Engineering Commons^™

Dynamic Data Reserved Modeling Method Based On Steady-State Component Estimation And State Tracking, Dong Ze, Erxin Yin

Journal of System Simulation

Abstract: Aiming at the existing problems of conventional industrial system modeling methods, a dynamic data reserved modeling method based on steady-state component estimation and state tracking is proposed. The dynamic response data of the system is selected as the modeling data. The input value at the end of the selected data is chosen as steady-state component, and the steady-state component value of output is artificial given. Steady-state component of the modeling data is removed according to the steady-state component of input and output, and the modeling data is divided into three sections. The prediction model and the state observer are …

Adaptively Resampling 3d Mesh Models Based On Editable Features, Jiajia Dai, Lipeng Fan, Mingyong Pang

Journal of System Simulation

Abstract: We propose a hybrid algorithm for adaptively resampling 3D triangulations by user-defined editable features. The method parameterizes a 3D mesh model into 2D parameter plane, and the geometric properties of the original model is calculated and represented on a planar domain. According to a constructed geometric image of the original model and user-defined editing information, the method creates a global density function for the resampled model. The sampling density function is employed to control distribution of samples in the 2D parameter domain. The method uses centroidal Voronoi tessellation technique to further optimize local distribution of the sampled points. The …

Design Method Of Tactical Level Hexagonal Wargame Map, Fen Tang, Zhang Xin, You Xiong, Zhiqiang Wu, Kunwei Li

Journal of System Simulation

Abstract: Wargame map is an indispensable component of wargame. The current research on wargame map focused itself on the hexagonal grid segmentation, the terrain quantization models and relevant algorithms, and the technical realization of the application algorithm based on wargame map. However, the wargame map design is inadequate in corresponding instructions and methods. Therefore, based on the traditional map design method and fully taking into account the characteristics of the army tactical level hexagonal wargame map, the principle and process of army tactical level hexagonal wargame map design are proposed, and the critical steps in the process of the wargame …

Remote Real-Time Rendering System Based On Graphics Cluster, Haiyang Liu, Xiaofeng Hu, Lei Xu

Journal of System Simulation

Abstract: In order to solve the problems of rendering application for many remote users with different requirements, according to the multi-user oriented asynchronous distributed application mode in graphics cluster environment, a general framework of remote real-time rendering system based on graphics cluster is proposed, and the main functional modules are designed. The integrated application of key technologies, including GPU rendering based on Docker, dynamic load balancing and real-time transmission control of images, is analyzed. The effectiveness of system solution is demonstrated by concrete examples.

Multi-Objective Operation Scheduling Optimization Of Shipborne-Equipment Based On Genetic Algorithm, Jinsong Bao, Zhiqiang Li, Yaqin Zhou

Journal of System Simulation

Abstract: Multi-objective operation scheduling of shipborne equipment is a complex combinational optimization problem under multi-task system. Existing research focuses mainly on single-objective optimization while several other objectives need to be considered during real operation such as path, duration, resource, etc. Considering the operation scheduling before exporting of an amphibious landing ship as the research object, both scheduling duration and resource requirement under the precedence constraint are optimized. The mathematical model of this multi-objective operation scheduling is established and solved using genetic algorithm. A fitness function which can be self-adaptively adjusted is designed; an adapting encoding strategy, a crossover operator, and …

Dbn Method For Risk Assessment Of Dairy Products Cold Chain Logistics, Weijiong Chen, Fan Wen, Xiaolin Zhu, Qimiao Xie, Xiaobei Yin

Journal of System Simulation

Abstract: Dairy cold chain logistics is a one-way dynamic process. According to the Bayesian theory, this paper considered the transitivity between risks and used the GeNIe software to establish the DBN risk assessment model. The cold chain logistics risk probability of dairy products was evaluated and the sensitivity analysis was carried out. The results revealed that the probability of transportation risk is the highest, and the sensitivity of processing risk is the highest. The processing and the transportation are the key links of the dairy product cold chain logistics. Comparing the results of DBN and the results of static Bayesian …

Lpv Controller Design Of Wind Turbine With Maximum Power Point Tracking, Zheng Yang, Dinghui Wu, Zhicheng Ji

Journal of System Simulation

Abstract: A design method of the polytopic controller under the maximum power point tracking (MPPT) is proposed in addressing the low efficiency of the wind turbine under rated wind speed and uncertainty of the wind speed. Considering high nonlinearity of the aerodynamic system, the Jacobi linearization and the convex decomposition technique are employed to transform the wind turbine system into a polytopic linear parameter varying (LPV) model with the bias torque of the aerodynamic torque as the scheduling variable. By solving the linear matrix inequalities (LMIs), a polytopic LPV controller is obtained. The simulation results show that the designed controller …

Trajectory Planning Method Of Overhead Crane, Xuejuan Shao, Li Yao, Jinggang Zhang, Xueliang Zhang

Journal of System Simulation

Abstract: To make the trolley of bridge crane move stably with smooth acceleration, a polynomial acceleration trajectory is proposed based on the constraint conditions of the crane and the friction between the trolley and the rail. An anti-swing plan is designed employing the dynamic coupling relationship between the motion of the trolley and the load swing. Results indicate that when the length of the rope is changed, the swing angle of the trolley is still within the limits. The stability of the system is proved by constructing Lyapunov energy equations, and the Barbalat lemma confirms that the planned reference trajectory …

Spatial Spectrum Estimation Method Of Flank Twin-Line Array Based On Cross-Spectrum Correlation, Zhizhong Li, Wang Sen, Zhongliang Xu, Weiguo Dai, Qijun Liu

Journal of System Simulation

Abstract: Considering the structural features of the flank twin-line array, researches on spatial spectrum estimation of twin-line array based on adaptive beam-forming and cross-spectrum correlation were carried out. A spatial spectrum estimation method based on cross-spectrum correlation is proposed according to the theory of cross-spectrum. The study of spectrum estimation performance comparison of the twin-line array was finished by that method combined with the conventional beam-forming and the adaptive beam-forming respectively. The results prove that the method based on cross-spectrum correlation has a better capability in noise suppression; and the method, which combined adaptive beam-forming with cross-spectrum correlation, is the …

Influence Of Composite Materials Surface Metal Mesh On Helicopter Lightning Stroke Effects, Junling Huang, Jiayu Xie

Journal of System Simulation

Abstract: The metal wire mesh is usually adopted to prevent the lightning stroke on composite materials. The effects of different materials and different thickness of metal mesh on helicopter lightning electromagnetic effect are compared. According to the method recommended by SAE-ARP5416, a numerical simulation software is used for carrying out the high current injection simulation. The results show that the surface mount metal mesh can effectively reduce the harm of lightning electromagnetic coupling effect; the difference between aluminum and copper on anti-lightning stroke effect is not obvious; when the thickness of aluminum grid is less than 0.15 mm, the …

Thai Language Names, Place Names And Organization Names Entity Recognition, Hongbin Wang, Hongkui Gao, Shen Qiang, Yantuan Xian

Journal of System Simulation

Abstract: Named entity recognition in Thai language is aimed to identify the names of a person, a locality,an organization or an institution,and so on. Due to the complexity of Thai word formation method and grammar rules, to solve this problem, the idea of the approach proposed is to treat the task of named entity recognition in Thai language as labeling the sign of a series of words in Thai sentence. Given the characteristics of Thai language itself, certain features in the context of the samples in the Thai entity recognition corpus are extracted to train the hidden Markov model and …

Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization, Cai Rui, Wang Wei, Jue Qu, Hu Bo

Journal of System Simulation

Abstract: Aiming at the allocation conflict between task and operator of multi-seats collaborative task planning in command and control cabin, a multi-seats collaborative task planning method based on improved particle swarm optimization is proposed. This method describes and analyzes the multi-seats collaborative task and establishes a solution space model based on task sequence. In solving the model, the particle swarm optimization (PSO) was improved by using multi-dimensional asynchronous processing and modifying inertia weight parameters so that the efficiency and local searching ability of the PSO were improved. The example analysis shows that the model and the algorithm can effectively reduce …

High-Dimensional Clustering Method Based On Variant Bat Algorithm, Kou Guang, Guangming Tang, Jiajing He, Hengwei Zhang

Journal of System Simulation

Abstract: With the advent of the era of big data, the information resource is growing rapidly, and the data are becoming high-dimensional. Traditional clustering methods have a good effect for low-dimensional data, but no longer apply to high-dimensional data. On the basis of existing high-dimensional clustering algorithm, a high-dimensional clustering algorithm based on intelligent optimization SSC-BA is proposed. A novel objective function is designed, which integrates the fuzzy weighting within-cluster compactness and the between-cluster separation. A variant bat algorithm is introduced to calculate the weight matrix, giving the new learning rules. Simulation experiments are made for the proposed algorithm, and …

A Co-Optimal Coverage Path Planning Method For Aerial Scanning Of Complex Structures, Zhexiong Shang, Justin Bradley, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

The utilization of unmanned aerial vehicles (UAVs) in survey and inspection of civil infrastructure has been growing rapidly. However, computationally efficient solvers that find optimal flight paths while ensuring high-quality data acquisition of the complete 3D structure remains a difficult problem. Existing solvers typically prioritize efficient flight paths, or coverage, or reducing computational complexity of the algorithm – but these objectives are not co-optimized holistically. In this work we introduce a co-optimal coverage path planning (CCPP) method that simultaneously co-optimizes the UAV path, the quality of the captured images, and reducing computational complexity of the solver all while adhering to …

Design And Modeling Of A New Biomimetic Soft Robotic Jellyfish Using Ipmc-Based Electroactive Polymers, Zakai J. Olsen, Kwang J. Kim

Mechanical Engineering Faculty Research

Smart materials and soft robotics have been seen to be particularly well-suited for developing biomimetic devices and are active fields of research. In this study, the design and modeling of a new biomimetic soft robot is described. Initial work was made in the modeling of a biomimetic robot based on the locomotion and kinematics of jellyfish. Modifications were made to the governing equations for jellyfish locomotion that accounted for geometric differences between biology and the robotic design. In particular, the capability of the model to account for the mass and geometry of the robot design has been added for better …

Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter

Doctoral Dissertations

A non-stationary dataset is one whose statistical properties such as the mean, variance, correlation, probability distribution, etc. change over a specific interval of time. On the contrary, a stationary dataset is one whose statistical properties remain constant over time. Apart from the volatile statistical properties, non-stationary data poses other challenges such as time and memory management due to the limitation of computational resources mostly caused by the recent advancements in data collection technologies which generate a variety of data at an alarming pace and volume. Additionally, when the collected data is complex, managing data complexity, emerging from its dimensionality and …

Big-Data Talent Analytics In The Public Sector: A Promotion And Firing Model Of Employees At Federal Agencies, Rabih Neouchi

Operations Research and Engineering Management Theses and Dissertations

Talent analytics is a relatively new area of focus to researchers working in analytics and data science. Talent Analytics has the potential to help companies make many informed critical decisions around talent acquisition, promotion and retention. This work investigates data science to predict “shiny star” employees in the U.S. public sector, defined as top-notch performers over the years of a given time span. Its scope falls within talent analytics, also called people analytics, a relatively new research area.

We clean a data set made available by the U.S. Office of Personnel Management (OPM) and present two models to predict the …

Exercises Integrating High School Mathematics With Robot Motion Planning, Ronald I. Greenberg, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

This paper presents progress in developing exercises for high school students incorporating level-appropriate mathematics into robotics activities. We assume mathematical foundations ranging from algebra to precalculus, whereas most prior work on integrating mathematics into robotics uses only very elementary mathematical reasoning or, at the other extreme, is comprised of technical papers or books using calculus and other advanced mathematics. The exercises suggested are relevant to any differerential-drive robot, which is an appropriate model for many different varieties of educational robots. They guide students towards comparing a variety of natural navigational strategies making use of typical movement primitives. The exercises align …

Demonstration Of Visible And Near Infrared Raman Spectrometers And Improved Matched Filter Model For Analysis Of Combined Raman Signals, Alexander Matthew Atkinson

Electrical & Computer Engineering Theses & Dissertations

Raman spectroscopy is a powerful analysis technique that has found applications in fields such as analytical chemistry, planetary sciences, and medical diagnostics. Recent studies have shown that analysis of Raman spectral profiles can be greatly assisted by use of computational models with achievements including high accuracy pure sample classification with imbalanced data sets and detection of ideal sample deviations for pharmaceutical quality control. The adoption of automated methods is a necessary step in streamlining the analysis process as Raman hardware becomes more advanced. Due to limits in the architectures of current machine learning based Raman classification models, transfer from pure …

Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger

Electrical and Computer Engineering Publications

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building or a single aggregated load to predict future consumption for that same building or aggregated load. With hundreds of thousands of meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Similarity-Based Chained Transfer Learning (SBCTL), an approach for building neural network-based models for many meters by …

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan

Dissertations

Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The …

Machine Learning-Based Network Vulnerability Analysis Of Industrial Internet Of Things, Maede Zolanvari, Marcio Teixeira, Lav Gupta, Khaled Khan, Raj Jain

Computer Science Faculty Works

No abstract provided.

Mining Semantic Knowledge Graphs To Add Explainability To Black Box Recommender Systems, Mohammed Alshammari, Olfa Nasraoui, Scott Sanders

Faculty and Staff Scholarship

Recommender systems are being increasingly used to predict the preferences of users on online platforms and recommend relevant options that help them cope with information overload. In particular, modern model-based collaborative filtering algorithms, such as latent factor models, are considered state-of-the-art in recommendation systems. Unfortunately, these black box systems lack transparency, as they provide little information about the reasoning behind their predictions. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less accurate than sophisticated black box models. Recent research has demonstrated that explanations are an essential component in bringing the powerful predictions of …

Digital Marketing In The Artificial Intelligence And Machine Learning Age, Z. Ruan, Keng Siau

Research Collection School Of Computing and Information Systems

We are living in a period of profound change driven by digitization, information and communication technology, artificial intelligence, machine learning, and robotics (Gupta, Keen, Shah, and Verdier, 2017; Wang and Siau, 2019). Traditional marketing is shifting to digital marketing enabled by AI and machine learning. Customer consumption behavior has changed from traditional in-store shopping to online shopping (Thiraviyam, 2018). The large volume of transaction and demographic data enables business analytics, AI, and machine learning to analyze and predict customer behavior to improve customer satisfaction and enhance sales (Siau and Wang, 2018). For example, predictive analytics uses different algorithms to predict …

Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore

School of Computing: Dissertations, Theses, and Student Research

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries.

To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We …

Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper points students towards ideas they can use towards developing a convenient library for robot navigation, with examples based on Botball primitives, and points educators towards mathematics and programming exercises they can suggest to students, especially advanced high school students.

Chatbots: Conversation Killers Or Makers?, Jing Jiang

MITB Thought Leadership Series

Whether you’re aware of it or not, the chances are you’ve been chatting to robots of late. While these bots are faceless and unseen, don’t be fooled into thinking they aren’t there. In fact, chatbots, have been around since the 1960s at least, but with the progress in artificial intelligence, cloud computing and voice recognition, they’ve received both a functionality and a popularity boost. From the cosmetic to the life-changing, nowadays, chatbots can do anything from helping a person lose weight to assisting refugees applying for asylum.

Entropy Based Independent Learning In Anonymous Multi-Agent Settings, Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc for matching restaurants to customers. In these online to offline service problems, individuals who are responsible for supply (e.g., taxi drivers, delivery bikes or delivery van drivers) earn more by being at the ”right” place at the ”right” time. We are interested in developing approaches that learn to guide individuals to be in the ”right” place at the ”right” time (to maximize revenue) in the presence of other …

Zac: A Zone Path Construction Approach 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, 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 in available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. The most relevant existing work has focussed on generating as many relevant feasible (with respect to available delay for customers) combinations of requests (referred to as trips) as possible in real-time. …

Using Feature Extraction From Deep Convolutional Neural Networks For Pathological Image Analysis And Its Visual Interpretability, Wei-Wen Hsu

Electrical & Computer Engineering Theses & Dissertations

This dissertation presents a computer-aided diagnosis (CAD) system using deep learning approaches for lesion detection and classification on whole-slide images (WSIs) with breast cancer. The deep features being distinguishing in classification from the convolutional neural networks (CNN) are demonstrated in this study to provide comprehensive interpretability for the proposed CAD system using the domain knowledge in pathology. In the experiment, a total of 186 slides of WSIs were collected and classified into three categories: Non-Carcinoma, Ductal Carcinoma in Situ (DCIS), and Invasive Ductal Carcinoma (IDC). Instead of conducting pixel-wise classification (segmentation) into three classes directly, a hierarchical framework with the …