Pub Date : 2025-04-03DOI: 10.1016/j.asej.2025.103376
Ruishi Liang , Zaiton Mat Isa , Shaymaa M.H. Darwish
In the mathematical modeling of the advection-diffusion equation (ADE) governing the transport of heavy metals in soil, it is essential to consider scenarios where the pollution source is not localized at the boundary but rather introduced as a source term within the equation, reflecting realistic situations where abrupt contamination events may occur within the soil matrix. Considering also adsorption and desorption, the ADE incorporate additional source term. This source term representing as a point source that satisfies instantaneous release and exponential decay release which can be used to simulate different types of pollution events in soil. Utilizing the Laplace transform method to obtain solutions, the dynamics of pollutant behavior in both cases are investigated. The results show that regardless of release type, the concentration reaches a peak near the source point area and remains higher while stabilizing over time. However, when the retardation factor varied, both shows similar behavior on the first day only but not at the fourth day. Additionally, the amount of particles release and exponential decay coefficient follows or aligns with its equations.
{"title":"Instantaneous and exponential decay point source effects on two-dimensional heavy metal transport with adsorption and desorption in soil","authors":"Ruishi Liang , Zaiton Mat Isa , Shaymaa M.H. Darwish","doi":"10.1016/j.asej.2025.103376","DOIUrl":"10.1016/j.asej.2025.103376","url":null,"abstract":"<div><div>In the mathematical modeling of the advection-diffusion equation (ADE) governing the transport of heavy metals in soil, it is essential to consider scenarios where the pollution source is not localized at the boundary but rather introduced as a source term within the equation, reflecting realistic situations where abrupt contamination events may occur within the soil matrix. Considering also adsorption and desorption, the ADE incorporate additional source term. This source term representing as a point source that satisfies instantaneous release and exponential decay release which can be used to simulate different types of pollution events in soil. Utilizing the Laplace transform method to obtain solutions, the dynamics of pollutant behavior in both cases are investigated. The results show that regardless of release type, the concentration reaches a peak near the source point area and remains higher while stabilizing over time. However, when the retardation factor varied, both shows similar behavior on the first day only but not at the fourth day. Additionally, the amount of particles release and exponential decay coefficient follows or aligns with its equations.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103376"},"PeriodicalIF":6.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research proposes a unidirectional circularly polarized tunable frequency circular patch antenna scheme for S-band uplink satellite communications. In the antenna scheme, the circular radiating patch is enclosed by 4×8 rectangular-shaped auxiliary elements along the +x, −x, +y, and −y−axes. To shift the resonant frequency of the antenna to lower frequencies, the auxiliary elements on the four axes are uniformly shorted. There are nine shorting configurations (configurations A – I) corresponding to the S-band uplink chain (2.025 GHz to 2.110 GHz). Besides, the circular polarization is switchable between right- (RHCP) and left-hand circular polarization (LHCP) by relocating the feed point from the +y axis for RHCP to +x axis for LHCP. Switching mechanisms dynamically reconfigure the antenna by modifying its electrical length to support multiple frequency bands, all of which maintain circular polarization. Since the proposed antenna scheme is intended for the S-band uplink frequency of 2.06 GHz, measurements are carried out with configuration F of the antenna scheme. The measured impedance bandwidth (≤-10 dB) and axial ratio bandwidth (AR<3 dB) are 6.2% and 4.49%, with the maximum gain of 6.54 dBic for RHCP and LHCP. The radiation pattern is of unidirectionality. Furthermore, the proposed antenna scheme meets the qualification sine vibration and random vibration test requirements. The proposed antenna scheme is thus suitable for S-band uplink satellite communications. The novelty of this research lies in the use of the auxiliary elements of various shorting configurations to achieve frequency tunability; and the alteration of the feed point location to switch between RHCP and LHCP.
{"title":"A circularly polarized tunable frequency circular patch antenna for S-band space base application","authors":"Likhit Waranon , Sitthichai Dentri , Watid Phakphisut , Monai Krairiksh , Chuwong Phongcharoenpanich","doi":"10.1016/j.asej.2025.103368","DOIUrl":"10.1016/j.asej.2025.103368","url":null,"abstract":"<div><div>This research proposes a unidirectional circularly polarized tunable frequency circular patch antenna scheme for S-band uplink satellite communications. In the antenna scheme, the circular radiating patch is enclosed by 4×8 rectangular-shaped auxiliary elements along the +<em>x</em>, −<em>x</em>, +<em>y</em>, and −<em>y</em>−axes. To shift the resonant frequency of the antenna to lower frequencies, the auxiliary elements on the four axes are uniformly shorted. There are nine shorting configurations (configurations A – I) corresponding to the S-band uplink chain (2.025 GHz to 2.110 GHz). Besides, the circular polarization is switchable between right- (RHCP) and left-hand circular polarization (LHCP) by relocating the feed point from the +<em>y</em> axis for RHCP to +<em>x</em> axis for LHCP. Switching mechanisms dynamically reconfigure the antenna by modifying its electrical length to support multiple frequency bands, all of which maintain circular polarization. Since the proposed antenna scheme is intended for the S-band uplink frequency of 2.06 GHz, measurements are carried out with configuration F of the antenna scheme. The measured impedance bandwidth (<span><math><mo>|</mo><msub><mrow><mi>S</mi></mrow><mrow><mn>11</mn></mrow></msub><mo>|</mo></math></span>≤-10 dB) and axial ratio bandwidth (AR<3 dB) are 6.2% and 4.49%, with the maximum gain of 6.54 dBic for RHCP and LHCP. The radiation pattern is of unidirectionality. Furthermore, the proposed antenna scheme meets the qualification sine vibration and random vibration test requirements. The proposed antenna scheme is thus suitable for S-band uplink satellite communications. The novelty of this research lies in the use of the auxiliary elements of various shorting configurations to achieve frequency tunability; and the alteration of the feed point location to switch between RHCP and LHCP.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103368"},"PeriodicalIF":6.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-04-01DOI: 10.1016/j.asej.2025.103382
Hongrui Wang , Pengbin Zhang , Kunpeng Xing , Jingyang Wang , Mingzhe Yuan
This paper focuses on the modeling of nonlinear multi-input, multi-output coupled steam generators in nuclear power plants. To address the problem of insufficient modeling accuracy due to the low signal-to-noise ratio of closed-loop operation sampling, a multi-stage identification framework integrating the least-squares method, instrumental variables method, and predictive error method is proposed. This framework is divided into three stages: parameter initialization, initial value estimation, and parameter optimization, aiming to progressively enhance the quality of model identification. Moreover, to address the complicated problem of piecewise linearization of nonlinear systems, a piecewise linearization strategy based on gap metrics with decreasing intervals from large to small is proposed. The strategy first uses data from large time-domain intervals for model identification, followed by refined time-domain interval data. This approach simplifies the piecewise linearization process and reduces the generation of redundant models. Through extensive simulation validation, this method has demonstrated its effectiveness in the modeling of nuclear power steam generators and valve condition monitoring. The enhancement percentages of the three steam generators are 18.95%, 10.19%, and 48.85%, respectively, highlighting the significant improvement in model accuracy. Additionally, fault monitoring simulations for the steam generator feedwater valve show significant differences between the predicted values and errors of the normal model under simulated fault scenarios. By setting safety thresholds based on historical data, the working status of the valve can be effectively monitored. This paper provides new research ideas and practical solutions for nuclear power steam generator modeling and condition monitoring, contributing to the advancement of related fields.
{"title":"Multi-stage identification framework for steam generator modeling with gap metrics","authors":"Hongrui Wang , Pengbin Zhang , Kunpeng Xing , Jingyang Wang , Mingzhe Yuan","doi":"10.1016/j.asej.2025.103382","DOIUrl":"10.1016/j.asej.2025.103382","url":null,"abstract":"<div><div>This paper focuses on the modeling of nonlinear multi-input, multi-output coupled steam generators in nuclear power plants. To address the problem of insufficient modeling accuracy due to the low signal-to-noise ratio of closed-loop operation sampling, a multi-stage identification framework integrating the least-squares method, instrumental variables method, and predictive error method is proposed. This framework is divided into three stages: parameter initialization, initial value estimation, and parameter optimization, aiming to progressively enhance the quality of model identification. Moreover, to address the complicated problem of piecewise linearization of nonlinear systems, a piecewise linearization strategy based on gap metrics with decreasing intervals from large to small is proposed. The strategy first uses data from large time-domain intervals for model identification, followed by refined time-domain interval data. This approach simplifies the piecewise linearization process and reduces the generation of redundant models. Through extensive simulation validation, this method has demonstrated its effectiveness in the modeling of nuclear power steam generators and valve condition monitoring. The enhancement percentages of the three steam generators are 18.95%, 10.19%, and 48.85%, respectively, highlighting the significant improvement in model accuracy. Additionally, fault monitoring simulations for the steam generator feedwater valve show significant differences between the predicted values and errors of the normal model under simulated fault scenarios. By setting safety thresholds based on historical data, the working status of the valve can be effectively monitored. This paper provides new research ideas and practical solutions for nuclear power steam generator modeling and condition monitoring, contributing to the advancement of related fields.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103382"},"PeriodicalIF":6.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-04-01DOI: 10.1016/j.asej.2025.103344
Zhe Wang , Jiaxing Shen , Xingyuan Zhang , Yinghua Yu , Yan Wang , Hu Zhu , Lianglu Zhang
To solve the problem of insufficient precision of gear fault diagnosis with small sample size, an adaptive floating convolutional sequence pattern neural network recognition method based on the combination of simplified Gramian Angle field and time–frequency feature images is proposed. One-dimensional data is converted to two-dimensional real-time data by simplifying Gramian Angle field. The time domain data and time frequency data are mixed enhanced by fast Fourier transform to obtain feature enhanced image-like data. The feature-enhanced image dataset generated by this method has a high degree of intra-group consistency in data features, which is beneficial to fault identification. The adaptive floating convolutional sequence model is used to construct neural network to identify image-like data and improve the accuracy of gear fault diagnosis with small samples. Moreover, the diagnosis method has strong robustness and high engineering application value.
{"title":"Gear fault diagnosis research based on GAF-TFR-2DCV with small sample size","authors":"Zhe Wang , Jiaxing Shen , Xingyuan Zhang , Yinghua Yu , Yan Wang , Hu Zhu , Lianglu Zhang","doi":"10.1016/j.asej.2025.103344","DOIUrl":"10.1016/j.asej.2025.103344","url":null,"abstract":"<div><div>To solve the problem of insufficient precision of gear fault diagnosis with small sample size, an adaptive floating convolutional sequence pattern neural network recognition method based on the combination of simplified Gramian Angle field and time–frequency feature images is proposed. One-dimensional data is converted to two-dimensional real-time data by simplifying Gramian Angle field. The time domain data and time frequency data are mixed enhanced by fast Fourier transform to obtain feature enhanced image-like data. The feature-enhanced image dataset generated by this method has a high degree of intra-group consistency in data features, which is beneficial to fault identification. The adaptive floating convolutional sequence model is used to construct neural network to identify image-like data and improve the accuracy of gear fault diagnosis with small samples. Moreover, the diagnosis method has strong robustness and high engineering application value.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 5","pages":"Article 103344"},"PeriodicalIF":6.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-04-01DOI: 10.1016/j.asej.2025.103380
Muhammet Emin Sahin , Umut Özkaya , Cagri Arisoy , Halil İbrahim Coşar , Hasan Ulutaş
The accurate diagnosis of plant diseases is crucial for improving agricultural productivity and ensuring global food security. This study introduces an advanced approach to cucumber leaf disease classification by integrating novel deep learning methodologies. Two custom-designed convolutional neural networks (CucuNet-CNN1 and CucuNet-CNN2) are proposed, alongside pre-trained models such as InceptionResNetV2, EfficientNetV2M, and NASNetMobile, to classify various disease types. To enhance classification performance, an ensemble model (5-EnsCNNs) is developed, combining the strengths of these architectures. Additionally, a Spiking Neural Network (SNN), inspired by neuromorphic computing principles, is employed. Experimental results show that the SNN achieves a remarkable accuracy of 98.91 % in classifying six cucumber leaf diseases, surpassing the performance of individual and ensemble models. The integration of novel CNN architectures, ensemble strategies, and SNN-based methods represents a significant advancement in automated plant disease diagnosis, paving the way for more accurate and reliable agricultural diagnostics.
{"title":"CucuNetCNNs: Application of novel ensemble deep neural networks for classification of cucumber leaf disease","authors":"Muhammet Emin Sahin , Umut Özkaya , Cagri Arisoy , Halil İbrahim Coşar , Hasan Ulutaş","doi":"10.1016/j.asej.2025.103380","DOIUrl":"10.1016/j.asej.2025.103380","url":null,"abstract":"<div><div>The accurate diagnosis of plant diseases is crucial for improving agricultural productivity and ensuring global food security. This study introduces an advanced approach to cucumber leaf disease classification by integrating novel deep learning methodologies. Two custom-designed convolutional neural networks (CucuNet-CNN1 and CucuNet-CNN2) are proposed, alongside pre-trained models such as InceptionResNetV2, EfficientNetV2M, and NASNetMobile, to classify various disease types. To enhance classification performance, an ensemble model (5-EnsCNNs) is developed, combining the strengths of these architectures. Additionally, a Spiking Neural Network (SNN), inspired by neuromorphic computing principles, is employed. Experimental results show that the SNN achieves a remarkable accuracy of 98.91 % in classifying six cucumber leaf diseases, surpassing the performance of individual and ensemble models. The integration of novel CNN architectures, ensemble strategies, and SNN-based methods represents a significant advancement in automated plant disease diagnosis, paving the way for more accurate and reliable agricultural diagnostics.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 5","pages":"Article 103380"},"PeriodicalIF":6.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-03-31DOI: 10.1016/j.asej.2025.103372
Qi Liu , Muhammad Zakria Javed , Muhammad Uzair Awan , Loredana Ciurdariu , Badr S. Alkahtani
It is evident that several inequalities have been explored via diverse strategies to acquire more reliable, robust, and accurate bounds of mathematical quantities. Although the role of convexity and generalized calculus is unprecedented in the development of both dynamical and analytical inequalities. Classical derivative and integral operators failed to investigate various classes of mappings. Symmetric calculus provides the framework to study the several classes of non-differentiable mappings. In this manuscript, we investigate the Hermite-Hadamard's and error inequalities of quadrature schemes leveraging the concepts of convex mapping and left and right symmetric operators. We start by proving various Hermite-Hadamard's like inequalities involving double, triple symmetric quantum integrals and a unified identity based on symmetric quantum differentiable mappings. Afterwards, we construct numerous integral inequalities corresponding with different quadrature schemes through convex mapping and elementary concepts from the theory of inequalities. To ensure the effectiveness and applicability of proposed results, we deduce several special scenarios, comparative analyses with previously explored results, and applications to linear combinations of means and composite quadrature schemes.
{"title":"Hermite-Hadamard's like inequalities via symmetric quantum calculus","authors":"Qi Liu , Muhammad Zakria Javed , Muhammad Uzair Awan , Loredana Ciurdariu , Badr S. Alkahtani","doi":"10.1016/j.asej.2025.103372","DOIUrl":"10.1016/j.asej.2025.103372","url":null,"abstract":"<div><div>It is evident that several inequalities have been explored via diverse strategies to acquire more reliable, robust, and accurate bounds of mathematical quantities. Although the role of convexity and generalized calculus is unprecedented in the development of both dynamical and analytical inequalities. Classical derivative and integral operators failed to investigate various classes of mappings. Symmetric calculus provides the framework to study the several classes of non-differentiable mappings. In this manuscript, we investigate the Hermite-Hadamard's and error inequalities of quadrature schemes leveraging the concepts of convex mapping and left and right symmetric operators. We start by proving various Hermite-Hadamard's like inequalities involving double, triple symmetric quantum integrals and a unified identity based on symmetric quantum differentiable mappings. Afterwards, we construct numerous integral inequalities corresponding with different quadrature schemes through convex mapping and elementary concepts from the theory of inequalities. To ensure the effectiveness and applicability of proposed results, we deduce several special scenarios, comparative analyses with previously explored results, and applications to linear combinations of means and composite quadrature schemes.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103372"},"PeriodicalIF":6.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-03-31DOI: 10.1016/j.asej.2025.103379
Yi Cao , Ding Ding , Yunzhang Li , Yeqian Zhang
The Mu Nia culture is an endangered alpine civilization, yet the foundational research on its architecture remains significantly inadequate. This study conducted field research on 52 Mu Nia buildings and performed a quantitative analysis of the passive technologies embedded within them. The research indicates that, compared to other spontaneously constructed Tibetan architectures, Mu Nia dwellings exhibit greater stylistic diversity while still adhering to a unified principle of solar energy utilization. In modern times, Mu Nia villagers have improved indoor quality with self-awareness in terms of enhancing the utilization of local materials, strengthening exterior wall insulation, adding sunspaces, and modifying Chinse fireplaces. In future research and practice, architects and scientists can refer to the pathways and trends proposed in this paper to achieve the preservation and development of Mu Nia culture.
{"title":"A quantitative investigation on the passive features in vernacular Mu Nia Tibetan houses","authors":"Yi Cao , Ding Ding , Yunzhang Li , Yeqian Zhang","doi":"10.1016/j.asej.2025.103379","DOIUrl":"10.1016/j.asej.2025.103379","url":null,"abstract":"<div><div>The Mu Nia culture is an endangered alpine civilization, yet the foundational research on its architecture remains significantly inadequate. This study conducted field research on 52 Mu Nia buildings and performed a quantitative analysis of the passive technologies embedded within them. The research indicates that, compared to other spontaneously constructed Tibetan architectures, Mu Nia dwellings exhibit greater stylistic diversity while still adhering to a unified principle of solar energy utilization. In modern times, Mu Nia villagers have improved indoor quality with self-awareness in terms of enhancing the utilization of local materials, strengthening exterior wall insulation, adding sunspaces, and modifying Chinse fireplaces. In future research and practice, architects and scientists can refer to the pathways and trends proposed in this paper to achieve the preservation and development of Mu Nia culture.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103379"},"PeriodicalIF":6.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-03-31DOI: 10.1016/j.asej.2025.103383
Mohammed S. Assiri , Mahmoud M. Selim
Hand gestures (HG) are the key communication technique for hearing-impaired people, which poses a problem for millions of individuals globally after communicating with those who don’t have hearing impairments. The importance of technology in improving accessibility and thus raising the standard of living for persons with hearing impairments is globally acclaimed. Machine learning (ML) is a section of artificial intelligence (AI) that concentrates on developing a method that depends on data. The major problem of HG recognition is that the machine does not identify the human language straightforwardly, and human–machine interaction is required of media for communication, which is determined by machines and, in addition to humans, to assist hearing-impaired individuals and ageing people. Thus, HG recognition as a communication media is necessary to provide instructions to the computer. This paper proposes the Swin Transformer-Driven Framework for Gesture Recognition by Integrating Deep Learning with the Secretary Bird Optimization (STFGR-IDLSBO) methodology. The main intention of the STFGR-IDLSBO methodology is to develop an efficient and robust system for gesture recognition to assist hearing-impaired persons. Initially, the proposed STFGR-IDLSBO method utilizes adaptive bilateral filtering (ABF) in the image pre-processing stage to reduce noise while preserving the edges of the gestures in the captured images. Furthermore, the swin transformer (ST) is a feature extractor that effectively captures multiscale representations and spatial hierarchies from gesture images. The hybrid model integrates the convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) technique, which is employed for the gesture classification process. Finally, the secretary bird optimizer algorithm (SBOA) is utilized for the optimum hyperparameter tuning of the CNN-BiLSTM classifier. To ensure the enhanced performance of the STFGR-IDLSBO methodology, a wide range simulation investigation is performed under the Traffic Police Gesture dataset. The performance validation of the STFGR-IDLSBO technique portrayed a superior accuracy value of 99.25% over existing methods.
{"title":"A swin transformer-driven framework for gesture recognition to assist hearing impaired people by integrating deep learning with secretary bird optimization algorithm","authors":"Mohammed S. Assiri , Mahmoud M. Selim","doi":"10.1016/j.asej.2025.103383","DOIUrl":"10.1016/j.asej.2025.103383","url":null,"abstract":"<div><div>Hand gestures (HG) are the key communication technique for hearing-impaired people, which poses a problem for millions of individuals globally after communicating with those who don’t have hearing impairments. The importance of technology in improving accessibility and thus raising the standard of living for persons with hearing impairments is globally acclaimed. Machine learning (ML) is a section of artificial intelligence (AI) that concentrates on developing a method that depends on data. The major problem of HG recognition is that the machine does not identify the human language straightforwardly, and human–machine interaction is required of media for communication, which is determined by machines and, in addition to humans, to assist hearing-impaired individuals and ageing people. Thus, HG recognition as a communication media is necessary to provide instructions to the computer. This paper proposes the Swin Transformer-Driven Framework for Gesture Recognition by Integrating Deep Learning with the Secretary Bird Optimization (STFGR-IDLSBO) methodology. The main intention of the STFGR-IDLSBO methodology is to develop an efficient and robust system for gesture recognition to assist hearing-impaired persons. Initially, the proposed STFGR-IDLSBO method utilizes adaptive bilateral filtering (ABF) in the image pre-processing stage to reduce noise while preserving the edges of the gestures in the captured images. Furthermore, the swin transformer (ST) is a feature extractor that effectively captures multiscale representations and spatial hierarchies from gesture images. The hybrid model integrates the convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) technique, which is employed for the gesture classification process. Finally, the secretary bird optimizer algorithm (SBOA) is utilized for the optimum hyperparameter tuning of the CNN-BiLSTM classifier. To ensure the enhanced performance of the STFGR-IDLSBO methodology, a wide range simulation investigation is performed under the Traffic Police Gesture dataset. The performance validation of the STFGR-IDLSBO technique portrayed a superior accuracy value of 99.25% over existing methods.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103383"},"PeriodicalIF":6.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-03-29DOI: 10.1016/j.asej.2025.103373
Abdul Mateen Khan , Wesam Salah Alaloul , Muhammad Ali Musarat , Abdul Muiz Fayyaz
The construction industry is a major contributor to global carbon emissions, with embodied carbon emissions from materials significantly impacting sustainability. Addressing these challenges requires innovative digital solutions for optimizing material selection and resource efficiency. This study introduces a BIM-based Value Engineering (VE) plugin that integrates cost, energy consumption, and embodied carbon assessments within BIM environments. Employing a mixed-methods approach, including theoretical modelling and a case study, the research demonstrates a 10% reduction in project costs and a 15% decrease in embodied carbon emissions. The findings highlight the role of digital tools in enhancing sustainability by enabling data-driven decision-making and lifecycle optimization. This study advances sustainable construction practices by presenting a structured methodology for integrating BIM and VE, offering a scalable framework that minimizes carbon footprints while enhancing both economic and environmental performance. These insights provide a foundation for further research and practical applications in low-carbon construction.
{"title":"Optimizing sustainable alternatives in value engineering Decision-Making through BIM-Integrated plugin automation for buildings","authors":"Abdul Mateen Khan , Wesam Salah Alaloul , Muhammad Ali Musarat , Abdul Muiz Fayyaz","doi":"10.1016/j.asej.2025.103373","DOIUrl":"10.1016/j.asej.2025.103373","url":null,"abstract":"<div><div>The construction industry is a major contributor to global carbon emissions, with embodied carbon emissions from materials significantly impacting sustainability. Addressing these challenges requires innovative digital solutions for optimizing material selection and resource efficiency. This study introduces a BIM-based Value Engineering (VE) plugin that integrates cost, energy consumption, and embodied carbon assessments within BIM environments. Employing a mixed-methods approach, including theoretical modelling and a case study, the research demonstrates a 10% reduction in project costs and a 15% decrease in embodied carbon emissions. The findings highlight the role of digital tools in enhancing sustainability by enabling data-driven decision-making and lifecycle optimization. This study advances sustainable construction practices by presenting a structured methodology for integrating BIM and VE, offering a scalable framework that minimizes carbon footprints while enhancing both economic and environmental performance. These insights provide a foundation for further research and practical applications in low-carbon construction.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 6","pages":"Article 103373"},"PeriodicalIF":6.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-03-28DOI: 10.1016/j.asej.2025.103347
Fachriza Afif Maani , Firman Bagja Juangsa
Ammonia (NH3) and hydrogen (H2) are promising non-carbon fuels for the decarbonization of thermal processes through combustion·NH3 can serve as an efficient carrier for H2 through partial decomposition. However, the combustion process of this partially decomposed NH3, especially its NOx emission, requires further investigation. This study employs Computational Fluid Dynamics (CFD) using ANSYS Fluent to simulate premixed combustion of partial NH3 decomposition through the Reynold Stress Model (RSM) and Eddy-Dissipation Model (EDM). The equivalence ratio varies from 0.2 to 1.4 in increments of 0.1. The RSM and EDM model could estimate the NOx production effectively without depending on the high computational computer and long-time simulations. Findings indicate that NOx emissions remain significantly low in rich combustion conditions, starting from an equivalence ratio of 1.1, with values below 150 mg/Nm3.
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