The key to producing a successful virtual environment is a fast update rate for the scene. This means that the virtual environment should be updated at a rate that creates a perceptually realistic experience. The problem is not necessarily the tracking device associated with the system, or even the display. Delays generally come from the time it takes a computer to graphically render a scene associated with the environment. Although computer-processing speeds have drastically increased in recent years, they are still not fast enough to generate a virtual scene that will provide the user with a truly realistic experience. The performance of any VR system is dependent not only on processing speeds, but also on the sensor (s) which generate information used to update the virtual environment. Magnetic sensors are the industry standard, but inertial, acoustical, and hybrid systems are also available. When using a head mounted display, ideally the head position would be read instantaneously. The problem remains that even if communication between the tracker and graphics generator were instantaneous, graphics generation of the scene would still require additional processing time. If however, graphics generation could begin before the user actually reached the next step in the virtual environment, the problems associated with processing delays would be reduced. Accurate prediction of the user's motion or position would allow the graphics of the scene to be generated beforehand and displayed for the user at the appropriate time. A new hybridtracking system that does have the ability to predict a users motion up to 50ms in advance has recently entered the market. This system collects 3 orientation readings from an inertial motion sensor and 3 position readings from 3 individual transponder beacons with each sampling. In comparison to the standard magnetic tracking system, the hybrid system has increased the sampling frequency thereby decreasing the average sampling lag as well as the system processing time. The combination of reduced processing time and prediction may be the next step in VR tracking devices.
subsystem runs on a single-board PC with interfaces to a camera and an inertial tracker, which are mounted to the user’s helmet. Hybridtracking delivers six de- grees of freedom of head pose at rates of approxi- mately 100 Hz. The visualization subsystem consists of a laptop with 3D graphics acceleration and a see- through head-mounted-display (HMD). The HMD delivers virtual 3D graphics as stereo video streams which are blended with the user’s natural perception of the real scene using semitransparent mirrors. An additional firewire webcam is mounted at the front of the helmet and connected to the laptop. This camera can be used (but was not used in our current experi- ments) for 3D human–computer interaction, e.g., tracking of an interaction pad and pen, as described in ref. 13. There are many exciting applications of mo- bile outdoor AR: architectural visualization, city guide, maintenance support, navigation, rescue and emergency operations, to name just a few. Most of these applications require a reliable continuous track- ing with high accuracy, low jitter, and no lag. Tracking requirements become even more stringent for mul- tiuser AR scenarios, where several mobile users re- quire an augmented perception which is consistent in space and time.
For this complex scenario, the tracking algorithm must deal with several hundred signiﬁcant corners, and inac- curate corner localization can lead to ambiguous land- mark matching, complicating the correspondence problem and target selection. At the time of this writing, we’re close to, but haven’t yet reached, real-time perfor- mance using the dual-processor equipment. We show ﬁrst results from a sequence that was captured in real time and processed ofﬂine. Figure 11 (next page) presents the tracking performance for the initial rotation (4-second sequence).
In this section three typical TMA scenarios are considered. In all scenarios a target is moving with a constant acceleration and own ship is moving on a circular path with a constant velocity. In the first scenario (section A) only the high rate bearing angle information for tracking the target (BOM tracking) is used, but in the second scenario (section B) in addition to using high rate bearing angle information, low rate range information (hybridtracking) is also employed. In the third scenario (section C) a system that only uses the low rate range and bearing angle measurements for tracking the target is proposed. The sequence of angular measurements (for BOM tracking) and sequence of angular-range measurements (for hybridtracking) are processed with EMPC-EKF and then the estimated target path in Cartesian coordinates is presented. At the end, the mean and Standard Deviation (STD) values of the tracking filter error by averaging the error along several independent trials of the same experiment are evaluated. In all scenarios the own ship is moving on a circular path whose center in Cartesian coordinates is 0 0 T . The constant velocity of own ship is 50 m s and the overall angle of rotation is 4 radian (own ship moves on the circular path two times). The passive sensor collects N 1 50 angular measurements. The time period between consecutive measurements is T 3 s . In the hybridtracking scenario as the passive sensor collects m 15 angular measurements, the active sensor reports one range measurement so the period of active sensor measurement is T 45 s (in this case the total range measurements is
system can be used to retain the non-renewable fossil fuels. The Photovoltaic-wind hybrid system profits the lowest unit cost values to sustain the same level of insufficiently of Power Supply Probability as compared to standalone solar and wind systems. For all load demands, the optimal energy cost for Photovoltaic-wind hybrid system is always lower than that of standalone solar PV or wind system. The Photovoltaic-wind hybrid system is best techno- economically practicable. This paper represents the hybrid energy system using solar and wind energy resources & multilevel converter for the generation of power. The multilevel inverters are applied in high voltage PV power plant mainly due to the high voltage efficiency, low switching frequency, and low power losses. The power system is connected to grid. The objective of this paper is to presents a simulation; modelling and analysing of a seven-level inverter operate on photovoltaic and wind power for generation of power. Solar-wind hybrid renewable energy system for grid connection system control is an intelligent grid lighting system. The advantage of this idea is to avoid daily running cost and make the system more independent.
Particle Swarm Optimization (PSO) is a global gradient less stochastic search method. It is used to search for continuous variable for optimization problems [7, 8]. Artificial Neural Network (ANN) is an information processing paradigm, which is based on the functional concepts of biological nervous systems. It works best to deal with nonlinear dependence between the inputs and outputs [9, 13]. In this study, a hybrid ANN and PSO method is proposed to extract the GP under partial shaded condition. The ANN algorithm initializes the optimal voltage Vopt initial value at the prevailing solar irradiance, temperature and PV current. This initial voltage is then fed into the PSO to reach the (Global Peak) GP location. ANN acts as a platform to aid the PSO algorithm to locate GP in a smaller range. Therefore, PSO can reach the true GP without having to sweep over the wide range of PV current which ultimately cut short the computational time. This avoids the operating point from lingering at LP and guarantees the reach of GP.
The operation of DC-DC electricity converters is also an essential part of a single, powerful water pumping device. Each zeta converter becomes powered by either a PSO-MPPT model to find full power through PV devices, while a dual loop power storage technique is used to monitor the symmetric DC-DC converters. 3.1 PSO algorithm and application in MPP tracking: In terms of power device issue optimization, electronics applications, harmonically energy harvesting converters, etc, it was noticed that PSO  was extremely useful. Many parametric calculations are required for genetic algorithms, colonic computation and other related biological algorithm. When contrast to many other biological optimization computation, PSO is simple to implement although time-consuming. Their particles throughout PSO travel throughout the space of the question, consider the best answer and store this in the brain. The highest health in the community as well as in the entire cycle is alluded to as the highest personal benefit as well as the leading international interest. Growing particle travels until a certain pace towards the best professional and global principles and updates them during each iteration. That pace and location of both the particle were modified as follows.
The present worldwide trends concern energy security and sustainable development across the globe. The role of renewable energy has therefore become ever more significant. The developed world is already on the track for walking out from the fossil fuel era and involving mainly the areas of renewable energy technologies and energy efficiency. The proposed system is implementable to those areas where the solar wind and hydro energies are available at moderate nature such as Indian circumstance. The nature of the solar wind and hydro energies is intermittent. Hence, using the individual system the continuous power generation is not possible, and it will also increase burden to the grid. The proposed system is able to supply the community in all seasons. The proposed hybrid system reduces the complexity of the electrical system, having less cost as compared to other renewable energy sources and reliable operation. The obtained results show that the proposed system has the potential to supply the local community.
2. David P. McMullen, Guy Hotson, Kapil D. Katyal, Brock A. Wester, Matthew S. Fifer, Timothy G. McGee, Andrew Harris, Matthew S. Johannes, R. Jacob Vogelstein, Alan D. Ravitz, William S. Anderson, Nitish V. Thakor, and Nathan E. Crone, "Demonstration of a Semi-Autonomous Hybrid Brain–Machine Interface Using Human Intracranial EEG, Eye Tracking, and Computer Vision to Control a Robotic Upper Limb Prosthetic", IEEE Transactions on Neural Systems And Rehabilitation Engineering, VOL. 22, NO. 4, pp. 784-796, JULY 2014.
In this paper, we proposed an optimized real-time hybrid cooperative multi-camera tracking system for large-scale au- tomate surveillance based on embedded smart cameras including stationary cameras and moving pan/tilt/zoom (PTZ) cameras embedded with TI DSP TMS320DM6446 for intelligent visual analysis. Firstly, the overlapping areas and projection relations between adjacent cameras' field of view (FOV) is calculated. Based on the relations of FOV ob- tained and tracking information of each single camera, a homography based target handover procedure is done for long-term multi-camera tracking. After that, we fully implemented the tracking system on the embedded platform de- veloped by our group. Finally, to reduce the huge computational complexity, a novel hierarchical optimization method is proposed. Experimental results demonstrate the robustness and real-time efficiency in dynamic real-world environ- ments and the computational burden is significantly reduced by 98.84%. Our results demonstrate that our proposed sys- tem is capable of tracking targets effectively and achieve large-scale surveillance with clear detailed close-up visual features capturing and recording in dynamic real-life environments.
A new hybrid algorithm is proposed in this paper combines some traditional methods such as MIE and data fusion . Almost all of the traditional algorithms in target tracking implement the current observed data and don’t use the benefits of the estimated states and inputs over the previous times. The obtained estimation from most of the available algorithms contains a transient state which affects the final tracking during the forward time after the input applied. This problem in control methods doesn't make a significant error, however this slight difference in transient period causes divergence in target tracking problem. In some control methods such as model predictive control (MPC), the main objective of design is the influence analysis of applied input in the future time and matching the output with desired value in a certain time period .
Studies show that eddy–eddy interaction is universal within the ocean (Trieling et al., 2005; Prants et al., 2011). A very small number of studies have investigated local- ized eddy splitting and merging, confirming eddy variation through traditional visual interpretation of sea surface height fields (Fang and Morrow, 2003; Schonten et al., 2000). Mat- suoka et al. (2016) proposed a new approach for eddy track- ing and detected splitting and merging events of eddies as well as the interaction between eddies and ocean currents. Le Vu et al. (2018) presented an angular momentum eddy detection and tracking algorithm (AMEDA) for detecting and tracking eddies in the Mediterranean Sea; this proce- dure identified the merging and splitting events and provided a complete dynamical evolution of the detected eddies during their lifetime. Similarly, Laxenaire et al. (2018) proposed an original assessment on Agulhas rings, whose novelty lies in the detection of eddy splitting and merging events, and they found these events are abundant and significantly impact the concept of a trajectory associated with a single eddy. Such studies simply considered an eddy at one moment as a sin- gle eddy entity, which was then split into two separate eddies at the next moment, without consideration of eddy–eddy in- teraction processes. Although such a simplified solution can reveal the dynamic behavior of eddies, the evolutionary pro- cess remains obscure. Some studies of eddy–eddy interac- tion have found abundant multicore eddy structures within the global oceans (Du et al., 2014; Le Vu et al., 2018; Triel- ing et al., 2005; Yi et al., 2014a). Generally, multicore struc- tures, which have two or more closed eddies of the same po- larity within their boundaries, represent an important transi- tional stage in which the component eddies might experience splitting, merging, or other energy-transferring interactions. In studying eddy–eddy interaction processes, clear identifi- cation of multicore eddy structures is necessary.
n . . . 18.36 (8) By the formula (8), the n value is approximate 18.36 r/s, the wind turbine speed at this time is the best value for speed. In the controller design circuit, tracking the speed value of the wind turbine can track the maximum power of wind energy.
particular scenarios. The value of the overall average overlap rate was 35 % higher than the highest value among the other algorithms. When tracking a single tar- get in a multi-hen mutual occlusion situation (the most challenging scenario), HSVM’s average overlap rate was 68 %, which was 41 % higher than the highest value attained for the other algorithms. HSVM was relatively stable with the average overlap rate maintained between 68 and 79 % across the specific cases and the overall average. The PLS algorithm attained the best perform- ance among the contrast algorithms because the PLS was able to model the correlation of target appearance and class labels due to its capacity for both dimensional- ity reduction and classification . The value of the average overlap rate for the changing of direction, two hens’ mutual occlusion, and preening scenarios was 55, 61 and 62 % respectively. However, PLS performed poorly in handling the heavy occlusion, which can easily and quickly change the appearance of targets . In the situation of multiple hens’ mutual occlusion, PLS lost the target hen for some frames resulting in a drop in the average overlap rate to 23 %. For the situation of mul- tiple hens’ mutual occlusion, the best performance (ex- cluding that of HSVM) was achieved by the Particle Filter Algorithm, whereby the average overlap rate only reached 27 %.
Experiment 3: A comparison of 3D-GNN with and with- out the use of the reprojection method. Contrary to a basic segmentation, our hybrid intensity/depth segmen- tation also recovered targets with no recoverable depth, which then became candidates for reprojection. In this experiment, an attempt was made to remove all of the tar- gets that were not fully defined in 3D, with the effect that the occurrence of false alarms was reduced, but this also removed some correct detections. The results shown in Figure 17 confirm the need to use targets with no recover- able depth to achieve a complete tracking. It is clear that in 3D the difficulties are related to observations with no depth; however, these observations are needed in order to consider the corresponding tracks. When using only full 3D defined observations, the increased number of targets had almost no effect on the performance. Therefore, in our application, the tracking results were directly driven by the quality of the segmentation.
Many real world applications managed in military and civilian require accurate tracking of moving targets acquired by sensors. In military applications, tracking is continuously updated the performance of target’s position and also tracking of enemy vehicles so that they are blocked and destroyed immediately . In civilian applications target tracking is of much use in autonomous vehicles, home security etc. Accurate target tracking is used in many situations to accommodate the need for constant human help and thus it is simple to achieve much higher degree of intelligent, wireless and automatic . There is loads of real time application for locomotive tracking and monitoring using satellite based navigation system with high level of speed and precision. These systems are more accurate, precise, efficient, low cost and less economic maintenance. But in poor satellite visible areas such as mountains, tunnel, valleys, deep cuttings etc. they are facing many service failure issues .
A hybrid energy system usually consisting of two or more renewable energy sources are used together to provide increased system efficiency as well as greater balance in energy supply. In this paper, the hybrid energy system is a photovoltaic array coupled with a wind turbine. Fig:11 shows the schematic diagram of hybrid system. The developed system consists of 100KW photovoltaic array and 100KW PMSG based wind turbine connected to the load for achieving maximum power point with a current reference control produced by MPPT algorithms.
Abstract: Now a day’s electricity is most needed facility for the human being. All the conventional energy resources are depleting day by day. So we have to shift from conventional to non-conventional energy resources. In this the combination of two energy resources is takes place i.e. wind and solar energy. This process reviles the sustainable energy resources without damaging the nature. We can give uninterrupted power by using hybrid energy system. Basically this system involves the integration of two energy system that will give continuous power. Solar panels are used for converting solar energy and wind turbines are used for converting wind energy into electricity. This electrical power can utilize for various purpose. Generation of electricity will be takes place at affordable cost. This paper deals with the generation of electricity by using two sources combine which leads to generate electricity with affordable cost without damaging the nature balance. Index Terms- electricity, hybrid, solar, power, wind.