Computer Sciences Commons^™

Water Body Extraction From High Resolution Remote Sensing Images Based On Fused Visual Word Bags, Xin Wang, Mingjun Xu, Jian Xiao, Lizhong Xu

Journal of System Simulation

Abstract: Aiming at the problem that water body extraction is easily influenced by shadow or light in high resolution remote sensing images, an improved algorithm based on fusion of visual word bags is proposed. Based on the deep analysis of the characteristics of remote sensing water body targets, a spectral feature extraction approach is designed. To enhance the description ability of water body targets, a novel visual word bag fusion model based on local binary pattern and spectral feature is constructed. Based on the proposed visual word bag fusion model, a water body target classifier is presented. …

Study On Building Fire Evacuation Path Planning Based On Improved Ant Colony Algorithm, Jiangtao Liang, Huiqin Wang

Journal of System Simulation

Abstract: Aiming at the problem of dynamic planning of evacuation paths in comprehensive building fires, with the shortest escape time required for evacuees as the goal, considering the impact of fire products and crowd density on the evacuation speed of personnel, an evacuation path planning model based on improved ant colony algorithm is constructed. A evacuation network data model composed of an obstacle vertex grid is established, the inspiration function of the ant colony algorithm and the deadlock processing strategy are improved, the explosion operator in the fireworks algorithm is introduced to optimize the ant path, and a comprehensive building …

Teaching-Learning-Based Optimization Algorithm For Permutation Flowshop Scheduling, Qiwen Zhang, Bin Zhang

Journal of System Simulation

Abstract: A multi-classes teaching-learning-based optimization (MCTLBO) algorithm is proposed for the permutation flowshop scheduling problem (PFSP) by combining continuous algorithm with discrete strategy. An improved nawaz enscore ham (NEH) population initialization method based on permutation mutation is adopted, which takes into account the quality and diversity of initial solutions. In the teaching stage, discrete adaptive teaching with duplicate removal is introduced to avoid meaningless teaching processes. A new self-learning strategy based on Levy flight is added, and the self-learning in discrete stage is simulated by variable neighborhood search. Learner phase and class communication are combined to improve the efficiency of …

Supply Chain Delivery Model And Simulation Based On Product Experience, Genshang Xing, Fang Lu, Shushan Li, Dingti Luo

Journal of System Simulation

Abstract: With the higher demand of consumers for delivery time of products purchased online, it is becoming more important for retailers to determine the delivery time of products based on product experience and market position. By constructing a supply chain delivery model under the three channel rights structure, the impact of product experience on the optimal delivery time, the retailer’s decision mode selection considering the delivery time and the supply chain profit after delivery are analyzed, and the correctness and reliability of the model are verified by numerical simulation. Research shows that the optimal product delivery time of retailers …

Murals Super-Resolution Reconstruction With The Stable Enhanced Generative Adversarial Network, Jianfang Cao, Yiming Jia, Minmin Yan, Xiaodong Tian

Journal of System Simulation

Abstract: Aiming at the problems of low resolution and unclear texture details of ancient murals, which led to insufficient viewing of murals and low research value, a stable enhanced super-resolution generative adversarial networks (SESRGAN) reconstruction algorithm is proposed. Based on the generative adversarial network, the generative network uses dense residual blocks to extract mural features, and uses the visual geometry group (VGG) network as the basic framework of the discriminating network to determine the authenticity of the input mural, and introduces perception loss, content loss and penalty loss to jointly optimize the model. Experimental results show that, compared with other …

Design Of Variable Stiffness Energy Storage Walking Assist Hip Exoskeleton And Simulation Of Assistance Effect, Bingshan Hu, Ke Cheng, Sheng Lu, Hongliu Yu

Journal of System Simulation

Abstract: Passive energy storage walking assist exoskeleton makes full use of the human’s own energy, reducing energy consumption when walking. Aiming at the present passive energy storage walking assist exoskeleton adopts fixed stiffness joint, a passive variable stiffness energy storage walking assist hip exoskeleton is designed, on the base of joint energy flow characteristics in the process of people walking and the change of stiffness characteristics. The human-exoskeletons coupling model is established, and the optimal stiffness that minimizes the power consumption of the human body walking on a flat surface, as well as the total metabolism and the main thigh …

Robot Path Planning Based On Bidirectional Aggregation Ant Colony Optimization, Xiangyang Deng, Limin Zhang, Wei Fang, Miao Tang

Journal of System Simulation

Abstract: Path planning is a key theoretical issue of the autonomous mobile robot technology. This paper utilizes an improved grid method to establish environment model, which involves a new priori advantage azimuth structure that includes two parts of the primary dominant grid cell and the subprime grid cell. It improves the pheromone mark ant colony optimization algorithm by putting forward a novel pheromone update strategy based on secondary path cognitive method, which is called bidirectional guidance strategies. It repeats an alternation of the starting point and the target point in each new round of iteration. The experimental results show that …

Research On Parametric Modeling And Deformation Method Of Human Muscle, Na Ni, Kunjin He, Xincheng Zhu, Zhengming Chen

Journal of System Simulation

Abstract: Due to the volume preserving constraint of human muscle in the deformation process, and the lack of three-dimensional multi-angle representation of muscle motion, a parametric modeling and deformation method of human muscle is proposed. Based on MRI (magnetic resonance imaging) data, the external contour line is extracted from the slice image generated by MRI data to construct a three-dimensional muscle model; muscle features are defined hierarchically, and the mapping relationship between semantic parameters is established to realize the volume preserving deformation of muscle; by establishing a vector-valued dynamic fourth-order differential equation, the feature curve dynamically simulates the process …

State Prediction Of Poverty Alleviation Objects Based On Hmm And Multidimensional Data, Jun He, Sunyan Hong, Yifang Zhou, Shikai Shen, Muquan Zou

Journal of System Simulation

Abstract: In order to solve the problems of inaccurate prediction of poverty, poverty reduction and poverty returen, and the difficulty in identifying the key factors affecting the state transition, 8 key features and 22 observed states are extracted from the poverty reduction basic data and multi-industry data. The relationship between observed state and implied state is constructed, and the hidden markov model (HMM) of poverty alleviation is established. Data of a deep poverty county for three consecutive years are used as samples for parameter training, test experiment and result verification. The results show that the method has a strong …

Simulation Of Navigation Process Based On Nonlinear Observer, Zhiwei Wang, Jizong Hu, Fengjie Wang, Jie Huang

Journal of System Simulation

Abstract: In order to solve the problem that the scope of using thetraditional observers is limited by assumptions, in the process of establishing the observer, a parameter projection relationship is designed and added to the observer to keep it under the condition of not being constrained by the assumptions. It is semi-globally stable, and the estimation process is more direct, which makes the parameter estimation process under nonlinear conditions converge faster. The simulation results show that the computational complexity of the nonlinear observer is reduced by nearly 80% compared with the multiplicative extended Kalman filter. The experimental results show that …

A Visual Analytics Of Urban Traffic Events Using Social Media Data, Xiangping Wu, Lijun Ping, Dongshi Xu

Journal of System Simulation

Abstract: Traffic text data in social media can supplement traffic flow information, for which a visual analysis method for traffic events is proposed. A text processing model is designed to process the social media data and extract the description information of traffic event. The vector representation of road node attributes is learned based on graph embedding algorithm, and a road similarity model is estbalished. A prediction model of the traffic event is built based on the road similarity and the kernel density model. An interactive visual analysis system is designed to carry out visual analysis. Though traffic …

Research On Visual Inspection Algorithm Of Crimping Appearance Defects For Wiring Harness Terminals, Bingan Yuan, Mingen Zhong, Jingxin Ni

Journal of System Simulation

Abstract: Aiming at the low efficiency and high missing rate of wiring harness terminals, an image detection method based on machine vision is proposed. The characteristic parameters of five typical defects in three main parts of wiring harness terminals are analyzed and defined. Tthe algorithms of extracting positioning datum, segmenting inspected-parts adaptively, extracting the defect features and calculating the characteristic parameters are designed respectively, and the defects criterions are given. The experimental results show that the algorithms are suitable for single defect and multi-class defects, both the miss detection rate and the false positiveness rate are low. The accuracy and …

Phased Array Radar Doa Estimation Simulation System Designed With Interactive Control, Fan Yu, Dongqi Luo, Binqiang Si, Jihong Zhu

Journal of System Simulation

Abstract: For the problem of simulation, evaluation and verification of phased array radar the direction of arrival (DOA) estimation of phased array radar, the modeling and evaluation of phased array radar DOA estimation is discussed. A real-time simulation system based on interactive control is designed. The simulation system can be used to model and simulate the interactive target & environment, phased array and target detection efficiency evaluation model. The signal generation, free space propagation, echo signal acquisition, signal processing and other processes can be simulated during the detection of real-time flying target, and the effect of DOA estimation can be …

Research On Immersive Virtual Reality Interactive System For Flow Visualization, Shijian Xu, Dan Zhao, Chengyu Su, Fupan Wang, Xiaorong Zhang, Fang Wang, Yadong Wu

Journal of System Simulation

Abstract: Aiming at the problem of low interaction efficiency due to the lack of depth information in the current desktop flow visualization application based on the two-dimensional display interaction environment, virtual reality technology is introduced to design and implement an immersive flow visualization system with diversified interaction methods. Based on the gaze and gesture interaction technology, the system designs and implements gesture-based navigation methods and three-dimensional interactive widgets based on user requirements, as well as immersive interactive panels based on user gaze and gestures. We designed and implemented an immersive interactive management method based on visual scenes and a visual …

Assessing The Effect Of Interactivity On Virtual Reality Second Language Learning, Christene Harris

Theses and Dissertations

Virtual Reality (VR) being used as a helpful tool in language education is widely supported by the current literature. It can provide a variety of stimulating scenarios that keep learner engagement high. The use of VR for language learning is a research area that has shown promise in recent years. This makes it necessary for further research to be conducted in the field to determine ways to maximize its potential. This thesis aims to determine if the level of interactivity present in a VR Language Learning Application is a factor that will impact a user's capability to successfully learn a …

Blockchain Storage – Drive Configurations And Performance Analysis, Jesse Garner, Aditya A. Syal, Ronald C. Jones

Other Student Works

This project will analyze the results of trials implementing various storage methods on Geth nodes to synchronize and maintain a full-archive state of the Ethereum blockchain. The purpose of these trials is to gain deeper insight to the process of lowering cost and increasing efficiency of blockchain storage using available technologies, analyzing results of various storage drives under similar conditions. It provides performance analysis and describes performance of each trial in relation to the others.

Low Memory Continual Learning Classification Algorithms For Low Resource Hardware, Autumn Lilly Chadwick

Theses and Dissertations

Continual Learning (CL) is a machine learning approach which focuses on continuous learning of data rather than single dataset-based learning. In this thesis, this same focus is applied with respect to the field of machine learning for embedded devices which is still in the early stages of development. This focus is further used to develop various algorithms such as utilizing prior trained starting networks, weighted output schemes, and replay or reduced datasets for training while maintaining a consistent focus on low resource devices to maintain acceptable performance. The experimental results show an improvement in model training times as compared to …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

What Does It Take To Bake A Cake? The Reciperef Corpus And Anaphora Resolution In Procedural Text, Biaoyan Fang, Timothy Baldwin, Karin Verspoor

Natural Language Processing Faculty Publications

Procedural text contains rich anaphoric phenomena, yet has not received much attention in NLP. To fill this gap, we investigate the textual properties of two types of procedural text, recipes and chemical patents, and generalize an anaphora annotation framework developed for the chemical domain for modeling anaphoric phenomena in recipes. We apply this framework to annotate the RecipeRef corpus with both bridging and coreference relations. Through comparison to chemical patents, we show the complexity of anaphora resolution in recipes. We demonstrate empirically that transfer learning from the chemical domain improves resolution of anaphora in recipes, suggesting transferability of general procedural …

A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh

Publications and Research

Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, a massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log …

Open Hardware In Science: The Benefits Of Open Electronics, Michael Oellermann, Jolle W. Jolles, Diego Ortiz, Rui Seabra, Tobias Wenzel, Hannah Wilson, Richelle L. Tanner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; …

Promoting Infrastructure Construction In Advance To Support Sci-Tech Self-Reliance And Self-Strengthening At Higher Level, Yang Wang, Yuanchun Zhou, Yanguang Wang, Jianhui Li, Fazhi Qi, Honglin He, Fangyu Liao

Bulletin of Chinese Academy of Sciences (Chinese Version)

The research infrastructure is the basic and strategic platform of scientific and technological innovation. In the last decade, China's research infrastructure has achieved leapfrog development in the level of observation, manufacturing, management, data acquisition, data sharing and utilization, which supports China's scientific and technological innovation activities at a higher level. Looking into the future, the scientific research paradigm is transforming. The network, data, and computing platform will not only support the development of major science and technology infrastructure and field stations in larger, more accurate, and more advanced approach, but also contribute to the transformation of scientific research paradigm. It …

Deep-Learning-Incorporated Augmented Reality Application For Engineering Lab Training, John Estrada, Sidike Paheding, Xiaoli Yang, Quamar Niyaz

Michigan Tech Publications, Part 1

Deep learning (DL) algorithms have achieved significantly high performance in object detection tasks. At the same time, augmented reality (AR) techniques are transforming the ways that we work and connect with people. With the increasing popularity of online and hybrid learning, we propose a new framework for improving students’ learning experiences with electrical engineering lab equipment by incorporating the abovementioned technologies. The DL powered automatic object detection component integrated into the AR application is designed to recognize equipment such as multimeter, oscilloscope, wave generator, and power supply. A deep neural network model, namely MobileNet-SSD v2, is implemented for equipment detection …

Missing Value Estimation Using Clustering And Deep Learning Within Multiple Imputation Framework, Manar D. Samad, Sakib Abrar, Norou Diawara

Computer Science Faculty Research

Missing values in tabular data restrict the use and performance of machine learning, requiring the imputation of missing values. Arguably the most popular imputation algorithm is multiple imputation by chained equations (MICE), which estimates missing values from linear conditioning on observed values. This paper proposes methods to improve both the imputation accuracy of MICE and the classification accuracy of imputed data by replacing MICE’s linear regressors with ensemble learning and deep neural networks (DNN). The imputation accuracy is further improved by characterizing individual samples with cluster labels (CISCL) obtained from the training data. Our extensive analyses of six tabular data …

Analysis Of Principles Of Development Of Key Technologies, Yungang Bao

Bulletin of Chinese Academy of Sciences (Chinese Version)

How to development key technologies requires understanding the principles of technology evolution. This study proposes that the development process of key technologies follows the Metcalf's Law. Furthermore, this paper presents two principles of the development of key technologies from different angles. Finally, several suggestions are raised.

Implementation Of A Least Squares Method To A Navier-Stokes Solver, Jada P. Lytch, Taylor Boatwright, Ja'nya Breeden

Rose-Hulman Undergraduate Mathematics Journal

The Navier-Stokes equations are used to model fluid flow. Examples include fluid structure interactions in the heart, climate and weather modeling, and flow simulations in computer gaming and entertainment. The equations date back to the 1800s, but research and development of numerical approximation algorithms continues to be an active area. To numerically solve the Navier-Stokes equations we implement a least squares finite element algorithm based on work by Roland Glowinski and colleagues. We use the deal.II academic library , the C++ language, and the Linux operating system to implement the solver. We investigate convergence rates and apply the least squares …

The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina

Student Theses and Dissertations

Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.

Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …

A Systematic Literature Review Of Requirements Engineering Education, Marian Daun, Alicia M. Grubb, Viktoria Stenkova, Bastian Tenbergen

Computer Science: Faculty Publications

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or budget-overspending of software development projects. It is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. To this date, there exists no central concept of what RE education shall comprise. To lay a foundation, we report on a systematic literature review of the feld and provide a systematic map describing the current state of RE …

The Stakeholder-Profile Framework For Tacit Knowledge Acquisition In Requirements Elicitation Interviews, Rasha Eltigani

Master of Science in Software Engineering Theses

The stakeholder’s tacit knowledge is a key crown jewel of requirements elicitation, and in turn software development at large. This critical element holds significant leverage in determining the outcome and the quality of the requirements, and therefore the development endeavor holistically. Due to its very nature of being tacit, it is innately covert and deeply hidden within the stakeholders’ minds, so it is extremely difficult to articulate and relay, as well as even harder to elicit and utilize. Additionally, the literature reports that there is a scarcity of available theorizations and solutions for addressing this challenge, posing a key and …