Sharif Digital Repository

In the aftermath of earthquakes, hospitals serve the critical role of treating casualties. In many cases, the key components of a hospital (i.e., the building, staff, medicine inventory, technical systems, and medical equipment) are affected by an earthquake. To handle the demand surge, affected hospitals should recover in an effective manner. Hospital recovery is a complex and dynamic process because each component requires specific types and amount of resources to recover. Furthermore, the recovery of each component not only affects its performance but also plays a role in the overall hospital recovery. Hospital administrators need to model the complex recovery process after a future... 

Recently, development of advanced materials of metal-organic frameworks (MOFs) has attracted attention for the fabrication of supercapacitors (SCs) because of their high surface area and high level of porosity. However, poor electrical conductivity and weak mechanical properties of the MOFs have restricted their applications in the field. In this study, a one-step, in-situ synthesis of Cobalt-based MOF with graphene (CoMG nanocomposite) was employed to overcome the poor properties of MOFs. Accordingly, when the nanocomposite (CoMG5) was use as a supercapacitor electrode material, a specific capacitance (CS) of 549.96 F g−1 was observed in a three-electrode system with 6 M KOH electrolyte... 

This study presents a framework that utilizes Bayesian regression to create probabilistic cost models for retrofit actions. Performance improvement is the key parameter introduced in the proposed framework. The incorporation of this novel feature facilitates the characterization of retrofit cost as a continuous function of the desired performance improvement. Accounting for the performance gained from retrofit enables the use of the models in determining the optimal level of retrofit. Furthermore, accounting for the model uncertainty facilitates the use of the models in risk and reliability analyses. The proposed framework is applied to create seismic retrofit cost models for masonry school... 

Recently, development of advanced materials of metal-organic frameworks (MOFs) has attracted attention for the fabrication of supercapacitors (SCs) because of their high surface area and high level of porosity. However, poor electrical conductivity and weak mechanical properties of the MOFs have restricted their applications in the field. In this study, a one-step, in-situ synthesis of Cobalt-based MOF with graphene (CoMG nanocomposite) was employed to overcome the poor properties of MOFs. Accordingly, when the nanocomposite (CoMG5) was use as a supercapacitor electrode material, a specific capacitance (CS) of 549.96 F g−1 was observed in a three-electrode system with 6 M KOH electrolyte... 

This study aims to find the differences between national and international relationships in Iran and Switzerland’s Nanoscience research between 2008–2015. The results show significant differences some of which are attributed to the general dichotomy of developed-developing countries like stronger University-Industry-Government relations in Switzerland; but others are not, especially those pertaining to bilateral relations. In summary, the Government-Industry relations in Switzerland are generally closer in this field because the emerging characteristics of Nanoscience call for more state intervention, even in the context of developed countries. Greater Government-University relations in Iran... 

To enhance impedance bandwidth of spherical Microstrip antenna with annular-circular patch, an air gap layer between antenna ground and substrate layer has been employed. The principle purpose of this work is to consider the effect of such layer on the impedance bandwidth and, consequently, antenna performance. To provide circular polarization, we have applied anisotropic uniaxial crystal as a substrate in spherical Microstrip antenna. Evaluating the impact of air gap layer on radiation pattern of spherical Microstrip antenna with annular-circular patch via CST program is the other goal of this correspondence for three types of substrate materials, anisotropic negative uniaxial crystal,... 

Engineering, procurement and construction (EPC) contracts are commonly used for the construction of oil and gas production facilities. These projects are subjected to many uncertainties. EPC contractors often assume most of the project risks. Several studies have focused on the identification and analysis of EPC project risks. However, they generally fail to define appropriate and effective risk management strategies. The objective of this study is to define efficient risk mitigation strategies that can be utilized in EPC oil and gas projects. A comprehensive review of literature was conducted to identify the risks in EPC projects. Experts' opinion were used to analyze and categorize these... 

Construction managers regularly monitor projects to ensure that the project performance is under control. The earned value method (EVM) is a widely used tool to forecast project cost and time at completion. However, the effectiveness of the EVM in forecasting schedule performance has been questioned particularly because of its inability to address the associated uncertainties and poor performance in predicting project duration. The objective of this study is to present an activity-based model to conduct a probabilistic assessment and estimation of schedule performance in repetitive construction projects. This model, called the Weibull evaluation and forecasting model (WEFM), emphasizes the... 

Providing a comprehensive overview of the safety status of similar large-scale rail spatial units (such as existing Rail Regions (RRs) in a country) is a first but very important step in identifying policies that can accelerate progress in improving rail safety. The aim of the current study is to present a new approach to assess RR's safety performance with an emphasis on the Resources and Equipment (R&E) of each RR. To reach the study goal, first, a conceptual framework is developed to make a relationship among exposure, safety, and R&E of RRs. In the next step, Data Envelopment Analysis (DEA) model with Fuzzy-Delphi method is used to evaluate the safety performance of different RRs. In... 

This manuscript presents a framework to develop vector error correction (VEC) models applicable to forecasting the short- and long-run movements of the average hourly earnings of construction labor, which is an essential predictor of the construction labor costs. These models characterize the relationship between average hourly earnings and a set of explanatory variables. The framework is applied to develop VEC forecasting models for the average hourly earnings of construction labor in the USA based on the identified variables that govern its movements, such as Global Energy Price Index, Gross Domestic Product, and Personal Consumption Expenditures. More than 150 candidate VEC models were... 

Purpose: Motivated by the high cost of material movements in road construction projects, past studies have used analytical methods to optimize materials logistics plans. A key shortcoming of these methods is their inability to capture the uncertain, dynamic and complex characteristics of the road construction material logistics. Failure to incorporate these characteristics can lead to sub-optimal results. The purpose of this study is to propose the use of discrete event simulation (DES) to address the existing shortfall. Design/methodology/approach: Despite the powerful capabilities of DES models in capturing the operational complexities of construction projects, they have not been... 

A disaster's response and recovery phases can be characterized by the breadth of activities, complex interrelationships of multiple involved agencies, and uncertain outcomes. Proper performance and collaboration of responsible agencies can mitigate disaster-induced losses. Past studies have not holistically investigated the role of responsible agencies’ operation and cooperation in post-disaster community recovery. This study proposes a hybrid framework that facilitates the probabilistic modeling of responsible agencies' post-disaster performance and coordination. An Agent-based Modeling (ABM) sub-model simulates the operations and interactions of responsible agencies. A System Dynamics (SD)... 

This study draws a historical picture of conceptual linkages of innovation systems (IS) and global value chains (GVC). We used a co-citation technique to map the evolution of these two fields since 1990. We highlighted the connecting nodes over the past three decades. The first decade witnessed a connection between national innovation systems (NIS) and GVC, mediated by regional studies related to industrial clusters and district-based innovation. The tradeoff between tacit sticky local and codified transferable global knowledge and innovation and learning's importance in upgrading in GVC generated two new routes in the second decade. In the last decade, although these routes are retained,... 

This paper proposes a sublime-optimum soft- computing based controller to follow a desired path with a desired velocity by mobile robots with identified dynamical behavior. This method consists of a fuzzy controller where a trained Neural Network sets its membership functions values in On-line mode. Training of the Network is done by a Genetic Algorithm for various vehicle initial positions and different path convexities in Off-line. After the training of the network, during vehicle motion, it retrieves sub-optimized fuzziness values and sends them to the fuzzy control algorithm according to the vehicle position. Meanwhile, the influential of the path convexity is considered in fuzziness of... 

In this study, scaling effects on fiber metal laminates under tensile and three-point bending tests were investigated numerically and experimentally. The fiber metal laminate specimens were made of aluminum 1050 and unidirectional glass-epoxy. Two scaled sizes of specimens were prepared based on A1n, 0n=90n s. Some specified mechanical properties of these samples were investigated and results showed that fiber metal laminates obey scaling law under quasi-static loading. Explicit finite element code LS-DYNA was utilized for numerical simulation. After validating numerical simulation with experiments, scaling law was studied numerically for four different... 

The goal of robust parameter estimation is developing a model which can properly fit to data. Parameter estimation of a geometric model, in presence of noise and error, is an important step in many image processing and computer vision applications. As the random sample consensus (RANSAC) algorithm is one of the most well-known algorithms in this field, there have been several attempts to improve its performance. In this paper, after giving a short review on existing methods, a robust and efficient method that detects the gross outliers to increase the inlier to outlier ratio in a reduced set of corresponding image points is proposed. It has a new hypothesis and verification scheme which... 

The goal of robust parameter estimation is developing a model which can properly fit to data. Parameter estimation of a geometric model, in presence of noise and error, is an important step in many image processing and computer vision applications. As the random sample consensus (RANSAC) algorithm is one of the most well-known algorithms in this field, there have been several attempts to improve its performance. In this paper, after giving a short review on existing methods, a robust and efficient method that detects the gross outliers to increase the inlier to outlier ratio in a reduced set of corresponding image points is proposed. It has a new hypothesis and verification scheme which... 

The pharmaceutical industry is facing enormous challenges due to high drug attribution rates. For the past decades, novel methods have been developed for safety and efficacy testing, as well as for improving early development stages. In vitro screening methods for drug-receptor binding are considered to be good alternatives for decreasing costs in the identification of drug candidates. However, these methods require lengthy and troublesome labeling steps. Biosensors hold great promise due to the fact that label-free detection schemes can be designed in an easy and low-cost manner. In this paper, for the first time in the literature, we aimed to compare the potential of label-free optical and... 

In the absence of effective and adequate vaccines, healthcare decision-makers must rely on non-pharmaceutical interventions (NPIs), such as lockdown, testing, hospital capacity building, and increasing the number of medical staff to control the outbreak of an infectious disease like COVID-19. This manuscript presents a System Dynamics (SD) model to analyze the healthcare system performance under various NPIs during a pandemic. The proposed model, which extends the commonly-used Susceptible-Exposed-Infectious-Recovered (SEIR) model, comprises four sub-models: outbreak, hospital performance, medicine supply, and staff functionality. These sub-models work in harmony to stimulate the impact of... 

In most image retrieval systems, images include various high-level semantics, called tags or annotations. Virtually all the state-of-the-art image annotation methods that handle imbalanced labeling are search-based techniques which are time-consuming. In this paper, a novel coupled dictionary learning approach is proposed to learn a limited number of visual prototypes and their corresponding semantics simultaneously. This approach leads to a real-time image annotation procedure. Another contribution of this paper is that utilizes a marginalized loss function instead of the squared loss function that is inappropriate for image annotation with imbalanced labels. We have employed a marginalized...