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An Optimization Approach For Automated Unit Test Generation Tools Using Multi-Objective Evolutionary Algorithms, Samar Ali Abdallah, ramdan mowad, Esaam Eldeen Fawzy 2020 Arab Academy for Science, Technology & Maritime Transport, Cairo, Egypt

An Optimization Approach For Automated Unit Test Generation Tools Using Multi-Objective Evolutionary Algorithms, Samar Ali Abdallah, Ramdan Mowad, Esaam Eldeen Fawzy

Future Computing and Informatics Journal

High code coverage is measured by the process of software testing typically using automatic test case generation tools. This standard approach is usually used for unit testing to improve software reliability. Most automated test case generation tools focused just on code coverage without considering its cost and redundancy between generated test cases. To obtain optimized high code coverage and to ensure minimum cost and redundancy a Multi-Objectives Evolutionary Algorithm approach (MOEA) is set in motion. An efficient approach is proposed and applied to different algorithms from MOEA Frame from the separate library with three fitness functions for Coverage, Cost, and ...


A Thresholding Based Technique To Extract Retinal Blood Vessels From Fundus Images, Jyotiprava Dash, Nilamani Bhoi 2020 Department of Electronic & Tele-communication, Veer Surendra Sai University of Technology, Burla, 768018, India.

A Thresholding Based Technique To Extract Retinal Blood Vessels From Fundus Images, Jyotiprava Dash, Nilamani Bhoi

Future Computing and Informatics Journal

Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i) pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii) segmentation using mean-C thresholding to extract ...


A Nove L F U Z Z Y L O G I C B A S E D R Eve R S E E N G I N E E R I N G O F G E N E R Eg U L A T O R Y N E T W O R K, Raviajot Kaur, Abhishek Bhola, Shailendra Singh 2020 Department of Computer Science and Engineering, PEC University of Technology, Chandigarh 160012, India

A Nove L F U Z Z Y L O G I C B A S E D R Eve R S E E N G I N E E R I N G O F G E N E R Eg U L A T O R Y N E T W O R K, Raviajot Kaur, Abhishek Bhola, Shailendra Singh

Future Computing and Informatics Journal

Genes of an organism play a very crucial role in the working of various cellular activities. Genes and other biological molecules like DNA, RNA do not operate alone but they all are correlated. Their relationships are shown with the help of networks commonly known as Gene Regulatory Networks. Gene Regulatory Networks are complex control networks that show the map of interactions among the genes. They provide very useful contribution to the genomic science and increase the understanding of various biological processes. In this paper, fuzzy logic based method is proposed for the reverse engineering of gene regulatory network from microarray ...


A Supporting Tool For Requirements Change Management In Distributed Agile Development, ramdan mowad, Domia Lloyd, Mona Kadry 2020 Faculty of Computers and Information Technology, Future University in Egypt, Cairo, Egypt

A Supporting Tool For Requirements Change Management In Distributed Agile Development, Ramdan Mowad, Domia Lloyd, Mona Kadry

Future Computing and Informatics Journal

Software development industry has witnessed the growth of the agile movement and approaches. Applying the agile approaches and practices in the distributed environment will lead to gain a lot of benefits such as reduced costs, higher efficiency and better customization, on the other hand it will face many challenges for example working in different time zones, requirements changes, personal selection and knowledge management. In order to gain these benefits, it should address the challenges that will face the agile approaches in a distributed environment. One of the main challenges is managing the requirements changes during the process of distributed agile ...


Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah 2020 University of Connecticut

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not ...


Evolution Of Computational Thinking Contextualized In A Teacher-Student Collaborative Learning Environment., John Arthur Underwood 2020 Louisiana State University and Agricultural and Mechanical College

Evolution Of Computational Thinking Contextualized In A Teacher-Student Collaborative Learning Environment., John Arthur Underwood

LSU Doctoral Dissertations

The discussion of Computational Thinking as a pedagogical concept is now essential as it has found itself integrated into the core science disciplines with its inclusion in all of the Next Generation Science Standards (NGSS, 2018). The need for a practical and functional definition for teacher practitioners is a driving point for many recent research endeavors. Across the United States school systems are currently seeking new methods for expanding their students’ ability to analytically think and to employee real-world problem-solving strategies (Hopson, Simms, and Knezek, 2001). The need for STEM trained individuals crosses both the vocational certified and college degreed ...


Using Case-Level Context To Classify Cancer Pathology Reports, Shang Gao, Mohammed Alawad, Noah Schaefferkoetter, Lynne Penberthy, Xiao-Cheng Wu, Eric B. Durbin, Linda Coyle, Arvind Ramanathan, Georgia Tourassi 2020 Oak Ridge National Laboratory

Using Case-Level Context To Classify Cancer Pathology Reports, Shang Gao, Mohammed Alawad, Noah Schaefferkoetter, Lynne Penberthy, Xiao-Cheng Wu, Eric B. Durbin, Linda Coyle, Arvind Ramanathan, Georgia Tourassi

Kentucky Cancer Registry Faculty Publications

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence-for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We ...


Chaprates, Brinly Xavier, Micole Amanda Marietta, Nidhi Vedantam 2020 Chapman University

Chaprates, Brinly Xavier, Micole Amanda Marietta, Nidhi Vedantam

Student Scholar Symposium Abstracts and Posters

On the Chapman campus, through taking and choosing various classes, there is a significant need for communication and feedback between students and peers, professors, tutors, and study groups. With this, we wanted to create an application that enables users from various majors to not only easily and effectively communicate with various people in their field, but one that also enables them to give and receive feedback on various classes through a rating system. We believe that the application will aid students in a myriad of specific ways, including being involved in study groups and getting tutoring help, determining which classes ...


Gait Characterization Using Computer Vision Video Analysis, Martha T. Gizaw 2020 College of William and Mary

Gait Characterization Using Computer Vision Video Analysis, Martha T. Gizaw

Undergraduate Honors Theses

The World Health Organization reports that falls are the second-leading cause of accidental death among senior adults around the world. Currently, a research team at William & Mary’s Department of Kinesiology & Health Sciences attempts to recognize and correct aging-related factors that can result in falling. To meet this goal, the members of that team videotape walking tests to examine individual gait parameters of older subjects. However, they undergo a slow, laborious process of analyzing video frame by video frame to obtain such parameters. This project uses computer vision software to reconstruct walking models from residents of an independent living retirement ...


Evaluating Machine Learning Models For Semantic Segmentation Over Cloud Images For Classification, Harsh Nagarkar 2020 University of Mississippi

Evaluating Machine Learning Models For Semantic Segmentation Over Cloud Images For Classification, Harsh Nagarkar

Honors Theses

Due to the increasing number of available approaches nowadays, choosing the most accurate image semantic segmentation model has become hard. The purpose of this research is to find the best-performing image semantic segmentation model for Cloud classification. For the purpose of this study, a data set of cloud images from the Max Planck Institute for meteorology is used. These images were taken from the by two NASA space satellite.Three main models UNet, PSPNet and FPN were used in combination of 4 differ-ent encoder Inception-ResNet-v2, MobileNet-v2, ResNet-34, and ResNet 101. After training all the models in the Mississippi Center for ...


Minet Magnetic Indoor Localization, Michael Drake 2020 University of Mississippi

Minet Magnetic Indoor Localization, Michael Drake

Honors Theses

Indoor localization is a modern problem of computer science that has no unified solution, as there are significant trade-offs involved with every technique. Magnetic localization, though less popular than WiFi signal based localization, is a sub-field that is rooted in infrastructure-free design, which can allow universal setup. Magnetic localization is also often paired with probabilistic programming, which provides a powerful method of estimation, given a limited understanding of the environment. This thesis presents Minet, which is a particle filter based localization system using the Earth's geomagnetic field. It explores the novel idea of state space limitation as a method ...


Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia 2020 Southern Methodist University

Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia

SMU Data Science Review

In this paper, we introduce a proof of concept that addresses the assumption and limitation of linear local boundaries by Local Interpretable Model-Agnostic Explanations (LIME), a popular technique used to add interpretability and explainability to black box models. LIME is a versatile explainer capable of handling different types of data and models. At the local level, LIME creates a linear relationship for a given prediction through generated sample points to present feature importance. We redefine the linear relationships presented by LIME as quadratic relationships and expand its flexibility in non-linear cases and improve the accuracy of feature interpretations. We coin ...


Sensitivity Analysis Of Data-Driven Groundwater Forecasts To Hydroclimatic Controls In Irrigated Croplands, Alessandro Amaranto, Francesca Pianosi, Dimitri Solomatine, Gerald Corzo-Perez, Francisco Munoz-Arriola 2020 University of Nebraska-Lincoln

Sensitivity Analysis Of Data-Driven Groundwater Forecasts To Hydroclimatic Controls In Irrigated Croplands, Alessandro Amaranto, Francesca Pianosi, Dimitri Solomatine, Gerald Corzo-Perez, Francisco Munoz-Arriola

Biological Systems Engineering: Papers and Publications

In the last decades, advancements in computational science have greatly expanded the use of artificial neural networks (ANNs) in hydrogeology, including applications on groundwater forecast, variable selection, extended lead-times, and regime-specific analysis. However, ANN-model performance often omits the sensitivity to ob- servational uncertainties in hydroclimate forcings. The goal of this paper is to implement a data-driven modeling framework for assessing the sensitivity of ANN-based groundwater forecasts to the uncertainties in observational inputs across space, time, and hydrological regimes. The objectives are two-folded. The first objective is to couple an ANN model with the PAWN sensitivity analysis (SA). The second objective ...


Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann 2020 University of New Mexico

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann

Mathematics & Statistics ETDs

This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements ...


Perturbed Stress Field Of The Human Lens Capsule After Cataract Surgery, Kurt Ameku, Caleb Berggren, Ryan M. Pedrigi 2020 University of Nebraska - Lincoln

Perturbed Stress Field Of The Human Lens Capsule After Cataract Surgery, Kurt Ameku, Caleb Berggren, Ryan M. Pedrigi

UCARE Research Products

Current modeling of the human lens capsule has been focused on the mechanism of accommodation and its decline with age, but few studies have modeled the effects of cataract surgery and quantified the altered mechanical environment introduced by the procedure. The goal of this study is to develop the first fully 3-D finite element model of the post-surgical human lens capsule with an implanted device in order to characterize lens capsule mechanics after cataract surgery. The model demonstrates a highly perturbed stress field compared to the native state, which we hypothesize is the primary driving force behind the long-term errant ...


The Effect Of Oxygen On Properties Of Zirconium Metal, Jie ZHAO 2020 University of Massachusetts Amherst

The Effect Of Oxygen On Properties Of Zirconium Metal, Jie Zhao

Doctoral Dissertations

The influence of oxygen on the thermophysical properties of zirconium has been investigated using MSL-EML (Material Science Laboratory Electromagnetic Levitator) on ISS (International Space Station) in collaboration with NASA (National Aeronautics and Space Administration), ESA (European Space Agency), and DLR (German Aerospace Center). Zirconium samples with different oxygen concentrations was subjected to multiple melt cycles during which the thermophysical properties, such as density, viscosity and surface tension, have been measured at various undercooled and superheated temperatures. Also, there are melt cycles for verifying the solidification mechanism. Similar samples were found to show anomalous nucleation of the solid for certain ranges ...


Dynamic Procedural Music Generation From Npc Attributes, Megan E. Washburn 2020 California Polytechnic State University, San Luis Obispo

Dynamic Procedural Music Generation From Npc Attributes, Megan E. Washburn

Master's Theses

Procedural content generation for video games (PCGG) has seen a steep increase in the past decade, aiming to foster emergent gameplay as well as to address the challenge of producing large amounts of engaging content quickly. Most work in PCGG has been focused on generating art and assets such as levels, textures, and models, or on narrative design to generate storylines and progression paths. Given the difficulty of generating harmonically pleasing and interesting music, procedural music generation for games (PMGG) has not seen as much attention during this time.

Music in video games is essential for establishing developers' intended mood ...


Computational Modeling Of Laminated Veneer Bamboo (Lvb) Dowel Joints, Niloufar Khoshbakht 2020 University of Massachusetts Amherst

Computational Modeling Of Laminated Veneer Bamboo (Lvb) Dowel Joints, Niloufar Khoshbakht

Doctoral Dissertations

Laminated veneer bamboo (LVB) is a sustainable building material that has been gaining interest in the construction industry of late. As a relatively new product, little is known about its connection performance, specifically, its failure behavior in dowel type joints and possible similarities it may have to engineered wood products in terms of failure mechanisms. Research is needed to aid in the understanding of LVB dowel connection failure behavior and to quantify the failure mechanism and key factors associated with LVB dowel connection strength. Modeling, as conducted in this research, is a valuable tool to help devise safe standards and ...


Analysis Of Pro-Drop Errors In L2 English By L1 Spanish Speakers, Marcos R. Ynoa 2020 The Graduate Center, City University of New York

Analysis Of Pro-Drop Errors In L2 English By L1 Spanish Speakers, Marcos R. Ynoa

Dissertations, Theses, and Capstone Projects

Although educators and linguists have described and studied L2 learner errors, often from the perspective of positive and negative transfer (Krashen, 1981), there is relatively little empirical data on the frequencies of L2 error types. Learner error rankings do exist (Donahue, 2001) (Cambridge learner corpus; (Nicholls, 1999)), but these rankings are often too general and may overlook specifics when it comes to particular language learner groups. The goal of our work is to develop a tool that can be used to explore error patterns, address educator needs, and help answer research questions in L2 language learning. The tool we have ...


Heart Valve Isogeometric Sequentially-Coupled Fsi Analysis With The Space–Time Topology Change Method, Takuya Terahara, Kenji Takizawa, Tayfun E. Tezduyar, Yuri Bazilevs, Ming-Chen Hsu 2020 Waseda University

Heart Valve Isogeometric Sequentially-Coupled Fsi Analysis With The Space–Time Topology Change Method, Takuya Terahara, Kenji Takizawa, Tayfun E. Tezduyar, Yuri Bazilevs, Ming-Chen Hsu

Mechanical Engineering Publications

Heart valve fluid–structure interaction (FSI) analysis is one of the computationally challenging cases in cardiovascular fluid mechanics. The challenges include unsteady flow through a complex geometry, solid surfaces with large motion, and contact between the valve leaflets. We introduce here an isogeometric sequentially-coupled FSI (SCFSI) method that can address the challenges with an outcome of high-fidelity flow solutions. The SCFSI analysis enables dealing with the fluid and structure parts individually at different steps of the solutions sequence, and also enables using different methods or different mesh resolution levels at different steps. In the isogeometric SCFSI analysis here, the first ...


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