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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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Management Transformation with a Single Digital Platform as Exemplified by Accounting
تحول مدیریت با یک پلتفرم دیجیتالی واحد به عنوان نمونه با حسابداری-2021 The paper considers the solution to the problem of accounting method transformation under
the influence of the accelerating economy digitalization that requires transition to new methods of
working with information: in addition to reflecting the history of business activities, accounting
statements should allow making decisions for the future at any time and at any production process stage;
that is, it should be re-oriented from the control function to the informative one. This, in turn, requires
integration based on digital standards of reporting information with information reflecting other aspects
of the business and the external environment through developing new indicators, new methods of
collecting and processing data. We have shown that a solution to this problem could be creating a single
digital economy management platform consisting of two specialized sub-platforms: an aggregator subplatform for collecting and accumulating primary data and an application sub-platform for production
management tasks. In this case, a widespread introduction of a single digital platform in any production
process allows to migrate to a new type of manufacturing enterprises: from the quality control phase after
the production phase towards the principle of current control over all production operation, which should
also affect the entire taxation system. This system will become more efficient by increasing tax
collection, reducing the cost of maintaining the financial and accounting service and actively including it
in the production management system. In addition, such a digital platform will release a significant
number of IT specialists, who are sorely lacking in the country, especially in agriculture, from the
financial and accounting service with their reorientation to the introduction of new digital technologies in
the form of mathematical models, artificial intelligence, big data, neural networks, which will give an
additional impetus to the accelerated digitalization of the economy.
Keywords: accounting | digital standards | information resources | digital platform | management. |
مقاله انگلیسی |
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The quiet revolution in machine vision - a state-of-the-art survey paper, including historical review, perspectives, and future directions
انقلاب آرام در بینایی ماشین-مقاله ای پیشرفته مروری، شامل مرور تاریخی ، چشم اندازها و جهت های آینده-2021 Over the past few years, what might not unreasonably be described as a true revolution has taken place in the field of machine vision, radically altering the way many things had previously been done and offering new and exciting opportunities for those able to quickly embrace and master the new techniques. Rapid developments in machine learning, largely enabled by faster GPU-equipped computing hardware, has facilitated an explosion of machine vision applications into hitherto extremely challenging or, in many cases, previously impossible to automate industrial tasks. Together with developments towards an internet of things and the availability of big data, these form key components of what many consider to be the fourth industrial revolution. This transformation has dramatically improved the efficacy of some existing machine vision activities, such as in manufacturing (e.g. inspection for quality control and quality assurance), security (e.g. facial biometrics) and in medicine (e.g. detecting cancers), while in other cases has opened up completely new areas of use, such as in agriculture and construction (as well as in the existing domains of manufacturing and medicine). Here we will explore the history and nature of this change, what underlies it, what enables it, and the impact it has had - the latter by reviewing several recent indicative applications described in the research literature. We will also consider the continuing role that traditional or classical machine vision might still play. Finally, the key future challenges and developing opportunities in machine vision will also be discussed.© 2021 Elsevier B.V. All rights reserved. Keywords: Machine vision | Machine learning | Deep learning | State-of-the-art |
مقاله انگلیسی |
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Networks of interpretation: An ethnography of the quest for IFRS consistency in a global accounting firm
شبکه های تفسیر: قوم نگاری تلاش برای سازگاری IFRS در یک شرکت حسابداری جهانی-2021 Because of their complexity and principle-based nature, the creation of International Financial Reporting
Standards (IFRS) engendered significant uncertainty that modified the order of things within large accounting firms. This motivated them to establish Professional Practice Function (PPF) units to try to
ensure a credible degree of consistency in applying IFRS across a wide range of financial reports at the
international level. We study backstage dynamics surrounding a PPF national unit in one of the Big Four
firms. We focus on the rise of the PPF as an expert-based control device within the firm, and the role PPF
members play as knowledge brokers to interpret IFRS. Our investigation is carried out through ethnographic fieldwork supplemented by interviews with PPF members and field auditors. The analysis brings
forward some of the organizational dynamics surrounding PPF members efforts to establish their
credibility as intermediaries both hierarchically, between administrative partners and field auditors, and
epistemically, between the unifying logic of IFRS and auditees financial reporting specifics. Ultimately,
our analysis points to the role of the PPF as a gatekeeping or internal control device that mediates between different pools of knowledge to monitor the firms reputation risk against IFRS implementation
challenges. From a legal perspective, our ethnography documents how accounting “law” is made at the
firm level and how PPF members strive for consistency e in spite of significant epistemological and
organizational challenges. Our ethnography also shows that complex IFRS interpretation issues are not
resolved through one persons judgment; instead, the firms structure surrounding the PPF allows for the
constitution of inter-individual judgment that transcends national, sectoral, and (sometimes) organizational boundaries. Finally, we see one important contribution of our work as helping reveal the limits of
large conceptual categories such as “auditors”, which tend to downplay the dynamics of convoluted
practice relationships.
keywords: بزرگ چهار | تجربه و تخصص | اجرای IFRS | خدمات حرفه ای | حسابرسی | کنترل کیفیت | قضاوت | Big four | Expertise | IFRS implementation | Professional service firm | Audit firm | Quality control | Structure-judgment |
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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An efficient optimization framework for tracking multiple quality attributes in supply chains of perishable products
یک چارچوب بهینه سازی کارآمد برای ردیابی چندین ویژگی کیفی در زنجیره های تأمین محصولات فاسدشدنی-2021 Improved supply chain optimization strategies can play a major role in addressing global food security
and safety in years to come. In particular, tighter safety regulations, changing consumer quality requirements and more stringent market competition call upon integrated supply chain decision-making frameworks that explicitly consider product quality control. This effort requires metrics of quality that accurately reflect product physico-chemical properties, as well as consumer purchasing preferences. However,
a critical challenge linked to embedding the complex dynamics of the evolution of product quality in time
within supply chain models is the large-scale nature of the ensuing optimization problems, which are
computationally intractable even for moderate-size, single-item systems. In the present work, we introduce a computationally efficient optimal production and distribution planning framework for perishable
products having multiple quality attributes that evolve in time as a function of environmental conditions
during shipment and storage. We also propose a model reduction strategy and a decomposition framework that enhance the scalability of our approach. We perform extensive numerical simulations using
different network instances to validate our theoretical findings, as well as to demonstrate the advantages
of the proposed supply chain management scheme. Keywords: Supply chain management | Quality control | Mixed integer programming | Perishable products |
مقاله انگلیسی |
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A Machine Vision Based Automated Quality Control System for Product Dimensional Analysis
سیستم کنترل کیفیت خودکار مبتنی بر بینایی ماشین برای تجزیه و تحلیل ابعاد محصول-2021 Quality control (QC) in manufacturing processes is critical to ensuring consumers receive products with proper functionality and reliability. Faulty products can lead to additional costs for the manufacturer and damage trust in a brand. A growing trend in QC is the use of machine vision (MV) systems because of their noncontact inspection, high repeatability, and relatively low cost. This paper presents a robust MV system developed to perform comparative dimensional inspection on diversely shaped samples, including additive manufacturing products. The algorithm used performs dimensional inspection on a base product considered to have acceptable dimensions. The perimeter, area, rectangularity, and circularity of the base product are determined using blob analysis on a calibrated camera. These parameters are then used as the standard with which to judge additional products. Each product following is similarly inspected and compared to the base product parameters. A likeness score is calculated for each product, which provides a single value tracking all parameter differences. Finally, the likeness score is considered on whether it is within a threshold, and the product is considered to be acceptable or defective. The proposed MV system has achieved satisfactory results, as discussed in the results section, that would allow it to serve as a dependable and accurate QC inspection system in industrial settings.© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)Peer-review under responsibility of the scientific committee of the Complex Adaptive Systems Conference, June 2021. Keywords: Machine Vision | Quality Control | Dimensional Analysis | Digital Quality | Rectangularity | Circularity | Production | Manufacturing |
مقاله انگلیسی |
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Optimizing strategies for e-waste supply chains under four operation scenarios
بهینه سازی استراتژی های زنجیره تامین زباله الکترونیکی تحت چهار سناریو عملیاتی-2021 Online recycling has become an increasingly popular research hotspot. However, few studies have
focused on its potential service functions such as online promotion and offline recycling. In this study,
considering such service functions, four models, namely, the manufacturer recycling channel (Model
A), recycler recycling channel (Model B), online channel recycling (Model C) and manufacturer’s self built platform + recycling channel (Model D), are established, and derived the corresponding profit functions of supply chain members. Game theory was utilized to optimize service quality control strategies
and supply chain member profits within the different models. Using numerical simulation, we examined
the influence of both the upper recycling incentive limit and market demand on the optimal recycling
channel strategies and profits. When the upper limit of the recovery incentive amount k 2 ð0; 3Þ, the
actual price and service quality to consumers under the manufacturer’s self-built platform + recycling
channel (Model D) are better than other channels, and the optimal manufacturer and online platform
profits initially increased and then decreased with increases in the recycling incentive upper limit. We
also found that the optimal recycler profit increased as the upper limit of the recycling incentive
increased, and that optimal supply chain member profits increased when market size D0 2 ð0; 100Þ. Keywords: E-waste | Closed-loop supply chain | Online recycling platform | Recycling incentive upper limit | Market scale |
مقاله انگلیسی |
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Performance assessment of coupled green-grey-blue systems for Sponge City construction
ارزیابی عملکرد سیستم های سبز و خاکستری-آبی همراه برای ساخت و ساز شهر اسفنجی-2020 In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of
Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source,
grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal.
However, the current approaches for assessing the performance of Sponge City construction are confined to
green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving
water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems
on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river
system models are coupled to provide quantitative simulation evaluations of a number of indicators of landbased
and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity
to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for
Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network
area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with
large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on
the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement.
This framework can be applied to Sponge City projects to achieve the enhancement of urban water
management. Keywords: Low impact development | Sponge City | Green-grey-blue system | Performance assessment | TOPSIS |
مقاله انگلیسی |
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Impact of hygiene on bacterial contamination in extended boar semen: An eight-year retrospective study of 28 European AI centers
تأثیر بهداشت بر آلودگی باکتریایی در منی گسترده گراز: مطالعه هشت ساله گذشته نگر از 28 مرکز هوش مصنوعی اروپا-2020 Antibiotic agents such as gentamicin represent essential components of semen extenders in order to
reduce bacterial contamination. But antibiotic resistance increases and AI centers start utilizing antibiotic
agents which are more potent. Therefore, a shift to preventing bacterial contamination has to take place.
In this study, we could demonstrate that hygiene is a tool capable of reducing bacterial load. In order to
analyze 1434 extended semen samples and nine specially established hygienic critical control points
(HCCPs, n ¼ 828), 92 quality control audits have been carried out in a time period from 2012 until 2019 in
28 European AI centers. The results show the process of introducing a basic hygienic standard in audit 1
(2012/2013) and 2 (2014/2015) and the resulting achievements by means of improved hygienic conditions
in audit 3 (2016/2017) and 4 (2018/2019). Within the scope of audit 1, 19% of the semen samples
were contaminated with bacteria (cutoff 100 colony-forming units/mL). Audit 2 showed a bacterial load
of 13.6% whereas during audit 3 and 4 very low bacterial contamination rates were recorded (4.5 and
5.5%, respectively). In the same manner, analysis of hygiene at different CCPs during semen production
showed a decrease in all average HCCP-scores (score 1e6) comparing audit 4 to 1. By regression analysis
we could show a significant audit-dependent association of the bacterial contamination in semen
samples and hygiene of HCCPs. Furthermore, analysis of the odds ratio (OR) reveals that the bacterial
contamination of certain HCCPs poses an increased risk of receiving bacterially contaminated semen
samples (filling machine: OR ¼ 3.02, P ¼ 0.06; extender: OR ¼ 8.97, P < 0.001; inner face of dilution tank
lids: OR ¼ 3.14, P ¼ 0.09). Around 60% of the variance of the bacterial contamination in semen samples
could be explained by hygienic conditions at different control points and their interaction with audit
period and AI center. Antimicrobial agents are essential to protect human and animal health but
excessive or inappropriate use can lead to the emergence of resistant bacteria. As shown in our study,
hygiene management can significantly reduce bacterial contamination and is therefore capable of preventing
antibiotic resistance. Keywords: Antimicrobial resistance | Bacteria | Bacterial contamination | Boar semen | Boar semen preservation | Hygiene |
مقاله انگلیسی |