Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys,
2017
Institute of Technology, Blanchardstown
Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys, Paul Stacey, Damon Berry
Conference papers
This paper describes the ongoing work of the authors in translating two-level system design techniques used in Health Informatics to the Earth Systems Science domain. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved. Translating two-level modelling techniques to a new domain is a complex task. A proof-of-concept archetype enabled data buoy eco-system is presented. The concept of operational templates-as-a service is proposed. Design recommendations and implementation experiences of re-working the proposed architecture to run …
A Survey Of Addictive Software Design,
2017
California Polytechnic State University at San Luis Obispo
A Survey Of Addictive Software Design, Chauncey J. Neyman
Computer Science and Software Engineering
The average smartphone owner checks their phone more than 150 times per day. As of 2015, 62% of smartphone users had used their phone to look up information about a health condition, while 57% had used their phone to do online banking. Mobile platforms have become the dominant medium of human-computer interaction. So how have these devices established themselves as our go to connection to the Internet? The answer lies in addictive design. Software designers have become well versed in creating software that captivates us at a primal level. In this article, we survey addictive software design strategies, their bases …
Farmbot Rfid Integration,
2017
California Polytechnic State University, San Luis Obispo
Farmbot Rfid Integration, Laura R. Swart
Computer Engineering
The purpose of this project is to assist the company FarmBot improve their product by adding RFID tracking to the FarmBot robot. RFID tracking will allow the robot to select and pick up tool heads without any user interference.
Blend It Wine Blending Distribution System,
2017
California Polytechnic State University, San Luis Obispo
Blend It Wine Blending Distribution System, Connor Clarry, Russell Temple, Matt Moren
Mechanical Engineering
No abstract provided.
Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking,
2017
Singapore Management University
Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian
Research Collection School Of Computing and Information Systems
Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of web APIs that can be used to implement the project. At its heart, WebAPIRec employs …
Scan: Multi-Hop Calibration For Mobile Sensor Arrays,
2017
Singapore Management University
Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele
Research Collection School Of Computing and Information Systems
Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor …
Sap: Improving Continuous Top-K Queries Over Streaming Data,
2017
Northeastern University
Sap: Improving Continuous Top-K Queries Over Streaming Data, Rui Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng, Guoren Wang
Research Collection School Of Computing and Information Systems
Continuous top-k query over streaming data is a fundamental problem in database. In this paper, we focus on the sliding window scenario, where a continuous top-k query returns the top-k objects within each query window on the data stream. Existing algorithms support this type of queries via incrementally maintaining a subset of objects in the window and try to retrieve the answer from this subset as much as possible whenever the window slides. However, since all the existing algorithms are sensitive to query parameters and data distribution, they all suffer from expensive incremental maintenance cost. In this paper, we propose …
Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications,
2017
Singapore Management University
Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The rapid emergence of head-mounted devices such as the Microsoft Holo-lens enables a wide variety of continuous vision applications. Such applications often adopt deep-learning algorithms such as CNN and RNN to extract rich contextual information from the first-person-view video streams. Despite the high accuracy, use of deep learning algorithms in mobile devices raises critical challenges, i.e., high processing latency and power consumption. In this paper, we propose DeepMon, a mobile deep learning inference system to run a variety of deep learning inferences purely on a mobile device in a fast and energy-efficient manner. For this, we designed a suite of …
Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications,
2017
Singapore Management University
Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Deep learning has revolutionized vision sensing applications in terms of accuracy comparing to other techniques. Its breakthrough comes from the ability to extract complex high level features directly from sensor data. However, deep learning models are still yet to be natively supported on mobile devices due to high computational requirements. In this paper, we present DeepMon, a next generation of DeepSense [1] framework, to enable deep learning models on conventional mobile devices (e.g. Samsung Galaxy S7) for continuous vision sensing applications. Firstly, Deep-Mon exploits similarity between consecutive video frames for intermediate data caching within models to enhance inference latency. Secondly, …
Low-Noise Speed-Optimized Large Area Cmos Avalanche Photodetector For Visible Light Communication,
2017
University of New Mexico
Low-Noise Speed-Optimized Large Area Cmos Avalanche Photodetector For Visible Light Communication, Md. Mottaleb Hossain, Sagar Ray, Jeng Shiuh Cheong, Liang Qiao, Aina N.A.P. Baharuddin, Mona Mostafa Hella, John P.R. David, Majeed M. Hayat
Electrical and Computer Engineering Faculty Research and Publications
Mean-gain and excess-noise measurements are presented for a 350 × 350 μm 2 P+/N-well/P-sub and a 270 × 270 μm 2 N-well/P-sub avalanche photodetectors fabricated using 0.13-μm CMOS technology. The active area of the P+/N-well/P-sub device was divided into multiple subsections to decrease transit time and increase speed. For the P+/N-well structure, remarkably low excess-noise factors of 4.1 and 4 were measured at a mean gain of 16 corresponding to a k value of approximately 0.1, using a 542 (633) nm laser. For a variant N-well/P-sub structure, excess-noise factors of 6.5 and 6.2 were measured at a mean-gain of 16 …
Optimizing Cloud-Service Performance: Efficient Resource Provisioning Via Optimal Workload Allocation,
2017
University of New Mexico
Optimizing Cloud-Service Performance: Efficient Resource Provisioning Via Optimal Workload Allocation, Zhuoyao Wang, Majeed M. Hayat, Nasir Ghani, Khaled B. Shaban
Electrical and Computer Engineering Faculty Research and Publications
Cloud computing is being widely accepted and utilized in the business world. From the perspective of businesses utilizing the cloud, it is critical to meet their customers' requirements by achieving service-level-objectives. Hence, the ability to accurately characterize and optimize cloud-service performance is of great importance. In this paper a stochastic multi-tenant framework is proposed to model the service of customer requests in a cloud infrastructure composed of heterogeneous virtual machines. Two cloud-service performance metrics are mathematically characterized, namely the percentile and the mean of the stochastic response time of a customer request, in closed form. Based upon the proposed multi-tenant …
Scalable And Fully Distributed Localization In Large-Scale Sensor Networks,
2017
Old Dominion University
Scalable And Fully Distributed Localization In Large-Scale Sensor Networks, Miao Jin, Su Xia, Hongyi Wu, Xianfeng David Gu
Electrical & Computer Engineering Faculty Publications
This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of …
Multi-Population-Based Differential Evolution Algorithm For Optimization Problems,
2017
New Jersey Institute of Technology
Multi-Population-Based Differential Evolution Algorithm For Optimization Problems, Ishani Chatterjee
Theses
A differential evolution (DE) algorithm is an evolutionary algorithm for optimization problems over a continuous domain. To solve high dimensional global optimization problems, this work investigates the performance of differential evolution algorithms under a multi-population strategy. The original DE algorithm generates an initial set of suitable solutions. The multi-population strategy divides the set into several subsets. These subsets evolve independently and connect with each other according to the DE algorithm. This helps in preserving the diversity of the initial set. Furthermore, a comparison of combination of different mutation techniques on several optimization algorithms is studied to verify their performance. Finally, …
Decision Tree Rule-Based Feature Selection For Imbalanced Data,
2017
New Jersey Institute of Technology
Decision Tree Rule-Based Feature Selection For Imbalanced Data, Haoyue Liu
Theses
A class imbalance problem appears in many real world applications, e.g., fault diagnosis, text categorization and fraud detection. When dealing with an imbalanced dataset, feature selection becomes an important issue. To address it, this work proposes a feature selection method that is based on a decision tree rule and weighted Gini index. The effectiveness of the proposed methods is verified by classifying a dataset from Santander Bank and two datasets from UCI machine learning repository. The results show that our methods can achieve higher Area Under the Curve (AUC) and F-measure. We also compare them with filter-based feature selection approaches, …
Preemptive Efficient Queueing For Scheduling Deadline-Bound Data Center Flows,
2017
New Jersey Institute of Technology
Preemptive Efficient Queueing For Scheduling Deadline-Bound Data Center Flows, Vinaykrishna Gopalakrishna
Theses
This thesis introduces a new deadline aware flow scheduling scheme called Preemptive Efficient Queuing (PEQ). Unlike other schemes which use policies like EDF, SJF or fair share, this scheme aims to procrastinate flows as much as they can afford to, while keeping with their deadlines. Thereby, PEQ prioritizes more urgent flows that have shorter time to procrastinate, or cushion time. Results of PEQ are compared with state-of-the-art schemes for the transport of data-center flows, such as Preemptive Distributed Quick (PDQ) and Deadline-Driven Delivery (D3). The results show that PEQ outperforms D3 and PDQ. We identify results …
Adaptive Screen Generation For Mobile Devices,
2017
Technological University Dublin
Adaptive Screen Generation For Mobile Devices, Caoimhín O’Nualláin, Sam Redfern
The ITB Journal
When one looks at any learning software - eLearning based or not - one cannot sometims help but think why the authors could not have organized the screens (or the means of navigation) in a way similar to some other piece of software which the user has used or come accustomed to using. In this paper it is hoped to be able to achieve just that. That is, to accommodate the adaptive screen design by building up a profile about the user which can capture the learning styles of the user and personal preferences, and to be able to have …
Voice Activated Command And Control With Speech Recognition Over Wireless Networks,
2017
Technological University Dublin
Voice Activated Command And Control With Speech Recognition Over Wireless Networks, Tony Ayres, Brian Nolan
The ITB Journal
This paper presents work conducted to date on the development of a voice activated command and control framework specifically for the control of remote devices in a ubiquitous computing environment. The prototype device is a Java controlled Lego Mindstorm robot. The research considers three different scenario configurations. A recognition grammar for command and control of the robot has been created and implemented in Java, in part in the recognition engine and in part on the robot. The physical topology involves Java at each node endpoint, that is, at the handheld PC (iPaq), the PC workstation, the Linux server and onboard …
Statistical Language Models For Graphical Object Recognition,
2017
Technological University Dublin
Statistical Language Models For Graphical Object Recognition, Laura Keyes, Andrew O'Sullivan, Adam Winstanley
The ITB Journal
This paper explores automatic recognition and semantic capture in vector graphics for graphical information systems. The low-level graphical content of graphical documents, such as a map or architectural drawing, are often captured manually and the encoding of the semantic content seen as an extension of this. The large quantity of new and archived graphical data available on paper makes automatic structuring of such graphical data desirable. A successful method for recognising text data uses statistical language models. This work will investigate and evaluate similar and adapted statistical models (Statistical Graphical Langauge Models, SGLM) to graphical languages based on the associations …
Interactive 2d And 3d Graphics Over The World-Wide Web With Actionscript,
2017
Technological University Dublin
Interactive 2d And 3d Graphics Over The World-Wide Web With Actionscript, Hugh Mccabe
The ITB Journal
Many efforts have been made to provide a mechanism for delivering interactive 3D content over the World-Wide Web. The majority of the solutions put forward require the use of a proprietary plug-in on the client browser and none of these required plug-ins have so far become part of the standard browser installation package. The Macromedia Flash player has however achieved near ubiquitous status as the standard plug-in for displaying interactive multimedia and graphics content. Flash does not provide native support for 3D graphics but the recent addition of the Shape Drawing API opens up the possibility of developers using ActionScript …
Voice Enabled Indoor Localisation,
2017
Technological University Dublin
Voice Enabled Indoor Localisation, Kieran Harkin, Kevin Curran, Eoghan Furey
The ITB Journal
The ability to track objects in real time offers a wide range of beneficial applications that include safety, security and the supply chain. The problem with location based systems is that they can be inconvenient and time-consuming to locate an object. A user has to access a computer and log onto a location system to locate an object. There are several problems with current location determination interfaces. Firstly a user has to log on to a computer; this can be inconvenient and time consuming as the user may have to locate a computer (which may be in another area of …
