با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
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
A mathematical model for neuronal differentiation in terms of anevolved dynamical system
یک مدل ریاضی برای تمایز عصبی از نظر سیستم دینامیکی برهم خورده-2020
We attempted to create a mathematical model for neuronal differentiation. The present study wasperformed within the framework of self-organization with constraints by looking for an optimized infor-mational unit. We treated networks of individual dynamical system units with an external input, whichwas provided by coupled one-dimensional maps with possible forms of unidirectionally feed-forwardnetwork, random network, small-world network, and fully-connected network. We used a genetic algo-rithm to maximize the information transmission for each type of network. Optimized maps were obtaineddepending on the coupling strength and network structure. These maps can be classified into three types:passive, excitable, and oscillatory. In particular, the excitable and oscillatory types of dynamical systemspossess characteristics that are quite similar to those of neurons, whereas the passive and oscillatorytypes of dynamical system may represent glial cells.
Keywords:Self-organization with constraints | Coupled dynamical systems | Evolutionary dynamics | Neuronal differentiation | Oscillology
Project schedule performance under general mode implementation disruptions
عملکرد برنامه پروژه تحت اختلال در اجرای کلی حالت-2020
This paper presents a simulation study for a resource-constrained project scheduling problem with mul- tiple alternatives. We decide on a set of baseline schedules at the project planning phase, resulting in options to switch between execution modes of activities during project execution. We assess the perfor- mance of the set of baseline schedules under general mode implementation disruptions. A simple, yet effective algorithm is presented to construct the set of baseline schedules. Moreover, a general disruption system is proposed to model different disruption types, disruption dependencies and disruption sizes.
Keywords: Project management | Execution alternatives | Matheuristic | Disruption system
Extreme learning machine for a new hybrid morphological/linear perceptron
دستگاه یادگیری شدید برای مورفولوژی جدید ترکیبی / پرسپترون خطی-2020
Morphological neural networks (MNNs) can be characterized as a class of artificial neural networks that perform an operation of mathematical morphology at every node, possibly followed by the application of an activation function. Morphological perceptrons (MPs) and (gray-scale) morphological associative memories are among the most widely known MNN models. Since their neuronal aggregation functions are not differentiable, classical methods of non-linear optimization can in principle not be directly applied in order to train these networks. The same observation holds true for hybrid morphological/ linear perceptrons and other related models. Circumventing these problems of non-differentiability, this paper introduces an extreme learning machine approach for training a hybrid morphological/linear perceptron, whose morphological components were drawn from previous MP models. We apply the resulting model to a number of well-known classification problems from the literature and compare the performance of our model with the ones of several related models, including some recent MNNs and hybrid morphological/linear neural networks.
Keywords: Mathematical morphology | Lattice computing | Morphological neural networks | Hybrid morphological/linear perceptron | Extreme learning machine | Classification
A novel approach for occupational health and safety and environment risk assessment for nuclear power plant construction project
یک رویکرد جدید برای بهداشت و ایمنی شغلی و ارزیابی خطر محیط زیست برای پروژه ساخت نیروگاه هسته ای-2020
Nuclear Power Plant (NPP) construction project is a mega one with high level of occupational health and safety and environment (OHSE) risks, and it is necessary to propose an approach for the OHSE risk assessment so as to prevent the OHSE accidents or reduce their outcomes. However, there has not been such an approach due to the high uncertainty and complexity of NPP construction project. Therefore, this paper proposed a novel approach for the OHSE risk assessment which includes systematically identifying the OHSE risks by using brainstorming method, establishing an OHSE risk assessment index system by using Delphi method, and formulating a mathematical model by combining set pair analysis (SPA), trapezoidal fuzzy number (TPFN), and set-valued statistics (SVS) methods for determining the overall OHSE risk level for NPP construction project. The approach was used to assess the OHSE risks for the NPP construction project in East China, and its overall OHSE risk level was assessed at level 2 (low OHSE risk level). In addition, the problems in the OHSE risk management were found, and the corresponding OHSE risk treatments for these problems were implemented. The results showed that the approach helped reduce the OHSE risk level and protect the workers occupational health and safety and the environment while the NPP construction project was under construction
Keywords: Nuclear power plant construction project | Occupational health and safety and | environment | Risk assessment | Mathematical model
In this paper, a novel problem in transshipment networks has been proposed. The main aims of this pa- per are to introduce the problem and to give useful tools for solving it both in exact and approximate ways. In a transshipment network it is important to decide which are the best paths between each pair of nodes. Representing the network by a graph, the union of thesepaths is a delivery subgraph of the original graph which has all the nodes and some edges. Nodes in this subgraph which are adjacent to more than two nodes are called switches because when sending the flow between any pair of nodes, switches on the path must adequately direct it. Switches are facilities which direct flows among users. The installation of a switch involves the installation of adequate equipment and thus an allocation cost. Furthermore, traversing a switch also implies a service cost or allocation cost. The Switch Location Prob- lem is defined as the problem of determining which is the delivery subgraph with the total lowest cost. Two of the three solutions approaches that we propose are decomposition algorithms based on articula- tion vertices, the exact and the math-heuristic ones. These two approaches could be embedded in expert systems for locating switches in transshipment networks. The results should help a decision maker to select the adequate approach depending on the shape and size of the network and also on the exter- nal time-limit. Our results show that the exact approach is a valuable tool if the network has less than 10 0 0 nodes. Two upsides of our heuristics are that they do not require special networks and give good solutions, gap-wise. The impact of this paper is twofold: it highlights the difficulty of adequately locating switches and it emphasizes the benefit of decomposing algorithms.
Keywords: Discrete location | Math-heuristic | Articulation vertex | Block-Cutpoint graph
استفاده از رسانه های اجتماعی برای شناسایی جذابیت گردشگری در شش شهر ایتالیا
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 18
تکامل فناوری و گسترش شبکه های اجتماعی به افراد اجازه داده است که مقادیر زیادی داده را در هر روز تولید کنند. شبکه های اجتماعی کاربرانی را فارهم می کند که به اطلاعات دسترسی دارند. هدف این مقاله تعیین جذابیت های شهرهای مختلف گردشگری ازطریق بررسی رفتار کاربران در شبکه های اجتماعی می باشد. پایگاه داده ای شامل عکس های جغرافیایی واقع شده در شش شهر می باشد که به عنوان یک مرکز فرهنگی و هنری در ایتالیا عمل می کنند. عکس ها از فلیکر که یک بستر به اشتراک گذاری داده می باشد دانلود شدند. تحلیل داده ها با استفاده از دیدگاه مدلهای یادگیری ریاضی و ماشینی انجام شد. نتایج مطالعه ما نشانگر نقشه های شناسایی رفتار کاربران، گرایش سالانه به فعالیت تصویری در شهرها و تاکید بر سودمند بودن روش پیشنهادی می باشد که قادر به تامین اطلاعات مکانی و کاربری است. این مطالعه تاکید می کند که چگونه تحلیل داده های اجتماعی می تواند یک مدل پیشگویانه برای فرموله کردن طرح های گردشگری خلق کند. در انتها، راهبردهای عمومی بازاریابی گردشگری مورد بحث قرار می گیرند.
|مقاله ترجمه شده|
Investigation of iron oxide nanoparticle cytotoxicity in relation to kidney cells: A mathematical modeling of data mining
بررسی سمیت سلولی نانوذرات اکسید آهن در رابطه با سلولهای کلیوی: مدل سازی ریاضی داده کاوی-2019
Iron oxide nanoparticles (IONs) have several applications in medical fields including magnetic resonance imaging (MRI), drug delivery, cancer treatment and cell splitting. Therefore, it is important to investigate their cellular toxicity. It is difficult to predict their cellular toxicity due to complexities associated with their cellular mechanisms. The present study was designed to collect data on the cell viability of IONs and obtain a mathematical modeling. For this purpose, particle size, concentration, incubation time and the surface charge of NPs were selected as the model inputs and the percentage of cell viability (%CV) as the model output. Using a version of the modeling called SA-LOOCV-GRBF, these issues can be resolved with favorable results. Since the behavior of positive zeta potential (PZP) is different from negative zeta potential (NZP), they were compared by separate modeling efforts. Kidney is a vital body organ that dispose of IONs in the body, but it is possible that these cells engage in unwanted interactions with IONs. Therefore, the kidney cell line was examined in this study.
Keywords: Cell viability | Iron oxide nanoparticle | Modeling | Negative zeta potential | Positive zeta potential
Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming
بهینه سازی تحت عدم اطمینان در عصر داده های بزرگ و یادگیری عمیق: وقتی یادگیری ماشین با برنامه نویسی ریاضی ملاقات می کند-2019
This paper reviews recent advances in the field of optimization under uncertainty via a modern data lens, highlights key research challenges and promise of data-driven optimization that organically integrates machine learning and mathematical programming for decision-making under uncertainty, and identifies potential research opportunities. A brief review of classical mathematical programming techniques for hedging against uncertainty is first presented, along with their wide spectrum of applications in Process Systems Engineering. A comprehensive review and classification of the relevant publications on data- driven distributionally robust optimization, data-driven chance constrained program, data-driven robust optimization, and data-driven scenario-based optimization is then presented. This paper also identifies fertile avenues for future research that focuses on a closed-loop data-driven optimization framework, which allows the feedback from mathematical programming to machine learning, as well as scenario- based optimization leveraging the power of deep learning techniques. Perspectives on online learning- based data-driven multistage optimization with a learning-while-optimizing scheme are presented.
Keywords: Data-driven optimization | Decision making under uncertainty | Big data | Machine learning | Deep learning
Analysis of automotive gearbox faults using vibration signal
تحلیل خطای گیربکس اتومبیل با استفاده از سیگنال لرزش-2019
The objective of this work is to identify the presence of damages and to diagnose the damaged component in automotive gearboxes by comparing the vibration signals of the damaged and undamaged systems. The vibration signals were obtained in the gearboxes test bench taking into account ten samples approved by subjective method (based on human hearing) and three gearboxes damaged (two with bearing damaged and one with gear tooth damaged). The signals were obtained through five accelerometers positioned in the samples and each test comprises ten different steps with different coupling configurations of the gears. Different signal analysis techniques based on wavelet transform, mathematic morphology and energy (entropy) were used to verify the presence of damage in the systems. The presence of damage to the systems is verified directly by comparing the energy levels and entropy of the signals of the damaged and undamaged systems for the ten steps tests. A signal processing technique combining pattern spectrum and selective filtering in certain frequencies ranges was used for identification of component failures. This technique will, further on, be part of a diagnostic and quality control system that will be able to evaluate and identify the damaged component at the automotive gearbox.
Keywords: Automotive gearbox | Damage | Mathematical morphology | Wavelet | Entropy