Abstract
With the increase in the number of electric vehicles (EVs), there might be substantial problems due to the charging transactions in the power system and the balancing between supply and demand sides can be provided in the modern power system by considering EVs as a flexible load. EVs cannot directly participate in buying and selling energy from/to the electricity market because of their relatively low energy and power capacities. In this manner, considering that EVs are generally parked during the day, an EV parking lot (EVPL) can offer economic charging opportunities to EV owners as multiple EVPLs can offer/bid for the buying/selling from/to the electricity market through an EVPL aggregator (EVPLA). In this study, a model in which the EVPLA offers/bids for the day-ahead (DA) and secondary reserve market in order to minimize the total cost is propounded. Furthermore, uncertainties related to the EV owners' behavior and market prices are handled by considering scenarios with real data in a stochastic manner. In addition, the EVPLA also takes into account the comfort of the EV owners when carrying out this operation. The comfort of EV owners as an essential issue similar to serving EV owners more economically is achieved by sustaining the minimum desired charge level by EV owners at the departure time. The results consist of a set of case studies to reveal the effectiveness of the proposed model considering the pricing conditions in Turkey, Finland, and USA-PJM DA and reserve markets. According to the results of the study, it is observed that an EV aggregator participating in DA and RE markets can make a significant profit for the three market conditions. An important result is also that the profit by the participation in reserve markets increases significantly compared to solely DA market participation.

Abstract
The stability and monitoring of AC microgrids (AC MG) are greatly influenced by gathering sufficient and precise information. Since installing several sensors on AC MGs is costly and increases AC MG ripple, integrating a minimum number of cost-effective sensors is preferred. In this paper, a joint-estimating advanced augmented-Kalman filter (KF) to estimate the current of the AC MG and unknown time-varying loads from the noisy measurement of the AC bus voltage is developed. The proposed approach also provides smooth and noise-less information from the measured voltage. The presented method has less complexity to handle and as a robust approach, it would be capable of dealing with uncertainties due to the load, which can be linear, nonlinear, or unbalanced. The joint-estimating augmented-KF outputs can be then utilized in the monitoring, fault detection, and control design purposes. The developed framework is tested on an AC MG supplying time-varying load and numerical results verify the applicability and accuracy of the developed technique to estimate the load and filter currents.

Abstract
Software Operational Profile (SOP) is a software specification based on how users use the software. This specification corresponds to a quantitative representation of software that identifies the most used software parts. As software reliability depends on the context in which users operate the software, the SOP is used in software reliability engineering. However, there are evidences of a misalignment between the software tested parts and SOP. Therefore, this paper investigates a possible misalignment between SOP and the tested software parts to obtain, based on experimental data, more evidence of this misalignment. We performed an exploratory study composed of four activities to verify: a) whether there are significant variations in how users operate the software; b) whether there is a misalignment between SOP and the tested software parts; c) if failures occur in untested SOP parts in case of misalignment; d) in case of misalignment between SOP and untested software parts, whether a test strategy based on the amplification of the existent test set with additional test data generated automatically, can contribute to reduce the misalignment. We collected data form four software while users were operating them. We analyzed this collected data in an attempt to reach the goals of this work. To evaluate the originality of this research, we performed a Literature Systematic Review (SLR) and presented its conclusions. The obtained results evidence that there are significant variations in how users operate the software and also that there is a misalignment between SOP and the tested software parts when we evaluated the four software mentioned above. There are also indications of the occurrence of failures in the untested SOP parts. Although the test strategy mentioned above has reduced the possible misalignment, the test strategy is not enough to avoid it, thus denoting the need of specifics test strategies using SOP as a test criterion. These results indicate that SOP becomes relevant not only to software reliability engineering but also to contribute to testing activities, regardless of the adopted strategy.

Abstract
Breast cancer imaging research has seen continuous progress throughout the years. Innovative visualization tools and easier planning techniques are being developed. Image segmentation methodologies generally have best results when applied to specific types of exams or sequences, as their features enhance and expedite those approaches. Particular methods have more purchase with the segmentation of particular structures. This is the case with diverse breast structures and the respective lesions on MRI sequences, over T1w and Dyn. The present study presents a methodology to tackle an unapproached task. We aim to facilitate the volumetric alignment of data retrieved from T1w and Dyn sequences, leveraging breast surface segmentation and registration. The proposed method revolves around Canny edge detection and mending potential holes on the surface, in order to accurately reproduce the breast shape. The contour is refined with a Level-set approach and the surfaces are aligned together using a restriction of the Iterative Closest Point (ICP) method. This could easily be applied to other paired same-time, volumetric sequences. The process seems to have promising results as average two-dimensional contour distances are at sub-voxel resolution and visual results seem well within range for the valid transference of other segmented or annotated structures.

Abstract
Electric vehicles (EVs) are developing due to concerns over global warming and the major role of the transportation sector in emissions. EVs can also flatten the power curve and increase the reliability of power grids when renewable energy sources are used. Despite of these benefits, EVs impose new loads on distribution networks. Simultaneous charging of EVs, especially at high penetration levels, can create new load peaks in the power curves as well as overloading transformers, shortening their service life. In actual applications, most electric cars are single-phase loads that need to be charged from household or commercial outlets. In this paper, an optimization method is presented to coordinate the dynamic charge operation of single-phase EVs in an unbalanced three-phase distribution network. In the proposed method, the main goal of charging management is to minimize the total cost, which considers both network security constraints and electric vehicle constraints. The proposed method is tested on a sample distribution network and the numerical results prove the effectiveness of the method.

Abstract
This paper models the role of electricity tariffs on the long-term adoption of photovoltaic and storage technologies as well as the consequent impact on the distribution grid. An adoption model that captures the economic rationality of tariff-driven investments and considers the stochastic nature of individual consumers' decisions is proposed. This model is then combined with a probabilistic load flow to evaluate the long-term impacts of the adoption on the voltage profiles of the distribution grid. To illustrate the methodology, different components of the electricity tariffs, including solar compensation mechanisms and time differentiation of Time-of-Use (ToU) rates, are evaluated, using a case study involving a section of a medium-voltage network with 118 nodes.