Computer Sciences Commons^™

Research On Key Technology Of Uavs Autonomous Landing Based On Relative Precise Point Position, Guohua Kang, Teng Zhao, Yao Fu, Weizheng Xu, Jianyu Wei, Yuhuan Qiu, Junfeng Wu

Journal of System Simulation

Abstract: In complex sea conditions with wind and waves, the relative motion between unmanned aerial vehicles (UAVs) requiring autonomous landing and ships is highly uncertain. In order to improve the accuracy of relative positioning and control during autonomous landing, and to ensure the safety and reliability of autonomous landing, a relative precise point positioning (RPPP) technique based on differential tropospheric error is proposed. The technology only relies on data link and carrier satellite positioning receiver to eliminate the same error of satellite positioning in the same environment and obtain accurate relative positioning. The combination of proportional navigation and linear quadratic …

Robust Optimal Configuration Of Pv-Energy Storage In Industrial Parks Considering The Uncertainty Of Photovoltaics, Guiting Xue, Boya Shan, Ti Wang, Xiao Wang, Wei Xing, Weiqing Sun

Journal of System Simulation

Abstract: Research on using rooftop resources in industrial parks to develop photovoltaic projects and reasonable configuration of energy storage will help improve the park's energy economy. To obtain the optimal PV-storage configuration scheme, an industrial park with three types of load demand, namely, cold, heat and electricity, is selected, and a robust optimization allocation model of park PV-storage is established with optimal operating profit as the objective function, considering the increased cost of power purchase caused by the PV uncertainty. The model uses the box uncertainty set in robust optimization for PV intensity, and linearizes the model using pairwise …

Evacuation Model Considering The Restricted View Of The Sign, Yinghua Song, Zheqian Zhang, Feizhou Huo, Danhui Fang

Journal of System Simulation

Abstract: In order to study the influence of restricted vision on the process of pedestrian evacuation, a cellular automata model of pedestrian evacuation under restricted vision is established. In the model, the evacuation space is divided into three different areas according to the field of view radius, pedestrians have different ways of moving in different areas. Different income parameters are defined to calculate the pedestrian movement income matrix and determine the target position of the pedestrian in the next time step. An evacuation scene is established to simulate the initial density of different pedestrians, the change of the field of …

Simulation Of O2o Platform Transaction Considering The Constituted Information, Wen Zheng, Ke Shi, Jingyi Zhu

Journal of System Simulation

Abstract: In the transactions concluded with the help of APP, the information intervenes into the transaction process in the form of constituted information. The constituted information is classified into three degrees in a two-sided market. By introducing the three degrees of the constituted information: information acceptance (IA), information diversity (ID) and information loss (IL), the Swarm Class Library and the interactive Agents are designed to construct a systematic O2O (online to offline)platform transaction model, which encapsulates the Consumer/Seller/PlatformAgents. The constituted information acts as the systematic conditions of invoking and judging, and the graphical user interface (GUI) outputs the …

Simulation And Experiment Of An Intelligent Control Model For The Cleaning Of A Rice-Wheat Combine Harvester, Qing Jiang, Rujing Wang

Journal of System Simulation

Abstract: Modeling and simulation of cleaning intelligent control according to the changes of cleaning loss rate and trash content rate is the focus of research and hot issues of intelligent control of rice-wheat combine harvester. A method for acquiring knowledge of the experts' experience and knowledge is constructed based on the flow chart of cleaning control, and a cleaning intelligent control knowledge base for the intelligent control of the field operation environment based on the production rule is proposed. Based on the principle of human-simulating intelligent control, a knowledge inference algorithm for adaptive selection of cleaning regulation strategy is …

Research On Mobile Edge Computing Resource Allocation With Energy Harvesting Device, Changyun Li, Jianbo Li, Xi Xu, Tingli Li

Journal of System Simulation

Abstract: In order to solve the problem of computing resource allocation of mobile edge computing system with energy gathering ability, an algorithm based on Lyapunov greed optimization (LGO) is proposed. This paper presents a dynamic optimization problem to minimize the combined cost of time delay and energy consumption of mobile devices under the gradual convergence of equipment battery power. Using Lyapunov dynamic optimization theory, the optimization problem is decomposed into three sub-problems of optimal local execution, unloading execution and energy harvesting for each time slot, and the optimal solution of the sub-problems is obtained by linear programming. By selecting the …

Multi-Uav Trajectory Planning Based On Adaptive Segmented Potential Field Method, Guangjian Tian, Jiyang Dai, Jin Ying, Ning Wang

Journal of System Simulation

Abstract: To solve the problems that the traditional artificial potential field method is prone to fall into the local extreme value, target unreachability and excessive curvature of the planned trajectory curvature in the application of UAV trajectory planning, on the basis of the layered potential field method, a method of adding a second local attractive field at the target point and an attractive set composed of the target attractive field is proposed. This method overcomes the defects of unreachable targets and easy falling into local extremes. In addition, a piecewise function is introduced into the original layered potential field method, …

Nonlinear System Identification Based On Combined Signal Sources, Tian Zheng, Feng Li, Naibao He, Ya Gu

Journal of System Simulation

Abstract: Aiming at the interference of noise in the nonlinear system, the identification modeling method of the neuro-fuzzy Hammerstein output error nonlinear system is considered. The combined signal sources are used to realize the parameter identification separation of the linear block and the nonlinear block. The correlation analysis method and the recursive least square identification method based on auxiliary model technique are derived to estimate the parameters of dynamic linear block and nonlinear block, which can effectively suppress the interference of system output noise. Compared with least square algorithm, polynomial model and multi-innovation method, the simulation results demonstrate that the …

Research On Network Public Opinion Transmission Mechanism Of Inversion Event Based On Integrating Improved Sir Model, Jianrong Tang, Jiatong Bao

Journal of System Simulation

Abstract: In order to identify the spreading rules of rumors in vicious news reversal events and make more targeted guiding decisions, a short-term prediction model is proposed to simulate the spread of virus information. This paper improves the traditional susceptible infected removed (SIR) model and solves the problem that the conversion rate is fixed and single due to the limitation of Markov chain when it is combined with systems dynamics (SD) model. The data is validated with the example of "asthmatic girls" . The results show that the model not only effectively simulates the crisis of public opinion communication in …

A Real-Time Ultrasound Simulation Platform Using Ray Tracing And Its Integration With Virtual Reality, Bo Peng, Qiang Wang, Ruibing Qing, Lixue Yin, Jingfeng Jiang

Journal of System Simulation

Abstract: In order to further improve the efficacy of ultrasound training and reduce the cost. An ultrasound training system that is integrated with a VR environment is developed. The main contribution of this study is to incorporate the Ray-tracing based ultrasound image simulation approach into a virtual reality environment, taking advantage of immersive VR experience for medical ultrasound training. The simulated ultrasound images obtained by the proposed method are then compared to images that are simulated using a generative adversarial network (GAN) technique and Field II ultrasound simulator. The data show that the ultrasound simulator can produce high-quality simulated …

A Two-Layer Network Propagation Model Of Awareness Diffusion And Seir Epidemic, Yurong Song, Yulin Bao, Ruqi Li

Journal of System Simulation

Abstract: In order to understand the transmission characteristics of epidemics similar to COVID-19 (coronavirus disease 2019) with obvious expose period, a two-layer network transmission model considering time-varying factors is proposed to make corresponding predictions and measures. The UAU (unaware-aware-unaware) information transmission model is used to represent the diffusion process of conscious information about epidemic. In the underlying network, the susceptible-exposed-infected- recovered (SEIR) epidemic-like transmission model with latent state is used to describe the epidemic transmission process affected by conscious information. The MMCA (microscopic Markov chain approach) is used to deduce the transmission threshold of epidemics diseases. By analyzing the key …

Design And Simulation-Based Evaluation Of Taxiway Operation Scheme For Multi-Runway Airport Maneuvering Area, Xinping Zhu, Chuan Xu, Jingjing Qu, Tingwen Su

Journal of System Simulation

Abstract: The operational scheme of the taxiway system is very important to promote the efficient utilization of airfield resources in multi-runway airports. The design and simulation evaluation methods of the taxiway operation scheme for multi-runway airports are studied. The design principles of "fixed, unidirectional, compliant and circular" taxiway operation scheme and the design paradigm of the operation scheme are presented, and the concepts of taxiway space occupancy index and potential conflict index are proposed. Using Haikou Meilan International Airport as the application scenario, the corresponding optimization scheme of the taxiway system in the maneuvering area is given based on …

Multi-Market Coupling Trading Simulation Of Electricity Green Certificate And Excess Consumption Under New Renewable Portfolio Standard, Peng Wang, Xiaohua Song, Haowen Yang, Xiaoying Zhai, Jingjing Han, Liwei Ju

Journal of System Simulation

Abstract: In order to clarify the multi-scale market coupling interaction relationship of electricity, green certificate, excess consumption under the renewable portfolio standards (RPS), the system dynamics is introduced, and the interactive trading model is constructed and simulated. Taking the logistics transformation of three market transaction targets as the clue, this paper designs a multi-scale market coupling transaction framework, constructs the complex causality of coupling transaction based on system dynamics method, and analyzes the impact of RPS on the revenue or cost of market participants. Simulation results show that under the new RPS, the electricity price will gradually decline, the …

Transresnet: Integrating The Strengths Of Vits And Cnns For High Resolution Medical Image Segmentation Via Feature Grafting, Muhammad Hamza Sharif, Dmitry Demidov, Asif Hanif, Mohammad Yaqub, Min Xu

Computer Vision Faculty Publications

High-resolution images are preferable in medical imaging domain as they significantly improve the diagnostic capability of the underlying method. In particular, high resolution helps substantially in improving automatic image segmentation. However, most of the existing deep learning-based techniques for medical image segmentation are optimized for input images having small spatial dimensions and perform poorly on high-resolution images. To address this shortcoming, we propose a parallel-in-branch architecture called TransResNet, which incorporates Transformer and CNN in a parallel manner to extract features from multi-resolution images independently. In TransResNet, we introduce Cross Grafting Module (CGM), which generates the grafted features, enriched in both …

A Robust Normalizing Flow Using Bernstein-Type Polynomials, Sameera Ramasinghe, Kasun Fernando, Salman Khan, Nick Barnes

Computer Vision Faculty Publications

Modeling real-world distributions can often be challenging due to sample data that are subjected to perturbations, e.g., instrumentation errors, or added random noise. Since flow models are typically nonlinear algorithms, they amplify these initial errors, leading to poor generalizations. This paper proposes a framework to construct Normalizing Flows (NFs) which demonstrate higher robustness against such initial errors. To this end, we utilize Bernstein-type polynomials inspired by the optimal stability of the Bernstein basis. Further, compared to the existing NF frameworks, our method provides compelling advantages like theoretical upper bounds for the approximation error, better suitability for compactly supported densities, and …

Face Pyramid Vision Transformer, Khawar Islam, Muhammad Zaigham Zaheer, Arif Mahmood

Computer Vision Faculty Publications

A novel Face Pyramid Vision Transformer (FPVT) is proposed to learn a discriminative multi-scale facial representations for face recognition and verification. In FPVT, Face Spatial Reduction Attention (FSRA) and Dimensionality Reduction (FDR) layers are employed to make the feature maps compact, thus reducing the computations. An Improved Patch Embedding (IPE) algorithm is proposed to exploit the benefits of CNNs in ViTs (e.g., shared weights, local context, and receptive fields) to model lower-level edges to higher-level semantic primitives. Within FPVT framework, a Convolutional Feed-Forward Network (CFFN) is proposed that extracts locality information to learn low level facial information. The proposed FPVT …

The Importance Of Social Engineering, Jalaya Allen

Cybersecurity Undergraduate Research Showcase

Most people are afraid of being attacked when walking to their car, relaxing at home, or doing normal things like shopping. Though the unlikeliest of attacks have become one of the most dangerous. Just imagine someone having the ability to watch your every move online and virtually. They can find your credit card information, passwords, social security number and so much more. Then with that information, they can steal your identity and sell it on the black market as well as threaten you for money. Attacks like these use something called Social Engineering to trick the user into giving up …

An Effective Deep Learning Approach For The Classification Of Bacteriosis In Peach Leave, Muneer Akbar, Mohib Ullah, Babar Shah, Rafi Ullah Khan, Tariq Hussain, Farman Ali, Fayadh Alenezi, Ikram Syed, Kyung Sup Kwak

All Works

Bacteriosis is one of the most prevalent and deadly infections that affect peach crops globally. Timely detection of Bacteriosis disease is essential for lowering pesticide use and preventing crop loss. It takes time and effort to distinguish and detect Bacteriosis or a short hole in a peach leaf. In this paper, we proposed a novel LightWeight (WLNet) Convolutional Neural Network (CNN) model based on Visual Geometry Group (VGG-19) for detecting and classifying images into Bacteriosis and healthy images. Profound knowledge of the proposed model is utilized to detect Bacteriosis in peach leaf images. First, a dataset is developed which consists …

How To Train Vision Transformer On Small-Scale Datasets?, Hanan Gani, Muzammal Naseer, Mohammad Yaqub

Computer Vision Faculty Publications

Vision Transformer (ViT), a radically different architecture than convolutional neural networks offers multiple advantages including design simplicity, robustness and state-of-the-art performance on many vision tasks. However, in contrast to convolutional neural networks, Vision Transformer lacks inherent inductive biases. Therefore, successful training of such models is mainly attributed to pre-training on large-scale datasets such as ImageNet with 1.2M or JFT with 300M images. This hinders the direct adaption of Vision Transformer for small-scale datasets. In this work, we show that self-supervised inductive biases can be learned directly from small-scale datasets and serve as an effective weight initialization scheme for fine-tuning. This …

Accurately Grasp The New Features Of Cybersecurity Technology Development And Fully Promote The Modernization Of National Security System And Capabilities, Dengguo Feng

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Studies On The Development Of China’S Network And Information Security, Jiwu Jing

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Lost At Sea: The Nintendo Gamecube’S Failure And The Transformation Of An Industry 1996-2006, Izsak Kayne Barnette

Doctoral Dissertations and Projects

The history of video games is critically underdeveloped. Long simmering under a veil of academic neglect, video games have long been denied the sort of academic relevance of their sister industries: books, film, music, and TV. It is long-past time that such neglect was addressed. Most historical analyses of games begin with their origins in the 1950s, discuss their ubiquity during the heyday of Atari or Nintendo, or rope in modern views of games as tools of diversity and inclusion. Very few studies pay attention to the rather ugly adolescent years of the game industry, its motorcycle-jacket wearing, rebellious teenage …

Hybrid Feature Selection Based On Principal Component Analysis And Grey Wolf Optimizer Algorithm For Arabic News Article Classification, Osama Ahmad Alomari, Ashraf Elnagar, Imad Afyouni, Ismail Shahin, Ali Bou Nassif, Ibrahim Abaker Hashem, Mohammad Tubishat

All Works

The rapid growth of electronic documents has resulted from the expansion and development of internet technologies. Text-documents classification is a key task in natural language processing that converts unstructured data into structured form and then extract knowledge from it. This conversion generates a high dimensional data that needs further analusis using data mining techniques like feature extraction, feature selection, and classification to derive meaningful insights from the data. Feature selection is a technique used for reducing dimensionality in order to prune the feature space and, as a result, lowering the computational cost and enhancing classification accuracy. This work presents a …

The Minority In The Minority, Black Women In Computer Science Fields: A Phenomenological Study, Blanche' D. Anderson

Doctoral Dissertations and Projects

The purpose of this transcendental phenomenological study was to describe the lived experiences of Black women with a bachelor’s, master’s, or doctoral degree in computer science, currently employed in the United States. The theory guiding this study was Krumboltz’s social learning theory of career decision-making, as it provides a foundation for understanding how a combination of factors leads to an individual’s educational and occupational preferences and skills. This qualitative study answered the following central research question: What are the lived experiences of Black women with a bachelor’s, master’s, or doctoral degree in computer science, currently employed in the United States? …

Exploring Misinformation Campaigns And How To Defend Against Them, Michelle S. Kuralt

Theses and Dissertations

Misinformation campaigns can have very real and lasting effects. Misinformation has been known to impact elections, create vaccine hesitancy, and increase polarization within societies. This paper reviewed existing literature regarding misinformation research, collected information from research participants to discern factors which may contribute to an increased susceptibility to misinformation, and examined Rule Based Training and a training program which utilized both rules and mindfulness to ascertain if these training programs might be effective in reducing participant susceptibility to misinformation.

A Review Of Risk Concepts And Models For Predicting The Risk Of Primary Stroke, Elizabeth Hunter, John D. Kelleher

Articles

Predicting an individual's risk of primary stroke is an important tool that can help to lower the burden of stroke for both the individual and society. There are a number of risk models and risk scores in existence but no review or classification designed to help the reader better understand how models differ and the reasoning behind these differences. In this paper we review the existing literature on primary stroke risk prediction models. From our literature review we identify key similarities and differences in the existing models. We find that models can differ in a number of ways, including the …

Computer Engineering Education, Marilyn Wolf

School of Computing: Conference and Workshop Papers

Computer engineering is a rapidly evolving discipline. How should we teach it to our students?

This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.

A Framework For Securing Edge Computing In Medical Devices, David Mcquaid

HECA Research Conference

Edge computing brings data collection, processing and analysis closer to data sources, either enabling execution within devices themselves or outsourcing to local servers and data centres instead of central locations The basic idea is to minimize data transmission time as much as possible and to leverage the implicit processing power that most IOT’s hardware possess.

Simulations Of Plasma Species During Liquid Plasma Interaction In Two Phase Flow At Atmospheric Pressure, Muhammad Iqbal

HECA Research Conference

Understand the characteristics of liquid plasma interaction in the PlasmaStream atmospheric pressure jet deposition system (PSAJD) during downward transport and find the operating conditions under which it will be useful for various applications, such as medicine, tissue engineering and surface deposition of materials. How to solve this problem using numerical modelling as well as computer programming? Which mathematical model would be most appropriate to describe the essential characteristics of plasma in the PlasmaStream System?

Integrating Computing Into Preservice Teacher Preparation Programs Across The Core: Language, Mathematics, And Science, Lauren E. Margulieux, Patrick Enderle, Pier Junor Clarke, Natalie King, Caroline Sullivan, Michelle Zoss, Joyce Many

Journal of Computer Science Integration

This paper describes the beginning of a design-based research project for integrating computing activities in preservice teacher programs throughout a middle and secondary education department. Computing integration activities use computing tools, like programming, to support learning in non-computing disciplines. The paper begins with the motivation for integrating computing that encouraged widespread buy-in, design goals, and design parameters. The primary motivating factor for this work was preparing teachers to use technology to support learning in their classrooms. Involving computing education faculty in the preparation enabled the activities to include computer science and spread computational literacy. The paper also describes the process …