Computer Engineering Commons^™

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 …

Spatial Spectrum Estimation Method Of Flank Twin-Line Array Based On Cross-Spectrum Correlation, Zhizhong Li, Wang Sen, Zhongliang Xu, Weiguo Dai, Qijun Liu

Journal of System Simulation

Abstract: Considering the structural features of the flank twin-line array, researches on spatial spectrum estimation of twin-line array based on adaptive beam-forming and cross-spectrum correlation were carried out. A spatial spectrum estimation method based on cross-spectrum correlation is proposed according to the theory of cross-spectrum. The study of spectrum estimation performance comparison of the twin-line array was finished by that method combined with the conventional beam-forming and the adaptive beam-forming respectively. The results prove that the method based on cross-spectrum correlation has a better capability in noise suppression; and the method, which combined adaptive beam-forming with cross-spectrum correlation, is the …

Influence Of Composite Materials Surface Metal Mesh On Helicopter Lightning Stroke Effects, Junling Huang, Jiayu Xie

Journal of System Simulation

Abstract: The metal wire mesh is usually adopted to prevent the lightning stroke on composite materials. The effects of different materials and different thickness of metal mesh on helicopter lightning electromagnetic effect are compared. According to the method recommended by SAE-ARP5416, a numerical simulation software is used for carrying out the high current injection simulation. The results show that the surface mount metal mesh can effectively reduce the harm of lightning electromagnetic coupling effect; the difference between aluminum and copper on anti-lightning stroke effect is not obvious; when the thickness of aluminum grid is less than 0.15 mm, the …

Thai Language Names, Place Names And Organization Names Entity Recognition, Hongbin Wang, Hongkui Gao, Shen Qiang, Yantuan Xian

Journal of System Simulation

Abstract: Named entity recognition in Thai language is aimed to identify the names of a person, a locality,an organization or an institution,and so on. Due to the complexity of Thai word formation method and grammar rules, to solve this problem, the idea of the approach proposed is to treat the task of named entity recognition in Thai language as labeling the sign of a series of words in Thai sentence. Given the characteristics of Thai language itself, certain features in the context of the samples in the Thai entity recognition corpus are extracted to train the hidden Markov model and …

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.

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 …

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 …

Personality Prediction Through Curriculam Vitae Analysis Involving Password Encryption And Prediction Analysis, Gagandeep Kaur, Shruti Maheshwari

Library Philosophy and Practice (e-journal)

A recruitment process requires an eligibility check, an aptitude evaluation and a psychometric analysis of prospective candidates. The work puts forward an application where the system allows employers to post new job offerings and registered candidates can apply. The application estimates applicant’s emotional aptitude through a psychometric analysis based on a test whereas the professional standard is verified via a technical aptitude test. OCEAN Model is used to assess emotional quotient and predict the personality traits. Machine learning techniques such as Logistic Regression are used for modelling the personality predictor. The details of the candidates are kept secure by using …

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.

Three Dimensional Object Detection Approaches For Indoor Navigation Aid, Junxiu Zhou

Theses and Dissertations

This dissertation aims to develop object detection approaches for an indoor navigation aid called smart cane. The goal of the object detection approaches is to provide object-level information of the environment to assist the visually impaired people to walk freely in the indoor environment. Although many object detection approaches have been proposed, object detection is still a challenging problem due to a large number of object categories, viewpoint changes, occlusions, cluttered backgrounds, etc. To address these challenges, first, an indoor 3D dataset is collected by using the smart cane navigation aid. Second, indoor objects are broadly divided into two types: …

Thermal-Kinect Fusion Scanning System For Bodyshape Inpainting And Estimation Under Clothing, Sirazum Munira Tisha

LSU Master's Theses

In today's interactive world 3D body scanning is necessary in the field of making virtual avatar, apparel industry, physical health assessment and so on. 3D scanners that are used in this process are very costly and also requires subject to be nearly naked or wear a special tight fitting cloths. A cost effective 3D body scanning system which can estimate body parameters under clothing will be the best solution in this regard. In our experiment we build such a body scanning system by fusing Kinect depth sensor and a Thermal camera. Kinect can sense the depth of the subject and …

On I/O Performance And Cost Efficiency Of Cloud Storage: A Client's Perspective, Binbing Hou

LSU Doctoral Dissertations

Cloud storage has gained increasing popularity in the past few years. In cloud storage, data are stored in the service provider’s data centers; users access data via the network and pay the fees based on the service usage. For such a new storage model, our prior wisdom and optimization schemes on conventional storage may not remain valid nor applicable to the emerging cloud storage.

In this dissertation, we focus on understanding and optimizing the I/O performance and cost efficiency of cloud storage from a client’s perspective. We first conduct a comprehensive study to gain insight into the I/O performance behaviors …

Automated Dynamic Detection Of Self-Hiding Behaviors, Luke Baird

Student Works

Certain Android applications, such as but not limited to malware, conceal their presence from the user, exhibiting a self-hiding behavior. Consequently, these apps put the user’s security and privacy at risk by performing tasks without the user’s awareness. Static analysis has been used to analyze apps for self-hiding behavior, but this approach is prone to false positives and suffers from code obfuscation. This research proposes a set of three tools utilizing a dynamic analysis method of detecting self-hiding behavior of an app in the home, installed, and running application lists on an Android emulator. Our approach proves both highly accurate …

A Co-Optimal Coverage Path Planning Method For Aerial Scanning Of Complex Structures, Zhexiong Shang, Justin Bradley, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

The utilization of unmanned aerial vehicles (UAVs) in survey and inspection of civil infrastructure has been growing rapidly. However, computationally efficient solvers that find optimal flight paths while ensuring high-quality data acquisition of the complete 3D structure remains a difficult problem. Existing solvers typically prioritize efficient flight paths, or coverage, or reducing computational complexity of the algorithm – but these objectives are not co-optimized holistically. In this work we introduce a co-optimal coverage path planning (CCPP) method that simultaneously co-optimizes the UAV path, the quality of the captured images, and reducing computational complexity of the solver all while adhering to …

A Comparison Of Contextual Bandit Approaches To Human-In-The-Loop Robot Task Completion With Infrequent Feedback, Matt Mcneill, Damian Lyons

Faculty Publications

Artificially intelligent assistive agents are playing an increased role in our work and homes. In contrast with currently predominant conversational agents, whose intelligence derives from dialogue trees and external modules, a fully autonomous domestic or workplace robot must carry out more complex reasoning. Such a robot must make good decisions as soon as possible, learn from experience, respond to feedback, and rely on feedback only as much as necessary. In this research, we narrow the focus of a hypothetical robot assistant to a room tidying task in a simulated domestic environment. Given an item, the robot chooses where to put …

Electronic Data Capture And Study Management, William A. Mattingly

Division of Infectious Diseases

Electronic Data Capture (EDC) is the process of recording data from a primary data source into a computerized system for improved reliability, security, and convenience. Data stored in EDC systems are used for analysis and, in the case of clinical studies, are an important part of the development pipeline for new drugs and medical devices. This text provides an introduction to data capture and the management of a scientific study using the popular EDC solution REDCap.

Why Deep Learning Is More Efficient Than Support Vector Machines, And How It Is Related To Sparsity Techniques In Signal Processing, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Several decades ago, traditional neural networks were the most efficient machine learning technique. Then it turned out that, in general, a different technique called support vector machines is more efficient. Reasonably recently, a new technique called deep learning has been shown to be the most efficient one. These are empirical observations, but how we explain them -- thus making the corresponding conclusions more reliable? In this paper, we provide a possible theoretical explanation for the above-described empirical comparisons. This explanation enables us to explain yet another empirical fact -- that sparsity techniques turned out to be very efficient in signal …

An Open-Source Integration Platform For Multiple Peripheral Modules With Kuka Robots, Mahyar Abdeetedal, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

This paper presents an open-source software interface for the integration of a Kuka robot with peripheral tools and sensors, KUI: Kuka User Interface. KUI is developed based on Kuka Fast Research Interface (FRI) which enables soft real-time control of the robot. Simulink Desktop Real-Time™ or any User Datagram Protocol (UDP) client can send real-time commands to Kuka robot via KUI. In KUI, third-party tools can be added and controlled synchronously with Kuka light-weight robot (LWR). KUI can send the control commands via serial communication to the attached devices. KUI can generate low-level commands using data acquisition (DAQ) boards. This feature …

Computing Without Computing: Dna Version, Vladik Kreinovich, Julio C. Urenda

Departmental Technical Reports (CS)

The traditional DNA computing schemes are based on using or simulating DNA-related activity. This is similar to how quantum computers use quantum activities to perform computations. Interestingly, in quantum computing, there is another phenomenon known as computing without computing, when, somewhat surprisingly, the result of the computation appears without invoking the actual quantum processes. In this chapter, we show that similar phenomenon is possible for DNA computing: in addition to the more traditional way of using or simulating DNA activity, we can also use DNA inactivity to solve complex problems. We also show that while DNA computing without …

Deep Learning (Partly) Demystified, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

Successes of deep learning are partly due to appropriate selection of activation function, pooling functions, etc. Most of these choices have been made based on empirical comparison and heuristic ideas. In this paper, we show that many of these choices -- and the surprising success of deep learning in the first place -- can be explained by reasonably simple and natural mathematics.

Artificial Intelligence Empowered Uavs Data Offloading In Mobile Edge Computing, Nicholas Alexander Kemp

Electrical and Computer Engineering ETDs

The advances introduced by Unmanned Aerial Vehicles (UAVs) are manifold and have paved the path for the full integration of UAVs, as intelligent objects, into the Internet of Things (IoT). This paper brings artificial intelligence into the UAVs data offloading process in a multi-server Mobile Edge Computing (MEC) environment, by adopting principles and concepts from game theory and reinforcement learning. Initially, the autonomous MEC server selection for partial data offloading is performed by the UAVs, based on the theory of the stochastic learning automata. A non-cooperative game among the UAVs is then formulated to determine the UAVs' data to be …