The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Extending from limited domain to a new domain is crucial for Natural Language Generation in Dialogue, especially when there are sufficient annotated data in the source domain, but there is little labeled data in the target domain. This paper studies the performance and domain adaptation of two different Neural Network Language Generators in Spoken Dialogue Systems: a gating-based Recurrent Neural...
Undeniably, the focus of several works revolved around finding a process of unification to follow along the modeling of mechatronic systems. This paper is a part of a general research designed to apply topology for the modeling of complex mechatronic systems. Notably, a topological approach to model a Wind Turbine is adopted in this study. The Wind Turbine model under study is modeled using a topological...
In order to overcome the limitation of transient stability analysis (TSA) which is unable to describe the non-fundamental or asymmetry characteristics of AC/DC power systems, electromagnetic transient modeling method with high efficiency is urgent for large scale power systems. According to actual HVDC converters, this paper first simplifies the valve group model as well as the transmission line model...
In this paper, we explore the use of recent conditional generative adversarial network framework for image to image translation applied to the domain of heterogeneous face sketch synthesis. Since the inception of the adversarial framework in 2014, great success has been noted with several variants till date. Further, we introduce a new dataset for composite sketch images. In particular we explore...
Random numbers are useful for a variety of purposes. A discrete representation of them can be obtained from pseudorandom numbers generators. This paper presents PseudoRandom, a prototype of a hypermedial educational material, which approaches the subject from a multidisciplinary and constructivist perspective.
In this paper, we propose a way of synthesizing realistic images directly with natural language description, which has many useful applications, e.g. intelligent image manipulation. We attempt to accomplish such synthesis: given a source image and a target text description, our model synthesizes images to meet two requirements: 1) being realistic while matching the target text description; 2) maintaining...
Video image dataset is playing an essential role in design and evaluation of traffic vision methods. However, there is a longstanding difficulty that manually collecting and annotating large-scale diversified dataset from real scenes is time-consuming and prone to error. In 2016, we proposed the parallel vision methodology to tackle the issues of conventional vision computing approach in data collection,...
We study unsupervised learning by developing a generative model built from progressively learned deep convolutional neural networks. The resulting generator is additionally a discriminator, capable of "introspection" in a sense — being able to self-evaluate the difference between its generated samples and the given training data. Through repeated discriminative learning, desirable properties...
This paper presents the computer simulation of a switched reluctance machine (SRM) operating as a generator proposing an alternative for the representation of the inductances of the machine coils and their respective rates of variation. The simulation results show the reliability of the proposed model, especially in comparison with other models of machine inductance representation. The validation...
As the memory and storage hierarchy get deeper and more complex, it is important to have new benchmarks and evaluation tools that allow us to explore the emerging middleware solutions to use this hierarchy. Skel is a tool aimed at automating and refining this process of studying HPC I/O performance. It works by generating application I/O kernel/benchmarks as determined by a domain-specific model....
This paper will present new developments in the identification of large scale network connected systems in the framework of subspace methods. Special structures based on Kronecker products will be proposed that give rise to bilinear structured low dimensional optimization problem. The problems of interest for these large scale problems are imaging systems where images are blurred by perturbations...
This paper presents the construction the time-voltage signal output model of the combination wave generator using neural networks. The discussed model of surge was developed using feedforward neural networks with one hidden layer with four neurons. The results of the comparative tests show the high efficiency of Leveneberg-Marquardt algorithm using in the developed model, despite the lack of optimization...
The paper considers the constructing issue of ontology for the GMDH-based inductive modeling domain. It examines the main components of the GMDH algorithms in terms of their synthesis for designing the domain ontology. Such ontology significantly expands opportunities for construction of inductive modeling tools for model building and forecast of complex processes of different nature.
Generative Adversarial Networks (GANs) are efficient frameworks for estimating generative model via adversarial process. However, GAN has known for suffering from training instability. Wasserstein GAN (WGAN) improves the training stability significantly but also brings an additional Lipschitz requirement for the critic network. To enforce the Lipschitz constraint, instead of weight clipping strategy,...
This paper applies ultra-local models (also labeled intelligent PID) to Automatic Generation Control (AGC) for a Multi-Area power system in the presence of communication delay. The AGC model is built in Simulink/Matlab and co-simulated with Network Simulator 2 (NS2) through PiccSIM, a simulation platform for (wireless/wired) networked control systems. A careful comparison is made between the performance...
High levels of renewable energy sources (RES) can significantly impact system stability and system resilience as conventional generators are replaced by these units. Typically, positive sequence models of RES are used for stability analysis and interconnection studies of RES. Although these models can accurately represent the dynamic behavior of RES, there are certain limitations of their usage. This...
Previous approaches for early-stage shipboard-power-system simulation were driven by a need to perform time-domain simulation during the early design stage and included an internal idealized representation of the control system. Herein, the reduced-order physical model of the power system is combined with an independent representation of the control system. This allows the benefits of faster simulation...
Crowd-sourced reviews are used daily by potential customers to learn relevant information about a business. While textual reviews have become prominent in many recommendation-based systems, the inclusion of images can significantly increase the effectiveness of a review. However, it is difficult to verify the accuracy and usefulness of the information provided by a contributing user. In this paper,...
This paper compares the stochastic convergence of the Uniform Random number generators of two simulation software namely Matlab and Python and establishes the significance in choosing the right random number generator for error propagation studies. It further discusses about the application of Gaussian type of these random number generators to nonlinear cases of Error propagation using the Monte Carlo...
In this work, a new technique for an efficient, simple and fast equivalent circuit and full wave numerical modeling of the electrostatic discharge (ESD) generator is presented. A novel circuit model of the NoiseKen ESD simulator is proposed based on the frequency domain measurement of the standard waveform calibration setup. The simple full wave electromagnetic (EM) model of the same generator, which...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.