Pub Date : 2023-11-21DOI: 10.9734/jerr/2023/v25i111018
Ojo, P. E., Igbokwe, J. I., Oliha, A. O., Ojanikele, W. A.
Woji Creek plays a crucial role in vessel navigation, supports diverse flora and fauna habitats, and sustains local livelihoods. However, human activities and natural events have led to changes in its riverbed over time. Given its significance for coastal stability and geomorphology, there is a pressing need to classify, evaluate, and ensure its environmental sustainability. The primary objective of this study is to employ side scan sonar technology to classify and assess the riverbed of Woji Creek in Port Harcourt, Nigeria. The study aims to classify the riverbed, analyze water depth variations, evaluate navigational suitability, and determine turbidity levels within the creek. To achieve these objectives, the methodology involved acquiring Side-Scan Sonar (SSS) and Sub-bottom profile data. These datasets underwent backscatter processing to create geocoded backscatter images. Feature points were extracted and matched from these images to derive riverbed classification, depth categories, water volume distribution, and river turbidity analysis. The riverbed classification revealed the presence of three primary sediment types: Clayey Silty Sand, Silty Clay, and Silty Sand, each with distinct implications for navigation. Shallow, Moderate, Deep, and Very Deep areas were identified within Woji Creek, each influencing navigational conditions. Additionally, the water volume distribution analysis provided essential insights into depth limitations and route planning. Moreover, the assessment of river turbidity identified low, moderate, and high turbidity zones, reflecting water clarity and suspended particle levels. These findings serve as invaluable decision support tools for navigation planning and management in Woji Creek, offering comprehensive insights into the riverbed, depth suitability, volume distribution, and water quality. Leveraging this data can enhance strategic decision-making processes and contribute to the sustainable management of this vital waterway.
{"title":"Assessment and Characterization of Woji Creek Riverbed in Port Harcourt, Rivers State, Nigeria, Utilizing Side Scan Sonar Technology","authors":"Ojo, P. E., Igbokwe, J. I., Oliha, A. O., Ojanikele, W. A.","doi":"10.9734/jerr/2023/v25i111018","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111018","url":null,"abstract":"Woji Creek plays a crucial role in vessel navigation, supports diverse flora and fauna habitats, and sustains local livelihoods. However, human activities and natural events have led to changes in its riverbed over time. Given its significance for coastal stability and geomorphology, there is a pressing need to classify, evaluate, and ensure its environmental sustainability. The primary objective of this study is to employ side scan sonar technology to classify and assess the riverbed of Woji Creek in Port Harcourt, Nigeria. The study aims to classify the riverbed, analyze water depth variations, evaluate navigational suitability, and determine turbidity levels within the creek. To achieve these objectives, the methodology involved acquiring Side-Scan Sonar (SSS) and Sub-bottom profile data. These datasets underwent backscatter processing to create geocoded backscatter images. Feature points were extracted and matched from these images to derive riverbed classification, depth categories, water volume distribution, and river turbidity analysis. The riverbed classification revealed the presence of three primary sediment types: Clayey Silty Sand, Silty Clay, and Silty Sand, each with distinct implications for navigation. Shallow, Moderate, Deep, and Very Deep areas were identified within Woji Creek, each influencing navigational conditions. Additionally, the water volume distribution analysis provided essential insights into depth limitations and route planning. Moreover, the assessment of river turbidity identified low, moderate, and high turbidity zones, reflecting water clarity and suspended particle levels. These findings serve as invaluable decision support tools for navigation planning and management in Woji Creek, offering comprehensive insights into the riverbed, depth suitability, volume distribution, and water quality. Leveraging this data can enhance strategic decision-making processes and contribute to the sustainable management of this vital waterway.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"39 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139254289","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 : 2023-11-20DOI: 10.9734/jerr/2023/v25i111017
Hrishitva Patel
The emergence of big data has brought about a significant transformation in the domain of Information Systems, presenting academics and companies with unparalleled prospects and complexities. This abstract examines the potential risks and benefits associated with conducting research in a dynamic and fast growing field. The field of Information Systems is characterized by the significant potential of big data research to bring about transformative effects on various sectors and societies. However, this promising development also gives rise to apprehensions surrounding issues of privacy, ethics, and data security. The potential benefits of big data research are many and varied. First and foremost, this technology offers the potential to extract practical and applicable knowledge from extensive and varied collections of data. This, in turn, facilitates decision-making based on data, fosters innovation, and enhances effectiveness across multiple industries. Furthermore, it enables the progression of cutting-edge technologies, such as machine learning and artificial intelligence, which possess the capacity to propel substantial improvements in the field of Information Systems. In conclusion, the utilization of big data research has the potential to augment our comprehension of intricate phenomena, facilitate predictive analytics, and stimulate the advancement of tailored services, consequently amplifying user experiences. Nevertheless, the potential risks associated with conducting big data research are equally substantial. The rapid expansion of data gathering and analysis has given rise to apprehensions regarding the protection of data privacy, security, and ownership. Academic researchers are confronted with the task of effectively addressing ethical quandaries pertaining to the acquisition and utilization of sensitive personal data. Furthermore, it is imperative to carefully contemplate the significant concern around algorithmic bias and discrimination in the context of data-driven decision-making. Furthermore, the considerable quantity and intricate nature of data provide obstacles in relation to the quality of data, the administration of data, and the ability to scale.
{"title":"Big Data in Information Systems: A Review","authors":"Hrishitva Patel","doi":"10.9734/jerr/2023/v25i111017","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111017","url":null,"abstract":"The emergence of big data has brought about a significant transformation in the domain of Information Systems, presenting academics and companies with unparalleled prospects and complexities. This abstract examines the potential risks and benefits associated with conducting research in a dynamic and fast growing field. The field of Information Systems is characterized by the significant potential of big data research to bring about transformative effects on various sectors and societies. However, this promising development also gives rise to apprehensions surrounding issues of privacy, ethics, and data security. The potential benefits of big data research are many and varied. First and foremost, this technology offers the potential to extract practical and applicable knowledge from extensive and varied collections of data. This, in turn, facilitates decision-making based on data, fosters innovation, and enhances effectiveness across multiple industries. Furthermore, it enables the progression of cutting-edge technologies, such as machine learning and artificial intelligence, which possess the capacity to propel substantial improvements in the field of Information Systems. In conclusion, the utilization of big data research has the potential to augment our comprehension of intricate phenomena, facilitate predictive analytics, and stimulate the advancement of tailored services, consequently amplifying user experiences. Nevertheless, the potential risks associated with conducting big data research are equally substantial. The rapid expansion of data gathering and analysis has given rise to apprehensions regarding the protection of data privacy, security, and ownership. Academic researchers are confronted with the task of effectively addressing ethical quandaries pertaining to the acquisition and utilization of sensitive personal data. Furthermore, it is imperative to carefully contemplate the significant concern around algorithmic bias and discrimination in the context of data-driven decision-making. Furthermore, the considerable quantity and intricate nature of data provide obstacles in relation to the quality of data, the administration of data, and the ability to scale.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139255121","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 : 2023-11-18DOI: 10.9734/jerr/2023/v25i111016
Frank C. Mbachu, I. Nwaogazie
The aim of this study is the development of water quality models against water quality parameters from 5 selected ponds in Aboh-Mbaise local government area (LGA) of Imo state. Water quality index (WQI) as dependent variable computed based on water quality parameters which were taken as independent variables and modelled as multiple linear regression. Given that there are over 25 water quality parameters (physiochemical, heavy metals and microbials), it was necessary to adopt factor reduction technique using principal component analysis. In this approach, 3 principal component factors were generated having corresponding factors (independent variables of 5, 6 and 5 respectively). The resulting multiple regression for the 3 principal component factors yielded Goodness of Fit of 92.9, 99.0 and 96.6% as well as root mean square error (RMSE) of 66.673, 0.672 and 51.968 respectively. The model verification was accomplished by plotting the computed WQI against predicted values from the developed models and the best option was the one with 99.0% R2 value with the following independent variables-sulphate, TSS, phosphate, turbidity, total solid and nitrates. The model output is relevant in WQI prediction given the applicable water quality characteristics. This predictive model will find wide application in selecting water treatment options for pond water in the study area.
{"title":"Modelling and Prediction of Water Quality Index of Selected Pond Water in Aboh Mbaise Local Government Area, Imo State, Nigeria","authors":"Frank C. Mbachu, I. Nwaogazie","doi":"10.9734/jerr/2023/v25i111016","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111016","url":null,"abstract":"The aim of this study is the development of water quality models against water quality parameters from 5 selected ponds in Aboh-Mbaise local government area (LGA) of Imo state. Water quality index (WQI) as dependent variable computed based on water quality parameters which were taken as independent variables and modelled as multiple linear regression. Given that there are over 25 water quality parameters (physiochemical, heavy metals and microbials), it was necessary to adopt factor reduction technique using principal component analysis. In this approach, 3 principal component factors were generated having corresponding factors (independent variables of 5, 6 and 5 respectively). The resulting multiple regression for the 3 principal component factors yielded Goodness of Fit of 92.9, 99.0 and 96.6% as well as root mean square error (RMSE) of 66.673, 0.672 and 51.968 respectively. The model verification was accomplished by plotting the computed WQI against predicted values from the developed models and the best option was the one with 99.0% R2 value with the following independent variables-sulphate, TSS, phosphate, turbidity, total solid and nitrates. The model output is relevant in WQI prediction given the applicable water quality characteristics. This predictive model will find wide application in selecting water treatment options for pond water in the study area.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"55 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262180","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 : 2023-11-13DOI: 10.9734/jerr/2023/v25i101022
N. Tayisepi, L. Mugwagwa, Margret Munyau, Takudzwa M. Muhla
This paper reports on the IEUOCPPTM (Integrated Energy Use Optimisation and Cutting Parameters Prediction Tool Model) designed to optimise the machining parameters planning process of titanium alloy machining on the CNC lathe. It aimed to create a novel systematic methodology for determination of optimised cutting parameters. MATLAB genetic algorithm and Visual Basic Application softwares were integrated to generate the IEUOCPPTM optimised machining process planning tool for titanium alloys. The empirical 18 full factorial experiment runs design was carried out using Minitab. Determination of appropriate cutting parameters is vital for conserving energy and achieving sustainability for the titanium alloy machining businesses confronted with immense pressure to produce cost-effectively in record delivery times. Machining is a fundamental, and electrical energy intensive, activity in the profiling process of cylindrical T-alloy, Ti6Al4V, components used in the aerospace, automotive and general metal working industries. Varied performance outcomes were achieved, on the machined components after predicting the input parameters using the tool as opposed to the good-guess approach currently being applied in industry. Validation experiments confirmed functionality of IEUOCPPTM in forecasting the cutting parameter settings required, to achieve desired responses during machining of Ti6Al4V within an average error range of 8%.
{"title":"Integrated Energy Use Optimisation and Cutting Parameter Prediction Model - Aiding Process Planning of Ti6Al4V Machining on the CNC Lathe","authors":"N. Tayisepi, L. Mugwagwa, Margret Munyau, Takudzwa M. Muhla","doi":"10.9734/jerr/2023/v25i101022","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i101022","url":null,"abstract":"This paper reports on the IEUOCPPTM (Integrated Energy Use Optimisation and Cutting Parameters Prediction Tool Model) designed to optimise the machining parameters planning process of titanium alloy machining on the CNC lathe. It aimed to create a novel systematic methodology for determination of optimised cutting parameters. MATLAB genetic algorithm and Visual Basic Application softwares were integrated to generate the IEUOCPPTM optimised machining process planning tool for titanium alloys. The empirical 18 full factorial experiment runs design was carried out using Minitab. Determination of appropriate cutting parameters is vital for conserving energy and achieving sustainability for the titanium alloy machining businesses confronted with immense pressure to produce cost-effectively in record delivery times. Machining is a fundamental, and electrical energy intensive, activity in the profiling process of cylindrical T-alloy, Ti6Al4V, components used in the aerospace, automotive and general metal working industries. Varied performance outcomes were achieved, on the machined components after predicting the input parameters using the tool as opposed to the good-guess approach currently being applied in industry. Validation experiments confirmed functionality of IEUOCPPTM in forecasting the cutting parameter settings required, to achieve desired responses during machining of Ti6Al4V within an average error range of 8%.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139279048","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 : 2023-09-07DOI: 10.9734/jerr/2023/v25i8965
Tushar Khinvasara, Stephanie Ness, N. Tzenios
In spite of the fact that risk management has developed into an essential component of the process of developing medical devices, as mandated by both domestic and international regulations and standards, there is still no all-encompassing model that describes how risk management in the development of medical devices ought to be approached, particularly in terms of the types of risks that ought to be addressed. This is due to the fact that risk management has developed into an essential component of the process, which is mandated by both domestic and international regulations and standards. The present focus of risk management in the industry of developing medical devices is on technical risks, such as product, usability, and development process hazards. This is done in compliance with the norms and laws of standards. On the other hand, non-technical risks, such as those associated with businesses and projects, are not given nearly enough consideration. This review focuses on the risk management in medical device industry.
{"title":"Risk Management in Medical Device Industry","authors":"Tushar Khinvasara, Stephanie Ness, N. Tzenios","doi":"10.9734/jerr/2023/v25i8965","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i8965","url":null,"abstract":"In spite of the fact that risk management has developed into an essential component of the process of developing medical devices, as mandated by both domestic and international regulations and standards, there is still no all-encompassing model that describes how risk management in the development of medical devices ought to be approached, particularly in terms of the types of risks that ought to be addressed. This is due to the fact that risk management has developed into an essential component of the process, which is mandated by both domestic and international regulations and standards. The present focus of risk management in the industry of developing medical devices is on technical risks, such as product, usability, and development process hazards. This is done in compliance with the norms and laws of standards. On the other hand, non-technical risks, such as those associated with businesses and projects, are not given nearly enough consideration. This review focuses on the risk management in medical device industry.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114267947","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 : 2023-09-06DOI: 10.9734/jerr/2023/v25i8964
Akpan, Abasiama J., Olosunde, William A., Antia, Orua O.
In an effort to easily use the Orua Antia’s energy and power equations to determine the minimum comminution energy and power requirements of a given material; the mass Index being a constant in these equations is necessary to be provided for materials that could be subjected to comminution. In this study, the mass indices of some selected food materials such as cassava, yam, crayfish, beans and soybeans which finds applications in food industries were evaluated using static impact force technique coupled with graphical and computational approaches. In graphical method Equation 17 obtained from energy expression for mass-size reduction Equation 14 was employed; while Equation 16 which is a combination of Equation 14 and the potential energy Equation 15 was used in the computational method. Also the relative errors of mass indices obtained from these two methods were evaluated. Results showed that computational or graphical method could be used to obtain the mass index of each selected material. It was observed that moisture content had little influence on the value of mass index. Hence, the average mass index per selected food type within its percentage moisture content wet basis range could be utilized in the minimum comminution energy and power Equations 4 to 6 and 12 to 13 respectively, via the equations constants as applicable and expressed as Equations 9, 10 and 11. Further analysis revealed that the average mass indices were 1.71230.5835, 1.89150.6377,20.27043.0846, 18.19601.0337 and 23.77912.3094 for cassava, yam, crayfish, beans and soy beans respectively.
{"title":"Mass-Indices (B-Values) of Legumes, Tuber and Sea Food for Mass-Size Reduction Operations","authors":"Akpan, Abasiama J., Olosunde, William A., Antia, Orua O.","doi":"10.9734/jerr/2023/v25i8964","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i8964","url":null,"abstract":"In an effort to easily use the Orua Antia’s energy and power equations to determine the minimum comminution energy and power requirements of a given material; the mass Index being a constant in these equations is necessary to be provided for materials that could be subjected to comminution. In this study, the mass indices of some selected food materials such as cassava, yam, crayfish, beans and soybeans which finds applications in food industries were evaluated using static impact force technique coupled with graphical and computational approaches. In graphical method Equation 17 obtained from energy expression for mass-size reduction Equation 14 was employed; while Equation 16 which is a combination of Equation 14 and the potential energy Equation 15 was used in the computational method. Also the relative errors of mass indices obtained from these two methods were evaluated. Results showed that computational or graphical method could be used to obtain the mass index of each selected material. It was observed that moisture content had little influence on the value of mass index. Hence, the average mass index per selected food type within its percentage moisture content wet basis range could be utilized in the minimum comminution energy and power Equations 4 to 6 and 12 to 13 respectively, via the equations constants as applicable and expressed as Equations 9, 10 and 11. Further analysis revealed that the average mass indices were 1.71230.5835, 1.89150.6377,20.27043.0846, 18.19601.0337 and 23.77912.3094 for cassava, yam, crayfish, beans and soy beans respectively.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124433080","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 : 2023-09-06DOI: 10.9734/jerr/2023/v25i8963
Akyen Thomas, Christopher Kwesi Baah, Jonathan Odonkoh, Samuel Wilberforce Offei
Alternative materials are now being used for the construction of various projects in Ghana due to the expansion of infrastructure in the country. The quantity of materials needed to build infrastructure presents a significant opportunity to reuse some of the waste products. It has become possible to investigate the recycling of plastic waste into the construction of bricks due to the substantial discrepancy between the supply and demand of traditional building materials. In this study, an effort was made to recycle a sizable amount of HDPE waste gathered from markets, shopping centers, landfills, and supermarkets for utilization of bricks for housing projects. To determine the efficacy and durability of the bricks made from recycled plastic waste for various uses in civil engineering projects, several experimental tests including the compressive strength test, split tensile test, and water absorption tests were conducted. The mix ratios for the plastic bricks for compressive and tensile strength are 1:3, 1:4, and 1:5.5, respectively, while their water absorption mix ratios are 1:2, 1:3, and 1:4. The experimental findings demonstrated that the bricks produced had good compressive strength, tensile strength and low water absorption rates. Additionally, it was observed that the manufactured bricks are lightweight, have a smooth surface and fine edges, and can be an excellent substitute for clay and conventional concrete blocks, which have been used for decades to build housing projects in the country.
{"title":"Investigation of Recycled Plastic Waste into Bricks for the Construction of Housing Projects in Ghana","authors":"Akyen Thomas, Christopher Kwesi Baah, Jonathan Odonkoh, Samuel Wilberforce Offei","doi":"10.9734/jerr/2023/v25i8963","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i8963","url":null,"abstract":"Alternative materials are now being used for the construction of various projects in Ghana due to the expansion of infrastructure in the country. The quantity of materials needed to build infrastructure presents a significant opportunity to reuse some of the waste products. It has become possible to investigate the recycling of plastic waste into the construction of bricks due to the substantial discrepancy between the supply and demand of traditional building materials. In this study, an effort was made to recycle a sizable amount of HDPE waste gathered from markets, shopping centers, landfills, and supermarkets for utilization of bricks for housing projects. To determine the efficacy and durability of the bricks made from recycled plastic waste for various uses in civil engineering projects, several experimental tests including the compressive strength test, split tensile test, and water absorption tests were conducted. The mix ratios for the plastic bricks for compressive and tensile strength are 1:3, 1:4, and 1:5.5, respectively, while their water absorption mix ratios are 1:2, 1:3, and 1:4. The experimental findings demonstrated that the bricks produced had good compressive strength, tensile strength and low water absorption rates. Additionally, it was observed that the manufactured bricks are lightweight, have a smooth surface and fine edges, and can be an excellent substitute for clay and conventional concrete blocks, which have been used for decades to build housing projects in the country.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133141369","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 : 2023-09-05DOI: 10.9734/jerr/2023/v25i8962
K. Dozie, M. U. Uwaezuoke
This article presents the condition(s) under which the multiplicative model with the error variances best describes the pattern in an observed time series, while comparing it with those of the additive and mixed models. The method of estimation is based on the periodic, seasonal and overall averages and variances of time series data arranged in a Buys-Ballot table. The method assumes that (1) the underlying distribution of the variable, X i j , i = 1, 2, ..., m , j = 1 , 2 , ..., s , under study is normal. (2) the trending curve is linear (3) the decomposition method is either additive or multiplicative or mixed. For multiplicative model, the error variance is not known and needs to be estimated with time series data. For additive and mixed models, the error variances are known and assumed to be equal to 1. Result shows that, under the stated assumptions, the seasonal variances of the Buys-Ballot table, for multiplicative model, a function of column ( j ) through the seasonal component S2j with error variance.
本文提出了带误差方差的乘法模型最能描述观测时间序列模式的条件，并将其与加性模型和混合模型进行了比较。估计方法是根据在投票表中排列的时间序列数据的周期性、季节性和总体平均值和方差。该方法假定(1)变量X i j, i = 1,2，…的底层分布， m, j = 1,2，…， s，在研究中是正常的。(2)趋势曲线为线性;(3)分解方法为加性、乘性或混合性。对于乘法模型，误差方差是未知的，需要用时间序列数据进行估计。对于加性模型和混合模型，误差方差是已知的，并假定为等于1。结果表明，在规定的假设下，对投票表的季节方差，对于乘法模型，列(j)的函数通过季节分量S2j与误差方差。
{"title":"The Proposed Buys-Ballot Estimates for Multiplicative Model with the Error Variances","authors":"K. Dozie, M. U. Uwaezuoke","doi":"10.9734/jerr/2023/v25i8962","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i8962","url":null,"abstract":"This article presents the condition(s) under which the multiplicative model with the error variances best describes the pattern in an observed time series, while comparing it with those of the additive and mixed models. The method of estimation is based on the periodic, seasonal and overall averages and variances of time series data arranged in a Buys-Ballot table. The method assumes that (1) the underlying distribution of the variable, X i j , i = 1, 2, ..., m , j = 1 , 2 , ..., s , under study is normal. (2) the trending curve is linear (3) the decomposition method is either additive or multiplicative or mixed. For multiplicative model, the error variance is not known and needs to be estimated with time series data. For additive and mixed models, the error variances are known and assumed to be equal to 1. Result shows that, under the stated assumptions, the seasonal variances of the Buys-Ballot table, for multiplicative model, a function of column ( j ) through the seasonal component S2j with error variance.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127228194","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 : 2023-09-04DOI: 10.9734/jerr/2023/v25i8960
M. T. Bello, M. H. Bichi
The research is on the quality assessment of Sokoto water distribution networks. Sample coordinates of the study area were taken using GPS, the experiments were carried out at different consumer locations with thirty (30) samples of water collected weekly for four (4) weeks, to determine various purification parameters that are related to both bulk (kb) and wall (KW) reactions coefficients for Sokoto water distribution pipe network, these include residual chlorine, pH, dissolved oxygen (DO), temperature and conductivity. pH, dissolved oxygen (DO) and conductivity have average values ranging from 6.7 to 7.5; 1.1 to 6.5ppm; 310 to 520 μs/cm respectively and conform to the Nigerian Standard for Drinking Water Quality (NSDWQ), except temperature which has the average values between 29 oC, and 32.6oC, and the individual values between 26 oC, and 38.4oC, chlorine residual average values obtained, ranging from 0.11mg/l to 0.26mg/l with the lowest individual value obtained being 0.011mg/l. The age of water supply from the treatment plants in the distribution network is 6 hours and both first and second-order decay reactions were ascertained from the graph and first-order decay having the highest number of occurrences was used in Epanet 2.0 water quality modeling. The kb values ranged from 0.0025 to 0.013md-1. A total of 86 out of the 120 samples, which constitute 71.7% were straight lines which indicate first-order and thus, the average kb was determined to be 0.006/day (0.144/hour). It was observed that of all the 120 samples examined in the study, chlorine reaction with natural organic matter (NOM) was small. The average kw for Sokoto WDS was deduced to be 0.078m/h, considering, the following steel pipe conditions used in the network area. kW (ft/h), -α =-38.5, H-W C=150, kW = 38.5/150 = 0.257ft/h = 0.078m/h (-0.078m/h).
本研究为索科托供水管网质量评价研究。使用GPS获取研究区域的样本坐标，在不同的消费者位置进行实验，每周收集三十(30)个水样本，持续四(4)周，以确定与Sokoto配水管网的体积(kb)和壁(KW)反应系数相关的各种净化参数，包括余氯、pH、溶解氧(DO)、温度和电导率。pH、溶解氧(DO)和电导率的平均值为6.7 ~ 7.5;1.1 - 6.5ppm;除温度平均值在29℃~ 32.6℃之间，个别值在26℃~ 38.4oC之间外，其余氯残留量平均值在0.11mg/l ~ 0.26mg/l之间，个别值最低为0.011mg/l。从配网中的处理厂供水年龄为6小时，从图中确定了一阶和二阶衰变反应，并在Epanet 2.0水质建模中使用了出现次数最多的一阶衰变。kb的取值范围为0.0025 ~ 0.013md-1。120个样本中有86个样本(占71.7%)为直线，表示一阶，因此，确定平均kb为0.006/天(0.144/小时)。研究发现，在120个样品中，氯与天然有机物(NOM)的反应很小。考虑到网络区域使用的钢管条件，索科托WDS的平均kw为0.078m/h。千瓦(ft / h) -α= -38.5,H-W C = 150千瓦= 38.5/150 = 0.257英尺/ h = 0.078 m / h (-0.078 m / h)。
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Pub Date : 2023-09-04DOI: 10.9734/jerr/2023/v25i8961
Yapeng Liu
The identification of bridge structural damage can be divided into four processes: determining whether there is damage, determining the location of the damage, determining the degree of damage, and evaluating the load-bearing capacity of the bridge structure after the damage occurs. The dynamic response data takes modal parameters as characteristic parameters, and the modal parameters of the bridge structure are independent of external loads, reflecting the structural characteristics of the structure itself. This article introduces five methods for damage identification based on dynamic characteristics, analyzes the identification principles, characteristics, and applications of each method, and summarizes their application conditions.
{"title":"Research on Bridge Damage Identification Method Based on Dynamic Characteristics","authors":"Yapeng Liu","doi":"10.9734/jerr/2023/v25i8961","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i8961","url":null,"abstract":"The identification of bridge structural damage can be divided into four processes: determining whether there is damage, determining the location of the damage, determining the degree of damage, and evaluating the load-bearing capacity of the bridge structure after the damage occurs. The dynamic response data takes modal parameters as characteristic parameters, and the modal parameters of the bridge structure are independent of external loads, reflecting the structural characteristics of the structure itself. This article introduces five methods for damage identification based on dynamic characteristics, analyzes the identification principles, characteristics, and applications of each method, and summarizes their application conditions.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"17 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120909999","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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