Time tracking

Redmine is wellknown as one of the best open source project management applications. But, it's also one of the best project hosting and issue tracking solutions. In addition it incorporates Wiki, repository management, forums, time tracking, and more. This book reveals the power of Redmine and manifests its exceptional flexibility and customizability.
366p titatu_123 09032013 56 12 Download

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Efﬁcient Adaptive Combination of Histograms for RealTime Tracking
11p sting09 21022012 23 2 Download

Due to the high cost of fossilbased energy, several methods are proposed to reduce the usage of the energy in logistics and fleet management to be even more GPS tracking system is a common approach to get vehicle location information in realtime for fleet planning
6p zero22hero 06112012 39 12 Download

The paper introduces an algorithm to design a feedback controller, which guarantees the tracking of time varying bilinear system outputs for desired values in the presence of input constraint. The proposed controller employs the ideas of receding horizon principle and constrained optimal control.
10p dieutringuyen 07062017 2 1 Download

WHY TRACKING AND PREDICTION ARE NEEDED IN A RADAR Let us ﬁrst start by indicating why tracking and prediction are needed in a radar. Assume a fanbeam surveillance radar such as shown in Figure 1.11. For such a radar the fan beam rotates continually through 360 , typically with a period of 10 sec. Such a radar provides twodimensional information about a target. The ﬁrst dimension is the target range (i.e., the time it takes for a transmitted pulse to go from the transmitter to the target and back); the second dimension is the azimuth of the target,...
61p khinhkha 30072010 63 22 Download

A RealTime Computer Vision System for Vehicle Tracking and Traffic Surveillance
33p nhan4321 29102009 98 15 Download

KALMAN FILTER 2.1 TWOSTATE KALMAN FILTER Up to now we have used a deterministic description for the target motion. Speciﬁcally, we have assumed a target having a constantvelocity motion as given by _ x nþ1 ¼ x n þ T x n _ _ x nþ1 ¼ x n ð1:11aÞ ð1:11bÞ In the real world the target will not have a constant velocity for all time. There is actually uncertainty in the target trajectory, the target accelerating or turning at any given time. Kalman allowed for this uncertainty in the target motion by adding a random component to the target dynamics [19,...
47p khinhkha 30072010 61 14 Download

LEASTSQUARES AND MINIMUM– VARIANCE ESTIMATES FOR LINEAR TIMEINVARIANT SYSTEMS 4.1 GENERAL LEASTSQUARES ESTIMATION RESULTS In Section 2.4 we developed (2.43), relating the 1 Â 1 measurement matrix Y n to the 2 Â 1 state vector X n through the 1 Â 2 observation matrix M as given by Y n ¼ MX n þ N n ð4:11Þ It was also pointed out in Sections 2.4 and 2.10 that this linear timeinvariant equation (i.e., M is independent of time or equivalently n) applies to more general cases that we generalize further here. Speciﬁcally we assume Y n is a 1 Â ðr...
50p khinhkha 30072010 64 13 Download

GENERAL FORM FOR LINEAR TIMEINVARIANT SYSTEM 8.1 TARGET DYNAMICS DESCRIBED BY POLYNOMIAL AS A FUNCTION OF TIME 8.1.1 Introduction In Section 1.1 we deﬁned the target dynamics model for target having a constant velocity; see (1.11). A constantvelocity target is one whose trajectory can be expressed by a polynomial of degree 1 in time, that is, d ¼ 1, in (5.91). (In turn, the tracking ﬁlter need only be of degree 1, i.e., m ¼ 1.) Alternately, it is a target for which the ﬁrst derivative of its position versus time is a constant. In Section 2.4 we rewrote the target...
8p khinhkha 30072010 44 13 Download

INTRODUCTION In Section 6.3 we developed a recursive leastsquares growing memoryﬁlter for the case where the target trajectory is approximated by a polynomial. In this chapter we develop a recursive leastsquares growingmemory ﬁlter that is not restricted to having the target trajectory approximated by a polynomial [5. pp. 461–482]. The only requirement is that Y nÀi , the measurement vector at time n À i, be linearly related to X nÀi in the errorfree situation. The Y nÀi can be made up to multiple measurements obtained at the time n À i as in (4.
4p khinhkha 30072010 49 12 Download

NONLINEAR OBSERVATION SCHEME AND DYNAMIC MODEL (EXTENDED KALMAN FILTER) 16.1 INTRODUCTION In this section we extend the results for the linear timeinvariant and timevariant cases to where the observations are nonlinearly related to the state vector and/or the target dynamics model is a nonlinear relationship [5, pp. 105– 111, 166–171, 298–300]. The approachs involve the use of linearization procedures. This linearization allows us to apply the linear leastsquares and minimumvariance theory results obtained so far.
10p khinhkha 30072010 77 12 Download

BAYES ALGORITHM WITH ITERATIVE DIFFERENTIAL CORRECTION FOR NONLINEAR SYSTEMS 17.1 DETERMINATION OF UPDATED ESTIMATES We are now in a position to obtain the updated estimate for the nonlinear observation and target dynamic model cases [5, pp. 424–443]. We shall use the example of the ballistic projectile traveling through the atmosphere for deﬁniteness in our discussion. Assume that the past measurements have " permitted us to obtain the state vector estimate Xðt À Þ at the time t À , the last time observations were made on the target. As done at the end of Section 16.
8p khinhkha 30072010 65 12 Download

HOUSEHOLDER ORTHONORMAL TRANSFORMATION In the preceding chapter we showed how the elementary Givens orthonormal transformation triangularized a matrix by successfully zeroing out one element at a time below the diagonal of each column. With the Householder orthonormal transformation all the elements below the diagonal of a given column are zeroed out simultaneously with one Householder transformation.
7p khinhkha 30072010 44 10 Download

LINEAR TIMEVARIANT SYSTEM 15.1 INTRODUCTION In this chapter we extend the results of Chapters 4 and 8 to systems having timevariant dynamic models and observation schemes [5, pp. 99–104]. For a timevarying observation system, the observation matrix M of (4.11) and (4.15) could be different at different times, that is, for different n. Thus the observation equation becomes Y n ¼ M nX n þ N n ð15:11Þ For a timevarying dynamics model the transition matrix È would be different at different times. In this case È of (8.
3p khinhkha 30072010 55 7 Download

Moving objects detection and tracking in video stream are basic fundamental and critical tasks in many computer vision applications. We have presented in this paper effectiveness increase of algorithms for moving objects detection and tracking. For this, we use additive minimax similarity function. Background reconstruction algorithm is developed. Moving and tracking objects detection algorithms are modified on the basis of additive minimax similarity function. Results of experiments are presented according to time expenses of the moving object detection and tracking. ...
9p tuanlocmuido 19122012 31 6 Download

Chapter 14 Analysing Point Motion with Geographic Knowledge Discovery Techniques Patrick Laube 1, Ross S. Purves 2, Stephan Imfeld 2 and Robert Weibel 2 1 School of Geography and Environmental Science, University of Auckland, New Zealand 2 Department of Geography, University of Zurich, Switzerland 14.1 Introduction Mobility is key to contemporary life. In a globalised world, people, goods, data and ideas move in increasing volumes at increasing speeds over increasing distances, and more and more leave a digital trail behind them.
24p gaucon_ngoan 26122011 30 4 Download

Tuyển tập các báo cáo nghiên cứu khoa học ngành toán học được đăng trên tạp chí toán học quốc tế đề tài: Realtime reliability measuredriven multihypothesis tracking using 2D and 3D features
21p sting03 04022012 24 4 Download

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A RealTime ModelBased Human Motion Tracking and Analysis for Human Computer Interface Systems
15p sting12 11032012 24 4 Download

So you want to be a bigtime music producer? Whether the boatload of cash, the adoring fans, the mansions, the vacations, or the yachts is the big appeal for you, one thing is certain: You won’t be able to achieve any of these things unless you first get Home Studio installed and configured.
337p transang3 30092012 23 4 Download

China has a dualtrack interestrate system: bank deposit and lending rates are regulated while money and bond rates are marketdetermined. The central bank also imposes an indicative target, which may not be binding at all times, for total credit in the banking system. We develop and cali brate a theoretical model to illustrate the conduct of monetary policy within the framework of dual track interest rates and a juxtaposition of price and quantitybased policy instruments.
0p taisaovanchuavo 23012013 34 4 Download