alexandria engineering journal最新文献

{"title":"Risk identification and propagation in apron operations based on directed complex networks","authors":"Ruxin Wang,&nbsp;Hong Yan","doi":"10.1016/j.aej.2025.01.104","DOIUrl":"10.1016/j.aej.2025.01.104","url":null,"abstract":"<div><div>Ensuring the identification of risks in apron operations is crucial for airport safety and efficiency. However, current research primarily focuses on optimizing apron process operations and identifying static hazards, neglecting the mechanisms of dynamic risk propagation. To address this gap, this paper proposes a comprehensive model based on Event Tree Analysis and complex networks. Event chains are extracted to construct an apron operation risk network encompassing four dimensions: personnel, equipment, environment, and management. Considering the delay effects in safety control, the SIRS model is used to simulate the processes of risk occurrence, spread, mitigation, and recurrence. Network-wide analysis results indicate that management factors have a significant influence on risk propagation. Interaction analysis within event chains further reveals how management factors amplify risk propagation through compounding effects. Sensitivity analysis identifies infection rate and recovery probability as the most critical parameters influencing risk dynamics, highlighting their pivotal roles in controlling risks. Experimental results validate that the model effectively reproduces the mechanisms and patterns of risk propagation in apron operations. Specifically, management factors such as ‘inadequate risk management’ and ‘non-standardized technical operation management’ are identified as key nodes with peak infection rates of 0.479 and 0.467, respectively. Targeted safety management for these key nodes can effectively suppress risk propagation, offering novel insights and methodologies for enhancing apron safety management.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 647-664"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388460","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}

{"title":"Exploring the effects of IoT-enhanced exercise and cognitive training on executive function in middle-aged adults","authors":"Yu Peng ,&nbsp;Guoqing Zhang ,&nbsp;Huadong Pang","doi":"10.1016/j.aej.2025.01.011","DOIUrl":"10.1016/j.aej.2025.01.011","url":null,"abstract":"<div><div>IoT-based devices and wearable sensors are now common in daily life, with smartwatches, smartphones, and other digital tools tracking physical activity and health data. This lifelogging process provides valuable insights into people’s lives. This paper analyzes a publicly available lifelog dataset of 14 individuals to explore how exercise affects mood and, in turn, executive function. Results show that moderate physical activity significantly improves mood, reduces stress, and enhances cognitive functions like decision-making and focus. Improved mood not only boosts exercise performance but also strengthens executive function, suggesting exercise benefits both emotional and cognitive well-being. This opens the door for personalized exercise plans tailored to emotional states to optimize brain function.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 106-115"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387827","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}

{"title":"Techno-economic evaluation of hybrid solar thermal and photovoltaic cooling systems in the industrial sector implementing a dynamic load estimation method","authors":"Andrés Villarruel-Jaramillo ,&nbsp;Josué F. Rosales-Pérez ,&nbsp;Manuel Pérez-García ,&nbsp;José M. Cardemil ,&nbsp;Rodrigo Escobar","doi":"10.1016/j.aej.2025.01.016","DOIUrl":"10.1016/j.aej.2025.01.016","url":null,"abstract":"<div><div>Hybrid solar cooling systems (HYBS) that combine air-to-water and absorption chillers driven by photovoltaic and solar thermal collector fields could improve the techno-economic performance of renewable cooling technologies in industrial applications. However, the limited access to dynamic cooling load data is a notable barrier to evaluating these systems. This research evaluates and compares the techno-economic performance of HYBS with conventional solar and fossil-powered alternatives. For this purpose, a dynamic cooling load profile method for the winemaking industry based on the conduction time series and the heat balance methods was developed, which only requires meteorological data and the annual volume of wine production. The HYBS were evaluated considering Chilean wine regions (high, medium and low solar radiation). The results showed that the HYBS could achieve the highest solar fraction values in all evaluated scenarios. Moreover, HYBS reaches a reduction of 7% of the levelized cost of heating and cooling in medium and low solar radiation sceneries, and the economic performance is highly influenced by the local cost of fossil energy. This research contributes to identifying the potential of HYBS in the industry and presents a useful method to generate dynamic cooling loads from commonly available data.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 128-153"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387829","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}

{"title":"MCNet: A unified multi-center graph convolutional network based on skeletal behavior recognition","authors":"Haiping Zhang ,&nbsp;Xinhao Zhang ,&nbsp;Dongjing Wang ,&nbsp;Fuxing Zhou ,&nbsp;Junfeng Yan","doi":"10.1016/j.aej.2025.01.118","DOIUrl":"10.1016/j.aej.2025.01.118","url":null,"abstract":"<div><div>The enhanced stability and computational efficiency of skeletal data render it a highly sought-after option for video action recognition. Although some progress has been made in existing research on skeleton behavior recognition based on graph convolutional networks (GCN), the fixation of the graph structure and the lack of interaction of the objects in the dataset with the objects lead to the lack of some flexibility of the traditional model in recognizing actions with a large degree of similarity. This will have an impact on the final performance of the model. To address these issues, we propose a unified multi-center graph convolutional network (MCNet) for skeletal behavior recognition. Some of the actions with a large movement amplitude will result in a change of the human body centers. A multi-center training approach is proposed for the recognition of such actions, in which three centers are defined in the construction of the topology graph. A Multi-Center Data Selector (MCDS) is employed to differentiate and select these centers, thereby enhancing the adaptability of the recognition task. Some of the action categories are easily confused with each other, and in order to facilitate the recognition of actions with high similarity, a multi-modal training scheme is proposed. This employs a large-scale language model as a knowledge engine to provide textual descriptions for global actions in different centers, thus enabling the differentiation of actions and further improvement of the recognition effect. Finally, an attention mechanism module is employed to aggregate the features of a multi-scale adjacency matrix along the channel dimension. In order to verify the effectiveness of the network model proposed in this paper, a series of ablation experiments and model analyses were conducted on three datasets. The model was also compared with other state-of-the-art models, including CTR-GCN, Info-GCN, and STF. The results demonstrated that the model proposed in this paper reached the SOTA level. MCNet outperforms CTR-GCN(Baseline) by 0.6% on X-Sub and 0.3% on X-View on the NTU RGB+D 60 dataset. On the NTU RGB+D 120 dataset, the performance is even more pronounced, with an improvement of up to 0.8% for the X-Sub and X-Set benchmarks, respectively.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 116-127"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387828","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}

{"title":"Multi-strain COVID-19 dynamics with vaccination strategies: Mathematical modeling and case study","authors":"Venkatesh Ambalarajan ,&nbsp;Ankamma Rao Mallela ,&nbsp;Prasantha Bharathi Dhandapani ,&nbsp;Vinoth Sivakumar ,&nbsp;Víctor Leiva ,&nbsp;Cecilia Castro","doi":"10.1016/j.aej.2025.01.105","DOIUrl":"10.1016/j.aej.2025.01.105","url":null,"abstract":"<div><div>The emergence of alpha, beta, gamma, and delta COVID-19 variants has posed important challenges to global health. Understanding the transmission dynamics and evaluating the impact of vaccination strategies are critical for effective pandemic management. The present study develops a novel mathematical model that incorporates time-dependent vaccination rates to analyze the spread of these four COVID-19 variants, utilizing India as a case study. We assess the model’s positivity, boundedness, and disease-free equilibrium, as well as we calculate basic reproduction numbers. A sensitivity analysis is conducted to evaluate the impact of key parameters on transmission dynamics. Using optimal control theory, we evaluate three strategies: continuous vaccination of susceptible individuals, public awareness campaigns to reduce contact rates, and quarantine/hospitalization of infected individuals. Numerical simulations over a 300-day period demonstrate that the combined strategy — continuous vaccination, public awareness campaigns, and quarantine/hospitalization — leads to the greatest reduction in infections across all four variants. This is confirmed by the incremental cost-effectiveness ratio and provides practical insights for optimizing pandemic response. The model extends prior research by integrating real-world vaccination data with multi-strain COVID-19 dynamics, offering a comprehensive framework that can guide policymakers in managing future outbreaks. Our study emphasizes the necessity of synergistic public health strategies, and highlights their practical relevance for epidemic management in regions with high population density and limited healthcare resources.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 665-684"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394620","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}

{"title":"New stochastic traveling wave solutions for the Kundu–Mukherjee–Naskar equation with random variable coefficients","authors":"Wael W. Mohammed ,&nbsp;Farah M. Al-Askar","doi":"10.1016/j.aej.2025.02.002","DOIUrl":"10.1016/j.aej.2025.02.002","url":null,"abstract":"<div><div>The stochastic Kundu–Mukherjee–Naskar (SKMN) equation with multiplicative noise is considered. We apply the appropriate transformation to the SKMN to create another Kundu–Mukherjee–Naskar equation with random variable coefficients. We use the mapping approach to provide innovative trigonometric, hyperbolic, and rational solutions for KMNE-RVCs. Following that, we obtain the solutions of SKMN. For the first time in the Kundu–Mukherjee–Naskar equation, we propose that the solution to the wave equation is stochastic, while all prior studies assumed it was deterministic. Some previous results are generated. Furthermore, we provide a variety of graphical representations to show how multiplicative noise affects the exact solutions of the stochastic Kundu–Mukherjee–Naskar.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 154-161"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387830","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}

{"title":"Energy-efficient scalable routing algorithm based on hierarchical agglomerative clustering for Wireless Sensor Networks","authors":"Xuguang Chai ,&nbsp;Yalin Wu ,&nbsp;Lei Feng","doi":"10.1016/j.aej.2025.02.018","DOIUrl":"10.1016/j.aej.2025.02.018","url":null,"abstract":"<div><div>In hierarchical Wireless Sensor Networks (WSNs), the unbalanced energy consumption caused by multi-hop routing poses requirements for the cluster head’s selection and distribution of clusters. Aiming to improve the network lifetime and achieve the balance of energy consumption among sensor nodes, we propose an Energy efficient Scalable Routing algorithm based on Hierarchical Agglomerative Clustering (ESR-HAC) for WSNs by jointly optimizing the cluster formation and energy efficiency of inter-cluster communication. Firstly, to reduce the transmission cost and time/space complexity during the clustering process, a hierarchical clustering method is proposed to achieve a reasonable cluster distribution. Secondly, by taking into account of multiple parameters such as the coverage range, connectivity and remaining energy of sensor nodes, a cost function for cluster head’s selection is defined to reduce the communication overhead between member nodes and cluster heads. Furthermore, to resolve the hot spot problem caused by inter-cluster data forwarding, a genetic algorithm is introduced to obtain the optimal inter cluster routing to balance the network energy consumption. The experimental results show that our algorithm can obtain better energy balance of sensor nodes, ensure the effectiveness of data delivery and extend network lifetime.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 95-105"},"PeriodicalIF":6.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387826","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}

{"title":"Sensitivity analysis of fractional order SVEIR Lumpy Skin Disease model","authors":"Savita Rathee ,&nbsp;Yogeeta Narwal ,&nbsp;Komal Bansal ,&nbsp;Homan Emadifar","doi":"10.1016/j.aej.2025.01.076","DOIUrl":"10.1016/j.aej.2025.01.076","url":null,"abstract":"<div><div>Lumpy skin disease (LSD) is a highly contagious and often fatal infection in cattle, primarily characterized by the formation of skin lumps. It leads to severe economic losses due to reduced milk production, weight loss, infertility, and hide damage. This study aims to comprehensively analyze the dynamics of LSD and devise effective mitigation strategies through mathematical modeling. A fractional SVEIR model is proposed to predict the transmission dynamics within affected cattle populations. The model’s feasibility is verified using the Laplace transformation, demonstrating both local stability, using the Matignon criterion, and global stability, employing Lyapunov functions and LaSalle’s invariance principle. The basic reproduction number (<span><math><msub><mrow><mi>R</mi></mrow><mrow><mi>L</mi><mi>S</mi><mi>D</mi></mrow></msub></math></span>) is calculated using the next-generation matrix method. Sensitivity analysis, based on the normalized forward sensitivity index, identifies key parameters influencing <span><math><msub><mrow><mi>R</mi></mrow><mrow><mi>L</mi><mi>S</mi><mi>D</mi></mrow></msub></math></span>: A 30% decrease in the average number of bites (<span><math><mi>β</mi></math></span>) reduces the infected cattle population by 16.58%. A 30% increase in the recovery rate (<span><math><mi>ρ</mi></math></span>) leads to a 29.35% reduction in infections. Increasing the vaccination rate (<span><math><mi>γ</mi></math></span>) by 79% lowers the number of sick cattle by 20%. Numerical simulations explore LSD transmission across five cattle populations under different scenarios of disease persistence and elimination. The findings are supported by theoretical analysis and visually represented through graphical illustrations, offering valuable insights into LSD control and prevention strategies.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 609-622"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377919","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}

{"title":"Strategic coopetition in parking system: A game theory analysis of shared parking platforms","authors":"Jian Li ,&nbsp;Qian Zhao ,&nbsp;Jiafu Su","doi":"10.1016/j.aej.2025.02.012","DOIUrl":"10.1016/j.aej.2025.02.012","url":null,"abstract":"<div><div>The shared parking platform alleviates the insufficient supply of public parking, but it may also lead to competition with the public parking lot. To relieve the negative impact of competition, the public parking lot has a choice to partially cooperate with the platform, leading to a coopetition relationship.</div></div><div><h3>Purpose</h3><div>This study examines the competition and coopetition dynamics between a shared parking platform and a public parking lot.</div></div><div><h3>Method</h3><div>We apply game-theoretic models to analyze the strategic interactions between these two entities under competition and coopetition scenarios.</div></div><div><h3>Results</h3><div>Our analysis reveals that when the inconvenience cost is low, cooperation is likely to occur. Shared parking platforms can incentivize public parking lots to participate by offering financial subsidy. As the quantity of idle private parking spaces and inconvenience cost increases, the willingness to cooperate between the two parties grows. However, this willingness first increases and then decreases as the demand rises.</div></div><div><h3>Conclusions</h3><div>Compared to the competition scenario, private parking space owners in the coopetition scenario experience lower revenue and consumers face reduced surplus. However, both the shared parking platform and the public parking lot benefit from higher profits, and social welfare is greater in the coopetition scenario when the inconvenience cost is high, whereas the opposite is true when such cost is low.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 634-646"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377921","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}

{"title":"GS-LinYOLOv10: A drone-based model for real-time construction site safety monitoring","authors":"Yang Song ,&nbsp;ZhenLin Chen ,&nbsp;Hua Yang ,&nbsp;Jifei Liao","doi":"10.1016/j.aej.2025.01.021","DOIUrl":"10.1016/j.aej.2025.01.021","url":null,"abstract":"<div><div>Real-time safety monitoring on construction sites is essential for ensuring worker safety, but traditional detection methods face challenges in dynamic environments with moving objects, occlusions, and complex conditions. To address these limitations, we propose GS-LinYOLOv10, an improved model based on YOLOv10, specifically designed for drone-based safety monitoring. The GSConv module introduces a lightweight feature extraction mechanism, reducing computational complexity without compromising detection accuracy. The Linformer-based attention mechanism efficiently captures global context, addressing challenges in dynamic and complex environments. The model integrates IoT sensor data for real-time feedback, incorporates the GSConv module for lightweight feature extraction, and utilizes a Linformer-based attention mechanism to efficiently capture global context. These innovations reduce computational complexity while significantly improving detection accuracy. Experimental results show that GS-LinYOLOv10 achieves a precision of 91.2% and a mean average precision (mAP) of 89.4%, outperforming existing models. The integration of IoT sensors allows the drone system to dynamically adjust its monitoring focus, improving adaptability to changing environments and enhancing hazard detection. This research provides an advanced, drone-based IoT-enhanced solution for real-time construction site safety monitoring, offering a more effective and efficient approach to safety management.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 62-73"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378716","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}