Engineering Commons^™

Using Freebase, An Automatically Generated Dictionary, And A Classifier To Identify A Person's Profession In Tweets, Abraham Hall

Electronic Theses and Dissertations

Algorithms for classifying pre-tagged person entities in tweets into one of eight profession categories are presented. A classifier using a semi-supervised learning algorithm that takes into consideration the local context surrounding the entity in the tweet, hash tag information, and topic signature scores is described. In addition to the classifier, this research investigates two dictionaries containing the professions of persons. These two dictionaries are used in their own classification algorithms which are independent of the classifier. The method for creating the first dictionary dynamically from the web and the algorithm that accesses this dictionary to classify a person into one …

Automatically Acquiring A Semantic Network Of Related Concepts, Sean Szumlanski

Electronic Theses and Dissertations

We describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to automatically disambiguate them to their corresponding WordNet noun senses (i.e., concepts). The resultant concept-to-concept associations, stemming from 7,593 target nouns, with 17,104 distinct senses among them, constitute a large-scale semantic …

Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In this paper, we seek robust policies for uncertain Markov Decision Processes (MDPs). Most robust optimization approaches for these problems have focussed on the computation of maximin policies which maximize the value corresponding to the worst realization of the uncertainty. Recent work has proposed minimax regret as a suitable alternative to the maximin objective for robust optimization. However, existing algorithms for handling minimax regret are restricted to models with uncertainty over rewards only. We provide algorithms that employ sampling to improve across multiple dimensions: (a) Handle uncertainties over both transition and reward models; (b) Dependence of model uncertainties across state, …

Current-Mode Quadrature Oscillator Based On Cccdtas With Noninteractive Dual-Current Control For Both Condition Of Oscillation And Frequency Of Oscillation, Adirek Jantakun, Winai Jaikla

Turkish Journal of Electrical Engineering and Computer Sciences

The realization of 2 current-mode quadrature oscillators using current-controlled current differencing transconductance amplifiers (CCCDTAs) and grounded capacitors is presented. The proposed oscillators can provide 2 sinusoidal output currents with a 90° phase difference. They enable noninteractive dual-current control for both the condition of oscillation and the frequency ofi oscillation. The high-output impedances of the configurations enable the circuit to be cascaded without additional current buffers. The use of only grounded capacitors is ideal for integration. The circuit performances are depicted through PSpice simulations; they show good agreement to theoretical anticipation.

Ssr Mitigation With Sssc Thanks To Fuzzy Control, Seyed Mohammad Hassan Hosseini, Hadi Samadzadeh, Javad Olamaei, Murtaza Farsadi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper deals with the capability of a static synchronous series compensator (SSSC) to attenuate the subsynchronous resonance (SSR). Two well-known controllers are designed, namely a conventional damping controller (CDC) and fuzzy logic damping controller (FLDC). These 2 damping controllers are added to a main control loop of a SSSC operating as a SSR damping controller. It should be noted that, to optimize the parameters of the CDC, a versatile optimization technique is implemented, namely particle swarm optimization (PSO). A comprehensive comparison between the 2 control methods is carried out for different operational conditions. To observe the superior performance of …

Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts

Theses and Dissertations--Computer Science

I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.

Information Security Challenge Of Qr Codes, Nik Thompson, Kevin Lee

Journal of Digital Forensics, Security and Law

The discipline of information security must adapt to new technologies and methods of interaction with those technologies. New technologies present both challenges and opportunities for the security professional, especially for areas such as digital forensics. Challenges can be in the form of new devices such as smartphones or new methods of sharing information, such as social networks. One such rapidly emerging interaction technology is the use of Quick Response (QR) codes. These offer a physical mechanism for quick access to Web sites for advertising and social interaction. This paper argues that the common implementation of QR codes potentially presents security …

Measuring Inconsistency Methods For Evidentiary Value, Fred Cohen

Journal of Digital Forensics, Security and Law

Many inconsistency analysis methods may be used to detect altered records or statements. But for admission as evidence, the reliability of the method has to be determined and measured. For example, in China, for evidence to be admitted, it has to have 95% certainty of being correct,1 and that certainty must be shown to the court, while in the US, evidence is admitted if it is more probative than prejudicial (a >50% standard).2 In either case, it is necessary to provide a measurement of some sort in order to pass muster under challenges from the other side. And in most …

Technology Corner Visualising Forensic Data: Evidence (Part 1), Damian Schofield, Ken Fowle

Journal of Digital Forensics, Security and Law

Visualisation is becoming increasingly important for understanding information, such as investigative data (for example: computing, medical and crime scene evidence) and analysis (for example: network capability assessment, data file reconstruction and planning scenarios). Investigative data visualisation is used to reconstruct a scene or item and is used to assist the viewer (who may well be a member of the general public with little or no understanding of the subject matter) to understand what is being presented. Analysis visualisations, on the other hand, are usually developed to review data, information and assess competing scenario hypotheses for those who usually have an …

How Often Is Employee Anger An Insider Risk I? Detecting And Measuring Negative Sentiment Versus Insider Risk In Digital Communications, Eric Shaw, Maria Payri, Michael Cohn, Ilene R. Shaw

Journal of Digital Forensics, Security and Law

This research introduced two new scales for the identification and measurement of negative sentiment and insider risk in communications in order to examine the unexplored relationship between these two constructs. The inter-rater reliability and criterion validity of the Scale of Negativity in Texts (SNIT) and the Scale of Insider Risk in Digital Communications (SIRDC) were established with a random sample of email from the Enron archive and criterion measures from established insiders, disgruntled employees, suicidal, depressed, angry, anxious, and other sampled groups. In addition, the sensitivity of the scales to changes over time as the risk of digital attack increased …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Technology Corner: Visualising Forensic Data: Evidence Guidelines (Part 2), Damian Schofield, Ken Fowle

Journal of Digital Forensics, Security and Law

Visualisation is becoming increasingly important for understanding information, such as investigative data (for example: computing, medical and crime scene evidence) and analysis (for example, network capability assessment, data file reconstruction and planning scenarios). Investigative data visualisation is used to reconstruct a scene or item and is used to assist the viewer (who may well be a member of the general public with little or no understanding of the subject matter) to understand what is being presented. Analysis visualisations, on the other hand, are usually developed to review data, information and assess competing scenario hypotheses for those who usually have an …

How Often Is Employee Anger An Insider Risk Ii? Detecting And Measuring Negative Sentiment Versus Insider Risk In Digital Communications–Comparison Between Human Raters And Psycholinguistic Software, Eric Shaw, Maria Payri, Michael Cohn, Ilene R. Shaw

Journal of Digital Forensics, Security and Law

This research uses two recently introduced observer rating scales, (Shaw et al., 2013) for the identification and measurement of negative sentiment (the Scale for Negativity in Text or SNIT) and insider risk (Scale of Indicators of Risk in Digital Communication or SIRDC) in communications to test the performance of psycholinguistic software designed to detect indicators of these risk factors. The psycholinguistic software program, WarmTouch (WT), previously used for investigations, appeared to be an effective means for locating communications scored High or Medium in negative sentiment by the SNIT or High in insider risk by the SIRDC within a randomly selected …

Trends In Android Malware Detection, Kaveh Shaerpour, Ali Dehghantanha, Ramlan Mahmod

Journal of Digital Forensics, Security and Law

This paper analyzes different Android malware detection techniques from several research papers, some of these techniques are novel while others bring a new perspective to the research work done in the past. The techniques are of various kinds ranging from detection using host based frameworks and static analysis of executable to feature extraction and behavioral patterns. Each paper is reviewed extensively and the core features of each technique are highlighted and contrasted with the others. The challenges faced during the development of such techniques are also discussed along with the future prospects for Android malware detection. The findings of the …

Risk Management Of Email And Internet Use In The Workplace, John Ruhnka, Windham E. Loopesko

Journal of Digital Forensics, Security and Law

The article surveys the changing risk environment for corporations from their employees’ electronic communications. It identifies the types of liabilities that corporations can incur from such employee communications. It discusses the objectives of corporate internet use policies and the types of provisions such policies should contain. It suggests an alternative risk-based approach to corporate acceptable use policies instead of a traditional “laundry list” of internet use prohibitions.

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Analysis Of A Second Hand Google Mini Search Appliance, Stephen Larson

Journal of Digital Forensics, Security and Law

Information and the technological advancements for which mankind develops with regards to its storage has increased tremendously over the past few decades. As the total amount of data stored rapidly increases in conjunction with the amount of widely available computer-driven devices being used, solutions are being developed to better harness this data (LaTulippe, 2011). One of these solutions is commonly known as a search appliance. Search appliances have been used in e-discovery for several years. The Google Mini Search Appliance (Mini) has not only been used for e-discovery, but for indexing and searching internal documents. To accomplish these tasks, search …

System-Generated Digital Forensic Evidence In Graphic Design Applications, Enos Mabuto, Hein Venter

Journal of Digital Forensics, Security and Law

Graphic design applications are often used for the editing and design of digital art. The same applications can be used for creating counterfeit documents such as identity documents (IDs), driver’s licences, passports, etc. However, the use of any graphic design application leaves behind traces of digital information that can be used during a digital forensic investigation. Current digital forensic tools examine a system to find digital evidence, but they do not examine a system specifically for the creating of counterfeit documents created through the use of graphic design applications. The paper in hand reviews the system-generated digital forensic evidence gathered …

Hyperspectral Image Classification Using A Spectral-Spatial Sparse Coding Model, Ender Oguslu, Guoqing Zhou, Jiang Li, Lorenzo Bruzzone (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based spectral-spatial classification model for hyperspectral image (HSI) datasets. The proposed method consists of an efficient sparse coding method in which the l₁/l_q regularized multi-class logistic regression technique was utilized to achieve a compact representation of hyperspectral image pixels for land cover classification. We applied the proposed algorithm to a HSI dataset collected at the Kennedy Space Center and compared our algorithm to a recently proposed method, Gaussian process maximum likelihood (GP-ML) classifier. Experimental results show that the proposed method can achieve significantly better performances than the GP-ML classifier when training data …

Unmanned Autonomous Object Retrieval: Old Dominion University 2013 International Aerial Robotics Competition Entry, Johnathan Bailey, Austin Boyd, Chung-Hao Chen, Stephen Dailey, Lisa Henderson, Jeremy Stuart, Christina Williams

Electrical & Computer Engineering Faculty Publications

This paper describes the design implementation of a Quadrotor Unmanned Aerial Vehicle (UAV) with the capability of exploring indoor locations without the assistance of external aids. For relative position, the use of a laser range sensor, an optical flow sensor, and sonar sensor combined allows for the vehicle to generate mapping information. With relative position in mind, the vehicle uses vision algorithms to recognize immediate obstacles, sign, and entry ways to allow for quick movement responses and object recognition. A proportional-integral-differentiator controller allows for flight stability and mitigation in the tight confines of the indoor spaces. A mapping algorithm allows …

Performance Evaluation And Comparison Of Distributed Messaging Using Message Oriented Middleware, Naveen Mupparaju

UNF Graduate Theses and Dissertations

Message Oriented Middleware (MOM) is an enabling technology for modern event- driven applications that are typically based on publish/subscribe communication [Eugster03]. Enterprises typically contain hundreds of applications operating in environments with diverse databases and operating systems. Integration of these applications is required to coordinate the business process. Unfortunately, this is no easy task. Enterprise Integration, according to Brosey et al. (2001), "aims to connect and combines people, processes, systems, and technologies to ensure that the right people and the right processes have the right information and the right resources at the right time"[Brosey01]. Communication between different applications can be achieved …

Orientation Invariant Ecg-Based Stethoscope Tracking For Heart Auscultation Training On Augmented Standardized Patients, Nahom Kidane, Salim Chemlal, Jiang Li, Frederic D. Mckenzie, Tom Hubbard

Computational Modeling & Simulation Engineering Faculty Publications

Auscultation, the act of listening to the heart and lung sounds, can reveal substantial information about patients’ health and other cardiac-related problems; therefore, competent training can be a key for accurate and reliable diagnosis. Standardized patients (SPs), who are healthy individuals trained to portray real patients, have been extensively used for such training and other medical teaching techniques; however, the range of symptoms and conditions they can simulate remains limited since they are only patient actors. In this work, we describe a novel tracking method for placing virtual symptoms in correct auscultation areas based on recorded ECG signals with various …

Integration Of Multispectral Face Recognition And Multi-Ptz Camera Automated Surveillance For Security Applications, Chung-Hao Chen, Yi Yao, Hong Chang, Andreas Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Due to increasing security concerns, a complete security system should consist of two major components, a computer-based face-recognition system and a real-time automated video surveillance system. A computer-based face-recognition system can be used in gate access control for identity authentication. In recent studies, multispectral imaging and fusion of multispectral narrow-band images in the visible spectrum have been employed and proven to enhance the recognition performance over conventional broad-band images, especially when the illumination changes. Thus, we present an automated method that specifies the optimal spectral ranges under the given illumination. Experimental results verify the consistent performance of our algorithm via …

A Large Scale Distributed Syntactic, Semantic And Lexical Language Model For Machine Translation, Ming Tan

Browse all Theses and Dissertations

The n-gram model is the most widely used language model (LM) in statistical machine translation system, due to its simplicity and scalability. However, it only encodes the local lexical relation between adjacent words and clearly ignores the rich syntactic and semantic structures of the natural languages. Attempting to increase the order of an n-gram to describe longer range dependencies in natural language immediately runs into the curse of dimensionality. Although previous researches tried to increase the order of n-gram on a large corpus, they did not see obvious improvement beyond 6-gram. Meanwhile, other LMs, such as syntactic language models and …

Visual Exploration And Information Analytics Of High-Dimensional Medical Images, Darshan Pai

Wayne State University Dissertations

Data visualization has transformed how we analyze increasingly large and complex data sets. Advanced visual tools logically represent data in a way that communicates the most important information inherent within it and culminate the analysis with an insightful conclusion. Automated analysis disciplines - such as data mining, machine learning, and statistics - have traditionally been the most dominant fields for data analysis. It has been complemented with a near-ubiquitous adoption of specialized hardware and software environments that handle the storage, retrieval, and pre- and postprocessing of digital data. The addition of interactive visualization tools allows an active human participant in …

Opacity Of Discrete Event Systems: Analysis And Control, Majed Mohamed Ben Kalefa

Wayne State University Dissertations

The exchange of sensitive information in many systems over a network can be manipulated

by unauthorized access. Opacity is a property to investigate security and

privacy problems in such systems. Opacity characterizes whether a secret information

of a system can be inferred by an unauthorized user. One approach to verify security

and privacy properties using opacity problem is to model the system that may leak confidential

information as a discrete event system. The problem that has not investigated

intensively is the enforcement of opacity properties by supervisory control. In other

words, constructing a minimally restrictive supervisor to limit the system's …

A Semantics-Based Approach To Machine Perception, Cory Andrew Henson

Browse all Theses and Dissertations

Machine perception can be formalized using semantic web technologies in order to derive abstractions from sensor data using background knowledge on the Web, and efficiently executed on resource-constrained devices. Advances in sensing technology hold the promise to revolutionize our ability to observe and understand the world around us. Yet the gap between observation and understanding is vast. As sensors are becoming more advanced and cost-effective, the result is an avalanche of data of high volume, velocity, and of varied type, leading to the problem of too much data and not enough knowledge (i.e., insights leading to actions). Current estimates predict …

A Methodology For Extracting Human Bodies From Still Images, Athanasios Tsitsoulis

Browse all Theses and Dissertations

Monitoring and surveillance of humans is one of the most prominent applications of today and it is expected to be part of many future aspects of our life, for safety reasons, assisted living and many others. Many efforts have been made towards automatic and robust solutions, but the general problem is very challenging and remains still open. In this PhD dissertation we examine the problem from many perspectives. First, we study the performance of a hardware architecture designed for large-scale surveillance systems. Then, we focus on the general problem of human activity recognition, present an extensive survey of methodologies that …

Anomalies In Sensor Network Deployments: Analysis, Modeling, And Detection, Giovani Rimon Abuaitah

Browse all Theses and Dissertations

A sensor network serves as a vital source for collecting raw sensory data. Sensor data are later processed, analyzed, visualized, and reasoned over with the help of several decision making tools. A decision making process can be disastrously misled by a small portion of anomalous sensor readings. Therefore, there has been a vast demand for mechanisms that identify and then eliminate such anomalies in order to ensure the quality, integrity, and/or trustworthiness of the raw sensory data before they can even be interpreted.

Prior to identifying anomalies, it is essential to understand the various anomalous behaviors prevalent in a sensor …

Cooperative Interactive Distributed Guidance On Mobile Devices, Gregory Burnett

Browse all Theses and Dissertations

Mobiles device are quickly becoming an indispensable part of our society. Equipped with numerous communication capabilities, they are increasingly being examined as potential tools for civilian and military usage to aide in distributed remote collaboration for dynamic decision making and physical task completion. With an ever growing mobile workforce, the need for remote assistance in aiding field workers who are confronted with situations outside their expertise certainly increases. Enhanced capabilities in using mobile devices could significantly improve numerous components of a task's completion (i.e. accuracy, timing, etc.). This dissertation considers the design of mobile implementation of technology and communication capabilities …