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Improving Syntactic Relationships Between Language And Objects, Benjamin Wilke, Tej Tenmattam, Anand Rajan, Andrew Pollock, Joel Lindsey 2020 Southern Methodist University

Improving Syntactic Relationships Between Language And Objects, Benjamin Wilke, Tej Tenmattam, Anand Rajan, Andrew Pollock, Joel Lindsey

SMU Data Science Review

This paper presents the integration of natural language processing and computer vision to improve the syntax of the language generated when describing objects in images. The goal was to not only understand the objects in an image, but the interactions and activities occurring between the objects. We implemented a multi-modal neural network combining convolutional and recurrent neural network architectures to create a model that can maximize the likelihood of word combinations given a training image. The outcome was an image captioning model that leveraged transfer learning techniques for architecture components. Our novelty was to quantify the effectiveness of transfer learning ...


Physical Dispersions Of Meteor Showers Through High Precision Optical Observations, Denis Vida 2020 The University of Western Ontario

Physical Dispersions Of Meteor Showers Through High Precision Optical Observations, Denis Vida

Electronic Thesis and Dissertation Repository

Meteoroids ejected from comets form meteoroid streams which disperse over time due to gravitational perturbations and non-gravitational forces. When stream meteoroids collide with the Earth's atmosphere, they are visible as meteors emanating from a common point-like area (radiant) in the sky. Measuring the size of meteor shower radiant areas can provide insight into stream formation and age. The tight radiant dispersion of young streams are difficult to determine due to measurement error, but if successfully measured, the dispersion could be used to constrain meteoroid ejection velocities from their parent comets. The estimated ejection velocity is an uncertain, model-dependent value ...


Advanced Techniques To Detect Complex Android Malware, Zhiqiang Li 2020 University of Nebraska - Lincoln

Advanced Techniques To Detect Complex Android Malware, Zhiqiang Li

Computer Science and Engineering: Theses, Dissertations, and Student Research

Android is currently the most popular operating system for mobile devices in the world. However, its openness is the main reason for the majority of malware to be targeting Android devices. Various approaches have been developed to detect malware.

Unfortunately, new breeds of malware utilize sophisticated techniques to defeat malware detectors. For example, to defeat signature-based detectors, malware authors change the malware’s signatures to avoid detection. As such, a more effective approach to detect malware is by leveraging malware’s behavioral characteristics. However, if a behavior-based detector is based on static analysis, its reported results may contain a large ...


Open Dynamic Interaction Network: A Cell-Phone Based Platform For Responsive Ema, Gisela Font Sayeras 2020 University of Nebraska - Lincoln

Open Dynamic Interaction Network: A Cell-Phone Based Platform For Responsive Ema, Gisela Font Sayeras

Computer Science and Engineering: Theses, Dissertations, and Student Research

The study of social networks is central to advancing our understanding of a wide range of phenomena in human societies. Social networks co-evolve concurrently alongside the individuals within them. Selection processes cause network structure to change in response to emerging similarities/differences between individuals. At the same time, diffusion processes occur as individuals influence one another when they interact across network links. Indeed, each network link is a logical abstraction that aggregates many short-lived pairwise interactions of interest that are being studied. Traditionally, network co-evolution is studied by periodically taking static snapshots of social networks using surveys. Unfortunately, participation incentives ...


Dolphinnext: A Distributed Data Processing Platform For High Throughput Genomics, Onur Yukselen, Osman Turkyilmaz, Ahmet R. Ozturk, Manuel Garber, Alper Kucukural 2020 University of Massachusetts Medical School

Dolphinnext: A Distributed Data Processing Platform For High Throughput Genomics, Onur Yukselen, Osman Turkyilmaz, Ahmet R. Ozturk, Manuel Garber, Alper Kucukural

Open Access Articles

BACKGROUND: The emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) is transforming biological research. The dramatic increase in the volume of data, the variety and continuous change of data processing tools, algorithms and databases make analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for highly parallel, flexible, portable, and reproducible data processing frameworks. Several platforms currently ...


Computational Chemistry In The Cloud, Gregory Campbell 2020 Hope College

Computational Chemistry In The Cloud, Gregory Campbell

19th Annual Celebration of Undergraduate Research and Creative Activity (2020)

Computational chemistry requires expensive computers and significant computer expertise. We are remedying these issues by using cloud computing to lower costs and by developing our Server In The Cloud (SITC) script to reduce the need for local expertise. SITC implements computational chemistry engines with the user-friendly WebMO interface on Google and Amazon cloud computers. In this way, we are making computational chemistry cheaper and more accessible to a wider range of chemistry students and researchers.


Fast Clustering Using A Grid-Based Underlying Density Function Approximation, Daniel Brown 2020 Kennesaw State University

Fast Clustering Using A Grid-Based Underlying Density Function Approximation, Daniel Brown

Master of Science in Computer Science Theses

Clustering is an unsupervised machine learning task that seeks to partition a set of data into smaller groupings, referred to as “clusters”, where items within the same cluster are somehow alike, while differing from those in other clusters. There are many different algorithms for clustering, but many of them are overly complex and scale poorly with larger data sets. In this paper, a new algorithm for clustering is proposed to solve some of these issues. Density-based clustering algorithms use a concept called the “underlying density function”, which is a conceptual higher-dimension function that describes the possible results from the continuous ...


Sight Helper, Misael Uzcategui 2020 Harrisburg University of Science and Technology

Sight Helper, Misael Uzcategui

Other Student Works

No abstract provided.


Context Aware Data Generation Through Domain Specific Language, Caleb Druckemiller 2020 Harrisburg University of Science and Technology

Context Aware Data Generation Through Domain Specific Language, Caleb Druckemiller

Other Student Works

No abstract provided.


Human Activity Recognition & Mobily Path Prediction, Priya Patel 2020 Harrisburg University of Science and Technology

Human Activity Recognition & Mobily Path Prediction, Priya Patel

Other Student Works

Individual Mobility is the study that depicts how individuals move inside a region or system. As of late a few researches have been accomplished for this reason and there has been a flood in enormous informational accessible in individual developments. Most of these information’s are gathered from cellphone or potentially GPS with variable accuracy relying upon the distance from the tower. Enormous scope information, for example, cell phone follows are significant hotspot for urban modeling. The individual travel designs breakdown into a solitary likelihood distribution however despite the assorted variety of their travel history people follow basic reproducible examples ...


Effective Smart Video Survillance And Alertinng, Kranthikumar Putta 2020 Harrisburg University of Science and Technology

Effective Smart Video Survillance And Alertinng, Kranthikumar Putta

Other Student Works

Machine learning models & AI are popular term in past couple of years. Almost every aspect on our daily life we are using these machine learning models & AI knowing or unknowing. The simple statement of this research paper is to prove reduction of human effort in camera surveillance by using machine learning models such as objection detection & facial recognition.

TensorFlow is leading open source tool developed and published by Google helps to build objection detection and facial recognition library. The code we about to develop can allow user to train model with his choice of images of objects and faces of ...


Stock Investment Helper, Mingrui Xu 2020 Harrisburg University of Science and Technology

Stock Investment Helper, Mingrui Xu

Other Student Works

No abstract provided.


A Study Over Registration Server System Simulation, Maolin Hang 2020 Harrisburg University of Science and Technology

A Study Over Registration Server System Simulation, Maolin Hang

Other Student Works

This paper is a continuous study of the registration server system using a previous created real-time simulation application for my working product- T-Mobile Digits’ registration server system - an Enterprise-level solution ensembles Skype for Business, but with a sizable testing user pool.

As a standard system design normally includes the hardware infrastructure, computational logics and its own assigned rules/configures, and as all the complex system, a well-set server structure is the kernel for no matter testing or commercial purpose. The challenges are real and crucial for both business success besides the concerns of access capability and security. It will begin ...


Uprising Digital Cyber-Attacks And Stagnant Cyber Laws Worldwide, Rahul Parekh 2020 Harrisburg University of Science and Technology

Uprising Digital Cyber-Attacks And Stagnant Cyber Laws Worldwide, Rahul Parekh

Other Student Works

Cybersecurity is vast area for research with multiple domains. Any individual can focus on minimum topics for research and it becomes cumbersome to follow various tools and technique. In this research paper, I have tried to focus on digital cybersecurity crime and terrorism efforts by hackers however there are numerous ways to minimize the hacking activities. To reduce such attacks and understand the chronology, research paper will display research and understanding.


Evote – The Revolution Of Vote, Tianming Zhu 2020 Harrisburg University of Science and Technology

Evote – The Revolution Of Vote, Tianming Zhu

Other Student Works

This report focuses on independently developed applications that are primarily used to support group or group solutions. The tools used to develop this application include Android development tools, and Google Firebase development tools are also involved in the development process.


A Tool For Securities Analysis And Trading Strategy Back-Testing, Qiaosheng Yu 2020 Harrisburg University of Science and Technology

A Tool For Securities Analysis And Trading Strategy Back-Testing, Qiaosheng Yu

Other Student Works

The platform created in this project will help users to analyze stock/ETF performance, define and improve their asset allocation plans and trade ideas. Using real market data, user can do a deep dive into securities performance, historical correlation, risk and return. Furthermore, user can use the platform back test their trade ideas, modify the parameters, including percentage allocation, risk limits and rebalancing frequency, and create the best strategy which suits their risk/return criteria and long-term wealth management goals.


Chat Application With Distributed System, Shuyang Zhu 2020 Harrisburg University of Science and Technology

Chat Application With Distributed System, Shuyang Zhu

Other Student Works

This project created a web application for users to instantly communicate with each other. An the most important part of building a good chat application is focus on the data flow on web. This project spends a good amount of research to find the most appropriate technology for deliver the data flow, which is REST api for account management, WebSocket for text chat and WebRTC for video and audio and find the result pleasant.


Deep Learning Framework Of Vehicle Detection And Tracking System, Rui Zhang 2020 Harrisburg University of Science and Technology

Deep Learning Framework Of Vehicle Detection And Tracking System, Rui Zhang

Other Student Works

In the last semester, I designed a system to detect and track vehicle system on the highway. The system is based on the public deep learning framework and utilize pre-trained model to implement the functions of this system. In this paper, I will use my own framework to implement this system. This try will help us better understand the details of deep learning framework. I will public the code of deep learning framework and make sure everyone can modify it.

This semester will focus on the researching of Naïve Convolutional Neural Networks. Neural networks are commonlyused for the analysis of ...


Achieving Obfuscation Through Self-Modifying Code: A Theoretical Model, Heidi Waddell 2020 Liberty University

Achieving Obfuscation Through Self-Modifying Code: A Theoretical Model, Heidi Waddell

Senior Honors Theses

With the extreme amount of data and software available on networks, the protection of online information is one of the most important tasks of this technological age. There is no such thing as safe computing, and it is inevitable that security breaches will occur. Thus, security professionals and practices focus on two areas: security, preventing a breach from occurring, and resiliency, minimizing the damages once a breach has occurred. One of the most important practices for adding resiliency to source code is through obfuscation, a method of re-writing the code to a form that is virtually unreadable. This makes the ...


Dugesia Japonica Is The Best Suited Of Three Planarian Species For High-Throughput Toxicology Screening, D. Ireland, Veronica Bochenek , '22, Daniel Chaiken , '20, C. Rabeler, Sumi Onoe , '21, Ameet Soni, Eva-Maria S. Collins 2020 Swarthmore College

Dugesia Japonica Is The Best Suited Of Three Planarian Species For High-Throughput Toxicology Screening, D. Ireland, Veronica Bochenek , '22, Daniel Chaiken , '20, C. Rabeler, Sumi Onoe , '21, Ameet Soni, Eva-Maria S. Collins

Biology Faculty Works

High-throughput screening (HTS) using new approach methods is revolutionizing toxicology. Asexual freshwater planarians are a promising invertebrate model for neurotoxicity HTS because their diverse behaviors can be used as quantitative readouts of neuronal function. Currently, three planarian species are commonly used in toxicology research: Dugesia japonica, Schmidtea mediterranea, and Girardia tigrina. However, only D. japonica has been demonstrated to be suitable for HTS. Here, we assess the two other species for HTS suitability by direct comparison with D. japonica. Through quantitative assessments of morphology and multiple behaviors, we assayed the effects of 4 common solvents (DMSO, ethanol, methanol, ethyl acetate ...


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