Computer Sciences Commons^™

Local Deformation Method For Soft Cylindrical Model, Hongqian Chen, Fang Yi, Qianyu Yang, Fengxia Li, Chen Yi

Journal of System Simulation

Abstract: To simulate the bending effect for the soft cylindrical objects in realtime, a deformation method was proposed that could achieve the detiail-preservation and surface area-preservation. The method obtained the shape properties such as the bottom and the height from the original cylindrical model. The base model consisted of the regular mesh was built according to the shape properties. The detail model could be obtained by the raidus function of separating from the base model. The uniform deformation algorithm for the base model was adopted to decrease the complexity of the processing. The damping oscillation curve was employed t0 simulate …

Simulation Method For Large-Scale Water Area In Rainy Days, Tingting Yao, Zhongming Xie, Yunfei Li

Journal of System Simulation

Abstract: The rendering of large-scale water area rain scene is one of the most challenging problems in computer graphics, and a method of rendering large-scale water area rain scene was proposed. By introducing the improved wave equation into the fuctuation of water surface and the interaction of water and raindrop, and incorporating the periodicity and wind tendency of FFT, an interactive fluctuation of water mathematical model in rainy days was established, based on which an interactive height map was rendered. Through the lighting rendering, the reflection effect and rain streaks were simulated. In order to enhance the efficiency, the level-of- …

Study On 3d Battlefield Construction Based On Uav Remote Sensing Images, Bin Liu, Xiangning Chen, Lianpeng Guo

Journal of System Simulation

Abstract: According to the demand for rapid construction of 3D battlefield environment, an automatic 3D battlefield environment construction technology was proposed based on UAV Remote Sensing Images. The specified area remote sensing images were captured using UAV The sparse reconstruction and calibrations were obtained using SFM method. The dense reconstruction was done using multi-view stereo matching algorithms. The scene surface was fit using dense points and texture mapping was done to generate 3D battlefield environment. The experimental results show that the proposed method can quickly reconstruct the battlefield, and improves the efficiency of 3D modeling. It has significant intelligence in …

Real-Time Shadow Algorithm Improvements In Digital Earth Scenarios, Defa Zhang, Yiwei Wang, Wang Rui

Journal of System Simulation

Abstract: Studying real- time shadow generating and rendering algorithms in digital earth virtual reality scenes, a new method was provided to improve the shadow rendering quality and efficiency of earth scenes, based on the characteristics of huge dataset, huge coordinates and frequent scheduling mechanisms. Comparing with the classics CSM shadow map algorithm, the method proposed focused on the optimization of shadow splitting ranges, as well as a new pipeline separating the rendering steps of terrain tiles and objects, so to improve both the correctness and efficiency. analyzes The problems caused by shadow rendering while running dynamic terrain tile scheduler simultaneously …

Research Of Liver Solid Texture Synthesis And Mapping Method With Cuda Acceleration, Guodong Chen, Hanxin He

Journal of System Simulation

Abstract: A liver solid texture synthesis and mapping method based on Computer Unified Device Architecture acceleration (CUDA) was proposed to solve the problem of the overlong time consuming within the period of synthesizing liver solid texture in traditional way. The relevance in traditional serial texture synthesis was elim inated in the new method. The work of selecting and distributing blocks of space synthesis of the liver solid texture was processed by using the parallel processing of multiple threads based on CUDA. Both the procedures of tinting the surface grid nodes of liver model and internal point set traversal in mapping …

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 …

Molecule Optimization By Explainable Evolution, Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song

Machine Learning Faculty Publications

Optimizing molecules for desired properties is a fundamental yet challenging task in chemistry, material science, and drug discovery. This paper develops a novel algorithm for optimizing molecular properties via an Expectation-Maximization (EM) like explainable evolutionary process. The algorithm is designed to mimic human experts in the process of searching for desirable molecules and alternate between two stages: the first stage on explainable local search which identifies rationales, i.e., critical subgraph patterns accounting for desired molecular properties, and the second stage on molecule completion which explores the larger space of molecules containing good rationales. We test our approach against various baselines …

Multi-Modal Classification Using Images And Text, Stuart J. Miller, Justin Howard, Paul Adams, Mel Schwan, Robert Slater

SMU Data Science Review

This paper proposes a method for the integration of natural language understanding in image classification to improve classification accuracy by making use of associated metadata. Traditionally, only image features have been used in the classification process; however, metadata accompanies images from many sources. This study implemented a multi-modal image classification model that combines convolutional methods with natural language understanding of descriptions, titles, and tags to improve image classification. The novelty of this approach was to learn from additional external features associated with the images using natural language understanding with transfer learning. It was found that the combination of ResNet-50 image …

Low Light Image Enhancement Via Global And Local Context Modeling, Aditya Arora, Muhammad Haris, Syed Waqas Zamir, Munawar Hayat, Fahad Shahbaz Khan, Ling Shao, Ming-Hsuan Yang

Computer Vision Faculty Publications

Images captured under low-light conditions manifest poor visibility, lack contrast and color vividness. Compared to conventional approaches, deep convolutional neural networks (CNNs) perform well in enhancing images. However, being solely reliant on confined fixed primitives to model dependencies, existing data-driven deep models do not exploit the contexts at various spatial scales to address low-light image enhancement. These contexts can be crucial towards inferring several image enhancement tasks, e.g., local and global contrast, brightness and color corrections; which requires cues from both local and global spatial extent. To this end, we introduce a context-aware deep network for low-light image enhancement. First, …

Using Torchattacks To Improve The Robustness Of Models With Adversarial Training, William S. Matos Díaz

Cybersecurity: Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment

Adversarial training has proven to be one of the most successful ways to defend models against adversarial examples. This process consists of training a model with an adversarial example to improve the robustness of the model. In this experiment, Torchattacks, a Pytorch library made for importing adversarial examples more easily, was used to determine which attack was the strongest. Later on, the strongest attack was used to train the model and make it more robust against adversarial examples. The datasets used to perform the experiments were MNIST and CIFAR-10. Both datasets were put to the test using PGD, FGSM, and …

Fireeye: Cybersecurity In Action, Singapore Management University

Perspectives@SMU

FireEye built its success on its ‘Human + AI’ philosophy. But can a cybersecurity firm get ahead of the attackers and predict an attack…on itself?

Fairer Evaluation Of Zero Shot Action Recognition In Videos, Kaiqiang Huang, Sarah Jane Delany, Susan Mckeever

Conference Papers

Zero-shot learning (ZSL) for human action recognition (HAR) aims to recognise video action classes that have never been seen during model training. This is achieved by building mappings between visual and semantic embeddings. These visual embeddings are typically provided via a pre-trained deep neural network (DNN). The premise of ZSL is that the training and testing classes should be disjoint. In the parallel domain of ZSL for image input, the widespread poor evaluation protocol of pre-training on ZSL test classes has been highlighted. This is akin to providing a sneak preview of the evaluation classes. In this work, we investigate …

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 …