Pub Date : 2020-12-17DOI: 10.17577/ijertv9is110271
Md. Shahin Azad
Moringa oleifera is a multipurpose tree. The main aim of this study was to use the Moringa oleifera bark with low doses as an adsorbent for the maximum removal of copper (Cu) and cadmium (Cd) from wastewater. There are some vital parameters which influence adsorption process such as contact time, adsorbent dose, initial concentration and pH were investigated. The activated carbon of Moringa oleifera bark with surface area of 439.2309m2/g and pore volume of 0.189245cm3/g was achieved at 700 °C and used (10%) zinc chloride and (0.5M) sulfuric acid as an activating agent to char ratio (5:1). The copper (Cu) was fully eliminated (100%) from aqueous solution within 10 min while cadmium (Cd) also was significantly removed using 0.25gm/L of adsorbents. The Freundlich isotherm, pseudosecond order kinetic equations were well fitted with a correlation coefficient of (0.993 and 1) for copper and (0.953 and 0.999) for cadmium respectively. We observed that at pH 11, adsorbents showed maximum adsorption capacity. Therefore, it can be used as a potential, eco-friendly non-toxic, cost effective application for wastewater treatment. Finally, this works also focused regeneration of adsorbents using solvents for further highest reuse of it. Keywords— Moringa oleifera bark; Activated carbon; Adsorption; Heavy metal; Wastewater treatment
{"title":"Efficiently Removal of Copper and Cadmium from Wastewater using Activated Carbon Produced from Moringa oleifera Bark","authors":"Md. Shahin Azad","doi":"10.17577/ijertv9is110271","DOIUrl":"https://doi.org/10.17577/ijertv9is110271","url":null,"abstract":"Moringa oleifera is a multipurpose tree. The main aim of this study was to use the Moringa oleifera bark with low doses as an adsorbent for the maximum removal of copper (Cu) and cadmium (Cd) from wastewater. There are some vital parameters which influence adsorption process such as contact time, adsorbent dose, initial concentration and pH were investigated. The activated carbon of Moringa oleifera bark with surface area of 439.2309m2/g and pore volume of 0.189245cm3/g was achieved at 700 °C and used (10%) zinc chloride and (0.5M) sulfuric acid as an activating agent to char ratio (5:1). The copper (Cu) was fully eliminated (100%) from aqueous solution within 10 min while cadmium (Cd) also was significantly removed using 0.25gm/L of adsorbents. The Freundlich isotherm, pseudosecond order kinetic equations were well fitted with a correlation coefficient of (0.993 and 1) for copper and (0.953 and 0.999) for cadmium respectively. We observed that at pH 11, adsorbents showed maximum adsorption capacity. Therefore, it can be used as a potential, eco-friendly non-toxic, cost effective application for wastewater treatment. Finally, this works also focused regeneration of adsorbents using solvents for further highest reuse of it. Keywords— Moringa oleifera bark; Activated carbon; Adsorption; Heavy metal; Wastewater treatment","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77149002","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 : 2020-12-09DOI: 10.17577/ijertv9is110225
I. Sadiq, S. Sharma, Rabilu Ado
In this study, we have done regression analysis to get confirmed positive cases of Covid-19 in the peripheral of Indian. We have applied 5% level of significance to get an ideal mathematical model to reach on conclusion about positive cases of COVID-19. We have used two relevant statistical software RStudio and Gretl to find residual plot of the fitted modeled, Actual confirmed cases, Active cases, Recovered cases, Forecasting about Actual fitted deceased cases. This statistical precise calculation may be useful to predict actual data of all above mentioned variables so that doctors and government give them proper treatment.
{"title":"Statistical Analysis of Future Prospective in COVID-19 Cases in India","authors":"I. Sadiq, S. Sharma, Rabilu Ado","doi":"10.17577/ijertv9is110225","DOIUrl":"https://doi.org/10.17577/ijertv9is110225","url":null,"abstract":"In this study, we have done regression analysis to get confirmed positive cases of Covid-19 in the peripheral of Indian. We have applied 5% level of significance to get an ideal mathematical model to reach on conclusion about positive cases of COVID-19. We have used two relevant statistical software RStudio and Gretl to find residual plot of the fitted modeled, Actual confirmed cases, Active cases, Recovered cases, Forecasting about Actual fitted deceased cases. This statistical precise calculation may be useful to predict actual data of all above mentioned variables so that doctors and government give them proper treatment.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77238074","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 : 2020-12-09DOI: 10.17577/ijertv9is110224
I. Sadiq, J. Raghav, Rabilu Ado
Corona virus recently has become a unique universal severe problem required much attention of researcher to come out with optimum solution. The specific intention of this research is to make comparison and test the homogeneity of various averages. Analyses of Variance (ANOVA) by using the R-Studio and tests concern to the effects of weather in corona spread were observed. Over the rapid increased in daily and widespread active reported positive cases of covid-19 in the set of three neighboring state of India were observed. Objective of this paper is to find indication and homogeneity of COVID-19 variations under the specific weather effects with the conclusion at 5% and 1% level of significance.
{"title":"A Statistical Analysis: “Impact of Weather in Homogeneity of Covid-19 Variations In India”","authors":"I. Sadiq, J. Raghav, Rabilu Ado","doi":"10.17577/ijertv9is110224","DOIUrl":"https://doi.org/10.17577/ijertv9is110224","url":null,"abstract":"Corona virus recently has become a unique universal severe problem required much attention of researcher to come out with optimum solution. The specific intention of this research is to make comparison and test the homogeneity of various averages. Analyses of Variance (ANOVA) by using the R-Studio and tests concern to the effects of weather in corona spread were observed. Over the rapid increased in daily and widespread active reported positive cases of covid-19 in the set of three neighboring state of India were observed. Objective of this paper is to find indication and homogeneity of COVID-19 variations under the specific weather effects with the conclusion at 5% and 1% level of significance.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88915627","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 : 2020-12-08DOI: 10.17577/ijertv9is110277
Laura Arce, S. Bayne
Offshore wind energy is a sustainable and innovative energy source. However, its performance is extremely dependent on the local meteorology and oceanographic conditions. There are numerous opportunities as well as challenges to generate energy on a commercial scale in Colombia. This work tries to set up a base for harnessing offshore wind energy, considering the integration into the Colombian grid to offshore wind energy and the cost compared with the current system. The roadmap of the future of offshore wind energy in Colombia must be to fulfill three primary objectives identify the best opportunities for harnessing the offshore wind resource, to improve the investment in resources, and to reduce carbon dioxide emissions. This study provides specific knowledge about opportunities and challenges of offshore wind energy in Barranquilla, Colombia, through both technical and economic aspects. Keywords—Offshore wind energy; techno-economic analysis; wind power density; Weibull distribution; energy storage; Colombia
{"title":"Analysis of Offshore Wind Energy in Colombia: Current Status and Future Opportunities","authors":"Laura Arce, S. Bayne","doi":"10.17577/ijertv9is110277","DOIUrl":"https://doi.org/10.17577/ijertv9is110277","url":null,"abstract":"Offshore wind energy is a sustainable and innovative energy source. However, its performance is extremely dependent on the local meteorology and oceanographic conditions. There are numerous opportunities as well as challenges to generate energy on a commercial scale in Colombia. This work tries to set up a base for harnessing offshore wind energy, considering the integration into the Colombian grid to offshore wind energy and the cost compared with the current system. The roadmap of the future of offshore wind energy in Colombia must be to fulfill three primary objectives identify the best opportunities for harnessing the offshore wind resource, to improve the investment in resources, and to reduce carbon dioxide emissions. This study provides specific knowledge about opportunities and challenges of offshore wind energy in Barranquilla, Colombia, through both technical and economic aspects. Keywords—Offshore wind energy; techno-economic analysis; wind power density; Weibull distribution; energy storage; Colombia","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77185793","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}
J. G. Raurich, Anna Mas Herrador, Queralt Pérez Ruiz
— Dysphagia is a digestive disorder recognized by the World Health Organization (WHO) in the International Classification of Diseases (ICD) characterized by the difficulty in forming or moving the bolus from the mouth to the oesophagus that can cause the passage of food into the respiratory tract. Foods for people with dysphagia are prepared with products that modify viscosity to make them safer when ingested. The aim of this work is to establish the interaction between citric acid, widely used by the food industry, with different thickeners, both first and second range, in order to check whether they fulfil the functions for which they have been designed. The time stability and viscosity as a function of the hydration time of six thickeners and their behavior in the temperature range between 25 and 50 °C were determined. Thickener concentrations up to a maximum of 6% were used in combination with 3acid concentrations (0.5, 1 and 2%). In distilled water, the sedimentation of first range thickeners and the gelification of second range thickeners were checked, as well as the change from non-Newtonian to Newtonian behaviour after the hydrolysis process in both types of thickeners. In the presence of citric acid, the behaviour of both types of thickeners was analogous. Second range thickeners have been found to be much safer than first range thickeners in modifying the viscosity of liquids for people with dysphagia due to the fact that they do not sediment. .
{"title":"Effect of citric acid on thickeners used in products for people suffering oropharyngeal dysphagia","authors":"J. G. Raurich, Anna Mas Herrador, Queralt Pérez Ruiz","doi":"10.5281/ZENODO.4400125","DOIUrl":"https://doi.org/10.5281/ZENODO.4400125","url":null,"abstract":"— Dysphagia is a digestive disorder recognized by the World Health Organization (WHO) in the International Classification of Diseases (ICD) characterized by the difficulty in forming or moving the bolus from the mouth to the oesophagus that can cause the passage of food into the respiratory tract. Foods for people with dysphagia are prepared with products that modify viscosity to make them safer when ingested. The aim of this work is to establish the interaction between citric acid, widely used by the food industry, with different thickeners, both first and second range, in order to check whether they fulfil the functions for which they have been designed. The time stability and viscosity as a function of the hydration time of six thickeners and their behavior in the temperature range between 25 and 50 °C were determined. Thickener concentrations up to a maximum of 6% were used in combination with 3acid concentrations (0.5, 1 and 2%). In distilled water, the sedimentation of first range thickeners and the gelification of second range thickeners were checked, as well as the change from non-Newtonian to Newtonian behaviour after the hydrolysis process in both types of thickeners. In the presence of citric acid, the behaviour of both types of thickeners was analogous. Second range thickeners have been found to be much safer than first range thickeners in modifying the viscosity of liquids for people with dysphagia due to the fact that they do not sediment. .","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"20 1","pages":"14-24"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87202827","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 : 2020-11-30DOI: 10.17577/ijertv9is110211
R. Bhansali, Rahul Kumar
In recent years, usage of deep learning models for medical image classification tasks has grown exponentially due to their state of the art accuracy and efficiency; however, the performance of these models are often limited by insufficient publicly available data. In this study, we continue our previous work in exploring the applications of the Laplace Operator, a detail enhancing image filter, in deep learning models in order to overcome these performance plateaus. Specifically, we evaluate the performance of ResNet-18 in diagnosing COVID-19 from a relatively small dataset of X-ray images. When comparing the performance of our model, dubbed CoronaNeXt, on images without the Laplacian applied to images with the Laplacian applied, we find significant increases in all maximum validation metrics: accuracy improved from 87.6% to 94.8%; F1 score improved from 0.860 to 0.968; specificity improved from 0.865 to 0.944; and sensitivity improved from 0.885 to 0.992. Based on these results, we describe the potential of the Laplacian Operator in drastically improving the performance of deep learning architectures in medical image classification tasks, particularly when utilizing small to medium sized datasets. Notably, sensitivity underwent the most significant improvement, correlating with the results achieved in our previous work using the CT modality. We hope our research will spark further exploration of the Laplace Operator and other derivative-based image preprocessing methodologies in conjunction with powerful deep learning models for medical image tasks. Keywords— COVID-19, Chest X-rays, Laplace Operator, Deep Learning
{"title":"CoronaNeXt Evaluating the Performance of the Laplacian Operator in Diagnosing COVID-19 from Chest X-Rays","authors":"R. Bhansali, Rahul Kumar","doi":"10.17577/ijertv9is110211","DOIUrl":"https://doi.org/10.17577/ijertv9is110211","url":null,"abstract":"In recent years, usage of deep learning models for medical image classification tasks has grown exponentially due to their state of the art accuracy and efficiency; however, the performance of these models are often limited by insufficient publicly available data. In this study, we continue our previous work in exploring the applications of the Laplace Operator, a detail enhancing image filter, in deep learning models in order to overcome these performance plateaus. Specifically, we evaluate the performance of ResNet-18 in diagnosing COVID-19 from a relatively small dataset of X-ray images. When comparing the performance of our model, dubbed CoronaNeXt, on images without the Laplacian applied to images with the Laplacian applied, we find significant increases in all maximum validation metrics: accuracy improved from 87.6% to 94.8%; F1 score improved from 0.860 to 0.968; specificity improved from 0.865 to 0.944; and sensitivity improved from 0.885 to 0.992. Based on these results, we describe the potential of the Laplacian Operator in drastically improving the performance of deep learning architectures in medical image classification tasks, particularly when utilizing small to medium sized datasets. Notably, sensitivity underwent the most significant improvement, correlating with the results achieved in our previous work using the CT modality. We hope our research will spark further exploration of the Laplace Operator and other derivative-based image preprocessing methodologies in conjunction with powerful deep learning models for medical image tasks. Keywords— COVID-19, Chest X-rays, Laplace Operator, Deep Learning","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74894871","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 : 2020-11-26DOI: 10.17577/ijertv9is110166
R. Bhansali, Rahul Kumar
—The purpose of this report is to retrospectively analyze and compare the early COVID-19 pandemic mitigation strategies of South Korea and the United States as the insights and knowledge gained can be applied to subsequent pandemics to minimize devastation. Additionally, this report will specifically give attention to the role of new emerging technologies in the detection, prevention, and treatment of this virus, as well as their role in the future and addresses early mitigation strategies that are implemented within two months of each country’s first detected case. First, we present a basic historical background regarding the nature of pandemics, as well as previous early mitigation techniques and their respective outcomes. This contains a background regarding the characteristics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the COVID-19 disease; additionally, we analyze the global spread of the virus prior to the imposition of universal travel bans. The second section provides comparative analysis regarding the different preparatory measures invoked by South Korea and the United States, the country in which COVID-19 cases are most prevalent. We examine a plethora of statistics, such as the rate of spread and percent of people tested, in order to reach a holistic conclusion about the effectiveness of each country’s mitigation strategy. In the third section we bring to light technological advancements that have been developed or are under development that have immense potential for application in virus detection, prevention, and mitigation.
{"title":"A Retrospective Comparative Analysis Regarding Strategies for Early COVID-19 Pandemic Mitigation in the US and South Korea","authors":"R. Bhansali, Rahul Kumar","doi":"10.17577/ijertv9is110166","DOIUrl":"https://doi.org/10.17577/ijertv9is110166","url":null,"abstract":"—The purpose of this report is to retrospectively analyze and compare the early COVID-19 pandemic mitigation strategies of South Korea and the United States as the insights and knowledge gained can be applied to subsequent pandemics to minimize devastation. Additionally, this report will specifically give attention to the role of new emerging technologies in the detection, prevention, and treatment of this virus, as well as their role in the future and addresses early mitigation strategies that are implemented within two months of each country’s first detected case. First, we present a basic historical background regarding the nature of pandemics, as well as previous early mitigation techniques and their respective outcomes. This contains a background regarding the characteristics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the COVID-19 disease; additionally, we analyze the global spread of the virus prior to the imposition of universal travel bans. The second section provides comparative analysis regarding the different preparatory measures invoked by South Korea and the United States, the country in which COVID-19 cases are most prevalent. We examine a plethora of statistics, such as the rate of spread and percent of people tested, in order to reach a holistic conclusion about the effectiveness of each country’s mitigation strategy. In the third section we bring to light technological advancements that have been developed or are under development that have immense potential for application in virus detection, prevention, and mitigation.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78619816","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 : 2020-11-26DOI: 10.17577/ijertv9is110163
R. Bhansali
Chest X-rays are the most frequently used medical imaging procedure and contain among the most significant and perilous diseases. Hospitals, especially those that are understaffed or have underqualified radiologists, would benefit greatly from an automated method of diagnosing these X-rays, which would drastically lower healthcare costs as well. This paper explores a combination of past, present, and future research that implements artificial intelligence towards this goal of automated diagnoses. Additionally, the importance of chest X-rays in light of COVID-19 is also analyzed. Keywords—Chest X-rays, radiology, artificial intelligence,
{"title":"Using Machine Learning to Diagnose Chest Xrays and Interpret Patient Symptoms and Medical History","authors":"R. Bhansali","doi":"10.17577/ijertv9is110163","DOIUrl":"https://doi.org/10.17577/ijertv9is110163","url":null,"abstract":"Chest X-rays are the most frequently used medical imaging procedure and contain among the most significant and perilous diseases. Hospitals, especially those that are understaffed or have underqualified radiologists, would benefit greatly from an automated method of diagnosing these X-rays, which would drastically lower healthcare costs as well. This paper explores a combination of past, present, and future research that implements artificial intelligence towards this goal of automated diagnoses. Additionally, the importance of chest X-rays in light of COVID-19 is also analyzed. Keywords—Chest X-rays, radiology, artificial intelligence,","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"126 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76829366","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 : 2020-11-26DOI: 10.17577/IJERTV9IS100186
Yilak A Kebede
-Road traffic fatalities disproportionately affect lowand middle-income countries. This research provides a method that helps cities in developing countries to use their limited resource to control accident-prone locations with satellite data insights. The proposed method is a mixed approach from both transport and the emerging machine learning discipline. In the first step, accident spots labeled using the Weighted Severity Index (WSI) with 14 risk factors that potentially influence the occurrence of an accident. Then, the computer is trained to look for blackspots using the labeled geoinformation data obtained from the WSI analysis. This cuttingedge method is called transfer learning with Convolutional Neural Networks (CNNs), which is the knowledge gained from previous training uses to identify a similar problem to a new location. The method is an inexpensive and reliable blackspot identifying solutions that extract data insights from freely available satellite imagery and open-source data. Keywords—road accident, hotspots; mapping; satellite imagery
{"title":"A Mixed-Method Proposal for Traffic Hotspots Mapping in African Cities using Raw Satellite Imagery","authors":"Yilak A Kebede","doi":"10.17577/IJERTV9IS100186","DOIUrl":"https://doi.org/10.17577/IJERTV9IS100186","url":null,"abstract":"-Road traffic fatalities disproportionately affect lowand middle-income countries. This research provides a method that helps cities in developing countries to use their limited resource to control accident-prone locations with satellite data insights. The proposed method is a mixed approach from both transport and the emerging machine learning discipline. In the first step, accident spots labeled using the Weighted Severity Index (WSI) with 14 risk factors that potentially influence the occurrence of an accident. Then, the computer is trained to look for blackspots using the labeled geoinformation data obtained from the WSI analysis. This cuttingedge method is called transfer learning with Convolutional Neural Networks (CNNs), which is the knowledge gained from previous training uses to identify a similar problem to a new location. The method is an inexpensive and reliable blackspot identifying solutions that extract data insights from freely available satellite imagery and open-source data. Keywords—road accident, hotspots; mapping; satellite imagery","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87009952","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 : 2020-11-12DOI: 10.17577/ijertv9is100264
Mehdi Moayyedian, A. Mamedov, J. Derakhshandeh, Abdelrahman Elkattan
This work is devoted to the optimization of temperature measurement procedure by determination of the effect of significant parameters throughout the temperature measurement. The experimental studies result in Negative Temperature Coefficient thermistors, which will shed light on a critical point during temperature measurement. The results of experimental temperature measurement are presented by applying different tools in Design of Experiments (DOE), namely Taguchi method and Analysis of Variance (ANOVA). In the experimental studies, the effects of four parameters are considered, including the operator, air velocity, immersion level and the diameter of the probe. These parameters are chosen because in most test cases they are repeatedly involved. The results demonstrate that the probe diameter of the thermistor is the most significant factor with the percentage of contribution of 41.87%. Hence, Design of Experiment is considered as reasonable tool in finding the critical parameters and their contributions in temperature measurement.
{"title":"Determination of Significant Parameters and Their Contributions In Temperature Measurement using Analysis of Variance and Taguchi Method","authors":"Mehdi Moayyedian, A. Mamedov, J. Derakhshandeh, Abdelrahman Elkattan","doi":"10.17577/ijertv9is100264","DOIUrl":"https://doi.org/10.17577/ijertv9is100264","url":null,"abstract":"This work is devoted to the optimization of temperature measurement procedure by determination of the effect of significant parameters throughout the temperature measurement. The experimental studies result in Negative Temperature Coefficient thermistors, which will shed light on a critical point during temperature measurement. The results of experimental temperature measurement are presented by applying different tools in Design of Experiments (DOE), namely Taguchi method and Analysis of Variance (ANOVA). In the experimental studies, the effects of four parameters are considered, including the operator, air velocity, immersion level and the diameter of the probe. These parameters are chosen because in most test cases they are repeatedly involved. The results demonstrate that the probe diameter of the thermistor is the most significant factor with the percentage of contribution of 41.87%. Hence, Design of Experiment is considered as reasonable tool in finding the critical parameters and their contributions in temperature measurement.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80099906","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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