Engineering Commons^™

Tool Support For Reasoning In Display Calculi, Samuel Balco, Sabine Frittella, Giuseppe Greco, Alexander Kurz, Alessandra Palmigiano

Engineering Faculty Articles and Research

We present a tool for reasoning in and about propositional sequent calculi. One aim is to support reasoning in calculi that contain a hundred rules or more, so that even relatively small pen and paper derivations become tedious and error prone. As an example, we implement the display calculus D.EAK of dynamic epistemic logic. Second, we provide embeddings of the calculus in the theorem prover Isabelle for formalising proofs about D.EAK. As a case study we show that the solution of the muddy children puzzle is derivable for any number of muddy children. Third, there is a set of meta-tools, …

Combining Interval And Probabilistic Uncertainty In Engineering Applications, Andrew Martin Pownuk

Open Access Theses & Dissertations

In many practical application, we process measurement results and expert estimates. Measurements and expert estimates are never absolutely accurate, their result are slightly different from the actual (unknown) values of the corresponding quantities. It is therefore desirable to analyze how this measurement and estimation inaccuracy affects the results of data processing. There exist numerous methods for estimating the accuracy of the results of data processing under different models of measurement and estimation inaccuracies: probabilistic, interval, and fuzzy. To be useful in engineering applications, these methods should provide accurate estimate for the resulting uncertainty, should not take too much computation time, …

Ontology-Driven Integration Of Data For Freight Performance Measures, Eduardo J. Torres

Open Access Theses & Dissertations

Transportation performance measures are defined as quantitative and qualitative indicators that rely on data or information to explain mobility, congestion, safety, environmental and other factors. Though performance measures have been used for freeways and other highways, not many have been specified and applied to the freight transportation system. Recently, freight performance measures have been recommended by Federal Highway Administration to quantify the operating efficiency of the freight transportation system on existing infrastructures. This research seeks to expand this concept and to develop a comprehensive freight performance measurement framework. The expanded framework recommended in this Thesis consists of four criteria: safety, …

Creating Multi-Functional G-Code For Multi-Process Additive Manufacturing, Efrain Aguilera Jr

Open Access Theses & Dissertations

Additive manufacturing (AM) started over thirty years ago and with it a manufacturing revolution that moves industrial production into the personal home. With recent interest shifting into multi-functional parts fabricated through AM technologies, unified systems are being developed. Merging different manufacturing technologies into one single machine is a challenge but undergoing research has shown promise in the development of multi-functional systems. Concurrent work is being done in the software, automation, and hardware aspect of multi-functional systems. An effort to use industry compatible Computer Aided Design (CAD) software to design multi-functional parts including circuits, micro-machining, and foil embedding then exporting and …

Towards The Scalability And Hybrid Parallelization Of A Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez

Open Access Theses & Dissertations

The purpose of this research is to design a faster implementation of the spatially variant algorithm that improves its performance when it is running on a parallel computer system.

The spatially variant algorithm is used to synthesize a spatially variant lattice for a periodic electromagnetic structure. The algorithm has the ability to spatially vary the unit cell orientation and exploit its directional dependencies. The algorithm produces a lattice that is smooth, continuous and free of defects. The lattice spacing remains strikingly uniform when the unit cell orientation, lattice spacing, fill fraction and more are spatially varied. This is important for …

Design And Evaluation Of The Impact Of A Multi-Agent Control System (Framework) Applied To A Social Setting, Perez Antonio Perez

Open Access Theses & Dissertations

The objective of this research is to design and analyze the performance of a new mechanism to improve the advising of students in a nontraditional environment. This nontraditional environment includes: a minority serving, commuter campus with a high percentage of transfer students. Specifically, these demographics are unable to keep a tightly controlled cohort of students flowing through to the completion of the curriculum. Students in these circumstances usually have varied course loads and competing priorities due to family and financial needs or other societal responsibilities. Therefore, there is a need for an individualized approach to advising.

University administrations face challenges …

A Cloud-Based Framework For Smart Permit System For Buildings, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur

Faculty Publications

In this paper we propose a novel cloud-based platform for building permit system that is efficient, user-friendly, transparent, and has quick turn-around time for homeowners. Compared to the existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of a) the end user experience, by analyzing explicit and implicit user feedback, and b) the permitting and urban planning process, allowing a gleaning of key insights for real estate development and city planning purposes, by analyzing how users interact with the system depending on …

Pro-Fit: Exercise With Friends, Saumil Dharia, Vijesh Jain, Jvalant Patel, Jainikkumar Vora, Rizen Yamauchi, Magdalini Eirinaki, Iraklis Varlamis

Faculty Publications

The advancements in wearable technology, where embedded accelerometers, gyroscopes and other sensors enable the users to actively monitor their activity have made it easier for individuals to pursue a healthy lifestyle. However, most of the existing applications expect continuous commitment from the end users, who need to proactively interact with the application in order to connect with friends and attain their goals. These applications fail to engage and motivate users who have busy schedules, or are not as committed and self-motivated. In this work, we present PRO-Fit, a personalized fitness assistant application that employs machine learning and recommendation algorithms in …

Threshold-Bounded Influence Dominating Sets For Recommendations In Social Networks, Magdalini Eirinaki, Nuno Moniz, Katerina Potika

Faculty Publications

The process of decision making in humans involves a combination of the genuine information held by the individual, and the external influence from their social network connections. This helps individuals to make decisions or adopt behaviors, opinions or products. In this work, we seek to investigate under which conditions and with what cost we can form neighborhoods of influence within a social network, in order to assist individuals with little or no prior genuine information through a two-phase recommendation process. Most of the existing approaches regard the problem of identifying influentials as a long-term, network diffusion process, where information cascading …

Time-Based Ensembles For Prediction Of Rare Events In News Streams, Nuno Moniz, Luís Torgo, Magdalini Eirinaki

Faculty Publications

Thousands of news are published everyday reporting worldwide events. Most of these news obtain a low level of popularity and only a small set of events become highly popular in social media platforms. Predicting rare cases of highly popular news is not a trivial task due to shortcomings of standard learning approaches and evaluation metrics. So far, the standard task of predicting the popularity of news items has been tackled by either of two distinct strategies related to the publication time of news. The first strategy, a priori, is focused on predicting the popularity of news upon their publication when …

Positioning Commuters And Shoppers Through Sensing And Correlation, Rufeng Meng

Theses and Dissertations

Positioning is a basic and important need in many scenarios of human daily activities. With position information, multifarious services could be vitalized to benefit all kinds of users, from individuals to organizations. Through positioning, people are able to obtain not only geo-location but also time related information. By aggregating position information from individuals, organizations could derive statistical knowledge about group behaviors, such as traffic, business, event, etc.

Although enormous effort has been invested in positioning related academic and industrial work, there are still many holes to be filled. This dissertation proposes solutions to address the need of positioning in people’s …

Interest Detection In Image, Video And Multiple Videos: Model And Applications, Yuewei Lin

Theses and Dissertations

Interest detection is detecting an object, event, or process that draws attention. In this dissertation, we focus on interest detection in images, video and multiple videos. Interest detection in an image or a video is closely related to visual attention. However, the interest detection in multiple videos needs to consider all the videos as a whole rather than considering the attention in each single video independently.

Visual attention is an important mechanism of human vision. The computational model of visual attention has recently attracted a lot of interest in the computer vision community mainly because it helps find the objects …

Digital Forensics In Law Enforcement: A Needs Based Analysis Of Indiana Agencies, Teri A. Cummins Flory

Journal of Digital Forensics, Security and Law

Cyber crime is a growing problem, with the impact to society increasing exponentially, but the ability of local law enforcement agencies to investigate and successfully prosecute criminals for these crimes is unclear. Many national needs assessments have previously been conducted, and all indicated that state and local law enforcement did not have the training, tools, or staff to effectively conduct digital investigations, but very few have been completed recently. This study provided a current and localized assessment of the ability of Indiana law enforcement agencies to effectively investigate crimes involving digital evidence, the availability of training for both law enforcement …

Verification Of Recovered Digital Evidence On The Amazon Kindle, Marcus Thompson, Raymond Hansen

Journal of Digital Forensics, Security and Law

The Amazon Kindle is a popular e-book reader. This popularity will lead criminals to use the Kindle as an accessory to their crime. Very few Kindle publications in the digital forensics domain exist at the time of this writing. Various blogs on the Internet currently provide some of the foundation for Kindle forensics. For this research each fifth generation Kindle was populated with various types of files a typical user may introduce using one method, the USB interface. The Kindle was forensically imaged with AccessData’s Forensic Toolkit Imager before and after each Kindle was populated. Each file was deleted through …

Making Sense Of Email Addresses On Drives, Neil C. Rowe, Riqui Schwamm, Michael R. Mccarrin, Ralucca Gera

Journal of Digital Forensics, Security and Law

Drives found during investigations often have useful information in the form of email addresses which can be acquired by search in the raw drive data independent of the file system. Using this data we can build a picture of the social networks that a drive owner participated in, even perhaps better than investigating their online profiles maintained by social-networking services because drives contain much data that users have not approved for public display. However, many addresses found on drives are not forensically interesting, such as sales and support links. We developed a program to filter these out using a Naïve …

Countering Noise-Based Splicing Detection Using Noise Density Transfer, Thibault Julliand, Vincent Nozick, Hugues Talbot

Journal of Digital Forensics, Security and Law

Image splicing is a common and widespread type of manipulation, which is defined as pasting a portion of an image onto a second image. Several forensic methods have been developed to detect splicing, using various image properties. Some of these methods exploit the noise statistics of the image to try and find discrepancies. In this paper, we propose a new counter-forensic approach to eliminate the noise differences that can appear in a spliced image. This approach can also be used when creating computer graphics images, in order to endow them with a realistic noise. This is performed by changing the …

Evidential Reasoning For Forensic Readiness, Yi-Ching Liao, Hanno Langweg

Journal of Digital Forensics, Security and Law

To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Electronic Voting Service Using Block-Chain, Kibin Lee, Joshua I. James, Tekachew G. Ejeta, Hyoung J. Kim

Journal of Digital Forensics, Security and Law

Cryptocurrency, and its underlying technologies, has been gaining popularity for transaction management beyond financial transactions. Transaction information is maintained in the block-chain, which can be used to audit the integrity of the transaction. The focus on this paper is the potential availability of block-chain technology of other transactional uses. Block-chain is one of the most stable open ledgers that preserves transaction information, and is difficult to forge. Since the information stored in block-chain is not related to personally identify information, it has the characteristics of anonymity. Also, the block-chain allows for transparent transaction verification since all information in the block-chain …

Exploring Deviant Hacker Networks (Dhn) On Social Media Platforms, Samer Al-Kateeb, Kevin Conlan, Nitin Agarwal, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Online Social Networks (OSNs) have grown exponentially over the past decade. The initial use of social media for benign purposes (e.g., to socialize with friends, browse pictures and photographs, and communicate with family members overseas) has now transitioned to include malicious activities (e.g., cybercrime, cyberterrorism, and cyberwarfare). These nefarious uses of OSNs poses a signi_cant threat to society, and thus requires research attention. In this exploratory work, we study activities of one deviant groups: hacker groups on social media, which we term Deviant Hacker Networks (DHN). We investigated the connection between different DHNs on Twitter: how they are connected, identified …

Towards Syntactic Approximate Matching-A Pre-Processing Experiment, Doowon Jeong, Frank Breitinger, Hari Kang, Sangjin Lee

Electrical & Computer Engineering and Computer Science Faculty Publications

Over the past few years, the popularity of approximate matching algorithms (a.k.a. fuzzy hashing) has increased. Especially within the area of bytewise approximate matching, several algorithms were published, tested, and improved. It has been shown that these algorithms are powerful, however they are sometimes too precise for real world investigations. That is, even very small commonalities (e.g., in the header of a file) can cause a match. While this is a desired property, it may also lead to unwanted results. In this paper, we show that by using simple pre-processing, we significantly can influence the outcome. Although our test set …

Find Me If You Can: Mobile Gps Mapping Applications Forensic Analysis & Snavp The Open Source, Modular, Extensible Parser, Jason Moore, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

The use of smartphones as navigation devices has become more prevalent. The ubiquity of hand-held navigation devices such as Garmins or Toms Toms has been falling whereas the ownership of smartphones and their adoption as GPS devices is growing. This work provides a comprehensive study of the most popular smartphone mapping applications, namely Google Maps, Apple Maps, Waze, MapQuest, Bing, and Scout, on both Android and iOS. It details what data was found, where it was found, and how it was acquired for each application. Based on the findings, the work allowed for the construction of a tool capable of …

3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall

Maseeh Summer Undergraduate Research Experience

Physical size limitations in miniaturizing two-dimensional (2D) transistors are becoming more difficult to overcome. In order to continue increasing the processing power of electronic circuits, new design paradigms are needed. Three-dimensional (3D) architectures provide a solution to this issue and are currently being implemented via wafer stacking. However, more significant gains in terms of packing and speed can be achieved by CMOS components with truly integrated 3D cellular architectures. One of these is the Cell Matrix, a self-configurable defect- and fault-tolerant architecture, which is ideally suited for ultra large-scale integration. For this project, we worked to expand the Cell Matrix …

Detecting, Segmenting And Tracking Bio-Medical Objects, Mingzhong Li

Doctoral Dissertations

"Studying the behavior patterns of biomedical objects helps scientists understand the underlying mechanisms. With computer vision techniques, automated monitoring can be implemented for efficient and effective analysis in biomedical studies. Promising applications have been carried out in various research topics, including insect group monitoring, malignant cell detection and segmentation, human organ segmentation and nano-particle tracking.

In general, applications of computer vision techniques in monitoring biomedical objects include the following stages: detection, segmentation and tracking. Challenges in each stage will potentially lead to unsatisfactory results of automated monitoring. These challenges include different foreground-background contrast, fast motion blur, clutter, object overlap and …

Flexc: Protein Flexibility Prediction Using Context-Based Statistics, Predicted Structural Features, And Sequence Information, Ashraf Yaseen, Mais Nijim, Brandon Williams, Lei Qian, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan

Research Collection School Of Computing and Information Systems

We espouse a vision of small data-based immersive retail analytics, where a combination of sensor data, from personal wearable-devices and store-deployed sensors & IoT devices, is used to create real-time, individualized services for in-store shoppers. Key challenges include (a) appropriate joint mining of sensor & wearable data to capture a shopper’s product level interactions, and (b) judicious triggering of power-hungry wearable sensors (e.g., camera) to capture only relevant portions of a shopper’s in-store activities. To explore the feasibility of our vision, we conducted experiments with 5 smartwatch-wearing users who interacted with objects placed on cupboard racks in our lab (to …

Leveraging Heritrix And The Wayback Machine On A Corporate Intranet: A Case Study On Improving Corporate Archives, Justin F. Brunelle, Krista Ferrante, Eliot Wilczek, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

In this work, we present a case study in which we investigate using open-source, web-scale web archiving tools (i.e., Heritrix and the Wayback Machine installed on the MITRE Intranet) to automatically archive a corporate Intranet. We use this case study to outline the challenges of Intranet web archiving, identify situations in which the open source tools are not well suited for the needs of the corporate archivists, and make recommendations for future corporate archivists wishing to use such tools. We performed a crawl of 143,268 URIs (125 GB and 25 hours) to demonstrate that the crawlers are easy to set …

Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood

Maseeh Summer Undergraduate Research Experience

The goal of this work is to explore applications of reservoir computing in biomolecular computation. Reservoir computing is a unique model for representing a mapping from one instance in time to a specific output. A neural network of randomly connected neurons is linked with a single output neuron or multiple output neurons. The output neurons are capable of mapping inputs to desired outputs using adaptable algorithms. This framework is investigated by using the Python programming language and object oriented design and programming. Neurons are created in programs by bundling information like input data and attributes of the network, which utilize …

An Efficient Method For Optimizing Segmentation Parameters, Jacob D' Avy, Wei-Wen Hsu, Chung-Hao Chen, Andreas F. Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Segmenting an image into meaningful regions is an important step in many computer vision applications such as facial recognition, target tracking and medical image analysis. Because image segmentation is an ill-posed problem, parameters are needed to constrain the solution to one that is suitable for a given application. For a user, setting parameter values is often unintuitive. We present a method for automating segmentation parameter selection using an efficient search method to optimize a segmentation objective function. Efficiency is improved by utilizing prior knowledge about the relationship between a segmentation parameter and the objective function terms. An adaptive sampling of …