In this paper, we adopt the fuzzy actor–critic learning (FACL) and model predictive control (MPC) algorithms to solve pursuit–evasion game (PEG) of quadrotors. FACL is used for perception, decision-making, predicting trajectories agents, while MPC utilized address flight target optimization Specifically, based on information opponent, agent obtains its own strategy by using algorithm. Based reference input from algorithm, algorithm develop altitude, translation, attitude controllers...

Imbalanced data classification is an important research topic in real-world applications, like fault diagnosis aircraft manufacturing system. The over-sampling method often used to solve this problem. It generates samples according the distance between minority data. However, traditional may change original distribution, which harmful performance. In paper, we propose a new called Conditional Self-Attention Generative Adversarial Network with Differential Evolution (CSAGAN-DE) for imbalanced...

Extracting and visualizing of protein-protein interaction (PPI) from text literatures are a meaningful topic in protein science. It assists the identification interactions among proteins. There is lack tools to extract PPI, visualize classify results. We developed PPI search system, termed PPLook, which automatically extracts visualizes text. Given query name, PPLook can dataset for other proteins interacting with it by using keywords dictionary pattern-matching algorithm, display...

Semi-supervised learning is attracting increasing attention due to the fact that datasets of many domains lack enough labeled data. Variational Auto-Encoder (VAE), in particular, has demonstrated benefits semi-supervised learning. The majority existing VAEs utilize a classifier exploit label information, where parameters are introduced VAE. Given limited data, for classifiers may not be an optimal solution exploiting information. Therefore, this paper, we develop novel approach VAE without...

Industrial control systems (ICS) now usually connect to Wireless Sensor Networks and the Internet, exposing them security threats resulting from cyber-attacks. However, detecting such attacks is non-trivial task. The high-dimensional network data pose significant challenges on anomaly detection. In this work, we propose a flow processing method, which can make complex more standardized unified assist Then, generation method applied collect enough training data. We also evaluation for...

This paper, the fourth part of a series papers on arithmetic average (AA) density fusion approach and its application for target tracking, addresses intricate challenge distributed heterogeneous multisensor multitarget where each inter-connected sensor operates probability hypothesis (PHD) filter, multiple Bernoulli (MB) filter or labeled MB (LMB) they cooperate with other via information fusion. Earlier in this have proven that proper AA these filters is all exactly built averaging their...

In order to analyze the choice of optimal strategy cyber security attack and defense in unmanned aerial vehicles’ (UAVs) range, a game model-based UAV range risk assessment method is constructed. Through tree model, calculated. The model with incomplete information established Bayesian–Nash equilibrium mixed focus on mutual influence actions both sides dynamic change confrontation process. According calculation methods different benefits strategies selected offensive defensive game, are...

The liver is a key player for maintaining glucose homeostasis. Excessive hepatic production considered to be the onset of type 2 diabetes mellitus. primary function heme oxygenase-1 (HO1) catalyze degradation into biliverdin, ferrous iron, and carbon monoxide. Previous studies have demonstrated that by HO1 in results mitochondrial dysfunction drives insulin resistance. In this study, overexpressing hepatocytes mice, we showed promotes gluconeogenesis Foxo1-dependent manner. Importantly,...

Efficient continual learning of humans is enabled by interactions a series mechanisms and human memory system. Constructivism theory in education that proposes learners construct knowledge from their experiences, assimilation accommodation are key to this process. Also, research shows system represented as high-dimensional sparse vector. Motivated these, our paper, we propose feature method based on constructivisim We divide into two stages. In stage, model captures cannot be meta-knowledge...

Information of the subcellular localizations proteins is important because it can provide useful insights about their functions, as well how and in what kind cellular environments they interact with each other molecules. Facing explosion newly generated protein sequences post genomic era, we are challenged to develop an automated method for fast reliably annotating localizations. To tackle challenge, a novel sequence-segmented pseudo amino acid composition (PseAAC) introduced represent...

Multiple Model Estimation (MME) in hybrid systems, as a powerful approach to adaptive estimation, has been widely applied great deal of attention due its unique power handle problems with both structural and parametric uncertainties. In this paper, multiple well-known methods MME are represented the form Bayesian Networks (BN), which is used artificial intelligence. The discussion implies that may be special case BN.

As a representative evidential clustering algorithm, c-means (ECM) provides deeper insight into the data by allowing an object to belong not only single class, but also any subset of collection classes, which generalizes hard, fuzzy, possibilistic, and rough partitions. However, compared with other partition-based algorithms, ECM must estimate numerous additional parameters, thus insufficient or contaminated will have greater influence on its performance. To solve this problem, in study,...