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1 |
Evaluation on risks of sustainable supply chain based on optimized BP neural networks in fresh grape industry
ارزیابی خطرات زنجیره تأمین پایدار بر اساس شبکه های عصبی بهینه شده BP در صنعت انگور تازه-2021 In order to improve the risk evaluation and management in fresh grape supply chain and enhance the sustainable level of the supply chain, this study applied neural network to evaluate the risk of fresh grape supply chain from the perspective of sustainable development. Firstly, the possible risk factors in the supply chain were identified and the risk evaluation index system were proposed; then risk evaluation models based on single BP and optimized BP (GABP and PSO-BP) neural network were established; and then the models were trained, tested and evaluated using data set from supply chain survey. The survey and analysis results showed that the risk of fresh grape supply chain was at a low level but the risk in each link was discrepant, the biggest risk was the risks among the links in the chain (R0), and the high risk dimensions were the economic risk, social risk and cooperation risk; most risky events were located in the second quadrant (small probability & high damage risk events). The results of models training and testing indicated that the optimized model was superior to single BP neural network for risk assessment in grape sustainable supply chain, and the PSO-BP model was more accurate and suitable with less evaluation errors and a bigger R2. The results also extracted the risk factors that contributed most to the overall risk of grape sustainable supply chain. This paper enriches the method of supply chain risk assessment theoretically, and provides practical suggestions for risk prevention, stable operation and sustainability improvement of fresh grape supply chain. Keywords: Sustainable supply chain | Supply chain risk | GA-BP neural network | PSO-BP neural network | Risk evaluation |
مقاله انگلیسی |
2 |
A flexible risk assessment framework for marine plastic pollution that synthesizes waste management and ecological impact data
یک چارچوب ارزیابی ریسک انعطافپذیر برای آلودگی پلاستیکی دریایی که دادههای مدیریت زباله و اثرات زیستمحیطی را ترکیب میکند-2021 The vast quantity of plastic in the world’s ocean poses an urgent problem for marine ecosystems and coastal
communities. While considerable research has aimed to understand how plastics impact marine life, there remains a gap in connecting this knowledge with waste management practices. Because these practices often
determine the end fate of plastic items, bridging this gap is critical to reducing the flow of harmful plastics into
the ocean. The framework proposed here identifies policy actions to reduce consumption of high-impact plastics
using a compound risk score that encompasses both an item’s likelihood of entering the ocean and its negative
ecological impact. We illustrate the framework’s application using a case study of single-use plastic (SUP)
consumption at a large Canadian university. We quantified SUPs purchased over one year at the University of
British Columbia and collected data from its associated waste management system to identify factors that influence an item’s end fate. We used these data to estimate the relative risk of items exiting the recycling stream,
then combined this with published data on the items’ marine impacts to calculate their compound risk scores.
The results identify high-risk plastic items to prioritize in waste reduction strategies and lower-risk alternatives.
The results also highlight specific policy avenues to improve the efficiency of the focal waste management
system. This framework is flexible to diverse contexts, requiring only information about plastic consumption and
waste management practices. It is thus an accessible and useful tool to support local transitions toward a reduced
marine footprint.
keywords: Risk assessment Waste management | Plastic pollution | Marine debris |
مقاله انگلیسی |
3 |
Accounting for Safety Barriers Degradation in the Risk Assessment of Oil and Gas Systems by Multistate Bayesian Networks
حسابداری برای تخریب موانع ایمنی در ارزیابی ریسک سیستم های نفت و گاز توسط شبکه های چندگانه بیزی-2021 In this paper, a multistate Bayesian Network (BN) is proposed to model and evaluate the functional performance
of safety barriers in Oil and Gas plants. The nodes of the BN represent the safety barriers Health States (HSs) and
the corresponding conditional Failure Probability (FP) values are assigned. HSs are assessed on the basis of
specific Key Performance Indicators (KPIs) related to the barrier characteristics (i.e., technical, procedural or
organizational, continuously monitored or event-based characterized). FP values are estimated from failure
datasets (for technical barriers), evaluated by Human Reliability Analysis (HRA) (for operational and organi-
zational barriers) and assigned by expert elicitation (for barriers lacking data or information). For illustration,
the multistate BN model is developed for preventive barriers and applied to a case study related to the potential
release of flammable material in the slug catcher of a representative O&G Upstream plant which may lead to
major accident scenarios (fire, explosion, toxic dispersion). The results from the case study demonstrate that the
multistate BN model is able to account for the safety barriers HS and their associated functional performance. keywords: ارزیابی ریسک کمی | ارزیابی خطر زندگی | شبکه بیزی | مانع ایمنی | شاخص عملکرد کلیدی | حاشیه ایمنی احتمالی | Quantitative Risk Assessment | Living Risk Assessment | Bayesian Network | Safety Barrier | Key Performance Indicator | Probabilistic Safety Margins |
مقاله انگلیسی |
4 |
Backtracking and prospect on LNG supply chain safety
پیگیری و چشم انداز ایمنی زنجیره تامین LNG-2021 The safety issues of Liquefied Natural Gas (LNG) in production, storage, loading/unloading, transportation/ shipping, and re-gasification have became a major concern, since an accident in the LNG industry would be very costly. Understanding the threat of LNG not only contributes to the process safety and reliability in the research and development (R&D) system, but improves the efficiency of loss prevention, fire protection and emergency responses. As of April 2019, in order to obtain the present status and trend of LNG safety research, basing 1122 documents of the Web of Science database about safety research of LNG as a data source, Cite Space and VOS viewer were used for network knowledge map analysis. A comprehensive knowledge map of LNG safety field was obtained from several research aspects including scientific research power, research hot spots and trends, research knowledge base and frontier. According to the study results, the development of LNG safety research was divided into four stages from 1970s to 2019, China and South Korea made a lot of contributions, and the United States is the most influential. Among them, the research from 2005 to 2019 was the most representative. Current research results indicate that a combination of Formal Safety Assessment (FSA) methodology and Dynamic Procedure for Atypical Scenarios Identification (DyPASI) will fully identify risks; The PHAST and TerEx programs quickly define safety zones. Computational Fluid Dynamics (CFD) software package can provide ac- curate quantitative data for the study of LNG safety. Research on quantitative risk assessment (QRA) and LNG evaporated gas (BOG) has been a hot topic and trend in this field. The application of expansion foam in LNG accident mitigation covers most of the research content in this field, and the optimization of LNG liquefaction process has a great influence on this industry. As the international demand for LNG energy output increases, floating liquefied natural gas (FLNG) will have considerable development, and increasingly researchers attach vital importance to the safety of LNG offshore production integrated unit. Keywords: Liquefied natural gas | Supply chain | Safety | FLNG | CiteSpace | VOS viewer |
مقاله انگلیسی |
5 |
Modelling of supply chain disruption analytics using an integrated approach: An emerging economy example
مدل سازی تجزیه و تحلیل اختلال در زنجیره تامین با استفاده از یک رویکرد یکپارچه: یک مثال اقتصاد در حال ظهور-2021 The purpose of this paper is to develop a framework to identify, analyze, and to assess supply chain disruption factors and drivers. Based on an empirical analysis, four disruption factor categories including natural, human- made, system accidents, and financials with a total of sixteen disruption drivers are identified and examined in a real-world industrial setting. This research utilizes an integrated approach comprising both the Delphi method and the fuzzy analytic hierarchy process (FAHP). To test this integrated method, one of the well-known examples in industrial contexts of developing countries, the ready-made garment industry in Bangladesh is considered. To evaluate this industrial example, a sensitivity analysis is conducted to ensure the robustness and viability of the framework in practical settings. This study not only expands the literature scope of supply chain disruption risk assessment but through its application in any context or industry will reduce the impact of such disruptions and enhance the overall supply chain resilience. Consequently, these enhanced capabilities arm managers the ability to formulate relevant mitigation strategies that are robust and computationally efficient. These strategies will allow managers to take calculated decisions proactively. Finally, the results reveal that political and regulatory instability, cyclones, labor strikes, flooding, heavy rain, and factory fires are the top six disruption drivers causing disruptions to the ready-made garment industry in Bangladesh. Keywords: Supply chain management | Disruption factors and drivers | Fuzzy analytic hierarchy process | Delphi method |
مقاله انگلیسی |
6 |
Risk-averse supplier selection and order allocation in the centralized supply chains under disruption risks
انتخاب تامین کننده متنفر از ریسک و تخصیص سفارش در زنجیره های تأمین متمرکز تحت خطرات اخلال-2021 This paper proposes a mixed-integer non-linear programming (MINLP) model for the integrated supplier selec- tion and order allocation in a centralized supply chain considering the disruption risks and a risk-averse decision- maker. In order to capture a realistic scenario of considering the geographical characteristics of the suppliers, we assume that the suppliers belong to two regions: the buyer’s region (domestic suppliers) and outside of the buyer’s region (foreign suppliers). Considering this realistic feature, the supply chain might face two types of disruption risk: first, local disruption risks which might uniquely occur inside each supplier such as equipment breakdowns, and second, regional disruption risks that might occur in the region of the suppliers located in the same geographical region such as natural hazards. We formulate the problem considering a risk-neutral decision- maker as a benchmark, and then a risk-averse model is presented. In the latter case, we apply two types of risk assessment tools introduced in the finance literature to analyze the decision maker’s behavior: value-at-risk (VaR) and conditional value-at-risk (CVaR). We show that developed models are non-convex programming, and therefore, we apply the particle swarm optimization (PSO) algorithm as the solution approach. We also compare the developed PSO algorithm with the Genetic algorithm (GA) and the commercial GAMS solver to verify the efficiency of the solution method. The computational experiments indicate the impact of the decision maker’s attitude on the supplier selection and the order quantity. Keywords: Supplier selection | Disruption risks | Order allocation | Conditional value-at-risk | Meta-heuristic algorithms |
مقاله انگلیسی |
7 |
Knowledge, attitude, and practice of forensic practitioners during COVID-19 pandemic in Arab countries
دانش، نگرش و عملکرد پزشکان قانونی در طول همه گیری COVID-19 در کشورهای عربی-2021 COVID-19 pandemic burdens forensic practice worldwide. The experience of crisis management is a lesson
learned that guides future preparedness for similar casualties. Thus, the present study takes an in-depth look at
the knowledge, attitude, and practice of forensic practitioners during the COVID-19 pandemic in the Arab world.
A comprehensive questionnaire was adopted in compliance with optimum international standards for the
management of deaths during the pandemic. The survey was electronically distributed in 13 Arab countries. The
responses were received from 29 forensic practitioners from 11 countries. Total median knowledge, attitude, and
practice scores of respondents constituted 37.9%, 74%, and 36.8% of optimum scores respectively. Regarding
knowledge, better scores are related to risk assessment and routes of exposure to Coronavirus, whereas, least
scores were related to ventilation and negative pressure system. Most of the participants had a positive attitude,
85.2% were concerned about proper management of COVID-19 deaths, and 77.8% trusted the decisions of their
teams. Considering practice, better scores are related to forensic staff competence, whereas, least scores were
related to the implementation of ideal safety measures. Participants described the management process as useful
(52%), reliable (35%), high quality (21%), and cost-effective (17%), however, they expressed challenges as staff
infection, limited resources, and infrastructure issues. This survey guides readjusting of procedures and future
preparedness for similar disasters in the Arab world. This research adopted a questionnaire that could be used in
initial and periodic assessments in any medicolegal institute worldwide. Also, it could support infrastructure
projects and disaster management plans. keywords: تمرینکنندگان قانونی | دانش | نگرش | کشورهای عربی | پاندمی کووید 19 | Forensic practitioners | Knowledge | Attitude | Arab countries | COVID-19 pandemic |
مقاله انگلیسی |
8 |
Research on the policy route of China’s distributed photovoltaic power generation
تحقیق در مورد مسیر سیاست تولید انرژی فتوولتائیک و توزیع شده در چین-2020 The distributed photovoltaic power generation is an important way to make use of solar energy in
cities. China issues a series of policies to support the development of distributed photovoltaics in
law, electricity price, grid connection standard, project management, financial support and so on.
However, there are still some defects in policies and market mechanism. China creates a competitive
market with a significant number of projects of distributed photovoltaic power through the reform of
the electricity market, yet substantial drawbacks of the corresponding investment subsidies prevent
distributed photovoltaic power from rapidly developing. This paper summarizes the status quo of
China’s distributed photovoltaic power development, given its long-term plan, presents excellences and
shortcomings of the existing policy system, and looks into the supporting policies and implementation
paths for China’s distributed photovoltaic power in different stages. Innovative business models and
financial support models are conducive to the development of distributed photovoltaic power. Financial
innovation methods such as crowd funding and asset securitization should be encouraged to develop
a sound risk assessment mechanism for projects, involve insurance institutions, and establish a risk
sharing mechanism. In the context of a series of supporting policies, the distributed photovoltaic
power in China will move towards market-oriented standardization for a healthier and more stable
development. Keywords: Distributed photovoltaic power | Electricity price | Policy route | Development strategy |
مقاله انگلیسی |
9 |
AIS-Based Vessel Trajectory Reconstruction with U-Net Convolutional Networks
بازسازی مسیر کشتی مبتنی بر AIS با شبکه های کانولوشن U-Net-2020 The vessel trajectory data indicated by the
Automatic Identification System (AIS) is important and useful
in maritime data analysis, navigational safety and maritime
risk assessment. However, the raw trajectory data contains
noise, missing data and other errors which can lead to a wrong
conclusion. Therefore, it is essential to develop a vessel
trajectory reconstruction method, which is meaningful for
enhancing the applicability of vessel trajectory and improving
the navigation safety. In recent years, there have been many
studies about vessel trajectory reconstruction, but the
performance of these methods will degrade when they are
faced with curved trajectories with high loss rate. In this paper,
we propose a novel trajectory reconstruction method via U-net.
Benefiting from the architecture of U-net, this method makes
great use of historical trajectories and takes advantage of the
rich skip connections in this network which help copy low-level
features to corresponding high-level features. Consequently,
this method is robust to the trajectories with different
sampling rates, missing points, and noisy data. In addition, the
proposed method is tested and compared with cubic spline
interpolation. The results show that our method is capable of
higher accuracy than the cubic spline interpolation especially
when the trajectories are curved and have a high loss rate. Keywords: Trajectory reconstruction | U-net | Machine learning | AIS data | Traffic safety |
مقاله انگلیسی |
10 |
Qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions
ارزیابی ریسک کمی و کیفی پروژه با استفاده از یک مدل توسعه یافته PMBOK تحت شرایط غیر قطعی-2020 This study presented a qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions. Accordingly, an exploratory and applied research design was employed in this study. The research sample included 15 experienced staff working in main and related positions in Neyr Perse Company. After reviewing the literature and the Project Management Body of Knowledge (PMBOK), 32 risk factors were identified and their number reduced to 17 risks using the expert opinions via the fuzzy Delphi technique run through three stages. The results of the confirmatory factor analysis showed that all risks were confirmed by the members of the research sample. Then the identified risks were structured and ranked using fuzzy DEMATEL and fuzzy ANP techniques. The final results of the study showed that the political and economic sanctions had the highest weight followed by foreign investors’ attraction and the lack of regional infrastructure. Keywords: Project risks | Project management body of knowledge (PMBOK) | Uncertainty | Mixed qualitative and quantitative risk assessment approach | Mathematics | Probability theory | Engineering | Industrial engineering | Business |
مقاله انگلیسی |