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Understanding where people look in images is an important problem in computer vision. Despite significant research, it remains unclear to what extent human fixations can be predicted by low-level (contrast) compared to highlevel (presence of objects) image features. Here we address this problem by introducing two novel models that use different feature spaces but the same readout architecture. The...
The ability to predict and therefore to anticipate the future is an important attribute of intelligence. It is also of utmost importance in real-time systems, e.g. in robotics or autonomous driving, which depend on visual scene understanding for decision making. While prediction of the raw RGB pixel values in future video frames has been studied in previous work, here we introduce the novel task of...
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their names. Most existing unsupervised ZSL methods aim to learn a model for directly comparing image features and class names. However, this proves to be a difficult task due to dominance of non-visual semantics in underlying vector-space embeddings of class names. To address this issue, we discriminatively...
This paper presents a lambda tuner tool for the analysis and the design proportional-integral-derivative (PID) controllers using Matlab/Simulink software. The proposed application allows the user to easily obtain control parameters with lambda method and several traditional tuning methods. The lambda method guarantees robustness, stability and non-oscillatory response. It should be noted that the...
Matrix converters are devices that allow the management of bidirectional flows of energy, reduced size, increased useful life and high efficiency in wind schemes. In this paper we present the experimental results obtained after the application of a predictive current control technique for two matrix converters feeding isolated loads. One scheme is based on IGBT technology and the other on SiC-MOSFET...
Serious sealing problems cause premature retirement of Lithium-ion punch cells in the service stage. This paper mainly investigates the sealing failure behavior of Li-ion punch cell. A non-linear peeling model was established with experimental verification to explain the failure behavior of sealing cohesive zone. Based on the peeling model, a sealing life prediction method is proposed by describing...
Electricity consumption prediction is an important but demanding issue in the study of power systems. It is difficult for the conventional prediction methods, such as linear models, to utilize relevant domain knowledge in the forecasting of power peaks. In this paper, we propose an approach merging a regression predictor and a peak compensator together. The latter is designed to compensate for the...
In this paper, an off-design performance prediction model for a single shaft industrial gas turbine (IGT) using Microsoft Excel with Visual Basic for Applications (VBA) programming is presented. The modelling architecture is comprised of fundamental thermodynamic equations describing the performance of IGTs. A graphical user interface has been constructed to allow an easy interaction of the model...
As a state-of-the-art ensemble method, random forest which exhibits a good ability to predict and generalize on various dataset is often composed of a large number of trees. Redundancy of ensemble and connotative decision rules result in expensive operational costs as well as difficulties in comprehension. In this paper, novel leaf node-level pruning methods for random forest are proposed. Each leaf...
Photovoltaic (PV) power generation's advantage of mitigating fossil energy consumption and environment friendly results in its widespread utilization. However, inaccurate PV output prediction will cause problems of dispatching, stability and reliability in power system. PV output is directly affected by the solar irradiance. Without solar irradiance monitoring facilities and only relying on the basic...
A tracking simulator is an online simulation system that utilizes dynamic parameter estimation for calibrating model parameters to achieve state synchronization with the process. It can be utilized as a plant-wide virtual sensors or as a predictive tool to provide production forecasts based on the current state of the plant. The appearance of industrial applications based on tracking simulators has...
Link prediction is a fundamental problem in social systems, including the prediction of user interaction and the links between users and items, which is also referred to as recommendation. Previous works mainly focus on the prediction task independently, which predict either the links between users or the links between users and items. However, these two prediction tasks are always coupled with each...
Multilevel current source converter (MCSC) is an effective way to increase the power rating of conventional current source-fed motor drive, especially its current rating. However, there are still several challenges existing in this configuration, which mainly focus on its modulation and control techniques, and the inherent DC current imbalance issue. In this paper, a model predictive control (MPC)...
A novel single-phase five-level active rectifier based on the VIENNA-type rectifier with model predictive current control is presented. The proposed topology operates in unidirectional mode, imposing a sinusoidal grid-side current with unitary power factor. A unidirectional electric vehicle battery charger is the target application in which the proposed rectifier is used; however, it can also be used...
Medical institutes use Electronic Medical Record (EMR) to record a series of medical events, including diagnostic information (diagnosis codes), procedures performed (procedure codes) and admission details. Plenty of data mining technologies are applied in the EMR data set for knowledge discovery, which is precious to medical practice. The knowledge found is conducive to develop treatment plans, improve...
This paper proposes a Model predictive control (MPC) for linear induction motor drive. Model Predictive Control (MPC) is a strong method for controlling drives of the linear induction motor. In comparison with the Direct Force Control (DFC), MPC is more precise and more effective in the selection of the voltage vector. The results show that this control method has a better performance in comparison...
Insulated gate bipolar transistors (IGBTs) are one of the most critical components in the Electric Vehicles (EVs) because of their complex running environment, high power dissipation and frequent junction temperature fluctuation. Therefore, it's essential to predict the lifetime of IGBTs by considering the actual factors in applications. The aim of this paper is to present a lifetime prediction method...
File transfers between the decentralized storage sites over dedicated wide-area connections are becoming increasingly important in high-performance computing and big data scenarios. Designing such scientific workflows for large file transfers is extremely challenging as they depend on the file, I/O, host, and local- and wide-area network subsystems, and their interactions. To gain insights into file-transfer...
Owning property is one of the most important investments that a person can make in their lifetime. Therefore, being able to accurately know the real-time value of any property is crucial for making wise sales and purchases. Since the online real estate database company Zillow first developed a machine learning system to predict property sale prices in real time, it has continually worked to improve...
Nowadays, the control systems based on communication networks are used various industries such as manufacturing, automotive, aerospace, power generation and distribution, with many advantages and a couple of disadvantages. The latter can seriously affect the performances and the stability of each control system in the network and of the complex system as a whole. Moreover, it is well known that packet...
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