Computer Engineering Commons^™

Enginews Fall 2022, School Of Computer Science & Engineering

News, Magazines and Reports

In this issue:

• New Engineering professor, Okechukwu ‘Okey’ Ugweje
• Business Minor
• S-STEM Grant, National Science Foundation
• Embedded Systems course
• Engineering Explorations course
• SHU Innovate club
• Formula SAE Go-Kart "Road Kill"
• Recent faculty publications and press releases

Softskip: Empowering Multi-Modal Dynamic Pruning For Single-Stage Referring Comprehension, Dulanga Weerakoon, Vigneshwaran Subbaraju, Tuan Tran, Archan Misra

Research Collection School Of Computing and Information Systems

Supporting real-time referring expression comprehension (REC) on pervasive devices is an important capability for human-AI collaborative tasks. Model pruning techniques, applied to DNN models, can enable real-time execution even on resource-constrained devices. However, existing pruning strategies are designed principally for uni-modal applications, and suffer a significant loss of accuracy when applied to REC tasks that require fusion of textual and visual inputs. We thus present a multi-modal pruning model, LGMDP, which uses language as a pivot to dynamically and judiciously select the relevant computational blocks that need to be executed. LGMDP also introduces a new SoftSkip mechanism, whereby 'skipped' visual …

Performance Analytics Of Cloud Networks, Derek Phanekham

Computer Science and Engineering Theses and Dissertations

As the world becomes more inter-connected and dependent on the Internet, networks become ever more pervasive, and the stresses placed upon them more demanding. Similarly, the expectations of networks to maintain a high level of performance have also increased. Network performance is highly important to any business that operates online, depends on web traffic, runs any part of their infrastructure in a cloud environment, or even hosts their own network infrastructure. Depending upon the exact nature of a network, whether it be local or wide-area, 10 or 100 Gigabit, it will have distinct performance characteristics and it is important for …

Machine Learning And Artificial Intelligence Methods For Cybersecurity Data Within The Aviation Ecosystem, Anna Baron Garcia

Doctoral Dissertations and Master's Theses

Aviation cybersecurity research has proven to be a complex topic due to the intricate nature of the aviation ecosystem. Over the last two decades, research has been centered on isolated modules of the entire aviation systems, and it has lacked the state-of-the-art tools (e.g. ML/AI methods) that other cybersecurity disciplines have leveraged in their fields. Security research in aviation in the last two decades has mainly focused on: (i) reverse engineering avionics and software certification; (ii) communications due to the rising new technologies of Software Defined Radios (SDRs); (iii) networking cybersecurity concerns such as the inter and intra connections of …

Metaversekg: Knowledge Graph For Engineering And Design Application In Industrial Metaverse, Utkarshani Jaimini, Tongtao Zhang, Georgia Olympia Brikis

Publications

While the term Metaverse was first coined by the author Neal Stephenson in 1992 in his science fiction novel “Snow Crash”, today the vision of an integrated virtual world is becoming a reality across different sectors. Applications in gaming and consumer products are gaining traction, industrial metaverse applications are, still in their early stages of development with one of the challenges being interoperability across various metaverse development platforms and existing software tools. In this work we propose the use of a knowledge graph based semantic data exchange layer, the Metaverse Knowledge Graph, to enable seamless transfer of information across platforms. …

2022 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2022.

Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher, Ayman Taha, Jane Courtney, Susan Mckeever

Articles

Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the …

Learning To Automate Follow-Up Question Generation Using Process Knowledge For Depression Triage On Reddit Posts, Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy, Vignesh Narayanan, Ponnurangam Kumaraguru, Amit Sheth

Publications

Conversational Agents (CAs) powered with deep language models (DLMs) have shown tremendous promise in the domain of mental health. Prominently, the CAs have been used to provide informational or therapeutic services (e.g., cognitive behavioral therapy) to patients. However, the utility of CAs to assist in mental health triaging has not been explored in the existing work as it requires a controlled generation of follow-up questions (FQs), which are often initiated and guided by the mental health professionals (MHPs) in clinical settings. In the context of `depression', our experiments show that DLMs coupled with process knowledge in a mental health questionnaire …

Monocular Camera Viewpoint-Invariant Vehicular Traffic Segmentation And Classification Utilizing Small Datasets, Amr Yousef, Jeff Flora, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The work presented here develops a computer vision framework that is view angle independent for vehicle segmentation and classification from roadway traffic systems installed by the Virginia Department of Transportation (VDOT). An automated technique for extracting a region of interest is discussed to speed up the processing. The VDOT traffic videos are analyzed for vehicle segmentation using an improved robust low-rank matrix decomposition technique. It presents a new and effective thresholding method that improves segmentation accuracy and simultaneously speeds up the segmentation processing. Size and shape physical descriptors from morphological properties and textural features from the Histogram of Oriented Gradients …

Reflecting On Experiences For Response Generation, Chenchen Ye, Lizi Liao, Suyu Liu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multimodal dialogue systems attract much attention recently, but they are far from skills like: 1) automatically generate context- specific responses instead of safe but general responses; 2) naturally coordinate between the different information modalities (e.g. text and image) in responses; 3) intuitively explain the reasons for generated responses and improve a specific response without re-training the whole model. To approach these goals, we propose a different angle for the task - Reflecting Experiences for Response Generation (RERG). This is supported by the fact that generating a response from scratch can be hard, but much easier if we can access other …

Remgen: Remanufacturing A Random Program Generator For Compiler Testing, Haoxin Tu, He Jiang, Xiaochen Li, Zhide Zhou, Lingxiao Jiang, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Program generators play a critical role in generating bug-revealing test programs for compiler testing. However, existing program generators have been tamed nowadays (i.e., compilers have been hardened against test programs generated by them), thus calling for new solutions to improve their capability in generating bug-revealing test programs. In this study, we propose a framework named Remgen, aiming to Remanufacture a random program Generator for this purpose. RemgEnaddresses the challenges of the synthesis of diverse code snippets at a low cost and the selection of the bug-revealing code snippets for constructing new test programs. More specifically, RemgEnfirst designs a grammar-aided synthesis …

A Comprehensive Characterization Of Hollow Conductor Additively Manufactured Coils And Thermal Management System For A 250 Kw Spm Machine, Sina Vahid, Salar Koushan, Towhid Islam Chowdhury, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

This paper provides an extensive and comprehensive analysis on characterization of additively manufactured coils and heat pipe based liquid cooling thermal management system, for a 250 kW and 5,000 rpm machine. AC and DC electrical tests at 140 Arms and 70 ADC are conducted on AlSi10Mg additively manufactured coils to extract their thermal and electrical characteristics. Heat pipes and liquid cooling test setups are described and discussed. The thermal discussion is concluded by experimental results showing the effectiveness of the thermal management system proposed in this paper. FEA are performed on the coils using ANSYS Maxwell to accurately predict the …

Parallel Simulation System Of Equipment Precision Maintenance Based On Cloud-Edge-End Architecture, Yanqiang Di, Ting Li, Shaochong Feng, Qiongyao Liu, Jianhong Lü, Zhijia Chen, Yang Zhang, Pengfei Cao

Journal of System Simulation

Abstract: Aiming at the demands of equipment precision maintenance, based on the previous research results of equipment parallel simulation, the algorithm of equipment remaining useful life (RUL)prediction is optimized and a parallel simulation system for equipment precision maintenance with cloud-edge-end architecture is designed. At the equipment end, the system collects equipment status data and preprocesses it with edge devices. At the cloud end, based on simulation model, in parallel with the equipment entity, the system dynamically predicts the RUL of equipment. The prediction results are applied to the formulation and deduction of equipment maintenance plans to support the equipment …

Unmanned Air Vehicles Launching Aircraft Combat System And Key Technologies For Penetrating Counterair, Minghao Li, Wenhao Bi, An Zhang, Wenxuan Sun

Journal of System Simulation

Abstract: Penetrating counterair is an important countermeasure to the anti-access/area denial environment. Under this operational requirement, the unmanned air vehicles launching aircraft (UAVLA)has received much attention due to the advantages of load quantity and variety, operational range and duration, and development time and cost. Based on the review of the concept development and supporting research related to the UAVLA, the top-level concepts of operations such as the component systems,operational process, operational events tracking, and information interaction of the UAVLA combat system (UAVLACS) are designed. The key technologies of the system are prospected from four aspects:intelligent cognition of battlefield situation under …

Opnet Based Simulation Of Hybrid Tdma Protocol For Helicopters Datalink, Yanfang Fu, Nan Zhang, Jianing Wei, Shaochun Qu, Ying Lu, Chang Liu

Journal of System Simulation

Abstract: For the current time slot allocation problem of the data link, an improved hybrid time slot allocation protocol based on grey relational analysis is proposed and implemented. Through the aggregation of throughput, delay and load of current message buffer by grey relational analysis, the comprehensive evaluation index is obtained, and the time slot is allocated dynamically. The fixed time slot allocation is also adopted to ensure that at least one time slot is available for nodes in the network.Simulation results show that compared with the fixed TDMA(time division multiple access) protocol and the P-TDMA(priority-TDMA) protocol, the proposed protocol …

Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen

Journal of System Simulation

Abstract: As the key technology of multi-agent game confrontation, opponent modeling is a typical cognitive modeling method of agent's behavior. Several typical models of multi-agent game confrontation,non-stationary problems, and meta-game theory are introduced; opponent modeling methods that concludes the frontier theory of opponent modeling are summarized, and the applications and challenges are analyzed. Based on the theory of meta-game, a general opponent modeling framework is constructed with three modules: opponent policy recognition and generation, opponent policy space reconstruction,and opponent exploitation. It is expected to provide theoretical and methodological reference for opponent modeling in multi-agent game confrontation.

Siamese Object Tracking Algorithm Combined With The Intersection Over Union Loss, Wei Zhou, Yuxiang Liu, Guangping Liao, Xin Ma

Journal of System Simulation

Abstract: To improve the accuracy of the object bounding box regression prediction of the SiamRPN,solve the problem of low discrimination of positive samples in classification prediction and the lack of correlation between regression prediction and classification prediction, an improved object tracking algorithm of SiamRPN which combined with IoU(intersection over union) loss is proposed. A joint optimization module of IoU-smooth L1 is designed to optimize the IoU loss of the best positive sample and the smooth L1 loss of other positive samples jointly. According to the regression prediction results, the weighted classification prediction is performed on the positive samples with the …

Relative-Residual-Based Dynamic Schedule For Decoding Of Ldpc Codes, Fatang Chen, Hebin Li, Zhihao Zhang, Zhiqiang Mei

Journal of System Simulation

Abstract: In order to solve the problems of the oscillation phenomenon and greedy characteristics in the dynamic scheduling decoding algorithm for low-density parity-check (LDPC) codes, the relative-residual-based dynamic schedule (RRB-BP) algorithm is proposed based on variable-to-check residual belief propagation (VC-RBP) algorithm. The variable nodes are grouped, then the relative residual value of the message passed by the variable nodes to the check node is taken as a reference, and the node with the largest relative residual value is updated in priority to accelerate the decoding convergence speed. For variable nodes oscillating in the decoding process, the posterior LLR (log likelihood …

Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu

Journal of System Simulation

Abstract: Based on the comprehensive consideration of economic indicators and environmental factors, the energy-efficient scheduling problem of multi-objective flexible job shop with uncertain processing time is studied. The interval number is used to describe uncertain processing time of the workpiece, and the optimization model for energy-efficient problem of interval flexible job shop scheduling is established to minimize the maximum interval completion time and total energy consumption. According to the domination relation of interval possibility degree, an effective interval multi-objective evolutionary algorithm is designed. The simulation experiments of the interval multi-objective evolutionary algorithm, SPEA-II and NSGA-II are carried out through 15 …

Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu

Journal of System Simulation

Abstract: In the early stage of major public health events, medical supplies are rapidly consumed and severely insufficient. In order to distribute medical supplies in a reasonable and efficient manner, research on the distribution of emergency medical materials is carried out. The entropy method is introduced to determine the urgency of demand points, thus could give priority to the demand points with high urgency and make the distribution routing as short as possible on that basis to realize the construction of a split delivery and multi-objective emergency medical materials scheduling model based on different urgency of demand points. Meanwhile the …

Design Of Optical Compound Eye Simulation Software For Small Aircraft Applications, Qiming Qi, Ruigang Fu, Ping Wang, Min Wang, Hongqi Fan

Journal of System Simulation

Abstract: Optical compound eye has the advantages of large field of view, multiple viewing angles and high resolution. With another advantage that it can conformal combine with small aircraft, optical compound eye has application value in reconnaissance and surveillance, target detection, image navigation and other aspects. An optical compound eye simulation software for small aircraft is designed for the current situation of long development period of optical compound eye design and high cost of flight test in practical applications. The software integrates compound eye imaging, aircraft simulation and data management, and each functional module is extensible. The simulation results show …

Mesoscopic Modeling And Simulation Of Mixed Traffic Flow Of Buses And Vehicles, Yiting Zhu, Yun Yan, Zhaocheng He

Journal of System Simulation

Abstract: Aiming at the problem that the existing mesoscopic simulation models only convert buses into several standard vehicles and ignore the movement difference between buses and vehicles, a mesoscopic simulation model of mixed traffic flow is proposed. In the process of road driving, on the one aspect, we consider the feature that bus speed is usually lower than vehicle speed, and correspondingly establish the reduction function of bus speed; on the other aspect, we consider the influences of bus-station queue overflow on the adjacent lanes, and correspondingly construct the lane-based speed model of mixed flow.Moreover, we use the …

Electrical Resistance Tomography And Flow Pattern Identification Method Based On Deep Residual Neural Network, Weiguo Tong, Shichao Zeng, Lifeng Zhang, Zhe Hou, Jiayue Guo

Journal of System Simulation

Abstract: Aiming at the low accuracy of inverse problem imaging and flow pattern recognition in electrical resistance tomography (ERT), a two-phase flow electrical resistance tomography and flow pattern recognition method based on the deep residual neural network is proposed. The finite element method is used to model the ERT forward problem to construct the "boundary voltage-conductivity distribution-flow pattern category" dataset of various gas-liquid two-phase flow distributions. The residual neural network for ERT image reconstruction and flow pattern identification of gas-liquid two-phase flow is built and trained. The two outputs of the residual neural network are processed respectively to obtain …

Study On Invulnerability Of Urban Agglomeration Passenger Traffic Network Considering Time Characteristics, Chengbing Li, Yunfei Li, Peng Wu

Journal of System Simulation

Abstract: The cascading failure invulnerability study of comprehensive passenger transport network in urban agglomeration is helpful to improve the safety and transportation efficiency of intercity travel. In order to be consistent with the actual situation, a comprehensive passenger transport network model for urban agglomerations is constructed based on multi-layer complex network theory and actual passenger flow. The passenger transport network cascading failure invulnerability model considering time characteristics is established with unit time step. The spatial and temporal evaluation indexes are put forward to analyze the network situation in each period. Taking Hu-Bao-E-Yu urban agglomeration as an example, the results show …

Research On Ofdm Signal Detection Method Based On Intrawell Stochastic Resonance Of Bistable System, Gaohui Liu, Ying Liang

Journal of System Simulation

Abstract: In order to solve the problem of weak OFDM (orthogonal frequency division multiplexing)signal detection at the receiver in OFDM transmission system, the intrawell stochastic resonance of bistable system is combined with the OFDM signal enhancement and demodulation process. Analytical expression is derived for the time required to change from zero state to potential well state for the intrawell stochastic resonance system under the excitation of multicarrier signals, and the energy loss of multicarrier signals in one symbol caused by the transient response is analyzed. The steady-state output equation of system is derived, and the problem of superimposing the …

Architecture Design And Prototype Verification Of Railway Vehicle Dynamics Cloud Platform, Junjie Sheng, Zhao Tang, Shaodi Dong, Shuyang Wu, Hao Liang

Journal of System Simulation

Abstract: Since almost all the software in the railway vehicle field is controlled by foreign capital, it is difficult to catch up with the development of independent vehicle system software based on single machine deployment mode in a short time. In view of this, a set of autonomous and controllable vehicle system dynamics software architecture based on cloud platform is proposed. Based on the railway vehicle system dynamics and cloud services, a cloud platform with automatic process modeling, cloud computing,post-processing analysis is built. A simulation model of a trailer caris applied in the platform, and compared with the SIMPACK …

A High Resolution Reconstruction Method Of Temperature Distribution In Acoustic Tomography, Lifeng Zhang, Yu Miao

Journal of System Simulation

Abstract: Accurate measurement temperature distribution is important for industrial production. In order to solve the number of mesh divisions will impact reconstruction accuracy in acoustic tomography, the TR-RBF (Tikhonov regularization-radial basis function) reconstruction algorithm is rebuilt to reconstruct the temperature field with high resolution. The Tikhonov regularization is used to reconstruct the ultrasound time of flight (TOF) to obtain a temperature distribution on coarse grids, and use local weighted regression method to smooth processing; use RBF neural networks to predict the temperature distribution on fine grids. Through numerical simulation with and without noise, compared with ART,SVD and Tikhonov, the proposed …

Research On Cooperative Adaptive Cruise Control Strategy Based On Improved Mpc, Qiming Wang, Jiangyue Jiang, Zhichao Lü, Hanzu Zhang

Journal of System Simulation

Abstract: To solve the problems of environmental interference, sensor noise and poor tracking stability of time-varying speed, an improved MPC (model predictive control) algorithm based on KF (kalman filtering) is proposed. The longitudinal kinematics model of CACC(cooperative adaptive cruise control)between vehicles is established and the discrete state space equation is created. KF is used to reduce the noise of state variables, and at the same time, the prediction model is designed for robustness. The CACC control objectives are analyzed under different working conditions and the objective optimization functions are created. Verify by building Simulink and CarSim co-simulation model, the simulation …

Simulation Of The Market Exclusive Competition Between Platforms, Wen Zheng, Zhe Zhang, Jingyi Zhu

Journal of System Simulation

Abstract: As for the problem of an exclusive competition between the platforms, 2 competing PlatformsAgent, 100 ConsumersAgent and 300 SellersAgent are introduced and encapsulated into a closed market environment in BarriersModelSwarm. A two-sided market system is constructed with the cross-network externality. Through BarriersObserverSwarm, the Agents attribute information and behavior strategy are cross-called, and the virtual connection class Orderand ArrayList class in the Virtual Connection Classes are generated to run cyclically. The unilateral dependence degree of Consumers/SellersAgent is triggered, which restores the exclusive of the two-sided market competition in comparison with the platform transaction scale, market concentration, and platform cumulative capital. …

Turbofan Engine Fault Prediction Based On Evidential Reasoning And Belief Rule Base, Hailong Zhu, Ruxia Jia, Liang Zhang, Wei He

Journal of System Simulation

Abstract: Aiming at the fault prediction problem of a turbofan engine, a fault prediction model based on evidential reasoning (ER) and belief rule base (BRB) is proposed. In order to describe the health state of turbofan engine, ER algorithm is adopted to fuse the state information. Combined with prior knowledge, a hybrid driven simulation prediction of BRB model is established. Projection covariance matrix adaptive evolution strategy (P-CMA-ES) is used to optimize the model parameters. The validity of the model is verified by experiments. Experimental results show that the proposed method not only accurately predicts the probability of failure …