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نتیجه جستجو - Decision Support

تعداد مقالات یافته شده: 184
ردیف عنوان نوع
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
5 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
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