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A novel anomaly detection algorithm is proposed to detect anomalies in trajectory data of autonomous underwater vehicles (AUVs). Compared to existing work, the proposed algorithm estimates vehicle speed (i.e., through-water speed) from trajectory data and detect abnormal motion with estimated vehicle speed by a threshold technique. The influence of ocean flow on AUVs is significant and must disturb...
An event-driven positioning control algorithm based active disturbance rejection control (ADRC) method is proposed for dynamic positioning (DP) ship under the influence of external disturbances. The time-driven positioning controller is firstly designed using ADRC method. Then, the event-driven condition is introduced by extending the designed positioning controller, moreover, the trigger decision...
As a new type of flexible drive, pneumatic artificial muscle (PAM) has been widely concerned in various fields, but the research on the dynamic characteristics is difficult because of its strong nonlinearity and hysteresis. In this paper, the effects of system hardware configuration and control algorithm on the dynamic displacement characteristics of the double parallel Mckibben artificial muscles...
In this paper, we first propose a Quality of Experience (QoE) evaluation model for dynamic adaptive streaming over HTTP (DASH) services. The proposed model predicts the perceived quality of user based on segment media quality, playback continuity and perceptual quality fluctuations caused by bitrate switching. Large quantities of subjective mean-opinion-score (MOS) tests demonstrate that our QoE evaluation...
In recent years, there has been growing interest in learning to rank. We considered the current state of learning to rank in information retrieval systems. We proposed an approach for learning to rank problem based on multi-criteria optimization using the method of Pareto optimization and Genetic Algorithms. The performance of the method has been investigated on test data collections, also a comparison...
The multilayer perceptrons (MLPs) have been widely used in many communication applications, however, the learning process of the multilayer perceptrons often becomes very slow, which is due to the existence of the singularities in the parameter space. As the singularities significantly affect the learning dynamics of MLPs, the standard gradient descent method is not Fisher efficient. In order to overcome...
A new methodology for image synthesis based on two cooperative training ConvNets is proposed. Two generative ConvNets and unsupervised joint learning are designed to effectively reflect the characteristics of real scenery and image pattern. Every ConvNet is directly derived from the discriminate ConvNet and has the potential to learn from big unlabeled data, either by contrastive divergence. One ConvNet...
In this paper, a recursive filtering method based on Kalman filter is proposed for the sensor delay in each state measurement of power system. Due to sampling frequency in the power system is generally high in milliseconds, the network topology is unchanged and the system state does not change much, therefore the system state at the next moment can be approximately linear relationship with the current...
There has been intense research activity in the last decade, in the field of Ubiquitous Computing, since it is a model of interaction, which integrates the processing of information with the peoplés daily activities. This current study focuses on the implementation of a three-tier architecture application of geolocation in real time through mobile devices, in order to facilitate the mobility of people...
Maximal Clique and Maximum Clique are two related and famous computational problems known to be intractable in the most general case. We propose a formulation of the Maximal Clique problem as a Boolean Satisfaction problem. The constraints are then mapped to a Constraint Logic Programming representation. The resulting representation can be input to a Constraint Logic Programming system that can be...
To the optical mechanical complexes of tracking and positioning, strict requirements are produced on the dynamics and permissible errors under such conditions as external and internal nonstationary disturbances, as well as presence of elastic deformations in the links of the driven mechanism. In modern systems, adaptive control algorithms have proven themselves as complementary to the main control...
With the technology improvements, managing a large amount of multimedia objects such as audio, video, picture or a combination of these has become possible. Multimedia data needs more real time storage and high data transfer than traditional textual and numeric data. In addition to these requirements, significant amount of computation is demanded for multimedia applications to serve many users at...
Restricted Boltzmann Machines (RBMs) have received special attention in the last decade due to their outstanding results in number of applications, such as face and human motion recognition, and collaborative filtering, among others. However, one of the main concerns about RBMs is related to the number of hidden units, which is application-dependent. Infinite RBM (iRBM) was proposed as an alternative...
In Bike-Sharing System (BSS), great efforts have been devoted to performing resources prediction, redistribution and trip planning to alleviate the unbalance of resources and inconvenience of bike utilization caused by the explosion of users. However, there is few work in trip planning noticing that the complete trip composes of three segments: from user's start point to a start station, from the...
In recent years, the statistical inference and algorithm for the complex diffusion process of incomplete data have become a hot topic that scholars of probability and statisticians are concerned with and calls for further study. Based upon the all-directional, multi-angle random dynamic information flow research, this article expands the information flow research in the ordinary information space...
Dynamic programming is an effective technique for the evaluation of the potential of optimal fuel consumption of drive trains, as it guarantees a globally optimal solution. This paper investigates two major problems associated with the application of dynamic programming. The first problem is the high computational complexity. Iterative dynamic programming is proposed as an alternative to dynamic programming...
Renewable Energies (RE) are considered as an important alternative sources of energy for the generation of electricity such as hydrogen and photovoltaic energies. To ensure an efficient photovoltaic energy conversion several Maximum Power Point Tracking (MPPT) algorithms have been developed to incite the PV field to deliver maximum power. This paper presents a comprehensive comparative study of two...
How to reduce the energy consumption of urban rail transit system is always the focus of attention. The automatic train operation(ATO) system operates trains between successive stations by controlling the speed automatically, which is very important for the train energy saving operation. The traditional ATO recommended speed curve optimization research is based on line information, train information...
In this paper, a new strategy combining the MDPSO (multimodal delayed particle swarm optimization) and continuous Bezier curve is developed for the global smooth path planning of mobile robots. Firstly, the preliminaries on Bezier curve and the MDPSO are briefly introduced. Secondly, the environment modeling is presented and the smooth path planning problem is mathematically formulated. Then, the...
This paper tackles the problem of finding the list of solutions with strictly increasing cost for the Semi-Assignment Problem. Four different algorithms are described and compared. The first two algorithms are based on a mathematical model and on a modification of Murty's algorithm, which was designed to find the list of solutions for the classical assignment problem. The third approach is a heuristic...
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