Computer Engineering Commons^™

Blockchain Based Efficient And Robust Fair Payment For Outsourcing Services In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng

Research Collection School Of Computing and Information Systems

As an attractive business model of cloud computing, outsourcing services usually involve online payment and security issues. The mutual distrust between users and outsourcing service providers may severely impede the wide adoption of cloud computing. Nevertheless, most existing payment solutions only consider a specific type of outsourcing service and rely on a trusted third-party to realize fairness. In this paper, in order to realize secure and fair payment of outsourcing services in general without relying on any third-party, trusted or not, we introduce BCPay, a blockchain based fair payment framework for outsourcing services in cloud computing. We first present the …

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, …

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 …

Retrieval Of Infotainment System Artifacts From Vehicles Using Ive, Celia J. Whelan, John Sammons, Brian Mcmanus, Terry W. Fenger

Journal of Applied Digital Evidence

The analysis of mobile devices and hard drives has been the focus of the digital forensics world for years, but there is another source of potential evidence not often considered: vehicles. Many of today’s “connected cars” have systems that function like computers, storing information they process including user data from devices synced to the system. There has been little to no research done regarding what types of user artifacts can be found on the system, how long these artifacts remain, whether or not the user can remove those artifacts, and whether certain systems provide more information than others. For this …

Privacy-Preserving Mining Of Association Rule On Outsourced Cloud Data From Multiple Parties, Lin Liu, Jinshu Su, Rongmao Chen, Ximeng Liu, Xiaofeng Wang, Shuhui Chen, Ho-Fung Fung Leung

Research Collection School Of Computing and Information Systems

It has been widely recognized as a challenge to carry out data analysis and meanwhile preserve its privacy in the cloud. In this work, we mainly focus on a well-known data analysis approach namely association rule mining. We found that the data privacy in this mining approach have not been well considered so far. To address this problem, we propose a scheme for privacy-preserving association rule mining on outsourced cloud data which are uploaded from multiple parties in a twin-cloud architecture. In particular, we mainly consider the scenario where the data owners and miners have different encryption keys that are …

Network Traffic Time Series Performance Analysisusing Statistical Methods, Purnawansyah Purnawansyah, Haviluddin Haviluddin, Rayner Alfred, Achmad Fanany Onnlita Gaffar

Knowledge Engineering and Data Science

This paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential smoothing techniques were used additive and multiplicative model. Then, ARIMA based-on Box-Jenkins methodology. The results of ARIMA (1,0,2) was shown the best model that can be used to the internet network traffic forecasting

Decision Support System Determination Of Main Work Unitin Wpp-711 Using Fuzzy Topsis, Hozairi Hozairi, Yaser Krisnafi

Knowledge Engineering and Data Science

Decision-making to determine the working units for being prioritized to be developed in order to improve fishery monitoring in WPP-711 is imperative. The Ministry of Maritime Affairs and Fisheries should make no mismatch decision-making through long-term calculation and analysis. The problem of determining the priority of working units is a complex problem, thus it is required to find an appropriate method to avoid a mismatch decision. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a decision-making method capable of solving multi-criteria problems. TOPSIS working principle determines the alternative by considering the shortest distance from the positive …

Market Basket Analysis To Identify Customer Behaviorsby Way Of Transaction Data, Fachrul Kurniawan, Binti Umayah, Jihad Hammad, Supeno Mardi Susiki Nugroho, Mochammad Hariadi

Knowledge Engineering and Data Science

Transaction data is a set of recording data result in connections with sales-purchase activities at a particular company. In these recent years, transaction data have been prevalently used as research objects in means of discovering new information. One of the possible attempts is to design an application that can be used to analyze the existing transaction data. That application has the quality of market basket analysis. In addition, the application is designed to be desktop-based whose components are able to process as well as re-log the existing transaction data. The used method in designing this application is by way of …

Capital Letter Pattern Recognition In Text To Speechby Way Of Perceptron Algorithm, Novan Wijaya

Knowledge Engineering and Data Science

Computer vision is a data transformation retrieved or generated from webcam into another form in means of determining decision. All kinds of transformations are carried through to attain specific aims. One of the supporting techniques in implementing computer vision on a system is digital image processing as the objective of digital image processing is to transform digital-formatted picture so that it can be processed in computer. Computer vision and digital image processing can be implemented in a system of capital letter introduction and real-time handwriting reading on a whiteboard supported by artificial neural network mode “perceptron algorithm” used as a …

Sql Logic Error Detection Using Start End Mid Algorithm, Jevri Tri Ardiansyah, Aji Prasetya Wibawa, Triyanna Widiyaningtyas, Okazaki Yasuhisa

Knowledge Engineering and Data Science

Database is an important part of a system and it stores data to be manipulated. SQL (Structured Query Language) is used for manipulating those data to extract information and make decision. There are two types of error which make SQL is challenging to learn, namely syntax error and logic error. Compiler can detect syntax error, but it does not show error warning while logical error occurred. It makes logic error more difficult to understand than syntax error. A web based SQL compiler with errors detection ability by using Start End Mid algorithm is then developed, To help database's user to …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …

Investigating On Through Glass Via Based Rf Passives For 3-D Integration, Libo Qian, Jifei Sang, Yinshui Xia, Jian Wang, Peiyi Zhao

Mathematics, Physics, and Computer Science Faculty Articles and Research

Due to low dielectric loss and low cost, glass is developed as a promising material for advanced interposers in 2.5-D and 3-D integration. In this paper, through glass vias (TGVs) are used to implement inductors for minimal footprint and large quality factor. Based on the proposed physical structure, the impact of various process and design parameters on the electrical characteristics of TGV inductors is investigated with 3-D electromagnetic simulator HFSS. It is observed that TGV inductors have identical inductance and larger quality factor in comparison with their through silicon via counterparts. Using TGV inductors and parallel plate capacitors, a compact …

Genetic Algorithm Amplifier Biasing System (Gaabs): Genetic Algorithm For Biasing On Differential Analog Amplifiers, Sean Whalen

Computer Engineering

Genetic Algorithm Amplifier Biasing System (GAABS) - Senior Project Analysis

Summary of Functional Requirements

This project integrates LTSpice with a python script that runs a genetic algorithm to bias a differential amplifier. The system biases the amplifier with 2 different voltages, the base voltage for the PNP BJTs of the active loads and a voltage controlling the current of the current sink. The project runs via a python script, gets data from LTSpice’s command line call, and iteratively runs until the system is biased to achieve the greatest gain on an arbitrary input voltage.

Primary Constraints

Some of the main …

Delegation Application, Erik Matthew Phillips

Computer Science and Software Engineering

Delegation is a cross-platform application to provide smart task distribution to users. In a team environment, the assignment of tasks can be tedious and difficult for management or for users needing to discover a starting place for where to begin with accomplishing tasks. Within a specific team, members possess individual skills within different areas of the team’s responsibilities and specialties, and certain members will be better suited to tackle specific tasks. This project provides a solution, consisting of a smart cross-platform application that allows for teams and individuals to quickly coordinate and delegate tasks assigned to them.

Microgrid Protection Student Laboratory: Human-Machine Interface And Scada Database, Nathan P. Martinez

Electrical Engineering

The electric utility system, a ubiquitous and fundamental component of modern life, has changed more in the last 20 years than the last 100. With more homes and businesses installing distributed energy resources (DERs) such as solar panels, battery storage, and other intermittent sources, massive changes need to take place in the electric transmission and distribution systems. Engineers must develop a new skill set for a modern utility industry. This project summarizes a component for a new laboratory class aimed at power engineering students at Cal Poly which supports the laboratory through the creation of a human-machine interface (HMI) and …

Laser-Scribed Graphene Micro-Supercapacitors, Kimi D. Owens

Maseeh Summer Undergraduate Research Experience

M. F. El-Kady and R. B. Kaner, “Scalable fabrication of high-power graphene micro-supercapacitors for flexible and on-chip energy storage,” Nature Communications, vol. 4, p. 1475, Feb. 2013.

Supercapacitors are electrical components that have higher energy density than regular capacitors. Currently, they are large and bulky which makes it hard to be implemented into smaller electronic devices or on-chip. In Scalable Fabrication of High-power Graphene Micro-supercapacitors for Flexible and On-chip Energy Storage, El-Kady and Kaner developed an inexpensive and reliable method for scaling down supercapacitors to be approximately 7.53 x 5.35 mm. To make the laser-scribed graphene (LSG) micro-supercapacitors, an aqueous …

Combining Algorithms For More General Ai, Mark Robert Musil

Maseeh Summer Undergraduate Research Experience

Two decades since the first convolutional neural network was introduced the AI sub-domains of classification, regression and prediction still rely heavily on a few ML architectures despite their flaws of being hungry for data, time, and high-end hardware while still lacking generality. In order to achieve more general intelligence that can perform one-shot learning, create internal representations, and recognize subtle patterns it is necessary to look for new ML system frameworks. Research on the interface between neuroscience and computational statistics/machine learning has suggested that combined algorithms may increase AI robustness in the same way that separate brain regions specialize. In …

An Embarrassment Of Riches: Data Integration In Vr Pompeii, Adam Schoelz

Computer Science and Computer Engineering Undergraduate Honors Theses

It is fair to say that Pompeii is the most studied archaeological site in the world. Beyond the extensive remains of the city itself, the timing of its rediscovery and excavation place it in a unique historiographical position. The city has been continuously studied since the 18th century, with historians and archaeologists constantly reevaluating older sources as our knowledge of the ancient world expands. While several studies have approached the city from a data driven perspective, no studies of the city have taken a quantitative holistic approach on the scale of the VR Pompeii project. Hyper-specificity has been the order …

An Empirical Study On The Recovery Speed Of Usb Flash Drives Utilizing Raid-5 Compared To Hdds And Ssds, Joshua Manuel Martins

Honors Theses

Since their creation and implementation, storage drives have undergone and continue to undergo drastic changes in speed, size, and reliability. The original storage drives, known as hard disk drives (HDDs), are constructed using moving parts. The second modern type of storage drives, known as solid state drives (SSDs), are constructed using a series of silicon chips that utilize no moving parts. The third and most recent innovation in storage drives, known as USB flash drives (USBs), use only a single silicon chip to provide storage which grants them the smallest form factor of the three drive types.

This study compared …

Library Awesome Sauce Undergraduate Research, Jeremy Evert, Phillip Joe Fitzsimmons, Hector Lucas

Faculty Articles & Research

Library Awesome Sauce Undergraduate Research was a presentation at the 2018 CADRE Conference in Stillwater, OK. The presenters discussed their collaboration on a video project to film interviews of students giving progress reports about their software engineering projects. The videos were posted on the institutional repository.

The speakers discussed Student-Led research and the role that academic libraries play in facilitating student and faculty research and publishing for all disciplines on campus.

Early Alert Of At-Risk Students: An Ontology-Driven Framework, Elias S. Lopez

Electrical and Computer Engineering ETDs

As higher education continues to adapt to the constantly shifting conditions that society places on institutions, the enigma of student attrition continues to trouble universities. Early alerts for students who are at-risk academically have been introduced as a method for solving student attrition at these institutions. Early alert systems are designed to provide students who are academically at-risk a prompt indication so that they may correct their performance and make progress towards successful semester completion. Many early alert systems have been introduced and implemented at various institutions with varying levels of success. Currently, early alert systems employ different techniques for …

Strategic Implications Of Blockchain, William R. Adams

Undergraduate Honors Theses

This thesis introduces blockchain, the underlying technology of cryptocurrencies such as Bitcoin, and discusses how best to conceptualize it relative to other technologies. Following an explanation of the fundamentals of blockchain, also known as the distributed ledger, I identify the characteristics of the technology. Building upon blockchain’s inherent strengths and limitations, I explore potential business applications of blockchain. Finally, I recommend that leaders continue to track the development and adoption of blockchain technology, even if they decide that implementing it does not align with their organization’s strategy at present.

Image Processing Applications In Real Life: 2d Fragmented Image And Document Reassembly And Frequency Division Multiplexed Imaging, Houman Kamran Habibkhani

LSU Doctoral Dissertations

In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied.

In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the …

Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo

Research Collection School Of Computing and Information Systems

We present a new type of public-key encryption called Criteria-based Encryption (or , for short). Different from Attribute-based Encryption, in , we consider the access policies as criteria carrying different weights. A user must hold some cases (or answers) satisfying the criteria and have sufficient weights in order to successfully decrypt a message. We then propose two Schemes under different settings: the first scheme requires a user to have at least one case for a criterion specified by the encryptor in the access structure, while the second scheme requires a user to have all the cases for each criterion. We …

Continuous Top-K Monitoring On Document Streams (Extended Abstract), Leong Hou U, Junjie Zhang, Kyriakos Mouratidis, Ye Li

Research Collection School Of Computing and Information Systems

The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user preferences are indicated by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. The objective is to support large numbers of users and high stream rates, while refreshing the topk results almost instantaneously. Our solution abandons the traditional frequency-ordered indexing approach, …

Assured Android Execution Environments, Brandon P. Froberg

Theses and Dissertations

Current cybersecurity best practices, techniques, tactics and procedures are insufficient to ensure the protection of Android systems. Software tools leveraging formal methods use mathematical means to assure both a design and implementation for a system and these methods can be used to provide security assurances. The goal of this research is to determine methods of assuring isolation when executing Android software in a contained environment. Specifically, this research demonstrates security properties relevant to Android software containers can be formally captured and validated, and that an implementation can be formally verified to satisfy a corresponding specification. A three-stage methodology called "The …

Digital Forensics Event Graph Reconstruction, Daniel J. Schelkoph

Theses and Dissertations

Ontological data representation and data normalization can provide a structured way to correlate digital artifacts. This can reduce the amount of data that a forensics examiner needs to process in order to understand the sequence of events that happened on the system. However, ontology processing suffers from large disk consumption and a high computational cost. This paper presents Property Graph Event Reconstruction (PGER), a novel data normalization and event correlation system that leverages a native graph database to improve the speed of queries common in ontological data. PGER reduces the processing time of event correlation grammars and maintains accuracy over …

Assessment Of Structure From Motion For Reconnaissance Augmentation And Bandwidth Usage Reduction, Jonathan B. Roeber

Theses and Dissertations

Modern militaries rely upon remote image sensors for real-time intelligence. A typical remote system consists of an unmanned aerial vehicle, or UAV, with an attached camera. A video stream is sent from the UAV, through a bandwidth-constrained satellite connection, to an intelligence processing unit. In this research, an upgrade to this method of collection is proposed. A set of synthetic images of a scene captured by a UAV in a virtual environment is sent to a pipeline of computer vision algorithms, collectively known as Structure from Motion. The output of Structure from Motion, a three-dimensional model, is then assessed in …

Skylux Smartphone Controlled Skylight, James A. Green Vi

Computer Engineering

There are numerous electric skylight openers available for purchase for home-use, but the majority of them are remote based, or operated by a wall-unit. Furthermore, these devices are in hard to reach places, so if one were to lose the remote on a remote operated system, the only option is to contact the manufacturer for a new device. As such, my senior project, in collaboration with Colton Sundstrom’s senior project, build upon our existing capstone project in order to allow operation of the Internet of Things (IoT) device over the internet. Our client, Richard Murray, was unsatisfied with the current …

Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz Khan, Nirmalya Roy, Archan Misra

Research Collection School Of Computing and Information Systems

We investigate the problem of making human activityrecognition (AR) scalable–i.e., allowing AR classifiers trainedin one context to be readily adapted to a different contextualdomain. This is important because AR technologies can achievehigh accuracy if the classifiers are trained for a specific individualor device, but show significant degradation when the sameclassifier is applied context–e.g., to a different device located ata different on-body position. To allow such adaptation withoutrequiring the onerous step of collecting large volumes of labeledtraining data in the target domain, we proposed a transductivetransfer learning model that is specifically tuned to the propertiesof convolutional neural networks (CNNs). Our model, …