Engineering Commons^™

Fiber-Optic Temperature And Flow Sensory System And Methods, Ming Han, Guigen Liu, Weilin Hou, Qiwen Shen

Department of Electrical and Computer Engineering: Faculty Publications

A fiber optic sensor, a process for utilizing a fiber optic sensor, and a process for fabricating a fiber optic sensor are described, where a double-side-polished silicon pillar is attacked to an optical fiber tip and forms, a Fabry-Perot cavity. In an implementation, a fiber optic sensor in accordance with an examplary embodiment includes an optical fiber configured to be coupled to a light source and a spectrometer; and a single silicon layer or multiple silicon layers disposed on an end face of the optical fiber, where each of the silicon layer(s) defines a Fabry-Perot interferometer, and where the sensor …

Quantitative Metrics For Mutation Testing, Amani M. Ayad

Dissertations

Program mutation is the process of generating versions of a base program by applying elementary syntactic modifications; this technique has been used in program testing in a variety of applications, most notably to assess the quality of a test data set. A good test set will discover the difference between the original program and mutant except if the mutant is semantically equivalent to the original program, despite being syntactically distinct.

Equivalent mutants are a major nuisance in the practice of mutation testing, because they introduce a significant amount of bias and uncertainty in the analysis of test results; indeed, mutants …

Asro (Amphibious Spy Robot): Prototipe Robot Amfibi Pengintai Dengan First Person View Dan Sistem Navigasi Berbasis Sensor Kompas, R. Amirur Rajif, Fatchul Arifin

Elinvo (Electronics, Informatics, and Vocational Education)

Robots have an important role in all aspects of life, including the military field. The purpose of making this final project are building hardware and software of robot and to know the performance of robots. The method used in making the final project consists of identifying and analyzing requirements, designing and manufacturing hardware and software, and testing. The result of the performance of ASRO is that, the buoyancy force of the robot is greater than the weight of the object, namely Fa = 22,808 N and W = 15,696 N or Fa> W which makes the robot float while operate …

Kinerja Dari Prototipe Robot Visual Pengumpul Sampah Perairan Dengan Remote Control Menggunakan Telemetri, Faiz Sulistyawan, Sri Waluyanti

Elinvo (Electronics, Informatics, and Vocational Education)

The making of prototype robot waste water collection aims to know the performance itself. The prototype of the Aquatic Waste Collection Robot is designed to float and clean trash in remote controlled waters. The main control drives a series of DC brushless motors to drive while the MG995 servo motor drives a rudder or defender. The device is also equipped with a camera as a medium to see the condition of the robot directly or in real time which will be displayed on the monitor screen. The camera and screen are connected to a telemetry circuit consisting of a transmitter …

Perancangan Sistem Pemantauan Suhu Dan Kelembaban Pada Proses Dekomposisi Pupuk Kompos Berbasis Iot, Farida Hardyanti, Pramudi Utomo

Elinvo (Electronics, Informatics, and Vocational Education)

The problem that often occurs in making compost is the level of fertilizer maturity that is not perfect. This is caused by humidity and temperature in the unstable manufacturing process. This article aims to develop a system capable of controlling temperature and humidity as well as monitor changes in the process of compost decomposition wirelessly and describe the results of testing the system. This research uses a development method with several stages, namely: problem identification and needs analysis, design, implementation, and testing. The results show that: (1) a temperature and humidity monitoring system is realized to monitor and regulate the …

Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger

Electrical and Computer Engineering Publications

The smart grid employs computing and communication technologies to embed intelligence into the power grid and, consequently, make the grid more efficient. Machine learning (ML) has been applied for tasks that are important for smart grid operation including energy consumption and generation forecasting, anomaly detection, and state estimation. These ML solutions commonly require sufficient historical data; however, this data is often not readily available because of reasons such as data collection costs and concerns regarding security and privacy. This paper introduces a recurrent generative adversarial network (R-GAN) for generating realistic energy consumption data by learning from real data. Generativea adversarial …

Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data, Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang

Computer Science Faculty Research

Background: Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause computational challenges to applying conventional survival analysis. Results: We propose a novel biologically interpretable pathway-based sparse deep neural network, named Cox-PASNet, which integrates high-dimensional gene expression data and clinical data on a simple neural network architecture for survival analysis. Cox-PASNet is biologically interpretable where nodes in the neural network correspond to biological genes and pathways, while capturing the nonlinear …

Design And Implementation Of Anomaly Detections For User Authentication Framework, Iman Abu Sulayman

Electronic Thesis and Dissertation Repository

Anomaly detection is quickly becoming a very significant tool for a variety of applications such as intrusion detection, fraud detection, fault detection, system health monitoring, and event detection in IoT devices. An application that lacks a strong implementation for anomaly detection is user trait modeling for user authentication purposes. User trait models expose up-to-date representation of the user so that changes in their interests, their learning progress or interactions with the system are noticed and interpreted. The reason behind the lack of adoption in user trait modeling arises from the need of a continuous flow of high-volume data, that is …

Identifying Customer Churn In After-Market Operations Using Machine Learning Algorithms, Vitaly Briker, Richard Farrow, William Trevino, Brent Allen

SMU Data Science Review

This paper presents a comparative study on machine learning methods as they are applied to product associations, future purchase predictions, and predictions of customer churn in aftermarket operations. Association rules are used help to identify patterns across products and find correlations in customer purchase behaviour. Studying customer behaviour as it pertains to Recency, Frequency, and Monetary Value (RFM) helps inform customer segmentation and identifies customers with propensity to churn. Lastly, Flowserve’s customer purchase history enables the establishment of churn thresholds for each customer group and assists in constructing a model to predict future churners. The aim of this model is …

Analysis Of The Duration And Energy Consumption Of Aes Algorithms On A Contiki-Based Iot Device, Brandon Tsao

Computer Science and Engineering Master's Theses

With the growing prevalence of the Internet of Things, securing the sheer abundance of devices is critical. The current IoT and security landscapes lack empirical metrics on encryption algorithm implementations that are optimized for constrained devices, such as encryption/decryption duration and energy consumption. In this paper, we achieve two things. First, we survey for optimized implementations of symmetric encryption algorithms. Seconds, we study the performance of various symmetric encryption algorithms on a Contiki-based IoT device. This paper provides encryption and decryption durations and energy consumption results on three implementations of AES: TinyAES, B-Con’s AES, and Contiki’s own built-in AES. In …

Non-Trivial Off-Path Network Measurements Without Shared Side-Channel Resource Exhaustion, Geoffrey I. Alexander

Computer Science ETDs

Most traditional network measurement scans and attacks are carried out through the use of direct, on-path network packet transmission. This requires that a machine be on-path (i.e, involved in the packet transmission process) and as a result have direct access to the data packets being transmitted. This limits network scans and attacks to situations where access can be gained to an on-path machine. If, for example, a researcher wanted to measure the round trip time between two machines they did not have access to, traditional scans would be of little help as they require access to an on-path machine to …

Leveraging Cloud-Based Nfv And Sdn Platform Towards Quality-Driven Next-Generation Mobile Networks, Hassan Hawilo

Electronic Thesis and Dissertation Repository

Network virtualization has become a key approach for Network Service Providers (NSPs) to mitigate the challenge of the continually increasing demands for network services. Tightly coupled with their software components, legacy network devices are difficult to upgrade or modify to meet the dynamically changing end-user needs. To virtualize their infrastructure and mitigate those challenges, NSPs have started to adopt Software Defined Networking (SDN) and Network Function Virtualization (NFV). To this end, this thesis addresses the challenges faced on the road of transforming the legacy networking infrastructure to a more dynamic and agile virtualized environment to meet the rapidly increasing demand …

Rehabilitation Training System Of Vr-Based Speech Apraxia, Huanhuan Jiao, Zhigeng Pan, Shuchang Xu, Qingshu Yuan

Journal of System Simulation

Abstract: Aiming at the problem that the enthusiasm of active training in patients with traditional speech apraxia rehabilitation is gradually weakened, a virtual reality-based rehabilitation training system for speech apraxia is designed. The system simulates the 26 monosyllabic pronunciation mouths shapes made by virtual human in Chinese and uses it for the learning module. It is proposed to identify 26 monosyllabic words by using the isolated word speech recognition algorithm, which improves the accuracy of speech recognition. The system includes a training module and a scene module for assisting the patient's pronunciation rehabilitation training. The evaluation results show that …

Multi-Objective Optimization Design Of Aerodynamic Layout For Twin Swept-Wing Aircraft, Yuchang Lei, Dengcheng Zhang, Yanhua Zhang, Guangxu Su, Luo Hao, Zhan Ren

Journal of System Simulation

Abstract: Multi-objective optimization of aerodynamic layout is a key technology in the design of vehicles. The overall configuration of the shape parameters is optimized with a double swept-shaped wave shape as the basic configuration. We use NSGA-Ⅱ multi-objective genetic algorithm, take the aircraft double sweep angle as the design variable, consider the maximum takeoff weight, range, volume ratio and other performance indicators, use Elman neural network to establish the relationship between shape parameters and performance parameters, and establish constraints based on mission planning requirements. The Pareto optimal solution set is obtained by using optimized design and the individuals with …

Dynamic Simulation Of Marine Pasture Water Quality Monitoring Network Based On Aug, Wenxia Xue, Bin Lin, Hu Xu, Jingbo Zhang

Journal of System Simulation

Abstract: The development of marine pastures puts forward higher requirements for water quality monitoring. In order to achieve large-scale and long-term underwater water quality monitoring, AUG-based Underwater Sensor Network (AUSN) is studied. The AUG is introduced as the underwater sink node of the sensor network and the sleep scheduling mechanism is adopted for the sensors, which can effectively reduce the total energy consumption of the network. Based on the analysis of energy consumption characteristics of underwater sensor networks, the energy consumption calculation formula of underwater sensor networks is discussed. Combined with the virtual visualization technology, the underwater sensor network simulation …

A Temporal Action Detection Algorithm Based On Spatio-Temporal Feature Pyramid Network, Liu Wang, Jinyu Sun, Shiwei Ma

Journal of System Simulation

Abstract: In view of the discontinuity of motion timing detection in the frame-level prediction network structure, a novel algorithm based on spatio-temporal feature pyramid network (ST-FPN) is proposed. In the frame-level action prediction, several 3D convolution-de-convolution (CDC) networks are used to sample spatial feature down to 1 dimension and sample temporal feature up to corresponding proposal level. Then the prediction scores of different CDC networks are fused by non-maximum suppression (NMS). The softmax classifier is used to classify frame-level actions, and then temporal action detection is obtained. The experimental results on dataset THUMOS14 show that the proposed algorithm improves the …

Fault Identification Of High-Speed Train Bogie Based On Siamese Convolutional Neural Network, Yunpu Wu, Weidong Jin, Junxiao Ren

Journal of System Simulation

Abstract: The performance degradation and failure of high-speed train bogie components will threaten the operation security of train. This paper proposes a fault type identification method based on siamese convolutional neural network to address the scarcity of data and the high-dimension of monitoring signals. Deep residual network with one-dimension convolution layers is employed for features extraction and fusion of vibration signals from multiple sensors. The siamese structure is employed to obtain the similarities between samples. Fault types are identified by ranking similarities in the support set. The experimental results show that the proposed method can identify the fault types with …

Pedestrian Navigation Method Based On Uwb And Sins, Yang Yang, Li Qing

Journal of System Simulation

Abstract: In view of the problem that the inertial navigation error is accumulating with time and UWB indoor is hard to continue tracking problems in complex environment, an extended Kalman filter (EKF) fusing UWB and sins pedestrian navigation is proposed.The zero speed correction algorithm is used to trigger EKF at zero speed. The sins is corrected by the velocity error measurement provided by sins and the position error measurement provided by UWB restraining error accumulation.When UWB signal is interrupted, the position of UWB output without interruption is taken as the starting position. The experiment results of SINS autonomous navigation …

Evaluation Method Of Simulation Results Based On Principal Component Analysis, Rusheng Ju, Zimin Cai, Yang Mei, Wang Song

Journal of System Simulation

Abstract: A large amount of result data are produced by complex system simulation. These data types are diverse and complex. Usually they cannot be used directly. The inner pattern can only be found by effective evaluation. Based on the characteristics of complex combat simulation results, this paper utilizes the Principal Component Analysis method to reduce the dimension of data analysis and explore the relationship between the system input data and output data. The key influence factors of the measure of force effectiveness is found. The application verification is done by typical examples. The selected principle factors are explored in …

Research On Nondestructive Blood Glucose Cloud Detection System Based On Improved Deep Regression Network, Mengjia He, Yingnian Wu, Yang Rui

Journal of System Simulation

Abstract: Invasive blood glucose measurement has a strong sense of discomfort and risk of infection, so the study of non-invasive blood glucose has a strong practical significance. At present, the optical method is not convenient for practical use, and the energy conservation method requires strict requirements. In view of the above problems, infrared thermography is used to detect blood glucose. After acquiring infrared thermal images of face figure, we extract the gray feature and reduce its dimension. In order to speed up the training and prevent over fitting, depth regression network is improved to model the infrared thermal image gray …

Intelligent Collaborative Networking Method For Workshop Emergencies, Kong Tao, Wang Yan

Journal of System Simulation

Abstract: Due to the complex environment of intelligent manufacturing workshop, abnormal emergencies will cause huge security threats and economic losses to the workshop. It is difficult to transmit the abnormal event data continuously, quickly and completely in the workshop production site, and the fluctuation of abnormal event data is great with high requirements on the integrity and real-time of data transmission. In this paper, a multi-agent cooperative networking method for workshop emergencies is proposed. Mobile robots are introduced as intermediary Sink nodes for data transmission between sensor networks and the Internet. In case of emergencies, the intelligent node and cluster …

A Method Of Manifold Learning For Locality Preserving Projections Based On Geodesic, Lijun Xu, Jinghan Fang, Yiping Wang

Journal of System Simulation

Abstract: In order to solve the problem of under-fitting state of LPP algorithm in practical application,in this paper, the mapping principle of Locality Preserving Projections (LPP) is discussed in detail. The relationship of LPP method between the under-fitting state on certain dataset and adjacency graph is analyzed. The LPP manifold learning method (ISOLPP) is proposed on the basis of geodesic. The experiment results show that the good embedded effect is achieved by implenmenting ISOLPP method on multiple test data sets. It significantly improves the adaptability of the algorithm by not only inheriting the advantages of LPP algorithm with explicit projection …

Research On Gear Appearance Defect Recognition Based On Improved Faster R-Cnn, Weixi Ji, Du Meng, Peng Wei, Xu Jie

Journal of System Simulation

Abstract: In order to achieve automatic identification of gear appearance defects and improve the qualification rate of gear products, aiming at the generalization of traditional defect recognition algorithms and the time-consuming of manual features extraction, this paper proposes an improved gear flaw detection algorithm for Faster R-CNN. VGG-2CF network is designed to improve the ability to identify smaller targets. Introducing AM-Softmax loss function is introduced to reduce the intra-class variation and optimize the inter-class difference. Combining with F-measure in machine learning algorithm, an AMF-Softmax loss function is proposed to solve the problem of data imbalance. The experimental results show the …

Intelligent Manufacturing Plan Management Based On Digital Twins, Yingying Xiao, Wang Mei, Liqin Guo, Xing Chi, Changhui Zhuang

Journal of System Simulation

Abstract: For the multi-variety and small-batch manufacturing mode, the planning management system cannot be timely automatically adjusted according to uncertain factors. This paper proposes an intelligent manufacturing plan management system based on factory digital twins. The plan management PDCA business process model is established. In addition, the processing logic model and constraints of the periodic static scheduling model and the dynamic emergency scheduling model are proposed. Based on the planning management case of hybrid assembly of two types of aerospace complex products, it is verified that the management model proposed in this paper can support the intelligent dynamic adjustment of …

A Cloud Service Composition Optimization Based On Hnn, Huili Zhang, Zhihe Li

Journal of System Simulation

Abstract: With the rapid development of Cloud service application, how to effectively optimize the composition of Cloud services on cloud platform and improve the overall performance of cloud platform system have become an urgent research issue. In order to improve the efficiency of Cloud services, a combined optimization model based on Hopfield neural network is proposed. The problem of Cloud services is modeled. The problem is expressed as Hopfield Neural Network energy model for optimization, and a PSO group algorithm with Cauchy disturbance is designed to improve the Hopfield model. The experimental comparison shows that the method can improve …

Design Of Universal Control Load System Of Helicopter Flight Simulator, Chen Zhen, Haikuan Yang, Jiang Nan, Yuancheng Wang, Tianjiao Jiang

Journal of System Simulation

Abstract: To improve the universality and handling quality of control system of helicopter flight simulator, a universal control load system of helicopter flight simulator suitable for helicopter flight simulator is designed. The dynamic feedback model is proposed to solve the contradiction between control rigidity and stability, control precision and response frequency, the control rigidity and kinematic accuracy are improved.The operating load mechanism is designed, the system structure and drive system are simplified, the smoothness of force perception is improved; the third order smoothing algorithm and fieldbus technology based on EtherCAT are applied to improve the anti-jamming capability and response speed, …

Robot Arm Control Method Based On Deep Reinforcement Learning, Heyu Li, Zhilong Zhao, Gu Lei, Liqin Guo, Zeng Bi, Tingyu Lin

Journal of System Simulation

Abstract: Deep reinforcement learning continues to explore in the environment and adjusts the neural network parameters by the reward function. The actual production line can not be used as the trial and error environment for the algorithm, so there is not enough data. For that, this paper constructs a virtual robot arm simulation environment, including the robot arm and the object. The Deep Deterministic Policy Gradient (DDPG),in which the state variables and reward function are set,is trained by deep reinforcement learning algorithm in the simulation environment to realize the target of controlling the robot arm to move the gripper below …

Research On Corridor Setting Based On Pedestrian Simulation Of Social Groups, Yiting Xu, Zhang Rui

Journal of System Simulation

Abstract: As the connector of each space in the hub, the rail transit hub corridor plays the role of transition and buffer. The existence of social groups makes an important impact on pedestrian traffic and its simulation. The paper supplements the consideration of pedestrian traffic related studies on social groups travel, analyses the characteristics of social groups in rail transit hub corridor, improves Moussaïd social group force model, and redevelops AnyLogic micro-simulation platform based on Python language. Taking a subway station in Beijing as an example, fully considering the influence of social groups, it is obtained that the optimal channel …

Downhole Drilling Processing Data Acquisition And Stick Slip Characteristic Analysis, Huang Sheng, Zhang Tao, Chongjun Huang, Yumei Li, Deng Hu, Zhang Xia

Journal of System Simulation

Abstract: During oil drilling process, drill string vibrations are detrimental to the bit and drill string, which even causes failure of equipment. Researches show that, studying the law of near bit vibration data can reduce non-production time (NPT) and improve drilling efficiency. This paper uses power spectral density and wavelet transform to analyze vibration signals, then compares with normal drilling situation to find out stick slip characteristics. The results show that, when stick slip occurs, the mean value of lateral vibration fluctuates greatly, which indicates stick slip is mainly based on torsional vibration. From the perspective of power spectral density …

Evaluation Method Of Node Importance In Equipment Support Network Based On Polymeric Degree, Zhang Qiang, Junhai Cao, Tailiang Song, Yan Xu

Journal of System Simulation

Abstract: Aiming at the problem that the heterogeneity of nodes in equipment support network and the different support relationships leading to the inaccuracy of judging the importance of nodes based on single attributes such as degree value, this paper puts forward the concept of polymeric degree, and mines the importance information of nodes from the aspects of polymeric degree, betweenness centrality, closeness centrality and Eigenvector centrality. Because of the shortcoming that the Euclidean distance can not reflect the vertical distance in the traditional method of Order Preference by Similarity to an Ideal Solution (TOPSIS), the TOPSIS method is improved. The …