Dayhanna S. Vargas, Andrés C. Vélez, Christian J. Yépez, Juan J. Bravo, Juan C. Osorio
The potato is one of the main agricultural products in Colombia and is the second most important crop in the country. The production of this tuber represents 3.3% of the country’s agricultural gross domestic product (GDP). More than 100,000 producer families subsist on cultivation at the national level, the vast majority of which are smallholdings. However, smallholders are not able to exploit the full potential of this activity, and one of the main factors that does not allow for improving productivity is the inefficient use of land in agricultural activities. This leads to issues such as erosion, overexploitation of soil resources, reduced productivity, and, depending on the time of year, even an excess of potato supply. Therefore, a multicriteria methodology is proposed based on the key elements of the potato crop production cycle and its environment, made up of farmers from the municipality of Ventaquemada, located in Boyacá, where potato cultivation is a traditional practice. This department is the second-largest potato-producing department in the country. A review of the literature was carried out to determine and characterise the area of the selected department, and based on the above, the relevant criteria were defined and the alternatives to be evaluated were identified. Second, the proposed model is evaluated with its respective prioritisation process of both the criteria and the alternatives according to the analytic hierarchy process (AHP) methodology. Finally, the results of the model are presented, prioritizing the type of tillage, irrigation method, seed type, and its disinfection process for potato cultivation. This takes into account topographic and climatic conditions, the ecosystem, soil type, implementation costs, among other factors specific to the case study.
{"title":"Multicriteria Methodology for the Efficient Programming of Agricultural Cultivation Activities in a Colombian Region","authors":"Dayhanna S. Vargas, Andrés C. Vélez, Christian J. Yépez, Juan J. Bravo, Juan C. Osorio","doi":"10.1155/2023/1988392","DOIUrl":"https://doi.org/10.1155/2023/1988392","url":null,"abstract":"The potato is one of the main agricultural products in Colombia and is the second most important crop in the country. The production of this tuber represents 3.3% of the country’s agricultural gross domestic product (GDP). More than 100,000 producer families subsist on cultivation at the national level, the vast majority of which are smallholdings. However, smallholders are not able to exploit the full potential of this activity, and one of the main factors that does not allow for improving productivity is the inefficient use of land in agricultural activities. This leads to issues such as erosion, overexploitation of soil resources, reduced productivity, and, depending on the time of year, even an excess of potato supply. Therefore, a multicriteria methodology is proposed based on the key elements of the potato crop production cycle and its environment, made up of farmers from the municipality of Ventaquemada, located in Boyacá, where potato cultivation is a traditional practice. This department is the second-largest potato-producing department in the country. A review of the literature was carried out to determine and characterise the area of the selected department, and based on the above, the relevant criteria were defined and the alternatives to be evaluated were identified. Second, the proposed model is evaluated with its respective prioritisation process of both the criteria and the alternatives according to the analytic hierarchy process (AHP) methodology. Finally, the results of the model are presented, prioritizing the type of tillage, irrigation method, seed type, and its disinfection process for potato cultivation. This takes into account topographic and climatic conditions, the ecosystem, soil type, implementation costs, among other factors specific to the case study.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"32 19","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138974790","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}
Inarguably, saving is very important for the life of a senior citizen. Artificial neural network (ANN) and multiple linear regression (MLR) analyses have been successfully used to predict and analyze factors affecting the savings of people in several regions of the world. Many studies concluded that ANN is more efficient than MLR. However, some studies concluded that MLR is more efficient. To investigate this issue further, this study directly compared the efficiencies of unoptimized ANN and MLR in predicting and analyzing factors affecting the savings of people in the central region of Thailand in 2019, based on secondary data from a household socioeconomic survey, i.e., the National Statistical Staff Household Income Survey. The data were collected from January 2019 to December 2019 from questionnaires distributed to samples of households. The savings of people in the 25 provinces of Thailand were investigated with MLR and unoptimized ANN. Their prediction efficiencies were compared in terms of root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and processing time. The results showed that for all categories of savings—savings of low-, middle-, and high-income households—MLR was faster in processing time. It also provided a lower RMSE and a higher R2 than the unoptimized ANN. Nevertheless, unoptimized ANN provided a lower MAE than MLR for the savings of low- and high-income household data. The most important factor affecting the savings of low-, middle-, and high-income households was the factor of deposit interest, bond, share dividends, and other types of investment.
{"title":"Efficiency Comparison of Prediction Methods and Analysis of Factors Affecting Savings of People in the Central Region of Thailand","authors":"Achara Phaeobang, Saichon Sinsomboonthong","doi":"10.1155/2023/1388200","DOIUrl":"https://doi.org/10.1155/2023/1388200","url":null,"abstract":"Inarguably, saving is very important for the life of a senior citizen. Artificial neural network (ANN) and multiple linear regression (MLR) analyses have been successfully used to predict and analyze factors affecting the savings of people in several regions of the world. Many studies concluded that ANN is more efficient than MLR. However, some studies concluded that MLR is more efficient. To investigate this issue further, this study directly compared the efficiencies of unoptimized ANN and MLR in predicting and analyzing factors affecting the savings of people in the central region of Thailand in 2019, based on secondary data from a household socioeconomic survey, i.e., the National Statistical Staff Household Income Survey. The data were collected from January 2019 to December 2019 from questionnaires distributed to samples of households. The savings of people in the 25 provinces of Thailand were investigated with MLR and unoptimized ANN. Their prediction efficiencies were compared in terms of root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and processing time. The results showed that for all categories of savings—savings of low-, middle-, and high-income households—MLR was faster in processing time. It also provided a lower RMSE and a higher R2 than the unoptimized ANN. Nevertheless, unoptimized ANN provided a lower MAE than MLR for the savings of low- and high-income household data. The most important factor affecting the savings of low-, middle-, and high-income households was the factor of deposit interest, bond, share dividends, and other types of investment.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"54 8","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138592050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The replacement of the loading zone is not considered in the active calculation method on fatigue life of remanufactured bearings. In practical application, when the radial bearings are reinstalled after remanufacturing, it is required to replace the loading zone, which results in a large deviation between the calculated fatigue life according to the active calculation method and the actual life. In this paper, the fatigue life factors of radial bearings with different remanufacturing levels are calculated according to the actual application condition. The results of case studies show that with the improvement of the remanufacturing level, regardless of whether the loading zone is replaced or not, the remanufacturing bearing life factor is gradually increased and the maximum can reach 1. Considering the replacement of the loading zone, the life factors of remanufactured bearings with different fixed rings are also very different, among which the remanufacturing deviation of fixed outer-ring level II is the largest, reaching 11.3%. However, with the increase of the remanufacturing level, the deviation decreases gradually. The life factors by the method presented in this paper of remanufactured radial bearings with the replaced loading zone are significantly higher than those of the active calculation method. The research results of this paper provides a more accurate calculation scheme for the fatigue life of remanufactured radial rolling bearings, which is a supplement to the active calculation method and has important practical significance for the practice of bearing remanufacturing engineering.
{"title":"Fatigue Life Analysis of Remanufactured Radial Rolling Bearing with the Replaced Loading Zone","authors":"L. Chen, D. T. Bu, Z. B. Feng, H. B. Liu","doi":"10.1155/2023/6038824","DOIUrl":"https://doi.org/10.1155/2023/6038824","url":null,"abstract":"The replacement of the loading zone is not considered in the active calculation method on fatigue life of remanufactured bearings. In practical application, when the radial bearings are reinstalled after remanufacturing, it is required to replace the loading zone, which results in a large deviation between the calculated fatigue life according to the active calculation method and the actual life. In this paper, the fatigue life factors of radial bearings with different remanufacturing levels are calculated according to the actual application condition. The results of case studies show that with the improvement of the remanufacturing level, regardless of whether the loading zone is replaced or not, the remanufacturing bearing life factor is gradually increased and the maximum can reach 1. Considering the replacement of the loading zone, the life factors of remanufactured bearings with different fixed rings are also very different, among which the remanufacturing deviation of fixed outer-ring level II is the largest, reaching 11.3%. However, with the increase of the remanufacturing level, the deviation decreases gradually. The life factors by the method presented in this paper of remanufactured radial bearings with the replaced loading zone are significantly higher than those of the active calculation method. The research results of this paper provides a more accurate calculation scheme for the fatigue life of remanufactured radial rolling bearings, which is a supplement to the active calculation method and has important practical significance for the practice of bearing remanufacturing engineering.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"32 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138596597","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}
Sensible and judicious utilization of water for agriculture in conjunction with prediction techniques increases the crop yield. The Ethiopian economy relies on and is exclusively dependent on agricultural-based activities. Different soil compositions (nitrogen, phosphorous, and potassium), crop alternation, soil dampness, and climate conditions play an imperative contribution in cultivation. The primary purpose of this study was to conduct a machine learning approach which can be practiced dynamically for efficient farming at a low cost. The support vector machine (SVM) was applied as a machine learning procedure, whereas long short-term memory (LSTM) and the recurrent neural network (RNN) were considered as deep learning procedures. The research comprised a model that is combined with machine learning procedures (ANN, random forest, and decision tree) to know efficient and appropriate crop types. The planned model is improved through conducting deep learning methods incorporated to the existing practice for different crop condition. Pure data and related evidence are attained concerning the quantities of soil constituents desired through their expenditures distinctly. It delivers well precision as compared to the current model examining the specified documents and assisting the local agronomists in forecasting different types of crop and gain benefits. In RNN, LSTM, and SVM algorithms, the accuracy is determined as 96% which is comparatively preferable as compared to other machine learning procedures under different feature and crop types. The techniques are evaluated in terms of percentage in prediction accuracy. The results generated are important for agrarians, experts, researchers, and local farmers to maximize the crop productivity and help to enhance agriculture and climate change-related decisions, especially in low-to-middle-income countries.
{"title":"Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia","authors":"A. Ayalew, T. K. Lohani","doi":"10.1155/2023/6675523","DOIUrl":"https://doi.org/10.1155/2023/6675523","url":null,"abstract":"Sensible and judicious utilization of water for agriculture in conjunction with prediction techniques increases the crop yield. The Ethiopian economy relies on and is exclusively dependent on agricultural-based activities. Different soil compositions (nitrogen, phosphorous, and potassium), crop alternation, soil dampness, and climate conditions play an imperative contribution in cultivation. The primary purpose of this study was to conduct a machine learning approach which can be practiced dynamically for efficient farming at a low cost. The support vector machine (SVM) was applied as a machine learning procedure, whereas long short-term memory (LSTM) and the recurrent neural network (RNN) were considered as deep learning procedures. The research comprised a model that is combined with machine learning procedures (ANN, random forest, and decision tree) to know efficient and appropriate crop types. The planned model is improved through conducting deep learning methods incorporated to the existing practice for different crop condition. Pure data and related evidence are attained concerning the quantities of soil constituents desired through their expenditures distinctly. It delivers well precision as compared to the current model examining the specified documents and assisting the local agronomists in forecasting different types of crop and gain benefits. In RNN, LSTM, and SVM algorithms, the accuracy is determined as 96% which is comparatively preferable as compared to other machine learning procedures under different feature and crop types. The techniques are evaluated in terms of percentage in prediction accuracy. The results generated are important for agrarians, experts, researchers, and local farmers to maximize the crop productivity and help to enhance agriculture and climate change-related decisions, especially in low-to-middle-income countries.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"13 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138602895","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 : 2023-12-02DOI: 10.31026/j.eng.2023.12.05
H. Rashid
The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storage capacity of the reservoir within two elevations. According to the study results, the live storage capacity of Dukan Reservoir at elevation 511.78 m had decreased from 8000 MCM to 7007.77MCM and 6923.53 MCM using NDWI and MNDWI respectively, due to sedimentation, resulting in a capacity loss of 14.59% and 15.83% for NDWI and MNDWI respectively. The annual sedimentation was 13.78 MCM and 14.95 MCM for NDWI and MNDWI, respectively. Joglekar's equation and Khosla's formula have demonstrated that the sedimentation rate in the Dukan reservoir exceeds the critical rate. The findings of this study will inform the development of sediment management strategies aimed at preserving the reservoir's capacity.
{"title":"Reservoir Sedimentation Assessment Using Geospatial Technology: A case Study of Dukan Reservoir, Sulaimani Governorate, Kurdistan Region, Iraq","authors":"H. Rashid","doi":"10.31026/j.eng.2023.12.05","DOIUrl":"https://doi.org/10.31026/j.eng.2023.12.05","url":null,"abstract":"The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storage capacity of the reservoir within two elevations. According to the study results, the live storage capacity of Dukan Reservoir at elevation 511.78 m had decreased from 8000 MCM to 7007.77MCM and 6923.53 MCM using NDWI and MNDWI respectively, due to sedimentation, resulting in a capacity loss of 14.59% and 15.83% for NDWI and MNDWI respectively. The annual sedimentation was 13.78 MCM and 14.95 MCM for NDWI and MNDWI, respectively. Joglekar's equation and Khosla's formula have demonstrated that the sedimentation rate in the Dukan reservoir exceeds the critical rate. The findings of this study will inform the development of sediment management strategies aimed at preserving the reservoir's capacity.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"111 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607650","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 : 2023-12-02DOI: 10.31026/j.eng.2023.12.08
Mohammed Saleh Mohammed, M. D. Ahmed
The complexity and partially defined nature of jet grouting make it hard to predict the performance of grouted piles. So the trials of cement injection at a location with similar soil properties as the erecting site are necessary to assess the performance of the grouted piles. Nevertheless, instead of executing trial-injected piles at the pilot site, which wastes money, time, and effort, the laboratory cement injection devices are essential alternatives for evaluating soil injection ability. This study assesses the performance of a low-pressure laboratory grouting device by improving loose sandy soil injected using binders formed of Silica Fume (SF) as a chemical admixture (10% of Ordinary Portland Cement OPC mass) to different (W/C) water/cement ratios (by mass materials) mixes. Trial grouting processes were executed to optimize the practical ranges of the operating factors of the laboratory device to obtain consistent grouted model pile samples. The paper examined the relations of the binders' W/C ratios with the densities, elasticity modulus (E), and Uniaxial Compression Stress (UCS) of the grouted piles. The investigation results show that as the binder W/C ratio rises, the grouted pile samples' dry density, E, and UCS values decrease. For the binder injected with a W/C ratio of one and 10% SF additive by weight of cement mass, the highest values of the grouted pile for density, E, and UCS were about 2.32 g/cm3, 23 MPa, and 2000 MPa, respectively. The UCS of the grouted pile proved that the binders' W/C ratios and the SF addition have an evident effect on the investigated factors of the grouted piles.
{"title":"Performance Assessment of Pile Models Chemically Grouted by Low-Pressure Injection Laboratory Device for Improving Loose Sand","authors":"Mohammed Saleh Mohammed, M. D. Ahmed","doi":"10.31026/j.eng.2023.12.08","DOIUrl":"https://doi.org/10.31026/j.eng.2023.12.08","url":null,"abstract":"The complexity and partially defined nature of jet grouting make it hard to predict the performance of grouted piles. So the trials of cement injection at a location with similar soil properties as the erecting site are necessary to assess the performance of the grouted piles. Nevertheless, instead of executing trial-injected piles at the pilot site, which wastes money, time, and effort, the laboratory cement injection devices are essential alternatives for evaluating soil injection ability. This study assesses the performance of a low-pressure laboratory grouting device by improving loose sandy soil injected using binders formed of Silica Fume (SF) as a chemical admixture (10% of Ordinary Portland Cement OPC mass) to different (W/C) water/cement ratios (by mass materials) mixes. Trial grouting processes were executed to optimize the practical ranges of the operating factors of the laboratory device to obtain consistent grouted model pile samples. The paper examined the relations of the binders' W/C ratios with the densities, elasticity modulus (E), and Uniaxial Compression Stress (UCS) of the grouted piles. The investigation results show that as the binder W/C ratio rises, the grouted pile samples' dry density, E, and UCS values decrease. For the binder injected with a W/C ratio of one and 10% SF additive by weight of cement mass, the highest values of the grouted pile for density, E, and UCS were about 2.32 g/cm3, 23 MPa, and 2000 MPa, respectively. The UCS of the grouted pile proved that the binders' W/C ratios and the SF addition have an evident effect on the investigated factors of the grouted piles.\u0000 ","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"71 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606607","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 : 2023-12-02DOI: 10.31026/j.eng.2023.12.12
I. Muhsin
The construction sector is considered an important and influential pivot in the national economy of any country. Nations are working to develop this sector, receiving modern and developed techniques. So, this sector can be a carrier or a receiver of modern technologies. The cost of technology transfer between the international companies that sponsor this sector is a matter of great importance, especially since different factors affect the need for this advanced technology. The cost of technology transfer in construction is related to multiple factors presented by Knowledge, equipment, plant, hardware and software. The lack of distinguishing and evaluating the direct and indirect costs in the construction sector during technology transfer may lead to infractions in the company's budget. This manuscript aims to investigate the direct and indirect costs of transferring technology and the major factors constrained by this process. This work adopted a theoretical study and investigated the opinions of experts and engineers (by questionnaire) working in different construction sites. This Manuscript showed that the largest weight of the cost for both modern equipment and counsulant/designers is a direct cost and indirect cost, respectively, for transferring technology in the construction sector.
{"title":"The Cost of Technology Transfer in Construction Companies (In Iraq)","authors":"I. Muhsin","doi":"10.31026/j.eng.2023.12.12","DOIUrl":"https://doi.org/10.31026/j.eng.2023.12.12","url":null,"abstract":"The construction sector is considered an important and influential pivot in the national economy of any country. Nations are working to develop this sector, receiving modern and developed techniques. So, this sector can be a carrier or a receiver of modern technologies. The cost of technology transfer between the international companies that sponsor this sector is a matter of great importance, especially since different factors affect the need for this advanced technology. The cost of technology transfer in construction is related to multiple factors presented by Knowledge, equipment, plant, hardware and software. The lack of distinguishing and evaluating the direct and indirect costs in the construction sector during technology transfer may lead to infractions in the company's budget. This manuscript aims to investigate the direct and indirect costs of transferring technology and the major factors constrained by this process. This work adopted a theoretical study and investigated the opinions of experts and engineers (by questionnaire) working in different construction sites. This Manuscript showed that the largest weight of the cost for both modern equipment and counsulant/designers is a direct cost and indirect cost, respectively, for transferring technology in the construction sector.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"84 26","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138605996","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 : 2023-12-02DOI: 10.31026/j.eng.2023.12.09
Abeer Ahmed Ali, Faten Abd Ali Dawood
Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed classification model is divided into three major phases, including pre-processing, training the Resnet-50 network, and classification with evaluation. In the first phase, pre-processing techniques are applied to the APTOS2019 fundus images dataset to find the best features and highlight some fine details of these images. The resnet-50 network was trained in the second phase using the training set and saved the best model obtained that gives high accuracy during the training process. Finally, this saved model has been implemented on the testing dataset for classification DR grades. The proposed model shows good and best classification performance, which was obtained with an accuracy of 98.3%, a precision of 98.4%, an F1-Score of 98.5 % and the recall of 98.4%.
{"title":"Deep Learning of Diabetic Retinopathy Classification in Fundus Images","authors":"Abeer Ahmed Ali, Faten Abd Ali Dawood","doi":"10.31026/j.eng.2023.12.09","DOIUrl":"https://doi.org/10.31026/j.eng.2023.12.09","url":null,"abstract":"Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed classification model is divided into three major phases, including pre-processing, training the Resnet-50 network, and classification with evaluation. In the first phase, pre-processing techniques are applied to the APTOS2019 fundus images dataset to find the best features and highlight some fine details of these images. The resnet-50 network was trained in the second phase using the training set and saved the best model obtained that gives high accuracy during the training process. Finally, this saved model has been implemented on the testing dataset for classification DR grades. The proposed model shows good and best classification performance, which was obtained with an accuracy of 98.3%, a precision of 98.4%, an F1-Score of 98.5 % and the recall of 98.4%.\u0000 ","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"69 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606471","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 : 2023-12-02DOI: 10.31026/j.eng.2023.12.04
Saifullah Omar Mohammed, K. R. Erzaij
Institutions and companies are looking to reduce spending on buildings and services according to scientific methods, provided they reach the same purpose but at a lower cost. On this basis, this paper proposes a model to measure and reduce maintenance costs in one of the public sector institutions in Iraq by using performance indicators that fit the nature of the work of this institution and the available data. The paper relied on studying the nature of the institution’s work in the maintenance field and looking at the type of data available to know the type and number of appropriate indicators to create the model. Maintenance data were collected for the previous six years by reviewing the maintenance and financial department records. On this basis, three performance indicators are proposed in creating the model. The result is a model to reduce maintenance costs based on three indicators; each indicator contains a baseline value and a target value. If this model is applied, it will significantly help measure, track, control, and reduce maintenance costs in government institutions.
{"title":"Reducing Maintenance Costs for Government Projects in Iraq Using Performance Indicators","authors":"Saifullah Omar Mohammed, K. R. Erzaij","doi":"10.31026/j.eng.2023.12.04","DOIUrl":"https://doi.org/10.31026/j.eng.2023.12.04","url":null,"abstract":"Institutions and companies are looking to reduce spending on buildings and services according to scientific methods, provided they reach the same purpose but at a lower cost. On this basis, this paper proposes a model to measure and reduce maintenance costs in one of the public sector institutions in Iraq by using performance indicators that fit the nature of the work of this institution and the available data. The paper relied on studying the nature of the institution’s work in the maintenance field and looking at the type of data available to know the type and number of appropriate indicators to create the model. Maintenance data were collected for the previous six years by reviewing the maintenance and financial department records. On this basis, three performance indicators are proposed in creating the model. The result is a model to reduce maintenance costs based on three indicators; each indicator contains a baseline value and a target value. If this model is applied, it will significantly help measure, track, control, and reduce maintenance costs in government institutions.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"120 24","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606999","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 : 2023-12-02DOI: 10.31026/j.eng.2023.12.06
H. R. Abed, H. A. Rashid
In Iraq, more than 1031 school projects have been halted due to disputes and claims resulting from financial, contractual, or other issues. This research aims to identify, prioritize, and allocate the most critical risk factors that threaten these projects’ success for the duration (2017-2022). Based on a multi-step methodology developed through systematic literature reviews, realistic case studies, and semi-structured interviews, 47 risk factors were identified. Based on 153 verified responses, the survey reveals that the top-ranked risk factors are corruption and bribery, delaying the payments of the financial dues to the contractors or sub-contractors, absence of risk management strategy, multiple change orders due to changing designs and specifications during construction; inaccuracy in time and budget estimation; construction material price; financial and economic crisis/financial instability; selecting the contractor only based on the lowest bid, regardless of technical competence; instability within the political system of the government/instability of the government as a client; foreign exchange rates fluctuate against the Iraqi dinar. The study also showed that the respondents recommended allocating four risks to the owner, eight risk factors to the contractor, one risk to the consultant, and 32 factors allocated as shared. The study concluded that the results could help identify the most critical risks facing this type of project and the contracting party that can bear the risks and manage them efficiently.
{"title":"Empirical Study for Capturing and Allocating Significant Risk Factors in School Construction Projects in Iraq","authors":"H. R. Abed, H. A. Rashid","doi":"10.31026/j.eng.2023.12.06","DOIUrl":"https://doi.org/10.31026/j.eng.2023.12.06","url":null,"abstract":"In Iraq, more than 1031 school projects have been halted due to disputes and claims resulting from financial, contractual, or other issues. This research aims to identify, prioritize, and allocate the most critical risk factors that threaten these projects’ success for the duration (2017-2022). Based on a multi-step methodology developed through systematic literature reviews, realistic case studies, and semi-structured interviews, 47 risk factors were identified. Based on 153 verified responses, the survey reveals that the top-ranked risk factors are corruption and bribery, delaying the payments of the financial dues to the contractors or sub-contractors, absence of risk management strategy, multiple change orders due to changing designs and specifications during construction; inaccuracy in time and budget estimation; construction material price; financial and economic crisis/financial instability; selecting the contractor only based on the lowest bid, regardless of technical competence; instability within the political system of the government/instability of the government as a client; foreign exchange rates fluctuate against the Iraqi dinar. The study also showed that the respondents recommended allocating four risks to the owner, eight risk factors to the contractor, one risk to the consultant, and 32 factors allocated as shared. The study concluded that the results could help identify the most critical risks facing this type of project and the contracting party that can bear the risks and manage them efficiently.","PeriodicalId":15716,"journal":{"name":"Journal of Engineering","volume":"77 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606024","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：