Development of a real-time latching control algorithm based on wave force prediction

Optimal wave energy control is noncausal as the control command is optimized based on incoming wave force. Therefore, implementation of wave energy control requires forecasting of future wave force. A real-time latching control algorithm based on short-term wave force prediction is developed in this study to tackle such noncausality. The future wave forces are forecasted using a gray model. The receding horizon strategy is used to optimize the control command online, over the prediction horizon interval. Based on the predicted wave forces, the power extraction is maximized by locking and releasing the buoy alternately according to the optimized control command. Simulation results show that the power extraction is increased substantially with implementation of the developed real-time latching control algorithm, even if the future wave forces are predicted. Effects of prediction length and prediction error on the energy conversion are examined. It is found that more wave energy is harvested when a long prediction length is employed while prediction error decreases the control efficiency. The extreme load of power takeoff system increases when the wave energy control is implemented although its travel distance is hardly varied

Distance Based Image Classification: A solution to generative classification's conundrum?

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory's hierarchical generative process and non-semantic factors by an instance specific noise term. We use the model to develop a classification scheme which suppresses the impact of noise while preserving semantic cues. The result is a surprisingly accurate generative classifier, that takes the form of a modified nearest-neighbor algorithm; we term it distance classification. Unlike discriminative classifiers, a distance classifier: defines semantics by what-they-are; is amenable to incremental updates; and scales well with the number of classes.Comment: accepted by IJC

Individualized analysis reveals CpG sites with methylation aberrations in almost all lung adenocarcinoma tissues

Additional file 1: Table S1. Stable and reversal CpG site pairs identified in the samples measured by two platforms

A kognitív készségek rendszere és fejlődése

Additional file 7: Figure S1. The KEGG pathways separately enriched with hypermethylated (a) and hypomethylated (b) genes in at least 10% of the 539 TCGA lung adenocarcinoma samples

Two-step multi-objective management of hybrid energy storage system in all-electric ship microgrids

The all-electric ship (AES) usually employs battery energy storage systems (ESSs) in the shipboard microgrid. However, the battery-only storage usually experiences frequent deep discharging or charging to meet the sudden load variations in a voyage, which may lead to significant degradation of battery lifetime. This paper, hybridizes two types of ESSs and proposes a two-step multi-objective optimization method for hybrid ESS (HESS) management. The first step regulates the HESS with the onboard diesel generators to simultaneously optimize both the economic and environmental objectives, and the second step is to split the active power of HESS into two individual ESSs for minimizing the battery cycle degradation. The first step is formulated as a bi-level optimization model through constraint decomposition. Then, a normal boundary intersection method combining with the column-and-constraint generation algorithm is developed to solve the proposed model. Extensive simulations demonstrate that the HESS can effectively resolve the power-density shortage of the battery-only system, and its integration into AES is able to extend the battery lifetime and improve both the economic and environmental indices.The authors would like to thank the Key Laboratory of Maritime Intelligent Equipment and System, Ministry of Education, Shanghai Jiao tong University, for providing valuable data for the research

Analysis of characteristics of foreign unmanned surface vehicle swarm combat application and proposed countermeasures

As an important component of future naval campaigns, the unmanned surface vehicle (USV) swarm is an important direction for the development of unmanned maritime assets in various counties. This paper first summarizes the current strategic planning and application status of USV swarms in foreign countries, then dissects the research progress of USV swarms in such aspects as cluster communication, battlefield situation awareness and cooperative task assignment. At the same time, the typical combat operation modes and main benefits of USV swarms are analyzed and assessed. Finally, current challenges that need to be tackled in USV swarm combat operation are analyzed, and countermeasures that can be taken against the technological development of USV swarm combat operation are predicted

Distance based image classification: A solution to generative classification’s conundrum?

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory's hierarchical generative process and non-semantic factors by an instance specific noise term. We use the model to develop a classification scheme which suppresses the impact of noise while preserving semantic cues. The result is a surprisingly accurate generative classifier, that takes the form of a modified nearest-neighbor algorithm; we term it distance classification. Unlike discriminative classifiers, a distance classifier: defines semantics by what-they-are; is amenable to incremental updates; and scales well with the number of classes.Comment: accepted by IJC

AGEs Decrease Insulin Synthesis in Pancreatic b-Cell by Repressing Pdx-1 Protein Expression at the Post- Translational Level

Advanced glycation end products (AGEs) have been implicated in diverse pathological settings of many diabetic complications, and the possible mechanisms have been widely reported. However, the relationship between AGEs and pancreatic b-cell dysfunction is still poorly understood. Recent studies have shown that AGEs can impair b-cell function by inducing apoptosis or decreasing insulin secretion. Our previous research revealed that AGEs could significantly downregulate insulin transcription and reduce b-cell glucose-stimulated insulin secretion (GSIS). Here, we investigated the possible mechanisms underlying AGE-related suppression of insulin synthesis. In the rat pancreatic b-cell line INS-1, we found that AGEs induced dephosphorylation of Foxo1 and increased its accumulation in the nucleus. The translocation of Foxo1 subsequently inhibited pancreatic-duodenal homeobox factor-1 (Pdx-1) levels in both nuclear and cytoplasmic compartments. We observed that with AGEs treatment, Pdx-1 protein levels decreased after 4 h, but there was no change in the Pdx-1 mRNA level or promoter activity at the same time point; this demonstrated that the decrease in Pdx-1 expression was not regulated at the transcriptional level. In our study, the decrease in Pdx-1 protein level was related to its reduced stability, overexpression of DN-Foxo1 could partially reverse the inhibition of Pdx-1 expression. Pretreatment with AGEs receptor (RAGE) antibody also prevented the AGE-induced diminution of Pdx-1 protein and insulin mRNA expression. In summary, AGEs induced nuclear accumulation of Foxo1; this in turn reduced Pdx-1 expression by decreasing its protei