This paper is aimed at sizing solar-wind-battery standalone microgrid for supplying irrigation and domestic loads in Toshka area, Toshka, Egypt. Not only the MG system components but also the interconnection cables and feeders are sized. Steady-state power flow through the MG system is analysed at varying sun irradiation and wind speed. Modeling of the MG components and their control of system voltages, currents and powers are investigated. Power flows during different MG operation conditions including absence of wind and sun as well as sudden disconnection of the load are studied

This paper is aimed at sizing solar-wind-battery standalone microgrid for supplying irrigation and domestic loads in Toshka area, Toshka, Egypt. Not only the MG system components but also the interconnection cables and feeders are sized. Steady-state power flow through the MG system is analysed at varying sun irradiation and wind speed. Modeling of the MG components and their control of system voltages, currents and powers are investigated. Power flows during different MG operation conditions including absence of wind and sun as well as sudden disconnection of the load are studied

This paper is aimed at sizing solar-wind-battery standalone microgrid for supplying irrigation and domestic loads in Toshka area, Toshka, Egypt. Not only the MG system components but also the interconnection cables and feeders are sized. Steady-state power flow through the MG system is analysed at varying sun irradiation and wind speed. Modeling of the MG components and their control of system voltages, currents and powers are investigated. Power flows during different MG operation conditions including absence of wind and sun as well as sudden disconnection of the load are studied

This paper is aimed at sizing solar-wind-battery standalone microgrid for supplying irrigation and domestic loads in Toshka area, Toshka, Egypt. Not only the MG system components but also the interconnection cables and feeders are sized. Steady-state power flow through the MG system is analysed at varying sun irradiation and wind speed. Modeling of the MG components and their control of system voltages, currents and powers are investigated. Power flows during different MG operation conditions including absence of wind and sun as well as sudden disconnection of the load are studied

This paper is aimed at sizing solar-wind-battery standalone microgrid for supplying irrigation and domestic loads in Toshka area, Toshka, Egypt. Not only the MG system components but also the interconnection cables and feeders are sized. Steady-state power flow through the MG system is analysed at varying sun irradiation and wind speed. Modeling of the MG components and their control of system voltages, currents and powers are investigated. Power flows during different MG operation conditions including absence of wind and sun as well as sudden disconnection of the load are studied

This paper examines parametric density estimation using a variable weighted sum of Gaussian kernels, where the weights may take positive and negative values. Various statistical properties of the estimator are studied as well as its extensions to multidimensional probability density estimation. Identification of the estimator parameters are computed by a modified EM algorithm and the number of kernels are estimated by information theoretic approach, using the Akiake Information Criterion (AIC). This paper provides empirical evaluation of the estimator with respect to window-based estimators and the classical linear combinations of Gaussian estimator that uses only positive weights, showing its robustness (in terms of accuracy and speed) for various applications in image and signal analysis and machine learning.

This paper examines feature-based nodule description for the purpose of nodule categorization (i.e., associating detected nodules into types) in low-dose CT scanning (LDCT). The multi-resolution Local Binary Pattern (LBP) and Distance Transform of the edge maps were used to generate the features that describe the texture and shape of common nodules and non-nodules. The LBP of the Distance Transform output were merged together to obtain shape and texture based feature descriptors of the nodules and non-nodules. These features were optimized using PCA and LDA, and the resultant sets were used for classifying/categorization into five categories: juxta-pleural, vascularized, pleural-tail, well-circumscribed and non-nodule. In the categorization process, the combinational shape and texture based feature descriptor resulted in an overall 12% enhancement in results when compared to using shape and texture features separately. These results are encouraging and good indicators for progress towards fully automated detection, segmentation, categorization (into types) and classification (into pathologies) of lung nodules from LDCT scans.

This paper describes a framework for simultaneous identification and tracking of moving targets in random media. Video and IR thermal sensors are used to obtain the target signature. Classical Kalman filtering methods are implemented on targets with unknown trajectories. Computer vision methodologies are proposed to design a smart interceptor which identifies the targets based on shape and thermal signatures. The paper also describes a platform for basic studies in tracking of targets using vision-guided robotics. The system enables multiple object tracking and recognition.

To diagnose the osteoporosis accurately, the bone mineral density (BMD) measurements of the vertebral bodies (VBs) are required. In this paper, we propose a new segmentation and registration method in order to assist the BMD measurements and fracture analysis (FA) accurately. In this experiment, image appearance and shape information of VBs are used. Our shape model is required to be registered to the testing image to avoid user interaction(s). Our proposed framework has four phases: i) the detection of vertebral body (VB) using the Matched filter, ii) initial segmentation using the intensity and spatial interaction models, iii) the registration of the shape prior and initially segmented image by matching a vector distance function (VDF), and iv) final segmentation using graph cuts which integrates intensity, spatial interaction and shape prior. Preliminary results show that our new algorithm is very promising and can solve many segmentation and registration problems.

This paper proposes a robust fully automated method for geometric co-registration, and an accurate statistical based change detection technique for multi-temporal high-resolution satellite imagery. The proposed algorithm is based on four main steps: First, multi-spectral scale-invariant feature transform (M-SIFT) is used to extract a set of correspondence points in a pair, or multiple pairs, of images that are taken at different times and under different circumstances, then Random Sample Consensus (RANSAC) is used to remove the outlier set. To insure an accurate matching, uniqueness constrain in the correspondence is assumed. Second, the resulting inliers matched points is used to register the given images. Third, changes in registered images are identified using statistical analysis of image differences. Finally, Markov-Gibbs Random Field (MGRF) is used to model the spatial-contextual information contained in the resulting change mask. Experiments with generated synthetic multiband images, and LANDSAT5 Images, confirm the validity of the proposed algorithm.