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We test an approach to modelling the car driver behaviour during simulated lane changing tasks, aiming to obtain a sufficiently precise model in the simplest possible form, namely, with a small number of parameters. Various applications of such models are available in the literature. Based on a recent review of the research to date, the cybernetic single-loop transfer function models employing McRuer’s theory are applied. The purpose of the presented method is to evaluate the optimal structure of the transfer function via cross-validation as a technique known from machine learning. The experiments utilize a driving simulator with in-house developed software; this configuration facilitates acquiring the data at the desired sampling frequency and in a manner that ensures the repeatability of the test process scenarios. Using the cross-validation results, we evaluate the second-order model with a derivative state and a reaction delay component as an optimal structure for approximating the measured data, which originated from a set of measurements on 92 active drivers. Even though more complex driving tasks could require high-order models, driver’s control action during our specific experiment is described through only four parameters. The parameters are jointly determined by the current driver’s mental state and the testing conditions defined in our scenario. Since the parameters are related to his/her dynamical behaviour, they allow easier mutual comparison of the drivers than complex models with many parameters. The results are verified via establishing a relationship to the multi-loop model presented in the recent literature. The larger dataset enables evaluating the confidence intervals of the drivers’ parameters which is inconvenient with 4 to 10 drivers commonly presented in the relevant sources.

Ensuring reliable data transmission in all Vehicular Ad-hoc Network (VANET) segments is paramount in modern vehicular communications. Vehicular operations face unpredictable network conditions which affect routing protocol adaptiveness. Several solutions have addressed those challenges, but each has noted shortcomings. This work proposes a centralised-controller multi-agent (CCMA) algorithm based on Software-Defined Networking (SDN) and Delay-Tolerant Networking (DTN) principles, to enhance VANET performance using Reinforcement Learning (RL). This algorithm is trained and validated with a simulation environment modelling the network nodes, routing protocols and buffer schedules. It optimally deploys DTN routing protocols (Spray and Wait, Epidemic, and PRoPHETv2) and buffer schedules (Random, Defer, Earliest Deadline First, First In First Out, Large/smallest bundle first) based on network state information (that is; traffic pattern, buffer size variance, node and link uptime, bundle Time To Live (TTL), link loss and capacity). These are implemented in three environment types; Advanced Technological Regions, Limited Resource Regions and Opportunistic Communication Regions. The study assesses the performance of the multi-protocol approach using metrics: TTL, buffer management,link quality, delivery ratio, Latency and overhead scores for optimal network performance. Comparative analysis with single-protocol VANETs (simulated using the Opportunistic Network Environment (ONE)), demonstrate an improved performance of the proposed algorithm in all VANET scenarios.

The trustworthiness of nodes in Vehicular Ad-Hoc Networks (VANETs) is essential for disseminating truthful event messages. False messages may cause vehicles to behave in unintended ways, creating an unreliable transportation system. The efficiency and reliability of the transportation system can be obtained through trustworthy vehicular nodes providing correct event messages. In a VANET, the consensus issue can be resolved by employing blockchain. Even if we employ blockchain in a VANET, the trustworthiness of each message recorded needs to be verified separately since the blockchain itself does not guarantee the trust level of each event message. For instance, when there are multiple conflicting messages associated with a single accident on the road, a vote based on majority opinion can be considered one option for making a decision regarding the accident. In this work, we design the VANET event message clustering algorithm (VEMCA) to resolve the conflicting message problem. Furthermore, we develop a simulator for the VANET environment that demonstrates how the clustering algorithm can be used for event message validation. Experimental results show that our algorithm outperforms state-of-the-art clustering algorithms in terms of accuracy, precision, recall, f1-score, and computational time.

Radio Frequency Identification (RFID) technology is becoming very popular in the new era of Industry 4.0, especially for warehouse management, retails, and logistics. RFID systems can be used for objects identification, localization, and tracking, facilitating everyday operators’ efforts. However, the deployment of RFID tags and reader antennas in real-world application scenarios is crucial and takes time. Indeed, deciding where to place tags and/or readers’ requires examining many conditions. If some weaknesses appear in the design, the arrangement must be reconsidered. The proposed work presents a novel open-source RFID simulator that allows modeling environments and testing the deployment of RFID tags and antennas apriori. In such a way, validating the performance of the localization or tracking algorithms in simulation, possible weaknesses that could arise may be fixed before facilities are applied on the field. Any number of tags and antennas can be placed in any position in the created scenario, and the simulator provides the phase and the RSSI signals for each tag. Every reader antenna is parametrized so that different antennas of different vendors can be reproduced. The simulator is implemented as a plugin of Gazebo, a widely used robotic framework integrated with the Robot Operating System (ROS), to reach a broad audience. In order to validate the simulator, a warehouse scenario is modeled, and a tag localization algorithm that uses the phase unwrapping technique and hyperbolae intersection method employing a reader antenna mounted on a mobile robot is used to estimate the position of the tags deployed in the scenario. The outcomes of the experiments showed realistic results.

Design-space exploration for low-power manycore design is a daunting and time-consuming task which requires some complex tools and frameworks to achieve. In the presence of process variation, the problem becomes even more challenging, especially the time associated with trial-and-error selection of the proper options in the tools to obtain the optimal power dissipation. The key contribution of this work is the novel use of machine learning to speed up the design process by embedding the tool expertise needed for low power design-space exploration for manycores into a trained neural network. To enable this, we first generate a large volume of data for 36000 benchmark applications by running them under all possible configurations to find the optimal one in terms of power. This is done using our own tool called LVSiM, a holistic manycore optimization program including process variations. A neural network is trained with this information to build in the expertise. A second contribution of this work is to define a new set of features, relevant to power and performance optimization, when training the neural network. At design time, the trained neural network is used to select the proper options on behalf of the user based on the features of any new application. However, one problem encountered with this approach is that the database constructed for machine learning has many outliers due to randomness associated with process variation which creates a major headache for classification - the supervised learning task performed by neural networks. The third key contribution of this work is a novel data coercion algorithm used as a corrective measure to handle the outliers. The proposed data coercion scheme produces results that are within 3.9% of the optimal power consumption compared to 7% without data coercion. Furthermore, the proposed method is about an order of magnitude faster than a heuristic approach and two orders of magnitude faster than a brute-force approach for design-space exploration.

When a stretchable display is stretched, the area of the exposed substrate between the light-emitting diodes (LEDs) increases, decreasing the image luminance. Currently, this problem is not addressed in existing high-resolution display systems. Although the mean-based method and gamma correction method using general image processing techniques, which are first presented in this paper, can compensate for the decrease in luminance, these methods cannot be adaptively applied for stretchable display systems. Therefore, this paper proposes a novel image compensation method optimized for stretchable displays. The proposed distribution density-aware method (DDAM) compensates for the decrease in luminance particularly for the area involving the newly exposed substrate. The DDAM solves the saturation problem associated with the mean-based method and the problem of inaccurate luminance estimation associated with the gamma correction method. Compared with the mean-based method and the gamma correction method, the peak signal-to-noise ratio of the DDAM is 0.600 dB and 1.977 dB higher, respectively. The structural similarity index measure is also 0.055 and 0.057 higher, respectively. In addition, we develop a novel simulator to evaluate the stretching of high-pixel-per-inch displays, which are being actively researched, and use it to verify the performance of above mentioned luminance reduction compensation methods.

Radio-frequency-based noncooperative monitoring of humans has numerous applications ranging from law enforcement to ubiquitous sensing applications such as ambient assisted living and biomedical applications for nonintrusively monitoring patients. Large training datasets, almost unlimited memory capacity, and ever-increasing processing speeds of computers could drive forward the data-driven deep-learning-focused research in the abovementioned applications. However, generating and labeling large volumes of high-quality, diverse radar datasets is an onerous task. Furthermore, unlike the fields of vision and image processing, the radar community has limited access to databases that contain large volumes of experimental data. Therefore, in this article, we present an open-source motion capture data-driven simulation tool, SimHumalator, that can generate large volumes of human micro-Doppler radar data in passive WiFi scenarios. The simulator integrates IEEE 802.11 WiFi Standards (IEEE 802.11 g, n, and ad) compliant transmissions with the human animation data to generate the micro-Doppler features that incorporate the diversity of human motion characteristics and the sensor parameters. The simulated signatures have been validated with experimental data gathered using an in-house-built hardware prototype. This article describes simulation methodology in detail and provides case studies on the feasibility of using simulated micro-Doppler spectrograms for data augmentation tasks. [ABSTRACT FROM AUTHOR]

Objective: A simulator for retrobulbar anesthesia administration mimicking the orbital anatomy and providing tactile sensation is proposed. Methods: The production process involves 3D modeling of anatomical structures on the basis of computerized tomography (CT) images, printing the models using a 3D printer, and casting the silicone. Twenty ophthalmologists administered retrobulbar anesthesia using the simulator with four different ocular axial lengths (including extreme myopes); the position of the needle tip was evaluated. The effectiveness of this simulator for training was also surveyed. Results: The proportions of the final location of the needle tip were 59.25%, 36.25%, and 4.5% for the retrobulbar space, peribulbar space, and intraocular space, respectively. Experienced ophthalmologists showed lower complication rates than residents (0.5% vs 8.5%, $P < 0.001$ ) and agreed that this simulator will help young ophthalmologists advance their anesthesia-administering skills. Discussion/Conclusion: The 3D-printered simulator for retrobulbar anesthesia was produced and performance was verified. The technology could be used to simulate critical orbital anatomic features and could be used as a training tool for resident ophthalmologists.

A significant quantity of space-borne Global Navigation Satellite Systems-Reflectometry (GNSS-R) data over land was made available in the last decade, leading to an increasing interest in the assessment of the potentialities of this new remote sensing technique for land monitoring. In this frame, an electromagnetic simulator, such as the Soil And VEgetation Reflection Simulator (SAVERS), has the key role to support the understanding of the physical mechanism involved in the bistatic scattering and to identify the surface features mainly contributing to the observed signal. Originally developed for ground and airborne GNSS-R observations over homogeneous areas, in this study, SAVERS was upgraded to account for space-borne systems. The new version of SAVERS takes into account the inhomogeneity characterizing the large area observed from space altitudes, due to a variable surface elevation and land cover. Coherent and incoherent scattering and polarization rotation are computed taking into account the local slope and elevation of the surface. The simulator was validated against TechDemoSat-1 observations over a bare surface with a complex topography and over a forested surface with a gentle topography. The validation results show the capability of SAVERS to correctly estimate the effect of the topography, enhancing the understanding of the observations. Moreover, it was found that the sensitivity to soil moisture is independent of the topography (about 1.5 dB for a 10% variation of soil moisture). Whereas a saturation of the GNSS-R reflectivity over a variable topography is reached for lower values of biomass, earlier than in the flat case.

Nowadays, the space missions employing the global navigation satellite system reflectometry (GNSS-R) are UK TDS-1, NASA CYGNSS, and the Chinese BuFeng-1A/B twin satellites, part of the first Chinese global navigation satellite system reflectometry (GNSS-R) satellite mission. They provide delay-Doppler map (DDM) measurements reflected from the land as well as the ocean. Using land reflected DDMs, several studies have been conducted to retrieve land geophysical parameters, such as soil moisture and biomass. Despite the clear dependence on these parameters, many other parameters impact the DDMs as well, such as topography, surface roughness, etc. The impact of these perturbing factors must be analyzed, and modeled in various conditions. This article presents a comprehensive end-to-end simulator that can generate synthetic DDMs reflected over land. It is an extension of a previously developed simulator validated for ocean applications. This simulator is very generic, and it includes numerous configurable parameters such as arbitrary scattering geometry (transmitter and receiver positions and speeds), arbitrary GPS and Galileo transmitted signals and frequencies, GNSS-R instrument antenna and receiver errors, as well as surface topography, roughness, soil moisture, vegetation cover, etc. The sensitivities of GNSS-R observables with respect to soil moisture and vegetation are obtained and compared to previous experimental results, and synthetic DDMs are compared and validated against TDS-1 ones.

Dynamic wireless charging (DWC) is an attractive technology which can significantly extend the mileage of electric vehicles. However, experimental evaluation on a DWC system is often implemented at high costs due to the requirement on a movable platform. To address this problem, this article proposes a receiver-side-oriented DWC simulator characterized with wide speed range, compact size, flexible configurations, and controllable testing conditions. First, the emulated I-type multiphase receiver system and its basic operating characteristics are introduced. Then, the fundamental principle employing receiver-induced voltage equivalence and an implementation for a DQ-phase receiver DWC system are demonstrated. Further, movable platform experiments and circuit simulations are conducted to verify the accuracy of the simulator at full-range driving speeds. Finally, application demonstrations for operating the simulator are presented to show the feasibility and flexibility. [ABSTRACT FROM AUTHOR]

This paper aimed to develop an IoT-based X-ray educational simulator (IoT-based dental education and learning: IDEAL) and establish a dental X-ray education system that allows students in dentistry colleges or dental hygiene departments to obtain a quality education without radiation exposure. A simulator that has a shape and operating motion range similar to those of intraoral X-ray machines widely used in clinical settings were created. Angle sensors were installed inside the cone and detector to enable the user to monitor rotation angles in these areas. Information regarding measured angles was sent to servers through wired telecommunications or a network, and it was analyzed and used as evidence to determine whether the user placed the patient in a suitable posture and position to take X-ray images. This paper demonstrated that this dental X-ray simulator can provide safe X-ray practical training without the risk of radiation exposure and that it can be used in many dental hygiene education settings in the future.

Fog computing is a paradigm that extends the cloud to intermediate network devices with computational and storage capacities. This allows the execution of applications closer to edge devices and end-users by allocating services in those intermediate devices. The placement of those services has an influence on the performance of the fog architecture. We propose a fog computing simulator for analyzing the design and deployment of applications through customized and dynamical strategies. We model the relationships among deployed applications, network connections, and infrastructure characteristics through complex network theory, enabling the integration of topological measures in dynamic and customizable strategies, such as the placement of application modules, workload location, and path routing and scheduling of services. We present a comparative analysis of the efficiency and the convergence of results of our simulator with the most referenced one, iFogSim. To highlight the YAFS functionalities, we model three scenarios that, to the best of our knowledge, cannot be implemented with current fog simulators: dynamic allocation of new application modules, dynamic failures of network nodes, and user mobility along with the topology.

Cost overruns and schedule delays are pervasive in complex projects despite the use of systems engineering and traditional project management models and tools. These disciplines can often work in isolation leading to inconsistencies in product information, tracking of design changes, and challenges in decision-making. While the literature proposes theoretical approaches to integrating these disciplines, there does not appear to be a practical approach offered. In response, this article presents a management flight simulator that represents a digital twin of set-based design, design change, knowledge, and agile project management practices. It integrates discipline-specific submodels through key linkages that are derived from the intrinsic properties of a system case study and intangible assets such as knowledge, communication, culture, and process maturity. It captures the techno-socio-economic and cultural factors involved in design change decisions and project management. The simulator provides immediate feedback on whether a change is going to help or disrupt design integrity through the monitoring of system attribute trends and cues. It also provides the impact on lifecycle management curves using a system dynamics submodel. From this feedback, several system, policy, and process levers are available within the simulator for what-if scenarios with the goal to improve product, organizational, and project performance. [ABSTRACT FROM AUTHOR]

With the advent of big data applications and new process technologies, Process-in-Memory (PIM) attracts much attention in memory research as the architecture studies gradually shift from processors to heterogeneous aspects. How to achieve reliable and efficient PIM architecture modeling becomes increasingly urgent for the researchers, who want to experiment on critical issues from detailed implementations of their proposed PIM designs. This paper proposes PIMSim, a full-system and highly-configurable PIM simulator to facilitate circuit-, architecture- and system-level researches. PIMSim enables architectural simulation of PIM and implements three simulation modes to provide a wide range of speed/accuracy tradeoffs. It offers detailed performance and energy models to simulate PIM-enabled instructions, compiler, in-memory processing logic, various memory devices, and PIM coherence. PIMSim is open source and available at https://github.com/vineodd/PIMSim. [ABSTRACT FROM AUTHOR]

Reliable electromagnetic simulators are of prime importance for the design of radar sounder instruments and for supporting the subsequent analysis of their data. In this paper, we present a coherent, facet method-based simulator that can compute radar echoes from the subsurface of a target area with an arbitrary number of geological layers, thus going beyond the surface-only or the two-layer descriptions so far implemented in coherent ray-tracing radar sounder simulators. Propagation of fields throughout the subsurface is computed according to Snell’s law following a ray-tracing approach. For each ray interacting with the surface, be it a direct reflection or a refracted ray coming from the subsurface, the phase contribution of each facet is calculated through the linear phase approximation, while the total field received at the antenna is computed using Huygen’s principle. Validation simulations have been performed against the radar data of lunar and martian areas characterized by a multilayer nature and collected by the Lunar Radar Sounder instrument of JAXA’s Kaguya lunar probe and the Shallow Radar instrument onboard NASA’s Mars Reconnaissance Orbiter, respectively. Results confirm the effectiveness of the proposed simulator. [ABSTRACT FROM AUTHOR]

We develop and evaluate a respiratory rate (RR) estimation algorithm that utilizes data from the pressure-sensitive mat (PSM) technology for continuous patient monitoring in neonatal intensive care units. An analysis of the random effect of drift and systematic effect of creep in the PSM data is presented, showing that these are essentially dependent on the applied load and contact surface. Uncertainty measurements are pivotal when estimating physiologic parameters. The standard uncertainty in the PSM data is here represented by the percent drift. Next, we evaluate the applicability of the PSM technology to estimate RR in neonatal patient simulator trials under five mixed effects including internally and externally induced motion, mattress type, grunting, laying position, and different breathing rates. We analyze the limits of agreement on the mixed effects model to derive the uncertainty in the estimated RR obtained through two estimation techniques. In comparison with the gold standard RR values, we achieved a mean bias of 0.56 breaths per minute (bpm) with an error bounded by a 95% confidence interval of [−2.26, 3.37] bpm. These results meet the clinical accuracy requirements of RR within ±5 bpm. [ABSTRACT FROM AUTHOR]

In the past decade Global Navigation Satellites System Reflectometry (GNSS-R) has emerged as a new technique for earth remote sensing for various applications, such as ocean altimetry and sea state monitoring. After the success of the GNSS-R demonstrator payloads aboard the UK-DMC or TDS-1 satellites; at present, there are several missions planned to carry GNSS reflectometers. The GNSS rEflectometry, Radio Occultation, and Scatterometry onboard International Space Station (GEROS-ISS) is an innovative ISS experiment exploiting GNSS-R technique to measure key parameters of ocean, land, and ice surfaces. For GEROS-ISS mission, the European Space Agency (ESA) supported the study of GNSS-R assessment of requirements and consolidation of retrieval algorithms (GARCA). For this, it was required to accurately simulate the GEROS-ISS measurements including the whole range of parameters affecting the observation conditions and the instrument, which is called GEROS-SIM. To meet these requirements, the PAU/PARIS end-to-end performance simulator (P^2EPS) previously developed by UPC BarcelonaTech was used as the baseline building blocks for the level 1 (L1) processor of GEROS-SIM. P ^2EPS is a flexible tool, and is capable of systematically simulating the GNSS-R observations for spaceborne GNSS-R missions. Thanks to the completeness and flexibility, the instrument-to-L1 data module of GEROS-SIM could be implemented by proper modification and update of P ^2EPS. The developed GEROS-SIM was verified and validated in the GARCA study as comparing to the TDS-1 measurements. This paper presents the design, implementation, and results of the GEROS-SIM L1 module in a generic way to be applied to GNSS-R instruments. [ABSTRACT FROM PUBLISHER]

WiSE-Mnet++ is a holistic simulator that abstracts the key functions of smart-camera networks and models the main operations to account for hardware capabilities, the complexities of visual data, and their associated high-data-rate communication. [ABSTRACT FROM AUTHOR]

Toward a maritime surveillance objective, many ship detection and tracking algorithms have been investigated but are faced with poor performance in practical ocean environments. Compact high-frequency (HF) radar has also faced critical issues due to its long coherent processing interval and varying response from its orthogonal antenna structure. Hence, a simulator based on compact HF radar is proposed in this letter to provide a guideline for effective assessment of ship detection and tracking algorithms while considering these practical issues. To validate the proposed simulator, the simulator generated data has been compared with real data obtained by the compact HF radar sites. [ABSTRACT FROM PUBLISHER]

PowerShift-Atlantic (PSA) is a pilot project lead by Canadian Maritime utilities that demonstrates direct load control strategies for up to 20 MW of commercial and residential loads for the purpose of balancing the intermittency of renewable generation and supporting demand-side management programs. On the residential side, domestic electric water heaters (DEWHs) form a significant end use class. The ability to accurately estimate and predict the state of individual end use devices allows aggregated control systems to better ensure end-use performance and comfort levels. This paper presents a methodology for estimating and predicting the state of individual DEWHs from models of their thermodynamics and water consumption that are derived under two scenarios: 1) when measurements of both power consumption and water temperature are available; and 2) when only measurements of power consumption are available. The proposed methodology was implemented as part of the PSA pilot project for the DEWH load class to simulate the behavior of the load in presence of the controller and evaluate the performance of the controller. Experimental results show that the model and water usage profile mimic the actual behavior of DEWHs, and can predict the future power consumption when the thermostatic control of a DEWH is interrupted as part of a load control strategy. [ABSTRACT FROM PUBLISHER]

Heterogeneous Computing is a promising direction to address the challenges of performance and power walls in high-performance computing, where CPU-FPGA architectures are particularly promising for application acceleration. However, the development of such architectures associated with optimal memory hierarchies is challenging due to the absence of an integrated simulator to support full system simulation and architectural exploration. In this work, we present HeteroSim, a full system simulator supporting x86 multi-cores integrated with an FPGA via bus connection. It can support fast architectural exploration with respect to number of cores, number of accelerated kernels on FPGA, and different memory hierarchies between CPU and FPGA. Various performance metrics are returned for further performance analysis and architectural configuration optimization. [ABSTRACT FROM PUBLISHER]

With scaling technology, emerging nonvolatile devices, and data-intensive applications, memory faults have become a major reliability concern for computing systems. With various hardware and software approaches proposed to address this issue, a comprehensive evaluation is required to understand the effectiveness of these solutions. Considering the complex nature of various memory faults as well as interactions between various correction mechanisms, we propose MEMRES, a fast main memory system reliability simulator. It enables memory fault simulation with error-correcting code (ECC) algorithms and modern memory reliability management, including memory page retirement, mirroring, scrubbing, and hardware sparing. MEMRES is computationally efficient in obtaining memory failure probabilities in the presence of multiple failure mechanisms and complex correction scheme, allowing the optimization of memory system reliability, the prediction of emerging memory reliability, and designing a reliability enhancement technique. The accuracy of MEMRES is verified by an existing analytical model and an existing memory fault simulator. We performed a case study on spin-transfer torque random access memory (STT-RAM)-based main memory, and the results indicate that in-memory ECC can significantly mitigate the write error rate of STT-RAM, demonstrating the capability of handling emerging memory system. [ABSTRACT FROM PUBLISHER]

Objective: Like all scientific research, computational neuroscience research must be reproducible. Big data science, including simulation research, cannot depend exclusively on journal articles as the method to provide the sharing and transparency required for reproducibility. Methods: Ensuring model reproducibility requires the use of multiple standard software practices and tools, including version control, strong commenting and documentation, and code modularity. Results: Building on these standard practices, model-sharing sites and tools have been developed that fit into several categories: 1) standardized neural simulators; 2) shared computational resources; 3) declarative model descriptors, ontologies, and standardized annotations; and 4) model-sharing repositories and sharing standards. Conclusion: A number of complementary innovations have been proposed to enhance sharing, transparency, and reproducibility. The individual user can be encouraged to make use of version control, commenting, documentation, and modularity in development of models. The community can help by requiring model sharing as a condition of publication and funding. Significance: Model management will become increasingly important as multiscale models become larger, more detailed, and correspondingly more difficult to manage by any single investigator or single laboratory. Additional big data management complexity will come as the models become more useful in interpreting experiments, thus increasing the need to ensure clear alignment between modeling data, both parameters and results, and experiment. [ABSTRACT FROM PUBLISHER]

This paper presents a simulator to help electrical engineering students and professionals in the learning process. The proposed tool embodies Virtual Reality technologies on the improvement of understanding equipment maneuvers in distribution power systems. The tool has a virtual didactic distribution network in which the students handle several real tasks related to operation and maintenance of distribution network through applied technology. We hope that this tool can contribute to develop and improve professional skills in engineering at a low cost and furthermore it supports laboratory and associated technical activities. [ABSTRACT FROM PUBLISHER]

In this work, we present a Simulator Program that identifies the topologies and supports operation staff in decision-making about loads reassignments and changes in electric network, offering a selection of the best settings. Facing a contingency situation or action of relocation of electrical system of subtransmission lines, the Simulator considers the current state and uses special algorithms that detect the current network topology, interprets results and presents for operation the possible different maneuvers with their respective degrees of reliability. For these actions the software Simulator elaborates the states investigation of circuit breakers and electric keys, analysis of load flow, makes risk prediction and the mathematical analysis of remote sensing values. The software Simulator uses in some of his actions, special algorithms that are based on Paraconsistent Annotated Logic (PAL), which is a non-classical logic whose main property is to accept contradiction in their fundamentals. These algorithms based on PAL offer greater speed of processing and allows the Paraconsistent Simulator of topologies (ParaSimTop) to be implemented in real time. [ABSTRACT FROM PUBLISHER]

The urban traffic network has temporal and spatial characteristics whose changing conditions have often unpredictable effects on the flow of loads that include passengers and freight. As a result, the current traffic network is unbalanced, leading to high and low peaks of traffic in both time and space. The freight transportation chain can utilize these high and low peaks in the road and rail network in order to utilize more effectively available capacity. The purpose of this paper is to develop a coordinated multimodal dynamic freight load balancing (MDFLB) system to balance freight loads across the rail and road network. The MDFLB system collects and updates information from all the shipping companies and assigns freight loads to the available carriers using an optimization model while taking into account current and predicted dynamical changes in the associated networks. Since the freight loads can change the assumed states of the network, namely, the link travel times, which could then render the solution of the optimization problem no longer optimum, an iterative approach is considered involving online network simulation models. The simulation models are used to test and modify the optimization-based load balancing solution and estimate the new states of the network used by the optimizer. This feedback iterative approach guarantees that the overall cost function is non-increasing and it stops when it converges to a minimum or when a stopping criterion is satisfied depending on the time horizon of interest. A simulation case study that focuses on distribution of freight in an area that includes the two major sea ports in Southern California is used to demonstrate the effectiveness of the proposed coordinated MDFLB. [ABSTRACT FROM PUBLISHER]

This paper presents the design, development, and preliminary evaluation of a computer-based system capable of simulating the consequences of several eye diseases in human vision. The system consists of a video camera, a computer, and a virtual reality (VR) helmet. Real-time image processing techniques are applied to the camera's video signal and the result is projected on the VR helmet. Upon the use of filters or masks, users can experience eye pathologies such as glaucoma, hemianopsia, macular degeneration, retinitis pigmentosa, among others. The system was validated by qualified experts and evaluated by healthy sighted in tasks such as reading and mobility. Results obtained allowed users to develop a greater awareness of the nature of visual impairments. The system is also intended to be used as a technological platform for testing assistive devices for visually impaired people. [ABSTRACT FROM PUBLISHER]

With the advent of web programming languages the so called web applications are emerging, applications that run directly from your browser, without installing additional plug-ins. A major advantage of web applications is the fact that they are multiplatform, offering the possibility of running on smartphones and tablets, technologies that are more and more present in day-to-day lives. And due to the constantly expanding of the power electronics theme, largely due to increased use of switching power supplies in electronic products today, a web application to connect web applications and power electronics was developed. An application that calculates parameters of Buck converters and plots information relevant to it to the user in a simple and easy way. [ABSTRACT FROM PUBLISHER]

Bioimpedance measurements on the human thorax are suitable for assessment of body composition or hemodynamic parameters, such as stroke volume; they are non-invasive, easy in application and inexpensive. When targeting personal healthcare scenarios, the technology can be integrated into textiles to increase ease, comfort and coverage of measurements. Bioimpedance is generally measured using two electrodes injecting low alternating currents (0.5–10 mA) and two additional electrodes to measure the corresponding voltage drop. The impedance is measured either spectroscopically (bioimpedance spectroscopy, BIS) between 5 kHz and 1 MHz or continuously at a fixed frequency around 100 kHz (impedance cardiography, ICG). A thorax simulator is being developed for testing and calibration of bioimpedance devices and other new developments. For the first time, it is possible to mimic the complete time-variant properties of the thorax during an impedance measurement. This includes the dynamic real part and dynamic imaginary part of the impedance with a peak-to-peak value of 0.2 \Omega and an adjustable base impedance (24.6 \Omega \geq Z0 \geq 51.6 {\Omega}). Another novelty is adjustable complex electrode-skin contact impedances for up to 8 electrodes to evaluate bioimpedance devices in combination with textile electrodes. In addition, an electrocardiographic signal is provided for cardiographic measurements which is used in ICG devices. This provides the possibility to generate physiologic impedance changes, and in combination with an ECG, all parameters of interest such as stroke volume (SV), pre-ejection period (PEP) or extracellular resistance (Re) can be simulated. The speed of all dynamic signals can be altered. The simulator was successfully tested with commercially available BIS and ICG devices and the preset signals are measured with high correlation (r = 0.996). [ABSTRACT FROM PUBLISHER]