Abstract
This work presents the 2nd Cross-Spectrum Iris/Periocular Recognition Competition (Cross-Eyed2017). The main goal of the competition is to promote and evaluate advances in cross-spectrum iris and periocular recognition. This second edition registered an increase in the participation numbers ranging from academia to industry: five teams submitted twelve methods for the periocular task and five for the iris task. The benchmark dataset is an enlarged version of the dual-spectrum database containing both iris and periocular images synchronously captured from a distance and within a realistic indoor environment. The evaluation was performed on an undisclosed test-set. Methodology, tested algorithms, and obtained results are reported in this paper identifying the remaining challenges in path forward.

Abstract

Abstract

Abstract
This paper presents a novel analytic method to uniquely solve inverse kinematics of 7 degrees-of-freedom manipulators while avoiding joint limits and singularities. Two auxiliary parameters are introduced to deal with the self-motion manifolds: the global configuration (GC), which specifies the branch of inverse kinematics solutions; and the arm angle (psi) that parametrizes the elbow redundancy within the specified branch. The relations between the joint angles and the arm angle are derived, in order to map the joint limits and singularities to arm angle values. Then, intervals of feasible arm angles for the specified target pose and global configuration are determined, taking joint limits and singularities into account. A simple metric is proposed to compute the elbow position according to the feasible intervals. When the arm angle is determined, the joint angles can be uniquely calculated from the position-based inverse kinematics algorithm. The presented method does not exhibit the disadvantages inherent to the use of the Jacobian matrix and can be implemented in real-time control systems. This novel algorithm is the first position-based inverse kinematics algorithm to solve both global and local manifolds, using a redundancy resolution strategy to avoid singularities and joint limits.

Abstract
Electric vehicle (EV) technology with a vehicle to grid (V2G) property is used in power systems to mitigate greenhouse gas emissions, reduce peak load of the distribution system, provide ancillary service, etc. In addition, demand response (DR) programs as an effective strategy can provide an opportunity for consumers to play a significant role in the planning and operation of a smart distribution company (SDISCO) by reducing or shifting their demand, especially during the on-peak period. In this paper, the optimal operation of a SDISCO is evaluated, including renewable energy resources (RERs) along with EV parking lots (PLs). RER and PL uncertainties and a suitable charging/discharging schedule of EVs are also considered. Furthermore, price-based DR programs and incentive-based DR programs are used for operational scheduling. To achieve this aim, a techno-economic formulation is developed in which the SDISCO acts as the owner of RERs and PLs. Moreover, DR programs are prioritized by using the technique for order preference by similarity to ideal solution method. In addition, a sensitivity analysis is carried out to investigate different factors that affect the operational scheduling of the SDISCO. The proposed model is tested on the IEEE 15-bus distribution system over a 24-h period, and the results prove the effectiveness of the model.

Abstract