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ردیف | عنوان | نوع |
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1 |
Evaluation of corporate requirements for smart manufacturing systems using predictive analytics
ارزیابی الزامات شرکت برای سیستمهای تولید هوشمند با استفاده از تجزیه و تحلیل پیشبینیکننده-2022 Smart manufacturing systems (SMS) are one of the most important applications in the Industry
4.0 era, offering numerous advantages over traditional production systems and rapidly being
used as a performance-enhancing strategy of manufacturing enterprises. A few of the technologies that must be connected to construct an SMS are the Industrial Internet of Things (IIoT),
Big Data, Robotics, Blockchain, 5G Communication, Artificial Intelligence (AI), and many more.
SMS is an innovative and popular manufacturing setup that produces increasingly intelligent
production systems; yet, designers must adapt to business tastes and requirements. This study
employs an analytical and descriptive research technique to identify and assess functional and
non-functional, technological, economic, social, and performance evaluation components that
are essential to SMS evaluation. A predictive analytics framework, which is a key component
of many decision support systems, is used to assess corporate needs as well as proposed and
prioritize SMS services.
keywords: صنعت 4.0 | تجزیه و تحلیل پیش بینی کننده | سیستم های تولید هوشمند | اینترنت اشیاء صنعتی | سیستم پشتیبانی تصمیم | Industry4.0 | Predictive analytics | Smart manufacturing systems | Industrial Internet of Things | Decision support system |
مقاله انگلیسی |
2 |
An easy-to-explain decision support framework for forensic analysis of dynamic signatures
یک چارچوب پشتیبانی تصمیم آسان برای تجزیه و تحلیل پزشکی قانونی امضاهای پویا-2021 Forensic handwriting examination is often criticized for its lack of objective standards and rigorous scientific validation. On the other hand, cutting-edge techniques for biometric handwriting and signature verification are often perceived as perfect black boxes and are not used by forensic handwriting examiners in their work environment. This paper presents an easy-to-explain yet effective framework to support semi-automatic signature verification in forensic settings. The proposed approach is based on measuring similarities between signatures by applying Dynamic Time Warping on easy-to-derive dynamic features. The goal is to provide forensic handwriting examiners with a decision support tool for making reproducible and less questionable inferences, while being both intuitive and easy to explain. The method is tested on a newly proposed dataset that also takes into account the so-called disguised sig- natures which are of extreme importance in this scenario.© 2021 Elsevier Ltd. All rights reserved. Keywords: Dynamic signatures | Forensic handwriting examination | Behavioral biometrics | Decision support system | Disguised signatures |
مقاله انگلیسی |
3 |
The value of forest ecosystem services: A meta-analysis at the European scale and application to national ecosystem accounting
ارزش خدمات اکوسیستم جنگل: یک متاآنالیز در مقیاس اروپایی و کاربرد آن به حسابداری اکوسیستم ملی-2021 A great share of ecosystem services (ES) at the global scale is provided by forest biomes, and acknowledging the
value of forest ES is critically important towards sustainable decision making. The literature inventory of forest
valuation studies is extensive and thus a significant mass of knowledge is already available concerning the value
of forest ES. To this end, meta-analysis is a prominent benefit transfer approach that has been employed in the
past to provide value transfers of forest ES taking advantage of contemporary knowledge. For the purposes of
conducting a meta-analysis, we collected 158 primary studies, originated in Europe and dated from 2000 to
2017, of which 30 provided relevant information for a statistical meta-analysis, yielding 71 value observations.
The results reveal that GDP per capita and the type of ecosystem service are significant determinants in
explaining the variation in forest value. We also apply the meta-analysis model results so as to estimate the ES
provided by forests in the Czech Republic. We find that the total value of forest is approximately 2842 US
$ ha(cid:0) 1 year(cid:0) 1, with regulation and maintenance ES being the most valuable services. We finally attempt to show
the prospects of using this method for accounting purposes and illustrate the supply and use forest accounting
tables based on the meta-analysis outcomes. Meta-analysis can potentially form a promising decision support tool
for start-up accounts considered as a second best valuation approach. Nonetheless, the method still remains
questionable due to the great variation in how primary valuation studies are reported and the lack of guidelines
with reference to its application in ecosystem accounting as such. keywords: انتقال سود | جنگل | متا رگرسیون | عرضه و استفاده از جداول | Benefit transfer | Forest | Meta-regression | Supply and use tables |
مقاله انگلیسی |
4 |
Capturing causality and bias in human action recognition
ثبت علیت و سوگیری در تشخیص عمل انسان-2021 Human action recognition using various sensors is a mandatory component of autonomous vehicles, humanoid robots, and ambient living environments. A particular interest is the detection and recognition of falls. In this paper, we propose the use of temporal convolution networks guided by knowledge distilla- tion for detecting falls and recognizing types of falls using accelerometer data. Tri-axial accelerometers attached to the body measure the acceleration of the body joints when an action occurs. These data are used for pattern analysis and body action recognition. We demonstrate the existence of biases caused by soft biometrics when recognizing human body actions. We introduce a causal network to capture the influences of biases on system performance and illustrate how knowledge distillation can be applied to mitigate the bias effect. Crown Copyright © 2021 Published by Elsevier B.V. All rights reserved. Keywords: Machine learning | Decision support | Human action recognition | Machine reasoning | Belief networks |
مقاله انگلیسی |
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Optimal pricing and replenishment policy for perishable food supply chain under inflation
سیاست قیمت گذاری و بازپرداخت بهینه زنجیره تامین مواد غذایی فاسدشدنی تحت تورم-2021 The COVID-19 outbreak-caused blockade and disruption of the supply chain have dramatically increased the prices of perishable food and other products that rely heavily on the timeliness of supply chains. In the case of inflation, this study aims to make some adjustment to the pricing and replenishment strategy of perishable food and compare it with the scenario without considering inflation to determine the impact of the inflation rate, quality deterioration, time value of money, and characteristics of cash flow of perishable food sales on the supply chain decision-making. We used the discounted cash flow (DCF) model to measure retailers’ revenue, which established that the optimal pricing and replenishing strategy could maximize the retailers’ profit. Besides, the findings were compared with the traditional profit model. Moreover, numerical experiments and sensitivity analysis were provided for decision support to retailers. Overall, this study validates that inflation significantly affects the pricing and replenishment strategy, and the DCF model is more suitable to evaluate the profits of perishable food. Keywords: Inflation | Optimal pricing | Replenishment strategy | Supply chain | Time value of money | Perishable food |
مقاله انگلیسی |
6 |
Transformation of semantic knowledge into simulation-based decision support
تحول دانش معنایی به پشتیبانی تصمیم گیری مبتنی بر شبیه سازی-2021 Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, indepth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model.
This knowledge-intensity leads to long development times of respective projects, which contradicts the need
for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to
foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation
model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides
a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully
parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing
guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into
instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated
transformation of this conceptual model into an executable one. This novel modeling approach makes model
development more efficient by reducing its complexity. It is validated in a use case implementation from
semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate
the impacts of the COVID-19 pandemic on a global supply chain network.
keywords: تحول دانش | پشتیبانی تصمیم | هستی شناسی | مدل سازی ترکیبی | شبیه سازی همه گیر | شبیه سازی زنجیره تامین | Knowledge Transformation | Decision Support | Ontologies | Hybrid modeling | Pandemic Simulation | Supply chain simulation |
مقاله انگلیسی |
7 |
Using multi-criteria analysis the assess impacts of change in ecosystem-based fisheries management: The case of the Icelandic cod
با استفاده از تجزیه و تحلیل چند معیار ارزیابی اثرات تغییر در مدیریت شیلات مبتنی بر اکوسیستم: مورد COD ایسلندی-2020 This paper presents the outcome of one of the case-studies of the EU-funded FP7 research project MareFrame.
The project sought to remove the barriers preventing more widespread use of the ecosystem-based approach to
fisheries management by developing integrated ecosystem-based assessment methods and a decision support
framework for the management of marine resources. The findings are intended to support the implementation of
the Common Fisheries Policy (CFP) and Marine Strategy Framework Directive (MSFD). The case study focused on the
Icelandic cod fishery which is by far the most important fishery in Iceland, accounting for 43% of the country’s
total export values of seafood in 2016. Sound biological and economic management of the fishery is therefore
essential for both the nation as a whole as well as individual fisheries-dependent communities. The analysis is
done in two main steps. We first use the statistical multi-species model Gadget, developed by the Icelandic
Marine and Freshwater Research Institute, to estimate the development of catches by fleet segments (trawl, net
and longline) and stock size. Comparisons are made with two scenarios: a) adhering to the present harvest
control rule or b) changing the effort to a level corresponding to fishing mortality associated with maximum
sustainable yield (FMSY). In the second step, the two outcomes and their socio-economic effects are examined
using a three-stage analytic hierarchy process. The case study has been developed in close cooperation with
Icelandic stakeholders, and in this paper we describe how the co-creation approach was employed in an
ecosystem-based fisheries management framework. Keywords: Ecosystem-based fisheries management | Co-creation | Gadget | Multi-criteria analysis | Analytic hierarchy process | Cod |
مقاله انگلیسی |
8 |
A decision support tool for cement industry to select energy efficiency measures
یک ابزار پشتیبانی تصمیم گیری برای صنعت سیمان برای انتخاب اقدامات بهره وری انرژی-2020 Cement industry is one of the most energy intensive industrial sub-sectors. It accounts for almost 15% of the total
energy consumed by manufacturing. Numerous energy efficiency initiatives and measures have been introduced
and employed in this industry. To implement the most appropriate solutions for a certain cement plant, both
technological and non-technological constraints need to be considered. To date, researchers have focused on
outcomes such as energy savings, investment and emission reduction and therefore, both qualitative criteria and
current circumstances of the plant have been largely overlooked. In this study, an integrated 3-phase model is
presented to address these shortcomings and assist the plant managers to select and invest in the most suitable
projects. The proposed tool, which is founded on a multi-criteria decision model, will assist the cement managers
in achieving their energy saving targets. The tool is tested for 3 cases showing its applicability with real data
resulting in the ranked list of opportunities for each of the plants. Keywords: Cement industry | Energy efficiency | Decision support tool | Energy management |
مقاله انگلیسی |
9 |
Telemedicine DSS-AI Multi Level Platform for Monoclonal Gammopathy Assistance
پلت فرم چند سطحه از راه دور پزشکی DSS-AI برای کمک به گاموپاتی مونوکلونال-2020 The proposed work describes preliminary results
of a research project based on the realization of a Decision
Support System -DSS- platform embedding medical and
artificial intelligence -AI- algorithms. Specifically the
telemedicine platform is suitable for the optimization of
assistance processes of patients affected by Monoclonal
Gammopaty. The results are related to the whole design of the
platform implementing a DSS based on a multi-level decision
making process. Starting from the main architecture
specifications, is formulated a flowchart based on different
alerting levels of patient risk including artificial intelligence -
AI- decision supporting facilities. Finally, the perspectives of
the performed research are discussed. Keywords: Telemedicine | Digital Assistance | Decision Support System | Artificial Intelligence | Monoclonal Gammopathy |
مقاله انگلیسی |
10 |
The Importance of the Social License to Operate at the Investment and Operations Stage of Coal Mining Projects: Application using a Decision Support System
اهمیت پروانه اجتماعی برای فعالیت در مرحله سرمایه گذاری و عملیات پروژه های استخراج زغال سنگ: درخواست با استفاده از سیستم پشتیبانی تصمیم-2020 The Social License to Operate (SLO) and the Value Chain business model are basic elements that need to be considered both at the planning and operation stages of mining operations and in particular in coal mining projects. If a coal mining enterprise loses its SLO, it may face risks in operations, which may lead to value chain risks. One of the causes of enterprise failure as related to coal mining operations is the inability to reliably assess/ manage risk holistically and the inability to understand that lack of SLO is a critical risk. Although financial risks are typically assessed for mining projects, lack of SLO risk should also be taken into account starting as early as the bankable feasibility study. Furthermore, as it is difficult to establish a proactive decision-making policy for SLO risk in coal mining operations, the Operational Risk Management (ORM) methodology is probably a good tool to apply towards that goal. For this reason, a Mining Operational Risk Management Model (MORMM) was developed to incorporate risk probabilities and risk severities evaluated by experts. The final risk assessment is coded using Risk Assessment Codes (RACs). A hypothetical scenario was developed utilizing the MORMM model in order to illustrate how risks can be managed during the SLO granting process. This scenario describes a hypothetical coal mining project evaluated by virtual risk evaluators under specific hazard categories. Risk evaluation involves the assessment of risk probability and risk severity. Through this scenario this paper presents ways: (i) to establish a baseline ORM process that will be applicable to any coal mining operation environment, and (ii) to provide a theoretical example to demonstrate how the method can be applied to coal mining operations. The resulting RACs can provide critical information to decision makers regarding the rejection, acceptance or re-engineering of the mining business plan. Keywords: Social License to Operate | Operational risk management | coal mining | Value Chain |
مقاله انگلیسی |