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2017

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Full-Text Articles in Engineering

Rapid Tagging And Reporting For Functional Language Extraction In Scientific Articles, Mahdi Ramezani, Vijay K. Kalivarapu, Stephen B. Gilbert, Sarah R. Huffman, Elena Cotos, Annette M. O'Connor Dec 2017

Rapid Tagging And Reporting For Functional Language Extraction In Scientific Articles, Mahdi Ramezani, Vijay K. Kalivarapu, Stephen B. Gilbert, Sarah R. Huffman, Elena Cotos, Annette M. O'Connor

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

This paper describes the development of a web-based application for tagging scientific articles, in part to create machine learning training datasets for automated functional language identification and extraction (AFLEX). The initial intent for this work was to provide a new member of the ecosystem of tools that facilitate the structured automation of systematic reviews, an area of work that typically requires critical analysis of multiple research studies and provides an exhaustive summary of literature related to a research question. However, the tool’s modular interface allows use across disciplines. A user may upload PDF or text documents and quickly tag ...


College Of Engineering Senior Design Competition Fall 2017, University Of Nevada, Las Vegas Dec 2017

College Of Engineering Senior Design Competition Fall 2017, University Of Nevada, Las Vegas

Senior Projects (COE)

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 ...


Host Managed Contention Avoidance Storage Solutions For Big Data, Pratik Mishra, Arun K. Somani Dec 2017

Host Managed Contention Avoidance Storage Solutions For Big Data, Pratik Mishra, Arun K. Somani

Electrical and Computer Engineering Publications

The performance gap between compute and storage is fairly considerable. This results in a mismatch between the application needs from storage and what storage can deliver. The full potential of storage devices cannot be harnessed till all layers of I/O hierarchy function efficiently. Despite advanced optimizations applied across various layers along the odyssey of data access, the I/O stack still remains volatile. The problems associated due to the inefficiencies in data management get amplified in Big Data shared resource environments. The Linux OS (host) block layer is the most critical part of the I/O hierarchy, as it ...


Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad Dec 2017

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

Computer Science and Engineering: Theses, Dissertations, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible ...


An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly Dec 2017

An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly

Computer Science and Engineering: Theses, Dissertations, and Student Research

Prescribed fires can lessen wildfire severity and control invasive species, but some terrains may be difficult, dangerous, or costly to burn with existing tools. This thesis presents the design of an unmanned aerial system that can ignite prescribed fires from the air, with less cost and risk than with aerial ignition from a manned aircraft. The prototype was evaluated in-lab and successfully used to ignite interior areas of two prescribed fires. Additionally, we introduce an approach that integrates a lightweight fire simulation to autonomously plan safe flight trajectories and suggest effective fire lines. Both components are unique in that they ...


Policy Gradient With Value Function Approximation For Collective Multiagent Planning, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau Dec 2017

Policy Gradient With Value Function Approximation For Collective Multiagent Planning, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Decentralized (PO)MDPs provide an expressive framework for sequential decision making in a multiagent system. Given their computational complexity, recent research has focused on tractable yet practical subclasses of Dec-POMDPs. We address such a subclass called CDec-POMDP where the collective behavior of a population of agents affects the joint-reward and environment dynamics. Our main contribution is an actor-critic (AC) reinforcement learning method for optimizing CDec-POMDP policies. Vanilla AC has slow convergence for larger problems. To address this, we show how a particular decomposition of the approximate action-value function over agents leads to effective updates, and also derive a new way ...


Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau Dec 2017

Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Port capacity is determined by three major infrastructural resources namely, berths, yards and gates. Theadvertised capacity is constrained by the least of the capacities of the three resources. While a lot ofattention has been paid to optimizing berth and yard capacities, not much attention has been given toanalyzing the gate capacity. The gates are a key node between the land-side and sea-side operations in anocean-to-cities value chain. The gate system under consideration, located at an important port in an Asiancity, is a multi-class parallel queuing system with non-homogeneous Poisson arrivals. It is hard to obtaina closed form analytic approach for ...


Law Enforcement Resource Optimization With Response Time Guarantees, Jonathan Chase, Jiali Du, Na Fu, Truc Viet Le, Hoong Chuin Lau Dec 2017

Law Enforcement Resource Optimization With Response Time Guarantees, Jonathan Chase, Jiali Du, Na Fu, Truc Viet Le, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In a security-conscious world, and with the rapid increase in the global urbanized population, there is a growing challenge for law enforcement agencies to efficiently respond to emergency calls. We consider the problem of spatially and temporally optimizing the allocation of law enforcement resources such that the quality of service (QoS) in terms of emergency response time can be guaranteed. To solve this problem, we provide a spatio-temporal MILP optimization model, which we learn from a real-world dataset of incidents and dispatching records, and solve by existing solvers. One key feature of our proposed model is the introduction of risk ...


Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Junwei Zhang, Zhiquan Liu Dec 2017

Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Junwei Zhang, Zhiquan Liu

Research Collection School Of Computing and Information Systems

Searchable encryption (SE) techniques allow cloud clients to easily store data and search encrypted data in a privacy-preserving manner, where most of SE schemes treat the cloud server as honest-but-curious. However, in practice, the cloud server is a semi-honest-but-curious third-party, which only executes a fraction of search operations and returns a fraction of false search results to save its computational and bandwidth resources. Thus, it is important to provide a results verification method to guarantee the correctness of the search results. Existing SE schemes allow multiple data owners to upload different records to the cloud server, but these schemes have ...


Graphmp: An Efficient Semi-External-Memory Big Graph Processing System On A Single Machine, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao Dec 2017

Graphmp: An Efficient Semi-External-Memory Big Graph Processing System On A Single Machine, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Recent studies showed that single-machine graph processing systems can be as highly competitive as clusterbased approaches on large-scale problems. While several outof-core graph processing systems and computation models have been proposed, the high disk I/O overhead could significantly reduce performance in many practical cases. In this paper, we propose GraphMP to tackle big graph analytics on a single machine. GraphMP achieves low disk I/O overhead with three techniques. First, we design a vertex-centric sliding window (VSW) computation model to avoid reading and writing vertices on disk. Second, we propose a selective scheduling method to skip loading and processing ...


Who Are Your Users? Comparing Media Professionals' Preconception Of Users To Data-Driven Personas, Lene Nielsen, Soon-Gyu Jung, Jisun An, Joni Salminen, Haewoon Kwak, Bernard J. Jansen Dec 2017

Who Are Your Users? Comparing Media Professionals' Preconception Of Users To Data-Driven Personas, Lene Nielsen, Soon-Gyu Jung, Jisun An, Joni Salminen, Haewoon Kwak, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

One of the reasons for using personas is to align user understandings across project teams and sites. As part of a larger persona study, at Al Jazeera English (AJE), we conducted 16 qualitative interviews with media producers, the end users of persona descriptions. We asked the participants about their understanding of a typical AJE media consumer, and the variety of answers shows that the understandings are not aligned and are built on a mix of own experiences, own self, assumptions, and data given by the company. The answers are sometimes aligned with the data-driven personas and sometimes not. The end ...


Wearete: A Scalable Wearable E-Textile Triboelectric Energy Harvesting System For Human Motion Scavenging, Xian Li, Ye Sun Nov 2017

Wearete: A Scalable Wearable E-Textile Triboelectric Energy Harvesting System For Human Motion Scavenging, Xian Li, Ye Sun

Michigan Tech Publications

In this paper, we report the design, experimental validation and application of a scalable, wearable e-textile triboelectric energy harvesting (WearETE) system for scavenging energy from activities of daily living. The WearETE system features ultra-low-cost material and manufacturing methods, high accessibility, and high feasibility for powering wearable sensors and electronics. The foam and e-textile are used as the two active tribomaterials for energy harvester design with the consideration of flexibility and wearability. A calibration platform is also developed to quantify the input mechanical power and power efficiency. The performance of the WearETE system for human motion scavenging is validated and calibrated ...


Bikemate: Bike Riding Behavior Monitoring With Smartphones, Weixi Gu, Zimu Zhou, Yuxun Zhou, Han Zou, Yunxin Liu, Costas J. Spanos, Lin Zhang Nov 2017

Bikemate: Bike Riding Behavior Monitoring With Smartphones, Weixi Gu, Zimu Zhou, Yuxun Zhou, Han Zou, Yunxin Liu, Costas J. Spanos, Lin Zhang

Research Collection School Of Computing and Information Systems

Detecting dangerous riding behaviors is of great importance to improve bicycling safety. Existing bike safety precautionary measures rely on dedicated infrastructures that incur high installation costs. In this work, we propose BikeMate, a ubiquitous bicycling behavior monitoring system with smartphones. BikeMate invokes smartphone sensors to infer dangerous riding behaviors including lane weaving, standing pedalling and wrong-way riding. For easy adoption, BikeMate leverages transfer learning to reduce the overhead of training models for different users, and applies crowdsourcing to infer legal riding directions without prior knowledge. Experiments with 12 participants show that BikeMate achieves an overall accuracy of 86.8% for ...


Reconstructing Yeasts Phylogenies And Ancestors From Whole Genome Data, Bing Feng, Yu Lin, Lingxi Zhou, Yan Guo, Robert Friedman, Roufan Xia, Chao Liu, Jijun Tang Nov 2017

Reconstructing Yeasts Phylogenies And Ancestors From Whole Genome Data, Bing Feng, Yu Lin, Lingxi Zhou, Yan Guo, Robert Friedman, Roufan Xia, Chao Liu, Jijun Tang

Faculty Publications

Phylogenetic studies aim to discover evolutionary relationships and histories. These studies are based on similarities of morphological characters and molecular sequences. Currently, widely accepted phylogenetic approaches are based on multiple sequence alignments, which analyze shared gene datasets and concatenate/coalesce these results to a final phylogeny with maximum support. However, these approaches still have limitations, and often have conflicting results with each other. Reconstructing ancestral genomes helps us understand mechanisms and corresponding consequences of evolution. Most existing genome level phylogeny and ancestor reconstruction methods can only process simplified real genome datasets or simulated datasets with identical genome content, unique genome ...


Reconstructing Yeasts Phylogenies And Ancestors From Whole Genome Data, Bing Feng, Yu Ling, Lingxi Zhou, Roufan Xia, Fei Hu, Chao Liu Nov 2017

Reconstructing Yeasts Phylogenies And Ancestors From Whole Genome Data, Bing Feng, Yu Ling, Lingxi Zhou, Roufan Xia, Fei Hu, Chao Liu

Faculty Publications

Phylogenetic studies aim to discover evolutionary relationships and histories. These studies are based on similarities of morphological characters and molecular sequences. Currently, widely accepted phylogenetic approaches are based on multiple sequence alignments, which analyze shared gene datasets and concatenate/coalesce these results to a final phylogeny with maximum support. However, these approaches still have limitations, and often have conflicting results with each other. Reconstructing ancestral genomes helps us understand mechanisms and corresponding consequences of evolution. Most existing genome level phylogeny and ancestor reconstruction methods can only process simplified real genome datasets or simulated datasets with identical genome content, unique genome ...


Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun Nov 2017

Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun

Computer Science Faculty Research & Creative Works

The utilization of onsite generation system with renewable sources in manufacturing plants plays a critical role in improving the resilience, enhancing the sustainability, and bettering the cost effectiveness for manufacturers. When designing the capacity of onsite generation system, the manufacturing energy load needs to be met and the cost for building and operating such onsite system with renewable sources are two critical factors need to be carefully quantified. Due to the randomness of machine failures and the variation of local weather, it is challenging to determine the energy load and onsite generation supply at different time periods. In this paper ...


Projection-Based Stabilization Of Interface Lagrange Multipliers In Immersogeometric Fluid–Thin Structure Interaction Analysis, With Application To Heart Valve Modeling, David Kamensky, John A. Evans, Ming-Chen Hsu, Yuri Bazilevs Nov 2017

Projection-Based Stabilization Of Interface Lagrange Multipliers In Immersogeometric Fluid–Thin Structure Interaction Analysis, With Application To Heart Valve Modeling, David Kamensky, John A. Evans, Ming-Chen Hsu, Yuri Bazilevs

Mechanical Engineering Publications

This paper discusses a method of stabilizing Lagrange multiplier fields used to couple thin immersed shell structures and surrounding fluids. The method retains essential conservation properties by stabilizing only the portion of the constraint orthogonal to a coarse multiplier space. This stabilization can easily be applied within iterative methods or semi-implicit time integrators that avoid directly solving a saddle point problem for the Lagrange multiplier field. Heart valve simulations demonstrate applicability of the proposed method to 3D unsteady simulations. An appendix sketches the relation between the proposed method and a high-order-accurate approach for simpler model problems.


Intent Detection Through Text Mining And Analysis, Samantha Akulick, El Sayed Mahmoud Nov 2017

Intent Detection Through Text Mining And Analysis, Samantha Akulick, El Sayed Mahmoud

Publications and Scholarship

The article is about the work investigated using n-grams, parts-Of-Speech and Support Vector machines for detecting the customer intents in the user generated contents. The work demonstrated a system of categorization of customer intents that is concise and useful for business purposes. We examined possible sources of text posts to be analyzed using three text mining algorithms. We presented the three algorithms and the results of testing them in detecting different six intents. This work established that intent detection can be performed on text posts with approximately 61% accuracy.


Understanding Inactive Yet Available Assignees In Github, Jing Jiang, David Lo, Xinyu Ma, Fuli Feng, Li Zhang Nov 2017

Understanding Inactive Yet Available Assignees In Github, Jing Jiang, David Lo, Xinyu Ma, Fuli Feng, Li Zhang

Research Collection School Of Computing and Information Systems

Context In GitHub, an issue or a pull request can be assigned to a specific assignee who is responsible for working on this issue or pull request. Due to the principle of voluntary participation, available assignees may remain inactive in projects. If assignees ever participate in projects, they are active assignees; otherwise, they are inactive yet available assignees (inactive assignees for short). Objective Our objective in this paper is to provide a comprehensive analysis of inactive yet available assignees in GitHub. Method We collect 2,374,474 records of activities in 37 popular projects, and 797,756 records of activities ...


Intent Recognition In Smart Living Through Deep Recurrent Neural Networks, Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng, Xianzhi Wang Nov 2017

Intent Recognition In Smart Living Through Deep Recurrent Neural Networks, Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng, Xianzhi Wang

Research Collection School Of Computing and Information Systems

Electroencephalography (EEG) signal based intent recognition has recently attracted much attention in both academia and industries, due to helping the elderly or motor-disabled people controlling smart devices to communicate with outer world. However, the utilization of EEG signals is challenged by low accuracy, arduous and time-consuming feature extraction. This paper proposes a 7-layer deep learning model to classify raw EEG signals with the aim of recognizing subjects’ intents, to avoid the time consumed in pre-processing and feature extraction. The hyper-parameters are selected by an Orthogonal Array experiment method for efficiency. Our model is applied to an open EEG dataset provided ...


Learning Curve Analysis Using Intensive Longitudinal And Cluster-Correlated Data, Xiao Zhong, Zeyi Sun, Haoyi Xiong, Neil Heffernan, Md Monirul Islam Nov 2017

Learning Curve Analysis Using Intensive Longitudinal And Cluster-Correlated Data, Xiao Zhong, Zeyi Sun, Haoyi Xiong, Neil Heffernan, Md Monirul Islam

Engineering Management and Systems Engineering Faculty Research & Creative Works

Intensive longitudinal and cluster-correlated data (ILCCD) can be generated in any situation where numerical or categorical characteristics of multiple individuals or study units are observed and measured at tens, hundreds, or thousands of occasions. The spacing of measurements in time for each individual can be regular or irregular, fixed or random, and the number of characteristics measured at each occasion may be few or many. Such data can also arise in situations involving continuous-time measurements of recurrent events. Generalized linear models (GLMs) are usually considered for the analysis of correlated non-normal data, while multivariate analysis of variance (MANOVA) is another ...


Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu Nov 2017

Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection, and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate ...


Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu Nov 2017

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifyingtrue values of data items of interest from conflicting multi-sourceddata. Although considerable research efforts have been conducted on thistopic, existing approaches generally assume every data item has exactlyone true value, which fails to reflect the real world where data items withmultiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items.SourceVote models the endorsement relations among sources by quantifyingtheir two-sided inter-source agreements. In particular, two graphs areconstructed to model inter-source relations. Then two aspects of sourcereliability are derived from these ...


Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu Nov 2017

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifying true values of data items of interest from conflicting multi-sourced data. Although considerable research efforts have been conducted on this topic, existing approaches generally assume every data item has exactly one true value, which fails to reflect the real world where data items with multiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items. SourceVote models the endorsement relations among sources by quantifying their two-sided inter-source agreements. In particular, two graphs are constructed to model inter-source relations. Then two ...


All-Dielectric Metamaterials: Irrelevance Of Negative Refraction To Overlapped Mie Resonances, Navid Gandji, George Semouchkin, Elena Semouchkina Oct 2017

All-Dielectric Metamaterials: Irrelevance Of Negative Refraction To Overlapped Mie Resonances, Navid Gandji, George Semouchkin, Elena Semouchkina

Michigan Tech Publications

All-dielectric metamaterials comprised of identical resonators draw a lot of attention as low-loss media providing for negative refraction, which is commonly attributed to the double negativity of effective material parameters caused by overlapping of Mie resonances. We study dispersion diagrams of such metamaterials composed of dielectric rod arrays and show that bandwidths of positive and negative refraction and its type are irrelevant to the negativity of effective parameters; instead, they are unambiguously defined by the shape and the location of the second transmission branch in dispersion diagrams and thus can be controlled by the lattice constants.


Benchmarking Estonia's Cyber Security: An On-Ramping Methodology For Rapid Adoption And Implementation, Ernest Wong, Nan Porter, Mckinnon Hokanson, Bing Bing Xie Oct 2017

Benchmarking Estonia's Cyber Security: An On-Ramping Methodology For Rapid Adoption And Implementation, Ernest Wong, Nan Porter, Mckinnon Hokanson, Bing Bing Xie

Research Papers

In April of 2007, Estonia fell victim to a series of distributed denial of service (DDoS) attacks that crippled its government websites, email servers, media outlets, and banking system for nearly a month. Due to the devastating effects of these cyber attacks, Estonia took great efforts to strengthen its cyber security protocols. This research analyzes the reforms that Estonia has implemented in its domestic and foreign policies and attempts to determine if any of it systemic improvements can help to also bolster cyber security in the United States (US). The findings from this research are that Estonia’s policy reforms ...


Formal Performance Guarantees For An Approach To Human In The Loop Robot Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang Oct 2017

Formal Performance Guarantees For An Approach To Human In The Loop Robot Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang

Faculty Publications

Abstract— A key challenge in the automatic verification of robot mission software, especially critical mission software, is to be able to effectively model the performance of a human operator and factor that into the formal performance guarantees for the mission. We present a novel approach to modelling the skill level of the operator and integrating it into automatic verification using a linear Gaussians model parameterized by experimental calibration. Our approach allows us to model different skill levels directly in terms of the behavior of the lumped, robot plus operator, system.

Using MissionLab and VIPARS (a behavior-based robot mission verification module ...


Teaching Image Processing And Visualization Principles To Medicine Students, Christina Gillmann, Thomas Wischgoll, Jose T. Hernandez, Hans Hagen Oct 2017

Teaching Image Processing And Visualization Principles To Medicine Students, Christina Gillmann, Thomas Wischgoll, Jose T. Hernandez, Hans Hagen

Computer Science and Engineering Faculty Publications

Although image processing becomes increasingly important in most applications such as medicine, image processing and visualization is usually not a part of the medical education and therefore not widely spread in clinical daily routine. Contrary to students from computer science, medical students are usually not familiar to computational models or algorithms and require a different view of the algorithms instead of knowing each computational detail. To solve this problem this paper presents the concept of a lecture that aims to impart image processing and visualization principals for students in medicine in order to pioneer a higher acceptance and propagation of ...


What Does Explainable Ai Really Mean? A New Conceptualization Of Perspectives, Derek Doran, Sarah Schulz, Tarek R. Besold Oct 2017

What Does Explainable Ai Really Mean? A New Conceptualization Of Perspectives, Derek Doran, Sarah Schulz, Tarek R. Besold

Computer Science and Engineering Faculty Publications

We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached. The paper is motivated by a corpus analysis of NIPS, ACL, COGSCI, and ICCV/ECCV paper titles showing differences in how work on explainable AI is positioned in various fields. We close by introducing a fourth notion: truly explainable systems, where automated reasoning is central to output crafted explanations without requiring ...


Power-Efficient And Highly Scalable Parallel Graph Sampling Using Fpgas, Usman Tariq, Umer Cheema, Fahad Saeed Oct 2017

Power-Efficient And Highly Scalable Parallel Graph Sampling Using Fpgas, Usman Tariq, Umer Cheema, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Energy efficiency is a crucial problem in data centers where big data is generally represented by directed or undirected graphs. Analysis of this big data graph is challenging due to volume and velocity of the data as well as irregular memory access patterns. Graph sampling is one of the most effective ways to reduce the size of graph while maintaining crucial characteristics. In this paper we present design and implementation of an FPGA based graph sampling method which is both time- and energy-efficient. This is in contrast to existing parallel approaches which include memory-distributed clusters, multicore and GPUs. Our ...