Computer Sciences Commons^™

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 …

An Improved Smote Algorithm Based On Genetic Algorithm For Imbalanced Data Collection, Qiong Gu, Xian-Ming Wang, Zhao Wu, Bing Ning, Chun-Sheng Xin

Electrical & Computer Engineering Faculty Publications

Classification of imbalanced data has been recognized as a crucial problem in machine learning and data mining. In an imbalanced dataset, minority class instances are likely to be misclassified. When the synthetic minority over-sampling technique (SMOTE) is applied in imbalanced dataset classification, the same sampling rate is set for all samples of the minority class in the process of synthesizing new samples, this scenario involves blindness. To overcome this problem, an improved SMOTE algorithm based on genetic algorithm (GA), namely, GASMOTE was proposed. First, GASMOTE set different sampling rates for different minority class samples. A combination of the sampling rates …

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 …

From Boolean Equalities To Constraints, Sergio Antoy, Michael Hanus

Computer Science Faculty Publications and Presentations

Although functional as well as logic languages use equality to discriminate between logically different cases, the operational meaning of equality is different in such languages. Functional languages reduce equational expressions to their Boolean values, True or False, logic languages use unification to check the validity only and fail otherwise. Consequently, the language Curry, which amalgamates functional and logic programming features, offers two kinds of equational expressions so that the programmer has to distinguish between these uses. We show that this distinction can be avoided by providing an analysis and transformation method that automatically selects the appropriate operation. Without this distinction …

College Of Engineering Senior Design Competition Fall 2015, University Of Nevada, Las Vegas

Fred and Harriet Cox Senior Design Competition Projects

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the projects on …

Energy Forecasting For Event Venues: Big Data And Prediction Accuracy, Katarina Grolinger, Alexandra L'Heureux, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Advances in sensor technologies and the proliferation of smart meters have resulted in an explosion of energy-related data sets. These Big Data have created opportunities for development of new energy services and a promise of better energy management and conservation. Sensor-based energy forecasting has been researched in the context of office buildings, schools, and residential buildings. This paper investigates sensor-based forecasting in the context of event-organizing venues, which present an especially difficult scenario due to large variations in consumption caused by the hosted events. Moreover, the significance of the data set size, specifically the impact of temporal granularity, on energy …

Object Detection And Tracking In Wide Area Surveillance Using Thermal Imagery, Santosh Bhusal

UNLV Theses, Dissertations, Professional Papers, and Capstones

The main objective behind this thesis is to examine how existing vision-based detection and tracking algorithms perform in thermal imagery-based video surveillance. While color-based surveillance has been extensively studied, these techniques can not be used during low illumination, at night, or with lighting changes and shadows which limits their applicability. The main contributions in this thesis are (1) the creation of a new color-thermal dataset, (2) a detailed performance comparison of different color-based detection and tracking algorithms on thermal data and (3) the proposal of an adaptive neural network for false detection rejection.

Since there are not many publicly available …

Automated Multi-Modal Search And Rescue Using Boosted Histogram Of Oriented Gradients, Matthew A. Lienemann

Master's Theses

Unmanned Aerial Vehicles (UAVs) provides a platform for many automated tasks and with an ever increasing advances in computing, these tasks can be more complex. The use of UAVs is expanded in this thesis with the goal of Search and Rescue (SAR), where a UAV can assist fast responders to search for a lost person and relay possible search areas back to SAR teams. To identify a person from an aerial perspective, low-level Histogram of Oriented Gradients (HOG) feature descriptors are used over a segmented region, provided from thermal data, to increase classification speed. This thesis also introduces a dataset …

Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Electrical and Computer Engineering Faculty Publications

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly.

Once all data has been trained in …

Embedded System Design Of A Real-Time Parking Guidance System, Omkar Dokur

USF Tampa Graduate Theses and Dissertations

The primary objective of this work is to design a parking guidance system to reliably detect entering/exiting vehicles to a parking garage in a cost-efficient manner. Existing solutions (inductive loops, RFID based systems, and video image processors) at shopping malls, universities, airports etc., are expensive due to high installation and maintenance costs. There is a need for a parking guidance system that is reliable, accurate, and cost-effective. The proposed parking guidance system is designed to optimize the use of parking spaces and to reduce wait times. Based on a literature review we identify that the ultrasonic sensor is suitable to …

Whatsapp Network Forensics: Decrypting And Understanding The Whatsapp Call Signaling Messages, Filip Karpisek, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

WhatsApp is a widely adopted mobile messaging application with over 800 million users. Recently, a calling feature was added to the application and no comprehensive digital forensic analysis has been performed with regards to this feature at the time of writing this paper. In this work, we describe how we were able to decrypt the network traffic and obtain forensic artifacts that relate to this new calling feature which included the: a) WhatsApp phone numbers, b) WhatsApp server IPs, c) WhatsApp audio codec (Opus), d) WhatsApp call duration, and e) WhatsApp's call termination. We explain the methods and tools used …

A Computational Translation Of The Phaistos Disk, Peter Revesz

School of Computing: Conference and Workshop Papers

For over a century the text of the Phaistos Disk remained an enigma without a convincing translation. This paper presents a novel semi-automatic translation method that uses for the first time a recently discovered connection between the Phaistos Disk symbols and other ancient scripts, including the Old Hungarian alphabet. The connection between the Phaistos Disk script and the Old Hungarian alphabet suggested the possibility that the Phaistos Disk language may be related to Proto-Finno-Ugric, Proto-Ugric, or Proto-Hungarian. Using words and suffixes from those languages, it is possible to translate the Phaistos Disk text as an ancient sun hymn, possibly connected …

A Computational Model Of The Spread Of Ancient Human Populations Based On Mitochondrial Dna Samples, Peter Revesz

School of Computing: Conference and Workshop Papers

The extraction of mitochondrial DNA (mtDNA) from ancient human population samples provides important data for the reconstruction of population influences, spread and evolution from the Neolithic to the present. This paper presents a mtDNA-based similarity measure between pairs of human populations and a computational model for the evolution of human populations. In a computational experiment, the paper studies the mtDNA information from five Neolithic and Bronze Age populations, namely the Andronovo, the Bell Beaker, the Minoan, the Rössen and the Únětice populations. In the past these populations were identified as separate cultural groups based on geographic location, age and the …

A Computational Study Of The Evolution Of Cretan And Related Scripts, Peter Revesz

School of Computing: Conference and Workshop Papers

Crete was the birthplace of several ancient writings, including the Cretan Hieroglyphs, the Linear A and the Linear B scripts. Out of these three only Linear B is deciphered. The sound values of the Cretan Hieroglyph and the Linear A symbols are unknown and attempts to reconstruct them based on Linear B have not been fruitful. In this paper, we compare the ancient Cretan scripts with four other Mediterranean and Black Sea scripts, namely Phoenician, South Arabic, Greek and Old Hungarian. We provide a computational study of the evolution of the three Cretan and four other scripts. This study encompasses …

Professor Frank Breitinger's Full Bibliography, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

No abstract provided.

Towards Mhealth Solutions For Asthma Patients, Nahid Negar

Master's Theses (2009 -)

With the recent, rapid growth in mobile-computing technology, mobile health (mHealth) is becoming a popular research topic. mHealth is one of several examples of how using technology in the health sector is being more advanced every day. mHealth is being applied to the care of a broad spectrum of diseases from acute to chronic, such as the flu, asthma, and cancer. Due to the easy-to-understand and friendly user interfaces, mobility and cost effectiveness; a mobile application can be a powerful tool to collect patient information. Asthma is a common disease around the globe. Collecting the proper symptom, trigger, peak-flow and …

Mutations Of Adjacent Amino Acid Pairs Are Not Always Independent, Jyotsna Ramanan, Peter Revesz

School of Computing: Conference and Workshop Papers

Evolutionary studies usually assume that the genetic mutations are independent of each other. This paper tests the independence hypothesis for genetic mutations with regard to protein coding regions. According to the new experimental results the independence assumption generally holds, but there are certain exceptions. In particular, the coding regions that represent two adjacent amino acids seem to change in ways that sometimes deviate significantly from the expected theoretical probability under the independence assumption.

A-Maze-D: Advanced Maze Development Kit Using Constraint Databases, Shruti Daggumarti, Peter Revesz, Corey Svehla

School of Computing: Conference and Workshop Papers

In this paper, we describe the A-Maze-D system which shows that constraint databases can be applied conveniently and efficiently to the design of maze games. A-Maze-D provides a versatile set of features by a combination of a MATLAB library and the MLPQ constraint database system. A-Maze-D is the first system that uses constraint databases to build maze games and opens new ideas in video game development.

A Constraint Language For Static Semantic Analysis Based On Scope Graphs, Hendrik Van Antwerpen, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth

Computer Science Faculty Publications and Presentations

In previous work, we introduced scope graphs as a formalism for describing program binding structure and performing name resolution in an AST-independent way. In this paper, we show how to use scope graphs to build static semantic analyzers. We use constraints extracted from the AST to specify facts about binding, typing, and initialization. We treat name and type resolution as separate building blocks, but our approach can handle language constructs—such as record field access—for which binding and typing are mutually dependent.We also refine and extend our previous scope graph theory to address practical concerns including ambiguity checking and support for …

Clustering Data Of Mixed Categorical And Numerical Type With Unsupervised Feature Learning, Dao Lam, Mingzhen Wei, Donald C. Wunsch

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Mixed-type categorical and numerical data are a challenge in many applications. This general area of mixed-type data is among the frontier areas, where computational intelligence approaches are often brittle compared with the capabilities of living creatures. In this paper, unsupervised feature learning (UFL) is applied to the mixed-type data to achieve a sparse representation, which makes it easier for clustering algorithms to separate the data. Unlike other UFL methods that work with homogeneous data, such as image and video data, the presented UFL works with the mixed-type data using fuzzy adaptive resonance theory (ART). UFL with fuzzy ART (UFLA) obtains …

Rfid Microscope Lab, Patricia Carranza

Computer Engineering

The RFID Microscope Lab is a new exhibit created for the San Luis Obispo Children's Museum. The goal of the project is to create a modern, interactive exhibit that will teach children about different natural specimens through the use of technology. A computer, custom software, and RFID technology, will be used to display facts, microscopic images, and short videos of ten different specimens.

Bioinformatics Approaches To Single-Cell Analysis In Developmental Biology, Dicle Yalcin, Zeynep M. Hakguder, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging …

Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni

Dissertations and Theses

This research presents a methodology to evaluate data path topologies that implement a conditional statement for an average-case performance that is better than the worst-case performance. A conditional statement executes one of many alternatives depending on how Boolean conditions evaluate to true or false. Alternatives with simple computations take less time to execute. The self-timed designs can exploit the faster executing alternatives and provide an average-case behavior, where the average depends on the frequency of simple and complex computations, and the difference in the completion times of simple and complex computations. The frequency of simple and complex computations depends on …

Implementation Of A Speech Recognition Algorithm To Facilitate Verbal Commands For Visual Analytics Law Enforcement Toolkit, Shubham S. Rastogi, David L. Wiszowaty, Hanye Xu, Abish Malik, David S. Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

The VALET (Visual Analytics Law Enforcement Toolkit) system allows the user to visualize and predict crime hotspots and analyze crime data. Police officers have difficulty in using VALET in a mobile situation, since the system allows only conventional input interfaces (keyboard and mouse). This research focuses on introducing a new input interface to VALET in the form of speech recognition, which allows the user to interact with the software without losing functionality. First an Application Program Interface (API) that was compatible with the VALET system was found and initial code scripts to test its functionality were written. Next, the code …

Classification And Visualization Of Crime-Related Tweets, Ransen Niu, Jiawei Zhang, David S. Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

Millions of Twitter posts per day can provide an insight to law enforcement officials for improved situational awareness. In this paper, we propose a natural-language-processing (NLP) pipeline towards classification and visualization of crime-related tweets. The work is divided into two parts. First, we collect crime-related tweets by classification. Unlike written text, social media like Twitter includes substantial non-standard tokens or semantics. So we focus on exploring the underlying semantic features of crime-related tweets, including parts-of-speech properties and intention verbs. Then we use these features to train a classification model via Support Vector Machine. The second part is to utilize visual …

In Need Of A Domain-Specific Language Modeling Notation For Smartphone Applications With Portable Capability, Hamza Ghandorh, Luiz Fernando Capretz Dr., Ali Bou Nassif Dr.

Electrical and Computer Engineering Publications

The rapid growth of the smartphone market and its increasing revenue has motivated developers to target multiple platforms. Market leaders, such as Apple, Google, and Microsoft, develop their smartphone applications complying with their platform specifications. The specification of each platform makes a platform-dedicated application incompatible with other platforms due to the diversity of operating systems, programming languages, and design patterns. Conventional development methodologies are applied to smartphone applications, yet they perform less well. Smartphone applications have unique hardware and software requirements. All previous factors push smartphone developers to build less sophisticated and low-quality products when targeting multiple smartphone platforms. Model-driven …