Universal gates with wires in a row

We give some optimal size generating sets for the group generated by shifts and local permutations on the binary full shift. We show that a single generator, namely the fully asynchronous application of the elementary cellular automaton 57 (or, by symmetry, ECA 99), suffices in addition to the shift. In the terminology of logical gates, we have a single reversible gate whose shifts generate all (finitary) reversible gates on infinitely many binary-valued wires that lie in a row and cannot (a priori) be rearranged. We classify pairs of words u, v such that the gate swapping these two words, together with the shift and the bit flip, generates all local permutations. As a corollary, we obtain analogous results in the case where the wires are arranged on a cycle, confirming a conjecture of Macauley-McCammond-Mortveit and Vielhaber.

Characterizing Opportunity Power in the California Independent System Operator (CAISO) in Years 2015-2017

Studying the California Independent System Operator (CAISO) day-ahead and real-time markets for the period January 2015 to December 2017, we characterize the growth of curtailment and negative-priced power from renewable generators. Results show that renewable curtailment is growing rapidly, tripling to over 400 GWh from 2015-2018. Negative-priced renewable power is larger and also growing rapidly, reaching 1.5 TWh in 2017 for 40% CAGR.Resource-hours for negative pricing grew nearly 3-fold from 80,006 to 217,728 hours, with the highest single generator reaching 955 hours in 2017 or 33% of the daylight solar hours. Spatially, the quantity of negative-priced power is concentrated at a few dozen renewable generators, reaching peaks of 170GWh at the largest generator. We also consider an averaged-price model (NetPrice) that smooths over fluctuations to estimate the usable quantities of low-priced power. Results for NetPrice show a much larger quantity of low-priced power available than with either negative-pricing or curtailment alone. Overall, these results suggest both that opportunity power is a substantial and growing resource and a number of opportunities to exploit it.

Many-to-Many Symbolic Multi-Track Music Genre Transfer

This paper shows the feasibility of a variant of the Generative Adversarial Network (GAN), called Star GAN, for music genre transfer. This method is noteworthy in that it simultaneously learns many-to-many mappings across different attribute domains using a single generator network. A similar architecture to research in MuseGAN and CycleGAN is applied. Also, as in MGTGAN, Desert Camel MIDI dataset is use for training and testing.

Generative multi-adversarial network for striking the right balance in abdominal image segmentation

Purpose The identification of abnormalities that are relatively rare within otherwise normal anatomy is a major challenge for deep learning in the semantic segmentation of medical images. The small number of samples of the minority classes in the training data makes the learning of optimal classification challenging, while the more frequently occurring samples of the majority class hamper the generalization of the classification boundary between infrequently occurring target objects and classes. In this paper, we developed a novel generative multi-adversarial network, called Ensemble-GAN, for mitigating this class imbalance problem in the semantic segmentation of abdominal images. Method The Ensemble-GAN framework is composed of a single-generator and a multi-discriminator variant for handling the class imbalance problem to provide a better generalization than existing approaches. The ensemble model aggregates the estimates of multiple models by training from different initializations and losses from various subsets of the training data. The single generator network analyzes the input image as a condition to predict a corresponding semantic segmentation image by use of feedback from the ensemble of discriminator networks. To evaluate the framework, we trained our framework on two public datasets, with different imbalance ratios and imaging modalities: the Chaos 2019 and the LiTS 2017. Result In terms of the F1 score, the accuracies of the semantic segmentation of healthy spleen, liver, and left and right kidneys were 0.93, 0.96, 0.90 and 0.94, respectively. The overall F1 scores for simultaneous segmentation of the lesions and liver were 0.83 and 0.94, respectively. Conclusion The proposed Ensemble-GAN framework demonstrated outstanding performance in the semantic segmentation of medical images in comparison with other approaches on popular abdominal imaging benchmarks. The Ensemble-GAN has the potential to segment abdominal images more accurately than human experts.

Investigating the faulted performance of warship power systems with integrated energy storage

The need to integrate energy storage systems (ESS) with warship power systems to meet future dynamic loads such as high power electric weapons is apparent. This opens up challenges with design integration of ESS with power systems and operational aspects such as steady-state, transient and faulted performance. This paper describes the integration of ESS with a candidate power system as a case study as part of an ongoing timedomain simulation investigation at University College London. The paper describes the models and power management structure of the simulation testbed, that comprises battery based ESS and diesel generators in a hybrid electric power and propulsion system. The results of two scenarios are presented, the first verifies power sharing between a diesel generator and ESS during load levelling under single generator operation, the second illustrates the ability of the ESS to provide ride through power during a generator fault on the main distribution bus. The conclusions suggest that under voltage in the candidate system outside of acceptable limits occurs during fault ride through when in single generator operation.

Performance improvement of a STATCOM using fuzzy controller for isolated generator

Purpose This paper aims to demonstrate the efficacy of fuzzy logic controller (FLC) over proportional integral (PI) and sliding mode controller (SMC) for maintaining flat voltage profile at the load bus of a single-generator-based micro-grid system using STATCOM. Design/methodology/approach A STATCOM is used to improve the voltage profile of the load bus. The performance of the STATCOM is evaluated by using three different controllers: PI controllers, FLCs and SMCs. The performance comparison of the controllers is done with different dc bus voltages, different load bus voltage references, various loads such as R-L loads and dynamic loads. Findings A comparative analysis is done between the performances of the three different controllers. The comparative study culminates that FLC is found to be superior than the other proposed controllers. SMC is a close competitor of fuzzy controller. Originality/value Design of fuzzy logic and SMCs for a STATCOM implemented in a single-generator-based micro-grid system is applied.