Engineering Commons^™

Recognition Method On Two-Phase Flow Regime Based On Cross Recursive Analysis, Yongbo He, Yushan Dong, Rongrong Xue

Journal of System Simulation

Abstract: Aiming at the problems that the two-phase flow regime recognition speed is slow and the recognition accuracy is low, a flow regime recognition method is proposed based on cross recursive analysis (CRA) without imaging. The false nearest neighbors are used to analyze flow regime capacitance values measured by capacitance sensor to obtain an optimal embedding dimension; and the embedding dimension of cross recursive plot is established for several typical flow patterns. The capacitance values of the simulation flow regimes and the reference flow regimes are analyzed using cross recursion to get a set of cross recursive plots. The similarity …

Extending Lifetime Of Sensor Networks Based On Sleep-Scheduled Routing Algorithm, Zhuojin Pan, Stuart D., Luo Zhen, Yang Hua

Journal of System Simulation

Abstract: In order to minimize energy consumption of sensor nodes in wireless sensor networks, this paper presents an Energy Efficient Sleep-Scheduled Tree-Based Routing Protocol (EESSTBRP) that modifies the chain formation in PEGASIS to create a set of paired and unpaired nodes in the network based on a distance and sensing range threshold. The paired nodes switch between active and sleep modes so as to remove redundant data and save battery power. To minimize energy consumption as nodes switching between the modes, this scheme considers the transitioning to be done based on a point of near depletion of the nodes’ residual …

Parameter Matching Optimization Of Pure Electric Vehicle Based On Firefly Algorithm, Li Yan, Yigang He

Journal of System Simulation

Abstract: According to the design requirements and technical index of pure electric vehicle, the parameters of motor and battery related to power and economic performance are selected based on the computing results. Based on ADVISOR, a vehicle model of pure electric vehicle is established in MATLAB environment with the corresponding parameters validating the simulation results. On this basis, the multi-objective function is established, which includes the power performance, economic performance and cost price. This function is optimized by the firefly algorithm, which makes the dynamic parameters, the dynamic performance and economy performance of pure electric vehicle be improved significantly and …

Comparison And Analysis Of Output Performance Of Different Pv Structures Under Shadows, Yonghong Xia, Mengru Li, Jianbo Xin, Zen Fanpeng, Yunjun Yu

Journal of System Simulation

Abstract: The output power of PV array not only depends on the irradiance intensity of the partial shadows, but also on the shadows shape. For the serious power loss under partial shadows of the traditional SP (Series-Parallel) and TCT (Total-Cross-Tied) structures, an optimized TCT structure is proposed. Output capacity comparison was made based on the three structures in five shadow modes under the circumstances of the severe shadows and uneven irradiation. By using Matlab/ Simulink software, the output performance of the three structures was simulated under different shadow shapes in symmetrical and asymmetric arrays. The results show that PV array …

Identification And Prediction Of Room Temperature Delay Neural Network Model For Vav Air Conditioning, Xiuming Li, Jili Zhang, Tianyi Zhao, Tingting Chen

Journal of System Simulation

Abstract: Aiming at the problem of mathematical description for dynamic response characteristic of indoor temperature time-delay system, the fundamental principle of neural network model identification is introduced in regulation process of variable air volume (VAV) air conditioning system. Considering the model structure of Elman neural network, this paper presents an optimal selection algorithm for layer delay coefficient in order to determine delay time between indoor temperature and regulation parameters; and a multiple-step prediction model of indoor temperature time-delay system based on Elman neural network is built. The effectiveness of the proposed method is validated through the simulation experiment.

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

Journal of System Simulation

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

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

Journal of System Simulation

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

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

Journal of System Simulation

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

Sliding Mode Auto Disturbance Rejection Control Of Pmsm Without Speed Sensor, Limin Hou, Yifu Ren, Hengfei Liu, Lin Dong

Journal of System Simulation

Abstract: Aiming at the problem of parameter setting and response speed of the traditional ADRC method, a kind of novel sliding mode auto disturbance rejection speed controller is designed, and a sliding mode adaptive speed control system of PMSM without speed sensor is established. The nonlinear disturbance observer (NDOB) is used to replace the extended state observer (ESO) integrated disturbance estimation. The sliding mode control is introduced in the nonlinear state error feedback control; the sliding mode ADRC current controller and speed controller are designed; and the stability is proved by using Lyapunov theory. The rotor position and speed of …

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

Journal of System Simulation

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

A New Memristor Chaotic System And Its Application In Image Encryption, Shuanghui Qu, Zhihong Yang, Xuwei Rong, Shuhua Wu

Journal of System Simulation

Abstract: A new memristor chaotic system is designed by the method of bringing an ion migration memristor into the Chen system equation. The basic dynamic characteristics of the memristive system are investigated via bifurcation, Lyapunov exponent et al, which proves the validity of the new system. The new memristor system is applied in the image encryption to improve the security of the encryption key. A dual encryption algorithm is used, which makes every pixel value of plaintext influence all pixel values of ciphertext. Although there is no direct link between plaintext and ciphertext, the sensibility of ciphertext varying with …

Design Of Adaptive Predictive Controller For Superheated Steam Temperature Control, Qian Hong, Yuqing Feng

Journal of System Simulation

Abstract: An adaptive model predictive controller for overheating steam temperature control of thermal power plants is designed, which is based on the control object with large delay, large inertia, nonlinearity and strong time-varying properties. Through the on-line identification and control of different models, compared with predictive controllers in a general model, in terms of adjusting the superheat steam temperature, the adjusting time can be shortened drastically, the overshoot can be reduced or even eliminated, and the dynamic performance is improved greatly when applying in adaptive model predictive controller. The results show that the adaptive model predictive controller, because of its …

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

Journal of System Simulation

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

Rfid Item-Level Tagging In A Grocery Store Environment, Brian Truman

LSU Master's Theses

The purpose of this research was to investigate how effective item-level Radio Frequency Identification (RFID) tagging would be using current RFID technology as a replacement for barcodes in a supermarket/grocery store environment.

To accomplish this, an experiment was be performed that utilized commercially available RFID technology. Passive Ultra High Frequency (UHF) RFID Tags were affixed to various grocery store items of different material categories (Food, Metal, Plastic, Liquid, and Glass), and placed in a metal shopping cart. Eight (8) antenna arrangements were created, comprised of different combinations of four (4) antennas in different locations around the cart.

The experiment was …

Effective Fuzzing Framework For The Sleuthkit Tools, Shravya Paruchuri

LSU Master's Theses

The fields of digital forensics and incident response have seen significant growth over the last decade due to the increasing threats faced by organizations and the continued reliance on digital platforms and devices by criminals. In the past, digital investigations were performed manually by expert investigators, but this approach has become no longer viable given the amount of data that must be processed compared to the relatively small number of trained investigators. These resource constraints have led to the development and reliance on automated processing and analysis systems for digital evidence. In this paper, we present our effort to develop …

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

Journal of System Simulation

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

Algorithms For Designing Processes Of Electronic Interactive Services, Ozod Radjabov

Bulletin of TUIT: Management and Communication Technologies

Today, the integration of electronic interactive services is based on the correct placement of algorithms to ensure solidarity in information systems, the design stages of information systems based on interactive services and the corresponding events, the implementation of functions in a strict sequence.

A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh

Doctoral Dissertations

High performance parallel computing and direct (factorization-based) solution methods have been the two main trends in electromagnetic computations in recent years. When time-harmonic (frequency-domain) Maxwell's equation are directly discretized with the Finite Element Method (FEM) or other Partial Differential Equation (PDE) methods, the resulting linear system of equations is sparse and indefinite, thus harder to efficiently factorize serially or in parallel than alternative methods e.g. integral equation solutions, that result in dense linear systems. State-of-the-art sparse matrix direct solvers such as MUMPS and PARDISO don't scale favorably, have low parallel efficiency and high memory footprint. This work introduces a new …

Reputation-Aware Trajectory-Based Data Mining In The Internet Of Things (Iot), Samia Tasnim

FIU Electronic Theses and Dissertations

Internet of Things (IoT) is a critically important technology for the acquisition of spatiotemporally dense data in diverse applications, ranging from environmental monitoring to surveillance systems. Such data helps us improve our transportation systems, monitor our air quality and the spread of diseases, respond to natural disasters, and a bevy of other applications. However, IoT sensor data is error-prone due to a number of reasons: sensors may be deployed in hazardous environments, may deplete their energy resources, have mechanical faults, or maybe become the targets of malicious attacks by adversaries. While previous research has attempted to improve the quality of …

Trajectory Privacy Preservation And Lightweight Blockchain Techniques For Mobility-Centric Iot, Abdur Bin Shahid

FIU Electronic Theses and Dissertations

Various research efforts have been undertaken to solve the problem of trajectory privacy preservation in the Internet of Things (IoT) of resource-constrained mobile devices. Most attempts at resolving the problem have focused on the centralized model of IoT, which either impose high delay or fail against a privacy-invading attack with long-term trajectory observation. These proposed solutions also fail to guarantee location privacy for trajectories with both geo-tagged and non-geo-tagged data, since they are designed for geo-tagged trajectories only. While a few blockchain-based techniques have been suggested for preserving trajectory privacy in decentralized model of IoT, they require large storage capacity …

Malware Analysis For Evaluating The Integrity Of Mission Critical Devices, Robert Heras

FIU Electronic Theses and Dissertations

The rapid evolution of technology in our society has brought great advantages, but at the same time it has increased cybersecurity threats. At the forefront of these threats is the proliferation of malware from traditional computing platforms to the rapidly expanding Internet-of-things. Our research focuses on the development of a malware detection system that strives for early detection as a means of mitigating the effects of the malware's execution.

The proposed scheme consists of a dual-stage detector providing malware detection for compromised devices in order to mitigate the devices malicious behavior. Furthermore, the framework analyzes task structure features as well …

Security Of The Internet Of Things: Vulnerabilities, Attacks And Countermeasures, Ismail Butun, Houbing Song, Patrik Osterberg

Publications

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. Hence, …

Water Pipeline Leakage Detection Based On Machine Learning And Wireless Sensor Networks, Yang Liu, Xuehui Ma, Yong Tie, Yinghui Zhang, Jing Gao

Department of Electrical and Computer Engineering: Faculty Publications

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and …

Machine Current Sensor Fdi Strategy In Pmsms, Haibo Li, Yi Qian, Sohrab Asgarpoor, Hamid Sharif

Department of Electrical and Computer Engineering: Faculty Publications

This work proposes a machine current sensor fault detection and isolation (FDI) strategy in permanent magnet synchronous machines (PMSMs) resilient to multiple faults. The fault detection is performed by comparing the measured and estimated DC link currents. The fault isolation is achieved according to machine phase signal estimation and the corresponding residual examination. Single sensor fault, multiple sensor faults and non-sensor fault are covered by the proposed FDI method. The proposed sensor FDI method is not influenced by machine imbalance, feasible for FDI of both single and multiple machine current sensor faults, and capable of distinguishing between machine current sensor …

Algorithms And Circuits For Analog-Digital Hybrid Multibeam Arrays, Paboda Viduneth A. Beruwawela Pathiranage

FIU Electronic Theses and Dissertations

Fifth generation (5G) and beyond wireless communication systems will rely heavily on larger antenna arrays combined with beamforming to mitigate the high free-space path-loss that prevails in millimeter-wave (mmW) and above frequencies. Sharp beams that can support wide bandwidths are desired both at the transmitter and the receiver to leverage the glut of bandwidth available at these frequency bands. Further, multiple simultaneous sharp beams are imperative for such systems to exploit mmW/sub-THz wireless channels using multiple reflected paths simultaneously. Therefore, multibeam antenna arrays that can support wider bandwidths are a key enabler for 5G and beyond systems.

In general, N- …

Shortest Path Calculation Using Contraction Hierarchy Graph Algorithms On Nvidia Gpus, Roozbeh Karimi

LSU Doctoral Dissertations

PHAST is to date one of the fastest algorithms for performing single source shortest path (SSSP) queries on road-network graphs. PHAST operates on graphs produced in part using Geisberger's contraction hierarchy (CH) algorithm. Producing these graphs is time consuming, limiting PHAST's usefulness when graphs are not available in advance. CH iteratively assigns scores to nodes, contracts (removes) the highest-scoring node, and adds shortcut edges to preserve distances. Iteration stops when only one node remains. Scoring and contraction rely on a witness path search (WPS) of nearby nodes. Little work has been reported on parallel and especially GPU CH algorithms. This …

Bibliometric Survey Of Privacy Of Social Media Network Data Publishing, Rupali Gangarde Ass. Prof., Amit Sharma Dr., Ambika Pawar Dr.

Library Philosophy and Practice (e-journal)

We are witness to see exponential growth of the social media network since the year 2002. Leading social media networking sites used by people are Twitter, Snapchats, Facebook, Google, and Instagram, etc. The latest global digital report (Chaffey and Ellis-Chadwick 2019) states that there exist more than 800 million current online social media users, and the number is still exploding day by day. Users share their day to day activities such as their photos and locations etc. on social media platforms. This information gets consumed by third party users, like marketing companies, researchers, and government firms. Depending upon the purpose, …

The Art Of Selecting Phd Students: Combination Of Bibliometric And Ahp Approach, Preeti Mulay Dr., Rahul Raghvendra Joshi Prof., Sophia Gaikwad Dr.

Library Philosophy and Practice (e-journal)

For the PhD guide or the advisor selecting the accurate PhD scholar is the most elephantine task. It actually requires an art for the perfect selection; as the length, breadth, depth and volume of PhD work is spread across the years and this relationship between the scholar and the guide should start and flourish positively for the immense experience throughout the PhD process. Hence it was essential to understand bibliometric details including how many researchers have already published their contributions in the form of papers and patents, in the Scopus database. In addition to the bibliometric details, in this study, …

Document Layout Analysis And Recognition Systems, Sai Kosaraju

Master of Science in Computer Science Theses

Automatic extraction of relevant knowledge to domain-specific questions from Optical Character Recognition (OCR) documents is critical for developing intelligent systems, such as document search engines, sentiment analysis, and information retrieval, since hands-on knowledge extraction by a domain expert with a large volume of documents is intensive, unscalable, and time-consuming. There have been a number of studies that have automatically extracted relevant knowledge from OCR documents, such as ABBY and Sandford Natural Language Processing (NLP). Despite the progress, there are still limitations yet-to-be solved. For instance, NLP often fails to analyze a large document. In this thesis, we propose a knowledge …

Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder, Yufei Tian, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we study abstractive review summarization. Observing that review summaries often consist of aspect words, opinion words and context words, we propose a two-stage reinforcement learning approach, which first predicts the output word type from the three types, and then leverages the predicted word type to generate the final word distribution. Experimental results on two Amazon product review datasets demonstrate that our method can consistently outperform several strong baseline approaches based on ROUGE scores.