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1 |
Assessing surface drainage conditions at the street and neighborhood scale: A computer vision and flow direction method applied to lidar data
ارزیابی شرایط زهکشی سطحی در مقیاس خیابان و محله: یک روش دید کامپیوتری و جهت جریان اعمال شده به داده های لیدار-2022 Surface drainage at the neighborhood and street scales plays an important role in conveying stormwater and
mitigating urban flooding. Surface drainage at the local scale is often ignored due to the lack of up-to-date fine-
scale topographical information. This paper addresses this issue by providing a novel method for evaluating
surface drainage at the neighborhood and street scales based on mobile lidar (light detection and ranging)
measurements. The developed method derives topographical properties and runoff accumulation by applying a
semantic segmentation (SS) model (a computer vision technique) and a flow direction model (a hydrology
technique) to lidar data. Fifty lidar images representing 50 street blocks were used to train, validate, and test the
SS model. Based on the test dataset, the SS model has 80.3% IoU and 88.5% accuracy. The results suggest that the
proposed method can effectively evaluate surface drainage conditions at both the neighborhood and street scales
and identify problematic low points that could be susceptible to water ponding. Municipalities and property
owners can use this information to take targeted corrective maintenance actions. keywords: تقسیم بندی معنایی | جهت جریان | لیدار موبایل | زهکشی سطحی | زیرساخت های زهکشی | Semantic segmentation | Flow direction | Mobile lidar | Surface drainage | Drainage infrastructure |
مقاله انگلیسی |
2 |
Computer vision for solid waste sorting: A critical review of academic research
بینایی کامپیوتری برای تفکیک زباله جامد: مروری انتقادی تحقیقات دانشگاهی-2022 Waste sorting is highly recommended for municipal solid waste (MSW) management. Increasingly, computer
vision (CV), robotics, and other smart technologies are used for MSW sorting. Particularly, the field of CV-
enabled waste sorting is experiencing an unprecedented explosion of academic research. However, little atten-
tion has been paid to understanding its evolvement path, status quo, and prospects and challenges ahead. To
address the knowledge gap, this paper provides a critical review of academic research that focuses on CV-enabled
MSW sorting. Prevalent CV algorithms, in particular their technical rationales and prediction performance, are
introduced and compared. The distribution of academic research outputs is also examined from the aspects of
waste sources, task objectives, application domains, and dataset accessibility. The review discovers a trend of
shifting from traditional machine learning to deep learning algorithms. The robustness of CV for waste sorting is
increasingly enhanced owing to the improved computation powers and algorithms. Academic studies were un-
evenly distributed in different sectors such as household, commerce and institution, and construction. Too often,
researchers reported some preliminary studies using simplified environments and artificially collected data.
Future research efforts are encouraged to consider the complexities of real-world scenarios and implement CV in
industrial waste sorting practice. This paper also calls for open sharing of waste image datasets for interested
researchers to train and evaluate their CV algorithms. keywords: زباله جامد شهری | تفکیک زباله | بینایی ماشین | تشخیص تصویر | یادگیری ماشین | یادگیری عمیق | Municipal solid waste | Waste sorting | Computer vision | Image recognition | Machine learning | Deep learning |
مقاله انگلیسی |
3 |
PortiK: A computer vision based solution for real-time automatic solid waste characterization – Application to an aluminium stream
PortiK: یک راه حل مبتنی بر بینایی کامپیوتری برای شناسایی خودکار زباله جامد در زمان واقعی - کاربرد در جریان آلومینیوم-2022 In Material Recovery Facilities (MRFs), recyclable municipal solid waste is turned into a precious commodity.
However, effective recycling relies on effective waste sorting, which is still a challenge to sustainable develop-
ment of our society. To help the operations improve and optimise their process, this paper describes PortiK, a
solution for automatic waste analysis. Based on image analysis and object recognition, it allows for continuous,
real-time, non-intrusive measurements of mass composition of waste streams. The end-to-end solution is detailed
with all the steps necessary for the system to operate, from hardware specifications and data collection to su-
pervisory information obtained by deep learning and statistical analysis. The overall system was tested and
validated in an operational environment in a material recovery facility.
PortiK monitored an aluminium can stream to estimate its purity. Aluminium cans were detected with 91.2%
precision and 90.3% recall, respectively, resulting in an underestimation of the number of cans by less than 1%.
Regarding contaminants (i.e. other types of waste), precision and recall were 80.2% and 78.4%, respectively,
giving an 2.2% underestimation. Based on five sample analyses where pieces of waste were counted and weighed
per batch, the detection results were used to estimate purity and its confidence level. The estimation error was
calculated to be within ±7% after 5 minutes of monitoring and ±5% after 8 hours. These results have demon-
strated the feasibility and the relevance of the proposed solution for online quality control of aluminium can
stream. keywords: امکانات بازیابی مواد | شناسایی مواد زائد جامد | یادگیری عمیق | شبکه عصبی عمیق | بینایی کامپیوتر | Material recovery facilities | MRF | Solid waste characterization | Deep-learning | Deep neural network | Computer vision |
مقاله انگلیسی |
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Utilizing LiDAR data to map tree canopy for urban ecosystem extent and condition accounts in Oslo
با استفاده از داده های LIDAR به نقشه سایبان درخت برای اکوسیستم های شهری و حساب های وضعیت در اسلو-2021 LiDAR-based segmentation of urban tree canopies and their physical properties (canopy height, canopy diameter,
3D surface and volume) is a replicable, complementary and useful information source for urban ecosystem
condition accounts, and an important basis for ecosystem service modeling and valuation. However, using
available LiDAR data collected for municipal purposes other than vegetation mapping (such as for example
engineering) entails a level of accuracy which may limit the usefulness of the data for change detection in
ecosystem accounts. To account for changes in the urban tree canopy of Oslo (capital city of Norway) between
2011 and 2017, a segmentation model was developed based on available airborne LiDAR data scanned for
general purposes. The results from the entire built-up area of Oslo indicate a general increase in the number of
tall trees (>15 m) and a moderate increase in the number of small trees (<15 m), with the exception of trees
between 6 and 10 m which seem to have a relatively constant development over the given period. The total tree
canopy area within the built-up area increased by 17.15%, with a corresponding 21.35% increase in the tree
canopy volume. The results for the Small House plan area, a policy focus area subject to urban densification and
special regulations for felling of large trees, indicate a large increase in small trees (<10 m) and a moderate
decrease in tall trees (>10 m). The total tree canopy area within the Small House plan area decreased by 1.04%,
with a corresponding 2.13% decrease in the tree canopy volume. With respect to the segmentation accuracy, the
changes in aggregate tree canopy cover are too small to determine canopy change with confidence. This study
demonstrates the potential for identifying ecosystem condition indicators as well as the limitations of using
general purpose LiDAR data to improve the precision of urban ecosystem accounting. For future ecosystem
service accounting in urban environments, we recommend that municipalities implement data acquisition programs that combine concurrent field data sampling and LiDAR campaigns designed for urban tree canopy
detection, as part of general urban structural inventorying. We recommend using LiDAR and satellite remote
sensing data depending on canopy densities. We also recommend that future tree canopy segmentation is done
within a cloud-computing environment to ensure sufficient geoprocessing capacity.
keywords: تشخیص نور و محدوده (LIDAR) | سیستم های اطلاعات جغرافیایی (GIS) | سنجش از راه دور | حسابداری اکوسیستم | خدمات محیط زیستی | تقسیم بندی سایبان درخت | Light Detection And Ranging (LiDAR) | Geographical Information Systems (GIS) | Remote sensing | Ecosystem accounting | Ecosystem services | Tree canopy segmentation |
مقاله انگلیسی |
5 |
Knowledge of Opioid-induced Respiratory Depression Among Chinese Healthcare Professionals:A Cross-Sectional Study
شناخت افسردگی تنفسی ناشی از مواد مخدر در میان متخصصان مراقبت های بهداشتی چینی: یک مطالعه مقطعی-2021 Purpose: The purposes of this study were to measure knowledge about opioid-induced
respiratory depression (OIRD) among Chinese healthcare professionals and to explore
the associated factors that influence Chinese healthcare professionals’s knowledge
Methods: A cross-sectional survey was conducted. A convenience sample of 90 0 Chinese healthcare professionals from 21 provinces, 4 municipalities, and 4 a utonomous regions was used. The OIRD knowledge questionnaire, which is a s elf-designed questionnaire based on evidence, was used to judges the degree of knowledge among Chinese healthcare professionals according to the accuracy r ate. The questionnaire included questions on 6 dimensions of knowledge. Socio -demographic characteristics were also measured by amulti-item questionnaire. Results: The mean accuracy and correct response rate range on the OIRD kno wledge questionnaire for all participants were 64.5±10.0% and 20%-100%, resp ectively. According to univariate analysis, Chinese healthcare professionals’ OIR D knowledge was positively correlated with age, region, profession, hospital lev el, type of hospitals and departments, education level, years of clinical working, and clinical practice of chronic cancer pain management. Multiple linear regress ion analysis showed differences in professions and regions.( all p<0. 0 5) . Conclusions Most Chinese healthcare professionals had misconceptions about O IRD and lacked relevant knowledge. We should assign importance to developin g targeted training programs and exploring feasible and effective training metho ds. keywords: Cancer pain | Opioid-induced respiratory depression | Knowledge | Healthcare professionals | Opioid-induced adverse |
مقاله انگلیسی |
6 |
Beyond blue: An extended framework of blue water footprint accounting
فراتر از آبی: یک چارچوب گسترده ای از حسابداری آبی آب آبی-2021 The water use of societies results in multiple environmental and social impacts and is a fundamental component
of sustainability. Correspondingly, water footprint studies have grown significantly in numbers over the last decade. However, these studies mostly account for the human appropriation of freshwater resources, while
overlooking various alternative water resources. This paper responds to the growing need for a complete
water footprint accounting and presents an extended framework of the blue water footprint, comprised of
seven water types. A case study shows spatially-explicit and use-specific analysis of Israels diverse water system.
Israels freshwater use accounts for only 40% of its total water use. Desalinated seawater and reused wastewater
contribute 52% and 45% to the countrys municipal and agricultural water use, respectively. The “original” blue
water footprint assumes only freshwater use; thus, it overestimates the appropriation of natural water resources
by humans. The extended blue water footprint accounts for seawater, brackish water, runoff, and reused wastewater along with surface water and fresh groundwater. It, therefore, estimates the human water use more
accurately.
Alternative water types use has some adverse environmental and health impacts. These include high energy intensity due to desalination, soil salinization from brackish water irrigation, and human exposure to traces of pharmaceutical in drinking water due to treated wastewater irrigation. By acknowledging the water mix of different sectors and regions, the extended blue water footprint contributes to advancing a water-energy nexus analysis or accounting for various environmental and health impacts of water use. keywords: دفع آب | مخلوط آب | تعاملات انسانی محیط زیست | Water-footprint | Water-mix | Human-environment-interactions |
مقاله انگلیسی |
7 |
Supply chain management of butyric acid-derived butanol: Stochastic approach
مدیریت زنجیره تأمین بوتانول مشتق از اسید بوتیریک: رویکرد تصادفی-2021 In this study, a stochastic model for strategic planning of the butyric acid-to-butanol supply chain network (Ba- to-Bu SCN) is developed to consider variations in the butanol (Bu) demand and butyric acid (Ba) supply derived from industrial/municipal waste. The proposed stochastic model can help determine where and how much Ba to process, Bu to produce, and Ba/Bu to transport to minimize the total cost of the Ba-to-Bu SCN design under Ba processing and Bu demand uncertainties. The features and capabilities of the stochastic model are validated and compared to those of the deterministic model by application of the future Ba-to-Bu SCN design for South Korea in 2030. The optimization results illustrate that the expected total cost of Ba-derived Bu by the stochastic model (US$4898.55 thousand per year) was at least 0.18% more economical that that of the deterministic model (US$4889.72 thousand per year). The goal of this study is to develop a decision making tool for a stochastic strategic problem to improve bio-economy caused by uncertainties. The proposed approach will help balance cost efficiency with stability in the uncertain future biorefinery infrastructure. Keywords: Strategic planning | Optimization | Organic waste | Stochastic model | Butanol | Supply chain |
مقاله انگلیسی |
8 |
Evaluating the urban metabolism sustainability of municipal solid waste management system: An extended exergy accounting and indexing perspective
ارزیابی متابولیسم شهری پایداری سیستم مدیریت ضایعات جامد شهری: حسابداری اگزرژی گسترده و دیدگاه نمایه سازی-2021 In this study, Extended Exergy Accounting was adopted to develop an accounting model to evaluate the performance of a Municipal Solid Waste Management System. Furthermore, urban metabolism sustainability index
for waste was also proposed to represent the unified society-economy-environment impacts of the MSWMS under
the framework of a comprehensive sustainability evaluation. A detailed analysis of wood and horticultural waste
treatment scenarios in Singapore was done as a case study. It was found that the gasification scenario theoretically performs significantly better than the incineration scenario, in terms of energy carrier consumption,
emissions, thermodynamic efficiency and sustainability. Analysis results show that, if extrapolated to Singapore’s
total wood and horticultural waste, gasification technology has potential to reduce energy consumption and
increase electricity output. An uncertainty analysis was carried out and it was found that the main extended
exergetic parameters of the two scenarios considered were in the range of 3–8%, thus confirming the reliability of the accounting results. A sensitivity analysis of the urban metabolism sustainability index for waste was conducted for the gasification scenario to identify key influencing factors and seek potential improvements; this was
done by considering changes in four variables: transportation distance, electrical efficiency, working hour
increment and gross capital cost per ton waste treated. It was found that, to ensure the feasibility and sustainability of gasification scenario, the following are required: keeping the electricity production efficiency greater
than 21.33%; the transportation distance between the gasification power plant and source of wood and horticultural waste should be kept within 17.08 km; employment of per kton annual treatment capacity should be less
than 0.14 workers; wood and horticultural waste source should control the waste collection frequency of no more
than 3 times per day and the number of workers participating in the collection each time is less than 4 persons,
totaling to 12 workers per day.
keywords: تجزیه و تحلیل Exergy را گسترش دهید | زباله جامد شهری | ارزیابی پایداری | متابولیسم شهری | اگزرژی کار | Exergy اصلاح محیط زیست | Extend exergy analysis | Municipal solid waste | Sustainability assessment | Urban metabolism | Labor exergy | Environmental remediation exergy |
مقاله انگلیسی |
9 |
A data management framework for strategic urban planning using blue-green infrastructure
یک چارچوب مدیریت داده برای برنامه ریزی شهری استراتژیک با استفاده از زیرساخت های آبی سبز-2021 Spatial planning of Blue-Green Infrastructure (BGI) should ideally be based on well-evaluated and context
specific solutions. One important obstacle to reach this goal relates to adequate provisioning of data to ensure
good governance of BGI, i.e., appropriate planning, design, construction, and maintenance. This study explores
the gap between data availability and implementation of BGI in urban planning authorities in Sweden. A multi
method approach including brainstorming, semi-structured interviews with urban planners and experts on BGI
and Geographical Information System (GIS), and validating workshops were performed to develop a framework
for structured and user-friendly data collection and use. Identified challenges concern data availability, data
management, and GIS knowledge. There is a need to improve the organisation of data management and the skills
of trans-disciplinary cooperation to better understand and interpret different types of data. Moreover, different
strategic goals require different data to ensure efficient planning of BGI. This calls for closer interactions between
development of strategic political goals and data collection. The data management framework consists of three
parts: A) Ideal structure of data management in relation to planning process, data infrastructure and organisa-
tional structure, and B) A generic list of data needed, and C) The development of structures for data gathering
and access. We conclude that it is essential to develop pan-municipal data management systems that bridge
sectors and disciplines to ensure efficient management of the urban environment, and which is able to support
the involvement of citizens to collect and access relevant data. The framework can assist in such development. keywords: زیرساخت آبی سبز | مدیریت اطلاعات | برنامه ریزی فضایی | برنامه ریزی استراتژیک | مدیریت طوفان | انطباق تغییرات اقلیمی | فضاهای سبز شهری | Blue-green infrastructure | Data management | Spatial planning | Strategic planning | Stormwater management | Climate change adaptation | Urban green spaces |
مقاله انگلیسی |
10 |
Towards a circular economy for sustainable development: An application of full cost accounting to municipal waste recyclables
به سمت یک اقتصاد دایره ای برای توسعه پایدار: استفاده از هزینه های کامل حسابداری به بازیافت های زباله های شهری-2021 From a circular economy perspective, the municipal waste (MW) sector remains a valuable input source
for waste recyclable re-industrialization among food, pollution, and energy. In this study, different accounting approaches and scenarios for sustainable MW management are explored to find the most cost
efficient and profitable approach. The Full Cost Accounting (FCA) method is adopted as the basis of
analysis in this study where an integrated sustainable framework for the Pay-As-You-Throw (PAYT)
pricing model is developed and designed that can optimize MW management in attaining ‘zero waste
disposal’ at the lowest cost as well as generating economic, environmental and social benefits. Using
waste management data from 27 councils in Egypt and two different PAYT methods (i.e. weight-based
and volume-based) under three case scenarios, this study documents that the prepaid bag system under the volume-based PAYT method leads to the lowest waste costs and creates more incentives for
households in terms of economic, social and environmental benefits. These findings have various implications for the policy makers, government councils, waste managers, businesses and communities in
the adoption of volume based PAYT schemes for cost-effective, profitable and socially acceptable reusing
and recycling of waste. Such valuable addition to MW management can contribute to the environmental
and socially sustainable development in emerging markets and in moving towards a circular economy
model.
keywords: اقتصاد دایره ای | پایداری | توسعه پایدار | مواد قابل بازیافت شهرداری | Pay-as-you-throw (payt) هزینه کامل | رویکرد حسابداری | بازار در حال ظهور | Circular economy | Sustainability | Sustainable development | Municipal waste recyclables | Pay-as-you-throw (PAYT) full cost | accounting approach | Emerging market |
مقاله انگلیسی |