Java Server Reliability In The Presence Of Failures, 2017 Marquette University
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 ...
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, 2017 Singapore Management University
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, Ding Ying, Yu, Jianfei, Jing Jiang
Research Collection School Of Information Systems
Opinion target extractionis a fundamental task in opinion mining. In recent years,neural network based supervised learning methods haveachieved competitive performance on this task. However, aswith any supervised learning method, neural network basedmethods for this task cannot work well when the training datacomes from a different domain than the test data. On the otherhand, some rule-based unsupervisedmethods have shown to berobust when applied to different domains. In this work, weuse rule-based unsupervised methods to create auxiliary labelsand use neural network models to learn a hiddenrepresentation that works well for different domains. When this hiddenrepresentation is used for opinion target extraction ...
Robust Optimization For Tree-Structured Stochastic Network Design, 2017 Singapore Management University
Robust Optimization For Tree-Structured Stochastic Network Design, Xiaojian Wu, Akshat Kumar, Daniel Sheldon
Research Collection School Of 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 ...
Streaming Classification With Emerging New Class By Class Matrix Sketching, 2017 Singapore Management University
Streaming Classification With Emerging New Class By Class Matrix Sketching, Xin Mu, Feida Zhu, Juan Du, Ee-Peng Lim, Zhi-Hua Zhou
Research Collection School Of Information Systems
Streaming classification with emerging new class is an important problem of great research challenge and practical value. In many real applications, the task often needs to handle large matrices issues such as textual data in the bag-of-words model and large-scale image analysis. However, the methodologies and approaches adopted by the existing solutions, most of which involve massive distance calculation, have so far fallen short of successfully addressing a real-time requested task. In this paper, the proposed method dynamically maintains two low-dimensional matrix sketches to 1) detect emerging new classes; 2) classify known classes; and 3) update the model in the ...
Developments Of 5g Technology, 2017 Governors State University
Developments Of 5g Technology, Ankit Nilesh Ganatra
All Student Theses
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 ...
On Leveraging Multi-Path Transport In Mobile Networks, 2017 University of Massachusetts Amherst
On Leveraging Multi-Path Transport In Mobile Networks, Yeon-Sup Lim
Multi-Path TCP (MPTCP) is a new transport protocol that enables mobile devices to simultaneously use several physical paths through multiple network interfaces. MPTCP is particularly useful for mobile devices, which usually have multiple wireless interfaces such as IEEE 802.11 (WiFi), cellular (3G/LTE), and Bluetooth. However, applying MPTCP to mobile devices introduces new concerns since they operate in harsh environments with resource constraints due to intermittent path availability and limited power supply. The goal of this thesis is to resolve these problems so as to be able to practically deploy MPTCP in mobile devices.
The first part of the ...
Correcting Pedestrian Dead Reckoning With Monte Carlo Localization Boxed For Indoor Navigation, Akira T. Murphy
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.
Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, 2017 Wright State University - Main Campus
Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma
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 ...
Identifying Depressive Disorder In The Twitter Population, 2017 Wright State University - Main Campus
Identifying Depressive Disorder In The Twitter Population, Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth
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.
A Semantics-Based Measure Of Emoji Similarity, 2017 Wright State University - Main Campus
A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran
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 ...
A Novel Approach For Classifying Gene Expression Data Using Topic Modeling, 2017 Wright State University - Main Campus
A Novel Approach For Classifying Gene Expression Data Using Topic Modeling, Soon Jye Kho, Himi Yalamanchili, Michael L. Raymer, Amit Sheth
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 ...
Relatedness-Based Multi-Entity Summarization, 2017 Wright State University - Main Campus
Relatedness-Based Multi-Entity Summarization, Kalpa Gunaratna, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng
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 ...
Smart Underground Antenna Arrays: A Soil Moisture Adaptive Beamforming Approach, 2017 University of Nebraska-Lincoln
Smart Underground Antenna Arrays: A Soil Moisture Adaptive Beamforming Approach, Abdul Salam, Mehmet C. Vuran
CSE 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 ...
Android Drone: Remote Quadcopter Control With A Phone, 2016 California Polytechnic State University, San Luis Obispo
Android Drone: Remote Quadcopter Control With A Phone, Aubrey John Russell
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 ...
Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, 2016 Wright State University - Main Campus
Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee
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 ...
Who's In And Who's Out?: What's Important In The Cyber World?, 2016 La Salle University
Who's In And Who's Out?: What's Important In The Cyber World?, Tony M. Kelly
The aim of this paper is to offer an introduction to the exploding field of cybersecurity by asking what are the most important concepts or topics that a new member of the field of cybersecurity should know. This paper explores this question from three perspectives: from the realm of business and how the cyber world is intertwined with modern commerce, including common weaknesses and recommendations, from the academic arena examining how cybersecurity is taught and how it should be taught in a classroom or laboratory environment, and lastly, from the author’s personal experience with the cyber world. Included information ...
Gaussian Weighted Neighborhood Connectivity Of Nonlinear Line Attractor For Learning Complex Manifolds, 2016 University of Dayton
Gaussian Weighted Neighborhood Connectivity Of Nonlinear Line Attractor For Learning Complex Manifolds, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla
Vijayan K. Asari
The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA ...
Using A Real-Time Object Detection Application To Illustrate Effectiveness Of Offloading And Prefetching In Cloudlet Architecture, 2016 The University of Western Ontario
Using A Real-Time Object Detection Application To Illustrate Effectiveness Of Offloading And Prefetching In Cloudlet Architecture, Xutong Zhu
Electronic Thesis and Dissertation Repository
In this thesis, we designed and implemented two versions of a real-time object de- tection application: A stand alone version and a cloud version. Through applying the application to a cloudlet environment, we are able to perform experiments and uses the results to illustrate the potential improvement that a cloudlet architecture can bring to mobile applications that require access to large amounts of cloud data or intensive com- putation. Potential improvements include data access speed, reduced CPU and memory usages as well as reduced battery consumption on mobile devices.
Techniques For Identifying Mobile Platform Vulnerabilities And Detecting Policy-Violating Applications, 2016 Singapore Management University
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 ...
Hifocap: An Android App For Wearable Health Devices, 2016 University of Texas at El Paso
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 ...