Sharif Digital Repository

Automatic image annotation has emerged as an important research topic due to the existence of the semantic gap and in addition to its potential application on image retrieval and management. In this paper we present an approach which combines regional contexts and visual topics to automatic image annotation. Regional contexts model the relationship between the regions, whereas visual topics provide the global distribution of topics over an image. Conventional image annotation methods neglected the relationship between the regions in an image, while these regions are exactly explanation of the image semantics, therefore considering the relationship between them are helpful to annotate the... 

PM10 prediction has attracted special legislative and scientific attention due to its harmful effects on human health. Statistical techniques have the potential for high-accuracy PM10 prediction and accordingly, previous studies on statistical methods for temporal, spatial and spatio-temporal prediction of PM10 are reviewed and discussed in this paper. A review of previous studies demonstrates that Support Vector Machines, Artificial Neural Networks and hybrid techniques show promise for suitable temporal PM10 prediction. A review of the spatial predictions of PM10 shows that the LUR (Land Use Regression) approach has been successfully utilized for spatial prediction of PM10 in urban areas.... 

The prevalence of complex Cyber-Physical Systems (CPS) as an increasingly ubiquitous technology, necessitates the incorporation of component based and compositional design methods for the development and deployment of such systems. In this paper, we introduce a hybrid coordination framework to specify CPSs with components and use the resulting models to simulate, validate and verify those systems, using UPPAAL statistical model checker (SMC). We use SMC because with a level of uncertainty and unpredictability (e.g., the physical environment with which a CPS interacts), simulation-based verification approaches, where properties are guaranteed with a degree of confidence, produce more... 

This study deals with the problem of outlier censoring from the secondary data in a radar scenario, where the number of outliers is unknown. To this end, a procedure consisting of joint likelihood estimation and statistical model order selection (MOS) is proposed. Since the maximum likelihood (ML) estimation of the outlier subset requires to solve a combinatorial problem, an approximate ML (AML) method is employed to reduce the complexity. Therefore, to determine the number of outliers, different MOS criteria based on likelihood function are applied. At the analysis stage, the performance of the proposed methods is assessed based on simulated data. The results highlight that the devised... 

The high resolution range profile (HRRP) is known as the most important tool in radar target recognition. Mainly, the sensitivity to the aspect angle limits the performance of the related methods. To overcome this problem, Gaussian mixture distribution is used to model the short-term relation of consecutive HRRPs. In this work, an alternative dynamical system based method is proposed to overcome the limitations of recent methods in the field such as the independency assumption. Here, the performance of the method is tested by the data produced in an electromagnetic simulation for the radar return from an aerial maneuvering target. The results show the performance of the proposed method... 

The increased penetration of cellular networks has made voice channels widely available ubiquitously. On the other hand, mobile voice channels possess properties that make them an ideal choice for high priority, low-rate real-time communications. Mobile voice channel with the mentioned properties, could be utilised in emergency applications in vehicular communications area such as the standardised emergency call system planned to be launched in 2015. This study aims to investigate the challenges of data transmission through these channels and proposes an efficient data transfer structure. To this end, a proper statistical model for the channel distortion is proposed and an optimum detector... 

Pulse Repetition Interval (PRI) Modulation Detection is an important subsystem of a typical electronic warfare support system. In this paper, a robust, fast, and well designed structure for detection of simple and complex PRI modulations based on statistical and sequential analysis of Pulse Repetition Interval (PRI) is proposed. Accuracy and robustness of the technique against electromagnetic noise are demonstrated via simulations  

These two papers present an innovative method of configurable flaw classification and volume estimation in oil pipelines. In part I, the ultrasonic image acquisition system is introduced and surface and volume of the flaw are estimated with fuzzy image processing. A number of real figures illustrate the system performance. The flops calculation reveals that this fuzzy estimator could be integrated in a real time flaw detection system. In part II, at first, the dynamic detection of interesting points, i.e. as feature points at different levels of images, is proposed using wavelet transform. Furthermore, a guided searching strategy is used for the best matching from the coarse level to a fine... 

One of the major problems in underdetermined Sparse Component Analysis (SCA) in the field of (semi) Blind Source Separation (BSS) is the appropriate estimation of the mixing matrix, A, in the linear model X = AS, especially where more than one source is active at each instant of time. Most existing algorithms require the restriction that at each instant (i.e. in each column of the source matrix S), there is at most one single dominant component. Moreover, these algorithms require that the number of sources must be determined in advance. In this paper, we proposed a new algorithm for estimating the matrix A, which does not require the restriction of single dominant source at each instant.... 

Employing a biharmonic boundary integral method with linear elements, coarsening dynamics of nanodroplets on topographical step heterogeneity is investigated. It is shown that the step height and droplet configuration have an influential effect on the dynamics. Increasing the step height slows down the process while locating the droplets close to the step boosts the coarsening rate. Considering a slip boundary condition enhances the dynamics and reveals a transition in the droplet migration direction. Our results reveal that increasing the surface wettability weakens the dynamics. Various types of the disjoining pressure over the step are also considered and their effects on the coarsening... 

The depth of anesthesia estimation has been one of the most research interests in the field of EEG signal processing in recent decades. In this paper we present a new methodology to quantify the depth of anesthesia by quantifying the dynamic fluctuation of the EEG signal. Extraction of useful information about the nonlinear dynamic of the brain during anesthesia has been proposed with the optimum Fractal Scaling Exponent. This optimum solution is based on the best box sizes in the Detrended Fluctuation Analysis (DFA) algorithm which have meaningful changes at different depth of anesthesia. The Fractal Scaling Exponent (FSE) Index as a new criterion has been proposed. The experimental results... 

Background: Codon degeneracy and codon usage by organisms is an interesting and challenging problem. Researchers demonstrated the relation between codon usage and various functions or properties of genes and proteins, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Researchers usually represent segments of proteins responsible for specific functions or structures in a family of proteins as sequence patterns or motifs. We asked the question if organisms use the same codons in pattern segments as compared to the rest of the sequence. Methods. We used the likelihood ratio test, Pearson's chi-squared test, and mutual information... 

To determine the outward permeability of retina-choroid-sclera (RCS) layer for different ophthalmic drugs and to develop correlations between drug physicochemical properties and RCS permeability. A finite volume model was developed to simulate pharmacokinetics in the eye following drug administration by intravitreal injection. The RCS permeability was determined for 32 compounds by best fitting the drug concentration-time profile obtained by simulation with previously reported experimental data. Multiple linear regression was then used to develop correlations between best fit RCS permeability and drugs physicochemical properties. The RCS drug permeabilities had values that ranged over 3 ×... 

Time-cost trade-off problems (TCT) are well-known in project management contents. This approach normally applied for scheduling of a project especially where the project should be completed under pre-determined deadline. This paper aims to extend time-cost trade-off (TCT) problems in order to provide a well-organized mechanism for both scheduling and rescheduling processes of a project. The proposed mechanism includes project scheduling which concerns with the TCT problem, monitoring of project performance during execution phase using earned value management (EVM), and also predicting project future performance through statistical modeling. Once the predicted values of project performance... 

The objective of this study was to propose a new analytical model for studying response of head impacts. Head is modeled by fluidfilled ellipsoidal shell of inconstant thickness impacted by a solid elastic sphere. Modeling the head as an ellipsoid is more realistic than modeling it as a sphere, the previous model existing in the literature [3]-[8]. In this model, the effect of Hertzian contact stiffness and local shell stiffness are combined to derive explicit equations for impact duration, the peak force transmitted to head, and the head injury criterion. One of the advantages of the model presented is sensitivity to the site of impact. A comparison between the present analytical results... 

Several methods have been proposed to construct Statistical Shape Model (SSM) to aim image analysis using computer in field Computer Aided Diagnosis (CAD), Computer Assisted Surgery (CAS), and other medical applications by providing a prior knowledge. The major challenge for liver shape model is a high variation in geometry such as size, shape and volume between livers. In this paper, we have presented a new technique for the automatic Multi-Scale Statistical Shape Model (MS-SSM) of three-dimensional (3-D) liver from volumetric segmented images data. The procedure included both building of Spherical Harmonics shape description and the Wavelet transform. Principal Component Analysis (PCA) was... 

A computational framework is presented, based on statistical shape modelling, for construction of race-specific organ models for internal radionuclide dosimetry and other nuclear-medicine applications. This approach was applied to the construction of a Japanese liver phantom, using the liver of the digital Zubal phantom as the template and 35 liver computed tomography (CT) scans of male Japanese individuals as a training set. The first step was the automated object-space registration (to align all the liver surfaces in one orientation), using a coherent-point-drift maximum-likelihood alignment algorithm, of each CT scan-derived manually contoured liver surface and the template Zubal liver...