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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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Combining computer vision with semantic reasoning for on-site safety management in construction
ترکیب بینایی ماشین با استدلال معنایی برای مدیریت ایمنی در هر دو سو در ساخت -2021 Computer vision has been utilized to extract safety-related information from images with the advancement of
video monitoring systems and deep learning algorithms. However, construction safety management is a
knowledge-intensive task; for instance, safety managers rely on safety regulations and their prior knowledge
during a jobsite safety inspection. This paper presents a conceptual framework that combines computer vision
and ontology techniques to facilitate the management of safety by semantically reasoning hazards and corre-
sponding mitigations. Specifically, computer vision is used to detect visual information from on-site photos while
the safety regulatory knowledge is formally represented by ontology and semantic web rule language (SWRL)
rules. Hazards and corresponding mitigations can be inferred by comparing extracted visual information from
construction images with pre-defined SWRL rules. Finally, the example of falls from height is selected to validate
the theoretical and technical feasibility of the developed conceptual framework. Results show that the proposed
framework operates similar to the thinking model of safety managers and can facilitate on-site hazard identi-
fication and prevention by semantically reasoning hazards from images and listing corresponding mitigations.
1. Introduction keywords: بینایی ماشین | هستی شناسی | استدلال معنایی | شناسایی ریسک | مدیریت ایمنی ساخت | Computer vision | Ontology | Semantic reasoning | Hazard identification | Construction safety management |
مقاله انگلیسی |
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Feasibility and efficacy of a pilot family model of diabetes self-management intervention in the Republic of the Marshall Islands
امکان سنجی و کارایی یک مدل خانواده آزمایشی مداخله خودمدیریتی دیابت در جمهوری جزایر مارشال-2021 Background: The Republic of the Marshall Islands (RMI) faces numerous health disparities, including one of the
highest prevalence of type 2 diabetes mellitus (T2DM) in the world. Diabetes self-management education and
support (DSMES) has shown efficacy in improving glycemic control and through increases in knowledge and selfmanagement activities; however, there is limited research on DSMES in the RMI. This study evaluated the
feasibility and efficacy of a culturally adapted family model of DSMES (F-DSMES) in the RMI. The F-DSME
included 8 h of group educational classes delivered in churches by a community health worker.
Methods: This pilot study assessed retention and dosage rates (e.g., class attendance) among the participants with T2DM (n = 41). Efficacy was evaluated by examining pre- and post-intervention differences in HbA1c, knowledge, family support, and self-management activities among those who completed the post-intervention data collection (n = 23). Results: The results indicate completion of post-intervention data collection and attendance were associated; 70% of participants who completed the post-intervention data collection received at least 6 h of intervention compared to 3 h for those who did not. Although the reduction in HbA1c was not statistically significant, participants demonstrated statically significant increases in knowledge, family support, and an increase in selfmanagement including in checking of blood glucose and feet. Conclusions: This study provides important information to help address T2DM disparities in the RMI, including the feasibility and efficacy of F-DSMES. Additional research will help in understanding how to translate improvements in knowledge, family support, and self-management activities into improvements in HbA1c. This may include addressing social ecological factors that affect glycemic control. keywords: Type 2 diabetes mellitus | Diabetes self-management education | HbA1c | Pre- and post-intervention | Marshallese |
مقاله انگلیسی |
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Vision-based hand signal recognition in construction: A feasibility study
تشخیص سیگنال دست مبتنی بر چشم انداز در ساخت و ساز: یک مطالعه امکان سنجی-2021 In construction fields, it is common for workers to rely on hand signals to communicate and express thoughts due to their simple but effective nature. However, the meaning of these hand signals was not always captured precisely. As a result, construction errors and even accidents were produced. This paper presented a feasibility study on investigating whether the hand signals could be captured and interpreted automatically with computer vision technologies. It starts with the literature review of existing hand gesture recognition methods for sign language understanding, human-computer interaction, etc. It is then followed by creating a dataset containing 11 classes of hand signals in construction. The performance of two state-of-the-art 3D convolutional neural networks is measured and compared. The results indicated that a high classification accuracy (93.3%) and a short inference time (0.17 s/gesture) could be achieved, illustrating the feasibility of using computer vision to automate hand signal recognition in construction. Keywords: Hand signal recognition | Dataset creation | Performance comparison | Feasibility study |
مقاله انگلیسی |
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A feasibility research on the application of machine vision technology in appearance quality inspection of Xuesaitong dropping pills
یک امکان سنجی در مورد استفاده از فناوری بینایی ماشین در بازرسی کیفیت ظاهر قرص های رهاسازی Xuesaitong-2021 Defect detection is a critical issue for the quality control of dropping pills, which is a special dosage form of traditional Chinese Medicine. Machine vision is a non-destructing testing technology and cost-effective with high accuracy that can be used to predict the detects of both interior and exterior of the sample by employing the camera. In this research, a machine vision system for inspecting quality of the Xuesaitong dropping pills (XDPs) that include non-spherical, abnormal sizes and colors was developed to evaluate the appearance quality of XDPs rapidly and accurately. Firstly, 270 images of XDPs containing qualified and three different types of defects were collected. Subsequently, the processing of the XDPs images were carried out. Finally, Three defecting categories classification models were developed and compared based on contour and color features. The experimental results showed that the Random Forest outperformed all the explored models and the classification accuracy for non-spherical, abnormal sizes and colors reached 98.52%, 100.00% and 100.00%, respectively. In summary, the method established in this research is scientific, reliable, fast and accurate, which has great application potential and can provide technical support for the automatic defect detection of dropping pills.© 2021 Elsevier B.V. All rights reserved. Keywords: Machine vision | Xuesaitong dropping pills | Defect detection | Classification model | Random forest |
مقاله انگلیسی |
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A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective
یک سایه دیجیتال مبتنی بر دانش برای صنعت ماشینکاری در یک چشم انداز دیجیتال دوتایی-2021 This paper addresses the problems of data management and analytics for decision-aid by proposing a new vision
of Digital Shadow (DS) which would be considered as the core component of a future Digital Twin. Knowledge
generated by experts and artificial intelligence, is transformed into formal business rules and integrated into the
DS to enable the characterization of the real behavior of the physical system throughout its operation stage. This
behavior model is continuously enriched by direct or derived learning, in order to improve the digital twin. The
proposed DS relies on data analytics (based on unsupervised learning) and on a knowledge inference engine. It
enables the incidents to be detected and it is also able to decipher its operational context. An example of this
application in the aeronautic machining industry is provided to stress both the feasibility of the proposition and
its potential impact on shop floor performance. keywords: سایه دیجیتال | دوقلو | داده ها و مدیریت دانش | ماشینکاری | Digital shadow | Digital twin | Data and knowledge management | Machining |
مقاله انگلیسی |
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A:L:L: Y:O:U: N:E:E:D: I:S: L:O:V:E: Manual on health self-management and patient-reported outcomes among low-income young adult Mexicans on chronic dialysis: Feasibility study
همه:شما:نیاز داشتن:است:عشق:دستیابی به سلامت خود مدیریت و نتایج گزارش شده بیمار در میان افراد کم درآمد جوانان مکزیکی های مزمن در دیالیز مزمن: مطالعه امکان سنجی-2021 Purpose: We evaluated disease knowledge/self-management skills among low-income Mexican young adults
maintained on dialysis and to test the effectiveness of the A.L.L. Y.O.U. N.E.E.D. I.S. L.O.V.E (AYNIL) Manual – Spanish Version on patient-reported outcomes. This is a low literacy teaching tool designed with patients and educators input.
Design and methods: A quasi-experimental study was conducted in 17 chronic dialysis patients at Mexico Citys
Hospital General de México, Dr. Eduardo Liceaga. Ages 18–30-year-old completed disease knowledge/selfmanagement and quality of life measures before the intervention and 6 weeks later.
Results: Significant increases were observed on disease knowledge/self-management scores in the STARx questionnaire from 47 (IQ: 40,51) to 50 (IQ: 48,54) p = 0.04. The UNC-TRxANSITION Index increased significantly from 4.8 (IQ: 3.9,5.7) to 7.7 (IQ: 7.5,8.2) p ≤0.001. Significant increases in scores were detected in the “Burden of kidney disease” (p = 0.008), “Effects of kidney disease” “ (p = 0.03) and “ Dialysis staff encouragement” (p = 0.027) based on the KDQoL survey. Conclusions: In this vulnerable population, the Spanish version of the A.L.L. Y.O.U. N.E.E.D. I.S. L.O.V.E. - AYNIL Manual improved CKD/ESRD disease knowledge/self-management skills and HRQoL. This study highlighted the need for low-literacy educational tools to improve patient-reported outcomes. Practice implications: Young adults with CKD/ESRD can benefit from patient-centered educational interventions to enhance their autonomy and the development of self-management behaviors that improve patientreported outcomes and potential complications of the disease. Special attention is needed in low-income patients with low rates of adherence to treatments and poor self-management skills. keywords: اقدامات گزارش شده بیمار گزارش شده است | خود مدیریت | ابزارهای کم سواد آموزی | آموزش بیمار | کیفیت زندگی | خود مراقبتی | Patient-reported outcome measures | Self-management | Low-literacy tools | Patient education | Quality of life | Self-care |
مقاله انگلیسی |
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Economic feasibility valuing of deep mineral resources based on risk analysis: Songtao manganese ore - China case study
ارزیابی امکان سنجی اقتصادی منابع معدنی عمیق بر اساس ریسک تجزیه و تحلیل: سنگ معدن منگنز Songtao - مطالعه موردی چین-2020 The exploitation of deep mineral resources is an inevitable choice under economic development and resource
shortage. Assessing the economic feasibility of deep mineral resource exploit projects is a prerequisite for
resource industry development. Mining industry have some problems influence its economic feasibility,
including long mining period, high infrastructure investment and lack flexibility, and have risks of geology
instability and economic reserve degrade. On the other hand, with the increase of the buried depth of mineral
resources, some problems have intensified the uncertainty of the profit of deep resource utilization project, such
as high stress, high lithology, high temperature environment, and increase of upgrading cost. Net Present Value
(NPV) and Internal Rate of Return (IRR) are traditional economic evaluation means which difficult to identify
and assess risks precisely. Decoupled Net Present Value (DNPV) provides an efficiency tool to separate the time
value and risk cost which is helpful to finds the real value of projects. A manganese mining project which is
located Guizhou province, China is analyzed, paper choices several mainly risks of influence expected revenue to
analysis project feasibility based on the DNPV technology, which includes the thickness of ore body, ore grade,
market price, operation cost and nature disaster. The cost of potential environmental risk (carbon emission cost)
also is analyzed. Paper constructs a risk management framework by risk identify, assess and classification, and
analyzes the corresponding measures to reduce risk costs. The mainly risk cost of study case from market price
shock and unexpected ore grade decline, which accounting for 80% of the total risk cost. In the process of deep
mineral resources exploit, effective cost control measures can reduce the risk cost to a certain extent, including
improving productivity, reducing unit cost of ore, improving mine sustainability and exploration accuracy. Green
mineral construction is a feasible direction of deep resource utilization. For improve the accuracy of economic
feasibility evaluation of deep mineral resources utilization, further improvement is needed in the selection and
construction of different risk assessment model. Keywords: Deep mining | Risk value assess | DNPV | Risk management | Songtao manganese |
مقاله انگلیسی |
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Experimental and feasibility study of spent coffee grounds upscaling via pyrolysis towards proposing an eco-social innovation circular economy solution
مطالعه تجربی و امکان سنجی قهوه مصرفی که از طریق تجزیه در اثر تجزیه در اثر تجزیه در اثر تجزیه در اثر تجزیه در اثر تجزیه در اثر تجزیه در اثر استفاده از تجزیه در اثر تجزیه و تحلیل مواد شیمیایی ، به منظور ارائه یک راه حل اقتصاد دایره ای نوآوری اقتصادی - اجتماعی-2020 There is a need for eco-social business models in the food waste sector that are more cascading and circular- based, while having economic, environmental and social benefits. The aim of this study is to bring insights and data of spent coffee grounds large-scale slow pyrolysis, to seize new opportunities for eco-innovative solutions in the circular economy, by identifying upcycling opportunities for resource recovery of this waste. First, an experimental study was conducted, and a set of pyrolysis experiments were carried out at a temperature range from 450 to 750 °C, with a heating rate of 50°/s, under helium atmosphere, to explore the products yields and the best process conditions. Second, an economic study was conducted for a standalone pyrolysis plant fueled with the spent coffee grounds streams from coffee shops of a city with 150,000 inhabitants, in central Greece, aiming at the cost and the profitability of the endeavor estimation. The calculations were based on the features of a slow pyrolysis rotary kiln technology designed at Aristotle University, and co-developed with an Irish company, under the funding of an EU LIFE+ project. For an estimated capacity of 2566 t/yr of SCG, the revenue of the endeavor was calculated at 47€/t of SCG. The economic indicators ROI and POT (ROI = 0.24, POT = 2.6), are very Abbreviations: CE, circular economy; FL, food loss; FW, food waste; HHV, higher heating value; LHV, lower heating value; POT, payout time; ROI, return on investment; SCG, spent coffee ground; GC, gas chromatograph.⁎ Corresponding author. E-mail address: azampani@auth.gr (A. Zabaniotou).https://doi.org/10.1016/j.scitotenv.2020.137316 0048-9697/© 2020 Elsevier B.V. All rights reserved. positive, suggesting pyrolysis of SCG as an efficient circular economy management solution, providing an eco- social innovation business in the coffee shop industry, engaging also consumers in the circular economy.© 2020 Elsevier B.V. All rights reserved. Keywords: Circular economy | Food wastes | Spent coffee grounds (SCG) | Pyrolysis: Economic study | Eco-social innovation |
مقاله انگلیسی |
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Feasibility of EVolutionary OPeration (EVOP) as a concept for herd-specific management in commercial dairy herds
امکان سنجی عملیات تکاملی (EVOP) به عنوان یک مفهوم برای مدیریت خاص گله در گله های لبنی تجاری-2020 Dairy farming is a complex production system involving biological, technological and human inputs. Therefore,
‘general knowledge of cause and effect’ often seems inadequate to identify and implement optimal management
procedures. To solve herd-specific problems, this paper explores the potential of planned experiments for internal
use at the farm level to take advantage of local causal relationships. The shift towards larger dairy herds
with access to automatic data recordings of a large number of relevant inputs and performance indicators
supports the development of management tools that are able to estimate the effect of changes made in daily
management on individual farms. The concept of EVolutionary OPeration (EVOP) implies making small systematic
changes in production factors or procedures while running the production and continuously evaluating
the results. The aim of this study was to develop and evaluate the feasibility of implementing EVOP in commercial
dairy herds as an integral part of herd management. The concept of EVOP-Dairy is based on five
principles: (1) farmer-driven identification of areas for improvement; (2) herd-specific goals for the interventions
to be evaluated in EVOP trials; (3) a short EVOP trial period; (4) simple, but statistically sound, EVOP designs
including data access and (5) regular estimation of intervention effects and frequent reporting to the farmer. The
project involved three activities: first, visiting a number of dairy farms with the aim of identifying areas for
management improvements and to define potential EVOP interventions and relevant designs of EVOP trials;
second, conducting a series of EVOP trials to develop data registration, statistical models, analysis and reporting;
third, interviewing the farmers to obtain their opinion of the conceptual idea and the process. These activities
were documented for the twelve project farms, and five different EVOP trials are described in detail to illustrate
the concept. In conclusion, the farmers found the concept a useful management improvement tool, although the
EVOP trials created additional work. The EVOP-Dairy statistical models need to include dynamic multilevel data
and control for confounding factors when estimating intervention effects, as design with randomization was not
feasible in the majority of the identified EVOP trials. Therefore, future development for the EVOP-Dairy should
focus on (i) easy to implement and execute interventions, (ii) guidelines to interpret intervention effect when
practical conditions hinder fully randomized and well replicated interventions, and (iii) automation of the data
analysis and reporting part of the concept. Keywords: Management | Dairy herd | EVolutionary OPeration (EVOP) | Dairy cow |
مقاله انگلیسی |