Computer Engineering Commons^™

Feature Extraction And Parallel Visualization For Large-Scale Scientific Data, Lina Yu

School of Computing: Dissertations, Theses, and Student Research

Advanced computing and sensing technologies enable scientists to study natural and physical phenomena with unprecedented precision, resulting in an explosive growth of data. The unprecedented amounts of data generated from large scientific simulations impose a grand challenge in data analytics and visualization due to the fact that data are too massive for transferring, storing, and processing.

This dissertation makes the first contribution to the design of novel transfer functions and application-aware data replacement policy to facilitate feature classification on highly parallel distributed systems. We design novel transfer functions that advance the classification of continuously changed volume data by combining the …

Can A Strictly Defined Security Configuration For Iot Devices Mitigate The Risk Of Exploitation By Botnet Malware?, David Kennefick

Dissertations

The internet that we know and use every day is the internet of people, a collection of knowledge and data that can be accessed anywhere is the world anytime from many devices. The internet of the future is the Internet of Things. The Internet of Things is a collection of automated technology that is designed to be run autonomously, but on devices designed for humans to use. In 2016 the Mirai malware has shown there are underlying vulnerabilities in devices connected to the internet of things. Mirai is specifically designed to recognise and exploit IoT devices and it has been …

An Analysis Of Predicting Job Titles Using Job Descriptions, John Lynch

Dissertations

A job title is an all-encompassing very short form description that conveys all of the pertinent information relating to a job. The job title typically encapsulates - and should encapsulate - the domain, role and level of responsibility of any given job. Significant value is attached to job titles both internally within organisational structures and to individual job holders. Organisations map out all employees in an organogram on the basis of job titles. This has a bearing on issues like salary, level and scale of responsibility, employee selection and so on. Employees draw value from their own job titles as …

Cybercrime: An Investigation Of The Attitudes And Environmental Factors That Make People More Willing To Participate In Online Crime, Dearbhail Kirwan

Dissertations

Cybercrime incidence rates are increasing. In order to identify solutions to this problem, the sources of cybercrime need to be identified. This research attempted to identify a potential set of circumstances that create an environment in which people are more likely to engage in cybercrime. There are three aspects to this; (1) Behaviour on the internet – Are people more likely to engage in illicit activities online than in the physical world? (2) Crime Perceptions – Do people perceive cybercrime as being less serious than non-cybercrime? (3) Resources on the Internet – Are people aware of the types of free …

“How Short Is A Piece Of String?”: An Investigation Into The Impact Of Text Length On Short-Text Classification Accuracy, Austin Mccartney

Dissertations

The recent increase in the widespread use of short messages, for example micro-blogs or SMS communications, has created an opportunity to harvest a vast amount of information through machine-based classification. However, traditional classification methods have failed to produce accuracies comparable to those obtained from similar classification of longer texts. Several approaches have been employed to extend traditional methods to overcome this problem, including the enhancement of the original texts through the construction of associations with external data enrichment sources, ranging from thesauri and semantic nets such as Wordnet, to pre-built online taxonomies such as Wikipedia. Other avenues of investigation have …

Personalized Microtopic Recommendation On Microblogs, Yang Li, Jing Jiang, Ting Liu, Minghui Qiu, Xiaofei Sun

Research Collection School Of Computing and Information Systems

Microblogging services such as Sina Weibo and Twitter allow users to create tags explicitly indicated by the # symbol. In Sina Weibo, these tags are called microtopics, and in Twitter, they are called hashtags. In Sina Weibo, each microtopic has a designate page and can be directly visited or commented on. Recommending these microtopics to users based on their interests can help users efficiently acquire information. However, it is non-trivial to recommend microtopics to users to satisfy their information needs. In this article, we investigate the task of personalized microtopic recommendation, which exhibits two challenges. First, users usually do not …

Comparing And Improving Facial Recognition Method, Brandon Luis Sierra

Electronic Theses, Projects, and Dissertations

Facial recognition is the process in which a sample face can be correctly identified by a machine amongst a group of different faces. With the never-ending need for improvement in the fields of security, surveillance, and identification, facial recognition is becoming increasingly important. Considering this importance, it is imperative that the correct faces are recognized and the error rate is as minimal as possible. Despite the wide variety of current methods for facial recognition, there is no clear cut best method. This project reviews and examines three different methods for facial recognition: Eigenfaces, Fisherfaces, and Local Binary Patterns to determine …

Natural Language Processing Based Generator Of Testing Instruments, Qianqian Wang

Electronic Theses, Projects, and Dissertations

Natural Language Processing (NLP) is the field of study that focuses on the interactions between human language and computers. By “natural language” we mean a language that is used for everyday communication by humans. Different from programming languages, natural languages are hard to be defined with accurate rules. NLP is developing rapidly and it has been widely used in different industries. Technologies based on NLP are becoming increasingly widespread, for example, Siri or Alexa are intelligent personal assistants using NLP build in an algorithm to communicate with people. “Natural Language Processing Based Generator of Testing Instruments” is a stand-alone program …

A Novel Privacy Preserving User Identification Approach For Network Traffic, Nathan Clarke, Fudong Li, Steven Furnell

Research outputs 2014 to 2021

The prevalence of the Internet and cloud-based applications, alongside the technological evolution of smartphones, tablets and smartwatches, has resulted in users relying upon network connectivity more than ever before. This results in an increasingly voluminous footprint with respect to the network traffic that is created as a consequence. For network forensic examiners, this traffic represents a vital source of independent evidence in an environment where anti-forensics is increasingly challenging the validity of computer-based forensics. Performing network forensics today largely focuses upon an analysis based upon the Internet Protocol (IP) address – as this is the only characteristic available. More typically, …

In Search Of Homo Sociologicus, Yunqi Xue

Dissertations, Theses, and Capstone Projects

The subject of this dissertation is to build an epistemic logic system that is able to show the spreading of knowledge and beliefs in a social network that contains multiple subgroups. Epistemic logic is the study of logical systems that express mathematical properties of knowledge and belief. In recent years, there have been increasing number of new epistemic logic systems that are focused on community properties such as knowledge and belief adoption among friends.

We are interested in revisable and actionable social knowledge/belief that leads to a large group action. Instead of centralized coordination, bottom-up approach is our focus. We …

Audiosense: Sound-Based Shopper Behavior Analysis System, Amit Sharma, Youngki Lee

Research Collection School Of Computing and Information Systems

This paper presents AudioSense, the system to monitor user-item interactions inside a store hence enabling precisely customized promotions. A shopper's smartwatch emits sound every time the shopper picks up or touches an item inside a store. This sound is then localized, in 2D space, by calculating the angles of arrival captured by multiple microphones deployed on the racks. Lastly, the 2D location is mapped to specific items on the rack based on the rack layout information. In our initial experiments conducted with a single rack with 16 compartments, we could localize the shopper's smartwatch with a median estimation error of …

Sugarmate: Non-Intrusive Blood Glucose Monitoring With Smartphones, Weixi Gu, Yuxun Zhou, Zimu Zhou, Xi Liu, Han Zou, Pei Zhang, Costas J. Spanos, Lin Zhang

Research Collection School Of Computing and Information Systems

Inferring abnormal glucose events such as hyperglycemia and hypoglycemia is crucial for the health of both diabetic patients and non-diabetic people. However, regular blood glucose monitoring can be invasive and inconvenient in everyday life. We present SugarMate, a first smartphone-based blood glucose inference system as a temporary alternative to continuous blood glucose monitors (CGM) when they are uncomfortable or inconvenient to wear. In addition to the records of food, drug and insulin intake, it leverages smartphone sensors to measure physical activities and sleep quality automatically. Provided with the imbalanced and often limited measurements, a challenge of SugarMate is the inference …

An Unsupervised Multilingual Approach For Online Social Media Topic Identification, Siaw Ling Lo, Raymond Chiong, David Cornforth

Research Collection School Of Computing and Information Systems

Social media data can be valuable in many ways. However, the vast amount of content shared and the linguistic variants of languages used on social media are making it very challenging for high-value topics to be identified. In this paper, we present an unsupervised multilingual approach for identifying highly relevant terms and topics from the mass of social media data. This approach combines term ranking, localised language analysis, unsupervised topic clustering and multilingual sentiment analysis to extract prominent topics through analysis of Twitter’s tweets from a period of time. It is observed that each of the ranking methods tested has …

Data Improving In Time Series Using Arx And Ann Models, Hermine Nathalie Akouemo Kengmo Kenfack, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Anomalous data can negatively impact energy forecasting by causing model parameters to be incorrectly estimated. This paper presents two approaches for the detection and imputation of anomalies in time series data. Autoregressive with exogenous inputs (ARX) and artificial neural network (ANN) models are used to extract the characteristics of time series. Anomalies are detected by performing hypothesis testing on the extrema of the residuals, and the anomalous data points are imputed using the ARX and ANN models. Because the anomalies affect the model coefficients, the data cleaning process is performed iteratively. The models are re-learned on “cleaner” data after an …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco

Libraries' Newsletters

No abstract provided.

Forensic State Acquisition From Internet Of Things (Fsaiot): A General Framework And Practical Approach For Iot Forensics Through Iot Device State Acquisition, Christopher S. Meffert, Devon R. Clark, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

IoT device forensics is a difficult problem given that manufactured IoT devices are not standardized, many store little to no historical data, and are always connected; making them extremely volatile. The goal of this paper was to address these challenges by presenting a primary account for a general framework and practical approach we term Forensic State Acquisition from Internet of Things (FSAIoT). We argue that by leveraging the acquisition of the state of IoT devices (e.g. if an IoT lock is open or locked), it becomes possible to paint a clear picture of events that have occurred. To this end, …

Bim+Blockchain: A Solution To The Trust Problem In Collaboration?, Malachy Mathews, Dan Robles, Brian Bowe

Conference papers

This paper provides an overview of historic and current organizational limitations emerging in the Architecture, Engineering, Construction, Building Owner / Operations (AECOO) Industry. It then provides an overview of new technologies that attempt to mitigate these limitations. However, these technologies, taken together, appear to be converging and creating entirely new organizational structures in the AEC industries. This may be characterized by the emergence of what is called the Network Effect and it’s related calculus. This paper culminates with an introduction to Blockchain Technology (BT) and it’s integration with the emergence of groundbreaking technologies such as Internet of Things (IoT), Artificial …

Research On Improving Navigation Safety Based On Big Data And Cloud Computing Technology For Qiongzhou Strait, Rui Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

The Future Is Coming : Research On Maritime Communication Technology For Realization Of Intelligent Ship And Its Impacts On Future Maritime Management, Jiacheng Ke

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Data-Driven Abstraction, Vivian Mankau Ho

LSU Master's Theses

Given a program analysis problem that consists of a program and a property of interest, we use a data-driven approach to automatically construct a sequence of abstractions that approach an ideal abstraction suitable for solving that problem. This process begins with an infinite concrete domain that maps to a finite abstract domain defined by statistical procedures resulting in a clustering mixture model. Given a set of properties expressed as formulas in a restricted and bounded variant of CTL, we can test the success of the abstraction with respect to a predefined performance level. In addition, we can perform iterative abstraction-refinement …

Parallel Computation Using Mems Oscillator-Based Computing System, Xinrui Wang, Ilias Bilionis, Salar Safarkhani

The Summer Undergraduate Research Fellowship (SURF) Symposium

In recent years, parallel computing systems such as artificial neural networks (ANNs) have been of great interest. In these systems which emulate the behavior of human brains, the processing is carried out simultaneously. However, it is still a challenging engineering problem to design highly efficient hardware for parallel computing systems. We will study the properties of networks of Microelectromechanical System (MEMS) oscillators to explore their capabilities as parallel computing infrastructure. Furthermore, we simulate the time-variant states of MEMS oscillators network under various initial conditions and performance of certain tasks. Recent theoretical results show that networks of MEMS oscillators have some …

Efficiently And Transparently Maintaining High Simd Occupancy In The Presence Of Wavefront Irregularity, Stephen V. Cole

McKelvey School of Engineering Graduate Student Theses & Dissertations

Demand is increasing for high throughput processing of irregular streaming applications; examples of such applications from scientific and engineering domains include biological sequence alignment, network packet filtering, automated face detection, and big graph algorithms. With wide SIMD, lightweight threads, and low-cost thread-context switching, wide-SIMD architectures such as GPUs allow considerable flexibility in the way application work is assigned to threads. However, irregular applications are challenging to map efficiently onto wide SIMD because data-dependent filtering or replication of items creates an unpredictable data wavefront of items ready for further processing. Straightforward implementations of irregular applications on a wide-SIMD architecture are prone …

Easier Parallel Programming With Provably-Efficient Runtime Schedulers, Robert Utterback

McKelvey School of Engineering Graduate Student Theses & Dissertations

Over the past decade processor manufacturers have pivoted from increasing uniprocessor performance to multicore architectures. However, utilizing this computational power has proved challenging for software developers. Many concurrency platforms and languages have emerged to address parallel programming challenges, yet writing correct and performant parallel code retains a reputation of being one of the hardest tasks a programmer can undertake.

This dissertation will study how runtime scheduling systems can be used to make parallel programming easier. We address the difficulty in writing parallel data structures, automatically finding shared memory bugs, and reproducing non-deterministic synchronization bugs. Each of the systems presented depends …

Parallel Real-Time Scheduling For Latency-Critical Applications, Jing Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

In order to provide safety guarantees or quality of service guarantees, many of today's systems consist of latency-critical applications, e.g. applications with timing constraints. The problem of scheduling multiple latency-critical jobs on a multiprocessor or multicore machine has been extensively studied for sequential (non-parallizable) jobs and different system models and different objectives have been considered. However, the computational requirement of a single job is still limited by the capacity of a single core. To provide increasingly complex functionalities of applications and to complete their higher computational demands within the same or even more stringent timing constraints, we must exploit the …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Systems Design Against Attacks: A Tri-Level Network Operation Model In Oil / Gas Production And Distribution, Mustafa Alassad

Theses and Dissertations

The oil and gas distribution networks are systems of external pipelines that are suffering from heterogeneous threats. Accordingly, hardening strategies against malicious attacks are discussed, where a tri-level leader-follower-operator game is established for determining the optimum fortification tactics to protect the critical assets considering the defender’s limited resources. In addition, the shared cognition concept is mathematically modeled by including defender’s deception. The resulted multi-origin(O)-destination(D) mixed integer nonlinear programming problem is decomposed into a master and sub-problem for illustrating the defender-operator and attacker-operator respectively. Furthermore, the bi-level sub-problem is successfully converted to a single level via duality theorem. In light of …

Improving Disciplinary Literacy In An Electronics Course, Ohbong Kwon, Juanita C. But, Sunghoon Jang

Publications and Research

Electronics (EMT1255) is a required course for the Associate Degree in Applied Science (AAS) in Electromechanical Engineering Technology (EMT) at New York City College of Technology. EMT1255 introduces semiconductor devices and their applications in electronic-circuits. Students are expected to understand the structures and principles of semiconductor devices and the configuration and principles of basic electronic circuits. They also learn to analyze and design electronic circuits. In the lab setting, they acquire troubleshooting knowledge and hands-on technical skills. In this reading intensive course, students need to read the lab manual and a textbook of over 700 pages. Therefore, reading and understanding …

Ani-Bot: A Mixed-Reality Ready Modular Robotics System, Zhuangying Xu, Yuanzhi Cao

The Summer Undergraduate Research Fellowship (SURF) Symposium

DIY modular robotics has always had a strong appeal to makers and designers; being able to quickly design, build, and animate their own robots opens the possibility of bringing imaginations to life. However, current interfaces to control and program the DIY robot either lacks connection and consistency between the users and target (Graphical User Interface) or suffers from limited control capabilities due to the lack of versatility and functionality (Tangible User interface). We present Ani-Bot, a modular robotics system that allows users to construct Do-It-Yourself (DIY) robots and use mixed-reality approach to interact with them instantly. Ani-Bot enables novel user …

Resource Estimation For Large Scale, Real-Time Image Analysis On Live Video Cameras Worldwide, Caleb Tung, Yung-Hsiang Lu, Anup Mohan

The Summer Undergraduate Research Fellowship (SURF) Symposium

Thousands of public cameras live-stream an abundance of data to the Internet every day. If analyzed in real-time by computer programs, these cameras could provide unprecedented utility as a global sensory tool. For example, if cameras capture the scene of a fire, a system running image analysis software on their footage in real-time could be programmed to react appropriately (perhaps call firefighters). No such technology has been deployed at large scale because the sheer computing resources needed have yet to be determined. In order to help us build computer systems powerful enough to achieve such lifesaving feats, we developed a …

Optimal Placement Of Intrusion Detection Systems To Identify Multi-Stage Attacks In Software Defined Networks, Rebecca S. Salo, Subramaniyam Kannan, Paul C. Wood

The Summer Undergraduate Research Fellowship (SURF) Symposium

A major threat to network security is the multi-stage attack, where an attacker compromises an outer edge server from which he penetrates an inner server, and so on, until he gains access to protected information deep in the network. Intrusion detection systems (IDS) can detect such attacks, but limited resources constrain the number of IDS deployed. Software defined networking (SDN) provides network flexibility, and combined with network function virtualization (NFV), it enables IDS placement optimizations that can relieve cost constraint pressures. In this work, we develop a novel algorithm for placing IDS to maximize network protection benefits and minimize costs. …