Finding a document that is similar to a specified query document within a large document database is one of important issues in the Big Data era, as most data available is in the form of unstructured texts. Our testin...
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Development of the mobile robot can be executed in two different ways. Firstly, this creation of the built-in system, secondly, the use of "ready to use" industrial components. With distribution of the indus...
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ISBN:
(数字)9781538659953
ISBN:
(纸本)9781538659960
Development of the mobile robot can be executed in two different ways. Firstly, this creation of the built-in system, secondly, the use of "ready to use" industrial components. With distribution of the industrial mobile robots in the market there are more and more components which can be used for creation of all control system and sensors of the robot mobile platform. Use of the ready components doesn't demand the hardware development that accelerates time of development and reduces cost. The chassis of the Belarus-132 mini-tractor is used as a platform of robotic system in the research, "creation" of the program for traffic control is required. Results of the practical research on design and model development of a mobile robotic complex are given.
Kalman filters (KFs) are popular methods to estimate position information from a set of time-of-flight (ToF) values in radio frequency (RF)-based locating systems. Such filters are proven to be optimal under zero-mean...
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Kalman filters (KFs) are popular methods to estimate position information from a set of time-of-flight (ToF) values in radio frequency (RF)-based locating systems. Such filters are proven to be optimal under zero-mean Gaussian error distributions. In presence of multipath propagation ToF measurement errors drift due to small-scale motion. This results in changing phases of the multipath components (MPCs) which cause a drift on the ToF measurements. Thus, on a short-term scale the ToF measurements have a non-constant bias that changes while moving. KFs cannot distinguish between the drifting measurement errors and the true motion of the tracked object. Hence, very rigid motion models have to be used for the KF which commonly causes the filters to diverge. Therefore, the KF cannot resolve the short-term errors of consecutive measurements and the long-term motion of the tracked object. This paper presents a data-driven approach that uses training sequences to derive a near-optimal position estimator. A Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) learns to interpret drifting errors in ToF measurements of a tracked dynamic object directly from raw ToF data. Our evaluation shows that our approach outperforms state-of-the-art KFs on both synthetically generated and real-world dynamic motion trajectories that include drifting ToF measurement errors.
The next phase of LHC Operations – High Luminosity LHC (HL-LHC), which is aimed at ten-fold increase in the luminosity of proton-proton collisions at the energy of 14 TeV, is expected to start operation in 2027-2028 ...
The next phase of LHC Operations – High Luminosity LHC (HL-LHC), which is aimed at ten-fold increase in the luminosity of proton-proton collisions at the energy of 14 TeV, is expected to start operation in 2027-2028 and will deliver an unprecedented scientific data volume of multi-exabyte scale. This amount of data has to be stored and the corresponding storage system should ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data processing model will not be able to provide the required infrastructure growth even taking into account the expected hardware technology evolution. To address this challenge the new state-of-the-art computing infrastructure technologies are now being developed and are presented here. The possibilities of application of the HL-LHC distributed data handling technique for other particle and astro-particle physics experiments dealing with large-scale data volumes like DUNE, LSST, Belle-II, JUNO, SKAO etc. are also discussed.
Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural...
Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of parameters tested, it appears that architecture provides the highest accuracy in one hundred hidden neural network. The architecture is used propagate the input value of the system implementation process into the user interface. The result of the identification of the type of the human movement has been clone to produce the highest acuracy of 98.5447%. The training process is done to get the best results.
Cyber incidents can disrupt regular mode of information and telecommunication systems functioning and to cause the substantial material and image losses for the company. One of the approaches in incident management is...
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ISBN:
(纸本)9781538609842
Cyber incidents can disrupt regular mode of information and telecommunication systems functioning and to cause the substantial material and image losses for the company. One of the approaches in incident management is the use of the theory of network-centric management for cyber incidents monitoring, but is not formalized stage of forming basic rules set. In this regard, in this work developed the method for rules set forming of cyber incidents extrapolation in network-centric monitoring, which allows to automate and increase accuracy operation of network-centric systems for information and telecommunication systems monitoring by determining possible types of cyber attacks and cyber incidents categories, forming vector-matrix of cyber incidents probability, cyber incidents ranging by their importance and determining limit values of probability, forming cyber incidents possibility indicators, and also development and establishment of cyber incidents extrapolation rules.
The diagnosis of possible faults in railway signaling systems is an important issue to provide safe travel and transportation in railways. Signaling system designers have to consider the possible faults which may occu...
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An elliptic second-order equation is solved by support of the finite element method that describes one thermal process. The solution is sought in the space . The finite-element approximation of the problem is provided...
An elliptic second-order equation is solved by support of the finite element method that describes one thermal process. The solution is sought in the space . The finite-element approximation of the problem is provided and the convergence rates are estimated.
Network Security is the most vital component in information security because it is responsible for securing all information passed through networked computers. Network Security refers to all hardware and software func...
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