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Investigation and assessment of blockchain technology adoption in the pharmaceutical supply chain
بررسی و ارزیابی پذیرش فناوری بلاکچین در زنجیره تأمین دارویی-2021 The global pharmaceutical industry has gone through several changes in the past decade related to the adoption of new technologies. The challenges that are faced by this industry mostly involve counterfeit drugs and operational issues. The involvement of cold chain for vaccines, medicine etc. is also impacting the secure logistics and transportation. Newly introduce blockchain technologies have capabilities to address these issues. The challenge which needs to address is the requirement of tracking the product authenticity from start production to consumption point to prevent further financial losses. The present study has proposed the investigation and assessment of blockchain for integration in the supply chain model of the pharmaceutical to securely record transactions between parties enhancing trust and transparency. The blockchain adaptation and implementation to address the supply chain challenges are discussed.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Confer- ence on Technological Advancements in Materials Science and Manufacturing. Keywords: Pharmaceutical supply chain | Blockchain technology | Decentralised system | Conceptual model | Assessment model |
مقاله انگلیسی |
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Computer vision technologies for safety science and management in construction: A critical review and future research directions
فناوری های بینایی رایانه ای برای علم ایمنی و مدیریت در ساخت و ساز: مروری انتقادی و جهت تحقیقات آینده-2021 Recent years have seen growing interests in developing and applying computer vision technologies to solve safety problems in the construction industry. Despite the technological advancements, there is no research that exams the theoretical links between computer vision technology and safety science and management. Thus, the ob- jectives of this paper are to: (1) investigate the current status of applying computer vision technology to con- struction safety, (2) examine the links between computer vision applications and key research themes of construction safety, (3) discuss the theoretical challenges of applying computer vision to construction safety, and(4) recommend future research directions. A five-step review approach was adopted to search and analyze peer- reviewed academic journal articles. A three-level computer vision development framework was proposed to categorized computer vision applications in the construction industry. The links between computer vision and three main safety research traditions: safety management system, behavior-based safety program, and safety culture, were discussed. The results suggest that the majority of past efforts were focused on object recognition, object tracking, and action recognition, with limited research focused on recognizing unsafe behavior. There are even fewer studies aimed at developing vision-based safety assessment and prediction systems. Based on the review findings, four future research directions are suggested: (1) develop and test a behavioral-cues-based safety climate measure, (2) develop safety behavior datasets, (3) develop a formal hazard identification and assessment model, and (4) develop criteria to evaluate the real impacts of vision-based technologies on safety performance. Keywords: Computer vision | Construction health and safety | Safety science | Safety culture | Safety Climate, Hazard | Safety management system | Digital technologies | Automation |
مقاله انگلیسی |
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A bi-objective optimization approach for selection of passive energy alternatives in retrofit projects under cost uncertainty
یک روش بهینه سازی دو هدفه برای انتخاب گزینه های انرژی منفعل در پروژه های مقاوم سازی تحت عدم اطمینان هزینه-2020 Improving energy performance of buildings is of particular importance in new construction and existing buildings. Building refurbishment is considered a practical pathway towards energy efficiency as the replacement of older buildings is at a slow pace. There are various ways of incorporating energy conservation measures in buildings through refurbishment projects. As such, we have to choose among various passive or active measures. In this study, we develop an integrated assessment model to direct energy management decisions in retrofit projects. Our focus will be on alternative passive measures that can be included in refurbishment projects to reduce overall energy consumption in buildings. We identify the relative priority of these alternatives with respect to their non- monetary (qualitative) benefits and issues using an analytic network process. Then, the above priorities will form a utility function that will be optimized along with the energy demand and retrofit costs using a multi-objective optimization model. We also explore various approaches to formulate the uncertainties that may arise in cost estimations and incorporate them into the optimization model. The applicability and authenticity of the proposed model is demonstrated through an illustrative case study application. The results reveal that the choice of the optimization approach for a retrofit project shall be done with respect to the extent of variations (uncertainties) in expected utilities (benefits) and costs for the alternative passive technologies. Keywords: Construction technologies | assive energy measures | Building retrofit | Multi-Objective Optimization | Cost uncertainty | Fuzzy set theory |
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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Evaluating the potential of Estonia as European REE recycling capital via an environmental social governance risks assessment model
ارزیابی پتانسیل استونی به عنوان سرمایه بازیافت REE اروپا از طریق مدل ارزیابی ریسک حاکمیت اجتماعی زیست محیطی-2020 The rare earth elements (REEs) are cornerstone metals of modern society and are used in many applications. Europe is dependant on other continents for the safe supply of rare earth elements as these are to date not mined in Europe. In order to circumvent the shortage of supply, the rare earth elements recycling, especially from End- of-Life (EoL) products are imperative. This article evaluated the feasibility of Estonia as viable REEs recycling hub in Europe via an environmental, social and governance risks evaluation model. The model assessed the pros and cons of Estonia`s environmental, social and governance indicators, and concluded that Estonia is very suitable for the establishment of REEs recycling industry. The environmental indicators showed continuous improvement in environmental health. The Estonian education system is of excellent quality and has produced a highly skilled workforce over the past years. The country’s economic indicators are good, management is transparent and business opportunities are diverse. The environmental, social and governance situations show that Estonia mostly meets the prerequisites for the establishment of a rare earth element recycling industry. The existence of such business will increase the quality of the labour force and economic growth in the long term. Keywords: Critical raw material | ESG | REE | Recycling |
مقاله انگلیسی |
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The use of readiness assessment for big data projects
استفاده از ارزیابی آمادگی برای پروژه های داده بزرگ-2020 Big data projects, including smart-city-related big data projects, are facing an alarmingly high percentage of
failure. The reasons behind this phenomenon and the lessons learned from it are well researched. However, big
data projects are still failing, as there is a lack of effective models to leverage the lessons learned from previous
projects to evaluate an organization’s readiness for a big data project.
In this paper, the authors introduce a novel readiness assessment model. This model leverages the lessons
learned from previous projects and the experience of experts to be better prepared for an upcoming smart-cityrelated
big data project. Cities can use the model to evaluate their readiness for this type of project in a
structured and comprehensive way that will allow for higher chances of conducting a successful big data project.
To develop the model, hierarchical decision modeling (HDM) and expert judgment quantification were used
to provide the categorization and relative ranking of factors that influence smart-city-related big data projects.
HDM is an effective way to understand the relationship between multiple factors and allows for expert panels to
prioritize those factors. Moreover, desirability functions were used to extend the understanding of the factors’
dynamics and what needs to be done to better prepare for the challenges associated with each factor. Finally, the
model was tested by applying it to several smart-city-related big data projects to show its value.
This research highlights the importance of readiness assessment for conducting big data projects and provides
a readiness assessment model that cities can use to prepare for an upcoming big data project. Keywords: Technology management | City readiness | Big data projects |
مقاله انگلیسی |
7 |
Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data
یادگیری ارزیابی کیفیت بدون مرجع مدل تصاویر پیشرفته با داده های بزرگ-2018 In this paper, we investigate into the problem of
image quality assessment (IQA) and enhancement via machine
learning. This issue has long attracted a wide range of attention
in computational intelligence and image processing communities,
since, for many practical applications, e.g., object detection and
recognition, raw images are usually needed to be appropriately
enhanced to raise the visual quality (e.g., visibility and contrast). In fact, proper enhancement can noticeably improve the
quality of input images, even better than originally captured
images, which are generally thought to be of the best quality.
In this paper, we present two most important contributions.
The first contribution is to develop a new no-reference (NR)
IQA model. Given an image, our quality measure first extracts
17 features through analysis of contrast, sharpness, brightness
and more, and then yields a measure of visual quality using
a regression module, which is learned with big-data training
samples that are much bigger than the size of relevant image
data sets. The results of experiments on nine data sets validate
the superiority and efficiency of our blind metric compared
with typical state-of-the-art full-reference, reduced-reference and
NA IQA methods. The second contribution is that a robust
image enhancement framework is established based on quality
optimization. For an input image, by the guidance of the
proposed NR-IQA measure, we conduct histogram modification
to successively rectify image brightness and contrast to a proper
level. Thorough tests demonstrate that our framework can well
enhance natural images, low-contrast images, low-light images,
and dehazed images. The source code will be released at
https://sites.google.com/site/guke198701/publications
Index Terms: Big data learning, enhancement, image quality assessment (IQA), no-reference (NR)/blind |
مقاله انگلیسی |
8 |
Information security risks management framework - A step towards mitigating security risks in university network
چارچوب مدیریت ریسک امنیت اطلاعات - یک قدم برای کاهش خطرات امنیتی در شبکه دانشگاهی-2017 Article history:Keywords: Security risk Security threatsUniversity campus network VulnerabilityInformation is one of the most prominent assets for Universities and must be protected from security breach. This paper analyzed the security threats specifically evolve in University’s network, and with con- sideration of these issues, proposed information security framework for University network environment. The proposed framework reduces the risk of security breach by supporting three phase activities; the first phase assesses the threats and vulnerabilities in order to identify the weak point in educational environment, the second phase focuses on the highest risk and create actionable remediation plan, the third phase of risk assessment model recognizes the vulnerability management compliance requirement in order to improve University’s security position. The proposed framework is applied on Vikram Uni- versity Ujjain India’s, computing environment and the evaluation result showed the proposed framework enhances the security level of University campus network. This model can be used by risk analyst and security manager of University to perform reliable and repeatable risk analysis in realistic and affordable manner.© 2017 Elsevier Ltd. All rights reserved. Keywords: Security risk | Security threats | University campus network | Vulnerability |
مقاله انگلیسی |
9 |
Environmental and economic assessment of pavement construction and management practices for enhancing pavement sustainability
ارزیابی محیطی و اقتصادی ساخت و سازهای پیاده رو و شیوه های مدیریت برای افزایش پایداری پیاده رو-2017 Stakeholders in the pavement sector have been seeking new engineering solutions to move towards
more sustainable pavement management practices. The general approaches for improving pavement
sustainability include, among others, reducing virgin binder and virgin aggregate content in HMA and
WMA mixtures, reducing energy consumed and emissions generated in mixtures production, applying
in-place recycling techniques, and implementing preventive treatments. In this study, a comprehensive
and integrated pavement life cycle costing- life cycle assessment model was developed to investigate,
from a full life cycle perspective, the extent to which several pavement engineering solutions, namely hot
in-plant recycling mixtures, WMA, cold central plant recycling and preventive treatments, are efficient in
improving the environmental and economic dimensions of pavement infrastructure sustainability, when
applied either separately or in combination, in the construction and management of a road pavement
section located in Virginia, USA. Furthermore, in order to determine the preference order of alternative
scenarios, a multicriteria decision analysis method was applied. The results showed that the implemen
tation of a recycling-based maintenance and rehabilitation strategy where the asphalt mixtures are of
type hot-mix asphalt containing 30% RAP, best suits the multidimensional and conflicting interests of
decision-makers. This outcome was found to be robust even when different design and performance
scenarios of the mixtures and type of treatments are considered.
Keywords: Life cycle costing | Life cycle assessment | In-place recycling techniques | Sustainable pavement construction and | management | Multi-criteria decision analysis |
مقاله انگلیسی |
10 |
The synthetic geo-ecological environmental evaluation of a coastal coal-mining city using spatiotemporal big data: A case study in Longkou, China
ارزیابی زیست محیطی مصنوعی محیط زیست یک شهر زغال سنگ ساحلی با استفاده از داده های بزرگ و طولانی مدت: مطالعه موردی در Longkou، چین-2017 The geological and ecological (geo-ecological) environment of the coastal coal-mining city is a basic
element for human subsistence, and it connects the regional economy with social sustainable devel
opment. Using Longkou, a coastal mining city, as an example, a geological and ecological environmental
quality assessment was conducted based on spatiotemporal big data. Remote sensing images, a digital
elevation model (DEM), and precipitation and interpolation processing were used to generate factor
layers. A synthetic evaluation index system was set up, including physical geography, geological condi
tions, mining intensity, ecological environmental recovery and geological hazards associated with
mining. Moreover, an analytical hierarchy process was used to calculate the factor weight of each
evaluation factor, and a consistency check was performed to build an assessment model of the geo
ecological environment of Longkou. The results indicate that multi-factor spatiotemporal big data pro
vide a scientific assessment of the geo-ecological environmental quality with indispensable data and
methods. The spatial distribution of geo-ecological environmental quality presented clear specialization
of zonality, showing poor quality in the coastal coal mine ore concentration area and good quality in the
inland and mountainous areas of Nanshan Mountain. The geo-ecological environmental quality of
Longkou was divided into 5 levels as worst, poor, middle, good and better districts. The good and better
districts accounted for 76.763% of the total area of the assessment region, indicating that the geo
ecological environmental quality of the study area was in good condition. The mining intensity and
ecological environment recovery were major factors in determining the regional variation of the geo
ecological environment of Longkou. The possible causes inducing uncertainties and limitations in eval
uation of the geo-ecological environmental quality were discussed. The model combining AHP with GIS
proposed in this paper is an effective means of evaluating regional geo-ecological environmental quality.
Keywords:Remote sensing|Analytic hierarchy process|Geo-ecological environmental assessment|Coal mine concentration area |
مقاله انگلیسی |