OS and Networks Commons^™

Eassistant: Cognitive Assistance For Identification And Auto-Triage Of Actionable Conversations, Hamid R. Motahari Nezhad, Kalpa Gunaratna, Juan Cappi

Kno.e.sis Publications

The browser and screen have been the main user interfaces of the Web and mobile apps. The notification mechanism is an evolution in the user interaction paradigm by keeping users updated without checking applications. Conversational agents are posed to be the next revolution in user interaction paradigms. However, without intelligence on the triage of content served by the interaction and content differentiation in applications, interaction paradigms may still place the burden of information overload on users. In this paper, we focus on the problem of intelligent identification of actionable information in the content served by applications, and in particular in …

A Dynamic Programming Approach For Quickly Estimating Large Network-Based Mev Models, Tien Mai, Emma Frejinger, Mogens Fosgereau, Fabian Bastin

Research Collection School Of Computing and Information Systems

We propose a way to estimate a family of static Multivariate Extreme Value (MEV) models with large choice sets in short computational time. The resulting model is also straightforward and fast to use for prediction. Following Daly and Bierlaire (2006), the correlation structure is defined by a rooted, directed graph where each node without successor is an alternative. We formulate a family of MEV models as dynamic discrete choice models on graphs of correlation structures and show that the dynamic models are consistent with MEV theory and generalize the network MEV model (Daly and Bierlaire, 2006). Moreover, we show that …

Network-On-Chip Based H.264 Video Decoder On A Field Programmable Gate Array, Ian Barge

Master's Theses (2009 -)

This thesis develops the first fully network-on-chip (NoC) based h.264 video decoder implemented in real hardware on a field programmable gate array (FPGA). This thesis starts with an overview of the h.264 video coding standard and an introduction to the NoC communication paradigm. Following this, a series of processing elements (PEs) are developed which implement the component algorithms making up the h.264 video decoder. These PEs, described primarily in VHDL with some Verilog and C, are then mapped to an NoC which is generated using the CONNECT NoC generation tool. To demonstrate the scalability of the proposed NoC based design, …

Java Server Reliability In The Presence Of Failures, Rich Coe

Master's Theses (2009 -)

A design for the separation of a server interface and work processing. Numerous sources, Tanenbaum (Tanenbaum Modern Operating Systems, 493), Goscinski (Goscinski Distributed operating systems, 203), and Birman (Birman Reliable distributed systems, 265), all discuss the concept of Two-Phase Commit, where a coordinator directs one or more processes to perform a transaction. If the transaction or any of the processes fail, the coordinator can decide how to proceed by either retrying or aborting the request. The popular web browser Chrome utilizes a separate process for each tab displayed. Should the rendering and display of a web page cause a crash, …

An Indoor Navigation System Using A Sensor Fusion Scheme On Android Platform, Jiayi Xin

Master's Theses (2009 -)

With the development of wireless communication networks, smart phones have become a necessity for people’s daily lives, and they meet not only the needs of basic functions for users such as sending a message or making a phone call, but also the users’ demands for entertainment, surfing the Internet and socializing. Navigation functions have been commonly utilized, however the navigation function is often based on GPS (Global Positioning System) in outdoor environments, whereas a number of applications need to navigate indoors. This paper presents a system to achieve high accurate indoor navigation based on Android platform. To do this, we …

A Comprehensive Context-Aware Interruption Management System, April Chunjiao Song

Master's Theses (2009 -)

The interruption system is an application that prevents the user from noticing phone calls when he/she is busy, by turning off the ringtone. In a previous project, the user can enter his/her class and work schedule on Google Calendar. The intelligent interruption system can detect if the current time matches the range of one of the events in the user's Google Calendar. Other contexts considered were: driving, relationship of the callers, and proximity of Bluetooth devices. This project is a continuation of the interruption system. We consider additional context, social media such as Twitter. Research is done on when is …

Dark Hazard: Large-Scale Discovery Of Unknown Hidden Sensitive Operations In Android Apps, Xiaorui Pan, Xueqiang Wang, Yue Duan, Xiaofeng Wang, Heng Yin

Research Collection School Of Computing and Information Systems

Hidden sensitive operations (HSO) such as stealing privacy user data upon receiving an SMS message are increasingly utilized by mobile malware and other potentially-harmful apps (PHAs) to evade detection. Identification of such behaviors is hard, due to the challenge in triggering them during an app’s runtime. Current static approaches rely on the trigger conditions or hidden behaviors known beforehand and therefore cannot capture previously unknown HSO activities. Also these techniques tend to be computationally intensive and therefore less suitable for analyzing a large number of apps. As a result, our understanding of real-world HSO today is still limited, not to …

Robust Optimization For Tree-Structured Stochastic Network Design, Xiaojian Wu, Akshat Kumar, Daniel Sheldon

Research Collection School Of Computing and Information Systems

Stochastic network design is a general framework for optimizing network connectivity. It has several applications in computational sustainability including spatial conservation planning, pre-disaster network preparation, and river network optimization. A common assumption in previous work has been made that network parameters (e.g., probability of species colonization) are precisely known, which is unrealistic in real- world settings. We therefore address the robust river network design problem where the goal is to optimize river connectivity for fish movement by removing barriers. We assume that fish passability probabilities are known only imprecisely, but are within some interval bounds. We then develop a planning …

A Riemannian Network For Spd Matrix Learning, Zhiwu Huang, Gool L. Van

Research Collection School Of Computing and Information Systems

Symmetric Positive Definite (SPD) matrix learning methods have become popular in many image and video processing tasks, thanks to their ability to learn appropriate statistical representations while respecting Riemannian geometry of underlying SPD manifolds. In this paper we build a Riemannian network architecture to open up a new direction of SPD matrix non-linear learning in a deep model. In particular, we devise bilinear mapping layers to transform input SPD matrices to more desirable SPD matrices, exploit eigenvalue rectification layers to apply a non-linear activation function to the new SPD matrices, and design an eigenvalue logarithm layer to perform Riemannian computing …

Bike Route Choice Modeling Using Gps Data Without Choice Sets Of Paths, Maëlle Zimmermann, Tien Mai, Emma Frejinger

Research Collection School Of Computing and Information Systems

Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. Route choice models can help achieve this objective by gaining insights into the trade-offs cyclists make when choosing their routes and by allowing the effect of infrastructure improvements to be analyzed. We estimate a link-based bike route choice model from a sample of GPS observations in the city of Eugene on a network comprising over 40,000 links. The so-called recursive logit (RL) model (Fosgerau et al., 2013) does not require to sample any …

Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

Kno.e.sis Publications

Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new …

Relatedness-Based Multi-Entity Summarization, Kalpa Gunaratna, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng

Kno.e.sis Publications

Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and …

A Novel Approach For Classifying Gene Expression Data Using Topic Modeling, Soon Jye Kho, Himi Yalamanchili, Michael L. Raymer, Amit Sheth

Kno.e.sis Publications

Understanding the role of differential gene expression in cancer etiology and cellular process is a complex problem that continues to pose a challenge due to sheer number of genes and inter-related biological processes involved. In this paper, we employ an unsupervised topic model, Latent Dirichlet Allocation (LDA) to mitigate overfitting of high-dimensionality gene expression data and to facilitate understanding of the associated pathways. LDA has been recently applied for clustering and exploring genomic data but not for classification and prediction. Here, we proposed to use LDA inclustering as well as in classification of cancer and healthy tissues using lung cancer …

Correcting Pedestrian Dead Reckoning With Monte Carlo Localization Boxed For Indoor Navigation, Akira T. Murphy

Honors Theses

Localization of phones is a ubiquitous part of the modern mobile electronics landscape. However, there are many situations where the current method of networked localization fails. A Pedestrian Dead Reckoning System where the location of the user is calculated by counting the steps and direction of the user was implemented as an iOS app with python for data analysis. A novel algorithm for wireless sensor localization using Ad-Hoc Bluetooth networks was proposed. A small experiment was performed proving that the system is nearly equal to state of the art algorithms.

A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

Kno.e.sis Publications

Emoji have grown to become one of the most important forms of communication on the web. With its widespread use, measuring the similarity of emoji has become an important problem for contemporary text processing since it lies at the heart of sentiment analysis, search, and interface design tasks. This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base. Using emoji descriptions, emoji sense labels and emoji sense definitions, and with different training corpora obtained from Twitter and Google News, we develop and test …

Identifying Depressive Disorder In The Twitter Population, Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth

Kno.e.sis Publications

Depression is a highly prevalent public health challenge and a major cause of disability across the globe.

• Annually 6.7% of Americans (that is, more than 16 million).
• Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires.
• Large temporal gaps and cognitive bias.

Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.

Smart Underground Antenna Arrays: A Soil Moisture Adaptive Beamforming Approach, Abdul Salam, Mehmet C. Vuran

School of Computing: Technical Reports

In this paper, a novel framework for underground beamforming using adaptive antenna arrays is presented. Based on the analysis of propagation in wireless underground channel, a theoretical model is developed which uses soil moisture information and feedback mechanism to improve performance wireless underground communications. Array element in soil has been analyzed empirically and impacts of soil type and soil moisture on return loss and resonant frequency are investigated. Beam patterns are investigated to communicate with both underground and above ground devices. Depending on the incident angle, refraction from soil-air interface has the adverse effects in the UG communications. It is …

Using Self-Organizing Maps For Computer Network Intrusion Detection, Manuel R. Parrachavez

Theses and Dissertations

Anomaly detection in user access patterns using artificial neural networks is a novel way of combating the ever-present concern of computer network intrusion detection for many entities around the world. Anomaly detection is a technique in network security in which a profile is built around a user's normal daily actions. The data collected for these profiles can be as following: file access attempts; failed login attempts; file creations; file access failures; and countless others. This data is collected and used as training data for a neural network.

There are many types of neural networks, such as multi-layer feed-forward network; recurrent …

Advances On Software Defined Wireless Networking, D. B. Rawat, M. Song, C. Xin

Electrical & Computer Engineering Faculty Publications

Software defined wireless networking is regarded as an emerging technology to enhance spectrum efficiency and improve the overall network performance. In this paper, we summarise the special issue on recent advances in software defined wireless networking. Specifically, this special issue publishes following findings: i) a novel context aware medium access control scheme for multichannel buffer-aided cognitive networks to reduce the delay by exploiting the packets’ contexts; ii) a utility-based uplink scheduling algorithm that accommodates different performance metrics and adapts its decisions based on user-specified profiles by incorporating an intermediary layer between the MAC and network layer; iii) an opportunistic spectrum …

Developments Of 5g Technology, Ankit Nilesh Ganatra

All Student Theses and Dissertations

This technology is the future of current LTE technology which would be a boost to the future of wireless and computer networks, as the speeds would be way higher than the current LTE networks, which will push the technology to a new level. This technology will make the radio channels to support data access speeds up to 10 Gb/s which will turn the bandwidth radio channels as WiFi. Comparing it with other LTE technology's it has high speed and capacity, support interactive multimedia, voice, internet and its data rate is 1 Gbps which makes it faster than other LTE’s . …

Android Drone: Remote Quadcopter Control With A Phone, Aubrey John Russell

Computer Engineering

The purpose of the “Android Drone” project was to create a quadcopter that can be controlled by user input sent over the phone’s Wi-Fi connection or 4G internet connection. Furthermore, the purpose was also to be able to receive live video feedback over the internet connection, thus making the drone an inexpensive option compared to other, equivalent drones that might cost thousands of dollars. Not only that, but the Android phone also has a host of other useful features that could be utilized by the drone: this includes GPS, pathing, picture taking, data storage, networking and TCP/IP, a Java software …

Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee

Kno.e.sis Publications

We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera as well as validated using the ground truth dataset. Our preliminary results indicate that the extraction of activity from the video …

A Method Of Integrating Correlation Structures For A Generalized Recursive Route Choice Model, Tien Mai

Research Collection School Of Computing and Information Systems

We propose a way to estimate a generalized recursive route choice model. The model generalizes other existing recursive models in the literature, i.e., (Fosgerau et al., 2013b; Mai et al., 2015c), while being more flexible since it allows the choice at each stage to be any member of the network multivariate extreme value (network MEV) model (Daly and Bierlaire, 2006). The estimation of the generalized model requires defining a contraction mapping and performing contraction iterations to solve the Bellman’s equation. Given the fact that the contraction mapping is defined based on the choice probability generating functions (CPGF) (Fosgerau et al., …

Computation Of Shortest Path Problem In A Network With Sv-Trapezoidal Neutrosophic Numbers, Florentin Smarandache, Said Broumi, Assia Bakali, Mohamed Talea, Luige Vladareanu

Branch Mathematics and Statistics Faculty and Staff Publications

In this work, a neutrosophic network method is proposed for finding the shortest path length with single valued trapezoidal neutrosophic number. The proposed algorithm gives the shortest path length using score function from source node to destination node. Here the weights of the edges are considered to be single valued trapezoidal neutrosophic number. Finally, a numerical example is used to illustrate the efficiency of the proposed approach

Static Loop Analysis And Its Applications, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Loops are challenging structures in program analysis, and an effective loop analysis is crucial in the applications, such as symbolic execution and program verification. In the research, we will first perform a deep analysis and propose a classification according to the complexity of the loops. Then try to propose techniques for analyzing and summarizing different loops. At last, we apply the techniques in multiple applications.

Summarization Of Egocentric Videos: A Comprehensive Survey, Ana Garcia Del Molino, Cheston Tan, Joo-Hwee Lim, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The introduction of wearable video cameras (e.g., GoPro) in the consumer market has promoted video life-logging, motivating users to generate large amounts of video data. This increasing flow of first-person video has led to a growing need for automatic video summarization adapted to the characteristics and applications of egocentric video. With this paper, we provide the first comprehensive survey of the techniques used specifically to summarize egocentric videos. We present a framework for first-person view summarization and compare the segmentation methods and selection algorithms used by the related work in the literature. Next, we describe the existing egocentric video datasets …

Proteus: Computing Disjunctive Loop Summary Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Yang Liu, Wei Le, Xiaohong Li

Research Collection School Of Computing and Information Systems

Loops are challenging structures for program analysis, especially when loops contain multiple paths with complex interleaving executions among these paths. In this paper, we first propose a classification of multi-path loops to understand the complexity of the loop execution, which is based on the variable updates on the loop conditions and the execution order of the loop paths. Secondly, we propose a loop analysis framework, named Proteus, which takes a loop program and a set of variables of interest as inputs and summarizes path-sensitive loop effects on the variables. The key contribution is to use a path dependency automaton (PDA) …

Techniques For Identifying Mobile Platform Vulnerabilities And Detecting Policy-Violating Applications, Mon Kywe Su

Dissertations and Theses Collection

Mobile systems are generally composed of three layers of software: application layer where third-party applications are installed, framework layer where Application Programming Interfaces (APIs) are exposed, and kernel layer where low-level system operations are executed. In this dissertation, we focus on security and vulnerability analysis of framework and application layers. Security mechanisms, such as Android’s sandbox and permission systems, exist in framework layer, while malware scanners protects application layer. However, there are rooms for improvement in both mechanisms. For instance, Android’s permission system is known to be implemented in ad-hoc manner and not well-tested for vulnerabilities. Application layer also focuses …

Hifocap: An Android App For Wearable Health Devices, Yoonsik Cheon, Rodrigo A. Romero

Departmental Technical Reports (CS)

Android is becoming a platform for mobile health-care devices and apps. However, there are many challenges in developing soft real-time, health-care apps for non-dedicated mobile devices such as smartphones and tablets. In this paper we share our experiences in developing the HifoCap app, a mobile app for receiving electroencephalogram (EEG) wave samples from a wearable device, visualizing the received EEG samples, and transmitting them to a cloud storage server. The app is network and data-intensive. We describe the challenges we faced while developing the HifoCap app---e.g., ensuring the soft real-time requirement in the presence of uncertainty on the Android platform---along …

Understanding Firewalld In Multi-Zone Configurations, Nathan R. Vance, William F. Polik

Faculty Publications

Stories of compromised servers and data theft fill today's news. It isn't difficult for someone who has read an informative blog post to access a system via a misconfigured service, take advantage of a recently exposed vulnerability, or gain control using a stolen password. Any of the many internet services found on a typical Linux server could harbor a vulnerability that grants unauthorized access to the system.

Since it's an impossible task to harden a system at the application level against every possible threat, firewalls provide security by limiting access to a system. Firewalls filter incoming packets based on their …