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Practical Server-Side Indoor Localization: Tackling Cardinality Outlier Challenges, Anuradha RAVI, Archan MISRA 2020 Singapore Management University

Practical Server-Side Indoor Localization: Tackling Cardinality Outlier Challenges, Anuradha Ravi, Archan Misra

Research Collection School Of Computing and Information Systems

In spite of many advances in indoor localization techniques, practical implementation of robust device independent, server-side Wi-Fi localization (i.e., without any active participation of client devices) remains a challenge. This work utilizes an operationally-deployed Wi-Fi based indoor location infrastructure, based on the classical RADAR algorithm, to tackle two such practical challenges: (a) low cardinality, whereby only the associated AP generates sufficient RSSI reports and (b) outlier identification, which requires explicit identification of mobile clients that are attached to the Wi-Fi network but outside the fingerprinted region. To tackle the low-cardinality problem, we present a technique that uses cardinality changes to …


Crowdsourcing Image Extraction And Annotation: Software Development And Case Study, Ana Jofre, Vincent Berardi, Kathleen P.J. Brennan, Aisha Cornejo, Carl Bennett, John Harlan 2020 SUNY Polytechnic

Crowdsourcing Image Extraction And Annotation: Software Development And Case Study, Ana Jofre, Vincent Berardi, Kathleen P.J. Brennan, Aisha Cornejo, Carl Bennett, John Harlan

Psychology Faculty Articles and Research

We describe the development of web-based software that facilitates large-scale, crowdsourced image extraction and annotation within image-heavy corpora that are of interest to the digital humanities. An application of this software is then detailed and evaluated through a case study where it was deployed within Amazon Mechanical Turk to extract and annotate faces from the archives of Time magazine. Annotation labels included categories such as age, gender, and race that were subsequently used to train machine learning models. The systemization of our crowdsourced data collection and worker quality verification procedures are detailed within this case study. We outline a data …


Generating Peptide Mass Spectrometry Ground Truth Data, Jessica L. Henning, Rob Smith 2020 The University Of Montana

Generating Peptide Mass Spectrometry Ground Truth Data, Jessica L. Henning, Rob Smith

Graduate Student Theses, Dissertations, & Professional Papers

Very few quantitative evaluations exist for precursor mass spectrometry data due to the lack of tools for enabling the manual feature finding necessary to generate this data. Other lacks the ability to capture, edit, save, and view precursor mass spectrometry data. We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating precursor ground truth. The software retains the first version’s capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also …


A Survey Of Spatial Crowdsourcing, Yongxin TONG, Zimu ZHOU, Yuxiang ZENG, Lei CHEN, Cyrus SHAHABI 2020 Beijing University of Aeronautics and Astronautics (Beihang University)

A Survey Of Spatial Crowdsourcing, Yongxin Tong, Zimu Zhou, Yuxiang Zeng, Lei Chen, Cyrus Shahabi

Research Collection School Of Computing and Information Systems

Crowdsourcing is a computing paradigm where humans are actively involved in a computing task, especially for tasks that are intrinsically easier for humans than for computers. Spatial crowdsourcing (SC) is an increasing popular category of crowdsourcing in the era of mobile Internet and sharing economy, where tasks are spatiotemporal and must be completed at a specific location and time. In fact, spatial crowdsourcing has stimulated a series of recent industrial successes including sharing economy for urban services (Uber and Gigwalk) and spatiotemporal data collection (OpenStreetMap and Waze). This survey dives deep into the challenges and techniques brought by the unique …


Remote Communication In Wilderness Search And Rescue: Implications For The Design Of Emergency Distributed-Collaboration Tools For Network-Sparse Environments, Brennan JONES, Anthony TANG, Carman NEUSTAEDTER 2020 University of Calgary

Remote Communication In Wilderness Search And Rescue: Implications For The Design Of Emergency Distributed-Collaboration Tools For Network-Sparse Environments, Brennan Jones, Anthony Tang, Carman Neustaedter

Research Collection School Of Computing and Information Systems

Wilderness search and rescue (WSAR) requires careful communication between workers in different locations. To understand the contexts from which WSAR workers communicate and the challenges they face, we interviewed WSAR workers and observed a mock-WSAR scenario. Our findings illustrate that WSAR workers face challenges in maintaining a shared mental model. This is primarily done through distributed communication using two-way radios and cell phones for text and photo messaging; yet both implicit and explicit communication suffer. WSAR workers send messages for various reasons and share different types of information with varying levels of urgency. This warrants the use of multiple communication …


Matlabta: A Style Critiquer For Novice Engineering Students, Marissa L. Walther 2020 Michigan Technological University

Matlabta: A Style Critiquer For Novice Engineering Students, Marissa L. Walther

Dissertations, Master's Theses and Master's Reports

Novice programmers, considered to be those who have yet to understand the fundamentals of programming, exist in both engineering and computing fields. Within computing, various resources exist to help novice programmers understand fundamentals and style guidelines such as WebTA, a code critique program that gives Java students feedback about their error and style issues. There is, however, a gap in automated code critique for MATLAB, a programming language that is popular in the engineering community. When it comes to MATLAB, there are not many programs that help novices understand their errors, and even fewer that help them understand style guidelines. …


Automatically Categorizing Software Technologies, Mathieu NASSIF, Christoph TREUDE, Martin P. ROBILLARD 2020 Singapore Management University

Automatically Categorizing Software Technologies, Mathieu Nassif, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Informal language and the absence of a standard taxonomy for software technologies make it difficult to reliably analyze technology trends on discussion forums and other on-line venues. We propose an automated approach called Witt for the categorization of software technologies (an expanded version of the hypernym discovery problem). Witt takes as input a phrase describing a software technology or concept and returns a general category that describes it (e.g., integrated development environment), along with attributes that further qualify it (commercial, php, etc.). By extension, the approach enables the dynamic creation of lists of all technologies of a given type (e.g., …


Deepdrawing: A Deep Learning Approach To Graph Drawing, Yong WANG, Zhihua JIN, Qianwen WANG, Weiwei CUI, Tengfei MA, Huamin QU 2020 Singapore Management University

Deepdrawing: A Deep Learning Approach To Graph Drawing, Yong Wang, Zhihua Jin, Qianwen Wang, Weiwei Cui, Tengfei Ma, Huamin Qu

Research Collection School Of Computing and Information Systems

Node-link diagrams are widely used to facilitate network explorations. However, when using a graph drawing technique to visualize networks, users often need to tune different algorithm-specific parameters iteratively by comparing the corresponding drawing results in order to achieve a desired visual effect. This trial and error process is often tedious and time-consuming, especially for non-expert users. Inspired by the powerful data modelling and prediction capabilities of deep learning techniques, we explore the possibility of applying deep learning techniques to graph drawing. Specifically, we propose using a graph-LSTM-based approach to directly map network structures to graph drawings. Given a set of …


Planningvis: A Visual Analytics Approach To Production Planning In Smart Factories, Dong SUN, Renfei HUANG, Yuanzhe CHEN, Yong WANG, Jia ZENG, Mingxuan YUAN, Ting-Chuen PONG, Huamin QU 2020 Singapore Management University

Planningvis: A Visual Analytics Approach To Production Planning In Smart Factories, Dong Sun, Renfei Huang, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu

Research Collection School Of Computing and Information Systems

Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent of industry 4.0, plenty of data recording the status of factory resources have been collected and further involved in production planning, which brings an unprecedented opportunity to understand, evaluate and adjust complex production plans through a data-driven approach. However, developing a systematic analytics approach for production planning is challenging due to the large volume of production data, the complex dependency between products, and unexpected changes in the market and the plant. Previous studies only provide …


Towards Automated Infographic Design: Deep Learning-Based Auto-Extraction Of Extensible Timeline, Zhutian CHEN, Yun WANG, Qianwen WANG, Yong WANG, Huamin QU 2020 Singapore Management University

Towards Automated Infographic Design: Deep Learning-Based Auto-Extraction Of Extensible Timeline, Zhutian Chen, Yun Wang, Qianwen Wang, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Designers need to consider not only perceptual effectiveness but also visual styles when creating an infographic. This process can be difficult and time consuming for professional designers, not to mention non-expert users, leading to the demand for automated infographics design. As a first step, we focus on timeline infographics, which have been widely used for centuries. We contribute an end-to-end approach that automatically extracts an extensible timeline template from a bitmap image. Our approach adopts a deconstruction and reconstruction paradigm. At the deconstruction stage, we propose a multi-task deep neural network that simultaneously parses two kinds of information from a …


Estimating Refactoring Efforts For Architecture Technical Debt, Samir Deeb 2020 WVU

Estimating Refactoring Efforts For Architecture Technical Debt, Samir Deeb

Graduate Theses, Dissertations, and Problem Reports (ETD)

Paying-off the Architectural Technical Debt by refactoring the flawed code is important to control the debt and to keep it as low as possible. Project Managers tend to delay paying off this debt because they face difficulties in comparing the cost of the refactoring against the benefits they gain. For these managers to decide whether to refactor or to postpone, they need to estimate the cost and the efforts required to conduct these refactoring activities as well as to decide which flaws have higher priority to be refactored among others.

Our research is based on a dataset used by other …


V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha 2020 CUNY City College

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …


Rancang Bangun Aplikasi Status Gizi Bayi Berbasis Android, Ima Kurniastuti, Ahmad Syafiq Kamil 2019 Universitas Nahdlatul Ulama Surabaya, Indonesia

Rancang Bangun Aplikasi Status Gizi Bayi Berbasis Android, Ima Kurniastuti, Ahmad Syafiq Kamil

Elinvo (Electronics, Informatics, and Vocational Education)

Penelitian ini bertujuan untuk menghasilkan Aplikasi Status Gizi Bayi Berbasis Android yang mempermudah petugas kesehatan dalam menentukan status gizi bayi. Proses pembuatan dilakukan menggunakan Android Studio. Fitur dalam Android Studio yang dimanfaatkan adalah fitur TextView, fitur Radiogroup dan fitur Button. Input dalam aplikasi terdiri dari lima macam yaitu usia, berat badan, panjang bayi, lingkar kepala memanfaatkan fitur TextView sedangkan input jenis kelamin menggunakan fitur Radiogroup. Aplikasi memiliki dua tombol yaitu tombol hitung dan tombol reset. Tombol hitung berfungsi untuk memulai proses pemeriksaan dan tombol reset berfungsi untuk menghapus semua input yang dilakukan oleh pengguna sebelumnya sehingga memudahkan pengguna dalam melakukan …


Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger 2019 Western University

Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger

Electrical and Computer Engineering Publications

The smart grid employs computing and communication technologies to embed intelligence into the power grid and, consequently, make the grid more efficient. Machine learning (ML) has been applied for tasks that are important for smart grid operation including energy consumption and generation forecasting, anomaly detection, and state estimation. These ML solutions commonly require sufficient historical data; however, this data is often not readily available because of reasons such as data collection costs and concerns regarding security and privacy. This paper introduces a recurrent generative adversarial network (R-GAN) for generating realistic energy consumption data by learning from real data. Generativea adversarial …


Automating Software Changes Via Recommendation Systems, Xiaoyu Liu 2019 Southern Methodist University

Automating Software Changes Via Recommendation Systems, Xiaoyu Liu

Computer Science and Engineering Theses and Dissertations

As the complexity of software systems is growing tremendously, it came with increasingly sophisticated data provided during development. The systematic and large-scale accumulation of software engineering data opened up new opportunities that infer information appropriately can be helpful to software development in a given context. This type of intelligent software development tools came to be known as recommendation systems.

Recommendation Systems in Software Change (RSSCs) share commonalities with conventional recommendation systems: mainly in their usage model, the usual reliance on data mining, and in the predictive nature of their functionality. So a major challenge for designing RSSCs is to automatically …


The Effects Of Automated Grading On Computer Science Courses At The University Of New Orleans, Jerod F A Dunbar 2019 University of New Orleans, New Orleans

The Effects Of Automated Grading On Computer Science Courses At The University Of New Orleans, Jerod F A Dunbar

LSU New Orleans Theses and Dissertations

This is a study of the impacts of the incorporation, into certain points of the Computer Science degree program at the University of New Orleans, of Course Management software with an Autograding component. The software in question, developed at Carnegie Mellon University, is called “Autolab.” We begin by dissecting Autolab in order to gain an understanding of its inner workings. We can then take out understanding of its functionality and apply that to an examination of fundamental changes to courses in the time since they incorporated the software. With that, we then compare Drop, Failure, Withdrawal rate data from before …


Application Development For Goods Management System Towards Waste Minimization Options, Wan Ahmad Nadzim 2019 Universiti Malaya

Application Development For Goods Management System Towards Waste Minimization Options, Wan Ahmad Nadzim

Student Works (2020-2029)

Waste is a global concern. Increasing waste generation levels are causing the increase of waste management costs. In fact, the greatest costs of waste are measured by its impacts to the environment, society and economy. Prevention is better than cure—since all wastes come from goods, thus the best way to manage wastes is to manage goods. An application model of goods management system has been developed using GIS (Geographic Information System) and app prototyping. The primary purpose of goods management is to maximize goods and minimize waste by promoting reduction and reuse. GIS was used to perform spatial analyses on …


Optimal Management Of Virtual Infrastructures Under Flexible Cloud Service Agreements, Zhiling GUO, Jin LI, Ram RAMESH 2019 Singapore Management University

Optimal Management Of Virtual Infrastructures Under Flexible Cloud Service Agreements, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

A cloud service agreement entails the provisioning of a required set of virtual infrastructure resources at a specified level of availability to a client. The agreement also lays out the price charged to the client and a penalty to the provider when the assured availability is not met. The availability assurance involves backup resource provisioning, and the provider needs to allocate backups cost-effectively by balancing the resource-provisioning costs with the potential penalty costs. We develop stochastic dynamic optimization models of the backup resource-provisioning problem, leading to cost-effective resource-management policies in different practical settings. We present two sets of dynamic provisioning …


Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah 2019 University of Nebraska-Lincoln

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

School of Computing: Dissertations, Theses, and Student Research

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.

This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the …


Food Scan: A Yelp For Dietary Restrictions, Andrew M. Bauer, Charlie Story, Curren Taber 2019 Chapman University

Food Scan: A Yelp For Dietary Restrictions, Andrew M. Bauer, Charlie Story, Curren Taber

Student Scholar Symposium Abstracts and Posters

Food restrictions pose a serious issue for Chapman students, with consequences as extreme as anaphylactic shock and death. Our team started the Food Scan project with a simple goal of streamlining how individuals with dietary restrictions find safe places to eat or buy food. The project name highlights our intention to clarify restaurant menu items for users by displaying important allergen and dietary information. Using Human-Computer Interaction methods, our team chose to develop a technology that is usable, effective, enjoyable, and inclusive by involving users during the entire design process. By integrating multimodal interfaces (including speech to text inputs), we …


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