Computer Sciences Commons^™

Optimparallel: An R Package Providing A Parallel Version Of The L-Bfgs-B Optimization Method, Florian Gerber, Reinhard Furrer

The R Journal

The R package optimParallel provides a parallel version of the L-BFGS-B optimization method of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time, especially when the evaluation time of the objective function is large and no analytical gradient is available. We introduce the R package and illustrate its implementation, which takes advantage of the lexical scoping mechanism of R.

Integration Of Networks And Pathways With Starbiotrek Package, Claudia Cava, Isabella Castiglioni

The R Journal

High-throughput genomic technologies bring to light a comprehensive hallmark of molecular changes of a disease. It is increasingly evident that genes are not isolated from each other and the identification of a gene signature can only partially elucidate the de-regulated biological functions in a disease. The comprehension of how groups of genes (pathways) are related to each other (pathway-cross talk) could explain biological mechanisms causing diseases. Biological pathways are important tools to identify gene interactions and decrease the large number of genes to be studied by partitioning them into smaller groups. Furthermore, recent scientific studies have demonstrated that an integration …

Whats For Dynr: A Package For Linear And Nonlinear Dynamic Modeling In R, Lu Ou, Michael D. Hunter, Sy-Miin Chow

The R Journal

Intensive longitudinal data in the behavioral sciences are often noisy, multivariate in nature, and may involve multiple units undergoing regime switches by showing discontinuities interspersed with continuous dynamics. Despite increasing interest in using linear and nonlinear differential/difference equation models with regime switches, there has been a scarcity of software packages that are fast and freely accessible. We have created an R package called dynr that can handle a broad class of linear and nonlinear discrete- and continuous-time models, with regime-switching properties and linear Gaussian measurement functions, in C, while maintaining simple and easy-to-learn model specification functions in R. We present …

Swgee: An R Package For Analyzing Longitudinal Data With Response Missingness And Covariate Measurement Error, Juan Xiong, Grace Y. Yi

The R Journal

Though longitudinal data often contain missing responses and error-prone covariates, relatively little work has been available to simultaneously correct for the effects of response missingness and covariate measurement error on analysis of longitudinal data. Yi (2008) proposed a simulation based marginal method to adjust for the bias induced by measurement error in covariates as well as by missingness in response. The proposed method focuses on modeling the marginal mean and variance structures, and the missing at random mechanism is assumed. Furthermore, the distribution of covariates are left unspecified. These features make the proposed method applicable to a broad settings. In …

Simcorrmix: Simulation Of Correlated Data With Multiple Variable Types Including Continuous And Count Mixture Distributions, Allison Fialkowski, Hemant Tiwari

The R Journal

The SimCorrMix package generates correlated continuous (normal, non-normal, and mixture), binary, ordinal, and count (regular and zero-inflated, Poisson and Negative Binomial) variables that mimic real-world data sets. Continuous variables are simulated using either Fleishman’s third-order or Headrick’s fifth-order power method transformation. Simulation occurs at the component level for continuous mixture distributions, and the target correlation matrix is specified in terms of correlations with components. However, the package contains functions to approximate expected correlations with continuous mixture variables. There are two simulation pathways which calculate intermediate correlations involving count variables differently, increasing accuracy under a wide range of parameters. The package …

Krahasimi I Karakteristikave Të Protokoleve Në Kuadër Të Eps, Ajnur Bullaku

Theses and Dissertations

Duke e marr parasysh përdorimin shumë të madhe të teknologjisë 4G në tërë globin, gjithmonë është në rritje edhe kërkesa e sigurisë të lartë për të mbrojtur informatat të cilat rrugëtojn ne rrjetë nga keqpërdoruesit. AAA mekanizmi është pika kyçë në ketë drejtim ku edhe kemi menduar se është e rëndësishme ta shtjellojmë ketë temë, që tregon se si funksion AAA mekanizmi dhe protokollet që bëjnë pjesë në të.

Kërkesa për AAA protokollet është duke u rritur çdo ditë e më shumë. Protokollet me më shumë përdorim janë RADIUS dhe TACACS+ por nuk po ja arritin ti ndjekin zhvillimet e …

E-Mail I Bazuar Në Zë Për Njerëzit Me Shikim Të Dëmtuar, Arianit Mujaj

Theses and Dissertations

Një aplikacion mobil në rastet më të shpeshta reprezenton një funksionalitet sado bazik apo të komplikuar që njerëzit përdorin në jetën e tyre personale ose profesionale, në formë mobile të cilën mund ta bartin ngado me vete. Zhvillimi i aplikacioneve mobile është një gjë relativisht sfiduese, e cila kërkon kohë dhe dedikim të veçantë si proces inxhinierik. Kjo temë ka për synim të shtjellojë procesin e zhvillimit dhe dizajnimit të aplikacionit mobil “E-mail i bazuar në zë” dhe implementimin e teknologjisë “Voice recognition”. Për zhvillimin e një aplikacioni mobil të veçantë dhe të suksesshëm të këtij lloji, përveç kodit nevojiten …

Big Data Analysis With Apache Pig-Apache Hadoop, Blerim Latifi

Theses and Dissertations

Në këtë temë prezentoj 'Big Data Analysis with Apache Pig-Apache Hadoop' në fushën e grumbullimit të të dhënave, për shkak se proceset e grumbullimit të të dhënave përdoren aktualisht nga shumica e organizatave në botën dixhitale që po zgjerohet me informacione të pafundme. Platformat paralele të përpunimit dhe sistemet paralele të të dhënave që janë gjithnjë e më popullore. Frameworkat kanë përmirësuar ndjeshëm performancën e analizës së të dhënave. Dhjetëra ose qindra nyje vrapojnë së bashku për të ekzekutuar një detyrë. Është shumë e rëndësishme të përmirësohet shfrytëzimi i burimeve dhe efikasiteti i llogaritjes. Sipas Microsoftit, ekziston rreth 30% përllogaritjeve …

Computational Neuroscience, Arnold Gashi

Theses and Dissertations

Understanding how the brain works is a challenge that is attracting a number of scientists from many disciplines. This thesis is a study, to understand some of the models that explain the procedure how the brain works. By understanding computational models of the brain, we as programmers can create simulated programs that try to mimic brain behavior, and using them in many divisions of technology. CNS is very wide field and has so many things to cover this thesis will cover the basic construction of the brain, from neurons, as the principle cell of nervous system, to understand their complex …

Analiza E Algoritmeve Në Cloud Dhe Aspekti I Sigurisë Së Tyre, Fatlum Arifi

Theses and Dissertations

Sistemet e ruajtjes në re(cloud) janë duke u bërë më të lira dhe më të disponueshme. Me rritjen e popullaritetit të sistemeve të ruajtjes së reve, si në industri ashtu dhe në jetën tonë personale njerëzit kanë filluar të kujdesen për sigurinë e të dhënave të tyre në cloud. Pra, siguria është një faktor i rëndësishëm në cloud-sisteme për të siguruar që të dhënat e klientëve të vendosen në mënyrë të sigurt në cloud.

Ky punim ka si qëllim studimin e Cloud kompjuterit; karakteristikat e një cloudi, tipet e tyre, modelet e ndryshme. Studimi është pajisur me një gamë të …

The Red Fox Y-Chromosome In Comparative Context, Halie M. Rando, William H. Wadlington, Jennifer L. Johnson, Jeremy T. Stutchman, Lyudmila N. Trut, Marta Farré, Anna V. Kukekova

Computer Science: Faculty Publications

While the number of mammalian genome assemblies has proliferated, Y-chromosome assemblies have lagged behind. This discrepancy is caused by biological features of the Y-chromosome, such as its high repeat content, that present challenges to assembly with short-read, next-generation sequencing technologies. Partial Y-chromosome assemblies have been developed for the cat (Felis catus), dog (Canis lupus familiaris), and grey wolf (Canis lupus lupus), providing the opportunity to examine the red fox (Vulpes vulpes) Y-chromosome in the context of closely related species. Here we present a data-driven approach to identifying Y-chromosome sequence among the scaffolds that comprise the short-read assembled red fox genome. …

Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt

Computer Engineering

This project was designed to explore and analyze the potential abilities and usefulness of applying machine learning models to data collected by parking sensors at a major metro shopping mall. By examining patterns in rates at which customer enter and exit parking garages on the campus of the Bellevue Collection shopping mall in Bellevue, Washington, a recurrent neural network will use data points from the previous hours will be trained to forecast future trends.

Keylime, Eli William Partker

Computer Engineering

Josh, Matt and I knew we wanted to develop a mobile app for our senior project because that is what we found ourselves to be most passionate about during our time here at Cal Poly. We started to think of problems we wanted to solve using an application and we came up with a couple ideas but chose to expand on one. Students come to Cal Poly every year new to the area and the food options San Luis Obispo provides. Many of the restaurants in SLO offer a variety of deals to the community and most of them to …

Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch

Computer Engineering

With the increasing development of autonomous vehicles, being able to detect driveable paths in arbitrary environments has become a prevalent problem in multiple industries. This project explores a technique which utilizes a discretized output map that is used to color an image based on the confidence that each block is a driveable path. This was done using a generalized convolutional neural network that was trained on a set of 3000 images taken from the perspective of a robot along with matching masks marking which portion of the image was a driveable path. The techniques used allowed for a labeling accuracy …

The R Journal (June 2019) 11(1): Complete Issue, The R Foundation

The R Journal

Editorial, Michael J. Kane

Contributed Research Articles

atable: Create Tables for Clinical Trial Reports, Armin Ströbel

Connecting R with D3 for Dynamic Graphics, to Explore Multivariate Data with Tours, Michael Kipp, Ursula Laa, and Dianne Cook

Optimization Routines for Enforcing One-to-One Matches in Record Linkage Problems, Diego Moretti, Luca Valentino, and Tiziana Tuoto

mixedsde: A Package to Fit Mixed Stochastic Differential Equations, Charlotte Dion, Simone Hermann, and Adeline Samson

Indoor Positioning and Fingerprinting: The R Package ipft, Emilio Sansano, Raúl Montoliu, Óscar Belmonte, and Joaquín Torres-Sospedra

RobustGaSP: Robust Gaussian Stochastic Process Emulation in R, Mengyang Gu, Jesus Palomo, and James …

Single Image Reflection Removal Beyond Linearity, Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Due to the lack of paired data, the training of image reflection removal relies heavily on synthesizing reflection images. However, existing methods model reflection as a linear combination model, which cannot fully simulate the real-world scenarios. In this paper, we inject non-linearity into reflection removal from two aspects. First, instead of synthesizing reflection with a fixed combination factor or kernel, we propose to synthesize reflection images by predicting a non-linear alpha blending mask. This enables a free combination of different blurry kernels, leading to a controllable and diverse reflection synthesis. Second, we design a cascaded network for reflection removal with …

Meta-Transfer Learning For Few-Shot Learning, Qianru Sun, Yaoyao Liu, Tat-Seng Chua, Bernt Schiele

Research Collection School Of Computing and Information Systems

Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples only, meta-learning typically uses shallow neural networks (SNNs), thus limiting its effectiveness. In this paper we propose a novel few-shot learning method called meta-transfer learning (MTL) which learns to adapt a deep NN for few shot learning tasks. Specifically, …

Adopting The Cybersecurity Curriculum Guidelines To Develop A Secondary And Primary Academic Discipline In Cybersecurity Postsecondary Education, Wasim A. Alhamdani

Journal of Cybersecurity Education, Research and Practice

A suggested curriculum for secondary and primarily academic discipline in Cybersecurity Postsecondary Education is presented. This curriculum is developed based on the Association for Computing Machinery guidelines and the National Centers of Academic Excellence Cyber Operations program.

From The Editors, Michael E. Whitman, Herbert J. Mattord, Carole L. Hollingsworth

Journal of Cybersecurity Education, Research and Practice

No abstract provided.

Car Hacking: Accessing And Exploiting The Can Bus Protocol, Bryson R. Payne

Journal of Cybersecurity Education, Research and Practice

With the rapid adoption of internet-connected and driver-assist technologies, and the spread of semi-autonomous to self-driving cars on roads worldwide, cybersecurity for smart cars is a timely concern and one worth exploring both in the classroom and in the real world. Highly publicized hacks against production cars, and a relatively small number of crashes involving autonomous vehicles, have brought the issue of securing smart cars to the forefront as a matter of public and individual safety, and the cybersecurity of these “data centers on wheels” is of greater concern than ever.

However, up to this point there has been a …

A Design Case: Assessing The Functional Needs For A Multi-Faceted Cybersecurity Learning Space, Charles J. Lesko Jr.

Journal of Cybersecurity Education, Research and Practice

Following a multi-year effort that developed not only a detailed list of functional requirements but also the preliminary physical and logical design layouts, the concept for a multi-faceted cybersecurity center was approved and the physical, as well as, additional infrastructure space was subsequently allocated. This effort briefly describes the structure and scope of the current cybersecurity program being supported and then draws out the functional requirements that were identified for the center based on the needs of the institution’s cybersecurity program. It also highlights the physical and logical design specifications of the center, as well as, the many external program …

Reviewable - Online Review Web Application For The International English-Language Market, Aline Da Silva Luciano, Adeel Mateen, Fábio Bernardo Silva

ICT

This report presents the development of an online review web application for the International English Language Market. While in Ireland this industry contributes hugely to the Irish economy, the few regulations on the sector caused a wave of closures from 2014 to 2016. Several specific aspects of this industry that have contributed to this situation, such as the fact that most hiring student are of non-EEA origin (which includes specific Immigration arrangements for this group) justifies the relevance of an online review tool. This project discusses alternatives for establishing trust in the sector through validation, while presents concerning topics surrounding …

Reach - A Community Service Application, Samuel Noel Magana

Computer Engineering

Communities are familiar threads that unite people through several shared attributes and interests. These commonalities are the core elements that link and bond us together. Many of us are part of multiple communities, moving in and out of them depending on our needs. These common threads allow us to support and advocate for each other when facing a common threat or difficult situation. Healthy and vibrant communities are fundamental to the operation of our society. These interactions within our communities define the way we as individuals interact with each other, and society at large. Being part of a community helps …

A Computational Model For Recovery From Traumatic Brain Injury, Wayne Wakeland, Erin S. Kenzie

Complex Systems Faculty Publications and Presentations

A computational simulation model calculates estimated recovery trajectories following traumatic brain injury (TBI). Prior publications include a multi-scale conceptual framework for studying concussion, a systems-level causal loop diagram (CLD) and an analysis of key feedback processes. A set of first order ordinary differential equations and their associated parameters determines recovery trajectories. The model contains 15 state variables, 73 auxiliary variables, and 50 parameters describing TBI pathology in an aggregate fashion at the cellular, network, cognitive and social levels. There are 1200 feedback loops, which give rise to a variety of behavior modes, many of which are highly nonlinear. Exogenous parameters …

Event Trend Aggregation Under Rich Event Matching Semantics, Olga Poppe, Chuan Lei, Elke A. Rundensteiner, David Maier

Computer Science Faculty Publications and Presentations

Streaming applications from cluster monitoring to algorithmic trading deploy Kleene queries to detect and aggregate event trends. Rich event matching semantics determine how to compose events into trends. The expressive power of stateof- the-art streaming systems remains limited since they do not support many of these semantics. Worse yet, they suffer from long delays and high memory costs because they maintain aggregates at a fine granularity. To overcome these limitations, our Coarse-Grained Event Trend Aggregation (Cogra) approach supports a rich variety of event matching semantics within one system. Better yet, Cogra incrementally maintains aggregates at the coarsest granularity possible for …

Design And Analysis Of An Instrumenting Profiler For Webassembly, Chandler Gifford

Master's Theses

This thesis presents the design, implementation, and analysis of WasmProf, an instrumenting profiler for WebAssembly programs. WebAssembly is a compiled language designed for use on the web that, at the time of this writing, is still being actively developed. At present, performance analysis for WebAssembly programs mostly consists of browsers’ built-in sampling profilers. These profilers work well in many cases but only give a statistical estimation of the distribution of function calls and are, therefore, not well-suited for more fine-grained analysis. The WasmProf instrumenting profiler fills this analysis gap. WasmProf is capable of tracking the number of calls made and …

Simulating Epidemics And Interventions On High Resolution Social Networks, Christopher E. Siu

Master's Theses

Mathematical models of disease spreading are a key factor of ensuring that we are prepared to deal with the next epidemic. They allow us to predict how an infection will spread throughout a population, thereby allowing us to make intelligent choices when attempting to contain the disease. Whether due to a lack of empirical data, a lack of computational power, a lack of biological understanding, or some combination thereof, traditional models must make sweeping assumptions about the behavior of a population during an epidemic.

In this thesis, we implement granular epidemic simulations using a rich social network constructed from real-world …

Cross-Company Customer Churn Prediction In Telecommunication: A Comparison Of Data Transformation Methods, Adnan Amin, Babar Shah, Asad Masood Khattak, Fernando Joaquim Lopes Moreira, Gohar Ali, Alvaro Rocha, Sajid Anwar

All Works

© 2018 Elsevier Ltd Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, …

A Data Driven Approach To Identify Journalistic 5ws From Text Documents, Venkata Krishna Mohan Sunkara

School of Computing: Dissertations, Theses, and Student Research

Textual understanding is the process of automatically extracting accurate high-quality information from text. The amount of textual data available from different sources such as news, blogs and social media is growing exponentially. These data encode significant latent information which if extracted accurately can be valuable in a variety of applications such as medical report analyses, news understanding and societal studies. Natural language processing techniques are often employed to develop customized algorithms to extract such latent information from text.

Journalistic 5Ws refer to the basic information in news articles that describes an event and include where, when, who, what and why …

Performance And Economic Evaluation Of Differentiated Multiple Vacation Queueing System With Feedback And Balked Customers, Amina A. Bouchentouf, Latifa Medjahri

Applications and Applied Mathematics: An International Journal (AAM)

The present paper deals with a single server feedback queueing system under two differentiated multiple vacations and balked customers. It is assumed that the service times of the two vacation types are exponentially distributed with different means. The steady-state probabilities of the model are obtained. Some important performance measures of the system are derived. Then, a cost model is developed. Further, a numerical study is presented.