Sharif Digital Repository

Monthly mean satellite derived Chl-a, aerosols, wind, SST, PAR, and turbidity datasets were used to investigate the possible factors regulating phytoplankton variability in the Persian Gulf. The spatial correlation analysis revealed two distinct regions of SST and PAR, and a relatively uniform spatial correlation pattern of the other parameters. The cross correlation between aeolian dusts and Chl-a was significantly positive with 1–3 months offset. The pattern of spatial correlation between Chl-a and SST was positive in the shallow regions without time lag, and was negative with time offset of 3–5 months in deeper regions. The cross correlation between Chl-a and north-ward winds were... 

Background and Objectives: Melanoma is a dangerous kind of skin disease with a high death rate, and its prevalence has increased rapidly in recent years. Diagnosis of melanoma in a primary phase can be helpful for its cure. Due to costs for dermatology, we need an automatic system to diagnose melanoma through lesion images. Methods: Here, we propose a sparse representation based method for segmentation and classification of lesion images. The main idea of our framework is based on a kernel sparse representation, which produces discriminative sparse codes to represent features in a high-dimensional feature space. Our novel formulation for discriminative kernel sparse coding jointly learns a... 

Melanoma is the deadliest type of human skin cancer. However, it is curable if diagnosed in an early stage. Recently, computer aided diagnosis (CAD) systems have drawn much interests. Segmentation is a crucial step of a CAD system. There are different types of skin lesions having high similarities in terms of color, shape, size and appearance. Most available works focus on a binary segmentation. Due to the huge variety of skin lesions and high similarities between different types of lesions, multi-class segmentation is still a challenging task. Here, we propose a method based on joint dictionary learning for multi-class segmentation of dermoscopic images. The key idea is based on combining... 

Spatial and temporal patterns of climatological seasonality, interannual variability, and phytoplankton phenology were estimated using satellite-derived ocean color chlorophyll-a data (Chl-a) 1998 to 2020 in the Persian Gulf from. Biogeography of phytoplankton seasonal and interannual climatology was determined using k-means multivariate clustering analysis applied on the Chl-a time-series data. As a result, two distinct regions were identified: one in the deep north and middle area (DZC) with a minimum value of Chl-a in April–July (0.62–0.76 mg m−3) and maximum in December–February (1.07–1.59 mg m−3), and the other in the north–west coastal areas and along the southwest-southern area (SZC)... 

UMTS is the European standard of third generation of mobile communications and its air interface is called WCDMA. In this paper a simple WCDMA system in downlink and in FDD mode is simulated and results is presented. The simulation that is an execution of apart of physical layer functions as layer 1, is including data modulation, spreading multipath channel, AWGN noise, data demodulation, despreading and Rake receiver. It is obvious that transmission methods of data correspond with WCDMA standard. In the other word, frames and slots structure, data symbols setting and requiring parameters follow the defined standards  

In CHES 2008 a generic side-channel distinguisher, Mutual Information, has been introduced to be independent of the relation between measurements and leakages as well as between leakages and data processed. Assuming a Gaussian model for the side-channel leakages, correlation power analysis (CPA) is capable of revealing the secrets efficiently. The goal of this paper is to compare mutual information analysis (MIA) and CPA when leakage of the target device fits into a Gaussian assumption. We first theoretically examine why MIA can reveal the correct key guess amongst other hypotheses, and then compare it with CPA proofs. As our theoretical comparison confirms and shown recently in ACNS 2009... 

UMTS is the European standard of the third generation of mobile communications and its air interface is called WCDMA. In this paper a simple WCDMA system in downlink and FDD mode is simulated and results are presented. The simulation that is an execution, apart from physical layer functions as layer 1, includes data modulation, spreading multipath channel, AWGN noise, data demodulation, despreading and Rake receiver. It is obvious that transmission methods of data correspond to WCDMA standards. In other words, frames and slots structure, data symbols setting and required parameters follow the defined standards. © 2002 St. Petersburg State Poly Univ  

Here we introduce a phase-shifting digital holography-based method to determine the temperature profile around an irradiated (sub-)micron spherical bead. The method utilizes a Mach-Zehnder interferometer implemented into an open setup microscope. The results of irradiated gold spheres with diameter of 400 nm and also silver-coated micron-sized silica beads embedded in silicone oil are presented. We show that the applied method is able to accurately determine the surface temperature with accuracy of 1 °C. Our experimental results perfectly confirm the theoretical prediction of temperature profile around the irradiated bead  

In this study, the existence of a sinusoidal splitter on the formation and distribution of hydrogen and air co-jets are investigated in a dual-combustion ramjet engine. The main scope of this research is to analyze the comprehensive flow structure and flame features directly downstream of the sinusoidal splitter. In this work, shockwave/shear-layer interactions behind the sinusoidal splitter are thoroughly studied through a computational fluid dynamic approach. Two different splitter profiles are compared with a simple splitter to demonstrate the main effects of multi shock wave interactions on fuel distribution and penetrations. To simulate co-air jet, Reynolds Average Navier-Stocks... 

In this study, the artificial neural network (ANN) was used for the prediction of WDT. The inputs to network are molar mass and pressure, and the output is WDT at each input. A two-layer network with different hidden neurons and different learning algorithms such as LM, SCG, GDA and BR were examined. The network with 16 hidden neurons and Levenberg-Marquardt (LM) train function showed the best results in comparison with the other networks. Also, the predicted results of this network were compared with the thermodynamic models and better accordance with experimental data for ANN was concluded  

In this study, 40% CaO/γ-Al2O3 catalyst was used for biodiesel production from corn oil. A transesterification reaction was done for 5h at a temperature of 65°C in the presence of corn oil, methanol (methanol to oil molar ratio of 12:1), and CaO/γ-Al2O3 catalyst (0.06g/g (6wt%)). Catalyst used in this study was synthesized using the sol-gel method. In this method, two parameters of gelation temperature and nitric acid concentration were used as variables in the catalyst synthesis step, and experiments were designed using central composite design (CCD). The results indicate that the optimal point is achieved at a gelation temperature of 70°C and... 

Estimating the depth of anesthesia (DOA) is still a challenging area in anesthesia research. The objective of this study was to design a fuzzy rule based system which integrates electroencephalogram (EEG) features to quantitatively estimate the DOA. The proposed method is based on the analysis of single-channel EEG using frequency and time domain features as well as Shannon entropy measure. The fuzzy classifier is trained with features obtained from four subsets of data comprising well-defined anesthesia states: awake, moderate, general anesthesia, and isoelectric. The classifier extracts efficient fuzzy if-then rules and the DOA index is derived between 100 (full awake) to 0 (isoelectric)... 

Estimating the depth of anesthesia (DOA) is still a challenging area in anesthesia research. The objective of this study was to design a fuzzy rule based system which integrates electroencephalogram (EEG) features to quantitatively estimate the DOA. The proposed method is based on the analysis of single-channel EEG using frequency and time domain methods. A clinical study was conducted on 22 patients to construct subsets of reference data corresponding to four well-defined anesthetic states: awake, moderate anesthesia, surgical anesthesia and isoelectric. Statistical analysis of features was used to design input membership functions (MFs). The input space was partitioned with respect to the... 

Excessive energy consumption is one of the serious problems of large cities in Iran. In order to avoid unreasonable growth in energy use as well as conservation of natural resources, more attention should be paid to energy consumption patterns in metropolitan cities. Accordingly, the current study aims at analyzing energy demand and its related pollutants in the household sector in Tehran Metropolitan. The study includes a discussion of past trends and future scenarios to reduce greenhouse gas emissions in this sector. Using LEAP software and according to Iran's long-term development policies, energy demand and its greenhouse gas emissions were evaluated based on a baseline scenario within a... 

Transesterification reaction was performed in the presence of soybean oil, methanol, and Demineralized water plant sedimentation catalyst at 60°C for 8 h in this study. Central composite design method was used to study the effect of catalyst concentration and methanol to oil molar ratio on purity and yield of produced biodiesel. The results showed catalyst concentration of 9.08 wt% and methanol to oil molar ratio of 22.49 as the optimum condition in which the values of purity and yield of the produced biodiesel in the second-order models were 99.89% and 81.83%, respectively. Experiments are in good agreement with the mentioned values as corresponded values are 99.95% and 86.68%,... 

Segmentation of the Left ventricle (LV) is a crucial step for quantitative measurements such as area, volume, and ejection fraction. However, the automatic LV segmentation in 2D echocardiographic images is a challenging task due to ill-defined borders, and operator dependence issues (insufficient reproducibility). U-net, which is a well-known architecture in medical image segmentation, addressed this problem through an encoder-decoder path. Despite outstanding overall performance, U-net ignores the contribution of all semantic strengths in the segmentation procedure. In the present study, we have proposed a novel architecture to tackle this drawback. Feature maps in all levels of the decoder...