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Determining the optimal location of a switching center in a tree network of users is accurately modeled by the median problem. A real-time approach is used in this paper to investigate the dynamics of such a communication network in two cases: (1) a growing tree of nodes associated with equal demand rates, and (2) a stream of corrections that arbitrarily change the demand rates at the nodes. The worst-case analysis performed in both situations clearly demonstrates the importance of parallelism in such real-time paradigms. It is shown that the error generated by the best sequential algorithm in the first case can be arbitrarily large. A synergistic behavior is revealed when the quality-up is investigated in the second case.

Traditionally, interest in parallel computation centered around the speedup provided by parallel algorithms over their sequential counterparts. In this paper, we ask a different type of question: Can parallel computers, due to their speed, do more than simply speed up the solution to a problem? We show that for real-time optimization problems, a parallel computer can obtain a solution that is better than that obtained by a sequential one. Specifically, a sequential and a parallel algorithm are exhibited for the problem of computing the best-possible approximation to the minimum-weight spanning tree of a connected, undirected and weighted graph whose vertices and edges are not all available at the outset, but instead arrive in real time. While the parallel algorithm succeeds in computing the exact minimum-weight spanning tree, the sequential algorithm can only manage to obtain an approximate solution. In the worst case, the ratio of the weight of the solution obtained sequentially to that of the solution computed in parallel can be arbitrarily large.

Nowadays, computers are frequently equipped with peripherals that transfer great amounts of data between them and the system memory using direct memory access techniques (i.e., digital cameras, high speed networks, …). Those peripherals prevent the processor from accessing system memory for significant periods of time (i.e., while they are communicating with system memory in order to send or receive data blocks). In this paper we study the negative effects that I/O operations from computer peripherals have on processor performance. With the help of a set of routines (SMPL) used to make discrete event simulators, we have developed a configurable software that simulates a computer processor and main memory as well as the I/O scenarios where the peripherals operate. This software has been used to analyze the performance of four different processors in four I/O scenarios: video capture, video capture and playback, high speed network, and serial transmission.

A method to reduce the side effects of dual-line timed address-event (TAE) vision system is proposed in this paper. The side effects include edge discontinuity and the natural insensitivity to object edges in the motion direction. X-event, a kind of artificial event is introduced to represent light intensity difference perpendicular to the motion direction of the target object. New timestamps are attached to the raw TAE data to adjust temporary resolution to the same order of magnitude with the vertical axis in the TAE representation. After removing noisy and redundant events, designed templates are used to generate X-events to renovate broken lines and reproduce perpendicular edges. It is a real-time process which is unnecessary to wait for the collection of all the raw TAE data. A behavioral model of a 2 × 256 TAE vision sensor is established in Matlab, and X-events Generation block is realized in FPGA. Experimental results show that the proposed method can patch the TAE representation effectively to obtain a one-pixel-wide, precise, closed and connected contour.

We present the design and evaluation of a high-performance network-on-chip (NoC) focused on telecommunication and multimedia applications that tolerate latency and bandwidth variations. The design is based on a connectionless strategy in which flits from different communication flows are interleaved in the same communication channel. Each flit carries routing information that is used by routers to perform arbitration and scheduling of the corresponding output ports in order to balance channel utilization. In order to compare our approach with others, we introduce an analytic model for the worst-case latency (WCL) of our NoC and recall those of related approaches. Analytic comparisons and experimental data show that our approach keeps average WCL lower for variable-bit-rate multimedia applications than a network based on resource reservation. For these applications, the overall throughput is larger than that of networks that perform resource reservation. A case study based on the proposed NoC shows that the average latency was 28% lower than the WCL expected for the experiment. Indeed, hard real-time flows designed considering the absolute WCL of the network will always meet the requirements of the associated hard real-time tasks, so no deadline can be lost due to network contention.

Eliminating the Gibbs oscillations that occur during the Finite Impulse Response (FIR) digital filter design with the Fourier Series method will ensure correct filtering. For this reason, the development of the window improves the performance of the filter and, therefore, the system. In this study, the cosh window function is designed using Particle Swarm Optimization, which is a preferred optimization method in many areas. Thus, alternatives to the standard results obtained from the existing traditional calculations will be produced, and different windows that perform the same function will be obtained. In addition, exponential and cosh window functions were designed in LabVIEW environment, which is a graphical programming language-based program, and the designed windows were analyzed at different parameter values. LabVIEW provides a fast and easy programming environment, and it provides the opportunity to realize real-time applications with its external hardware. Utilizing this feature, the amplitude spectrum of cosh window designed in LabVIEW is displayed in real time for different window parameter values. As a result, FIR digital filters were designed using cosh window based on optimization and the cosh window designed in LabVIEW, and the distorted EEG signal was filtered using these filters and displayed in real time.

The proposed system provides an energy management method for various types of an energy storage system including cascade utilization battery. The method is used to receive, store and manage the relevant operating data from the energy storage battery and also randomly determine the energy distribution coefficient of the energy storage battery. According to the adaptive energy distribution method, the power value of the total distributed energy storage power to the cascade utilization energy is calculated and also the energy distribution coefficient of the energy storage battery in real time is adjusted. Finally, the corrected command value of the energy storage battery power is obtained as an output. The system can not only prevent overcharging and over-discharging of the energy storage system, but also maintain the good performance of the energy storage system. To realize the coordinated control and energy management of the battery power plant, we use multiple types, including conventional battery and cascade utilization power battery control purpose. The performance metrics, namely, real-time energy management, computational time and operating cost are employed for the experimental purpose. The simulation results show the superior performance of the proposed energy management system over other state-of-the-art methods.

In this paper, an online chatting system with an embedded real-time chaotic encryption/decryption method is designed for the Internet. Such system not only provides a real-time communication platform, but also ensures a secure channel for communication. By the use of cipher feedback and the skew tent map, the input text can be real-time encoded and the cipher text is sent via TCP/IP. With the properties of randomness of the map, and its sensitivity on system parameters and the initial conditions, the encrypted transmitting messages are difficult to be eavesdropped. The implemented method is simple and can be easily embedded in any existing systems.

Real-time (RT) object-oriented (OO) distributed computing is a form of RT distributed computing realized with a distributed computer system structured in the form of an object network. Several approaches proposed in recent years for extending the conventional object structuring scheme to suit RT applications, are briefly reviewed. Then the approach to RT OO distributed computing which the author and his collaborators have been establishing in recent years will be reviewed in more detail. The approach named the TMO (Time-triggered Message-triggered Object) structuring scheme was formulated with the goal of instigating a quantum productivity jump in the design of complex real-time computing systems (RTCS's). The TMO scheme is intended to facilitate the pursuit of a new paradigm in designing RTCS's which is to realize real-time computing with a common and general design style that does not alienate the main-stream computing industry and yet to allow system engineers to confidently produce certifiable RTCS's for safety-critical applications. The TMO structuring scheme is a syntactically simple but semantically powerful extension of the conventional object structuring approaches and as such, its support tools can be based on various well-established OO programming languages such as C++ and JAVA and on ubiquitous commercial RT operating system kernels. The scheme enables a great reduction of the designer's efforts in guaranteeing timely service capabilities of application systems. Also, the scheme is applicable to structuring of not only complex distributed RTCS's but also application environment descriptors/simulators and requirement specifications.

Spectral rendering, or the synthesis of images by taking into account the constituent wavelengths of white light, enables the rendering of iridescent colors caused by phenomena such as dispersion, diffraction, interference and scattering. Caustics, the focusing and defocusing of light through a refractive medium, can be interpreted as a special case of dispersion where all the wavelengths travel along the same paths. In this paper we extend Adaptive Caustic Mapping (ACM), a previously proposed caustics mapping algorithm, to handle physically-based dispersion. Because ACM can display caustics in real-time, it is amenable to extension to handle the more general case of dispersion. We also present a novel algorithm for filling in the gaps that occur due to discrete sampling of the spectrum. Our proposed method runs in screen-space, and is fast enough to display plausible dispersion phenomena at real-time and interactive frame rates.

Combination of numerical modeling and artificial intelligence (AI) in bioengineering processes are a promising pathway for the further development of bioengineering sciences. The objective of this work is to use Artificial Neural Networks (ANN) to reduce the long computational times needed in the analysis of shear stress in the Abdominal Aortic Aneurysm (AAA) by finite element methods (FEM). For that purpose two different neural networks are created. The first neural network (Mesh Neural Network, MNN) creates the aneurysm geometry in terms of four geometrical factors (asymmetry factor, aneurism diameter, aneurism thickness, aneurism length). The second neural network (Tension Neural Network, TNN) combines the results of the first neural network with the arterial pressure (new factor) to obtain the maximum stress distribution (output variable) in the aneurysm wall. The use of FEM for the analysis and design of bioengineering processes often requires high computational costs, but if this technique is combined with artificial intelligence, such as neural networks, the simulation time is significantly reduced. The shear stress obtained by the artificial neural models developed in this work achieved 95% of accuracy respect to the wall stress obtained by the FEM. On the other hand, the computational time is significantly reduced compared to the FEM.

Viability of cancer cell is an important indicator of physiological state and function of cells, which can be effected by the change of pH in the medium solution, due to the increase of carbon oxide and lactic acid caused by respiration. Although many methods have been developed to detect the viability of cells, mostly based on cytochemical staining and polymerase chain reaction (PCR) technology are time consuming. In this paper, an electronic device was made by thermal reduced graphene oxide (RGO) for detection of cancer cell viability in real-time. This electronic device could be used to monitor the metabolic activity and viability of cancer cells based on the change in pH value. As the pH decreases, colon cancer cells loose viability and the current decreases. This RGO device is simple, sensitive and label-free and could serve as a platform for detection of cells and drug testing.

The integration of Unmanned Aerial Vehicles (UAVs) is being proposed in a spectrum of applications varying from military to civil. In these applications, UAVs are required to safely navigate in real-time in dynamic and uncertain environments. Uncertainty can be present in both the UAV itself and the environment. Through a literature study, this paper first identifies, quantifies and models different uncertainty sources using bounding shapes. Then, the UAV model, path planner parameters and four scenarios of different complexity are defined. To investigate the effect of uncertainty on path planning performance, uncertainty in obstacle position and orientation and UAV position is varied between 2% and 20% for each uncertainty source first separately and then concurrently. Results show a deterioration in path planning performance with the inclusion of both uncertainty types for all scenarios for both A* and the Rapidly-Exploring Random Tree (RRT) algorithms, especially for RRT. Faster and shorter paths with similar same success rates (>95%) result for the RRT algorithm with respect to the A* algorithm only for simple scenarios. The A* algorithm performs better than the RRT algorithm in complex scenarios.

Electrophoretic mobility (EPM) measurement on biological particles in fluids is well established. The current method in measuring EPM is using laser which the target particles are not visible. Additional morphology information is critical for the EPM measurement. Image processing is a promising method to obtain the EPM together with the morphology information. In this study, a setup of micro electrophoresis system with a compact CCD microscope was constructed. This setup was equipped with image processing method for capturing the images of the moving particles in an electric field. With the image processing method (Horn–Schunck method), the images captured were processed in real time to obtain the EPM of the particle. Velocity of the particles was then measured and the particles’ EPM was obtained. With the captured images of the particles in real time, the system can present the image of the targeted particle together with the EPM value. The setup of this prototype was calibrated with discrete particles (Polystyrene microsphere size of 10$\mu$m$\pm$ 5%) and with a magnification value of 125X. This system is suitable for the surface charge measurement of discrete particle with size in between 4$\mu$m and 20$\mu$m. Comparison of commercialized device with our laboratory setup for calibration on EPM of polystyrene beads had a variance of solely 13%. Measurement on yeast cells, normal (hFob 1.19) and cancer bone cells (U2OS) indicated that the EPM of yeast became highly negative in the pH value of 4.5 and 6.5. The negative EPM of the cancer cell is slightly larger than that of the normal cell for pH ranging from 4.4 to 5.0. In conclusion, the real-time EPM measurement set up for this study is able to display the real-time images of the moving particles in fluid suspension during measurement.

Although progress of radiation therapy in recent years is rapid, medical accidents like the irradiation of over and under dose occur frequently in Japan. To eradicate these accidents and to increase accuracy of radiation therapy, we are developing an implantable real time micro dosimeter system. CdTe semiconductor is used as an ideal detector. And the doses of radiation are monitored by measuring the magnetic field converted from the current. We investigated the relationship between dose rate and current value from CdTe semiconductor(4mm×4mm×0.5mm). The data showed that 70 to 90 nA of electric current is proportionally generated from the CdTe semiconductor when it is irradiated by a LINAC under an air condition by the dose rate of 1 ~ 6Gy/min. In addition, the proportion of irradiated dose and the current was confirmed under a subaqueous condition(15cm in depth). To investigate the influence of a magnetic field on a human body, we calculated the tolerance frequency for human body using FEM simulation method. The data showed that the sending and receiving of data as a frequency of magnetic field should be set 100MHz or less. We are now miniaturizing the dosimeter circuit up to the size of inserted level by a fine needle.

Increasing integrated avionics electronic system makes integrated avionics system structure increasingly complex, makes the demand for network topology and dynamics performance increasingly urgent, and the robustness of the dynamics of the network is very important performance. In this paper, using complex networks and network dynamics as a theoretical basis, based on TTE and AFDX network topology, we establish an integrated avionics system network in dual bus architecture model, and use the maximum communication subgraph and percolation theory to analyze the robustness of non-weighted and weighted network model.