The article developed a technique for using convolutional neural networks for automatic segmentation of roads in images obtained from satellites with a synthesized aperture. The analysis of the subject area and the re...
The article developed a technique for using convolutional neural networks for automatic segmentation of roads in images obtained from satellites with a synthesized aperture. The analysis of the subject area and the relevance of this study. The development of a neural network based on U-net was carried out in Python 3x using the libraries TensorFlow, TensorBoard, Pandas, Numpy, Scipy, Matplotlib, Sklearn. The neural network was trained on a training sample of 1200 images prepared by hand marking. The accuracy of the developed model when testing on prepared samples was 68%. According to the results of the study, conclusions were drawn and prospects for further functional development of the developed tools were determined.
Formal methods (in a broad sense) have been around almost since the beginning of computer science. Nonetheless, there is a perception in the formal methods community that take-up by industry is low considering the pot...
详细信息
Anomalies in the runtime behavior of software systems, especially in distributed systems, are inevitable, expensive, and hard to locate. To detect and correct such anomalies (like instability due to a growing memory c...
ISBN:
(纸本)9781931971362
Anomalies in the runtime behavior of software systems, especially in distributed systems, are inevitable, expensive, and hard to locate. To detect and correct such anomalies (like instability due to a growing memory consumption, failure due to load spikes, etc.) one has to automatically collect, store, and analyze the operational data of the runtime behavior, often represented as time series. There are efficient means both to collect and analyze the runtime behavior. But traditional time series databases do not yet focus on the specific needs of anomaly detection (generic data model, specific built-in functions, storage efficiency, and fast query execution).The paper presents Chronix, a domain specific time series database targeted at anomaly detection in operational data. Chronix uses an ideal compression and chunking of the time series data, a methodology for commissioning Chronix' parameters to a sweet spot, a way of enhancing the data with attributes, an expandable set of analysis functions, and other techniques to achieve both faster query times and a significantly smaller memory footprint. On benchmarks Chronix saves 20%-68% of the space that other time series databases need to store the data and saves 80%-92% of the data retrieval time and 73%-97% of the runtime of analyzing functions.
In the paper, based on a comparative analysis of the methods of processing time-interval codes used as secondary surveillance radar information signals consisting of a different sequence of performing joint decoding o...
详细信息
ISBN:
(数字)9781538652640
ISBN:
(纸本)9781538652657
In the paper, based on a comparative analysis of the methods of processing time-interval codes used as secondary surveillance radar information signals consisting of a different sequence of performing joint decoding operations, selecting signals by duration and time position, it is shown that the most effective is the signal processing method in which first the signals are decoded, then the signals are selected in accordance with the duration and in the future with the selection according to the time position, which provides the lowest probability of a false alarm of the first kind.
The paper, basing on analysis of the Monte-Carlo Tree Search (MCTS) method and specific features of its behavior for various cases of usage, proposes a new variant of the method, which was called as Monte-Carlo Tree S...
详细信息
ISBN:
(纸本)9781509030071
The paper, basing on analysis of the Monte-Carlo Tree Search (MCTS) method and specific features of its behavior for various cases of usage, proposes a new variant of the method, which was called as Monte-Carlo Tree Search with Tree Shape Control (MCTS-TSC) and which uses original Depth-Width Criteria (DWCs) for both tree shape estimation and control during search and for estimation and selection of potentially better options for search continuation. Proposed Tree Shape Control (TSC) technique can be used with some other tuning, pruning, and learning techniques. Besides, it can provide better scheduling of MCTS parallelization.
We address dynamic elasticity issues of VM provisioning in a heterogeneous distributed computing environment that integrates resources of a data center. We consider the scenario when the center includes dedicated reso...
详细信息
ISBN:
(纸本)9781538678800
We address dynamic elasticity issues of VM provisioning in a heterogeneous distributed computing environment that integrates resources of a data center. We consider the scenario when the center includes dedicated resources (private cloud) for providing virtualized service and non-dedicated resources for Grid-computing. Existing platforms for the resource virtualization does not support management of such an infrastructure. We propose an approach to a job management based on the dynamic elasticity of virtual machines provisioning using resources of both types. We develop the multi¬agent job scheduler for dedicated resources and hypervisor shell to launch virtual machines through queues of resource management systems in non-dedicated resources. The scheduler provides a dynamic elasticity of virtual machine provisioning. Advantages of the offered approach to the resource virtualization are demonstrated by an example of a job flow management for a scalable application to solve the complicated practical problem. It is related to the energy security of Vietnam. Provided experiments show that using the developed tools together with the platform for the resource virtualization enables agents to significantly speed up the problem-solving process.
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...
详细信息
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...
详细信息
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.
In the last years, Virtual Reality (VR) has been established itself as a highly promising media technology for reconstruction and presentation of cultural heritage sites to a wide audience. Virtual Reality enables not...
In the last years, Virtual Reality (VR) has been established itself as a highly promising media technology for reconstruction and presentation of cultural heritage sites to a wide audience. Virtual Reality enables not only an exploration of a single artefact but of many virtual objects spatially and temporally arranged into a single scene. The users enter an artificially created space and get a feeling of being a part of it. They can perceive and interact with the objects in the virtual environment in natural way. In this paper we propose a conceptual model of the VR module for the “Virtual Plaza for Immersive Representation of Bulgarian Cultural Heritage Sites”. It contains an analysis of the possible input data and the developed workflows to help experts from the cultural heritage domain to implement various scenarios for presentation of single artefacts and complete scene par of cultural heritage site using the benefits of Virtual Reality as visualization medium.
Given a synchronous system, we study the question whether - or, under which conditions - the behaviour of that system can be realized by a (non-trivially) distributed and hence asynchronous implementation. In this pap...
详细信息
暂无评论