A novel approach for shape modeling of the corpus callosum (cc) is introduced where the contours of the cc are extracted by image/volume segmentation, and a Bezier curve is used to connect the vertices of the sampled contours, generating a parametric polynomial representation. These polynomials are shown to maintain the characteristics of the original cc, thus are suitable for classification of populations. The Bernstein polynomials are used in fitting the Bezier curves. The coefficients of the Bernstein polynomials are shown to capture the geometric features of the cc, and are able to describe deformations. We use these coefficients, in conjunction with the Fourier Descriptors and other features, to discriminate between autistic and normal brains. The approach is tested on T1-weighted MRI scans of 16 normal and 22 autistic subjects and shows its ability to provide perfect classification, suggesting that the approach is worth investigating on a larger population with the hope of providing early identification and intervention of autism using neuroimaging.

One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Laplace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem.

This paper proposes a two-stage distributed method for the restoration problem using multi-agent system. The first stage gets a quick solution and implements it to restore as much loads as possible based on their priorities. The second stage will be applied to faults which expected to take longer time in order to maximize the restored loads (if there are loads still not energized from the first stage), minimize the power losses, and relieve the overloaded lines for more efficient and economical operation. Distribution system is represented as a multi-agent system with hierarchical architecture. Four types of agents are included, which are Bus Agents (BAGs) for monitoring and implementing the switching actions, DG Agents (DGAs) to represent DGs as supporting sources of power, Zone Agents (ZAGs) for negotiation and decision in the first-stage of restoration, and Global Agent (GAG) for decision in the second-stage of restoration. The proposed method is implemented in JADE and simulation results of 16-Bus system are included.

This paper presents a simple and efficient reconfiguration approach for balanced and unbalanced distribution networks with DG. The proposed approach that is based on load flow, begins with meshed networks by closing all tie switches. Branch currents were used as switching index to determine the open/closed states of the tie and sectionalizing switches with an objective of system losses reduction. The radial configuration was restored by opening the switch with smallest switching index in each loop. The proposed method has been tested on one balanced and two unbalanced systems with and without distributed generation, and compared with those reported in the literature

This paper presents a simple and efficient reconfiguration approach for balanced and unbalanced distribution networks with DG. The proposed approach that is based on load flow, begins with meshed networks by closing all tie switches. Branch currents were used as switching index to determine the open/closed states of the tie and sectionalizing switches with an objective of system losses reduction. The radial configuration was restored by opening the switch with smallest switching index in each loop. The proposed method has been tested on one balanced and two unbalanced systems with and without distributed generation, and compared with those reported in the literature

This paper presents a simple yet efficient service restoration algorithm for balanced and unbalanced radial distribution networks including Distributed Generators DG. The proposed algorithm that is based on load flow, begins with identifying the de-energized loads group due to fault isolation. All tie switches connecting this group with the rest of the network are the candidate switches for restoration. Branch currents from meshed network (i.e. closing all tie switches) were used as switching index to determine which one of these candidate tie switches should be closed for restoration. The restoration is carried out with objectives of maximizing the restored loads and minimizing the number of switching operations under line current limits, bus voltage limits and radial topology constraints. Each out-of-service group restored by closing the candidate tie switch with highest switching index. The proposed method has been tested on one balanced and two unbalanced systems with and without distributed generation, and compared with those reported in the literature.

This paper presents a simple and efficient multi-objective reconfiguration approach for balanced distribution networks. Two types of power quality indicators are minimized: (i) power losses and (ii) average system interruption frequency. The proposed approach starts with meshed networks by closing all tie switches. Three switching indices were defined for reconfiguration using branch failure rates and apparent power flow in lines. The radial configuration was restored by opening the switch with the highest switching index in each loop subjected to system operational constraints. The time varying nature of loads through using daily load profiles in each node of the system was considered. The results concluded the effectiveness of the fixed configuration compared to hourly reconfiguration in terms of energy losses and number of switching operations. The proposed method has been tested on two systems and compared with those reported in the literature

This paper presents a simple and efficient reconfiguration approach for balanced distribution networks with Distributed Generation (DG). The proposed approach starts with meshed networks by closing all tie switches. A switching index is defined for reconfiguration using apparent power flow in lines. The radial configuration was restored by opening the switch with the highest switching index in each loop subjected to system operational constraints. The time varying nature of loads through using daily load profiles in each node of the system was considered. The results concluded the effectiveness of the fixed configuration compared to hourly reconfiguration in terms of energy losses and number of switching operations. The proposed method has been tested on three systems with and without distributed generation, and compared with those reported in the literature.

Plug-in electric vehicles (PEVs) have uncertain penetration in electric grids due to uncertainties in charging and discharging patterns. This uncertainty together with various driving habits makes it difficult to accurately assess the effects on local distribution network. Extra electrical loads due uncoordinated charging of electric vehicles have different impacts on the local distribution grid. This paper proposes a method to evaluate the impacts of uncoordinated PEVs charging on the distribution grid during peak period. Two PEVs charging scenarios are studied, including normal and fast charging. The impact analysis is evaluated in terms of voltage violations, power losses and line loading, which is implemented on a real distribution system in Canada. The results of the analysis indicate that there are significant impacts on distribution networks due to PEVs charging, which limits the accommodation of desired penetration levels of PEVs.