Engineering Commons^™

Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection, Debrup Banerjee

Electrical & Computer Engineering Theses & Dissertations

Recognition of emotional state and diagnosis of trauma related illnesses such as posttraumatic stress disorder (PTSD) using speech signals have been active research topics over the past decade. A typical emotion recognition system consists of three components: speech segmentation, feature extraction and emotion identification. Various speech features have been developed for emotional state recognition which can be divided into three categories, namely, excitation, vocal tract and prosodic. However, the capabilities of different feature categories and advanced machine learning techniques have not been fully explored for emotion recognition and PTSD diagnosis. For PTSD assessment, clinical diagnosis through structured interviews is a …

Itsblue: A Distributed Bluetooth-Based Framework For Intelligent Transportation Systems, Ahmed Awad Alghamdi

Computer Science Theses & Dissertations

Inefficiency in transportation networks is having an expanding impact, at a variety of levels. Transportation authorities expect increases in delay hours and in fuel consumption and, consequently, the total cost of congestion. Nowadays, Intelligent Transportation Systems (ITS) have become a necessity in order to alleviate the expensive consequences of the rapid demand on transportation networks. Since the middle of last century, ITS have played a significant role in road safety and comfort enhancements. However, the majority of state of the art ITS are suffering from several drawbacks, among them high deployment costs and complexity of maintenance.

Over the last decade, …

Motion Planning For Simple Two-Wheeled Robots, Ronald I. Greenberg, Jeffery M. Karp

Computer Science: Faculty Publications and Other Works

This paper considers various simple ways of navigating in a 2-dimensianal territory with a two-wheeled robot of a type typical in educational robotics. We determine shortest paths under various modes of operation and compare.

Cyber Foraging: Fifteen Years Later, Rajesh Krishna Balan, Jason Flinn

Research Collection School Of Computing and Information Systems

Revisiting Mahadev Satyanarayanan's original vision of cyber foraging and reflecting on the last 15 years of related research, the authors discuss the major accomplishments achieved as well as remaining challenges. They also look to current and future applications that could provide compelling application scenarios for making cyber foraging a widely deployed technology. This article is part of a special issue on pervasive computing revisited.

Discovering Newsworthy Themes From Sequenced Data: A Step Towards Computational Journalism, Qi Fan, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan Tan

Research Collection School Of Computing and Information Systems

Automatic discovery of newsworthy themes from sequenced data can relieve journalists from manually poring over a large amount of data in order to find interesting news. In this paper, we propose a novel k -Sketch query that aims to find k striking streaks to best summarize a subject. Our scoring function takes into account streak strikingness and streak coverage at the same time. We study the k -Sketch query processing in both offline and online scenarios, and propose various streak-level pruning techniques to find striking candidates. Among those candidates, we then develop approximate methods to discover the k most representative …

Ict Adoption And Use In Tanzania Smes, Cuthbert Msuya

Tanzania Journal of Engineering and Technology (TJET)

The purpose of this paper was to establish the status of ICTs adoption and use in Tanzania SMEs. Previously, it was shown that there is a shortage of comprehensive, accurate and up to date data on many aspects of the SMEs sector including the level of ICT adoption and use. This has affected government efforts aimed at development of this important sector in the economic development of the country. Results show that: (i) By year 2014, adoption of ICTs in SMEs had grown from almost non-existence in year 2004 to 80.1% computer technology use, and over 56.6% for use of …

Pedagogical Resources For Industrial Control Systems Security: Design, Implementation, Conveyance, And Evaluation, Guillermo A. Francia Iii, Greg Randall, Jay Snellen

Journal of Cybersecurity Education, Research and Practice

Industrial Control Systems (ICS), which are pervasive in our nation’s critical infrastructures, are becoming increasingly at risk and vulnerable to internal and external threats. It is imperative that the future workforce be educated and trained on the security of such systems. However, it is equally important that careful and deliberate considerations must be exercised in designing and implementing the educational and training activities that pertain to ICS. To that end, we designed and implemented pedagogical materials and tools to facilitate the teaching and learning processes in the area of ICS security. In this paper, we describe those resources, the professional …

Insights Into The Binding Mode Of Mek Type-Iii Inhibitors. A Step Towards Discovering And Designing Allosteric Kinase Inhibitors Across The Human Kinome, Zheng Zhao, Lei Xie, Philip E. Bourne

Publications and Research

Protein kinases are critical drug targets for treating a large variety of human diseases. Type- III kinase inhibitors have attracted increasing attention as highly selective therapeutics. Thus, understanding the binding mechanism of existing type-III kinase inhibitors provides useful insights into designing new type-III kinase inhibitors. In this work, we have systematically studied the binding mode of MEK-targeted type-III inhibitors using structural systems pharmacology and molecular dynamics simulation. Our studies provide detailed sequence, structure, interaction-fingerprint, pharmacophore and binding-site information on the binding characteristics of MEK type-III kinase inhibitors. We hypothesize that the helix-folding activation loop is a hallmark allosteric binding site …

Intuitive Error Space Exploration Of Medical Image Data In Clinical Daily Routine, Christina Gillmann, Pablo Arbeláez, José Tiberio Hernández Peñaloza, Hans Hagen, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Medical image data can be affected by several image errors. These errors can lead to uncertain or wrong diagnosis in clinical daily routine. A large variety of image error metrics are available that target different aspects of image quality forming a highdimensional error space, which cannot be reviewed trivially. To solve this problem, this paper presents a novel error space exploration technique that is suitable for clinical daily routine. Therefore, the clinical workflow for reviewing medical data is extended by error space cluster information, that can be explored by user-defined selections. The presented tool was applied to two real-world datasets …

Data Analysis And Processing Techniques For Remaining Useful Life Estimations, John Scott Bucknam

Theses and Dissertations

In the field of engineering, it is important to understand different engineering systems and components, not only in how they currently perform, but also how their performance degrades over time. This extends to the field of prognostics, which attempts to predict the future of a system or component based on its past and present states. A common problem in this field is the estimation of remaining useful life, or how long a system or component functionality will last. The well-known datasets for this problem are the PHM and C-MAPSS datasets. These datasets contain simulated sensor data for different turbofan engines …

Recommending Personalized Schedules In Urban Environments, Cen Chen

Dissertations and Theses Collection

In this thesis, we are broadly interested in solving real world problems that involve decision support for coordinating agent movements in dynamic urban environments, where people are agents exhibiting different human behavior patterns and preferences. The rapid development of mobile technologies makes it easier to capture agent behavioral and preference information. Such rich agent specific information, coupled with the explosive growth of computational power, opens many opportunities that we could potentially leverage, to better guide/influence the agents in urban environments. The purpose of this thesis is to investigate how we can effectively and efficiently guide and coordinate the agents with …

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto

Computer Engineering

The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.

Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler

Research Collection School Of Computing and Information Systems

The PART-WHOLE relationship routinely finds itself in many disciplines, ranging from collaborative teams, crowdsourcing, autonomous systems to networked systems. From the algorithmic perspective, the existing work has primarily focused on predicting the outcomes of the whole and parts, by either separate models or linear joint models, which assume the outcome of the parts has a linear and independent effect on the outcome of the whole. In this paper, we propose a joint predictive method named PAROLE to simultaneously and mutually predict the part and whole outcomes. The proposed method offers two distinct advantages over the existing work. First (Model Generality), …

Geometry-Based Mass Grading Of Mango Fruits Using Image Processing, M. A. Momin, Md Towfiqur Rahman, M. S. Sultana, C. Igathinathane, A. T. M. Ziauddin, T. E. Grift

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mango (Mangifera indica) is an important, and popular fruit in Bangladesh. However, the post-harvest processing of it is still mostly performed manually, a situation far from satisfactory, in terms of accuracy and throughput. To automate the grading of mangos (geometry and shape), we developed an image acquisition and processing system to extract projected area, perimeter, and roundness features. In this system, images were acquired using a XGA format color camera of 8-bit gray levels using fluorescent lighting. An image processing algorithm based on region based global thresholding color binarization, combined with median filter and morphological analysis was developed …

Scalable And Fully Distributed Localization In Large-Scale Sensor Networks, Miao Jin, Su Xia, Hongyi Wu, Xianfeng David Gu

Electrical & Computer Engineering Faculty Publications

This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of …

Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian

Research Collection School Of Computing and Information Systems

Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of web APIs that can be used to implement the project. At its heart, WebAPIRec employs …

Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele

Research Collection School Of Computing and Information Systems

Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor …

Sap: Improving Continuous Top-K Queries Over Streaming Data, Rui Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng, Guoren Wang

Research Collection School Of Computing and Information Systems

Continuous top-k query over streaming data is a fundamental problem in database. In this paper, we focus on the sliding window scenario, where a continuous top-k query returns the top-k objects within each query window on the data stream. Existing algorithms support this type of queries via incrementally maintaining a subset of objects in the window and try to retrieve the answer from this subset as much as possible whenever the window slides. However, since all the existing algorithms are sensitive to query parameters and data distribution, they all suffer from expensive incremental maintenance cost. In this paper, we propose …

Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The rapid emergence of head-mounted devices such as the Microsoft Holo-lens enables a wide variety of continuous vision applications. Such applications often adopt deep-learning algorithms such as CNN and RNN to extract rich contextual information from the first-person-view video streams. Despite the high accuracy, use of deep learning algorithms in mobile devices raises critical challenges, i.e., high processing latency and power consumption. In this paper, we propose DeepMon, a mobile deep learning inference system to run a variety of deep learning inferences purely on a mobile device in a fast and energy-efficient manner. For this, we designed a suite of …

Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Deep learning has revolutionized vision sensing applications in terms of accuracy comparing to other techniques. Its breakthrough comes from the ability to extract complex high level features directly from sensor data. However, deep learning models are still yet to be natively supported on mobile devices due to high computational requirements. In this paper, we present DeepMon, a next generation of DeepSense [1] framework, to enable deep learning models on conventional mobile devices (e.g. Samsung Galaxy S7) for continuous vision sensing applications. Firstly, Deep-Mon exploits similarity between consecutive video frames for intermediate data caching within models to enhance inference latency. Secondly, …

An Improved Algorithm For Learning To Perform Exception-Tolerant Abduction, Mengxue Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Abstract

Inference from an observed or hypothesized condition to a plausible cause or explanation for this condition is known as abduction. For many tasks, the acquisition of the necessary knowledge by machine learning has been widely found to be highly effective. However, the semantics of learned knowledge are weaker than the usual classical semantics, and this necessitates new formulations of many tasks. We focus on a recently introduced formulation of the abductive inference task that is thus adapted to the semantics of machine learning. A key problem is that we cannot expect that our causes or explanations will be perfect, …

Understanding Deleted File Decay On Removable Media Using Differential Analysis, James H. Jones Jr, Anurag Srivastava, Josh Mosier, Connor Anderson, Seth Buenafe

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital content created by picture recording devices is often stored internally on the source device, on either embedded or removable media. Such storage media is typically limited in capacity and meant primarily for interim storage of the most recent image files, and these devices are frequently configured to delete older files as necessary to make room for new files. When investigations involve such devices and media, it is sometimes these older deleted files that would be of interest. It is an established fact that deleted file content may persist in part or in its entirety after deletion, and identifying the …

Harnessing Predictive Models For Assisting Network Forensic Investigations Of Dns Tunnels, Irvin Homem, Panagiotis Papapetrou

Annual ADFSL Conference on Digital Forensics, Security and Law

In recent times, DNS tunneling techniques have been used for malicious purposes, however network security mechanisms struggle to detect them. Network forensic analysis has been proven effective, but is slow and effort intensive as Network Forensics Analysis Tools struggle to deal with undocumented or new network tunneling techniques. In this paper, we present a machine learning approach, based on feature subsets of network traffic evidence, to aid forensic analysis through automating the inference of protocols carried within DNS tunneling techniques. We explore four network protocols, namely, HTTP, HTTPS, FTP, and POP3. Three features are extracted from the DNS tunneled traffic: …

An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.

Adaptive Region-Based Approaches For Cellular Segmentation Of Bright-Field Microscopy Images, Hady Ahmady Phoulady

USF Tampa Graduate Theses and Dissertations

Microscopy image processing is an emerging and quickly growing field in medical imaging research area. Recent advancements in technology including higher computation power, larger and cheaper storage modules, and more efficient and faster data acquisition devices such as whole-slide imaging scanners contributed to the recent microscopy image processing research advancement. Most of the methods in this research area either focus on automatically process images and make it easier for pathologists to direct their focus on the important regions in the image, or they aim to automate the whole job of experts including processing and classifying images or tissues that leads …

Inferring Motion Direction Using Commodity Wi-Fi For Interactive Exergames, Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Yang Zheng, Yunhao Liu

Research Collection School Of Computing and Information Systems

In-air interaction acts as a key enabler for ambient intelligence and augmented reality. As an increasing popular example, exergames, and the alike gesture recognition applications, have attracted extensive research in designing accurate, pervasive and low-cost user interfaces. Recent advances in wireless sensing show promise for a ubiquitous gesture-based interaction interface with Wi-Fi. In this work, we extract complete information of motion-induced Doppler shifts with only commodity Wi-Fi. The key insight is to harness antenna diversity to carefully eliminate random phase shifts while retaining relevant Doppler shifts. We further correlate Doppler shifts with motion directions, and propose a light-weight pipeline to …

Lightweight Data Aggregation Scheme Against Internal Attackers In Smart Grid Using Elliptic Curve Cryptography, Debiao He, Sherali Zeadally, Huaqun Wang, Qin Liu

Information Science Faculty Publications

Recent advances of Internet and microelectronics technologies have led to the concept of smart grid which has been a widespread concern for industry, governments, and academia. The openness of communications in the smart grid environment makes the system vulnerable to different types of attacks. The implementation of secure communication and the protection of consumers’ privacy have become challenging issues. The data aggregation scheme is an important technique for preserving consumers’ privacy because it can stop the leakage of a specific consumer’s data. To satisfy the security requirements of practical applications, a lot of data aggregation schemes were presented over the …

A Robotics Framework For Simulation And Control Of A Robotic Arm For Use In Higher Education, Craig Christensen

MS in Computer Science Project Reports

Robotic arms have been in common use for a several decades now in many areas from manufacturing and industrial uses to hobby projects and amusement park rides. However, there have been very few attempts to make an inexpensive robot arm with a software stack for use in higher education. This paper will outline a control and interfacing software stack built on the Robot Operating System (ROS) and a simulation of the 5 degree of freedom (DoF) robotic arm.

Toward Measuring Network Aesthetics Based On Symmetry, Zengqiang Chen, Matthias Dehmer, Frank Emmert-Streib, Abbe Mowshowitz, Yongtang Shi

Publications and Research

In this exploratory paper, we discuss quantitative graph-theoretical measures of network aesthetics. Related work in this area has typically focused on geometrical features (e.g., line crossings or edge bendiness) of drawings or visual representations of graphs which purportedly affect an observer’s perception. Here we take a very different approach, abandoning reliance on geometrical properties, and apply information-theoretic measures to abstract graphs and networks directly (rather than to their visual representaions) as a means of capturing classical appreciation of structural symmetry. Examples are used solely to motivate the approach to measurement, and to elucidate our symmetry-based mathematical theory of network aesthetics.

College Of Engineering Senior Design Competition Spring 2017, University Of Nevada, Las Vegas

Fred and Harriet Cox Senior Design Competition Projects

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the projects on …