Sharif Digital Repository

Large technology-intensive enterprises and companies face a constant challenge: How can a set of selected high-tech projects get done in a manner that would minimize the total cost across all projects? In majority of cases, projects are assumed independent, leading to a separate cost evaluation. This assumption often does not hold for real-world project portfolios, frequently sharing overlapping technologies. In this paper, we show how the order of the execution of the projects can directly affect the total cost of the portfolio, due to shared dependencies. Modeling the problems in this area can be achieved by combining two main fields: graph theory and technology mining. A novel method is... 

Purpose - This study aims to investigate the relationship between university and industry as two major infrastructures of national innovation system in all leading scientific and industrial settings. Design/methodology/approach - Large complex organizations with high technology that follow non-linear dynamic rules need to define concepts and adopt new approaches to achieve organizational efficiency and effectiveness. Among various models, a dynamic model of innovation was developed based on a joint investment between industry and university. Hence, the concepts of systems thinking and system dynamics were used.Findings- The results reveal three levels of industry and university communication... 

In both public and private sectors, critical technology-based tasks, such as innovation, forecasting, and road-mapping, are faced with unmanageable complexity due to the ever-expanding web of technologies which can range into thousands. This context cannot be easily handled manually or with efficient speed. However, more precise and insightful answers are expected. These answers are the fundamental challenge addressed by tech-mining. For tech-mining, discovering the associations among them is a critical task. These associations are used to form a weighted directed graph of technologies called “association tech-graph” which is used for technology development, trend analysis, policymaking,... 

In both public and private sectors, critical technology-based tasks, such as innovation, forecasting, and road-mapping, are faced with unmanageable complexity due to the ever-expanding web of technologies which can range into thousands. This context cannot be easily handled manually or with efficient speed. However, more precise and insightful answers are expected. These answers are the fundamental challenge addressed by tech-mining. For tech-mining, discovering the associations among them is a critical task. These associations are used to form a weighted directed graph of technologies called 'association tech-graph' which is used for technology development, trend analysis, policymaking,... 

One of the new forming world discipline feature is knowledge based innovation. World new discipline, vitality condition is to establish new science and technology and suitable utility from that. Therefore, the new era witness those grand variations in university systems and for more utilization process in national, regional and international economical development. In this context, traditional university variation and conversion to Entrepreneurial University and holding and creating idea and supporting it to transform in final product or service is concerned, which means knowledge-based entrepreneurship. Thus, this university can develop knowledge-based staff and has nontraditional processes... 

An efficient algorithm for the design optimization of the compressible fluid flow problem through a flexible structure is presented. The methodology has three essential parts: first the behavior of compressible flow in a supersonic diffuser was studied numerically in quasi-one-dimensional form using a flux splitting method. Second, a fully coupled sequential iterative procedure was used to solve the steady state aeroelastic problem of a flexible wall diffuser. Finally, a robust Genetic Algorithm was implemented and used to calculate the optimum shape of the flexible wall diffuser for a prescribed pressure distribution. © 2006 Elsevier Ltd. All rights reserved  

In this paper, the authors analyze conditions under which they can be certain on the intensity addition of a given device, such as tapped-delay lines, used in digital incoherent all-optical communication systems. A general expression for phase-induced intensity noise that is applicable to all types of semiconductor lasers is derived by defining an optical self-SNR expression that can be used to analyze and measure phase-induced intensity noise. The result shows that in order to have a minimal phase-induced intensity noise in most digital optical incoherent systems, a large optical self-SNR, e.g., 20 dB or more, is needed. This in turn is shown to place a limit on the maximum rate of... 

Nowadays, the number of digital images has increased so that the management of this volume of data needs an efficient system for browsing, categorising and searching. Automatic image annotation is designed for assigning tags to images for more accurate retrieval. Non-negative matrix factorisation (NMF) is a traditional machine learning technique for decomposing a matrix into a set of basis and coefficients under the non-negative constraints. In this study, the authors propose a two-step algorithm for designing an automatic image annotation system that employs the NMF framework for its first step and a variant of K-nearest neighbourhood as its second step. In the first step, a new multimodal... 

In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is... 

In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is... 

Automatic Image Annotation (AIA) helps image retrieval systems by predicting tags for images. In this paper, we propose an AIA system using Non-negative Matrix Factorization (NMF) framework. The NMF framework discovers a latent space, by factorizing data into a set of non-negative basis and coefficients. To model the images, multiple features are extracted, each one represents images from a specific view. We use multi-view graph regularization NMF and allow NMF to choose a different number of basis vectors for each view. For tag prediction, each test image is mapped onto the multiple latent spaces. The distances of images in these spaces are used to form a unified distance matrix. The... 

Real time road traffic monitoring is one of the challenging problems in machine vision, especially when one is using commercially available PCs as the main processor. In this paper, we describe a real-time method for extracting a few traffic parameters in highways such as, lane change detection, vehicle classification and vehicle counting. In addition, we will explain a real time method for multiple vehicles tracking that has the capability of occlusion detection. Our tracing algorithm uses Kalman filter and background differencing techniques. We used morphological operations for vehicle contour extraction and its recognition. Our algorithm has three phases, detection of pixels on moving... 

With the significant role that warehouse plays in connection to suppliers, distributors, and clients, and considering the costliness of storage systems, efforts have focused on the reduction of procedural expenses. Among the most significant expenses, one involves the distance traveled by operators or S/R machinery for the selection of ordered items; the common solution to which has been through the classification of stored items. Previous articles have focused on linear solutions to the abovementioned problem, such as P-Median. This article shall focus on the problems arising from the said solution, and instead a non-linear method proposed. Further, a heuristic algorithm is produced for the... 

A new and simple receiver structure for reducing the multipath inter-symbole interference (ISI) effect is proposed for infrared diffuse links. In this new method, bit-error rate (BER) performance of the system will be improved significantly without any essential change in the receiver structure. In our analysis, all major noise sources such as ambient light, signal shotnoise, dark current and thermal noise of the receiver are considered. © 2009 IEEE  

Veronica genus (Plantaginaceae) is broadly distributed in different habitats. In this study, the inhibitory activity of free soluble and conjugated phenolic extracts of Veronica persica on key enzymes associated to type 2 diabetes (α-glucosidase and α-amylase) and hypertension (angiotensin I converting enzyme, ACE) was assessed, as well as their antioxidant power. Our results showed that both the extracts inhibited α-amylase, α-glucosidase and ACE in a dose-dependent manner. In particular, free phenolic extract significantly (P < 0.05) inhibited α-glucosidase (IC50 532.97 μg/mL), whereas conjugated phenolic extract significantly (P < 0.05) inhibited a-amylase (IC50 489.73 μg/mL) and ACE... 

The suspension of titania nanoparticles in different alcohols (methanol, ethanol, and butanol) was prepared and triethanolamine (TEA) was used as a dispersant. The suspensions were characterized by different tests such as sedimentation, zeta potential, and Fourier transform infrared spectroscopy. The electrophoretic deposition (EPD) was performed at various voltages and times. EPD from butanolic suspension (0.8 g/L TEA) showed the slowest kinetics, because of the low electrophoretic mobility of titania nanoparticles in it (2.40 × 10-5 cm2·(V·s)-1). Also, it was observed that at low voltages (5, 10, and 20 V), the EPD kinetics from methanolic suspension (0 g/L TEA) was the fastest; however,... 

The alcoholic suspensions of titania nano-particles were prepared using the methanol, ethanol, isopropanol and butanol as the solvents as well as triethanolamine (TEA) as an dispersant. The colloidal stability of suspensions, both in the absence as well as presence of TEA, was studied by measuring the zeta potential, sedimentation, pH and electrical conductivity of suspensions, dispersant adsorption and particles size distribution. Results showed that in the absence of TEA, the stability of the suspensions increases with the molecular size of alcohol (from methanol to butanol), while the zeta potential decreases. It was also observed that with the addition of TEA up to the optimum dosage (4... 

Lithium ion batteries as one of the most important energy storage equipments, have several challenges including capacity drop as number of cycles increases. Cathode particle coating is an effective approach in improvement of electrochemical performance of the batteries. In this study, TiO2-Ag coating was used to improve NCM cathode performance. The microstructure and crystal structure properties of coated NCMs were evaluated by the FE-SEM and XRD. Electrochemical behavior of the batteries was investigated by cycling performance analysis and EIS. TiO2 coating was deposited as a uniform layer and Ag coating was precipitated as dispersed nanoparticles. The results shows that using of TiO2-Ag... 

This paper introduces the connection-graph-stability method and uses it to establish a new lower bound on the algebraic connectivity of graphs (the second smallest eigenvalue of the Laplacian matrix of the graph) that is sharper than the previously published bounds. The connection-graph-stability score for each edge is defined as the sum of the lengths of the shortest paths making use of that edge. We prove that the algebraic connectivity of the graph is bounded below by the size of the graph divided by the maximum connection-graph-stability score assigned to the edges  

Recurrent neural networks based on reservoir computing are increasingly being used in many applications. Optimization of the topological structure of the reservoir and the internal connection weights for a given task is one of the most important problems in reservoir computing. In this paper, considering the fact that one can construct a large matrix using Kronecker products of several small-size matrices, we propose a method to optimize the reservoir. Having a small number of parameters to optimize, a gradient based algorithm is applied to optimize parameters, and consequently the reservoir. In addition to reducing the number of parameters for optimization, potentially, the method is able...