Francisco Carvalho, João Manuel R. S. Tavares, Marta Campos Ferreira
This study explores the prediction and mitigation of pallet collapse during transportation within the glass packaging industry, employing a machine learning approach to reduce cargo loss and enhance logistics efficiency. Using the CRoss-Industry Standard Process for Data Mining (CRISP-DM) framework, data were systematically collected from a leading glass manufacturer and analysed. A comparative analysis between the Decision Tree and Random Forest machine learning algorithms, evaluated using performance metrics such as F1-score, revealed that the latter is more effective at predicting pallet collapse. This study is pioneering in identifying new critical predictive variables, particularly geometry-related and temperature-related features, which significantly influence the stability of pallets. Based on these findings, several strategies to prevent pallet collapse are proposed, including optimizing pallet stacking patterns, enhancing packaging materials, implementing temperature control measures, and developing more robust handling protocols. These insights demonstrate the utility of machine learning in generating actionable recommendations to optimize supply chain operations and offer a foundation for further academic and practical advancements in cargo handling within the glass industry.
本研究探讨了玻璃包装行业在运输过程中托盘倒塌的预测和缓解方法，采用机器学习方法来减少货物损失并提高物流效率。利用数据挖掘行业标准流程（CRISP-DM）框架，从一家领先的玻璃制造商处系统地收集并分析了数据。通过使用 F1 分数等性能指标对决策树和随机森林机器学习算法进行比较分析，发现后者在预测托盘坍塌方面更为有效。这项研究开创性地确定了新的关键预测变量，特别是与几何形状和温度相关的特征，它们对托盘的稳定性有重大影响。基于这些发现，我们提出了几种防止托盘坍塌的策略，包括优化托盘堆叠模式、改进包装材料、实施温度控制措施以及制定更稳健的处理规程。这些见解证明了机器学习在生成可操作建议以优化供应链运营方面的实用性，并为玻璃行业货物装卸方面的进一步学术和实践进步奠定了基础。
{"title":"A Machine Learning Approach for Predicting and Mitigating Pallet Collapse during Transport: The Case of the Glass Industry","authors":"Francisco Carvalho, João Manuel R. S. Tavares, Marta Campos Ferreira","doi":"10.3390/app14188256","DOIUrl":"https://doi.org/10.3390/app14188256","url":null,"abstract":"This study explores the prediction and mitigation of pallet collapse during transportation within the glass packaging industry, employing a machine learning approach to reduce cargo loss and enhance logistics efficiency. Using the CRoss-Industry Standard Process for Data Mining (CRISP-DM) framework, data were systematically collected from a leading glass manufacturer and analysed. A comparative analysis between the Decision Tree and Random Forest machine learning algorithms, evaluated using performance metrics such as F1-score, revealed that the latter is more effective at predicting pallet collapse. This study is pioneering in identifying new critical predictive variables, particularly geometry-related and temperature-related features, which significantly influence the stability of pallets. Based on these findings, several strategies to prevent pallet collapse are proposed, including optimizing pallet stacking patterns, enhancing packaging materials, implementing temperature control measures, and developing more robust handling protocols. These insights demonstrate the utility of machine learning in generating actionable recommendations to optimize supply chain operations and offer a foundation for further academic and practical advancements in cargo handling within the glass industry.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erato Oikonomopoulou, Vasiliki Palieraki, Elizabeth Vintzileou, Giovacchino Genesio
This study focuses on long concrete interfaces tested under cyclic actions, fastened with post-installed industrial steel screws. The overall behavior and the effect of roughness were investigated in three long interfaces, representative of connections between, e.g., a slab and a wall, a beam and a wall, etc. The results were compared with those of short interfaces tested by the authors in previous campaigns. It was observed that rough long interfaces activate their maximum resistance at small values of imposed shear slip. When roughness was reduced, the maximum resistance was also reduced, the corresponding shear slip was increased, and the overall behavior was stable. For large values of the shear slip, imposed at one end of the interface, the shear slips along it tended to be uniform, both in short and long interfaces. The limited embedment length of the screws led to their pronounced pullout. Finally, the asymmetry of resistance between the two loading directions that was observed in short interfaces was alleviated in the long ones, where also the scatter of the results was limited among duplicate specimens.
{"title":"Cyclic Behavior of Long Concrete Interfaces Crossed by Steel Screws","authors":"Erato Oikonomopoulou, Vasiliki Palieraki, Elizabeth Vintzileou, Giovacchino Genesio","doi":"10.3390/app14188246","DOIUrl":"https://doi.org/10.3390/app14188246","url":null,"abstract":"This study focuses on long concrete interfaces tested under cyclic actions, fastened with post-installed industrial steel screws. The overall behavior and the effect of roughness were investigated in three long interfaces, representative of connections between, e.g., a slab and a wall, a beam and a wall, etc. The results were compared with those of short interfaces tested by the authors in previous campaigns. It was observed that rough long interfaces activate their maximum resistance at small values of imposed shear slip. When roughness was reduced, the maximum resistance was also reduced, the corresponding shear slip was increased, and the overall behavior was stable. For large values of the shear slip, imposed at one end of the interface, the shear slips along it tended to be uniform, both in short and long interfaces. The limited embedment length of the screws led to their pronounced pullout. Finally, the asymmetry of resistance between the two loading directions that was observed in short interfaces was alleviated in the long ones, where also the scatter of the results was limited among duplicate specimens.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The objective of person re-identification (ReID) tasks is to match a specific individual across different times, locations, or camera viewpoints. The prevalent issue of occlusion in real-world scenarios affects image information, rendering the affected features unreliable. The difficulty and core challenge lie in how to effectively discern and extract visual features from human images under various complex conditions, including cluttered backgrounds, diverse postures, and the presence of occlusions. Some works have employed pose estimation or human key point detection to construct graph-structured information to counteract the effects of occlusions. However, this approach introduces new noise due to issues such as the invisibility of key points. Our proposed module, in contrast, does not require the use of additional feature extractors. Our module employs multi-scale graph attention for the reweighting of feature importance. This allows features to concentrate on areas genuinely pertinent to the re-identification task, thereby enhancing the model’s robustness against occlusions. To address these problems, a model that employs multi-scale graph attention to reweight the importance of features is proposed in this study, significantly enhancing the model’s robustness against occlusions. Our experimental results demonstrate that, compared to baseline models, the method proposed herein achieves a notable improvement in mAP on occluded datasets, with increases of 0.5%, 31.5%, and 12.3% in mAP scores.
{"title":"A Multi-Scale Graph Attention-Based Transformer for Occluded Person Re-Identification","authors":"Ming Ma, Jianming Wang, Bohan Zhao","doi":"10.3390/app14188279","DOIUrl":"https://doi.org/10.3390/app14188279","url":null,"abstract":"The objective of person re-identification (ReID) tasks is to match a specific individual across different times, locations, or camera viewpoints. The prevalent issue of occlusion in real-world scenarios affects image information, rendering the affected features unreliable. The difficulty and core challenge lie in how to effectively discern and extract visual features from human images under various complex conditions, including cluttered backgrounds, diverse postures, and the presence of occlusions. Some works have employed pose estimation or human key point detection to construct graph-structured information to counteract the effects of occlusions. However, this approach introduces new noise due to issues such as the invisibility of key points. Our proposed module, in contrast, does not require the use of additional feature extractors. Our module employs multi-scale graph attention for the reweighting of feature importance. This allows features to concentrate on areas genuinely pertinent to the re-identification task, thereby enhancing the model’s robustness against occlusions. To address these problems, a model that employs multi-scale graph attention to reweight the importance of features is proposed in this study, significantly enhancing the model’s robustness against occlusions. Our experimental results demonstrate that, compared to baseline models, the method proposed herein achieves a notable improvement in mAP on occluded datasets, with increases of 0.5%, 31.5%, and 12.3% in mAP scores.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ana Augusto, Marco F. L. Lemos, Susana F. J. Silva
Marine-derived nutrients and bioactive compounds may offer a myriad of biological benefits, such as anticancer and anti-inflammatory properties, and technological potential, enhancing food quality as additives. Their role in the sustainable development of food technology is fundamental, especially in advancing the knowledge of functional foods and related technologies. Algae are considered one of the major sources of marine-derived ingredients and the subject of several recent studies. Despite their potential, the translation of marine ingredients’ potential into a marine-based competitiveness of the food industry faces hurdles in the extraction process and operational systems scale-up that the industry needs to tackle. The complexity of marine matrices with diverse compounds and solubilities adds complexity to extraction processes and may lead to low yields or bioactivity loss. Contaminants, like heavy metals and pesticide residues in marine organisms, require rigorous purification processes for product safety. The use of biorefinery systems in marine-based ingredients’ production, particularly cascade processes, offers zero-waste solutions, contributing to the blue economy and aligning with UN sustainability goals. Sustainability assessment tools are critical for evaluating marine-based food production’s environmental, social, and economic impacts. A continued exploration and collaboration are essential for the future, fostering innovation and sustainability to create a resilient, equitable, and eco-friendly food system.
{"title":"Exploring Marine-Based Food Production: The Challenges for a Sustainable and Fast Biotechnology-Based Development","authors":"Ana Augusto, Marco F. L. Lemos, Susana F. J. Silva","doi":"10.3390/app14188255","DOIUrl":"https://doi.org/10.3390/app14188255","url":null,"abstract":"Marine-derived nutrients and bioactive compounds may offer a myriad of biological benefits, such as anticancer and anti-inflammatory properties, and technological potential, enhancing food quality as additives. Their role in the sustainable development of food technology is fundamental, especially in advancing the knowledge of functional foods and related technologies. Algae are considered one of the major sources of marine-derived ingredients and the subject of several recent studies. Despite their potential, the translation of marine ingredients’ potential into a marine-based competitiveness of the food industry faces hurdles in the extraction process and operational systems scale-up that the industry needs to tackle. The complexity of marine matrices with diverse compounds and solubilities adds complexity to extraction processes and may lead to low yields or bioactivity loss. Contaminants, like heavy metals and pesticide residues in marine organisms, require rigorous purification processes for product safety. The use of biorefinery systems in marine-based ingredients’ production, particularly cascade processes, offers zero-waste solutions, contributing to the blue economy and aligning with UN sustainability goals. Sustainability assessment tools are critical for evaluating marine-based food production’s environmental, social, and economic impacts. A continued exploration and collaboration are essential for the future, fostering innovation and sustainability to create a resilient, equitable, and eco-friendly food system.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fei Shan, Hui Li, Zhongren Wang, Ming Jin, Dawei Chen
Maintaining rural highways is crucial in ensuring the reliability and efficiency of transportation infrastructure in modern rural areas. Rural highways often suffer heavy traffic from logistics and regular transportation users. The efficient management of these roads is essential to avoid issues like traffic bottlenecks, fuel consumption, and environmental problems. Traditional maintenance approaches focus on cost reduction, which can lead to adverse effects such as network congestion and environmental damage. To address these challenges, this study proposes a bi-level mathematical programming model aiming at optimizing rural highway maintenance. This model balances maintenance costs, network congestion, system fuel consumption, and environmental impacts. By transforming the bi-level model into a single-level mixed-integer linear programming model, the study enhances the computational feasibility, enabling practical implementation using commercial solvers. The model’s effectiveness is validated through numerical examples, providing insights for the development of optimal maintenance schedules that minimize externality costs while adhering to financial constraints and operational guidelines, providing a valuable addition to the road engineer’s toolbox.
{"title":"Optimizing Rural Highway Maintenance Scheme with Mathematical Programming","authors":"Fei Shan, Hui Li, Zhongren Wang, Ming Jin, Dawei Chen","doi":"10.3390/app14188253","DOIUrl":"https://doi.org/10.3390/app14188253","url":null,"abstract":"Maintaining rural highways is crucial in ensuring the reliability and efficiency of transportation infrastructure in modern rural areas. Rural highways often suffer heavy traffic from logistics and regular transportation users. The efficient management of these roads is essential to avoid issues like traffic bottlenecks, fuel consumption, and environmental problems. Traditional maintenance approaches focus on cost reduction, which can lead to adverse effects such as network congestion and environmental damage. To address these challenges, this study proposes a bi-level mathematical programming model aiming at optimizing rural highway maintenance. This model balances maintenance costs, network congestion, system fuel consumption, and environmental impacts. By transforming the bi-level model into a single-level mixed-integer linear programming model, the study enhances the computational feasibility, enabling practical implementation using commercial solvers. The model’s effectiveness is validated through numerical examples, providing insights for the development of optimal maintenance schedules that minimize externality costs while adhering to financial constraints and operational guidelines, providing a valuable addition to the road engineer’s toolbox.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The genus Pycnoporus includes fungi with great potential for the production of antibiotic substances. It is necessary to develop new models to assess their effectiveness against microorganisms with an economic impact, such as phytopathogenic fungi. The objective of this study is to evaluate three models of Pycnoporus sanguineus for the growth inhibition of the phytopathogens Botrytis cinerea and Fusarium oxysporum. Model 1 involves dual tests of the antagonistic activity of P. sanguineus vs. phytopathogens, Model 2 involves antifungal effectiveness tests of cinnabarin, and Model 3 involves antifungal effectiveness tests of P. sanguineus extract. Models 2 and 3 are contrasted with products containing benomyl and captan. The results show that Model 3 is the most effective in controlling B. cinerea, with an inhibition percentage of 74.34% (p < 0.05) and a decrease in the growth rate (3.85 mm/day; p < 0.05); the same is true for F. oxysporum, with an inhibition percentage of 47.14% (p < 0.05). In general, F. oxysporum exhibits greater resistance (p < 0.05). The results of this study indicate that P. sanguineus extracts may be used as control agents for fungal species in the same way as other Pycnoporus species. Although commercial products are very efficient at inhibiting phytopathogens, one must consider the disadvantages of their use. In the short term, new models involving Pycnoporus for biological control in food production will be developed.
{"title":"Comparison of Three Biological Control Models of Pycnoporus sanguineus on Phytopathogenic Fungi","authors":"Ricardo Irving Pérez-López, Omar Romero-Arenas, Conrado Parraguirre Lezama, Anabel Romero López, Antonio Rivera, Lilia Cedillo Ramírez","doi":"10.3390/app14188263","DOIUrl":"https://doi.org/10.3390/app14188263","url":null,"abstract":"The genus Pycnoporus includes fungi with great potential for the production of antibiotic substances. It is necessary to develop new models to assess their effectiveness against microorganisms with an economic impact, such as phytopathogenic fungi. The objective of this study is to evaluate three models of Pycnoporus sanguineus for the growth inhibition of the phytopathogens Botrytis cinerea and Fusarium oxysporum. Model 1 involves dual tests of the antagonistic activity of P. sanguineus vs. phytopathogens, Model 2 involves antifungal effectiveness tests of cinnabarin, and Model 3 involves antifungal effectiveness tests of P. sanguineus extract. Models 2 and 3 are contrasted with products containing benomyl and captan. The results show that Model 3 is the most effective in controlling B. cinerea, with an inhibition percentage of 74.34% (p < 0.05) and a decrease in the growth rate (3.85 mm/day; p < 0.05); the same is true for F. oxysporum, with an inhibition percentage of 47.14% (p < 0.05). In general, F. oxysporum exhibits greater resistance (p < 0.05). The results of this study indicate that P. sanguineus extracts may be used as control agents for fungal species in the same way as other Pycnoporus species. Although commercial products are very efficient at inhibiting phytopathogens, one must consider the disadvantages of their use. In the short term, new models involving Pycnoporus for biological control in food production will be developed.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: This systematic literature review aims to explore the impact of rehabilitation in post-stroke patients, particularly highlighting the roles of virtual reality (VR) technology and functional electrical stimulation (FES). Methods: To ensure all relevant studies were included, a thorough search was conducted in PubMed and Web of Science databases using keywords such as ‘post-stroke’, ‘FES’, ‘functional electrical stimulation’, ‘virtual reality’, and ‘VR’. Studies on rehabilitating upper limb function through VR and FES in post-stroke patients were included, regardless of publication year. Studies had to compare this combination therapy with conventional methods and report outcomes related to upper limb coordination, functional mobility, and daily activities. Studies not meeting these criteria were excluded. The selection process involved screening titles, abstracts, and full texts by four independent reviewers. The quality and risk of bias of the included studies were assessed using the PEDro scale and Robvis tool. Results: The review included four studies involving 135 post-stroke patients. Two articles examined the effectiveness of an approach involving virtual reality, robotic therapy, and functional electrical stimulation in rehabilitating upper limbs in post-stroke patients, showing significant improvements in motor function and quality of life. The other two studies explored the effects of rehabilitation therapy using virtual reality combined with functional electrical stimulation on upper limb function in stroke patients, finding that combined therapy (FES with VR) was superior to functional electrical stimulation or robotic therapy. Discussion: The review was limited by the small number of studies and participants, which may affect the generalizability of the results. Variations in intervention protocols and outcome measures across studies posed challenges in synthesis. Integrating these technologies brings benefits and increases the potential for personalizing and optimizing the rehabilitation process, enhancing patient engagement and satisfaction, and promoting a holistic approach to post-stroke management. Future research should focus on larger, more standardized trials to confirm these findings and optimize intervention protocols.
背景：本系统性文献综述旨在探讨康复治疗对脑卒中后患者的影响，尤其强调虚拟现实（VR）技术和功能性电刺激（FES）的作用。研究方法为确保纳入所有相关研究，我们在 PubMed 和 Web of Science 数据库中使用 "中风后"、"FES"、"功能性电刺激"、"虚拟现实 "和 "VR "等关键词进行了全面搜索。有关中风后患者通过虚拟现实和功能性电刺激康复上肢功能的研究，无论发表年份如何，均包括在内。研究必须将这种综合疗法与传统方法进行比较，并报告与上肢协调性、功能移动性和日常活动相关的结果。不符合这些标准的研究将被排除在外。筛选过程包括由四位独立审稿人筛选标题、摘要和全文。采用 PEDro 量表和 Robvis 工具对纳入研究的质量和偏倚风险进行评估。结果综述包括四项研究，涉及 135 名中风后患者。其中两篇文章探讨了虚拟现实、机器人疗法和功能性电刺激在中风后患者上肢康复中的有效性，结果显示运动功能和生活质量均有显著改善。另外两项研究探讨了使用虚拟现实技术结合功能性电刺激对中风患者上肢功能进行康复治疗的效果，结果发现联合疗法（功能性电刺激与虚拟现实技术）优于功能性电刺激或机器人疗法。讨论：本综述受限于研究数量和参与人数较少，这可能会影响结果的普遍性。不同研究的干预方案和结果测量存在差异，这给综述带来了挑战。整合这些技术会带来益处，并增加个性化和优化康复过程的潜力，提高患者的参与度和满意度，促进卒中后管理的整体方法。未来的研究应侧重于更大规模、更标准化的试验，以证实这些发现并优化干预方案。
{"title":"Virtual Reality Associated with Functional Electrical Stimulation for Upper Extremity in Post-Stroke Rehabilitation: A Systematic Review","authors":"Diana Minzatanu, Nadinne Alexandra Roman, Adina Ionelia Manaila, Ionut Cristian Cozmin Baseanu, Vlad Ionut Tuchel, Elena Bianca Basalic, Roxana Steliana Miclaus","doi":"10.3390/app14188248","DOIUrl":"https://doi.org/10.3390/app14188248","url":null,"abstract":"Background: This systematic literature review aims to explore the impact of rehabilitation in post-stroke patients, particularly highlighting the roles of virtual reality (VR) technology and functional electrical stimulation (FES). Methods: To ensure all relevant studies were included, a thorough search was conducted in PubMed and Web of Science databases using keywords such as ‘post-stroke’, ‘FES’, ‘functional electrical stimulation’, ‘virtual reality’, and ‘VR’. Studies on rehabilitating upper limb function through VR and FES in post-stroke patients were included, regardless of publication year. Studies had to compare this combination therapy with conventional methods and report outcomes related to upper limb coordination, functional mobility, and daily activities. Studies not meeting these criteria were excluded. The selection process involved screening titles, abstracts, and full texts by four independent reviewers. The quality and risk of bias of the included studies were assessed using the PEDro scale and Robvis tool. Results: The review included four studies involving 135 post-stroke patients. Two articles examined the effectiveness of an approach involving virtual reality, robotic therapy, and functional electrical stimulation in rehabilitating upper limbs in post-stroke patients, showing significant improvements in motor function and quality of life. The other two studies explored the effects of rehabilitation therapy using virtual reality combined with functional electrical stimulation on upper limb function in stroke patients, finding that combined therapy (FES with VR) was superior to functional electrical stimulation or robotic therapy. Discussion: The review was limited by the small number of studies and participants, which may affect the generalizability of the results. Variations in intervention protocols and outcome measures across studies posed challenges in synthesis. Integrating these technologies brings benefits and increases the potential for personalizing and optimizing the rehabilitation process, enhancing patient engagement and satisfaction, and promoting a holistic approach to post-stroke management. Future research should focus on larger, more standardized trials to confirm these findings and optimize intervention protocols.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study analyzes the turbomachinery flow of a gas turbine using OpenFOAM, an open-source CFD code. While foam-extend, a version of OpenFOAM, includes tools for turbomachinery analysis, some of its codes are incomplete, resulting in incorrect results. Consequently, this study required the investigation and correction of the solvers and libraries. Specifically, foam-extend-4.1 and a compressible multi-reference-frame solver were utilized. Two primary errors related to temperature calculation were identified. The first error involved temperature discontinuity at the interface between the stator and rotor domain when using the mixingPlane. The second error was related to temperature rising at the wall. To address the temperature discontinuity problem, the rothalpy jump equation in the enthalpyJump code was modified from a scalar product to an inner product of vectors. To resolve the high-temperature problem at the wall, modifications were made to the energy equation code in iEqn.H. A rothalpy separation was introduced, and the rothalpy equation was adjusted to mimic the enthalpy equation. The results obtained with the corrected codes were consistent with those from the commercial code, demonstrating the effectiveness of the modifications.
{"title":"Improvement on Compressible Multiple-Reference-Frame Solver in OpenFOAM for Gas Turbine Flow Analysis","authors":"Seung-Hwan Kang, Dong-Ho Rhee, Young Seok Kang","doi":"10.3390/app14188269","DOIUrl":"https://doi.org/10.3390/app14188269","url":null,"abstract":"This study analyzes the turbomachinery flow of a gas turbine using OpenFOAM, an open-source CFD code. While foam-extend, a version of OpenFOAM, includes tools for turbomachinery analysis, some of its codes are incomplete, resulting in incorrect results. Consequently, this study required the investigation and correction of the solvers and libraries. Specifically, foam-extend-4.1 and a compressible multi-reference-frame solver were utilized. Two primary errors related to temperature calculation were identified. The first error involved temperature discontinuity at the interface between the stator and rotor domain when using the mixingPlane. The second error was related to temperature rising at the wall. To address the temperature discontinuity problem, the rothalpy jump equation in the enthalpyJump code was modified from a scalar product to an inner product of vectors. To resolve the high-temperature problem at the wall, modifications were made to the energy equation code in iEqn.H. A rothalpy separation was introduced, and the rothalpy equation was adjusted to mimic the enthalpy equation. The results obtained with the corrected codes were consistent with those from the commercial code, demonstrating the effectiveness of the modifications.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Person re-identification (Re-ID) is a technique for identifying target pedestrians in images or videos. In recent years, owing to the advancements in deep learning, research on person re-identification has made significant progress. However, current methods mostly focus on salient regions within the entire image, overlooking certain hidden features specific to pedestrians themselves. Motivated by this consideration, we propose a novel person re-identification network. Our approach integrates pedestrian edge features into the representation and utilizes edge information to guide global context feature extraction. Additionally, by modeling the internal relationships between different parts of pedestrians, we enhance the network’s ability to capture and understand the interdependencies within pedestrians, thereby improving the semantic coherence of pedestrian features. Ultimately, by fusing these multifaceted features, we generate comprehensive and highly discriminative representations of pedestrians, significantly enhancing person Re-ID performance. Experimental results demonstrate that our method outperforms most state-of-the-art approaches in person re-identification.
{"title":"Person Re-Identification Network Based on Edge-Enhanced Feature Extraction and Inter-Part Relationship Modeling","authors":"Chuan Zhu, Wenjun Zhou, Jianmin Ma","doi":"10.3390/app14188244","DOIUrl":"https://doi.org/10.3390/app14188244","url":null,"abstract":"Person re-identification (Re-ID) is a technique for identifying target pedestrians in images or videos. In recent years, owing to the advancements in deep learning, research on person re-identification has made significant progress. However, current methods mostly focus on salient regions within the entire image, overlooking certain hidden features specific to pedestrians themselves. Motivated by this consideration, we propose a novel person re-identification network. Our approach integrates pedestrian edge features into the representation and utilizes edge information to guide global context feature extraction. Additionally, by modeling the internal relationships between different parts of pedestrians, we enhance the network’s ability to capture and understand the interdependencies within pedestrians, thereby improving the semantic coherence of pedestrian features. Ultimately, by fusing these multifaceted features, we generate comprehensive and highly discriminative representations of pedestrians, significantly enhancing person Re-ID performance. Experimental results demonstrate that our method outperforms most state-of-the-art approaches in person re-identification.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to strengthen the security of autonomous vehicles by analyzing the current status of autonomous vehicle security, such as autonomous vehicle features, security threats, and compliance, and deriving security-level check items. Based on this, the relative importance could be obtained by applying it to the AHP (Analytic Hierarchy Process) model. The results of the empirical analysis showed that the order of priority was the establishment/implementation of a cybersecurity management system, encryption, and risk assessment. The significance of this study is that by deriving security-level check items related to autonomous vehicles and verifying the research model, we can reduce cyber security accidents that can cause loss of life and improve the level of autonomous vehicle security management of related companies. Additionally, by applying AHP evaluated by security experts to the autonomous vehicle field for the first time, it will contribute to the market expansion of the autonomous vehicle industry, which is concerned with security. Furthermore, major automobile companies have to manage the security levels of numerous tier companies due to the nature of the industry. Therefore, if they perform a Quick Check (QC) considering the relative importance of the autonomous vehicle security-level check items presented in this paper, they will be able to effectively identify the security levels of tier companies early.
{"title":"Autonomous Vehicle Ecosystem Security: Utilizing Autonomous Vehicle Security-Level Checks through Analytic Hierarchy Process","authors":"Dong-Sung Lim, Sang-Joon Lee","doi":"10.3390/app14188247","DOIUrl":"https://doi.org/10.3390/app14188247","url":null,"abstract":"This study aimed to strengthen the security of autonomous vehicles by analyzing the current status of autonomous vehicle security, such as autonomous vehicle features, security threats, and compliance, and deriving security-level check items. Based on this, the relative importance could be obtained by applying it to the AHP (Analytic Hierarchy Process) model. The results of the empirical analysis showed that the order of priority was the establishment/implementation of a cybersecurity management system, encryption, and risk assessment. The significance of this study is that by deriving security-level check items related to autonomous vehicles and verifying the research model, we can reduce cyber security accidents that can cause loss of life and improve the level of autonomous vehicle security management of related companies. Additionally, by applying AHP evaluated by security experts to the autonomous vehicle field for the first time, it will contribute to the market expansion of the autonomous vehicle industry, which is concerned with security. Furthermore, major automobile companies have to manage the security levels of numerous tier companies due to the nature of the industry. Therefore, if they perform a Quick Check (QC) considering the relative importance of the autonomous vehicle security-level check items presented in this paper, they will be able to effectively identify the security levels of tier companies early.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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