The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To a...The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.展开更多
Despite cities being recognized as being potential sources of microplastic pollution to the wider environment, most surveys of COVID-19 plastic-based litter have been undertaken through linear transects of marine beac...Despite cities being recognized as being potential sources of microplastic pollution to the wider environment, most surveys of COVID-19 plastic-based litter have been undertaken through linear transects of marine beaches. For the far fewer number of studies conducted on inland and urban locations, the site-specific focus has primarily been surveys along the length of streets. The present study is the first to specifically assess the standing stock (i.e., moment-in-time) of littered face masks for the entire surface area of urban parking lots. The density of face masks in 50 parking lots in a Canadian coastal town (0.00054 m2 ± 0.00051 m2) was found to be significantly greater than the background level of littering of town streets. Face mask density was significantly related to visitation “usage” of parking lots as gauged by the areal size of the lots and of their onsite buildings, as well as the number of vehicles present. Neither parking lot typology nor estimates of inferred export (various measures of wind exposure) and entrapment (various metrics of obstruction) of face masks had a significant influence on the extent of whole-lot littering. In consequence, modelling of the potential input of mask-derived microplastics to the marine environment from coastal communities can use the areal density of face masks found here in association with the total surface area of lots for individual municipalities as determined through GIS analysis.展开更多
In recent years,disorderly parking and difficult charging of electric bicycles have been challenges in urban management.The rapid growth of electric bicycles is in contradiction with the lack of dedicated parking spac...In recent years,disorderly parking and difficult charging of electric bicycles have been challenges in urban management.The rapid growth of electric bicycles is in contradiction with the lack of dedicated parking spaces and charging service facilities in towns and villages.To solve the issue of parking and charging electric bicycles in limited urban and rural spaces,prefabricated building technology is applied to the design of a multi-story electric bicycle parking lot.The multi-story prefabricated electric bicycle parking lot is utilized in urban and rural planning and design to upgrade parking facilities in old urban areas,land-constrained commercial areas,as well as counties,towns,and rural areas with inadequate municipal facilities.Multi-story prefabricated electric bicycle parking lots are the application exploration of industrial buildings,and promote the high-quality development planning and construction of towns and counties and villages.Compared with the single-story metal charging station,the multi-story assembled electric bicycle parking lot has the characteristics of integrating parking and charging,being more durable and safer in structure,accommodating a large number of vehicles,and improving the space utilization rate.展开更多
针对目前智能楼宇监测中数据可靠性低、测量点位分散、数据传输实时性不高和误报频繁等问题,提出基于物联网(Internet of Things,IoT)技术的智能楼宇监测系统设计。首先,采用ZigBee技术组建无线传感器网络,实现分散点位传感器数据的收集...针对目前智能楼宇监测中数据可靠性低、测量点位分散、数据传输实时性不高和误报频繁等问题,提出基于物联网(Internet of Things,IoT)技术的智能楼宇监测系统设计。首先,采用ZigBee技术组建无线传感器网络,实现分散点位传感器数据的收集,并将数据通过网关传输到物联网云平台。其次,利用改进的自适应加权算法融合传感器数据,有效提升多传感器检测数据的准确性。系统云平台能够分析和展示传感器数据,而且能够实时查看待测区域的视频图像,预留数据分析接口。应用表明,系统数据测量准确、相对误差较低、稳定性较好。展开更多
笔者在中国文化背景下对生活定向测验(Life Orientation Test ;LOT)与其修订版(LOT-R)的维度进行验证.采用主成分分析结合平行分析保留主成分数目,同时采用验证性因素分析比较不同模型对生活定向测验及其修订版反应数据的拟合.大多数测...笔者在中国文化背景下对生活定向测验(Life Orientation Test ;LOT)与其修订版(LOT-R)的维度进行验证.采用主成分分析结合平行分析保留主成分数目,同时采用验证性因素分析比较不同模型对生活定向测验及其修订版反应数据的拟合.大多数测验形式都呈现出两个维度,违背了测验编制者假定的单维性,与西方大多数研究者的结果一致,但是得到的两个维度是有实质意义的还是由于项目形式造成的则很难确定.在传统的因素分析框架下很难解决生活定向测验的维度争议,未来的研究应该从项目反应的理想点过程出发对该测验的维度进行探索和验证.展开更多
基金This research is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan,Grant No.AP19674517.
文摘The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.
文摘Despite cities being recognized as being potential sources of microplastic pollution to the wider environment, most surveys of COVID-19 plastic-based litter have been undertaken through linear transects of marine beaches. For the far fewer number of studies conducted on inland and urban locations, the site-specific focus has primarily been surveys along the length of streets. The present study is the first to specifically assess the standing stock (i.e., moment-in-time) of littered face masks for the entire surface area of urban parking lots. The density of face masks in 50 parking lots in a Canadian coastal town (0.00054 m2 ± 0.00051 m2) was found to be significantly greater than the background level of littering of town streets. Face mask density was significantly related to visitation “usage” of parking lots as gauged by the areal size of the lots and of their onsite buildings, as well as the number of vehicles present. Neither parking lot typology nor estimates of inferred export (various measures of wind exposure) and entrapment (various metrics of obstruction) of face masks had a significant influence on the extent of whole-lot littering. In consequence, modelling of the potential input of mask-derived microplastics to the marine environment from coastal communities can use the areal density of face masks found here in association with the total surface area of lots for individual municipalities as determined through GIS analysis.
文摘In recent years,disorderly parking and difficult charging of electric bicycles have been challenges in urban management.The rapid growth of electric bicycles is in contradiction with the lack of dedicated parking spaces and charging service facilities in towns and villages.To solve the issue of parking and charging electric bicycles in limited urban and rural spaces,prefabricated building technology is applied to the design of a multi-story electric bicycle parking lot.The multi-story prefabricated electric bicycle parking lot is utilized in urban and rural planning and design to upgrade parking facilities in old urban areas,land-constrained commercial areas,as well as counties,towns,and rural areas with inadequate municipal facilities.Multi-story prefabricated electric bicycle parking lots are the application exploration of industrial buildings,and promote the high-quality development planning and construction of towns and counties and villages.Compared with the single-story metal charging station,the multi-story assembled electric bicycle parking lot has the characteristics of integrating parking and charging,being more durable and safer in structure,accommodating a large number of vehicles,and improving the space utilization rate.
文摘针对目前智能楼宇监测中数据可靠性低、测量点位分散、数据传输实时性不高和误报频繁等问题,提出基于物联网(Internet of Things,IoT)技术的智能楼宇监测系统设计。首先,采用ZigBee技术组建无线传感器网络,实现分散点位传感器数据的收集,并将数据通过网关传输到物联网云平台。其次,利用改进的自适应加权算法融合传感器数据,有效提升多传感器检测数据的准确性。系统云平台能够分析和展示传感器数据,而且能够实时查看待测区域的视频图像,预留数据分析接口。应用表明,系统数据测量准确、相对误差较低、稳定性较好。
文摘笔者在中国文化背景下对生活定向测验(Life Orientation Test ;LOT)与其修订版(LOT-R)的维度进行验证.采用主成分分析结合平行分析保留主成分数目,同时采用验证性因素分析比较不同模型对生活定向测验及其修订版反应数据的拟合.大多数测验形式都呈现出两个维度,违背了测验编制者假定的单维性,与西方大多数研究者的结果一致,但是得到的两个维度是有实质意义的还是由于项目形式造成的则很难确定.在传统的因素分析框架下很难解决生活定向测验的维度争议,未来的研究应该从项目反应的理想点过程出发对该测验的维度进行探索和验证.
