Computer Sciences Commons^™

A Comprehensive Review On Deep Learning-Based Generative Linguistic Steganography, Dr Khaled Nagaty, Israa Lotfy Lotfy, Abeer Hamdy Dr.

Computer Science

. The recent development of deep learning has made a significant breakthrough in linguistic generative steganography. The text has become one of the most intensely used communication carriers on the Internet, making steganography an efficient carrier for concealing secret messages. Text steganography has long been used to protect the privacy and confidentiality of data via public transmission. Steganography utilizes a carrier to embed the data to generate a secret unnoticed and less attractive message. Different techniques have been used to improve the security of the generated text and quality of the steganographic text, such as the Markov model, Recurrent Neural …

Hyper-Heuristic Three Dimensional Eda For Solving Green Two-Sided Assembly Line Balancing Problem, Rong Hu, Shuai Ding, Bin Qian, Changsheng Zhang

Journal of System Simulation

Abstract: This paper establishes a model for green robotic two-sided assembly line balancing problem of type-I, and a hyper-heuristic three dimensional estimation of distribution algorithm (HH3DEDA) is proposed for solving this problem. In HH3DEDA, a combinatorial encoding rule based on process selectors is designed via considering the characteristics of the problem. Then, HH3DEDA with a high and low layered structure is proposed. In the upper layer, the three-dimensional probability matrix is utilized to learn high-quality high individual block structure and its distribution information, and then the matrix is sampled to generate new high level individuals. Each high individual is …

Research On Modeling And Solution Method Of Operational Tasks Optimization, Yue Ma, Lin Wu, Yun Liu, Guangzhao Ding

Journal of System Simulation

Abstract: Aiming at the problem of tasks optimization in operation task planning, this paper defines an operational tasks graph based on property graph and influence network to describe tasks, effects and their relationship. The model of operational tasks optimization is constructed based on the operational tasks graph, and the effect network transmission algorithm and resource constraint judgment algorithm are proposed. The problem is solved by the improved differential evolution algorithm. The experimental result shows that the operational tasks graph can vividly describe the relationship between operational tasks and effects, and the model and solution method are feasible and effective.

Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang

Journal of System Simulation

Abstract: In order to improve the convergence of multi-objective optimization algorithm and the diversity of optimization solution set, and alleviate the flown down of population in target space, a multi-objective optimization algorithm based on multi-attribute elite individual game mechanism is proposed. This paper uses Pareto dominance relationship and multi-index to comprehensively screen elite individuals. The elite individual game mechanism with K-means clustering is integrated with cross and mutation strategy, which effectively improves the convergence and diversity of the algorithm. A detailed convergence analysis of the algorithm is performed to prove the convergence of the algorithm. Eight representative comparison algorithms are …

Research On Decision Behavior Modeling Method Of Key Figures, Xiao Zheng, Xiaodong Peng, Minyu Lu, Tiejun Liu

Journal of System Simulation

Abstract: The decision-making of key figures is an important factor affecting the evolution of concerned events. The research on their decision-making behavior is of great significance for the prediction of important events. For the problem of decision behavior modeling and decision propensity prediction of key figures, the character attribute and measurement methods required for character modeling are analyzed, the character decision-making process and decision-making related influencing factors are analyzed, the exploration research of decision propensity prediction method is carried out, and the prediction model of decision propensity based on comprehensive interest characteristics and psychological characteristics is constructed. Through the research …

Flexible Job-Shop Scheduling Problem Based On Improved Wolf Pack Algorithm, Chaoyang Zhang, Liping Xu, Jian Li, Yihao Zhao, Kui He

Journal of System Simulation

Abstract: An improved wolf pack algorithm is proposed for solving multi-objective scheduling optimization for flexible job shop problems. A multi-objective flexible job shop scheduling model is developed with the maximum completion time of the workpiece and the energy consumption of the machine as the optimization goals. An improved wolf pack algorithm is proposed for solving the shortcomings that traditional wolf pack algorithm is easy to fall into the local optimization. Through improving the intelligent behavior of the wolf pack algorithm, individual codes are designed from the two levels of job's process and machine, and POX(precedence operation crossover) cross operation is …

Calculation Of Optimal Vocs Emission Reduction Based On Improved Seirs Model In Cloud Environment, Guangqiu Huang, Xixuan Zhao, Qiuqin Lu

Journal of System Simulation

Abstract: Volatile organic compounds (VOCs) emissions in different regions are correlated and influenced. In order to minimize the impact of VOCs on the atmospheric environment and achieve synergistic governance of VOCs regions, an optimal emission reduction model is established with the maximum VOCs emission reduction as the primary goal. An improved SEIRS infectious disease dynamics optimization algorithm considering environmental pollution(SEIRS-CE) is proposed and the model is solved in cloud environment. Taking Xi'an city as an example, the SEIRS-CE algorithm is used in Ali cloud server to calculate the emission reduction of VOCs associated with 13 meteorological monitoring stations in Xi …

Neutrosophic Model To Examine The Challenges Faced By Manufacturing Businesses In Adopting Green Supply Chain Practices And To Provide Potential Solutions, Zenat Mohamed, Mahmoud M. Ismail, Amal F. Abd El-Gawad

Neutrosophic Systems with Applications

Several obstacles stand in the way of companies trying to adopt green supply-chain practices. The purpose of this research is to examine the challenges faced by the industrial industry in adopting green supply chain practices and to provide potential solutions. The information for this research was gathered via in-depth, personal conversations with manufacturing sector managers who are well-versed in green supply chain practices. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) technique was used in the evaluation phase to evaluate obstacles and assess efficient options for introducing green supply chain practices. The TOPSIS method is integrated …

Learning-Based High-Performance Algorithm For Long-Term Motion Prediction Of Fluid Flows, Jingyuan Zhu, Huimin Ma, Jian Yuan

Journal of System Simulation

Abstract: Simulating the dynamics of fluid flows accurately and efficiently remains a challenging task nowadays, and traditional fluid simulation methods consume large computational resources to obtain accurate results. Deep learning methods have developed rapidly, which makes data-based fluid simulation and generation possible. In this paper, a motion prediction algorithm for long-term fluid simulation is proposed, which is based on a density field with a single frame and a previous velocity field of a sequence. The model focuses on matching the velocity and density fields predicted by the neural network with the simulated data based on the Navier-Stokes equation …

Simulation On Cooperative Control Of Connected And Automated Vehicles At Interchange Based On Petri Net, Mingbao Pang, Zhen Liu

Journal of System Simulation

Abstract: To improve the traffic efficiency of interchange, a simulation model of complete process is built by timed Petri net (TdPN) considering multiple separation and merging behaviors in the process of connected and automated vehicles (CAVs) passing through the interchange. In the light of vehicle priority, a speed guidance strategy is proposed and a CAVs cooperative control model is established, so as to form a complete interchange TdPN model. This method is verified by simulation and compared with the cooperative control method of interchange exit and its connecting area, cooperative control method of multi-merging areas within the interchange. The results …

Multi-Strategy Hybrid Abc For Microarray High-Dimensional Feature Selection, Chuandong Qin, Baosheng Li, Baole Han

Journal of System Simulation

Abstract: Traditional feature selection approaches have major limitations for high-dimensional microarrays, and it is difficult to accurately and efficiently propose the best feature subset. To address this problem, a multi-strategy hybrid artificial bee colony (ABC) algorithm based on wrapper is proposed, which mixes chaotic opposition-based learning strategy, elite guidance strategy, and Mantegna Lévy distribution strategy, and proposes two new search strategies in the employed and onlooker bee phases respectively. A new objective function is proposed for the microarray high-dimensional feature selection problem, which balances the optimal performance of the model with the minimization of the feature subset …

Dynamic Performance Evaluation Method For Transfer In Rail Transit Station Based On Station Simulation And Lstm, Bisheng He, Hongxiang Zhang, Yongjun Zhu, Gongyuan Lu

Journal of System Simulation

Abstract: Given the boom increasing of rail transit passenger volume, the dynamic performance evaluation method for transfer in rail transit stations based on machine learning are proposed to effectively evaluate the performance of the transfer station in different scenarios. Based on the proposed dynamic performance evaluation indexes of effective transfer number, transfer time and congestion, the influence factors of station dynamic performance are analyzed. The simulation model integrated train operation and pedestrian movement is built to provide the time-series data for the machine learning method. The long short-term memory (LSTM) is implemented to forecast the evaluation indicators, and the …

Application Of Digital Twin Model In Grinding Of Bearing Rings, Hongbin Liu, Zhiqiang Shen, Yize Wang, Ming Qiu, Wenrong Lin

Journal of System Simulation

Abstract: The digital twin model can effectively promote the virtual-real interaction between the actual product and the product model. Aiming at the grinding force generated in the grinding process of spherical roller bearings, this paper constructs the bearing ring raceway grinding process by performing dynamics, contact algorithm modeling and rigid-flexible coupling treatment on the components of the grinding work area. The digital twin model completes the virtual mapping of the grinding work area of the bearing ring in the digital space. The model is used to analyze and test the process parameters such as the grinding wheel linear speed and …

Multi-Media Energy Planning Optimization Of Steel Based On Improved Moea/D, Hongcai Ouyang, Dinghui Wu, Junyan Fan, Jing Wang

Journal of System Simulation

Abstract: To address the problems of multi-media iron and steel energy planning model with more variables, complex constraints and high difficulty in model solving, an improved MOEA/D (decomposition-based multi-objective evolutionary algorithm) based on adaptive neighborhood is proposed to realize multi-media energy planning optimization. Considering the characteristics of TOU price and the buffer effect of gas holder, the objective function to minimize operation cost and total energy consumption is constructed. And the model constraints are designed such as energy supply and demand balance. The decoding method based on energy production and consumption rules is designed to determine the target value. The …

A New Electromagnetic Positioning Model With Single Coil Receiver For Virtual Interventional Surgery, Jianhui Zhao, Peijun Zhong, Zhiyong Yuan, Wenyuan Zhao, Tingbao Zhang

Journal of System Simulation

Abstract: To meet the needs of 3D positioning of guide wire catheter in interventional surgery and the requirements of smaller size sensor for narrow cerebral vessels, a new electromagnetic positioning model is proposed with single coil receiver. Based on the electromagnetic theory and geometry principle, the electromagnetic field transmitter with groups of three orthogonal coils and the single coil receiver with smaller size than existing sensors are designed. Based on Biot-Savart Law, the distance between receiving end and geometric center of orthogonal coils is calculated, and spatial coordinate of receiving end is computed based on the spherical intersection formula. To …

Integrated Soft Sensor Modeling Of Fermentation Process Based On Transfer Component Analysis, Yuesheng Zhou, Weili Xiong

Journal of System Simulation

Abstract: The Penicillin fermentation process is an uncertain and multi-stage process. There are different working conditions among different batch fermentation processes, and the distribution of process data is not necessarily the same, which degrades the performance of the traditional soft sensing model. Combined with the transfer learning strategy and Gaussian mixture model, a multi-model ensemble soft sensor modeling method based on transfer component analysis is proposed. In this method, the transfer component analysis is used to get the shared feature mapping matrix between samples, and adapt the edge probability distribution of labeled dataset and unlabeled dataset; the modeling data are …

Lightweight Webvr Real-Time Simulation Of Large-Scale Fire Scenario In Metro, Yang Li, Huijuan Zhang, Chenchen Ge, Kang Xie, Zhuang Li, Jinyuan Jia

Journal of System Simulation

Abstract: Large-scale fire simulation requires a huge amount of calculation and excellent rendering capabilities, which poses a challenge to the realization of a real-time online fire simulation system on the Web. A lightweight Web-based real-time simulation technology framework for subway station fire is proposed. Based on the simplification of calculation formulas in the field of fire safety and the analysis of the impact of smoke prevention facilities in subway stations, a two-stage smoke diffusion model based on smoke bay is proposed to achieve the smoke diffusion trend calculation; a Web-side multi-granularity particle emitter framework at the smoke bay level is …

An Advanced Deep Learning Models-Based Plant Disease Detection: A Review Of Recent Research, Muhammad Shoaib, Babar Shah, Shaker Ei-Sappagh, Akhtar Ali, Asad Ullah, Fayadh Alenezi, Tsanko Gechev, Tariq Hussain, Farman Ali

All Works

Plants play a crucial role in supplying food globally. Various environmental factors lead to plant diseases which results in significant production losses. However, manual detection of plant diseases is a time-consuming and error-prone process. It can be an unreliable method of identifying and preventing the spread of plant diseases. Adopting advanced technologies such as Machine Learning (ML) and Deep Learning (DL) can help to overcome these challenges by enabling early identification of plant diseases. In this paper, the recent advancements in the use of ML and DL techniques for the identification of plant diseases are explored. The research focuses on …

Impacts Of Cutting-Edge Artificial Intelligence On Economic Research Paradigm, Yongmiao Hong, Shouyang Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Efficient Two-Stage Analysis For Complex Trait Association With Arbitrary Depth Sequencing Data, Zheng Xu, Song Yan, Shuai Yuan, Cong Wu, Sixia Chen, Zifang Guo

School of Computing: Faculty Publications

Sequencing-based genetic association analysis is typically performed by first generating genotype calls from sequence data and then performing association tests on the called genotypes. Standard approaches require accurate genotype calling (GC), which can be achieved either with high sequencing depth (typically available in a small number of individuals) or via computationally intensive multi-sample linkage disequilibrium (LD)-aware methods. We propose a computationally efficient two-stage combination approach for association analysis, in which single-nucleotide polymorphisms (SNPs) are screened in the first stage via a rapid maximum likelihood (ML)-based method on sequence data directly (without first calling genotypes), and then the selected SNPs are …

Predicting Code Refactoring Via Analyzing The History Of Quality Metrics And Code Anti-Patterns, Sarah Alanqari

College of Computing and Digital Media Dissertations

Code refactoring is the process of improving the internal structure of existing code without altering its functionality. Refactoring can help to reduce technical debt, enhance the quality of the code and make the code easy to evolve. However, the manual identification of the proper code refactoring operations to apply can be time-consuming and not scalable. In this thesis, we propose an approach based on data mining and machine learning techniques to analyze historical data and predict refactoring operations that may occur in a future release of a project. The approach uses a combination of techniques to identify patterns in the …

An Intelligent Decision Support Model For Optimal Selection Of Machine Tool Under Uncertainty: Recent Trends, Ibrahim M. Hezam

Neutrosophic Systems with Applications

Many scholars have been interested in the subject of machine tool selection as a result of the growing number of different machines and the continuous advancement of technology associated with these machines. The selection of an unsuitable machine tool may lead to a variety of issues, including limitations on production capacities and productivity indicators when taking into account both time and money from an industrial and practical perspective. The present strategy of selecting machine tools, known as multi-criteria decision-making (MCDM), relies on the subjective viewpoint the vast majority of the time. When selecting an appropriate machining tool, however, it is …

A Fog Computing Framework For Intrusion Detection Of Energy-Based Attacks On Uav-Assisted Smart Farming, Junaid Sajid, Kadhim Hayawi, Asad Waqar Malik, Zahid Anwar, Zouheir Trabelsi

All Works

Precision agriculture and smart farming have received significant attention due to the advancements made in remote sensing technology to support agricultural efficiency. In large-scale agriculture, the role of unmanned aerial vehicles (UAVs) has increased in remote monitoring and collecting farm data at regular intervals. However, due to an open environment, UAVs can be hacked to malfunction and report false data. Due to limited battery life and flight times requiring frequent recharging, a compromised UAV wastes precious energy when performing unnecessary functions. Furthermore, it impacts other UAVs competing for charging times at the station, thus disrupting the entire data collection mechanism. …

An Intelligent Decision Support Model For Optimal Selection Of Machine Tool Under Uncertainty: Recent Trends, Ibrahim M. Hezam

Neutrosophic Systems with Applications

Many scholars have been interested in the subject of machine tool selection as a result of the growing number of different machines and the continuous advancement of technology associated with these machines. The selection of an unsuitable machine tool may lead to a variety of issues, including limitations on production capacities and productivity indicators when taking into account both time and money from an industrial and practical perspective. The present strategy of selecting machine tools, known as multi-criteria decision-making (MCDM), relies on the subjective viewpoint the vast majority of the time. When selecting an appropriate machining tool, however, it is …

Toward Efficient Rendering: A Neural Network Approach, Qiqi Hou

Dissertations and Theses

Physically-based image synthesis has attracted considerable attention due to its wide applications in visual effects, video games, design visualization, and simulation. However, obtaining visually satisfactory renderings with ray tracing algorithms often requires casting a large number of rays and thus takes a vast amount of computation. The extensive computational and memory requirements of ray tracing methods pose a challenge, especially when running these rendering algorithms on resource-constrained platforms, and impede their applications that require high resolutions and refresh rates. This thesis presents three methods to address the challenge of efficient rendering.

First, we present a hybrid rendering method to speed …

Remote Medical Diagnosis Via Infrared Thermography And Augmented Reality, Frederick M. Selkey

USF Tampa Graduate Theses and Dissertations

Fast, accurate, and non-invasive diagnostic techniques are required by the medical industry to increase the success of medical treatments and enhance the quality of patient care. Medical IRT has been demonstrated reasonably effective at diagnosing and monitoring several physiological conditions. Diversities in the human body, physical and psychological condition, measurement equipment, and environment all influence the sensitive readings obtained by passive IR measurement devices. New standards for medical IRT and fever screening have been demonstrated effective, but there is limited adherence to the guidelines [36]. Absolute temperature readings require regular calibration checks and can easily be thrown off by noise. …

User-Centered Software Design: User Interface Redesign For Blockly–Electron, Artificial Intelligence Educational Software For Primary And Secondary Schools, Chenghong Cen, Guang Luo, Lujia Li, Yilin Liang, Kang Li, Tan Jiang, Qiang Xiong

All Works

According to the 2021 and 2022 Horizon Report, AI is emerging in all areas of education, in various forms of educational aids with various applications, and is carving out a similarly ubiquitous presence across campuses and classrooms. This study explores a user-centered approach used in the design of the AI educational software by taking the redesign of the user interface of AI educational software Blockly–Electron as an example. Moreover, by analyzing the relationship between the four variables of software usability, the abstract usability is further certified so as to provide ideas for future improvements to the usability of AI educational …

The Rise And Risks Of Internet Of Things, Diamond E. Hicks

Cybersecurity Undergraduate Research Showcase

Internet of Things (IoT) has become a necessary part of our everyday lives. IoT is the network in which many different devices communicate, connect, and share data. Though how IoT got to where it is today, the issues it faced, and how it affects our lives today is not common knowledge. Despite the fact that IoT has advanced our technology to what it is today, people do not completely understand what it does.

Delivering Computer-Based Training Within State Prisons, Kunal Jha

Theses and Dissertations

Internet-connected devices are ubiquitous, and our built environment allows us to tap into formerly impossible solutions. As our world increasingly depends on technology to operate, one demographic cannot gain exposure to internet-connected devices or web-based educational programs: incarcerated individuals. The Department of Justice reports that 5 out of 6 State Prisoners are arrested and returned to prison within nine years of their initial release. Research shows that education is a pathway to reducing the U.S. prison population. Individuals who participated in any educational program are 43 percent less likely to return to prison.1 Prisons in the United States often partner …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …