Software-based Simulation Research Articles

Simulation and real-life implementation of UAV autonomous landing system based on object recognition and tracking for safe landing in uncertain environments

The use of autonomous Unmanned Aerial Vehicles (UAVs) has been increasing, and the autonomy of these systems and their capabilities in dealing with uncertainties is crucial. Autonomous landing is pivotal for the success of an autonomous mission of UAVs. This paper presents an autonomous landing system for quadrotor UAVs with the ability to perform smooth landing even in undesirable conditions like obstruction by obstacles in and around the designated landing area and inability to identify or the absence of a visual marker establishing the designated landing area. We have integrated algorithms like version 5 of You Only Look Once (YOLOv5), DeepSORT, Euclidean distance transform, and Proportional-Integral-Derivative (PID) controller to strengthen the robustness of the overall system. While the YOLOv5 model is trained to identify the visual marker of the landing area and some common obstacles like people, cars, and trees, the DeepSORT algorithm keeps track of the identified objects. Similarly, using the detection of the identified objects and Euclidean distance transform, an open space without any obstacles to land could be identified if necessary. Finally, the PID controller generates appropriate movement values for the UAV using the visual cues of the target landing area and the obstacles. To warrant the validity of the overall system without risking the safety of the involved people, initial tests are performed, and a software-based simulation is performed before executing the tests in real life. A full-blown hardware system with an autonomous landing system is then built and tested in real life. The designed system is tested in various scenarios to verify the effectiveness of the system. The code is available at this repository: https://github.com/rnjbdya/Vision-based-UAV-autonomous-landing.

Reliability Enhancement of a Double-Switch Single-Ended Primary Inductance–Buck Regulator in a Wind-Driven Permanent Magnet Synchronous Generator Using a Double-Band Hysteresis Current Controller

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of (D (1+D)/(1−D). where D is the regulator transistor’s on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance.

Efficient Attacks on Strong PUFs via Covariance and Boolean Modeling

The physical unclonable function (PUF) is a widely used hardware security primitive. Before hacking into a PUF-protected system, intruders typically initiate attacks on the PUF as the first step. Many strong PUF designs have been proposed to thwart non-invasive attacks that exploit acquired CRPs. In this work, we propose a general framework for efficient attacks on strong PUFs by investigating from two perspectives, namely, statistical covariances in the challenge space and the design dependency among PUF compositions. The framework consists of two novel attack methods against a wide range of PUF families, including XOR APUFs, interpose PUFs, and bistable ring (BR)-PUFs. It can also exploit the knowledge of reliability information to improve attack efficiency with gradient optimization. We evaluate our proposed attacks through extensive experiments, running both software-based simulation and hardware implementations on FPGAs to compare with corresponding SOTA works. Considerable effort has been made in ensuring identical software/hardware conditions for a fair comparison. The results demonstrate that our framework significantly outperforms SOTA results. Moreover, we show that our framework can efficiently attack diverse PUF families built from entirely different types, while almost all existing works solely focused on attacking one or very limited number of PUF designs.

End-Users Know Best: Identifying Undesired Behavior of Alexa Skills Through User Review Analysis

The Amazon Alexa marketplace has grown rapidly in recent years due to third-party developers creating large amounts of content and publishing directly to a skills store. Despite the growth of the Amazon Alexa skills store, there have been several reported security and usability concerns, which may not be identified during the vetting phase. However, user reviews can offer valuable insights into the security & privacy, quality, and usability of the skills. To better understand the effects of these problematic skills on end-users, we introduce ReviewTracker, a tool capable of discerning and classifying semantically negative user reviews to identify likely malicious, policy violating, or malfunctioning behavior on Alexa skills. ReviewTracker employs a pre-trained FastText classifier to identify different undesired skill behaviors. We collected over 700,000 user reviews spanning 6 years with more than 200,000 negative sentiment reviews. ReviewTracker was able to identify 17,820 reviews reporting violations related to Alexa policy requirements across 2,813 skills, and 131,855 reviews highlighting different types of user frustrations associated with 9,294 skills. In addition, we developed a dynamic skill testing framework using ChatGPT to conduct two distinct types of tests on Alexa skills: one using a software-based simulation for interaction to explore the actual behaviors of skills and another through actual voice commands to understand the potential factors causing discrepancies between intended skill functionalities and user experiences. Based on the number of the undesired skill behavior reviews, we tested the top identified problematic skills and detected more than 228 skills violating at least one policy requirement. Our results demonstrate that user reviews could serve as a valuable means to identify undesired skill behaviors.

Effectiveness and safety of the simulation-based first-dose design of voriconazole

BackgroundWe investigated whether the initial voriconazole (VRCZ) dosing design, as determined using simulation software with a population pharmacokinetic model of Japanese patients, impacts the effectiveness and safety when compared with VRCZ initiation according to the package insert. MethodsIn this single-center retrospective observational study, we employed records from Tosei General Hospital (a 633-bed hospital), dated April 2017 to September 2023. Eligible patients were divided into the software-based simulation group, comprising patients administered initial VRCZ dosage adjustment by pharmacists using software-based simulation, and the standard therapy group, whose dosage was administered by a physician following the package insert recommendations without simulation. The primary objective of this study was to determine the efficacy of VRCZ first-dose design in reducing the incidence of hepatotoxicity and visual symptoms. ResultsThe median ages of enrolled participants (n=93) were 75 (68–79) and 72 (65–78) years in the software-based simulation and standard therapy groups, respectively. Regardless of formulation, initial trough concentrations were lower in the VRCZ software-based first dosage adjustment group and higher rate within the appropriate range (1–4 μg/mL) . The incidence of all-grade hepatotoxicity or visual symptoms was significantly lower in the software-based simulation group. The log-rank test revealed a significant impact on the occurrence of ≥grade 2 hepatotoxicity in the software-based first dosage adjustment group compared to that in the standard therapy group. ConclusionsThe initial VRCZ dosing design using simulation software improved the achievement of appropriate initial trough concentrations and resulted in fewer occurrences of hepatotoxicity (≥grade 2) when compared with the standard therapy.

Transient modelling and simulation of a switched reluctance machine in different operating modes

An appropriate numerical computational method and simplest model captures the performance of Switched Reluctance Machines (SRMs). Several papers and computer software-based simulation models are reported in the literature. Each model has its own merits and demerits. This paper proposes a mathematical model, based on a combination of voltage and mechanical equations, suitable for the transient running of a switched reluctance machine. The simulation results of current, torque and speed profile of SRM are produced under current chopping control and voltage pulse width modulation control. The proposed work has used experimental data of flux linkage and static torque in the mathematical model for best performance and control of the machine. The obtained simulation results are verified with experimental results. This model can be extended to a range of rotor position where the machine can be switched at decreased and increased inductance region which gives motoring and generating operation mode.

Mesoporous TiO2-layer’s rheological impact on the perovskite solar cell performance

The rheological impact of the mesoporous-TiO2 (m-TiO2) layer was investigated, which impacted perovskite solar cell (PSC) performance. This also implies the significance of morphological variations according to the pastes’ viscosity and corresponding thickness that cause a slight influence on their bandgap and hence device photovoltaic performance. The m-TiO2 paste results in a viscosity of 2.85 cP with a thickness of 1 μm, indicating the bandgap of ∼ 3.55 eV. In contrast, the higher viscous paste (3.85 cP) exhibits a slightly enhanced bandgap of ∼ 3.64 nm, leading to a thickness of > 1 μm. Besides, the data obtained from these analyses were used for cell performance analysis through the SCAPS 3.3 software-based simulation with a predicted power conversion efficiency of 23.59 %. It was observed that the PSC’s short circuit current density and the thickness of the m-TiO2 layer are inversely proportional, whereas the open-circuit voltage shows an independent effect on m-TiO2 viscosity. This study envisages an initial trade-off between the m-TiO2 layer’s porosity, bandgap and thickness that can ensure the PSC with improved performance parameters.

Moving Horizon Estimation for Digital Twins using Deep Autoencoders

Digital twins have emerged in recent years as black-box, software-based simulation tools that can mirror the behavior of complex dynamical systems. Digital twin simulations generate the same outputs as the target system using internal states; however, these states are not readily available online from the real system. In this paper, we develop a data-driven moving horizon estimation framework capable of using online noisy measurements of the real system in order to estimate digital twin states. Our framework combines the high expressiveness of deep autoencoders with a moving horizon state estimator that accurately predicts the internal state of the black-box digital twin without access to an analytical model of the system dynamics. We demonstrate that our approach outperforms extended and Koopman Kalman filter solutions on a benchmark reverse van der Pol oscillator example.

Software-Based Simulation on a 3D Environment for Vaccination Teaching and Learning: Design Science Research.

Student training requires specific laboratories for vaccination practice, which are usually limited, and even professionals' continuing education regularly lacks proper care. Thus, new methodologies, concepts, and technologies, such as software-based simulations, are in highly demand. This work aims to develop a 3D virtual environment to support teaching activities in the vaccination room. The software-based simulation must contribute positively to teaching considering a variable set of scenarios. We applied the design science research method to guide the work. First, the concepts and opportunities were raised, which we used to build the simulation (ie, the proposed technological artifact). The development was assisted by a specialist, in which we sought to create a vaccination room according to Brazilian standards. The artifact evaluation was achieved in 2 stages: (1) an evaluation to validate the design with experts through the Delphi method; and (2) a field evaluation with nursing students to validate aspects of usability (System Usability Scale [SUS]) and technology acceptance and use (Unified Theory of Acceptance and Use of Technology version 2). We built the simulation software using the Unity game engine. An additional module was also developed to create simulation scenarios and view the students' performance reports. The design evaluation showed that the proposed solution is adequate. Students' evaluations confirm good usability (SUS score of 81.4), besides highlighting Performance Expectation as the most positively influential factor of Behavioral Intention. Effort Expectancy is positively affected by younger users. Both evaluation audiences cited the high relevance of the proposed artifact for teaching. Points for improvement are also reported. The research accomplished its goal of creating a software-based simulation to support teaching scenarios in the vaccination room. The evaluations still reveal desirable improvements and user behavior toward this kind of technological artifact.

Combining Artificial Intelligence and Image Processing for Diagnosing Diabetic Retinopathy in Retinal Fundus Images

Retinopathy is an eye disease caused by diabetes, and early detection and treatment can potentially reduce the risk of blindness in diabetic retinopathy sufferers. Using retinal Fundus images, diabetic retinopathy can be diagnosed, recognized, and treated. In the current state of the art, sensitivity and specificity are lacking. However, there are still a number of problems to be solved in state-of-the-art techniques like performance, accuracy, and being able to identify DR disease effectively with greater accuracy. In this paper, we have developed a new approach based on a combination of image processing and artificial intelligence that will meet the performance criteria for the detection of disease-causing diabetes retinopathy in Fundus images. Automatic detection of diabetic retinopathy has been proposed and has been carried out in several stages. The analysis was carried out in MATLAB using software-based simulation, and the results were then compared with those of expert ophthalmologists to verify their accuracy. Different types of diabetic retinopathy are represented in the experimental evaluation, including exudates, micro-aneurysms, and retinal hemorrhages. The detection accuracies shown by the experiments are greater than 98.80 percent.

Software-based simulation to analyze the variation of digital modulation and atmospheric condition on the free space optic (FSO) link performance

Free Space Optic (FSO) is the solution for telecommunications technology that offers high data rates, wide bandwidth, and low power consumption. However, to maximize the performance of the FSO system, the modulation used should be considered in environmental conditions. This study aims to compare the performance of the FSO communication link based on digital modulation variations used in various weather conditions, including sunny, rainy, and foggy weather. This study uses two attenuation models, namely the Kim and Kruse models, with variations in transmission distance from 500 meters to 10 kilometers. Modulation variations used include QPSK, 8-PSK, 16-PSK, and 16-QAM at 10 Gbps bitrate. The simulation is accomplished using OptiSystem 17.0 software. The study results show that sunny weather (very clear) has the best visibility compared to rain and fog conditions with an attenuation value of 0.46 dB/km on the Kim and Kruse models. QPSK modulation has the best performance with a BER value of less than 1x10-12 up to a transmission distance of 8 km in sunny weather, 3 km in rainy weather (medium rain), and 800 m in foggy (moderate fog) weather. The 8-PSK modulation has a BER value of less than 1x10-12 with a range of 2000 m in sunny weather and 1500 m in rainy weather but does not meet the standards in foggy weather conditions. 16-PSK and 16-QAM modulation have above baseline BER values ​​during rainy and foggy conditions, but 16-QAM modulation still has a BER value of less than 1x10-3 during foggy conditions at a distance of 500 m.

Design and Experimentation Guidelines for DER’s Emulation Testbed

Due to the increasing integration of distributed energy resources (DERs) into the national grid, research is needed to understand high DER penetration in relation to grid reliability and stability. Emulation-based research is a viable option to consider hardware intensive investigations. Indeed, DER emulation-based research has advantages over DER software-based simulation and real DER implementation research. Some of these advantages are more realistic performance and boundaries and considerably less expense, higher safety, and modularity. While the downside of DER emulation-based research is the complexity of modeling large scale grid systems. This paper provides a rationalization for the selection of an emulation-based DER laboratory and description of the DER laboratory's capabilities. Additionally, guidelines for running experiments are discussed and two approaches, power scaling using rescaling coefficients and system sizing using Multi-Port Thevenin Equivalence (MPTE), are proposed to emulate realistic complex interconnected DER grid connected systems.

Self-Powered Artificial Mechanoreceptor Based on Triboelectrification for a Neuromorphic Tactile System.

A self‐powered artificial mechanoreceptor module is demonstrated with a triboelectric nanogenerator (TENG) as a pressure sensor with sustainable energy harvesting and a biristor as a neuron. By mimicking a biological mechanoreceptor, it simultaneously detects the pressure and encodes spike signals to act as an input neuron of a spiking neural network (SNN). A self‐powered neuromorphic tactile system composed of artificial mechanoreceptor modules with an energy harvester can greatly reduce the power consumption compared to the conventional tactile system based on von Neumann computing, as the artificial mechanoreceptor module itself does not demand an external energy source and information is transmitted with spikes in a SNN. In addition, the system can detect low pressures near 3 kPa due to the high output range of the TENG. It therefore can be advantageously applied to robotics, prosthetics, and medical and healthcare devices, which demand low energy consumption and low‐pressure detection levels. For practical applications of the neuromorphic tactile system, classification of handwritten digits is demonstrated with a software‐based simulation. Furthermore, a fully hardware‐based breath‐monitoring system is implemented using artificial mechanoreceptor modules capable of detecting wind pressure of exhalation in the case of pulmonary respiration and bending pressure in the case of abdominal breathing.

Simulation-based validation of activity logger data for animal behavior studies

Bio-loggers are widely used for studying the movement and behavior of animals. However, some sensors provide more data than is practical to store given experiment or bio-logger design constraints. One approach for overcoming this limitation is to utilize data collection strategies, such as non-continuous recording or data summarization that may record data more efficiently, but need to be validated for correctness. In this paper we address two fundamental questions—how can researchers determine suitable parameters and behaviors for bio-logger sensors, and how do they validate their choices? We present a methodology that uses software-based simulation of bio-loggers to validate various data collection strategies using recorded data and synchronized, annotated video. The use of simulation allows for fast and repeatable tests, which facilitates the validation of data collection methods as well as the configuration of bio-loggers in preparation for experiments. We demonstrate this methodology using accelerometer loggers for recording the activity of the small songbird Junco hyemalis hyemalis.

Use of a Team-Based Video Simulation to Complement a Lecture in Motivational Interviewing to Develop Students' Initial Attitudes and Skills.

Background: Motivational interviewing (MI) is increasingly recognized for its patient-centered approach to clinician-patient communication and often effective in evoking appropriate changes in patient behavior. Doctor of Pharmacy (PharmD) programs are increasingly incorporating MI education; however, doing so represents a challenge regarding availability of both time and labor capital. Case Description: This study reports on the use of a 90-minute software-based simulation and tutorial coupled with a 90-minute lecture in a 3-hour course session. In a subsequent session consisting of several brief interactions with standardized patients (SPs), students reflected upon their strengths and challenges as a result of attempting to apply the MI principles they learned during the educational intervention. Case Themes: Students' responses to a questionnaire delivered both before and after the simulation and lecture, showed improvements in several attitudinal components related to use of MI, as well as developing self-efficacies in deploying patient-centered communication strategies. A post-intervention survey without students' opportunity to study/prepare saw gains in student knowledge about MI. Case Impact: The measurements employed to determine student's attitude and knowledge showed good to very good internal consistency reliably based on calculated Cronbach's alpha and KR-20. Student reflections indicated their understanding of MI principles, even though they fell short of implementing them in large part during their encounters with SPs. Conclusion: Use of a video simulation undergone by teams of PharmD students coupled with a brief lecture might be an effective and efficient way of building a foundation for MI competency among PharmD students where instructors might lack labor capital and significant space in the curriculum.

Photovoltaic and Thermoelectric Generator Combined Hybrid Energy System with an Enhanced Maximum Power Point Tracking Technique for Higher Energy Conversion Efficiency

In this paper, the design and performance investigation of the hybrid photovoltaic–thermoelectric generator (PV–TEG) system with an enhanced fractional order fuzzy logic controller (FOFLC)-based maximum power point tracking (MPPT) technique is presented. A control strategy of the variable incremental conduction (INC) method is employed using FOFLC for the MPPT control technique to efficiently harvest the maximum power from the PV module. The fractional factor α used in the MPPT control algorithm is a supporting fuzzy logic controller (FLC) for the accurate tracking of the maximum power point (MPP) and to maintain the constant output after reaching the MPP. In the proposed system configuration, the TEG is mounted with the PV panel for generating the extra electrical power using the waste heat energy produced on the PV panel due to the incident solar irradiation. The PV and TEG are connected electrically in series to increase output voltage level and thereby improve the power output. The hybrid energy module has better energy conversion efficiency when compared to the standalone PV array. The performance of the proposed MPPT technique is studied for the PV–TEG hybrid energy module under various thermal and electrical operating conditions using a MATLAB software-based simulation. The results of the FOFLC-based MPPT technique are compared with the conventional perturb and observe (P&O) and FLC-based P&O methods. The proposed MPPT technique confirms its effectiveness in extracting the maximum power in terms of speed and accuracy. Moreover, the PV and TEG combined system provides higher energy efficiency than the individual PV module.

TeamSTEPPS online simulation: expanding access to teamwork training for medical students

BackgroundThe Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) programme is an evidence-based approach to teamwork training. In-person education is not always feasible for medical student education....

A Survey on Simulation for Weight Perception in Virtual Reality

Virtual reality (VR) technology can provide users with an immersive experience as if they are in the real world, which can be applied in the fields of entertainment, education and scientific research, etc. In order to improve the sense of presence and immersion in VR, the design of multimodal feedback is an important component. In particular, the simulation of weight of virtual objects poses many challenges due to the limitations of hardware and software. Many researchers focused on this issue in various ways. These methods are mainly divided into two categories: device-based simulation and software-based simulation. This paper investigates the focus of software-based simulation, particularly for the virtual feedback methods proposed by researchers in recent years. We introduce the background of these proposed methods, technical implementation principles, application scenarios, the advantages and disadvantages of these simulation methods, and the evaluation criteria. We also propose the future challenges and the development of simulation methods for weight perception of virtual objects in VR.

Combined software and hardware fault injection vulnerability detection

Fault injection is a well-known method to test the robustness and security vulnerabilities of software. Software-based and hardware-based approaches have been used to detect fault injection vulnerabilities. Software-based approaches typically rely upon simulations that can provide broad and rapid coverage, but may not correlate with genuine hardware vulnerabilities. Hardware-based experiments are indisputable in their results, but rely upon expensive expert knowledge and manual testing yielding ad hoc and extremely limited results. Further, there is very limited connection between software-based simulation results and hardware-based experiments. This work bridges software-based and hardware-based fault injection vulnerability detection by contrasting results of both approaches. This demonstrates that: not all software-based vulnerabilities can be reproduced in hardware; prior conjectures on the fault model for electromagnetic pulse attacks may not be accurate; and that there is a co-relation between software-based and hardware-based approaches. Further, combining both approaches can yield a vastly more accurate and efficient approach to detecting genuine fault injection vulnerabilities.

Analysis of thermoluminescence characteristics of a lithium disilicate glass ceramic using a nonlinear autoregressive with exogenous input model.

Dental ceramics because of their translucency exemplify the most biologically realistic restorative materials for aesthetic rehabilitation and can be used to estimate dose accumulated as a result of a nuclear accident or attack. In this study, lithium disilicate ceramic obtained from Vivadent Ivoclar, Turkey was studied for its thermoluminescence (TL) properties. The lithium disilicate glass ceramic was irradiated with a 90 Sr-90 Y β-source from 10 Gy to 6.9 kGy and the results read on a Harshaw 3500 reader. The TL peak of lithium disilicate ceramic showed sublinearity in the range 12 Gy to 6 kGy. The area under the TL glow curve increased by about 25% by the end of 10th measurement cycle. Fading values were also considered after irradiation. Lithium disilicate ceramic samples underwent 37% fading after 1 h and 59% fading after 1 week. In addition to the experimental study, a software-based simulation study was also undertaken using a MATLAB system identification tool. Experimental studies are generally time consuming and some materials used for experiments are very expensive. In this study, experimental, and simulation results were compared and produced almost the same outcome with a similarity of more than 98%.