Computer Sciences Commons^™

Enhancing Classroom Instruction With Online News, Michael D. Ekstrand, Katherine Landau Wright, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Purpose

Investigate how school teachers look for informational texts for their classrooms. Access to current, varied, and authentic informational texts improves learning outcomes for K-12 students, but many teachers lack resources to expand and update readings. The Web offers freely-available resources, but finding suitable ones is time-consuming. This research lays the groundwork for building tools to ease that burden.

Methodology

This paper reports qualitative findings from a study in two stages: (1) a set of semi-structured interviews, based on the Critical Incident Technique, eliciting teachers’ information-seeking practices and challenges; and (2) observations of teachers using a prototype teaching-oriented news search …

Optimal Scheduling And Decision Making Method For Dynamic Flexible Job Shop, Wang Yan, Ding Yu

Journal of System Simulation

Abstract: For multi-objective dynamic flexible job-shop scheduling, an improved multi-objective differential evolution algorithm is proposed. The adaptive cross-mutation operator is introduced into the differential evolution algorithm to improve its global search capability. The fast non-dominated sorting method based on immunological principles is introduced to improve the quality of the solution set in the selection and sorting. An improved TOPSIS-G1-EVM comprehensive decision-making method is proposed. The comprehensive weight of G1-EVM is calculated by Nash equilibrium theory. The comprehensive weight and TOPSIS evaluation system are combined to evaluate each dispatching scheme. The experimental results show that the optimal scheduling algorithm is superior …

Fast 3d Medical Image Registration Based On Geometric Feature Invariants, Juping Gu, Tianyu Cheng, Jianping Wang, Hua Liang, Fengshen Zhao, Jiang Ling

Journal of System Simulation

Abstract: Aiming at the of large amount of computational data and low registration efficiency in 3D cranial medical image registration, a fast registration method based on geometric feature space constraints is proposed. The algorithm extracts three-dimensional contour point clusters, and proposes a feature construction method based on the optimal fitting ring of point clusters. The feature rings and the centroids of each layer are used as feature quantities, and the fast registration is completed by using Iterative Closest Point (ICP) method. The experimental results show that the method has less computation amount, high satisfactory registration accuracy and much faster registration …

Research On Improvement Of Parameters Calibration Method Of Microscopic Traffic Simulation Model, Chenjing Zhou, Yacong Gao, Rong Jian

Journal of System Simulation

Abstract: Model parameter calibration is the precondition of application of micro traffic simulation technology. In view of the lack of refined analysis in the model parameter calibration classification and calibration result determination, the corresponding improvement is proposed. The parameter calibration system divides global parameters and local parameters, provides a micro-simulation model parameter calibration method that combines engineering measurement and intelligent optimization. Based on the information entropy as the analysis index of the parameter calibration results, a method of parameter recursion after clustering is proposed. On the basis of the actual survey data of signalized intersections, A simulation experiments and …

Design And Simulation On A Novel Sliding Mode Control For Linear Induction Motor, Kaiwei Han, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: The speed-tracking problem of linear induction motors under the influence of unmatched disturbances is studied. Based on the extended disturbance observers, the novel sliding mode controllers are designed to make the motor have effective response characteristics under unmatched disturbances. The extended disturbance observersis designed for the unmatched disturbances in the linear induction motor model with edge effects. The observations of the disturbance derivatives are filtered. The novel sliding mode controllers are designed based on the observations of the disturbances and their derivatives. The simulations results show that the designed controller has effective response characteristics and robustness. In addition, it …

A Fast Latin Hyper Cube Experiment Design Method Based On Soduku Grouping, Tiantian Zhang, Li Ni, Guanghong Gong, Yuanjie Lu

Journal of System Simulation

Abstract: In order to solve the long optimization time and parameter level combination explosion in the complex experiment design space of Latin Hypercube design, which is one of the most popular method in experiment design, a fast Soduku grouping-based method is proposed. The optimal seed design is expanded and transformed in the grouped spaces. Experiments are conducted to compare the Soduku grouping-based Latin Hypercube design method with other two commonly used Latin Hypercube design methods in the middle and high dimension experiment space. The results show that Soduku grouping method is more efficient in computation and has better space-filling performance.

Container-Based Automatic Packaging Technology For Complex System Simulation Application, Wang Shuai, Zhu Feng, Yiping Yao, Wenjie Tang, Yuhao Xiao

Journal of System Simulation

Abstract: Container-based technology provides a new solution for the rapid and flexible deployment of complex system simulation applications. Container supports service-based packaging of simulation applications, which greatly reduces the difficulty of deploying simulation applications. Current packaging technology mainly relies on manually writing Dockerfile, which results in low packaging efficiency and human errors. A container-based automatic packaging technology for complex system simulation application is proposed, and the reusable library component template is defined. Combined image template is generated by combining simulation application and library component templates. Dockerfile is generated by the combined template after syntax optimization and error detection. The experiments …

Simulation Of Incentive Mechanism Simulation On Reverse Supply Chain Of Waste Products Based On Dual Drive, Dongshi Sun, Danlan Xie, Guan Feng, Ji Yuan

Journal of System Simulation

Abstract: In view of the current situation of coordination failure caused by different benefits of different entities in the waste reverse supply chain, based on system dynamics, a three-party evolutionary game model of residents, waste disposal institutions and production enterprises is constructed. Vensim simulation software is used to establish the stock-flow chart with the strategy selection probability as the horizontal variable. In the two cases of exogenous variable in constant and a time-trend, the simulation is carried out separately, and the strategy evolution path of the three parties is obtained without external interference. Through sensitivity analysis, the exogenous variables …

Effect Of New Titanium Alloy On Biomechanical Behavior Of Dental Implant, Jiwu Zhang, Qiguo Rong

Journal of System Simulation

Abstract: Titanium alloy materials have excellent mechanical properties, chemical stability and biocompatibility, and have become the main raw materials for implants. However, the biomechanical compatibility of medical titanium alloys still needs to be improved in order to meet the long-term safety and functionality of patient's clinical treatment requirement. New medical titanium alloy materials with high strength and low modulus play an important role in reducing the loosening and shedding of implants caused by stress shielding. The effects of new medical titanium alloy materials and traditional medical titanium alloy materials on implant structure and stress distribution of jaw are compared and …

Research On Real-Time Simulation Method Of Bi-Sar Echo In Time-Varying Sea Scene, Guijie Diao, Ni Hong, Zhe Liu, Li Yang

Journal of System Simulation

Abstract: Based on bistatic scattering mechanism and the geometric relationship of bistatic synthetic aperture radar (Bi-SAR), a real-time simulation method of Bi-SAR radio frequency echo in time-varying sea scene is proposed. For the couple scattering in time-varying sea scene, a Bi-SAR echo signal model is established on the basis of multipath scattering model. The Bi-SAR system response function for time-varying sea target is calculated in real-time, using high performance computing technology, high-capacity real-time access technology and full-switching system designing. The simulation results show the effectiveness of the method.

A Pmbldc Motor Measurement And Control System Available For Zynq Hardware-In-The-Loop Simulation, Zhiguo Zhou, Jiaen Sun, Jiabao Yu, Xuehua Zhou

Journal of System Simulation

Abstract: In order to solve the modeling of permanent magnet brushless dc(PMBLDC) motor, it is difficult to modify the control algorithm, inconvenient to add and remove the closed loop, and has poor real-time measurement and control capability. Based on hall sensor position detection algorithm and PID control algorithm, combined with piecewise linear method to generate PWM waveform, Simulink graphical modeling platform is used, and a new closed-loop measurement and control method is proposed. A sudden load and sudden speed simulation are carried out to verify the established PMBLDC motor measurement and control system. The simulation results show that the system …

Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr

LSU Master's Theses

Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, simulation is computationally expensive and time consuming. This study explores reduced order models (ROMs) as an appropriate alternative. ROMs that use neural networks effectively capture nonlinear dependencies, and only require available operational data as inputs. Neural networks are a black box and difficult to interpret, however. Physics informed neural networks (PINNs) provide a potential solution to these shortcomings, but have not yet been applied extensively in petroleum engineering.

A mature black-oil simulation model from Volve public data release was used to generate training data …

Evaluation Of Reliability Indicators Of Mobile Communication System Bases, Dilmurod Davronbekov, Utkir Karimovich Matyokubov, Malika Ilkhamovna Abdullayeva

Bulletin of TUIT: Management and Communication Technologies

In this study, the reliability of mobile system base stations (BTS) is assessed by analyzing data obtained on faults in about 200 BTS over a six-month period. Five BTSs with the highest number of failures and duration of failure were selected in these BTSs. Based on the data obtained, reliability parameters were calculated and compared.

The study used Weibull’s dismissal process distribution method. The breakdown times of each BTS were sorted. In all five BTS, it was found that β(where the value of β is the approximate value obtained from the values of the smallest squares of the Weibull graph), …

Different Approximation Algorithms For Channel Scheduling In Wireless Networks, Qiufen Ni, Chuanhe Huang, Panos M. Pardalos, Jia Ye, Bin Fu

Computer Science Faculty Publications

We introduce a new two-side approximation method for the channel scheduling problem, which controls the accuracy of approximation in two sides by a pair of parameters . We present a series of simple and practical-for-implementation greedy algorithms which give constant factor approximation in both sides. First, we propose four approximation algorithms for the weighted channel allocation problem: 1. a greedy algorithm for the multichannel with fixed interference radius scheduling problem is proposed and an one side -IS-approximation is obtained; 2. a greedy -approximation algorithm for single channel with fixed interference radius scheduling problem is presented; 3. we improve the existing …

An Analysis Of The Effectiveness Of Cuban Cyberactivism, Neta Kanny

Journal of Global Initiatives: Policy, Pedagogy, Perspective

This article applies power-law degree distribution and network theory as a conceptual framework for assessing the effectiveness of Cuban cyberactivism based on an analysis of previous scholarly work on the topic. While Cuban cyberactivism indicates the potential for a more accessible, just, and transparent media environment, the movement continues to face serious obstacles due to extensive controls put in place by the Communist Party of Cuba.

Deep Learning In The Maintenance Industry, Paulo Cesar Ribeiro Silva

Doctoral

No abstract provided.

Integrating Deep Learning And Augmented Reality To Enhance Situational Awareness In Firefighting Environments, Manish Bhattarai

Electrical and Computer Engineering ETDs

We present a new four-pronged approach to build firefighter's situational awareness for the first time in the literature. We construct a series of deep learning frameworks built on top of one another to enhance the safety, efficiency, and successful completion of rescue missions conducted by firefighters in emergency first response settings. First, we used a deep Convolutional Neural Network (CNN) system to classify and identify objects of interest from thermal imagery in real-time. Next, we extended this CNN framework for object detection, tracking, segmentation with a Mask RCNN framework, and scene description with a multimodal natural language processing(NLP) framework. Third, …

Fusion-Features And Visual-Dictionary Image Recognition Methods For Apple Classification In Smart Manufacturing, Ahsiah Ismail

Student Works (2020-2029)

Smart manufacturing enables an efficient manufacturing process to optimize production. The optimization is performed through data analytics that requires reliable and informative data as input. Therefore, in this research, two image recognition feature extraction methods namely Curvelet Wavelet-Gray Level Co-occurrence Matrix (CWGLCM) and Fuzzy-Spatial Pyramid Matching (F-SPM) are proposed to provide reliable inputs for vision-based apple classification in smart manufacturing. Feature extraction is one of the major steps that could influent the efficiency of the manufacturing process. The CW-GLCM method is a feature extraction of fusion-features with Decision Tree classifier, while the F-SPM method uses a visual-dictionary based method to …

Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, Mehdi Bagherzadeh, Nicholas Fireman, Anas Shawesh, Raffi Khatchadourian

Publications and Research

Actor concurrency is becoming increasingly important in the development of real-world software systems. Although actor concurrency may be less susceptible to some multithreaded concurrency bugs, such as low-level data races and deadlocks, it comes with its own bugs that may be different. However, the fundamental characteristics of actor concurrency bugs, including their symptoms, root causes, API usages, examples, and differences when they come from different sources are still largely unknown. Actor software development can significantly benefit from a comprehensive qualitative and quantitative understanding of these characteristics, which is the focus of this work, to foster better API documentations, development practices, …

Energy-Efficient Communications In Wireless Powered Cognitive Radio Networks Based On Game Theory, Fadhil Mukhlif Aswad Al-Obaidy

Student Works (2020-2029)

There are challenging and prevalent problems related to spectrum resources with the interference of battery-based devices in future wireless networks. To address such challenges, this thesis proposes a theoretical framework for designing and analyzing the distributed power control algorithms in modern 5G cognitive networks. Previous experiments have shown that game theory tools can be used as a suitable and efficient technique to build scalable, balanced, and energy efficient for the distributed power control schemes in order to use it practically in battery-based devices in wireless networks. In reality, the power control issue is constructed as a non-cooperative game for which …

Countermeasures Against Various Network Attacks Using Machine Learning Methods, Yi Li

USF Tampa Graduate Theses and Dissertations

With the rapid development of a computer network, our lives are already inseparable from it. Wireless Fidelity (Wi-Fi) is in use everywhere; more and more devices are connected to the Internet, and many companies and individuals tend to store their data and information online. Furthermore, it is now very convenient to communicate with each other through email and text messages. However, widespread networks also provide more attack surfaces for attackers. There are a variety of network attacks aimed at information theft. To better defend against those network attacks, one needs to have a broad knowledge of existing attacks. In this …

System Support Of Concurrent Database Query Processing On A Gpu, Hao Li

USF Tampa Graduate Theses and Dissertations

The unrivaled computing capabilities of modern GPUs meet the demand of processing massive amounts of data seen in many application domains. While traditional HPC systems support applications as standalone entities that occupy the entire GPU, we propose a GPU-based DBMS (G-DBMS) that can run multiple tasks concurrently. To that end, system-level management mechanisms like resource allocation and buffer manager are needed to build such a concurrent database query processing system and fully unleash the GPUs’ computing power. However, CUDA does not provide enough OS-level functionalities to support it. Thus our research is focusing on implementing the optimization of resource allocation …

Identification Of Ecg Anomalies Through Deep Deterministic Learning, Uzair Iqbal

Student Works (2020-2029)

Electrocardiography (ECG) is a primary diagnostic tool for measuring the malfunctioning of the heart muscles in the context of morbidity of different cardiac diseases and arrhythmia. Different existing techniques and methods delivered accurate cardiac diseases myocardial infarction (heart stroke) and atrial fibrillation recognition. However, there are still some flaws in existing methods like recognition of special myocardial infarction situation flattened T wave in “Non-Specific ST-T Changes (nsst-t)” and reduction of computational cost in cardiac diseases recognition. Accurate recognition of cardiac diseases along with least computational complexity and feature analysis of flattened T wave in myocardial infarction remains an open job. …

Personalized Immunotherapy Treatment Strategies For A System Of Chronic Myelogenous Leukemia, Paul Valle

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Deep Learning With Physics Informed Neural Networks For The Airborne Spread Of Covid-19 In Enclosed Spaces, Udbhav Muthakana, Padmanabhan Seshaiyer, Maziar Raissi, Long Nguyen

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Study Of Sentiment Of Covid-19 Related Tweets In The Usa, Jack Luu, Rosangela Follmann

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Discrete Models And Algorithms For Analyzing Dna Rearrangements, Jasper Braun

USF Tampa Graduate Theses and Dissertations

In this work, language and tools are introduced, which model many-to-many mappings that comprise DNA rearrangements in nature. Existing theoretical models and data processing methods depend on the premise that DNA segments in the rearrangement precursor are in a clear one-to-one correspondence with their destinations in the recombined product. However, ambiguities in the rearrangement maps obtained from the ciliate species Oxytricha trifallax violate this assumption demonstrating a necessity for the adaptation of theory and practice.

In order to take into account the ambiguities in the rearrangement maps, generalizations of existing recombination models are proposed. Edges in an ordered graph model …

Formal Concept Analysis Applications In Bioinformatics, Sarah Roscoe

School of Computing: Dissertations, Theses, and Student Research

Bioinformatics is an important field that seeks to solve biological problems with the help of computation. One specific field in bioinformatics is that of genomics, the study of genes and their functions. Genomics can provide valuable analysis as to the interaction between how genes interact with their environment. One such way to measure the interaction is through gene expression data, which determines whether (and how much) a certain gene activates in a situation. Analyzing this data can be critical for predicting diseases or other biological reactions. One method used for analysis is Formal Concept Analysis (FCA), a computing technique based …

Barriers And Drivers Influencing The Growth Of E-Commerce In Uzbekistan, Madinakhon Tursunboeva

Theses and Dissertations

Electronic commerce (e-commerce) has become a major retail channel for businesses in developed countries. However, it is still considered an innovation in developing countries. Specifically, e-commerce in Uzbekistan is in the early stages of emergence despite its advance in recent years in terms of Internet penetration, a strong retail sector, new national regulations, and a young population. The study aimed to identify barriers and drivers influencing e-commerce growth in Uzbekistan. A Delphi research design was utilized to answer the research questions of the study, which categorized and ranked factors that Uzbekistani entrepreneurs are facing when engaging in e-commerce processes. A …

An Analysis Of Technological Components In Relation To Privacy In A Smart City, Kayla Rutherford, Ben Lands, A. J. Stiles

James Madison Undergraduate Research Journal (JMURJ)

A smart city is an interconnection of technological components that store, process, and wirelessly transmit information to enhance the efficiency of applications and the individuals who use those applications. Over the course of the 21st century, it is expected that an overwhelming majority of the world’s population will live in urban areas and that the number of wireless devices will increase. The resulting increase in wireless data transmission means that the privacy of data will be increasingly at risk. This paper uses a holistic problem-solving approach to evaluate the security challenges posed by the technological components that make up a …