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Focusing on detection technology for autonomous underwater detection device which found marine target which radiated noise signal submerged in background noise, chaotic detector based on Duffing oscillator is researched. In this paper, the Duffing oscillator and chaotic detector based on Duffing oscillator are described. Through numerical simulation and theoretical analysis, it is proved that the...
Given a database of spatial trajectories reporting the movement of a set of objects in a time frame, the problem is to discover the groups of objects that stay in close proximity within a geographical area for a significant time. To deal with the problem, techniques for the discovery of collective patterns, e.g. the meeting pattern, have been proposed. Such techniques, however, impose stringent constraints...
Transit advertising provides frequent exposure to a large number of residents in different urban regions. However, traditional methods are generally manual and qualitatively based on a rough estimation, such as the number of passengers taken by a bus or functional regions covered. How to accurately put an advertisement on appropriate transportations becomes an important task for potential business...
In order to control the interaction of industrial robots with soft materials many computationally-intensive sub-tasks have to be performed in parallel, such as material simulations, control policy optimization or path planning among many others. Since the robot control cannot process the amount of information needed for those tasks, the whole system needs to be split up in two parts: the physical...
This paper explores recent achievements and novel challenges of the annoying privacy-preserving big data stream mining problem, which consists in applying mining algorithms to big data streams while ensuring the privacy of data. Recently, the emerging big data analytics context has conferred a new light to this exciting research area. This paper follows the so-depicted research trend.
In conditions of a mass character of higher education, the problems of student identification are relevant because of the differences in the contingent of students in terms of level of training, personal and cognitive characteristics. The learning process is characterized by the presence of uncertainty factors, which requires modeling and control of the application process of methods and tools of...
Advances in modeling and knowledge representation, data mining, semantic Internet, analytical methods and open data are the basis for new models of knowledge analysis. The growth of information and data exceeds the ability of organizations to analyze them. This problem is particularly expressed in terms of knowledge and learning processes. Analytical methods can be successfully applied in studying...
The next generation cellular networks are predicted to face the challenge of massive data transmission originated from Machine Type Communication (MTC) devices with limited communication resources. The main objective of this paper is to reduce communication resources consumption in acceptable transmission latency for massive data generated from MTC devices. As an attempt to solve this challenge, a...
The present study has as objective to analyze frequencies of Thunderstorm that occurred in the province of Luanda (1998 to 2015), A thermodynamic study of an intense event, to evaluate the operation of the thermodynamic method. This method was based on the vertical profiles, predicted 48 hours in advance, indices of instability and trajectories of the HYSPLIT model for forecasting. Topographic influence...
In order to describe the inherent hysteresis nonlinearity of the piezo-actuated stages, a Krasnosel'skii-Pokrovskii (KP) model is presented in the paper. The parameters of the KP model are identified by a modified bat optimization algorithm based on Levy fights trajectory. The modified bat optimization algorithm uses the Levy fights trajectory to improve the global searching ability and break away...
Given 2D discrete vector-geometric trajectories generated by a controllable, quarter-plane causal system, we identify an unfalsified Roesser model for it. We first compute state trajectories from the factorization of constant matrices directly constructed from the data; the A, B, C and D matrices of the Roesser model are then determined solving a system of linear equations involving the data and the...
The true onset time of a disease, particularly slow-onset diseases like Type 2 diabetes mellitus (T2DM), is rarely observable in electronic health records (EHRs). However, it is critical for analysis of time to events and for studying sequences of diseases. The aim of this study is to demonstrate a method for estimating the onset time of such diseases from intermittently observable laboratory results...
We present a method to model and classify trajectory data that come from surveillance videos. Observations of the locations of moving entities are used to estimate their expected velocity in the scene. Such estimation is performed by a Gaussian process regression that enables to approximate probabilistically the expected velocity of entities given some observed evidence in the scene. Subsequently,...
With the fast development of the Internet, the lightweight 3-dimension (3D) geographic scenes visualization system is expected to play more important roles in web-based GIS. Finding an effective solution to render 3D geospatial data has great significance in Cartography and Geographic Information Systems. The emergence of HTML5, as well as WebGL (Web Graphics Library), provides a new approach for...
Haze is a negative consequence of forest and land fires that caused many health problems and contributed on global warming. This study aims to generate haze trajectory from peatland fires in South Sumatra in October 2015. We used the HYPLIT model to generate haze trajectories with hotspot sequences as the initial points of trajectory. The simulation was performed using the package Opentraj which is...
In this paper we consider the data caching problem in next generation data services in the cloud, which is characterized by using monetary cost and access trajectory information to control cache replacements, instead of exploiting capacityoriented strategies as in traditional research. In particular, given a stream of requests to a shared data item with respect to a homogeneous cost model, we first...
Video surveillance has been used extensively in our daily life today, for example, traffic safety, trajectory analysis, event monitoring, and crowd behavior identification. However, sometimes in many real-world video sequences dealing with complex scenario and environmental noise is still a challenging task. One solution is to consider information of scenario during tracking. In this paper, we propose...
Being as the pivot of avionics system, Flight Management System (FMS) plays an important role in flight planning, trajectory prediction, navigation and guidance of aircrafts. Aiming at researching the functions and validations of FMS, the advanced FMS simulation is constructed. Performance Based Navigation (PBN) and Trajectory Based Operation (TBO) require high-fidelity and high-accuracy data, of...
The main challenge for anomaly detection in Self-Organizing Industrial Systems (SOIS) is the high degree of freedom of the system, which causes a state-space explosion. Since the system is free to choose at runtime any solution out of the vast amount of possible ones, to ensure that the production process is optimal at all times, classic anomaly detection techniques can not be used one-to-one in SOISs...
In this work, we present a monitoring system for Self-Organizing Industrial Systems (SOIS). It is based on an anomaly detection approach which evaluates the movement of objects within a factory by putting them together from sub-trajectories. By introducing two metrics — relative user frequency and pathlet occurence per user — the existing method is extended so that not only anomalous trajectories...
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