In a criminal investigation, situations are quite often where no evidence but a witness is available. In these cases, facial composite is a tool applied in search for a perpetrator of a crime. Facial composites are im...
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In a criminal investigation, situations are quite often where no evidence but a witness is available. In these cases, facial composite is a tool applied in search for a perpetrator of a crime. Facial composites are images of faces drafted by a forensic technician requiring a precise description provided by a witness. Despites deploying the computational technique into the process, the naming rates remain very low (not reaching 5%). In this paper, we present a system developed according to the latest research on facial perception. Incorporating the interactive evolutionary algorithm, whole face images are automatically generated based on the witness’s selection. The system is presented in the latest tested version, providing information on the selected EA as well as several image manipulation algorithms inclusive of method for age progression and hair manipulation. Besides describing applied methods and in-office testing, testing in simulated field conditions is part of the paper.
We examine the role of character patterns in three tasks: morphological analysis, lemmatization and copy. We use a modified version of the standard sequence-to-sequence model, where the encoder is a pattern matching n...
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Simultaneous localization and mapping (SLAM) is a very current problem in robotics, and the development of new SLAM algorithms is carried out by leading research institutions. The text presents the implementation of s...
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ISBN:
(数字)9781665404792
ISBN:
(纸本)9781665404808
Simultaneous localization and mapping (SLAM) is a very current problem in robotics, and the development of new SLAM algorithms is carried out by leading research institutions. The text presents the implementation of selected SLAM algorithms on a custom made hardware platform built on the chassis of the 1:10 remote control Ackerman vehicle model. A transformation of a hobby vehicle platform to an autonomous robot requires hardware and software intervention the paper further describes a sensor setup, hardware configuration, and briefly apprises of the software architecture. Finally, the characteristics and performance of GMapping with wheel odometry and visual odometry, Hector SLAM, and CRSM SLAM algorithms are evaluated in a series of practical experiments.
This article presents a prototype reference design for a low-cost miniature magnetic levitation experiment. The proposed device is built as an Arduino expansion module, thus may be installed on a broad range of microc...
ISBN:
(数字)9781728109305
ISBN:
(纸本)9781728109312
This article presents a prototype reference design for a low-cost miniature magnetic levitation experiment. The proposed device is built as an Arduino expansion module, thus may be installed on a broad range of microcontroller prototyping boards. The open-source hardware design uses off-the-shelf and widely available components and 3D printing technology, thus its overall material cost is minimal. This way, the magnetic levitation experiment is transformed into a pocket laboratory that can be borrowed by students for take-home experiments. In addition to the device itself, we present an open-source application programming interface and the outline of classroom examples in modeling, system identification and closed-loop control.
Capturing the uncertainty in probabilistic wind power forecasts is challenging, especially when uncertain input variables, such as the weather, play a role. Since ensemble weather predictions aim to capture the uncert...
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In the current state of IoT systems development, the fog techniques become the key solution of latency and energy consumption reducing when collecting and processing end user data. Instead of processing and storing da...
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This paper presents a continuous-time model predictive control scheme based on B-spline functions used for signals and model approximation. The proposed controller offers two interesting advantages. First, it formulat...
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This paper presents a continuous-time model predictive control scheme based on B-spline functions used for signals and model approximation. The proposed controller offers two interesting advantages. First, it formulates the control signal as a continuous polynomial spline function, the nature of which is determined by its control polygon that is subject of optimization. Second, all continuous constraints assumed over prediction horizon are consistently transformed into constraints imposed on a finite number of elements of this control polygon. Using parametric quadratic programming we further show how to obtain an explicit representation of the proposed controller, which is known for its efficient online implementation. The featured simulation study demonstrates that by a suitable choice of number and position of knots of the spline function over the prediction horizon it is possible to substantially reduce the number of critical regions of the explicit controller while preserving control performance, and to mitigate the direct correlation between number of regions and chosen length of prediction horizon.
This paper introduces tools for the automatic detection of "hidden" behind-the-meter solar generation in case where there is no monitoring or connection agreement contract with the system operator. The objec...
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This paper introduces tools for the automatic detection of "hidden" behind-the-meter solar generation in case where there is no monitoring or connection agreement contract with the system operator. The objective is to reach the highest precision while discriminating the nodes with and without solar generation. The proposed methods are based on exogeneous information (smart meter and temperature data) and artificial intelligence techniques consisting of neural networks as well as analytical classification algorithms. A wide range of models differing in size, architecture and number of parameters has been investigated, and the best performing ones are presented in the article. The first method involves time series classification (TSC), and the second involves time series forecasting (TSF). Open-access consumption data were used for the training of the neural networks. The implemented solutions were tested across all the nodes of the simulated electrical grid and the sensitivity of the tools was analyzed with regard to the level of PV penetration. One of the proposed tools is able to detect up to 100% of new PV installation, depending on the exogenous conditions.
This paper introduces an open-source software for distributed and decentralized non-convex optimization named ALADIN-α. ALADIN-α is a MATLAB implementation of tailored variants of the Augmented Lagrangian Alternatin...
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The conceptually new approach based on the logarithmic norm to design of robust adaptive state-feedback controller for linear time-varying (LTV) systems under system's modeling uncertainty and nonlinear external d...
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