Pub Date : 2024-12-01DOI: 10.1016/j.jer.2023.08.004
Zhongbin Wang, Lei Si, Dong Wei, Jinheng Gu, Fulin Xu
Accurate recognition of coal-rock drilling sates is a prerequisite for achieving intelligent drilling pressure relief. In this paper, a novel coal-rock drilling states recognition method of drilling robot for rockburst prevention is proposed. Firstly, different coal-rock drilling signals are collected and processed by using improved antlion optimization (ALO) algorithm and variational mode decomposition (VMD). Meanwhile, the elite opposition-based learning (EOL) strategy is used to improve the global search ability and optimization performance of ALO, and the EOL-ALO is developed and employed to automatically search the optimal key parameters of VMD. Subsequently, the root mean square of frequency and kurtosis are used to extract the feature information from the decomposed signals and the singular value decomposition method is employed to reduce the dimensionality of high-dimensional feature vectors. Furthermore, an improved D-S evidence theory is developed to fuse the recognition results of support vector machine through a single sensor information and the fusion recognition framework of coal-rock drilling states is designed. Finally, a coal-rock drilling experimental platform is established and some experimental analysis is carried out. The experimental results indicate the feasibility and superiority of proposed coal-rock drilling states recognition method.
{"title":"Coal-rock drilling states recognition of drilling robot for rockburst prevention based on multi-sensor information fusion","authors":"Zhongbin Wang, Lei Si, Dong Wei, Jinheng Gu, Fulin Xu","doi":"10.1016/j.jer.2023.08.004","DOIUrl":"10.1016/j.jer.2023.08.004","url":null,"abstract":"<div><div>Accurate recognition of coal-rock drilling sates is a prerequisite for achieving intelligent drilling pressure relief. In this paper, a novel coal-rock drilling states recognition method of drilling robot for rockburst prevention is proposed. Firstly, different coal-rock drilling signals are collected and processed by using improved antlion optimization (ALO) algorithm and variational mode decomposition (VMD). Meanwhile, the elite opposition-based learning (EOL) strategy is used to improve the global search ability and optimization performance of ALO, and the EOL-ALO is developed and employed to automatically search the optimal key parameters of VMD. Subsequently, the root mean square of frequency and kurtosis are used to extract the feature information from the decomposed signals and the singular value decomposition method is employed to reduce the dimensionality of high-dimensional feature vectors. Furthermore, an improved D-S evidence theory is developed to fuse the recognition results of support vector machine through a single sensor information and the fusion recognition framework of coal-rock drilling states is designed. Finally, a coal-rock drilling experimental platform is established and some experimental analysis is carried out. The experimental results indicate the feasibility and superiority of proposed coal-rock drilling states recognition method.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 878-885"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83187524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jer.2023.07.002
Arulampalam Kunaraj , P. Chelvanathan , Ahmad Ashrif A Bakar , Iskandar Yahya
In the realm of optoelectronics to produce thin film, SWCNT (Single-Walled Carbon Nanotube) is a promising alternative to Indium Tin Oxide (ITO). However, it is still challenging to manufacture SWCNT thin film that is low-cost, homogenous and has minimal sheet resistance. In this work, SWCNT thin films were deposited by using the automated spray coating method. To enhance the film quality and optoelectronic characteristics, post-deposition treatment through nitric acid vapor was carried out. The optimized SWCNT thin films exhibited optical transparency in the range of 60.4% at 800 nm and sheet resistance of 6.6 Ω/square. The sheet resistance of our fabricated SWCNT thin films was lower than the value of ITO films (10 Ω/square), putting forth evidence which suggests the potential of SWCNTs as an alternative to ITO.
{"title":"Single-Walled Carbon Nanotube (SWCNT) thin films via automatic spray coating and nitric acid vapor treatment","authors":"Arulampalam Kunaraj , P. Chelvanathan , Ahmad Ashrif A Bakar , Iskandar Yahya","doi":"10.1016/j.jer.2023.07.002","DOIUrl":"10.1016/j.jer.2023.07.002","url":null,"abstract":"<div><div>In the realm of optoelectronics to produce thin film, SWCNT (Single-Walled Carbon Nanotube) is a promising alternative to Indium Tin Oxide (ITO). However, it is still challenging to manufacture SWCNT thin film that is low-cost, homogenous and has minimal sheet resistance. In this work, SWCNT thin films were deposited by using the automated spray coating method. To enhance the film quality and optoelectronic characteristics, post-deposition treatment through nitric acid vapor was carried out. The optimized SWCNT thin films exhibited optical transparency in the range of 60.4% at 800 nm and sheet resistance of 6.6 Ω/square. The sheet resistance of our fabricated SWCNT thin films was lower than the value of ITO films (10 Ω/square), putting forth evidence which suggests the potential of SWCNTs as an alternative to ITO.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 825-831"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77388314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jer.2024.04.006
Peter L. Bishay, Toby McKinney, Garrett Kline, Maria Manzo, Arthur Parian, Derenik Bakhshi, Andrew Langwald, Abraham Ortega, Matthew Gagnon, Gerbert Funes Alfaro
Wind turbines form an increasingly important source of renewable and sustainable energy. Traditional rigid wind turbine blades are unable to control the flow of air over their surfaces, resulting in higher loads and lower aerodynamic efficiency at non-optimal wind speeds and angles of attack. This paper presents the design of SCAMORSA-1 (“Sliding CAmber- MORphing Skin Action”), a camber-morphing turbine blade in a small scale Horizontal Axis Wind Turbine (HAWT) for increased aerodynamic efficiency and improved extreme load alleviation. The blade is linearly tapered and comprises three sections: a conventional rigid section, a morphing section, and a fixed blade tip, all covered by functionally graded composite skin. Measured from the root, the rigid section spans 0%-60% of the total blade length and its profile transitions at 20% from SD7062 thick airfoil to the thinner SD7037 airfoil. The rigid section includes carbon fiber composite spars that resist flap-wise bending. The morphing section occupies the next 30% of the span with SD2030 airfoil profile and can seamlessly change camber angle up to 10°. This section is composed of three hybrid ribs connected via two leading-edge composite spars and a trailing-edge synchronizing rod. Each hybrid rib has a solid leading-edge segment connected to a flexible trailing-edge segment via T-slots. The trailing-edge segment, where morphing occurs, is an enhanced version of the corrugated FishBAC design, with hexagonal honeycomb infill that increases the out-of-plane stiffness and allows for morphing deformation without internal buckling. Two of these hybrid ribs have servomotors housed in the leading-edge segment. These integrated actuators in the hybrid ribs actuate flexible carbon fiber ribbons that run through slits in the trailing-edge segment to morph it. At the trailing-edge portion of the morphing section, the composite skin transitions to a thin flexible layer that can slide over the deforming trailing-edge segment via skin sliders. Computational simulations were performed to quantify the performance gains and ensure safe operation of all components. A proof-of-concept model of SCAMORSA-1’s morphing section was manufactured and tested to demonstrate the effectiveness of the design.
{"title":"SCAMORSA-1: A camber-morphing wind turbine blade with sliding composite skin","authors":"Peter L. Bishay, Toby McKinney, Garrett Kline, Maria Manzo, Arthur Parian, Derenik Bakhshi, Andrew Langwald, Abraham Ortega, Matthew Gagnon, Gerbert Funes Alfaro","doi":"10.1016/j.jer.2024.04.006","DOIUrl":"10.1016/j.jer.2024.04.006","url":null,"abstract":"<div><div>Wind turbines form an increasingly important source of renewable and sustainable energy. Traditional rigid wind turbine blades are unable to control the flow of air over their surfaces, resulting in higher loads and lower aerodynamic efficiency at non-optimal wind speeds and angles of attack. This paper presents the design of SCAMORSA-1 (“Sliding CAmber- MORphing Skin Action”), a camber-morphing turbine blade in a small scale Horizontal Axis Wind Turbine (HAWT) for increased aerodynamic efficiency and improved extreme load alleviation. The blade is linearly tapered and comprises three sections: a conventional rigid section, a morphing section, and a fixed blade tip, all covered by functionally graded composite skin. Measured from the root, the rigid section spans 0%-60% of the total blade length and its profile transitions at 20% from SD7062 thick airfoil to the thinner SD7037 airfoil. The rigid section includes carbon fiber composite spars that resist flap-wise bending. The morphing section occupies the next 30% of the span with SD2030 airfoil profile and can seamlessly change camber angle up to 10°. This section is composed of three hybrid ribs connected via two leading-edge composite spars and a trailing-edge synchronizing rod. Each hybrid rib has a solid leading-edge segment connected to a flexible trailing-edge segment via T-slots. The trailing-edge segment, where morphing occurs, is an enhanced version of the corrugated FishBAC design, with hexagonal honeycomb infill that increases the out-of-plane stiffness and allows for morphing deformation without internal buckling. Two of these hybrid ribs have servomotors housed in the leading-edge segment. These integrated actuators in the hybrid ribs actuate flexible carbon fiber ribbons that run through slits in the trailing-edge segment to morph it. At the trailing-edge portion of the morphing section, the composite skin transitions to a thin flexible layer that can slide over the deforming trailing-edge segment via skin sliders. Computational simulations were performed to quantify the performance gains and ensure safe operation of all components. A proof-of-concept model of SCAMORSA-1’s morphing section was manufactured and tested to demonstrate the effectiveness of the design.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 931-940"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140774437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jer.2024.03.014
Mahmuod Torabi Jefroudi , Soroush Avakh Darestani
Supplier selection is the basis of a successful supply chain. It is also a key factor in improving the competitiveness of an organization. Being a complex process, the supplier selection plays an important role in upgrading the supply chain. The purpose of this research is to present an integrated approach based on fuzzy best-worst method (BWM) and failure mode and effects analysis (FMEA) for sustainable supplier selection considering seasonal quantity discounts and supplier risk for a radiator manufacturing company. Therefore, as the aim implies, this study addresses how organizations develop a sustainable supplier selection framework by integrating linear programming and decision-making in presence of seasonal discounts. To this end, fuzzy BWM and FMEA were employed to calculate weighting factors for different selection criteria and evaluate the supplier risk, respectively. Then, suppliers were ranked using the so-called technique for order of preference by similarity to ideal solution (TOPSIS). Finally, the discount type was examined by the LP-metric method. Results of the fuzzy BWM showed that the customer satisfaction was the criterion of highest priority, followed by long-term relationship, and then pollution control, among the total of 13 criteria considered in this work. Outputs of the TOPSIS referred to the supplier 3 as the top-ranked supplier, followed by supplier 6 and then supplier 1.
{"title":"A decision support system for sustainable supplier selection problem: Evidence from a radiator manufacturing industry","authors":"Mahmuod Torabi Jefroudi , Soroush Avakh Darestani","doi":"10.1016/j.jer.2024.03.014","DOIUrl":"10.1016/j.jer.2024.03.014","url":null,"abstract":"<div><div>Supplier selection is the basis of a successful supply chain. It is also a key factor in improving the competitiveness of an organization. Being a complex process, the supplier selection plays an important role in upgrading the supply chain. The purpose of this research is to present an integrated approach based on fuzzy best-worst method (BWM) and failure mode and effects analysis (FMEA) for sustainable supplier selection considering seasonal quantity discounts and supplier risk for a radiator manufacturing company. Therefore, as the aim implies, this study addresses how organizations develop a sustainable supplier selection framework by integrating linear programming and decision-making in presence of seasonal discounts. To this end, fuzzy BWM and FMEA were employed to calculate weighting factors for different selection criteria and evaluate the supplier risk, respectively. Then, suppliers were ranked using the so-called technique for order of preference by similarity to ideal solution (TOPSIS). Finally, the discount type was examined by the LP-metric method. Results of the fuzzy BWM showed that the customer satisfaction was the criterion of highest priority, followed by long-term relationship, and then pollution control, among the total of 13 criteria considered in this work. Outputs of the TOPSIS referred to the supplier 3 as the top-ranked supplier, followed by supplier 6 and then supplier 1.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 867-877"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143216049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jer.2024.01.018
Franciskus Antonius
Fifth generation (5G) and sixth generation (6G) networks are examples of next-generation networks that need higher levels of safety, lower latency, and more capacity and dependability. Reconfigurable wireless connection slicing becomes essential for satisfying these sophisticated networks' requirements, enabling many network instances on the same hardware to improve Quality of Service (QoS). Nonetheless, the centrally managed resource allocation for network slicers presents difficulties, particularly as the quantity of User Equipment (UEs) increases. This puts pressure on Radio Resource Management (RRM) and makes slice customization more difficult. In order to address these issues, this study presents an organizational radio resource distribution architecture in which the neighborhood radio resource managers (LRRMs) receive sub channel allocations from the RRM in slices, and the LRRMs then distribute the assigned capabilities to the corresponding UEs. The suggested model, which runs in MATLAB, uses an original method called CNN-Game Theory to achieve an exceptional 98 % accuracy, outperforming CNN-LSTM, RNN, DeepCog, and DHOA by 29.27 %. This method combines ideas from game theory with neural network weight optimization to produce an improved model with increased efficiency and accuracy. Many experiments illustrate how effective this method is and how it can be used to improve different machine learning applications. Metrics like slice type utilization, average packet delay for each LTE/5G category, and others are used to assess game optimization for resource allocation
{"title":"Efficient resource allocation through CNN-game theory based network slicing recognition for next-generation networks","authors":"Franciskus Antonius","doi":"10.1016/j.jer.2024.01.018","DOIUrl":"10.1016/j.jer.2024.01.018","url":null,"abstract":"<div><div>Fifth generation (5G) and sixth generation (6G) networks are examples of next-generation networks that need higher levels of safety, lower latency, and more capacity and dependability. Reconfigurable wireless connection slicing becomes essential for satisfying these sophisticated networks' requirements, enabling many network instances on the same hardware to improve Quality of Service (QoS). Nonetheless, the centrally managed resource allocation for network slicers presents difficulties, particularly as the quantity of User Equipment (UEs) increases. This puts pressure on Radio Resource Management (RRM) and makes slice customization more difficult. In order to address these issues, this study presents an organizational radio resource distribution architecture in which the neighborhood radio resource managers (LRRMs) receive sub channel allocations from the RRM in slices, and the LRRMs then distribute the assigned capabilities to the corresponding UEs. The suggested model, which runs in MATLAB, uses an original method called CNN-Game Theory to achieve an exceptional 98 % accuracy, outperforming CNN-LSTM, RNN, DeepCog, and DHOA by 29.27 %. This method combines ideas from game theory with neural network weight optimization to produce an improved model with increased efficiency and accuracy. Many experiments illustrate how effective this method is and how it can be used to improve different machine learning applications. Metrics like slice type utilization, average packet delay for each LTE/5G category, and others are used to assess game optimization for resource allocation</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 793-805"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139635655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jer.2023.09.024
P. Tamilarasu , G. Singaravel
The task scheduling has a potential impact on overall system performance and resource utilization in the domain of Cloud Computing. Cloud computing adopts a cloud service provider (CSP) for facilitating access and delivering services to the shared resources. Task scheduling in clouds can be attained some symmetry form which helps in achieving predominant resource optimization that includes energy efficiency and load balancing. This task scheduling process of cloud computing pertains to the problem of Non-deterministic Polynomial (NP) which can be significantly solved using the techniques of metaheuristic optimization for enhancing the job scheduling effectiveness. In this paper, an Improved Coati Optimization Algorithm-based Task Scheduling (ICOATS) is presented for addressing the issues of lengthier scheduling time, high consumptions of cost and maximized load on Virtual Machine (VM) in cloud computing environment. In this proposed ICOATS, a model for distribution and scheduling of tasks is constructed using the factors of VMs, cost and time. It further included a multi-objective fitness function which targets on minimizing makespan, and at the same time maximizing the rate of resource utilization. It established possible plan for every coati with respect to task scheduling process that aids in determining the best solution (optimal assignment of incoming tasks to VMs). It is proposed with the capability of handing the problem of premature convergence by incorporating an exploitation strategy which improving the local search potential with well-balanced trade-off amid exploration and exploitation. The simulation results of this ICOATS approach under its evaluation with the existing metaheuristic task scheduling approaches confirmed better improvement in reducing makespan, and simultaneously enhances the turnaround efficiency, success rate and availability.
{"title":"Quality of service aware improved coati optimization algorithm for efficient task scheduling in cloud computing environment","authors":"P. Tamilarasu , G. Singaravel","doi":"10.1016/j.jer.2023.09.024","DOIUrl":"10.1016/j.jer.2023.09.024","url":null,"abstract":"<div><div>The task scheduling has a potential impact on overall system performance and resource utilization in the domain of Cloud Computing. Cloud computing adopts a cloud service provider (CSP) for facilitating access and delivering services to the shared resources. Task scheduling in clouds can be attained some symmetry form which helps in achieving predominant resource optimization that includes energy efficiency and load balancing. This task scheduling process of cloud computing pertains to the problem of Non-deterministic Polynomial (NP) which can be significantly solved using the techniques of metaheuristic optimization for enhancing the job scheduling effectiveness. In this paper, an Improved Coati Optimization Algorithm-based Task Scheduling (ICOATS) is presented for addressing the issues of lengthier scheduling time, high consumptions of cost and maximized load on Virtual Machine (VM) in cloud computing environment. In this proposed ICOATS, a model for distribution and scheduling of tasks is constructed using the factors of VMs, cost and time. It further included a multi-objective fitness function which targets on minimizing makespan, and at the same time maximizing the rate of resource utilization. It established possible plan for every coati with respect to task scheduling process that aids in determining the best solution (optimal assignment of incoming tasks to VMs). It is proposed with the capability of handing the problem of premature convergence by incorporating an exploitation strategy which improving the local search potential with well-balanced trade-off amid exploration and exploitation. The simulation results of this ICOATS approach under its evaluation with the existing metaheuristic task scheduling approaches confirmed better improvement in reducing makespan, and simultaneously enhances the turnaround efficiency, success rate and availability.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 768-780"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134917285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data envelopment analysis (DEA) is a non-parametric method to calculate the efficiency of decision-making units (DMU) under evaluation that perform the same activity. The frontier obtained by this method is a relative frontier accessible in the real world. Due to the uncertainty of the population distribution, the accuracy of the achieved efficiency is questioned. Therefore, this research aims to present a network data envelopment analysis model to evaluate the performance of a sustainable supply chain using bootstrap simulation. In this research, using the two-step approach of data envelopment analysis and the bootstrap method, the information collected from 25 tomato paste companies for the year 2021 has been analyzed. To illustrate the proposed method, a real case study is considered in the Iranian tomato paste supply chain network. The findings showed that using definitive data, 16 companies are efficient and 9 companies are inefficient, and using bootstrap simulation data, 4 companies are efficient and 21 companies are inefficient. Using the proposed framework, the overall efficiency value has been calculated in two cases using DEA and the bootstrap model. In addition, the efficiency of the stage is calculated separately. Based on the calculated results, if a DMU is considered efficient, its efficiency score is equal to 1 in each of the stages. Otherwise, the cause of the inefficiency of each DMU is identified. Also, based on the comparisons made between the proposed model and the basic models based on sensitivity analysis, the accuracy of the proposed bootstrap-based model in introducing the number of efficient units has been better than the basic models. Therefore, the accuracy of the used method can be concluded.
{"title":"A network data envelopment analysis to evaluate the performance of a sustainable supply chain using bootstrap simulation","authors":"Masoud Vaseei , Maryam Daneshmand-Mehr , Morteza Bazrafshan , Armin Ghane Kanafi","doi":"10.1016/j.jer.2023.10.003","DOIUrl":"10.1016/j.jer.2023.10.003","url":null,"abstract":"<div><div>Data envelopment analysis (DEA) is a non-parametric method to calculate the efficiency of decision-making units (DMU) under evaluation that perform the same activity. The frontier obtained by this method is a relative frontier accessible in the real world. Due to the uncertainty of the population distribution, the accuracy of the achieved efficiency is questioned. Therefore, this research aims to present a network data envelopment analysis model to evaluate the performance of a sustainable supply chain using bootstrap simulation. In this research, using the two-step approach of data envelopment analysis and the bootstrap method, the information collected from 25 tomato paste companies for the year 2021 has been analyzed. To illustrate the proposed method, a real case study is considered in the Iranian tomato paste supply chain network. The findings showed that using definitive data, 16 companies are efficient and 9 companies are inefficient, and using bootstrap simulation data, 4 companies are efficient and 21 companies are inefficient. Using the proposed framework, the overall efficiency value has been calculated in two cases using DEA and the bootstrap model. In addition, the efficiency of the stage is calculated separately. Based on the calculated results, if a DMU is considered efficient, its efficiency score is equal to 1 in each of the stages. Otherwise, the cause of the inefficiency of each DMU is identified. Also, based on the comparisons made between the proposed model and the basic models based on sensitivity analysis, the accuracy of the proposed bootstrap-based model in introducing the number of efficient units has been better than the basic models. Therefore, the accuracy of the used method can be concluded.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 904-915"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134936394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sustainable construction has gained paramount importance due to the consideration of the devastating effects of construction activities on the environment. Researchers are exploring innovative approaches to mitigate the carbon footprint and enhance the durability of concrete. In order to regulate the demand and cost of concrete constituents, such as cement and sand, there is a need to invent alternative materials and utilize various industrial and agricultural wastes instead of concrete ingredients, either partially or completely. The experimental investigation and optimization of eco-concrete composites by integrating sugarcane bagasse ash (SCBA), metakaolin (MK), and crumb rubber (CR) are cutting-edge research areas that aim to develop environmentally friendly and high-performance concrete materials. The present research work has attempted to utilize SCBA up to 15% by weight of cement with an increment of 5%, MK as a fractional exchange of cement up to 15% with 5% intervals, and CR was utilized as fractional volumetric substitution of sand from 0% to 15% in concrete. Different sets of combinations were evaluated to identify effects on density, workability, compressive strength, split tensile strength, flexural strength, and microstructural properties. This study has obtained satisfactory results when compared to the control concrete for 10% substitution of cement with MK and 10% substitution of cement with SCBA, along with a 10% replacement of fine aggregate (i.e., sand) with CR. The results were analyzed and optimized using Response Surface Methodology (RSM), which illuminated a strong correlation between experimental findings and RSM models, with an R squared (R2) value of 0.9580. The experimental findings and RSM models showed a significant correlation. The increment in the substitution of sand with CR resulted in a decline in strength, and it can be controlled by adopting different effective pretreatment techniques for CR.
{"title":"Enhancing eco-concrete performance through synergistic integration of sugarcane, metakaolin, and crumb rubber: Experimental investigation and response surface optimization","authors":"Uday Waghe , Dhiraj Agrawal , Khalid Ansari , Monali Wagh , Mugahed Amran , Badr T. Alsulami , Hassan M. Maqbool , Yaser Gamil","doi":"10.1016/j.jer.2023.09.009","DOIUrl":"10.1016/j.jer.2023.09.009","url":null,"abstract":"<div><div>Sustainable construction has gained paramount importance due to the consideration of the devastating effects of construction activities on the environment. Researchers are exploring innovative approaches to mitigate the carbon footprint and enhance the durability of concrete. In order to regulate the demand and cost of concrete constituents, such as cement and sand, there is a need to invent alternative materials and utilize various industrial and agricultural wastes instead of concrete ingredients, either partially or completely. The experimental investigation and optimization of eco-concrete composites by integrating sugarcane bagasse ash (SCBA), metakaolin (MK), and crumb rubber (CR) are cutting-edge research areas that aim to develop environmentally friendly and high-performance concrete materials. The present research work has attempted to utilize SCBA up to 15% by weight of cement with an increment of 5%, MK as a fractional exchange of cement up to 15% with 5% intervals, and CR was utilized as fractional volumetric substitution of sand from 0% to 15% in concrete. Different sets of combinations were evaluated to identify effects on density, workability, compressive strength, split tensile strength, flexural strength, and microstructural properties. This study has obtained satisfactory results when compared to the control concrete for 10% substitution of cement with MK and 10% substitution of cement with SCBA, along with a 10% replacement of fine aggregate (i.e., sand) with CR. The results were analyzed and optimized using Response Surface Methodology (RSM), which illuminated a strong correlation between experimental findings and RSM models, with an R squared (R2) value of 0.9580. The experimental findings and RSM models showed a significant correlation. The increment in the substitution of sand with CR resulted in a decline in strength, and it can be controlled by adopting different effective pretreatment techniques for CR.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 645-658"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135347497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jer.2023.09.017
Gishma Paulson
The outbreak of covid-19 has helped M-commerce to strengthen its roots and helped to increase the number of customers in different industries. Likewise, Electronics product companies also developed M-commerce platforms such as mobile applications (Apps) regardless of their website to sell their products based on customers’ interests and likes. In order to create personalized and targeted marketing strategies, companies collect data from users of M-commerce platforms. For this, they have taken the data from the Handheld device users who installed the companies’ applications with or without the consent of the users which raises ethical concerns related to privacy and security. Unlike other studies this research explores the reason of increased data phishing cases in Kuwait from 2020 and the findings are supported by statistics using machine learning and python language. This paper examines the ethical implications-data phishing chances from users if M-commerce platforms of electronics Apps which are data unencrypted installed in the smartphones. The study employs a mixed-methods approach that includes semi-structured interviews with industry experts and customers, Checking the M-commerce Data privacy details, and analysis of relevant literature. Using the study's survey findings, the hypothesis was tested and a machine learning model was developed that predicts the likelihood of data theft when two specific apps are installed on a smartphone. The research pointed out that the null hypothesis is true and there is approximately 82% of chance if the smart phone users installs data unencrypted apps in the device.
{"title":"Assessing data phishing risks associated with unencrypted apps on smartphones with non-parametric test and random forest model: Insights from Kuwait phishing scam calls","authors":"Gishma Paulson","doi":"10.1016/j.jer.2023.09.017","DOIUrl":"10.1016/j.jer.2023.09.017","url":null,"abstract":"<div><div>The outbreak of covid-19 has helped M-commerce to strengthen its roots and helped to increase the number of customers in different industries. Likewise, Electronics product companies also developed M-commerce platforms such as mobile applications (Apps) regardless of their website to sell their products based on customers’ interests and likes. In order to create personalized and targeted marketing strategies, companies collect data from users of M-commerce platforms. For this, they have taken the data from the Handheld device users who installed the companies’ applications with or without the consent of the users which raises ethical concerns related to privacy and security. Unlike other studies this research explores the reason of increased data phishing cases in Kuwait from 2020 and the findings are supported by statistics using machine learning and python language. This paper examines the ethical implications-data phishing chances from users if M-commerce platforms of electronics Apps which are data unencrypted installed in the smartphones. The study employs a mixed-methods approach that includes semi-structured interviews with industry experts and customers, Checking the M-commerce Data privacy details, and analysis of relevant literature. Using the study's survey findings, the hypothesis was tested and a machine learning model was developed that predicts the likelihood of data theft when two specific apps are installed on a smartphone. The research pointed out that the null hypothesis is true and there is approximately 82% of chance if the smart phone users installs data unencrypted apps in the device.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 761-767"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135348908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Low cost-adsorbent has been a good candidate as an alternative for commercial activated carbon in the application of water treatment. As they possess the capability of adsorbing contaminants, from wastewater and their use minimizes waste in the environment. Heavy metals have been a primary water pollutant since the increase in processing and production of several materials such as steel, copper, etc. Therefore, research has been conducted on the utilization of agricultural wastes which may serve as low-price adsorbents. In this paper, four main categories of agricultural waste materials, namely nut shells/stones, hulls/husks/seed coats, agroforestry peels, and others were investigated and compared as adsorbents to remove or minimize several wastewater impurities described in previous research. The results showed that the Nut shells/stones, such as green coconut single component, demonstrate effective adsorption capacities for lead and cadmium, while hulls/husks/seed coats, including soya bean hulls and modified Lentil husk, exhibit remarkable adsorption of copper and lead. The utilization of agroforestry peels, including chemically modified orange peel and orange peel, shows promising results in the removal of cadmium and nickel. Furthermore, the cost analysis shows variations in the estimated expenses associated with the utilization of these waste materials. Agroforestry peels demonstrate slightly lower estimated expenses, while Nut shells and hulls/husks exhibit comparable cost estimates. Future research should focus on the optimization of adsorption capacities, the exploration of practical applications, and the assessment of economic feasibility for potential large-scale implementation.
{"title":"Utilization of agriculture waste materials as sustainable adsorbents for heavy metal removal: A comprehensive review","authors":"Abdalrahman Alsulaili , Khalad Elsayed , Abdelrahman Refaie","doi":"10.1016/j.jer.2023.09.018","DOIUrl":"10.1016/j.jer.2023.09.018","url":null,"abstract":"<div><div>Low cost-adsorbent has been a good candidate as an alternative for commercial activated carbon in the application of water treatment. As they possess the capability of adsorbing contaminants, from wastewater and their use minimizes waste in the environment. Heavy metals have been a primary water pollutant since the increase in processing and production of several materials such as steel, copper, etc. Therefore, research has been conducted on the utilization of agricultural wastes which may serve as low-price adsorbents. In this paper, four main categories of agricultural waste materials, namely nut shells/stones, hulls/husks/seed coats, agroforestry peels, and others were investigated and compared as adsorbents to remove or minimize several wastewater impurities described in previous research. The results showed that the Nut shells/stones, such as green coconut single component, demonstrate effective adsorption capacities for lead and cadmium, while hulls/husks/seed coats, including soya bean hulls and modified Lentil husk, exhibit remarkable adsorption of copper and lead. The utilization of agroforestry peels, including chemically modified orange peel and orange peel, shows promising results in the removal of cadmium and nickel. Furthermore, the cost analysis shows variations in the estimated expenses associated with the utilization of these waste materials. Agroforestry peels demonstrate slightly lower estimated expenses, while Nut shells and hulls/husks exhibit comparable cost estimates. Future research should focus on the optimization of adsorption capacities, the exploration of practical applications, and the assessment of economic feasibility for potential large-scale implementation.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"12 4","pages":"Pages 691-703"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135389181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号