Pub Date : 2022-03-28DOI: 10.38032/jea.2022.01.005
Karan Gaglani, Md. Amzad Hossain
The optimization of the design and operating conditions of industrial combustors depends on the fundamental study of combustion dynamics and flow behaviors. Complete combustion increases the thermal efficiency as well as reduces the emission significantly. A study of this kind also allows exploring alternative fuels that would increase the combustion efficiency thus the life cycle of the systems. To develop a highly-performed combustion system for rocket engines or power plants, fundamental research under an axisymmetric small-scale combustor is considered in this study. The k-Ɛ (2 Eqn.) and species transport model (STM) are used to study the flow turbulence and combustion behavior, respectively. A Parallel flow injection configuration of fuel and air is considered. In this study, combustion behavior is investigated at a wide range of fuel and air flowrate conditions while keeping the air slot dimension (240 mm) and fuel injection slot diameter (10 mm) constant. The fuel velocity (FV) and air velocity (AV) are changed from 2 m/s to 30 m/s so that a better test matrix could be proposed. At each run, turbulence, the flame temperature, reaction heat release rate, mass fraction of CO2, etc are studied. It is seen that the combustion temperature increases with the increase in fuel injection velocity. The static flame temperature reaches its maximum (2177 K-2287 K) and falls within the standard limits of CH4-Air combustion. The mass fraction of CO2 is found to be within the acceptable limit (0.121-0.153). The heat of the reaction is found to be high at variable Reair and ReCH4 conditions. It is observed that the computational models used in this study are capable of predicting the flow and combustion behaviors accurately.
{"title":"Fundamental Study of CH4-Air Combustion Under an Axisymmetric Small-scale Rectangular Combustor Using Computational Modeling","authors":"Karan Gaglani, Md. Amzad Hossain","doi":"10.38032/jea.2022.01.005","DOIUrl":"https://doi.org/10.38032/jea.2022.01.005","url":null,"abstract":"The optimization of the design and operating conditions of industrial combustors depends on the fundamental study of combustion dynamics and flow behaviors. Complete combustion increases the thermal efficiency as well as reduces the emission significantly. A study of this kind also allows exploring alternative fuels that would increase the combustion efficiency thus the life cycle of the systems. To develop a highly-performed combustion system for rocket engines or power plants, fundamental research under an axisymmetric small-scale combustor is considered in this study. The k-Ɛ (2 Eqn.) and species transport model (STM) are used to study the flow turbulence and combustion behavior, respectively. A Parallel flow injection configuration of fuel and air is considered. In this study, combustion behavior is investigated at a wide range of fuel and air flowrate conditions while keeping the air slot dimension (240 mm) and fuel injection slot diameter (10 mm) constant. The fuel velocity (FV) and air velocity (AV) are changed from 2 m/s to 30 m/s so that a better test matrix could be proposed. At each run, turbulence, the flame temperature, reaction heat release rate, mass fraction of CO2, etc are studied. It is seen that the combustion temperature increases with the increase in fuel injection velocity. The static flame temperature reaches its maximum (2177 K-2287 K) and falls within the standard limits of CH4-Air combustion. The mass fraction of CO2 is found to be within the acceptable limit (0.121-0.153). The heat of the reaction is found to be high at variable Reair and ReCH4 conditions. It is observed that the computational models used in this study are capable of predicting the flow and combustion behaviors accurately.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130827659","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 : 2022-03-24DOI: 10.38032/jea.2022.01.004
Sadman Shahriar, M. Arifuzzaman, Pranto Karua
The main objective of this research is to manufacture expanded perlite (EP) foam-filled stainless steel tubes for energy absorption application and to investigate their physical and compressive behavior. Foam-filled steel tubes (FFT) were manufactured by consolidating expanded perlite/sodium silicate composite foam inside the tube. The EP particles of size 5-6 mm were taken for manufacturing FFTs. Two different sodium silicate solution to water (S/W) ratios and three compaction ratios (CR) were the manufacturing parameters of the foams. The manufactured FFTs were characterized for density, yield stress, plateau stress, energy absorption, and energy absorption efficiency. The compression test results showed that the foam filling improved the compressive properties and energy absorption ability of the steel tube significantly. The failure analysis along with the stress-strain curves was also conducted. The change in failure mechanism is found to be the reason for high energy absorption and energy absorption efficiency for high-density foam-filled tubes.
{"title":"Mechanical and Energy Absorption Performance of Expanded Perlite Foam-filled Steel Tubes","authors":"Sadman Shahriar, M. Arifuzzaman, Pranto Karua","doi":"10.38032/jea.2022.01.004","DOIUrl":"https://doi.org/10.38032/jea.2022.01.004","url":null,"abstract":"The main objective of this research is to manufacture expanded perlite (EP) foam-filled stainless steel tubes for energy absorption application and to investigate their physical and compressive behavior. Foam-filled steel tubes (FFT) were manufactured by consolidating expanded perlite/sodium silicate composite foam inside the tube. The EP particles of size 5-6 mm were taken for manufacturing FFTs. Two different sodium silicate solution to water (S/W) ratios and three compaction ratios (CR) were the manufacturing parameters of the foams. The manufactured FFTs were characterized for density, yield stress, plateau stress, energy absorption, and energy absorption efficiency. The compression test results showed that the foam filling improved the compressive properties and energy absorption ability of the steel tube significantly. The failure analysis along with the stress-strain curves was also conducted. The change in failure mechanism is found to be the reason for high energy absorption and energy absorption efficiency for high-density foam-filled tubes.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133778673","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 : 2022-03-18DOI: 10.38032/jea.2022.01.003
Tafsirul Hassan, Md. Tazul Islam, Md. Mizanur Rahman, Abu Raihan Ibna Ali, Asif Al Ziyan
This paper presents an evaluation of five different turbulence models by comparing the numerical data derived from these models using ANSYS Fluent with experimental data at a Reynolds number and a Mach number of 0.05 × 106 and 0.015 respectively based on the centerline chord of the airfoil for the flow over NACA 0012 and NACA 2412 airfoils. Moreover, the aim of the present study is to demonstrate the difference in aerodynamic characteristics of the airfoils in order to find aerodynamically more advantageous airfoil. It is concluded that Spalart-Allmaras model and k-ω SST model are capable of providing the most accurate prediction for lift coefficient at a low angle of attack for both airfoils. Standard k - ε model gives a slightly low value of lift coefficient at low angle of attack and slightly high value of lift coefficient at high angle of attack for both airfoils. k-ω SST model, Spalart-Allmaras model, Transition k-kL - ω model, and γ-Rⅇθ Transition SST model can predict drag coefficient reasonably at low angle of attack. At a high angle of attack, however, no turbulence model is able to give a satisfactory prediction for lift coefficient as well as drag coefficient, which implies that these models are unable to predict post-stall characteristics. NACA 2412 airfoil produces more lift coefficient than that of the NACA 0012 airfoil at all angles of attack. Moreover, the drag coefficient of NACA 2412 airfoil is less than that of the NACA 0012 airfoil, which implies that NACA 2412 airfoil exhibits better aerodynamic performance. The lift to drag coefficient ratio of NACA 2412 airfoil is also higher than that of the NACA 0012 airfoil indicating NACA 2412 airfoil to be more fuel economic.
{"title":"Evaluation of Different Turbulence Models at Low Reynolds Number for the Flow over Symmetric and Cambered Airfoils","authors":"Tafsirul Hassan, Md. Tazul Islam, Md. Mizanur Rahman, Abu Raihan Ibna Ali, Asif Al Ziyan","doi":"10.38032/jea.2022.01.003","DOIUrl":"https://doi.org/10.38032/jea.2022.01.003","url":null,"abstract":"This paper presents an evaluation of five different turbulence models by comparing the numerical data derived from these models using ANSYS Fluent with experimental data at a Reynolds number and a Mach number of 0.05 × 106 and 0.015 respectively based on the centerline chord of the airfoil for the flow over NACA 0012 and NACA 2412 airfoils. Moreover, the aim of the present study is to demonstrate the difference in aerodynamic characteristics of the airfoils in order to find aerodynamically more advantageous airfoil. It is concluded that Spalart-Allmaras model and k-ω SST model are capable of providing the most accurate prediction for lift coefficient at a low angle of attack for both airfoils. Standard k - ε model gives a slightly low value of lift coefficient at low angle of attack and slightly high value of lift coefficient at high angle of attack for both airfoils. k-ω SST model, Spalart-Allmaras model, Transition k-kL - ω model, and γ-Rⅇθ Transition SST model can predict drag coefficient reasonably at low angle of attack. At a high angle of attack, however, no turbulence model is able to give a satisfactory prediction for lift coefficient as well as drag coefficient, which implies that these models are unable to predict post-stall characteristics. NACA 2412 airfoil produces more lift coefficient than that of the NACA 0012 airfoil at all angles of attack. Moreover, the drag coefficient of NACA 2412 airfoil is less than that of the NACA 0012 airfoil, which implies that NACA 2412 airfoil exhibits better aerodynamic performance. The lift to drag coefficient ratio of NACA 2412 airfoil is also higher than that of the NACA 0012 airfoil indicating NACA 2412 airfoil to be more fuel economic.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256487","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 : 2022-03-15DOI: 10.38032/jea.2022.01.002
Rafi Ahmed Miah, M. Alam, Aklima Khatun, M. H. Suhag, Md. Nazmul Kayes
Industrial wastewater containing dye can cause severe destruction to the human immune system as well as the nervous system. The purpose of the present study is to optimize the decolorization of a textile dye Novacron blue on the surface of jackfruit seed powder (JSP). Jackfruit seed can be obtained at a low cost and be used without further purification/chemical treatment to adsorb some pollutants on its surface. About 73% of Novacron blue was adsorbed on the surface of JSP after 60 minutes of contact time. Effects of various physico-chemical parameters such as adsorbent dose, initial dye concentration, pH, temperature, and contact time on the adsorption of Novacron blue have been investigated. The adsorption was found to be increased initially with the adsorbent dose and become maximum at 10 g of the adsorbent. The maximum adsorption capacity was 0.732 mg/g. The decolorization efficiency was inversely proportional to the initial concentration of Novacron blue. Basic medium and low temperature are preferred by the adsorbent for the adsorption of Novacron blue on JSP. Kinetics of adsorption was accomplished with the pseudo-first-order and pseudo-second-order model. Phytotoxic study on Red Amaranth reveals the abolishment of hazardous species from the wastewater.
{"title":"The Decolorization and Phytotoxic Efficiency of Jackfruit Seed on a Textile Dye Novacron Blue","authors":"Rafi Ahmed Miah, M. Alam, Aklima Khatun, M. H. Suhag, Md. Nazmul Kayes","doi":"10.38032/jea.2022.01.002","DOIUrl":"https://doi.org/10.38032/jea.2022.01.002","url":null,"abstract":"Industrial wastewater containing dye can cause severe destruction to the human immune system as well as the nervous system. The purpose of the present study is to optimize the decolorization of a textile dye Novacron blue on the surface of jackfruit seed powder (JSP). Jackfruit seed can be obtained at a low cost and be used without further purification/chemical treatment to adsorb some pollutants on its surface. About 73% of Novacron blue was adsorbed on the surface of JSP after 60 minutes of contact time. Effects of various physico-chemical parameters such as adsorbent dose, initial dye concentration, pH, temperature, and contact time on the adsorption of Novacron blue have been investigated. The adsorption was found to be increased initially with the adsorbent dose and become maximum at 10 g of the adsorbent. The maximum adsorption capacity was 0.732 mg/g. The decolorization efficiency was inversely proportional to the initial concentration of Novacron blue. Basic medium and low temperature are preferred by the adsorbent for the adsorption of Novacron blue on JSP. Kinetics of adsorption was accomplished with the pseudo-first-order and pseudo-second-order model. Phytotoxic study on Red Amaranth reveals the abolishment of hazardous species from the wastewater.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127987620","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 : 2022-03-04DOI: 10.38032/jea.2022.01.001
A. Asif, Farhana Chowdhury Tisha
One of the deadliest pandemics is now happening in the current world due to COVID-19. This contagious virus is spreading like wildfire around the whole world. To minimize the spreading of this virus, World Health Organization (WHO) has made protocols mandatory for wearing face masks and maintaining 6 feet physical distance. In this paper, we have developed a system that can detect the proper maintenance of that distance and people are properly using masks or not. We have used the customized attention-inceptionv3 model in this system for the identification of those two components. We have used two different datasets along with 10,800 images including both with and without Face Mask images. The training accuracy has been achieved 98% and validation accuracy 99.5%. The system can conduct a precision value of around 98.2% and the frame rate per second (FPS) was 25.0. So, with this system, we can identify high-risk areas with the highest possibility of the virus spreading zone. This may help authorities to take necessary steps to locate those risky areas and alert the local people to ensure proper precautions in no time.
{"title":"A Real-time Face Mask Detection and Social Distancing System for COVID-19 using Attention-InceptionV3 Model","authors":"A. Asif, Farhana Chowdhury Tisha","doi":"10.38032/jea.2022.01.001","DOIUrl":"https://doi.org/10.38032/jea.2022.01.001","url":null,"abstract":"One of the deadliest pandemics is now happening in the current world due to COVID-19. This contagious virus is spreading like wildfire around the whole world. To minimize the spreading of this virus, World Health Organization (WHO) has made protocols mandatory for wearing face masks and maintaining 6 feet physical distance. In this paper, we have developed a system that can detect the proper maintenance of that distance and people are properly using masks or not. We have used the customized attention-inceptionv3 model in this system for the identification of those two components. We have used two different datasets along with 10,800 images including both with and without Face Mask images. The training accuracy has been achieved 98% and validation accuracy 99.5%. The system can conduct a precision value of around 98.2% and the frame rate per second (FPS) was 25.0. So, with this system, we can identify high-risk areas with the highest possibility of the virus spreading zone. This may help authorities to take necessary steps to locate those risky areas and alert the local people to ensure proper precautions in no time.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123202257","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 : 2021-12-27DOI: 10.38032/jea.2021.04.008
Asif Mohammad, Mahruf Zaman Utso, Shifat Bin Habib, A. Das
Neural networks in image processing are becoming a more crucial and integral part of machine learning as computational technology and hardware systems are advanced. Deep learning is also getting attention from the medical sector as it is a prominent process for classifying diseases. There is a lot of research to predict retinal diseases using deep learning algorithms like Convolutional Neural Network (CNN). Still, there are not many researches for predicting diseases like CNV which stands for choroidal neovascularization, DME, which stands for Diabetic Macular Edema; and DRUSEN. In our research paper, the CNN (Convolutional Neural Networks) algorithm labeled the dataset of OCT retinal images into four types: CNV, DME, DRUSEN, and Natural Retina. We have also done several preprocessing on the images before passing these to the neural network. We have implemented different models for our algorithm where individual models have different hidden layers. At the end of our following research, we have found that our algorithm CNN generates 93% accuracy.
{"title":"Predicting Retinal Diseases using Efficient Image Processing and Convolutional Neural Network (CNN)","authors":"Asif Mohammad, Mahruf Zaman Utso, Shifat Bin Habib, A. Das","doi":"10.38032/jea.2021.04.008","DOIUrl":"https://doi.org/10.38032/jea.2021.04.008","url":null,"abstract":"Neural networks in image processing are becoming a more crucial and integral part of machine learning as computational technology and hardware systems are advanced. Deep learning is also getting attention from the medical sector as it is a prominent process for classifying diseases. There is a lot of research to predict retinal diseases using deep learning algorithms like Convolutional Neural Network (CNN). Still, there are not many researches for predicting diseases like CNV which stands for choroidal neovascularization, DME, which stands for Diabetic Macular Edema; and DRUSEN. In our research paper, the CNN (Convolutional Neural Networks) algorithm labeled the dataset of OCT retinal images into four types: CNV, DME, DRUSEN, and Natural Retina. We have also done several preprocessing on the images before passing these to the neural network. We have implemented different models for our algorithm where individual models have different hidden layers. At the end of our following research, we have found that our algorithm CNN generates 93% accuracy.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"312-315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130875636","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 : 2021-12-26DOI: 10.38032/jea.2021.04.007
Md. Ashraful Alam, Atikur Rahman Baizid
Lorentz Transformation is the relationship between two different coordinate frames time and space when one inertial reference frame is relative to another inertial reference frame with traveling at relative speed. In this paper, we have derived the transformation formula for the volume charge density in Geometric Product Lorentz Transformation. The changes of volume charge density of moving frame in terms of that rest frame in Geometric Product Lorentz Transformation at various velocities and angles were studied as well.
{"title":"Volume Charge Density in Geometric Product Lorentz Transformation","authors":"Md. Ashraful Alam, Atikur Rahman Baizid","doi":"10.38032/jea.2021.04.007","DOIUrl":"https://doi.org/10.38032/jea.2021.04.007","url":null,"abstract":"Lorentz Transformation is the relationship between two different coordinate frames time and space when one inertial reference frame is relative to another inertial reference frame with traveling at relative speed. In this paper, we have derived the transformation formula for the volume charge density in Geometric Product Lorentz Transformation. The changes of volume charge density of moving frame in terms of that rest frame in Geometric Product Lorentz Transformation at various velocities and angles were studied as well.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114917396","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 : 2021-12-23DOI: 10.38032/jea.2021.04.006
Toukir Ahmed Chowdhury, Towhedul Islam, Ahmad Abdullah Mujahid, Md. Bayazid Ahmed
Newton-Cotes integration formulae have been researched for a long time, but the topic is still of interest since the correctness of the techniques has not yet been explicitly defined in a sequence for diverse engineering situations. The purpose of this paper is to give the readers an overview of the four numerical integration methods derived from Newton-Cotes formula, namely the Trapezoidal rule, Simpson's 1/3rd rule, Simpson's 3/8th rule, and Weddle's rule, as well as to demonstrate the periodicity of the most accurate methods for solving each engineering integral equation by varying the number of sub-divisions. The exact expressions by solving the numerical integral equations have been determined by Maple program and comparisons have been done using Python version 3.8.
{"title":"The Periodicity of the Accuracy of Numerical Integration Methods for the Solution of Different Engineering Problems","authors":"Toukir Ahmed Chowdhury, Towhedul Islam, Ahmad Abdullah Mujahid, Md. Bayazid Ahmed","doi":"10.38032/jea.2021.04.006","DOIUrl":"https://doi.org/10.38032/jea.2021.04.006","url":null,"abstract":"Newton-Cotes integration formulae have been researched for a long time, but the topic is still of interest since the correctness of the techniques has not yet been explicitly defined in a sequence for diverse engineering situations. The purpose of this paper is to give the readers an overview of the four numerical integration methods derived from Newton-Cotes formula, namely the Trapezoidal rule, Simpson's 1/3rd rule, Simpson's 3/8th rule, and Weddle's rule, as well as to demonstrate the periodicity of the most accurate methods for solving each engineering integral equation by varying the number of sub-divisions. The exact expressions by solving the numerical integral equations have been determined by Maple program and comparisons have been done using Python version 3.8.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133305749","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 : 2021-12-18DOI: 10.38032/jea.2021.04.005
N. Islam
During the duration of the last decade, a growing interest has been noticed among transport practitioners and researchers to better understand the concept of service quality in the field of surface transportation and identify important service quality (SQ) attributes of different transportation services since these results have implications for transport managers. Due to advancements in computer technology and the availability of software packages, researchers are better able to extract meaningful results from passengers’ opinions collected through stated preference surveys and communicate their findings to transport managers looking to ameliorate SQ to boost ridership on a limited budget. Since the concept of SQ is itself complex owing to the nature of the service itself compared to a tangible product and characteristics of SQ attribute, different advanced modelling techniques based on multivariate analysis, machine learning, and artificial intelligence paradigms have become popular tools among researchers. This paper aims to summarize the trends of the SQ research in the field of surface transportation during the last decade with a focus on the methodological approaches and modelling techniques and delineate future directions for research in this field.
{"title":"A Review of Methodological Approaches and Modeling Techniques in Service Quality Evaluation of Surface Transportation during the Last Decade","authors":"N. Islam","doi":"10.38032/jea.2021.04.005","DOIUrl":"https://doi.org/10.38032/jea.2021.04.005","url":null,"abstract":"During the duration of the last decade, a growing interest has been noticed among transport practitioners and researchers to better understand the concept of service quality in the field of surface transportation and identify important service quality (SQ) attributes of different transportation services since these results have implications for transport managers. Due to advancements in computer technology and the availability of software packages, researchers are better able to extract meaningful results from passengers’ opinions collected through stated preference surveys and communicate their findings to transport managers looking to ameliorate SQ to boost ridership on a limited budget. Since the concept of SQ is itself complex owing to the nature of the service itself compared to a tangible product and characteristics of SQ attribute, different advanced modelling techniques based on multivariate analysis, machine learning, and artificial intelligence paradigms have become popular tools among researchers. This paper aims to summarize the trends of the SQ research in the field of surface transportation during the last decade with a focus on the methodological approaches and modelling techniques and delineate future directions for research in this field.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114272871","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 : 2021-12-15DOI: 10.38032/jea.2021.04.004
M. K. Vowotor, R. Edziah, S. S. Sackey, Emmanuel Kofi Amewode, Sandra Baaba Frempong
Heavy metal concentrations in some water bodies and the soil beneath these waters. These would have detrimental consequences on these water users and consumers of the fish in that water. Instrumental Neutron Activation Analysis technique using the Ghana Research Reactor-1 was employed to find out the concentrations of two heavy metals, Arsenic (As) and Copper (Cu) in the sediments, fishes, and water collected from the Benya Lagoon in the KEEA, Ghana. Cumulatively, Copper was found to be greater in concentration than Arsenic concerning the three parts of the ecology under study. On the other hand, Arsenic was more concentrated in the sediments than Copper, and Copper was more concentrated in the water and fish than Arsenic. Cumulatively, the level of contamination of Arsenic and Copper decreased in the order fish > sediment > water. Though Arsenic and Copper were found in elevated amounts in both water and fish which rendered the Lagoon water unsuitable for human use and the fish from the Lagoon unsafe for consumption, their concentrations in the sediment were found to have a low ecological risk index on the environment.
{"title":"Assessment of Arsenic and Copper Pollution of the Benya Lagoon, Ghana By Neutron Activation Analysis","authors":"M. K. Vowotor, R. Edziah, S. S. Sackey, Emmanuel Kofi Amewode, Sandra Baaba Frempong","doi":"10.38032/jea.2021.04.004","DOIUrl":"https://doi.org/10.38032/jea.2021.04.004","url":null,"abstract":"Heavy metal concentrations in some water bodies and the soil beneath these waters. These would have detrimental consequences on these water users and consumers of the fish in that water. Instrumental Neutron Activation Analysis technique using the Ghana Research Reactor-1 was employed to find out the concentrations of two heavy metals, Arsenic (As) and Copper (Cu) in the sediments, fishes, and water collected from the Benya Lagoon in the KEEA, Ghana. Cumulatively, Copper was found to be greater in concentration than Arsenic concerning the three parts of the ecology under study. On the other hand, Arsenic was more concentrated in the sediments than Copper, and Copper was more concentrated in the water and fish than Arsenic. Cumulatively, the level of contamination of Arsenic and Copper decreased in the order fish > sediment > water. Though Arsenic and Copper were found in elevated amounts in both water and fish which rendered the Lagoon water unsuitable for human use and the fish from the Lagoon unsafe for consumption, their concentrations in the sediment were found to have a low ecological risk index on the environment.","PeriodicalId":292407,"journal":{"name":"Journal of Engineering Advancements","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550314","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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