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In this paper, an inhomogeneous human body model was presented to investigate the propagation characteristics when the human body was used as an antenna to achieve signal transmission. Specifically, the channel gain of four scenarios, namely, (1) both TX electrode and RX electrode were placed in the air, (2) TX electrode was attached on the human body, and RX electrode was placed in the air, (3) TX electrode was placed in the air, and RX electrode was attached on the human body, (4) both the TX electrode and RX electrode were attached on the human body, were studied through numerical simulation in the frequency range 1 MHz to 90 MHz. Furthermore, the comparisons of input efficiency, accepted efficiency, total efficiency, absorption power of human body, and electric field distribution of different distances of four aforementioned scenarios were explored when the frequency was at 44 MHz. In addition, the influences of different human tissues, electrode position, and the distance between electrode and human body on the propagation characteristics were investigated respectively at 44 MHz. The results showed that the channel gain of Scenario 4 was the maximum when the frequency was from 1 MHz to 90 MHz. The propagation characteristics were almost independent of electrode position when the human body was using as an antenna. However, as the distance between TX electrode and human body increased, the channel gain decreased rapidly. The simulations were verified by experimental measurements. The results showed that the simulations were in agreement with the measurements. [ABSTRACT FROM AUTHOR]

The paper presents a numerical energy harvesting model for sensor nodes, SIVEH (Simulator I-V for EH), based on I-V hardware tracking. I-V tracking is demonstrated to be more accurate than traditional energy modeling techniques when some of the components present different power dissipation at either different operating voltages or drawn currents. SIVEH numerical computing allows fast simulation of long periods of time--days, weeks, months or years--using real solar radiation curves. Moreover, SIVEH modeling has been enhanced with sleep time rate dynamic adjustment, while seeking energy-neutral operation. This paper presents the model description, a functional verification and a critical comparison with the classic energy approach. [ABSTRACT FROM AUTHOR]

Sensor network simulations require high fidelity and timing accuracy to be used as an implementation and evaluation tool. The cycle-accurate and instruction-level simulator is the known solution for these purposes. However, this type of simulation incurs a high computation cost since it has to model not only the instruction level behavior but also the synchronization between multiple sensors for their causality. This paper presents a novel technique that exploits asynchronous simulations of interrupt service routines (ISR). We can avoid the synchronization overheads when the interrupt service routines are simulated without preemption. If the causality errors occur, we devise a rollback procedure to restore the original synchronized simulation. This concept can be extended to any instruction-level sensor network simulator. Evaluation results show our method can enhance the simulation speed up to 52% in the case of our experiments. For applications with longer interrupt service routines and smaller number of preemptions, the speedup becomes greater. In addition, our simulator is 2 to 11 times faster than the well-known sensor network simulator. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of estimating and tracking time-varying direction-of-arrivals (DoAs) with an antenna array. A sequential DoA estimation method is proposed by extending the capon and sparse iterative covariance-based estimation (C-SPICE) method, which is an iterative off-grid method for estimating constant DoAs. Then, a moving average initialization technique is introduced such that the spatial spectrum information estimated in this snapshot can be utilized in the next one. In uniform linear arrays (ULAs), we replace the uniform grid in direction domain with that in a "frequency" domain, to improve estimation accuracy without additional complexity in practical applications. The validity and efficiency of the proposed methods are demonstrated through numerical experiments. [ABSTRACT FROM AUTHOR]

This paper proposes a portable hand haptic system using Leap Motion as a haptic interface that can be used in various virtual reality (VR) applications. The proposed hand haptic system was designed as an Arduino-based sensor architecture to enable a variety of tactile senses at low cost, and is also equipped with a portable wristband. As a haptic system designed for tactile feedback, the proposed system first identifies the left and right hands and then sends tactile senses (vibration and heat) to each fingertip (thumb and index finger). It is incorporated into a wearable band-type system, making its use easy and convenient. Next, hand motion is accurately captured using the sensor of the hand tracking system and is used for virtual object control, thus achieving interaction that enhances immersion. A VR application was designed with the purpose of testing the immersion and presence aspects of the proposed system. Lastly, technical and statistical tests were carried out to assess whether the proposed haptic system can provide a new immersive presence to users. According to the results of the presence questionnaire and the simulator sickness questionnaire, we confirmed that the proposed hand haptic system, in comparison to the existing interaction that uses only the hand tracking system, provided greater presence and a more immersive environment in the virtual reality. [ABSTRACT FROM AUTHOR]

Recently, ocean exploration has increased considerably through the use of autonomous underwater vehicles (AUV). A key enabling technology is the precision of the AUV navigation capability. In this paper, we focus on understanding the limitation of the AUV navigation system. That is, what are the observable error-states for different maneuvering types of the AUV? Since analyzing the performance of an underwater navigation system is highly complex, to answer the above question, current approaches use simulations. This, of course, limits the conclusions to the emulated type of vehicle used and to the simulation setup. For this reason, we take a different approach and analyze the system observability for different types of vehicle dynamics by finding the set of observable and unobservable states. To that end, we apply the observability Gramian approach, previously used only for terrestrial applications. We demonstrate our analysis for an underwater inertial navigation system aided by a Doppler velocity logger or by a pressure sensor. The result is a first prediction of the performance of an AUV standing, rotating at a position and turning at a constant speed. Our conclusions of the observable and unobservable navigation error states for different dynamics are supported by extensive numerical simulation. [ABSTRACT FROM AUTHOR]

A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency difference between the driving mode and the detection mode is less than 1 Hz, and the offset of the input DC is smaller than 0.6 V. The optimal proportionality factor and integral coefficient are 1.5 and 20, respectively. The fuzzy PI controlling technology provides a good way for the parameter optimization to gain modal matching of micro gyro, via which the detecting accuracy and stability can be improved greatly. [ABSTRACT FROM AUTHOR]

In general, mechanical equipment such as cars, airplanes, and machine tools all operate with constant frequency characteristics. These constant working characteristics should be controlled if the dynamic performance of the equipment demands improvement or the dynamic characteristics is intended to change with different working conditions. Active control is a stable and beneficial method for this, but current active control methods mainly focus on vibration control for reducing the vibration amplitudes in the time domain or frequency domain. In this paper, a new method of dynamic frequency characteristics active control (DFCAC) is presented for a flat plate, which can not only accomplish vibration control but also arbitrarily change the dynamic characteristics of the equipment. The proposed DFCAC algorithm is based on a neural network including two parts of the identification implement and the controller. The effectiveness of the DFCAC method is verified by several simulation and experiments, which provide desirable results. [ABSTRACT FROM AUTHOR]

This paper presents a framework of incremental 3D cuboid modeling by using the mapping results of an RGB-D camera based simultaneous localization and mapping (SLAM) system. This framework is useful in accurately creating cuboid CAD models from a point cloud in an online manner. While performing the RGB-D SLAM, planes are incrementally reconstructed from a point cloud in each frame to create a plane map. Then, cuboids are detected in the plane map by analyzing the positional relationships between the planes, such as orthogonality, convexity, and proximity. Finally, the position, pose, and size of a cuboid are determined by computing the intersection of three perpendicular planes. To suppress the false detection of the cuboids, the cuboid shapes are incrementally updated with sequential measurements to check the uncertainty of the cuboids. In addition, the drift error of the SLAM is compensated by the registration of the cuboids. As an application of our framework, an augmented reality-based interactive cuboid modeling system was developed. In the evaluation at cluttered environments, the precision and recall of the cuboid detection were investigated, compared with a batch-based cuboid detection method, so that the advantages of our proposed method were clarified. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) is becoming increasingly popular due to its numerous applications. This is especially evident in games, medicine, education, and other areas that support our everyday activities. Moreover, this kind of computer system not only improves our vision and our perception of the world that surrounds us, but also adds additional elements, modifies existing ones, and gives additional guidance. In this article, we focus on interpreting a reality-based real-time environment evaluation for informing the user about impending obstacles. The proposed solution is based on a hybrid architecture that is capable of estimating as much incoming information as possible. The proposed solution has been tested and discussed with respect to the advantages and disadvantages of different possibilities using this type of vision. [ABSTRACT FROM AUTHOR]

In determining rockfall trajectories in the field, it is essential to calibrate and validate rockfall simulation software. This contribution presents an in situ device and a complementary Local Positioning System (LPS) that allow the determination of parts of the trajectory. An assembly of sensors (herein called rockfall sensor) is installed in the falling block recording the 3D accelerations and rotational velocities. The LPS automatically calculates the position of the block along the slope over time based on Wi-Fi signals emitted from the rockfall sensor. The velocity of the block over time is determined through post-processing. The setup of the rockfall sensor is presented followed by proposed calibration and validation procedures. The performance of the LPS is evaluated by means of different experiments. The results allow for a quality analysis of both the obtained field data and the usability of the rockfall sensor for future/further applications in the field. [ABSTRACT FROM AUTHOR]

RSS-based localization is considered a low-complexity algorithm with respect to other range techniques such as TOA or AOA. The accuracy of RSS methods depends on the suitability of the propagation models used for the actual propagation conditions. In indoor environments, in particular, it is very difficult to obtain a good propagation model. For that reason, we present a cooperative localization algorithm that dynamically estimates the path loss exponent by using RSS measurements. Since the energy consumption is a key point in sensor networks, we propose a node selection mechanism to limit the number of neighbours of a given node that are used for positioning purposes. Moreover, the selection mechanism is also useful to discard bad links that could negatively affect the performance accuracy. As a result, we derive a practical solution tailored to the strict requirements of sensor networks in terms of complexity, size and cost. We present results based on both computer simulations and real experiments with the Crossbow MICA2 motes showing that the proposed scheme offers a good trade-off in terms of position accuracy and energy efficiency. [ABSTRACT FROM AUTHOR]

An improved method which considers the use of Fourier and wavelet transform based analysis to infer and extract 3D information from an object by fringe projection on it is presented. This method requires a single image which contains a sinusoidal white light fringe pattern projected on it, and this pattern has a known spatial frequency and its information is used to avoid any discontinuities in the fringes with high frequency. Several computer simulations and experiments have been carried out to verify the analysis. The comparison between numerical simulations and experiments has proved the validity of this proposed method. [ABSTRACT FROM AUTHOR]

In this study, a hybridized neuro-genetic optimization methodology realized by embedding numerical simulations trained artificial neural networks (ANN) into a genetic algorithm (GA) is used to optimize the flow rectification efficiency of the diffuser element for a valveless diaphragm micropump application. A higher efficiency ratio of the diffuser element consequently yields a higher flow rate for the micropump. For that purpose, optimization of the diffuser element is essential to determine the maximum pumping rate that the micropump is able to generate. Numerical simulations are initially carried out using CoventorWare® to analyze the effects of varying parameters such as diffuser angle, Reynolds number and aspect ratio on the volumetric flow rate of the micropump. A limited range of simulation results will then be used to train the neural network via back-propagation algorithm and optimization process commence subsequently by embedding the trained ANN results as a fitness function into GA. The objective of the optimization is to maximize the efficiency ratio of the diffuser element for the range of parameters investigated. The optimized efficiency ratio obtained from the neuro-genetic optimization is 1.38, which is higher than any of the maximum efficiency ratio attained from the overall parametric studies, establishing the superiority of the optimization method. [ABSTRACT FROM AUTHOR]

In order to precisely determine the magnesium level in a titanium reduction retort by inductive methods, many interfering influences have to be considered. By using a look-up-table method, the magnesium level can be reliably identified by taking into account the interfering effects of the titanium sponge rings forming at the walls with their unknown geometrical and electrical parameters. This new method uses a combination of numerical simulations and measurements, whereby the simulation model is calibrated so that it represents the experimental setup as closely as possible. Previously, purely theoretical studies on this method were presented. Here, the practical feasibility of that method is demonstrated by performing measurements on a model experiment. The method is not limited to the production of titanium but can also be applied to other applications in metal production and processing. [ABSTRACT FROM AUTHOR]