Computer Engineering Commons^™

Spam Elimination And Bias Correction : Ensuring Label Quality In Crowdsourced Tasks., Lingyu Lyu

Electronic Theses and Dissertations

Crowdsourcing is proposed as a powerful mechanism for accomplishing large scale tasks via anonymous workers online. It has been demonstrated as an effective and important approach for collecting labeled data in application domains which require human intelligence, such as image labeling, video annotation, natural language processing, etc. Despite the promises, one big challenge still exists in crowdsourcing systems: the difficulty of controlling the quality of crowds. The workers usually have diverse education levels, personal preferences, and motivations, leading to unknown work performance while completing a crowdsourced task. Among them, some are reliable, and some might provide noisy feedback. It is …

Autonomous Discovery And Maintenance Of Mobile Frees-Space-Optical Links, Mahmudur Khan

Electronic Theses and Dissertations

Free-Space-Optical (FSO) communication has the potential to play a significant role in future generation wireless networks. It is advantageous in terms of improved spectrum utilization, higher data transfer rate, and lower probability of interception from unwanted sources. FSO communication can provide optical-level wireless communication speeds and can also help solve the wireless capacity problem experienced by the traditional RF-based technologies. Despite these advantages, communications using FSO transceivers require establishment and maintenance of line-of-sight (LOS). We consider autonomous mobile nodes (Unmanned Ground Vehicles or Unmanned Aerial Vehicles), each with one FSO transceiver mounted on a movable head capable of scanning in …

Security Services Using Blockchains: A State Of The Art Survey, Maeda Zolanvari, Aiman Erbad, Raj Jain, Mohammed Samaka

All Computer Science and Engineering Research

This article surveys blockchain-based approaches for several security services. These services include authentication, confidentiality, privacy and access control list (ACL), data and resource provenance, and integrity assurance. All these services are critical for the current distributed applications, especially due to the large amount of data being processed over the networks and the use of cloud computing. Authentication ensures that the user is who he/she claims to be. Confidentiality guarantees that data cannot be read by unauthorized users. Privacy provides the users the ability to control who can access their data. Provenance allows an efficient tracking of the data and resources …

Enginews, August 2018, School Of Computer Science & Engineering

News, Magazines and Reports

A Summer of Collaboration: MakerSpace students.

A Practical Incremental Learning Framework For Sparse Entity Extraction, Hussein Al-Olimat, Steven Gustafson, Jason Mackay, Krishnaprasad Thirunarayan, Amit Sheth

Publications

This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to reduce the annotation cost of sparse data and provide an online evaluation method as feedback. This incremental and interactive learning framework allows for rapid annotation and subsequent extraction of sparse data while maintaining high accuracy. We evaluate our framework on three publicly available datasets and show that it drastically reduces the cost of sparse entity …

Machine Learning For Internet Of Things Data Analysis: A Survey, Mohammad Saeid Mahdavinejad, Mohammadreza Rezvan, Mohammadamin Barekatain, Peyman Adibi, Payam Barnaghi, Amit Sheth

Publications

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the …

Split Latency Allocator: Process Variation-Aware Register Access Latency Boost In A Near-Threshold Graphics Processing Unit, Asmita Pal

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Over the last decade, Graphics Processing Units (GPUs) have been used extensively in gaming consoles, mobile phones, workstations and data centers, as they have exhibited immense performance improvement over CPUs, in graphics intensive applications. Due to their highly parallel architecture, general purpose GPUs (GPGPUs) have gained the foreground in applications where large data blocks can be processed in parallel. However, the performance improvement is constrained by a large power consumption. Likewise, Near Threshold Computing (NTC) has emerged as an energy-efficient design paradigm. Hence, operating GPUs at NTC seems like a plausible solution to counteract the high energy consumption. This work …

Scaling Up An Infrastructure For Controlled Experimentation With Testing Techniques, Wayne D. Motycka

School of Computing: Dissertations, Theses, and Student Research

Software testing research often involves reproducing previous experimental results. Previous work created a repository infrastructure for containment and dissemination of testable research subjects using a private centralized storage mechanism for hosting these test subject archives. While this is a good way to store these subjects it can be inefficient when the size of subjects increases or the number of versions of the subject’s source code is large. The delivery of these large subjects from a centralized repository can be quite large and on occasion may not succeed requiring the user to repeat the download request. Coupled with the limited resources …

Secure Device And Knowledge Discovery In Internet Of Things, Shahab Taregh Tayeb

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the ever-growing adoption of Internet of Things (IoT), there is continued development and deployment of new nodes with various capabilities and services. Such heterogeneity introduces complexity and a significant need for neighbor service discovery frameworks. Because the types of services available are orders of magnitude more than pre-IoT era, researchers need new techniques to accurately discover not only the topologies and adjacencies but also the capability of other nodes and neighbors. Device discovery is usually the first task to be performed, immediately after deployment, as it enables communications, scheduling, and channel estimation. The existing discovery mechanisms do not consider …

Efficacy Of Multi-Threshold Null Convention Logic In Low-Power Applications, Brent Bell

Graduate Theses and Dissertations

In order for an asynchronous design paradigm such as Multi-Threshold NULL Convention Logic (MTNCL) to be adopted by industry, it is important for circuit designers to be aware of its advantages and drawbacks especially with respect to power usage. The power tradeoff between MTNCL and synchronous designs depends on many different factors including design type, circuit size, process node, and pipeline granularity. Each of these design dimensions influences the active power and the leakage power comparisons. This dissertation analyzes the effects of different design dimensions on power consumption and the associated rational for these effects. Results show that while MTNCL …

Micron/Nano Structure Creation Through Dual Pulse Femtosecond Laser Surface Processing, Nicholas Roth

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new technique has been developed for creating multiscale micro/nanoscale surfaces on metals. This technique is based on past work in femtosecond laser surface processing (FLSP) and dual pulse laser induced breakdown spectroscopy (LIBS). Using a femtosecond laser, pulse pairs were created with varying pulse separations between 0 ps to 500 ps. The creation of surface structures with dual pulse FLSP was studied on Ag, Cu, Ti, Al, Ni, and 304 stainless steel in relation to pulse separation.

Using dual pulse FLSP micro/nano structures have been created for the first time on silver. The silver structures are multiscale in nature …

Learning Representations Of Ultrahigh-Dimensional Data For Random Distance-Based Outlier Detection, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu

Research Collection School Of Computing and Information Systems

Learning expressive low-dimensional representations of ultrahigh-dimensional data, e.g., data with thousands/millions of features, has been a major way to enable learning methods to address the curse of dimensionality. However, existing unsupervised representation learning methods mainly focus on preserving the data regularity information and learning the representations independently of subsequent outlier detection methods, which can result in suboptimal and unstable performance of detecting irregularities (i.e., outliers).This paper introduces a ranking model-based framework, called RAMODO, to address this issue. RAMODO unifies representation learning and outlier detection to learn low-dimensional representations that are tailored for a state-of-the-art outlier detection approach - the random …

Exact Processing Of Uncertain Top-K Queries In Multi-Criteria Settings, Kyriakos Mouratidis, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently uncertain due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we introduce the uncertain top-k query (UTK). Given uncertain preferences, that is, …

Apple Flower Detection Using Deep Convolutional Networks, Philipe A. Dias, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

To optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Several automated computer vision systems have been proposed to estimate bloom intensity, but their overall performance is still far from satisfactory even in relatively controlled environments. With the goal of devising a technique for flower identification which is robust to clutter and to changes in illumination, this paper presents a method in which a pre-trained convolutional neural network …

Code Smells For Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Marco Aurélio Gerosa, Arie Van Deursen

Research Collection School Of Computing and Information Systems

Previous studies have shown the negative effects that low-quality code can have on maintainability proxies, such as code change- and defect-proneness. One of the symptoms of low-quality code are code smells, defined as sub-optimal implementation choices. While this definition is quite general and seems to suggest a wide spectrum of smells that can affect software systems, the research literature mostly focuses on the set of smells defined in the catalog by Fowler and Beck, reporting design issues that can potentially affect any kind of system, regardless of their architecture (e.g., Complex Class). However, systems adopting a specific architecture (e.g., the …

Customer Segmentation Using Online Platforms: Isolating Behavioral And Demographic Segments For Persona Creation Via Aggregated User Data, Jisun An, Haewoon Kwak, Soon‑Gyo Jung, Joni Salminen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer …

The Singularity May Be Near, Roman V. Yampolskiy

Faculty and Staff Scholarship

Toby Walsh in "The Singularity May Never Be Near" gives six arguments to support his point of view that technological singularity may happen, but that it is unlikely. In this paper, we provide analysis of each one of his arguments and arrive at similar conclusions, but with more weight given to the "likely to happen" prediction.

Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A radiation detection and identification system is designed and implemented to perform gamma ray spectroscopy on radioactive sources and identify which isotopes are present in the sources. A multichannel analyzer is implemented on an ASIC to process the signal produced from gamma rays detected by a scintillator and photomultiplier tube and to quantize the gamma ray energies to build a histogram. A fast, low memory embedded neural network is implemented on a microcontroller ASIC to identify the isotopes present in the gamma ray histogram produced by the multichannel analyzer in real time.

Advisors: Sina Balkir and Michael W. Hoffman

Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan

Electrical and Computer Engineering Faculty Publications

A framework for designing orthogonal chaotic phase-coded waveforms with space-time complementary coding (STCC) is proposed for multiple-input multiple-output (MIMO) radar applications. The phase-coded waveform set to be transmitted is generated with an arbitrary family size and an arbitrary code length by using chaotic sequences. Due to the properties of chaos, this chaotic waveform set has many advantages in performance, such as anti-interference and low probability of intercept. However, it cannot be directly exploited due to the high range sidelobes, mutual interferences, and Doppler intolerance. In order to widely implement it in practice, we optimize the chaotic phase-coded waveform set from …

An Application Of Game Theory In Distributed Collaborative Decision Making, Angran Xiao

Publications and Research

In a distributed product realization environment, new paradigms and accompanying software systems are necessary to support the collaborative work of geographically dispersed engineering teams from different disciplines who have different knowledge, experience, tools and resources. To verify the concept of collaboration by separation, we propose a generic information communication medium to enable knowledge representation and exchange between engineering teams, a digital interface. Across digital interfaces, each engineering team maintains its own perspective towards the product realization problem, and each controls a subset of design variables and seeks to maximize its own payoff function subject to individual constraints. Hence, we postulate …