Engineering Commons^™

Tactical Maneuver Strategy Learning From Land Wargame Replay Based On Convolutional Neural Network, Jiale Xu, Haidong Zhang, Donghai Zhao, Wancheng Ni

Journal of System Simulation

Abstract: Aiming at collecting the high valuable knowledge of action decisions in "man-in-the-loop" wargame's replay data, a method of using convolutional neural network to learn the tactical maneuver strategy model from the replay data of wargame is proposed. In this method, the tactical maneuver strategy is modeled as a classification problem of making a good choice from the target candidate locations under the influence of current situation. The key factors affecting commander's decision-making are summarized, and the basic situation features are defined, which are composed of seven attributes such as "maneuverability range and observation range". The feature dataset with positive …

Weighted Local Complexity Invariance For Time Series Classification, Yitong Li, Xiaotao Liu, Jing Liu, Kai Wu

Journal of System Simulation

Abstract: Aiming at the misclassification of existing algorithms for long or unevenly distributed time series, the local complexity information is extracted and weighted local complexity-invariant distance (WLCID) is proposed, which includes the local complexity representation model and the weighted global complexity integration model. Sliding window is used to split up time series, and combined with the complexity-invariant distance, the local complexity information can be extracted. As to the class representation model, the integration weights are quantified with the normalized cumulative between-class distance, with the perspective that the subsequence contributes more greatly with larger between-class distance. Compared with other …

A K-Modes Clustering Method Based On Maximal Information Coefficient Data Preprocessing, Mingmei Li, Chenglin Wen, Shaolin Hu

Journal of System Simulation

Abstract: The existing k-modes clustering method ignores the weak correlation of variable attributes, which often results in poor clustering performance in practical applications. A new k-modes clustering method that includes the weak correlation of attributes is proposed. Maximum information coefficient (MIC) is introduced to measure the correlation of variable attributes in the data set. The obtained MIC value is merged with the original distance to establish a new measurement method containing weak attribute correlation information to enhance the completeness of related information of variable attributes, and a more refined k-modes clustering method is established. Three different data sets are used …

Research On Satellite Navigation Confrontation Deduction Model For Wargame System, Runqing Yang, Xi Wu

Journal of System Simulation

Abstract: Following the increasing reliance on space-based time-space metric of information warfare, satellite navigation confrontation becomes the major combat operation of competing for superiority in space-based position, navigation, and timing. Aiming at building a satellite navigation operation deduction model, on the basis of analyzing the relevant research, the navigation information environment computing model and the navigation deduction operation simulation model are designed, and the way to realize the visualization of navigation information environment of the wargame system and a substitution of high-resolution simulation computing model low-resolution probability effect model are explored, which support the pre-war planning and wartime evaluation …

Wind Power Primary Frequency Regulation Simulation Based On Wind Speed Prediction Model, Zhenyu Zhao, Xu Ma, Geriletu Bao

Journal of System Simulation

Abstract: To furtherly improve the accuracy of wind speed prediction, considering the coupled comprehensive features of data internal structure external influencing factors, and the characteristics of wind turbines power, a BP-ARIMA combined prediction model is constructed and the wind speed of wind farms is simulated. Compared with the actual data, the high prediction accuracy of the model is verified. Bases on the curve of typical power characteristic of wind turbine, the optimal configuration of energy storage device capacity and the stability of wind turbine are considered, and the MATLAB-SIMULINK platform is applied to simulate the primary frequency regulation of …

Multi-Sensory Fusion Method For Power Transformer Virtual Assembly, Xuqiang Shao, Haowei Zhang, Xiaohua Feng

Journal of System Simulation

Abstract: Virtual assembly technology is to truly restore the equipments and physical scenarios. In the real world, people can interact with the physical world through visual, auditory, tactile and other sense organ. Aiming at the existing virtual assembly system being limited the single sense human-computer interaction mode, so a multi-sense fusion information interaction method is proposed to improve the sense of immersion and operability. An improved AABB Octree bounding box collision detection algorithm of large size diffidence component to be assembled is proposed, which can greatly reduce the amount of calculation and improve the calculation accuracy. The experimental result verifies …

Reinforcement-Learning-Based Adaptive Tracking Control For A Space Continuum Robot Based On Reinforcement Learning, Da Jiang, Zhiqin Cai, Zhongzhen Liu, Haijun Peng, Zhigang Wu

Journal of System Simulation

Abstract: Aiming at the tracking control for three-arm space continuum robot in space active debris removal manipulation, an adaptive sliding mode control algorithm based on deep reinforcement learning is proposed. Through BP network, a data-driven dynamic model is developed as the predictive model to guide the reinforcement learning to adjust the sliding mode controller's parameters online, and finally realize a real-time tracking control. Simulation results show that the proposed data-driven predictive model can accurately predict the robot's dynamic characteristics with the relative error within ±1% to random trajectories. Compared with the fixed-parameter sliding mode controller, the proposed adaptive controller …

Simulation Research On Aerodynamic Characteristics Of A Miniature Munition, Haisen Wang, Junfang Fan

Journal of System Simulation

Abstract: Aiming at the existing constraints of layout design of miniature munition, a new layout optimization scheme is proposed. Based on the normal layout structure, a three-dimensional aerodynamic model of munition is established, and the aerodynamic hydrodynamics simulation of miniature munition is carried out, and the influence of wing size on static stability of munition is studied. To verify the feasibility of the design scheme, the aerodynamic simulation calculation is carried out, and the lift, drag and pitching moment parameters of miniature munition are obtained through simulated aerodynamic calculation under different flight conditions, and the lift-drag ratio …

Fatigue Detection Method Based On Facial Features And Head Posture, Rongxiu Lu, Bihao Zhang, Zhenlong Mo

Journal of System Simulation

Abstract: Aiming at the of the single fatigue characteristics, low robustness and inability to customize fatigue thresholds for different drivers of fatigue detection methods, a method based on facial features and head posture is proposed. In face detection and face key point positioning HOG feature operator and regression tree algorithm are used. In head posture estimation, head posture Euler angle is estimated by combining the face key points with the coordinate system transformation. In fatigue feature extraction, a deep residual neural network model is established to extract the eye fatigue features, which the eye, mouth aspect ratio and head posture …

Task Allocation Method For Multi-Uav Cooperative Reconnaissance In Complex Environment, Fuzhen Zhang, Yaoqin Zhu

Journal of System Simulation

Abstract: The existing cooperative planning methods of multiple UAVs often carry out path planning and task allocation separatly, which causes the cooperative scheme not being the best in a complex environment. The cost matrix of multi-UAV cooperative reconnaissance on heterogeneous targets is established. Aiming at the various obstacle constraints and the characteristics of UAV motion and track in complex environment, an improved PSO-AFSA is used to solve the single UAV track planning model. Hungarian algorithm is used to complete the cooperative allocation of reconnaissance tasks of UAVs. The simulation results show that the algorithm can make the flying range of …

Simulation Of Emergency Medical Materials Collaborative Distribution Considering Supplier Clustering, Zhe Wang, Hongyuan Shao, Zihao Cong, Wenwen Ma

Journal of System Simulation

Abstract: Aiming at the insufficient local government medical material reserves and low distribution efficiency to public health emergencies, consider supplier clustering a two-stage emergency medical supplies public-private collaborative location and alloation model is designed. In for disaster preparedness, fuzzy clustering algorithm to realize supplier clustering, and a cooperation mechanism with the government is establish realize the joint storage of emergency medical supplies; In the early stage of rescue, relying on the government and various suppliers' material storage and transportation capabilities, a location allocation simulation model to minimize the weighted sum of total logistics cost and demand unsatisfied rate is …

Research On High-Performance Emulation Technology Of Starlink Constellation Based On Cloud Platform, Yuan Liu, Xinyi Xue, Xiaofeng Wang

Journal of System Simulation

Abstract: Network emulation on Starlink constellation is an important verification and evaluation tool for the design and construction of low earth orbit constellations in the future. Aiming at the characteristics of large-scale and complex structure of the Starlink network, a high-performance satellite network emulation system is designed. Based on the distributed network emulation architecture of cloud platform, through the development of STK Engine underlying interface, satellite model library storage optimization and asynchronous message transmission technology, the rapid deployment of Starlink constellation is carried out, and has good scalability. The experimental results show that the proposed method can carry out …

Analysis And Research On End-To-End Optical Image Quality Of Large Aperture Off-Axis Space Telescope, Zhang Ban, Xiaobo Li, Xun Yang, Yuxi Jiang

Journal of System Simulation

Abstract: In order to evaluate the image quality of space on orbit telescope under the comprehensive constraints, the chain calculation analysis method is adopted. The main error factors of the optical image quality degradation are divided into six static errors and two dynamic errors. After calculation, the optical system wavefront aberration under the static loading error is reduced to 0.057λ on average. Under the influence of the static and dynamic errors, the 80% energy concentration of point spread function increases gradually. The method can be used to analyze and evaluate the influence of image stabilization control and precise temperature …

Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …

Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger

Electrical and Computer Engineering Publications

This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …

Updated Perspectives On The Role Of Biomechanics In Copd: Considerations For The Clinician, Jennifer M. Yentes, Wai-Yan Liu, Kuan Zhang, Eric J. Markvicka, Stephen I. Rennard

Department of Electrical and Computer Engineering: Faculty Publications

Patients with chronic obstructive pulmonary disease (COPD) demonstrate extra-pulmonary functional decline such as an increased prevalence of falls. Biomechanics offers insight into functional decline by examining mechanics of abnormal movement patterns. This review discusses biomechanics of functional outcomes, muscle mechanics, and breathing mechanics in patients with COPD as well as future directions and clinical perspectives. Patients with COPD demonstrate changes in their postural sway during quiet standing compared to controls, and these deficits are exacerbated when sensory information (eg, eyes closed) is manipulated. If standing balance is disrupted with a perturbation, patients with COPD are slower to return to baseline …

Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Rural Broadband Usage: Analyzing Satisfaction And Internet Speed Within The Rural Digital Divide, Angela Hollman, Tim Obermier, Jesse Andrews

Mountain Plains Business Conference

No abstract provided.

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti

Engineering Faculty Articles and Research

Due to various breakthroughs and advancements in machine learning and computer architectures, machine learning models are beginning to proliferate through embedded platforms. Some of these machine learning models cover a range of applications including computer vision, speech recognition, healthcare efficiency, industrial IoT, robotics and many more. However, there is a critical limitation in implementing ML algorithms efficiently on embedded platforms: the computational and memory expense of many machine learning models can make them unsuitable in resource-constrained environments. Therefore, to efficiently implement these memory-intensive and computationally expensive algorithms in an embedded computing environment, innovative resource management techniques are required at the …

Columnas: The Honors Program Newsletter At Bentley University, Debayan Sen, Hailey Jennato, Gabe Holmes, Daniel Furze

Honors Program

Page 1: SOCIAL MEDIA—A VEHICLE FOR SOCIAL CHANGE OR VIRTUE SIGNALING? ~ By Debayan Sen ’23

Page 2: WILL ARTIFICIAL INTELLIGENCE AND ROBOTICS REPLACE THE HUMAN WORKER? ~ By Hailey Jennato ’24

Page 3: HOW TO HEALTHILY COMMUNICATE IN A RELATIONSHIP: NO, NOT JUST A ROMANTIC ONE ~ By Gabe Holmes ’26

Page 4: THE W SLANT ~ By Daniel Furze ’26

Rewards And Challenges In Adopting Agility In An Academic Department, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu, Carlos Castro

Posters

Introducing agility into department processes may be challenging especially when interfacing with a non-agile environment. While frequent meetings can add more time constraints, the team environment emphasizes more communication, transparency, and accountability in completing the products leading to a higher sense of ownership of the completed work.

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 …

Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher Ph.D, 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 …

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 …

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.

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 …

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 …