造了30 x 70 x 1.6 mm尺寸的结构，用于低成本应用，并在三个不同的平面上分析了性能。通过与全接地的四元阵列进行比较，结果表明，有缺陷接地的四元阵列性能得到改善，回波损耗为-34.687 dB，与1.038的驻波比吻合较好。并对进给长度和衬底厚度进行了参数化研究，优化了结构尺寸的确定。研究表明，通过减小衬底厚度和增加进给长度，可以提高减损性能。对全接地和缺陷接地的前视图进行了仿真比较，结果表明，缺陷接地结构的驻波比从2.28降至1.03，损耗降低了-22 dB。利用CST软件对所设计的结构进行了仿真，仿真结果对比表明，所设计的结构可用于带宽为120 MHz、增益为3.52 dBi的机场监视雷达等S波段应用。为了更好地理解，将所提出的天线阵列与文献中现有的天线在带宽增益、反射系数和缺陷类型方面进行了比较。
{"title":"Microstrip Feed Trapezoidal Shape Antenna Array with Defected Ground Structure for S\u0000Band Applications","authors":"S. Santhanam, Thiruvalar Selvan Palavesam","doi":"10.35940/ijeat.d2497.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.d2497.0610521","url":null,"abstract":"In this proposal new trapezoidal patch microstrip feed\u0000antenna array with ground defected by square shape is designed\u0000for detailed antenna parameter study in terms of return loss,\u0000VSWR, gain and radiation pattern for S band applications from 2\u0000to 3 GHz. The bandwidth and radiation properties of four\u0000radiating element arranged in 2 x 2 array has been improved by\u0000defecting half of the ground by etching square shape opposite to\u0000the vertical feed point. 30 x 70 x 1.6 mm dimension structure has\u0000been fabricated in FR4 substrate for low cost applications and\u0000performance analyzed in three different planes. With comparison\u0000of four element array with full ground, the proposed array with\u0000defected ground has proved the improvement in behavior with\u0000return loss of -34.687 dB and ideally fit with VSWR of 1.038.\u0000Parametric study with feed length and substrate thickness has also\u0000been performed optimized decision of structure dimension. This\u0000study reveals that by reducing the substrate thickness and\u0000increasing the feed length, we can improve the performance of\u0000loss reduction. The front view has been simulated with full ground\u0000and defected ground for comparison and the compared results\u0000shows that the loss reduction of -22 dB has been achieved with\u0000VSWR value of 1.03 from 2.28 for defected ground structure. The\u0000designed structure has been simulated with CST software and the\u0000comparison of simulated results has conform that the proposed\u0000structure can be used for S band application like airport\u0000surveillance radars with wide bandwidth of 120 MHz and gain of\u00003.52 dBi. Comparison has been made between the proposed\u0000antenna array and the antennas available in literature with\u0000respect to bandwidth gain, reflection coefficient and defection type\u0000for better understanding.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82452953","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 : 2021-06-30DOI: 10.35940/ijeat.d2537.0610521
P. Shankar, M. K. Reddy
The primary object of this paper is to compare the traditional time series models with deep learning algorithm. The ARIMA model is developed to forecast Indian Gold prices using daily data for the period 2016 to 2020 obtained from World Gold Council. We fitted the ARIMA (2,1,2) model which exhibited the least AIC values. In the meanwhile, MLP, CNN and LSTM models are also examined to forecast the gold prices in India. Mean absolute error, mean absolute percentage error and root mean squared errors used to evaluate the forecasting performance of the models. Hence, LSTM model superior than that of the other three models for forecasting the gold prices in India.
{"title":"Forecasting Gold Prices in India using Time series and Deep Learning Algorithms","authors":"P. Shankar, M. K. Reddy","doi":"10.35940/ijeat.d2537.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.d2537.0610521","url":null,"abstract":"The primary object of this paper is to compare the\u0000traditional time series models with deep learning algorithm. The\u0000ARIMA model is developed to forecast Indian Gold prices using\u0000daily data for the period 2016 to 2020 obtained from World Gold\u0000Council. We fitted the ARIMA (2,1,2) model which exhibited the\u0000least AIC values. In the meanwhile, MLP, CNN and LSTM\u0000models are also examined to forecast the gold prices in India.\u0000Mean absolute error, mean absolute percentage error and root\u0000mean squared errors used to evaluate the forecasting\u0000performance of the models. Hence, LSTM model superior than\u0000that of the other three models for forecasting the gold prices in\u0000India.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86870175","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 : 2021-06-30DOI: 10.35940/ijeat.e2694.0610521
Daksh Gupta, Aashay Markale, Rishabh Kulkarni
The definition of mental disorders describes them as “health conditions involving changes in emotion, thinking or behavior or a combination of these”. Contemporary societies of 2020 still fall short in recognizing some of the most common afflictions as actual problems in people. Some of those are depression, anxiety and stress disorders. This paper proposes a Machine Learning based approach wherein the analysis of the multiple-choice inputs along with a neatly curated questionnaire based on feature extraction will be done and then supervised classification algorithms will be used to generate a mental health score as well as a detailed report based on responses the user gives.
{"title":"Mental Health Quantifier","authors":"Daksh Gupta, Aashay Markale, Rishabh Kulkarni","doi":"10.35940/ijeat.e2694.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2694.0610521","url":null,"abstract":"The definition of mental disorders describes them as\u0000“health conditions involving changes in emotion, thinking or\u0000behavior or a combination of these”. Contemporary societies of\u00002020 still fall short in recognizing some of the most common\u0000afflictions as actual problems in people. Some of those are\u0000depression, anxiety and stress disorders. This paper proposes a\u0000Machine Learning based approach wherein the analysis of the\u0000multiple-choice inputs along with a neatly curated questionnaire\u0000based on feature extraction will be done and then supervised\u0000classification algorithms will be used to generate a mental health\u0000score as well as a detailed report based on responses the user gives.","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":"86916698","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 : 2021-06-30DOI: 10.35940/ijitee.e8672.0610821
Karan Singhai, A. Prof
India has been facing many disasters since long. Among the entire disasters earthquake is of serious concern to Civil Engineers. Because of collapse of structures subjected to seismic loads many lives were lost because these buildings were not designed for seismic loads. The problem becomes more serious when additional storeys are constructed. In these buildings many of the columns are not safe if the building is analyzed for seismic load. To make the building safe we need to adopt the technique of FRP (Fiber Reinforced Polymer) jacketing. The FRP Jacketing is comparatively better than other retrofitting because no major strengthening of foundation is required in this technique, also original function of the building can be maintained without any major change in the original geometry of the building. The present study is on a four storey building that has been planned in STAAD.ProV8i, considering M30 cement and Fe415 steel bars.
{"title":"Seismic Strengthening of Existing RCC Structure by FRP Jacketing","authors":"Karan Singhai, A. Prof","doi":"10.35940/ijitee.e8672.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.e8672.0610821","url":null,"abstract":"India has been facing many disasters since long.\u0000Among the entire disasters earthquake is of serious concern to\u0000Civil Engineers. Because of collapse of structures subjected to\u0000seismic loads many lives were lost because these buildings were\u0000not designed for seismic loads. The problem becomes more\u0000serious when additional storeys are constructed. In these\u0000buildings many of the columns are not safe if the building is\u0000analyzed for seismic load. To make the building safe we need to\u0000adopt the technique of FRP (Fiber Reinforced Polymer)\u0000jacketing. The FRP Jacketing is comparatively better than other\u0000retrofitting because no major strengthening of foundation is\u0000required in this technique, also original function of the building\u0000can be maintained without any major change in the original\u0000geometry of the building. The present study is on a four storey\u0000building that has been planned in STAAD.ProV8i, considering\u0000M30 cement and Fe415 steel bars.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90192363","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 : 2021-06-30DOI: 10.35940/ijeat.e2552.0610521
Sathish Kumar Ravichandran, A. Sasi, Shaik Hussain Shaik Ibrahim
Forest Optimization Algorithm (FOA), a recent evolutionary algorithm suitable for continuous nonlinear optimization problems. It is inspired by a few trees in the forest that can last for several decades while other trees can only live for a short time. In FOA, the tree seeding technique is simulated so that certain seeds fall directly under the leaves, while others are dispersed over a large area by natural processes and animals that feed on the seeds or fruits. In this paper, we used the sphere mathematical function to implement FOA as a step-by-step process, and the iteration-based results are displayed. The findings of the experiments demonstrated that FOA performed well in certain data sets from the UCI repository..
{"title":"Forest Optimization Algorithm Implementation using Sphere Mathematical Function","authors":"Sathish Kumar Ravichandran, A. Sasi, Shaik Hussain Shaik Ibrahim","doi":"10.35940/ijeat.e2552.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2552.0610521","url":null,"abstract":"Forest Optimization Algorithm (FOA), a recent\u0000evolutionary algorithm suitable for continuous nonlinear\u0000optimization problems. It is inspired by a few trees in the forest\u0000that can last for several decades while other trees can only live for\u0000a short time. In FOA, the tree seeding technique is simulated so\u0000that certain seeds fall directly under the leaves, while others are\u0000dispersed over a large area by natural processes and animals that\u0000feed on the seeds or fruits. In this paper, we used the sphere\u0000mathematical function to implement FOA as a step-by-step\u0000process, and the iteration-based results are displayed. The\u0000findings of the experiments demonstrated that FOA performed\u0000well in certain data sets from the UCI repository..","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"111 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87603262","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 : 2021-06-30DOI: 10.35940/ijeat.d2535.0610521
A. Elsonbaty
Technologies are rapidly evolving, allowing people to live healthier and simpler lives. Sightless people are unable to carry out their everyday activities, such as walking down the street, visiting friends or relatives, or doing some other mundane tasks. As a result, the smart stick is a stick that can assist a person in walking safely without fear of colliding with another person or solid objects is proposed as a solution to this major issue. It is a development of the traditional blind stick as it acts as a companion for the blind when walking by sending audio alerts to the blind via a headphone connected to the phone with obstacles (water/walls/stairs / muddy ground) and also enables him to make a phone call to ask for help. EasyEda software was used for designing and simulating electrical circuits, was used to model the electric circuit. This system functions similarly to a white cane in that it assists blind people in scanning their surroundings for obstacles or orientation marks. This system will be mounted on a white cane with an ultrasonic sensor, and a water sensor to detect changes in the environment. Ultrasonic sensors detect obstacles in front of it using ultrasonic wave reflection, water detection sensors detect whether there is a puddle.
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