In this work, we present a new approach for a tsunami op- erational model that retains a high degree of the complexities of the physics involved and delivers a fast and accurate sim- ulation. This speed also enables real-timeoperation: a user can start forecasting simultaneously as a tsunami event oc- curs. Results are generated faster than realtime. The main goal is to accomplish a wide-area, ocean-size computation in short time while using resources efficiently. Our model, referred to hereinafter as TRITON-G (Tsunami Refinement and Inundation Real-Time Operational Numerical Model for GPU), implements a full-GPU computing approach for the whole tsunami model, composed of generation, propagation and inundation. Specialized kernels are developed for each part of the tsunami computation, and multi-GPU is used for further acceleration. Load balance is obtained using a weighted Hilbert space-filling curve. TRITON-G solves the nonlinear spherical shallow water equations across the en- tire domain to preserve the complexity of the propagation and the effects near the coastline. The method of character- istics with directional splitting and a third-order interpola- tion semi-Lagrangian numerical scheme is used to solve the governing equations. This allows for high accuracy and min- imizes effects of numerical dispersion and diffusion while also giving the ability to choose a larger time step compared to using a Runge–Kutta scheme and at the same time per- mits a light stencil suitable for fast computation. We imple- ment a tree-based block refinement to generate a computa- tional mesh that is flexible, light and can track complex coast- lines. Customized refinements by distance and focal area were developed, which permitting an efficient use of mem- ory and computational resources. In a collaborative project with RIMES (Regional Integrated Multi-Hazard Early Warn- ing System, 2017), we utilize their existing databases for bathymetry and fault sources where available and success- fully deployed TRITON-G as their tsunami forecast opera- tional model.
Abstract: The process safety management in the Exploration & Production is enhanced by digital coaction amongst operators and service providers. On the other hand, the data obtained from surface is associated with the drilling contractors who are not interested in the design of realtime data analysing tools. The analysing tools were employed in the oil & gas industry during the initial phase of exploration that too in the seismic processing and the interpretation of subsurface three dimensional & two dimensional contrast images. The present conditions is the right time to develop a real-timeoperation center (RTOC) in association with a drilling contractor as the upstream field is facing the financial challenge of low price to their products. More innovative techniques in their Exploration & Production will be fruitful, when the field suits up. This paper will discuss in detail about the role of drilling contractor in applying realtime data analysis and operation center for the safety enhanced ultradeep water drilling process.
In this paper, an eﬃcient technique of magnetic levitation system is proposed and successfully tested based on SIMLAB platform in realtimeoperation. Furthermore, the proposed system was described mathematically and implemented practically under diﬀerent tests and parameters. The present levitation system was implemented with modern controller which is LQR controller and compared with classical controller like PID controller under the same tuning parameters. Moreover, the proposed system has been examined under two tests: signal test and load test. The ﬁndings show that the LQR controller revealed a signiﬁcant improvement in system performance. It was observed that LQR controller oﬀered notable stability and better response than PID controller at the same input parameters.
Abstract - In recent Automated Guided Vehicles (AGV) are emerging as useful technology assisting manufacturing and production in industries. These vehicles are used as advanced technology to help in the process of industrial automation. There are various methods of path planning of AGV like; Grid-based map methods, Potential ﬁeld techniques, Fuzzy logic control, and Neural network algorithms. In this paper we are applying Grid based mapping with the help of AVR microcontroller kit, collision avoidance sensor, path following sensors, all integrated with LabVIEW for controlling and feedback operation. The objective of this paper is to design a prototype using Arduino board and LabVIEW software that will provide exact location and condition of AGV. Here we are developing an inexpensive, mobile and intelligent AGV prototype that will be interfaced with LabVIEW by use of toolkit named ‘LabVIEW interface for Arduino’ (LIFA) and Arduino-Uno board. The LabVIEW according to the sensor information given to the Arduino board gives commands for controlling the operation of the AGV. The communication between Arduino board situated on AGV and LabVIEW is achieved wirelessly by ZigBee module.
Water resources management is becoming more crucial under increasing population, urbanization, and changing climate. It is reported that still one billion people do not have access to safe drinking water and two billion people have no access to electricity . Reservoirs created by dams are one of the most important elements of integrated water resources management. Storage hydropower play an important role as being one of the main renewable resource for electricity production both for base and peak load. Operation them require proper tactical management due to their multiple objectives i.e. continuous availability of water supply, load balancing, maximization of hydropower production, flood mitigation etc. Optimization is also complex as a result of having various physical components and variables. Besides, stochasticity is inherent due to randomness of unregulated inflows, water requirements, energy needs. Implicit and explicit stochastic optimization techniques has been applied in the literature . However, most of them are offline techniques and do not directly reflect a realtimeoperation problem and forecast uncertainty.
All the data is communicated to a display device by wireless interfacing (Bluetooth protocol) so that angles can be observed in real-timeoperation of the vehicle and take corrective measures for optimum and safe performance.GSM technology is used to send the below details in the form of text message after the vehicle has crashed to a specified number. Final hardware set up of the prototype which includes Accelerometer ADXL335, Bluetooth module HC05, Arduino MEGA board. SD card module, 12V power supply for controller, GSM antenna, and GPS antenna is shown in Fig. 4.1.
In recent years theft has been seriously increased and there is no safety for people and their properties. Securing and monitoring have become the main objective for controlling theft. Security plays a vital role in monitoring a building in the absence and presence of people. Most of the theft happens by door break-ins. Sensor based theft intimation system are high technology and ensure the real-timeoperation and indication of the threat to the house. Securing and monitoring have become the main objective for controlling theft. If someone tries to break the house door, the microcontroller gets an interrupt through a switch mechanism connected to the system and commands the GSM modem to send an SMS. The owner receives the message.
In this paper, a holistic approach that considers security and privacy concurrently under constraints of low resource and real-timeoperation, is adopted for addressing the current security limitations in RFID systems and in particular passive RFIDs; work is presented that shows the practicality of integrating a strong cryptographic primitive into a battery-less (sometimes referred to as passive) RFID together with a secure protocol and supporting random number generator (RNG) to produce a working prototype tag without the need for writing to non-volatile memory during its normal operation. This is believed to be the first reported integrated implementation for such a design. A number of innovations, in terms of very low power, very low number of cycles and very low area for the strong cryptographic primitives, were made to achieve the required performance within the stringent constraints imposed by low frequency passive RFIDs. The results from a manufactured prototype, including a dedicated 0.18m CMOS chip, are presented to demonstrate functionality and performance.
Approach used here is that the system uses LPC2138 of ARM 7 as the core controller in the smart vehicle so as to achieve a real-timeoperation system (OS) μC/OS-II. The real-time μC/OS-II enhances the performance of control and simplifies the design and management of software. In addition, this system uses voice-driven principle, improving the human interaction between machines and operators. The utilization of high-precision of ultrasonic sensors on obstacle avoidance robot provides a guarantee for safety. And the usage of LCD as the machine interface facilitates the debugging and control of robot.
sential if it is to be used to model animat or robot neural circuitry in situated systems and neuroethological stud- ies; hence the use of a computationally ecient state system working at the level of membrane potential. Alecsis is intended primarily as a circuit design aid and so real-timeoperation is less of a concern, although the huge size of modern electronic circuits means that com- putational eciency during simulation remains para- mount if the iterative design process is to be supported eectively. Circuit designers are interested in currents and voltages so this is appropriate level of abstrac- tion; hence, the core simulation engine is based on nodal
In the simulation of anti-missile operation process, operating instructions, all information is distributed around the command and control center (C2BMC). Whether early warning satellite, radar, or the end of anti-missile weapons are all based on the synergy between C2BMC centralized control, so the structure of centric-DDS is more appropriate for simulation of anti-missile operation process. Command and control center C2BMC as the server node, detection equipment and other anti-missile weapons exist as a client node, the detection information is sent to C2BMC, or from C2BMC will hit the target location information in realtime distributed to all nodes, hit detection. In the centralized DDS architecture, data distribution service network in the presence of a globally unique server node, the server node stores each node communication between the necessary information, including data type information, subject information, publish/subscribe. The advantage of this kind of structure is good at facilitating the coordination between systems.
Cepstrum plots the gamnitude at the ordinate axis and the quefrency at the abscissa axis. Since families of side bands are periodic in the spectrum with constant bandwidth, the cepstrum will evidently contain peaks corresponding to the dominant side band spacing. The reciprocal of the quefrency (dimensions of time) associated with such peaks would give the corresponding side band spacing and thus the modulating frequency whereas the gamnitude would tell the relative strength of the peaks. For example, if there are two families of side bands in a spectrum with frequency differences of f 1 and
When science is healthy, scientists are skeptical [106-108]. Just as there was room for T. H. Huxley to doubt Lord Kelvin’s theory of the age of the earth, there is room to questionthe relativity of time given by Albert Einstein’s Theories of Relativity. L. T. More , wrote“The chief incentive to the development of relativity is the desire to express all natural phenomena by a set of simple equations; and he[Magie] is right when he objects to making the demand for simplicity the chief purpose of a scientific theory. It is better to keep science in homely contact with our sensations at the expense of unity than to build a universe on a simplified scheme of abstract equations. And in the last analysis, a solution of our problems must be intelligible to the man of general intelligence as well as to the trained specialist. From the contradictory statements of the specialists themselves he might also include them in the class which finds the Principle of Relativity of dubious clarity.”
Abstract— In this paper, a mathematical model is proposed to solve cell formation problem considering alternative process routings in which more than one process route for each part can be selected. The model attempts to minimize intercellular movements and incorporates several real-life production factors and practical constraints. In order to increase the flexibility provided by the multiplicity of routings, the model distributes production volume of each part among alternative routes. Also, a constraint enforcing work load balancing among machines is included in the model. Due to the complexity and combinatorial nature of this model, an enhanced algorithm comprised of a genetic algorithm (GA) and a linear programming (LP) is proposed for solving the model. At each iteration, the algorithm identifies the machine cells by GA. Consequently, the production quantity of each part in each route is determined by LP sub-problem. A numerical example is solved and compared with the solution approach from the literature that selects only one route for each part. The computational results show that the proposed approach offers better solution.
Let us say we want to use Timer 0 to count the number of cars that pass. If we look back to the bit table for the TMOD SFR (see Table 2-4 and Figure 2-4) we will see that there is a bit called “C/T0” – it is bit 2 (TMOD.2). Reviewing the explanation of the bit we see that if the bit is cleared then timer 0 will be incremented at every machine cycle, using the crystal oscillator. This is what we have already used in order to measure time. However, if we set C/T0 to 1, then timer 0 will monitor the P3.4 line. Instead of being incremented every machine cycle, timer 0 will count events (pulses) on the P3.4 line. So in our case we simply connect our sensor to P3.4 and let the 8051 do the work. Then, when we want to know how many cars have passed, we just read the value of timer 0 registers TL0 and TH0. This value of timer 0 will be the number of wheels that have passed. If we expect more than 65535 pulses, then we would also need to take care of how many overflows have taken place, but this too is easy since the overflows are indicated by TF0 bit being set. This can also be programmed to cause an interrupt and hence the TF0 interrupt routine simply counts the number of overflows automatically. Each overflow would indicate that 65536 wheels have passed. For this setup, TR0 is set to 1 and the GATE is set to 0. Thus TMOD = xxxx0101, setting Timer 0 in 16-bit mode.
Initially the user has to register his details with the application for the first time. The user has to enter the first name, last name, gender, etc. he also has to enter the userID and password for login purpose. So, registered user can login directly to use this application by using userID and password. Once the user registers, then he can use his userID and password to login in future. If the login is successful then home screen gets open.
In the CNN method, the data is transmitted with a network so that it becomes two-dimensional data, which can produce linear operations and the weighting parameters on CNN that are different. In the CNN linear operation method using convolution operations, although the weight is not one dimensional in size, it transforms into four dimensions which are set of convolution kernels as shown in Figure 3. The dimensions of the weight on CNN are:
movement discovery that fuses a few imaginative instruments . In November 2015 Bhaskar Dey and Malay K. Kundu utilized the developing High-Efficiency Video Coding (HEVC)  standard for video pressure, guarantees up to half piece rate investment funds thought about against the best of pressure plans accessible today. While the pressure productivity of HEVC offers a one of a kind chance to ease the transmission capacity crunch, new techniques for include extraction specifically from packed video must be figured into the outline of quicker calculations. Be that as it may, most best in class (SoA) calculations work on uncompressed pictures with an autonomous foundation display for every (pixel-based strategies). In this manner, packed recordings must experience computationally concentrated pre-preparing to be totally de- compacted, asserting critical time and memory before the use of such calculations. Ongoing exhibitions with precision tantamount to those of pixel-based techniques are focused on. At long last, pixel esteem is spread away from plain sight model of a neighboring pixel when the pixel is observed to be a piece of the foundation. By utilizing pseudo code and the parameter esteems, we depict our strategy in full subtle elements and contrast it with other foundation subtraction methods . Moving articles are portioned from the foundation by utilizing movement location calculation. To execute this, take a picture as foundation at the time t, signified by I(t) to look at with the foundation picture indicated by B. In this, we can section out the items just by utilizing picture subtraction strategy for every pixel in I(t), take the pixel esteem indicated by P[I(t)] and subtract it with the comparing pixels on the foundation picture signified as P[B].
Ensemble inflow predictions are artificially generated to supplement scarcity of actual prediction data. The synthetic generation model developed by Nohara et al. (2017) is employed to generate ensemble inflow predictions in this study. In this method, a predicted value is generated by adding a value of prediction error that is artificially generated to the true value of inflow. Values of prediction error are generated by randomly sampling values from a probabilistic distribution which prediction errors are assumed to follow. Although one can assume several types of distributions such as normal distributions and log normal distributions as the candidate for the probabilistic distribution of prediction errors, a normal distribution is employed in this study for a fundamental case study of impact assessment on preliminary release operation considering ensemble predictions. Values of prediction error are then generated by randomly sampling values from the assumed normal distribution. When the ensemble mean error and spread are considered as the parameters of prediction errors, those parameters can be controlled by changing the values for the mean and variance of the normal distribution of prediction errors. The generation of an ensemble inflow prediction sequence is conducted by use of the following method. Firstly, a value is randomly sampled for the prediction error of an ensemble member for the next time step (l=1). A series of prediction errors is then generated using a first-order autoregressive (AR(1)) model, which can be described as the following equations (Tokutsu et al., 2016):