Engineering Commons^™

Mobile Robot Slam Simulation With Multi Measurement Update, Yafang Xu, Zuoleit Sun, Liansun Zeng, Zhang Bo

Journal of System Simulation

Abstract: Aiming at the problem of the accumulation of linearization error in the nonlinear system linearizing of Simultaneous Localization and Mapping (SLAM) in mobile robot, an algorithm named multi measurement update was put forward according to the analysis of Fisher information. In order to compute the state estimation after each measurement update, the Fisher information weight relationship between prediction variable and update variable was made use of Due to a number of data association with an estimation which was more close to the real data than the former, the algorithm could achieve a more accuracy posterior state. As a result, …

Indoor Positioning System Algorithm Based On Rfid, Xuejun Shi, Zhicheng Ji

Journal of System Simulation

Abstract: In order to solve the radio frequency identification (RFID) positioning problem, the working principle, advantages and disadvantages of two positioning methods (AOA and TDOA) were analyzed in detail by comparison, on the basis of which, an indoor positioning hybrid approach of Ultra High Frequency (UHF) RFID was proposed. This proposed approach took the AOA as the core and integrated the idea of time diference in TDOA. Moreover; the stepping motor and UHF reader were used simultaneously instead of antennas array to make UHF RFID reader whirl around an axis. Therefore, it is easy to scan each tag that can …

Application-Aware Cross-Layer Enrgy-Eficient Routing Scheme, Xu Fang, Hiyin Zhang, Wang Jing, Xu Ning, Zhijong Wang, Deng Min

Journal of System Simulation

Abstract: An aplication- aware cross-layer energy-effcient routing scheme (ACER) was presented to minimize the effect of supplt of terminals in ad hoc network composed of smart mobile devices. Features of energy consumption were sensed by application aware energy model with the application monitor and the remaining energy monitor. Stability of network path was monitored by link stability monitoring module in Data link layer. As the scheme used the idea of cross-layer design, network topology information, application-aware information in application layer and link-stability were utilized synthetically to make routing deisions in network layer;Simulations were crried out on NS2 platform. The …

Trnek Befor Detet Agoritmn For Weak Iret Based On Ergodic Hogh Tasform, Yunfei Guo, Xiaofeng Zheng, Dongliang Peng, Zebin Zeng

Journal of System Simulation

Abstract: The performance of track-before-detect (TBD) algorithm based on standard Hough Transform is not satisfied due to low detection probability and long elapsed time. For this problem, an Ergodic Hough Transform based TBD method was proposed. The raw radar echo whose amplitude exceeded the first threshold was stored separately and stacked into a data space; all diferent data were combined to calculate line parameter which then was mapped into a parameter space and the amplitude of each paired wae added to an accumulator. All cells whose amplitude exceeded the second threshold was used to estimate the last line parameter and …

Test Data Compression Based On Logical Operationand Dimidiate Partition, Wu Qiong, Huang Li

Journal of System Simulation

Abstract: A new test data compression based on logical operation and dimidiate partition was proposed. The whole test was partitioned to several length-fixed blocks. Then logical operation was applied into runs of Is or 0s or alternating bits. They were turned into all 0s. For the others, dimidiate partition technique was used until they got to the minimum length. The length of code words could be expressed by the times of dimidiate and it is easy to coding when they are turned into all 0s. Compared with traditional data-coding methods the depression structure is simple and reduced the costs of …

Study Of Improved Generalized Predictive Control In Ball Mill Application, Lingfang Sun, Jingmiao Sun

Journal of System Simulation

Abstract: Direct-fired pulverizing system with double inlets and outlets is regarded as important generating equipment in power plant, which has characteristics of nonlinear, multivariable, strong coupling and time-varying. Started from the mechanism of law, the mechanism mathematical model of the ball mill was established and a certain amount of disturbance transfer ftinction model was added in a mathematical model of the mechanism of input variables to give step disturbance tests to establish the ball mill system. Combining the most widely used basic control--PID control as industrial process control, and on the basis of general generalized predictive control algorithm, the generalized …

New Identify Based Proxy Signature Scheme, Xiaojing Hong, Bin Wang

Journal of System Simulation

Abstract: Proxy signature schemes allow a proxy signer to generate proxy signatures on behalf of an original signer. Mambo, et ah first introduced the notion of proxy signature and a lot of research work can be found on this topic nowadays. To simplify key management, many identity based proxy signature schemes were proposed. However, some existing schemes are vulnerable to proxy key exposure attack. It is necessary to propose a security model for identity based proxy signature schemes against proxy key exposure attack. Then an efficient scheme based on pairings was presented, which is provably secure in the random oracle …

Efficient Real-Time Traffic Signal Control Algorithm, Zhongcheng Yang, Ye Chen, Zhenyu Yang

Journal of System Simulation

Abstract: For real time taffic signal contol isus, a mathematical model was proposed to minimize the waiting ime, meanwhile a huristi search aigorihm was given to sove the optinal sluton Simulatin Tresuts show that the hcurisi scarceh algorim sufrfs fom being couataoalal complx and umstable, therefore, a multi sage decisin optimization algorihm is added, and the serehes adopt in all stages subject to a time limit, which ensures a stable and real-time algorithm, and also a soution in fixed time. Simulation resuts based on actal tafic data show that the waiting time can be reduced in comparison with that of …

Modeling Emergence Of Network Radar Countermeasure System, Huang Chen, Jianqing Qi, Fangzheng Liu

Journal of System Simulation

Abstract: Network radar countermeasure system (NRCS) is a new kind of integrated electronic warfare system with the integrated network developing trend of radar and EW equipment, and emergence is the typical complex feature of NRCS. The connotation and composition of the NRCS emergence was interpreted. Four sources of the NRCS emergence were analyzed: composition effect, structural effect, interaction effect and environmental effect. The conceptual models and mathematical models of the NRCS emergence were built from three aspects: system reconnaissance detection emergence, system target identification emergence and system jamming emergence. Simulation results coincide with the NRCS emergence source analysis, which verifies …

Simulation Of Energy Optimization For Cooling Coil In Central Air-Conditioning System, Qinglong Meng, Xiuying Yan

Journal of System Simulation

Abstract: The optimized control of minimizing energy consumption in one air-conditioning system was studied. The main models that needed in the simulation software HVACSIM+ for air handling unit were introduced. The AHU and rooms of the first floor of certain Building were taken as the simulation target. Then the function describing the relation between the consumption of cooling coil and the chilled water velocity was found and taken as the objective function. With improved cyclic variable method, the controller^ parameters were optimized. Results show that the simulation system runs steadily while the controller works with the optimal parameters, and the …

Gait Simulation Of Snake Robot Based On Cpg Method, Gao Qin, Zhelong Wang, Weijian Hu, Lanying Zhao

Journal of System Simulation

Abstract: Biological snakes in nature have a variety of periodic motion patterns such as serpentine motion, linear motion and lateral motion. Gaits diversity has greatly improved the adaptability of natural snakes to complex environment. Biologists has proved that such rhythmic movements of vertebrate animals are generated by CPG (the central neural pattern generator). Special mechanical structure of a snake robot with high degree offreedom and locomotion characteristics of different gaits was considered to bulid a suitale CPG network model. Hopf oscillators were chosen as neuron models of a central pattern generator owing to their stable features. A snake robot prototype …

Optimized Analysis Of Milling Thin-Wall Parts Based On Shell Element Models, Yusong Liao, Han Jiang

Journal of System Simulation

Abstract: As to milling the thin-wall part accurately, here with the finite element model composed of SHELL elements, the effects of lowering position, size of the part and cutting parameters to the deformations of the thin-wall part were analyzed and compared, and the corresponding theoretical analysis was provided. The conclusions can be got as; the model composed of SHELL elements can analyze the factors causing the deforroations of the thin-wall part and optimize the cutting method and cutting parameters effectively to improve the machining accuracy and efficiency.

Modeling And Simulation Of Traction System In Hybrid Shunting Locomotive, Kun Shen, Wang Ling, Wang Jian, Xiaoyang Yao

Journal of System Simulation

Abstract: The structure of traction system in hybrid shunting locomotive was analyzed, and the working principles of traction system under multiform power models were introduced. Based on which, the models of traction system and power accumulators of this hybrid shunting locomotive were built by MATLAB/Simulink, then the simulation experiments on hybrid shunting locomotive with the power models of hybrid power, and pure diesel generator power or pure accumulator power were done respectively. The simulation results show that hybrid shunting locomotive can achieve reliable operation in diflFerent conditions by the designed main circuit structure, parameters and system energy management strategy.

Impact Of Number Of Solar Cells In Parallel/Series And Temperature On Junction Capacitance, Zhigang Zhao, Chunjie Zhang, Gao Pu, Hutang Sang, Xiaoqian Li

Journal of System Simulation

Abstract: The study to the dynamic parameters of the photovoltaic cell is of crucial importance for the design of the corresponding afterward stage controller in the photovoltaic power generation system. Beginning with the analysis to physical mechanism of the photovoltaic cell, more accurate equivalent formulation of the junction voltage and bias voltage of the photovoltaic cells /module/array was deduced, and the explicit formulation between the bias voltage and output voltage was received by using the Lambert W function based on equivalent series resistance and the saturation current. The formulation was adopted which combined the engineering mathematics model and intrinsic carrier …

Evaluation And Analysis Of New Method Of Measurement Of Target Scattering Matrix, Zhenyu Huang, Zhao Bo, Huanyao Dai, Liandong Wang, Xuequan Zhou

Journal of System Simulation

Abstract: The basic theory of radar polarization signal processing is measurement of the target scattering matrix. The current algorithm of measurement of the target scattering matrix is gotten through orthogonal dual polarization channel in time-sharing or simultaneously, which demands orthogonal polarization measurement signals with complex coding. The measuring accuracy is higher. The complexity and the cost of the system are relatively higher. Scattering matrix can also be obtained by making use of the spatial polarization characteristics of the antenna to processing the radar echo without structure reformation of the radar. It only. needs to renewal measurement technology. The comparison and …

Deep Learning Methods For Fingerprint-Based Indoor And Outdoor Positioning, Fahad Alhomayani

Electronic Theses and Dissertations

Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold:

First, a Convolutional Neural Network (CNN)-based method for …

Wind Turbine Parameter Calibration Using Deep Learning Approaches, Rebecca Mccubbin

Electronic Theses and Dissertations

The inertia and damping coefficients are critical to understanding the workings of a wind turbine, especially when it is in a transient state. However, many manufacturers do not provide this information about their turbines, requiring people to estimate these values themselves. This research seeks to design a multilayer perceptron (MLP) that can accurately predict the inertia and damping coefficients using the power data from a turbine during a transient state. To do this, a model of a wind turbine was built in Matlab, and a simulation of a three-phase fault was used to collect realistic fault data to input into …

Deep Learning For High-Impedance Fault Detection: Convolutional Autoencoders, Khushwant Rai, Firouz Badrkhani Ajaei, Farnam Hojatpanah, Katarina Grolinger

Electrical and Computer Engineering Publications

High-impedance faults (HIF) are difficult to detect because of their low current amplitude and highly diverse characteristics. In recent years, machine learning (ML) has been gaining popularity in HIF detection because ML techniques learn patterns from data and successfully detect HIFs. However, as these methods are based on supervised learning, they fail to reliably detect any scenario, fault or non-fault, not present in the training data. Consequently, this paper takes advantage of unsupervised learning and proposes a convolutional autoencoder framework for HIF detection (CAE-HIFD). Contrary to the conventional autoencoders that learn from normal behavior, the convolutional autoencoder (CAE) in CAE-HIFD …

Simplification Of Robotics Through Autonomous Navigation, Grant Turner

Mahurin Honors College Capstone Experience/Thesis Projects

With self-driving vehicles, college campus food delivery, or even automated home vacuuming systems, robotics is undoubtedly becoming more prevalent in everyday society and it can be expected to continue with time. While many people are owners, users, or even just spectators of theses robotic products or services, there seems to be a negative perception of robotics that poses an intimidation factor regarding the attempt to understand the ideas driving technology. This perception tends to view robotics as machines that require rich education to understand the complexity and interworkings of, thus attempts understand the field are neglected.

To combat this line …

Human Characteristics Impact On Strategic Decisions In A Human-In-The-Loop Simulation, Andrew J. Collins, Shieda Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

In this paper, a hybrid simulation model of the agent-based model and cooperative game theory is used in a human-in-the-loop experiment to study the effect of human demographic characteristics in situations where they make strategic coalition decisions. Agent-based modeling (ABM) is a computational method that can reveal emergent phenomenon from interactions between agents in an environment. It has been suggested in organizational psychology that ABM could model human behavior more holistically than other modeling methods. Cooperative game theory is a method that models strategic coalitions formation. Three characteristics (age, education, and gender) were considered in the experiment to see if …

Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Real-time ridesharing systems such as UberPool, Lyft Line and GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the “right” requests to travel together in the “right” available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible combinations of requests (with respect to the available delay for customers) as …

Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android has been the most popular smartphone system with multiple platform versions active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we conduct a systematic study of this modern software mechanism. Our objective is to measure the current practice of declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the (in)consistency between DSDK versions and their host apps’ API calls. To successfully analyze a modern dataset of 22,687 popular apps (with an …

Computational Intelligent Impact Force Modeling And Monitoring In Hislo Conditions For Maximizing Surface Mining Efficiency, Safety, And Health, Danish Ali

Doctoral Dissertations

"Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. Previously developed solutions have failed to produce satisfactory results as the vibrations at the truck operator seat still exceed the “Extremely Uncomfortable Limits”. This study was a novel effort in developing deep learning-based solution to the HISLO problem.

This research study developed a rigorous mathematical model and a 3D virtual simulation model to …

Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii

Masters Theses

“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …

Applied Machine Learning In Extrusion-Based Bioprinting, Shuyu Tian

Theses and Dissertations

Optimization of extrusion-based bioprinting (EBB) parameters have been systematically conducted through experimentation. However, the process is time and resource-intensive and not easily translatable across different laboratories. A machine learning (ML) approach to EBB parameter optimization can accelerate this process for laboratories across the field through training using data collected from published literature. In this work, regression-based and classification-based ML models were investigated for their abilities to predict printing outcomes of cell viability and filament diameter for cell-containing alginate and gelatin composite hydrogels. Regression-based models were investigated for their ability to predict suitable extrusion pressure given desired cell viability when keeping …

Secure And Trustworthy Hardware And Machine Learning Systems For Internet Of Things, Shayan Taheri

Electronic Theses and Dissertations, 2020-2023

The advancements on the Internet have enabled connecting more devices into this technology every day. This great connectivity has led to the introduction of the internet of things (IoTs) that is a great bed for engagement of all new technologies for computing devices and systems. Nowadays, the IoT devices and systems have applications in many sensitive areas including military systems. These challenges target hardware and software elements of IoT devices and systems. Integration of hardware and software elements leads to hardware systems and software systems in the IoT platforms, respectively. A recent trend for the hardware systems is making them …

Artificial Intelligence And Soft Computing In Smart Structural Systems, Sajad Javadinasab Hormozabad

Theses and Dissertations--Civil Engineering

Next-generation smart cities are the key feature in the next chapter of human life. Cities that employ innovative and technology-driven solutions to improve the sustainability, resilience, prosperity, and amenity of the community are considered smart cities. Development of smart cities requires fundamental innovations in many technical and technological aspects including those contributing to smart structures. Smart technologies improve the structural performance against natural disasters like earthquakes, hurricanes, tornados, and promote the sustainability of structural systems. Next-generation smart structures encompass a variety of technologies including Structural Control (SC) and Structural Health Monitoring (SHM). SC covers methodologies and technologies that modify the …

Light Field Compression And Manipulation Via Residual Convolutional Neural Network, Eisa Hedayati

Dissertations, Master's Theses and Master's Reports

Light field (LF) imaging has gained significant attention due to its recent success in microscopy, 3-dimensional (3D) displaying and rendering, augmented and virtual reality usage. Postprocessing of LF enables us to extract more information from a scene compared to traditional cameras. However, the use of LF is still a research novelty because of the current limitations in capturing high-resolution LF in all of its four dimensions. While researchers are actively improving methods of capturing high-resolution LF's, using simulation, it is possible to explore a high-quality captured LF's properties. The immediate concerns following the LF capture are its storage and processing …

Converting Optical Videos To Infrared Videos Using Attention Gan And Its Impact On Target Detection And Classification Performance, Mohammad Shahab Uddin, Reshad Hoque, Kazi Aminul Islam, Chiman Kwan, David Gribben, Jiang Li

Electrical & Computer Engineering Faculty Publications

To apply powerful deep-learning-based algorithms for object detection and classification in infrared videos, it is necessary to have more training data in order to build high-performance models. However, in many surveillance applications, one can have a lot more optical videos than infrared videos. This lack of IR video datasets can be mitigated if optical-to-infrared video conversion is possible. In this paper, we present a new approach for converting optical videos to infrared videos using deep learning. The basic idea is to focus on target areas using attention generative adversarial network (attention GAN), which will preserve the fidelity of target areas. …

Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya

Honors Theses

Magnetic resonance imaging (MRI) can help visualize various brain regions. Typical MRI sequences consist of T1-weighted sequence (favorable for observing large brain structures), T2-weighted sequence (useful for pathology), and T2-FLAIR scan (useful for pathology with suppression of signal from water). While these different scans provide complementary information, acquiring them leads to acquisition times of ~1 hour and an average cost of $2,600, presenting significant barriers. To reduce these costs associated with brain MRIs, we present pTransGAN, a generative adversarial network capable of translating both healthy and unhealthy T1 scans into T2 scans. We show that the addition of non-adversarial …