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In Electronic Travel Aids for the blind, accurately tracking a planned path is the foundation and premise of security guiding. To satisfy the requirement of accuracy and adaptability, a continuous closed-loop control method based on intelligent adaptive PID algorithm is proposed. The dynamic model of the walking guidance system is established, and the control law and the initial parameters of intelligent...
Energy consumption in Cloud computing is a significantissue and affects aspects such as the cost of energy, coolingin the data center and the environmental impact of cloud data centers. Monitoring and prediction provides the groundwork for improving the energy efficiency of data centers. This monitoring however is required to be fast and efficient without unnecessary overhead. It is also required...
In Data Mining classification plays prominent role in predicting outcomes. One of the best supervised classification techniques in Data Mining is Naive Bayes Classification. Naive Bayes Classification is good at predicting outcomes and often outperforms other classification techniques. One of the reasons behind the strong performance of Naive Bayes Classification is due to the assumption of conditional...
This paper reports the method allowing the determination of dependences between a position error and orientation of replaceable polyhedral plates of a compound disk milling cutter and its design parameters. It allowed defining the fields of admissible values of revealed design parameters.
This paper represents a study of the context of improvement the parallel robots accuracy. We introduced, in the first hand, the different reasons of inaccuracy according to the different references mentioned in our paper as well as the methods used for the calibration and the accuracy improvement. In the other hand, we detailed the description of the direct and inverse geometric modeling of a biped...
In this paper, we developed a method of simulation for intracerebral signals acquired during Deep Brain Stimulation - DBS surgery in one patient with Parkinson's disease. Based on our previous work, an auto-regressive (AR) parametric model with order 13 was used, because it generates one of the most accurate representations of basal ganglia signals in movement disorders. Then, the AR parameters were...
In hyperspectral image analysis, the classification task has generally been discussed with dimensionality reduction due to high correlation and noise between the spectral features, which might cause significantly low classification performance. In supervised classification, limited training samples in proportion to the number of spectral features have also negative impacts on the classification accuracy,...
Metallic cables are still frequently used in access telecommunications networks, especially in the last-mile network segments, together with digital subscriber line (DSL) technologies. Recently, the G.fast system for reaching gigabit transmission speed over short metallic lines has been introduced. In order to achieve such performance, the frequency band of G.fast was extended up to 106 MHz or 212...
Machine learning has received increased interest by both the scientific community and the industry. Most of the machine learning algorithms rely on certain distance metrics that can only be applied to numeric data. This becomes a problem in complex datasets that contain heterogeneous data consisted of numeric and nominal (i.e. categorical) features. Thus the need of transformation from nominal to...
The paper describes a method of supervised context classification for an industrial machinery. The main objective of this study is to compare single and ensemble classifiers in order to classify groups of contexts which are based on an operating state of the device. The applied research was conducted with the assumption that only classic and well-practised classification methods would be adopted....
Pairwise and higher order potentials in the Hierarchical Conditional Random Field (HCRF) model play a vital role in smoothing region boundary and extracting actual object contour in the labeling space. However, pairwise potential evaluated by color information has the tendency to over-smooth small regions which are similar to their neighbors in the color space; and the higher order potential associated...
It is estimated that 80% of crashes and 65% of near collisions involved drivers inattentive to traffic for three seconds before the event. This paper develops an algorithm for extracting characteristics allowing the cell phones identification used during driving a vehicle. Experiments were performed on sets of images with 100 positive images (with phone) and the other 100 negative images (no phone),...
In this paper, we report on experiments on deployment of an extended distance-aware KinFu algorithm, designed to generate 3D model from Kinect data, onto depth frames extracted from stereo camera data. The proposed idea allows to suppress the Kinect usage limitation for outdoor sensing due to the IR interference with sunlight. Besides this, exploiting the stereo data enables a hybrid 3D reconstruction...
Due to the increasing interest of the emerging millimeter wave (mmWave) frequency band for application to cellular networks, new flexible and scalable approaches for their modeling, analysis and optimization are needed. Recently, a new approach has been proposed: it is based on the theory of point processes and it leverages tools from stochastic geometry for tractable system-level modeling, performance...
Approximate computing is a paradigm for trading off program accuracy to save energy in memory or computational resources. However, determining feasible program approximations is difficult to achieve. Popular solutions involve programmer in annotating instructions or data that can be approximated. Recently, program testing based techniques have also been explored. But these are computationally expensive...
In recent years developments in medical interventions led to an increase in technical equipment and devices. By providing a spatio- temporal identification and localization framework beneficial applications can be realized in a crowded, dynamic and harsh environment. Ultra wideband using an impulse radio signaling scheme has attracted interest for applications where precise localization is needed...
By relying on a stochastic geometry abstraction modeling for the locations of the base stations and by considering an accurate channel model based on measurements, the author of [1] has recently proposed a tractable mathematical framework for evaluating coverage and rate of millimeter wave cellular networks. The approach proposed in [1] however, relies on a noise-limited approximation for millimeter...
In this paper we formulate the point-line registration problem, which generalizes absolute orientation to point-line matching, in terms of an instance of the orthogonal Procrustes problem, and derive its solution. The same formulation solves the Non-Perspective-n-Point camera pose problem, which in turn generalizes exterior orientation to non-central cameras, i.e., Generalized cameras where projection...
Wireless location is one of the core technologies of Wireless Sensor Network. In many applications, the accuracy of the location is the precondition of the useful of data information the node collected. Under the premise of cost limits, improving the accuracy of wireless sensor node position has crucial significance. After analyzing reasons of the location weakness of Dv-Distance algorithm due to...
This paper presents a labeled multi-Bernoulli filter for track-before-detect with a special focus on visual tracking of multiple targets in video. We show that labeled multi-Bernoulli distribution is a conjugate prior for an image likelihood function with a specific separable form. Following a previously formulated likelihood function (with the desirable separable form) using background subtraction,...
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