Computer Engineering Commons^™

Dataset To Analyzing Energy Use In 2 & 3d Imaging Systems And Workflows, Michael J. Bennett

Published Works

Analyzing Energy Use in 2D & 3D Imaging Systems and Workflows Dataset

CONTENTS: Z-WaveReportingProfiles; SessionInput; DroneFlights; SessionsComputed; Types; ByType; GrossSummaryUnweighted; WeightingSummary; Raw Sampling History Data

Artificial Sense-Making Dataset, Jason A. Bengtson, John Sandstrom, Nathan Camp

NMSU Library: Datasets

No abstract provided.

Ecu-Pmu-Fdi/Tsa, Taylah Griffiths, Mohiuddin Ahmed, Chadni Islam

Research Datasets

Cyberattacks are now targeting the electrical grid due to its inclusion of smart devices, e.g., smart meters, phasor measurement units. The need to understand and review the impacts of attacks is vital. ECU-PMU-FDI/TSA encompasses communications between a phasor measurement unit and a phasor data concentrator, using the IEEE C37.118 protocol. Benign traffic was captured as control, and for attacks false data injection and time synchronization attack traffic were captured.

Matthew Gaber: Peekaboo, Matthew Gaber, Mohiuddin Ahmed, Helge Janicke

Research Datasets

Cyber-attacks continue to evolve, increasing in frequency and sophistication where Artificial Intelligence (AI) is becoming essential in detecting modern malware. However, the accuracy of AI in malware detection is dependent on the quality of the features it is trained with. Static and dynamic analysis of malware is limited by the widespread use of obfuscation and anti-analysis techniques employed by malware authors, where if an analysis environment is detected the malware will hide its malicious behavior. However, Dynamic Binary Instrumentation (DBI) allows deep and precise control of the malware sample, thereby facilitating the extraction of authentic features from sophisticated and evasive …

Encrypted Malicious Network Traffic Detection Using Machine Learning, Niklas Knipschild

Symposium of Student Scholars

The research project aims to find ways to detect malicious packets inside encrypted network traffic. In addition to this goal maintaining user privacy is a priority. As encryption has become less expensive to implement more and more network traffic is encrypted. Currently, 90% of all network traffic is encrypted, and this trend is expected to increase. The creators of malware areemploying various methods to ensure delivery of their malware, including encryption. One proposed method to combat this suggests implementing machine learning with various algorithms to analyze packet attributes to determine if they contain malware, without actually knowing what's inside …

Developing A Web-Based System For Remote Collection And Analysis Of Vehicle Electrical Systems Over Canbus Using Carloop, Joshua N. Valle, Alex Columna-Fuentes

Capstone Showcase

Our program collects vehicle data using an OBD-II device called Carloop that is plugged into the vehicle's diagnostic port. The device executes our code which then communicates with the vehicle's onboard computer to collect data such as engine RPM, vehicle speed, fuel level, and other diagnostic information. This data is then sent over WiFi to Particle’s Cloud, which is a platform for managing IoT devices.

Integrations set up on Particle take care of sending data to our InfluxDB Database, which is hosted on our own cloud-based machine. InfluxDB is a high-performance time-series database that is optimized for storing and querying …

Bcse: Blockchain-Based Trusted Service Evaluation Model Over Big Data, Fengyin Li, Xinying Yu, Rui Ge, Yanli Wang, Yang Cui, Huiyu Zhou

Big Data Mining and Analytics

The blockchain, with its key characteristics of decentralization, persistence, anonymity, and auditability, has become a solution to overcome the overdependence and lack of trust for a traditional public key infrastructure on third-party institutions. Because of these characteristics, the blockchain is suitable for solving certain open problems in the service-oriented social network, where the unreliability of submitted reviews of service vendors can cause serious security problems. To solve the unreliability problems of submitted reviews, this paper first proposes a blockchain-based identity authentication scheme and a new trusted service evaluation model by introducing the scheme into a service evaluation model. The new …

Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu

Big Data Mining and Analytics

With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, …

Exploiting More Associations Between Slots For Multi-Domain Dialog State Tracking, Hui Bai, Yan Yang, Jie Wang

Big Data Mining and Analytics

Dialog State Tracking (DST) aims to extract the current state from the conversation and plays an important role in dialog systems. Existing methods usually predict the value of each slot independently and do not consider the correlations among slots, which will exacerbate the data sparsity problem because of the increased number of candidate values. In this paper, we propose a multi-domain DST model that integrates slot-relevant information. In particular, certain connections may exist among slots in different domains, and their corresponding values can be obtained through explicit or implicit reasoning. Therefore, we use the graph adjacency matrix to determine the …

Sampling With Prior Knowledge For High-Dimensional Gravitational Wave Data Analysis, He Wang, Zhoujian Cao, Yue Zhou, Zong-Kuan Guo, Zhixiang Ren

Big Data Mining and Analytics

Extracting knowledge from high-dimensional data has been notoriously difficult, primarily due to the so-called "curse of dimensionality" and the complex joint distributions of these dimensions. This is a particularly profound issue for high-dimensional gravitational wave data analysis where one requires to conduct Bayesian inference and estimate joint posterior distributions. In this study, we incorporate prior physical knowledge by sampling from desired interim distributions to develop the training dataset. Accordingly, the more relevant regions of the high-dimensional feature space are covered by additional data points, such that the model can learn the subtle but important details. We adapt the normalizing flow …

Toward Intelligent Financial Advisors For Identifying Potential Clients: A Multitask Perspective, Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu

Big Data Mining and Analytics

Intelligent Financial Advisors (IFAs) in online financial applications (apps) have brought new life to personal investment by providing appropriate and high-quality portfolios for users. In real-world scenarios, identifying potential clients is a crucial issue for IFAs, i.e., identifying users who are willing to purchase the portfolios. Thus, extracting useful information from various characteristics of users and further predicting their purchase inclination are urgent. However, two critical problems encountered in real practice make this prediction task challenging, i.e., sample selection bias and data sparsity. In this study, we formalize a potential conversion relationship, i.e., user→activated user→client and decompose this relationship into …

A Comparison Of Computational Approaches For Intron Retention Detection, Jiantao Zheng, Cuixiang Lin, Zhenpeng Wu, Hong-Dong Li

Big Data Mining and Analytics

Intron Retention (IR) is an alternative splicing mode through which introns are retained in mature RNAs rather than being spliced in most cases. IR has been gaining increasing attention in recent years because of its recognized association with gene expression regulation and complex diseases. Continuous efforts have been dedicated to the development of IR detection methods. These methods differ in their metrics to quantify retention propensity, performance to detect IR events, functional enrichment of detected IRs, and computational speed. A systematic experimental comparison would be valuable to the selection and use of existing methods. In this work, we conduct an …

Thinking On New System For Big Data Technology, Xueqi Chegn, Shenghua Liu, Ruqing Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, there are such significant improvements on the performance and efficiency of big data technology and system. As it is widely applied in various fields, big data has empowered industrial intelligence, and is the key step into the intelligent stage of information society. Therefore, we are facing greater challenges nowadays, such as the paradox of data flooding and high-value data lacking, the complexity and uncertainty of big data analysis, and the difficulty to balance the data on sharing and circulation, and trustworthiness and security. Moreover, these challenges will not only promote the innovation and change of big data …

Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher, Susan Mckeever, Ayman Taha, Jane Courtney

Datasets

Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the …

Technology Safety Audit In Computer Laboratories Using Iso/Iec 17799 : 2005 (Case Study: Ftk Uin Sunan Ampel Surabaya), Muqoffi Khosyatulloh, Nurul Fariidhotun Nisaa, Ilham, M. Kom

Library Philosophy and Practice (e-journal)

Management audit is very important for assessment of their information technology management to gain efficient and effective business running process. Information technology security as an effort of internal controlling for risk and threat security minimization, is mainly considered due to all learning and lecturing administration activities use information technology. Allso, the implementation of a number of computer labs to facilitate learning processes and access to information in order to support the lectures and personal development of students To find out how secure technology information is, it is then requiring an audit to make sure everything run based on procedure. Management …

Performance Of Lambda@Edge Vs. Lambda Environment, Sam Dotson, Wei Hao

Posters-at-the-Capitol

Abstract

The purpose of this research has been to observe how performance of the Lambda@EDGE environment compares to the base Lambda environment. This is in an effort to determine viability of the EDGE environment. 15 tests were conducted over a matter of days in each environment whereby the Fibonacci sequence was calculated to 20 terms. Performance metrics including RAM usage and response time were measured. Lambda@EDGE was determined to have not only a slightly higher average response time but also an average RAM usage of 1MB more in the aggregate tests.

Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala

Data

Corresponding data set for Tran-SET Project No. 18ITSLSU09. Abstract of the final report is stated below for reference:

"Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other drivers, …

Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey

Open Educational Resources

User-friendly Geographic Information Systems (GIS) is the common thread of this collection of presentations, and activities with full lesson plans. The first section of the site contains an overview of cartography, the art of creating maps, and then looks at historical mapping platforms like Hypercities and Donald Rumsey Historical Mapping Project. In the next section Google Earth Desktop Pro is introduced, with lessons and activities on the basics of GE such as pins, paths, and kml files, as well as a more complex activity on "georeferencing" an historic map over Google Earth imagery. The final section deals with ARCGIS Online …

Automated Segmentation Of Brain Ventricles Using 3d U-Net, Robert Sandor, Anish P. Dalal

Creative Activity and Research Day - CARD

Neuro-radiologists currently use qualitative volumetric change of brain ventricles after surgery to assess the safety of removing a ventriculoperitoneal (VP) shunt which is a medical device that relieves pressure on the brain caused by fluid accumulation. Following safe removal of the VP shunt, patients can be released from the hospital. The need for accurate and quick measurement of brain ventricular volumetric change makes automatic 3D segmentation software an ideal candidate to aid decisions after surgery. In this paper, we propose an approach to estimate the ventricular volume variation using segmentation in brain MRI and CT images. Our approach consists of …

Computational Thinking And Literacy, Sharin Rawhiya Jacob, Mark Warschauer

Journal of Computer Science Integration

Today’s students will enter a workforce that is powerfully shaped by computing. To be successful in a changing economy, students must learn to think algorithmically and computationally, to solve problems with varying levels of abstraction. These computational thinking skills have become so integrated into social function as to represent fundamental literacies. However, computer science has not been widely taught in K-12 schools. Efforts to create computer science standards and frameworks have yet to make their way into mandated course requirements. Despite a plethora of research on digital literacies, research on the role of computational thinking in the literature is sparse. …

Software Updates To A Multiple Autonomous Quadcopter Search System (Maqss), Jared Speck, Toby Chan

Computer Engineering

A series of performance-based and feature implementation software updates to an existing multiple vehicle autonomous target search system is outlined in this paper. The search system, MAQSS, is designed to address a computational power constraint found on modern autonomous aerial platforms by separating real-time and computationally expensive tasks through delegation to multiple multirotor vehicles. A Ground Control Station (GCS) is also described as part of the MAQSS system to perform the delegation and provide a low workload user interface. Ultimately, the changes to MAQSS noted in this paper helped to improve the performance of the autonomous search mission, the accuracy …

When Machines Decide: Justice.Exe Learning Modules, Praxis Lab Team

Law School Historical Documents

Learning modules for the Praxis Lab Honors Course

Implementing Software Lab At Hackathons, Istvan Gates

Williams Honors College, Honors Research Projects

Hackathons are events where groups of college students have 24 hours to build up a any project, using Computer Science and Electrical Engineering skillsets. These events are typically hosted on college campuses, and attract over 200 students per event. Each student brings 2 devices - their phone, and their laptop. That means that 400 devices are connected to a University venue's Internet network, commonly overloading it. Software Lab alleviates this overloading by providing an abstracted NAS node network for events. Software Lab guarantees speeds of at least 100 mbits/s, and provides a 8-10x improvement on download speeds over the common …

Robostock: Autonomous Inventory Tracking, Drew Christian Balthazor

Computer Engineering

No abstract provided.

Red Piston (Roborodentia), Gabriel Lee Hernandez, Davie Sy

Computer Science and Software Engineering

Roborodentia is an annual robotics competition held during Cal Poly’s Open House showcase. Teams of one to three people come together to build an autonomous robot to typically collect rings for points. The specifications of the competition will be detailed in the problem statement. For Roborodentia 2016, we built a machine dubbed Red Piston to tackle on this year’s competition. The following report will detail the design process and implementation of our robot.

Slaps Music Sharing App, Maximillian L. Parelius

Computer Engineering

Slaps is a fun way to share new songs with friends. Users can simply select songs from their personal library of music, select a short sample of the song to share, and then select which friends to share it with. If a user loves a song that he/she receives, they can link directly to iTunes through the app to download the full song.

Panorama: Multi-Path Ssl Authentication Using Peer Network Perspectives, William P. Harris

Computer Engineering

SSL currently uses certificates signed by Certificate Authorities (CAs) to authenticate connections. e.g. Google will pay a CA to sign a certificate for them, so that they can prove that they're not someone pretending to be Google. Unfortunately, this system has had multiple problems, and many believe that an alternative needs to be found.

One of the ideas for alternatives is using multiple "network perspectives" to authenticate a server. The idea behind this is that, though playing man-in-the-middle (MITM) with one connection is easy, it should be difficult for an adversary to do so with many connections, especially if they …

Growing Grounds Inventory Senior Project Application, Javier Balandran

Computer Engineering

No abstract provided.

Ghosts Of The Horseshoe, Heidi Rae Cooley, Richard Walker, Duncan Buell

Digital Projects

Ghosts of the Horseshoe (Ghosts) is a mobile interactive application that endeavors to bring into view--literally, on mobile micro screens (iPads and iPhones at present)--the largely unknown history of slavery at South Carolina College. It deploys game mechanics (i.e., ludic methods), as well as Augmented Reality (AR) and GPS functionality to generate awareness of and questioning about what otherwise seems ordinary: a grassy space at the center of a university campus. It organizes content into distinct but overlapping themes: (1) architectural ghosts (e.g., razed outbuildings); (2) human ghosts (e.g., un/named enslaved persons); and (3) the historic Wall delimiting the Horseshoe …

Forecast For The Future: Emerging Legal Technologies, Carol A. Watson

Continuing Legal Education Presentations

Begins by discussing technologies that are currently available on the web that can reduce office overhead. Also highlights current general technology trends and still-developing technologies. Concludes with a list of frivolous gadgets to provide food for thought about the coming prospects of technology.