The generative adversarial network (GAN) is usually built from the centralized, independent identically distributed (i.i.d.) training data to generate realistic-like instances. In real-world applications, however, may be over multiple clients and hard gathered due bandwidth, departmental coordination, or storage concerns. Although existing works, such as federated learning GAN (FL-GAN), adopt different strategies train models, there are still limitations when in a non-i.i.d. manner. These...

Imbalanced data cause deep neural networks to output biased results, and it becomes more serious when facing extremely imbalanced regarding the outliers with tiny size (the ratio of outlier image is around 0.05%). Many argumentation models are proposed supplement alleviate results. However, existing augmentation cannot synthesize outliers, which make generated unavailable. In this article, we propose a new model named generative adversarial nets (EID-GANs) address problem. First, design...

Content understanding is a crucial issue for website adaptation. In this paper we present Function-based Object Model (FOM) that attempts to understand authors’ intention by identifying function instead of semantic understanding. Every in serves certain functions (Basic and Specific Function) which reflect towards the purpose an Object. Based on consideration have proposed FOM model includes two complementary parts: Basic based basic functional properties category An automatic approach...

Limited data usually cause deep neural networks to hold poor performance after training, and many generative models are proposed synthesize improve the of models. However, existing ignore capturing small defect details (e.g., features locations), resulting in that most cannot augment Defect Location Sensitive Data (DLS data) which ratio object size image is 20%) locations defects only on object. In this paper, we propose a new augmentation model, named GAN (DLS-GAN), address DLS problem....

Abstract Large-scale atomic/molecular massively parallel simulator (LAMMPS) is a prevalent software package employed for molecular dynamics simulations, enabling the study of materials at atomic and scale. Its performance paramount in numerous industrial applications, driving need ongoing enhancements simulation speed efficiency. Previous works heavily rely on hardware accelerators, which lead to limited high costs. To address this, this work optimizes message passing interface (MPI) memory...

In this study, a chaos theory-based characterization method is proposed to address the nonlinear behavior of acoustic emission (AE) signals during startup and shutdown phases dry gas seals. AE were collected through controlled experiment at three distinct phases: startup, normal operation, shutdown. Analysis these identified transition speed 350 r/min between mixed lubrication (ML) hydrodynamic (HL) states. The maximum Lyapunov exponent, correlation dimension, K-entropy, attractors...

Traditional pattern growth-based approaches for sequential mining derive length-(k+1) patterns based on the projected databases of length-k recursively. At each level recursion, they unidirectionally grow length detected by one along suffix patterns, which needs k levels recursion to find a pattern. In this paper, novel data structure, UpDown Directed Acyclic Graph (UDDAG), is invented efficient mining. UDDAG allows bidirectional growth both ends patterns. Thus, can be in [log <sub...

Liquid fraud has plagued people with huge health risks. detection can help to reduce the risk of liquid hazards. However, existing systems that use biochemical tools or radio frequency signals for sensing are either expensive, intrusive, inconvenient public use. In this article, we propose HearLiquid, a low-cost and nonintrusive system using commodity acoustic devices. Our insight comes from fact impedance different liquids results in distinct absorption signal across frequencies when it...

A military-based distributed interactive simulation (DIS) such as ModSAF has been used for many years. Several problems of the DIS-based to support a large and heterogeneous virtual environments have discovered. To solve these problems, we propose an architectural multi-agent-based framework with 3D visualization using inexpensive game simulators. several software agents are interoperability between military nodes unreal tournament agent is reduce DIS traffic efficiently utilize network...

Mode collapse has been a persisting challenge in generative adversarial networks (GANs), and it directly affects the applications of GAN many domains. Existing works that attempt to solve this problem have some serious limitations: models using optimal transport (OT) strategies (e.g., Wasserstein distance) lead vanishing or exploding gradients; increasing number generators can cause several focusing on same mode; approaches modify loss also do not satisfactorily resolve mode collapse. In...

Color-tone represents the prominent color of an image, and training generative adversarial nets (GAN) to change color-tones generated images is desirable in many applications. Advances such as HistoGAN can manipulate with a target image. Yet, there are challenges. Kullback–Leibler (KL) divergence adopted by might bring color-tone mismatching, because it possible provide infinite score generator. Moreover, only relying on distribution estimation also produces lower fidelity HistoGAN. To...

The effect of laser cladding on the surface microstructure and corrosion properties coated/uncoated specimens were investigated. Fe-based alloy coating was produced 35CrMo steel by cladding. phase composition, microstructure, interface element distribution, microhardness resistance measured. results show that layer is mainly composed α-Fe phases, presents a gradient good metallurgical bond formed at boundary with substrate. Microhardness profiles average about 2.1 times higher than uncoated...

Link structure evaluation and improvement is a significant hard problem for Hypertext system. In this paper novel approach evaluating improving website link based on User Visiting Patterns instead of complex semantic analysis proposed. By optimizing re-evaluating the to increase Average Connectivity, our can effectively improve structure. Experiments have shown satisfactory results.

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part computer vision applications. As kind algorithms, fuzzy C-means clustering effective and concise algorithm. However, drawback FCM that it sensitive to noise. To solve problem, this paper designs a novel C-mean algorithm based on multi-objective optimization. We add parameter λ distance measurement formula improve The can adjust weights pixel local information. In algorithm,...

The performance of a depth-first frequent itemset (FI) miming algorithm is closely related to the total number recursions. In previous approaches this mainly decided by FIs, which results in poor when large FIs are involved. To solve problem, three-strategy adaptive algorithm, bitmap support counting (BISC), presented. core strategy, BISC1, used innermost steps recursion. For database D with only s items, approach need up levels recursions detect all (up 2 ). BISC1 completely replaces these...

Autonomous, arbitrary pattern formation is one of the most critical applications in multi-robot systems, where robots are required to form into circles, lines, and meshes or any other desired configuration. This task important military applications, search rescue operations, visual inspection infrastructure equipment tasks name a few. Most existing works very rigid, only able certain shapes, slight target changes can cause failure predefined pattern-specific rules trigger algorithm redesign....

Recently years, research in multi-robot systems has attracted increasingly attentions. One important topic is to design programming models that can facilitate the developers programme large-scale systems. However, existing works fail manage robots perform tasks with real-time requirements. To address this issue, we propose a new model called RMR (Real-time Multi-Robot). logic support. On basis of paradigm, allows code for system be written from global perspective, rather than managing large...

To reduce the low-order vibrations of high-voltage transmission towers in response to strong winds, a tuned mass damper (TMD) that uses eddy current damping (ECD) with omnidirectional function (ECD-TMD) is proposed here. Compared previous similar devices, outstanding advantage ECD-TMD lies its use non-contact ECD, structural simplicity, lack internal friction, ability sense micro-vibrations, and asymmetric cantilever pendulum structure enables vibration suppression. Aero-elastic model wind...