Social and Behavioral Sciences Commons^™

Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox

Research Collection School Of Computing and Information Systems

Singapore faces a major challenge in providing care and support for senior citizens due to its rapidlyageing population and declining old-age support ratio. The concept of Ageing-in-Place was introduced by the Singapore government [1] to allow older people to live independently in their own homes and communities so that the need for institutionalised care will only be utilised when necessary. We have three fundamental questions that this project will answer: 1. How to make community care serviceseffective through innovations in care delivery? How to lower the cost of service delivery and improve 2. productivity of caregivers, by leveraging information and …

Designing Bus Transit Services For Routine Crowd Situations At Large Event Venues, Jianli Du, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We are concerned with the routine crowd management problem after a major event at a known venue. Without properly design complementary transport services, such sudden crowd build-ups will overwhelm the existing infrastructure. In this paper, we introduce a novel flow-rate based model to model the dynamic movement of passengers over the transportation flow network. Based on this basic model, an integer linear programming model is proposed to solve the bus transit problem permanently. We validate our model against a real scenario in Singapore, where a newly constructed mega-stadium hosts various large events regularly. The results show that the proposed approach …

Retail Precinct Management: A Case Of Commercial Decentralization In Singapore, Robert De Souza, Hoong Chuin Lau, Mark Goh, Lindawati, Wee-Siong Ng, Puay-Siew Tan

Research Collection School Of Computing and Information Systems

The synchronized last mile logistics concept seeks to address, through coordinated collaboration, several challenges that hinder reliability, cost efficiency, effective resource planning, scheduling and utilization; and increasingly, sustainability objectives. Subsequently, the meeting of service level and contractual commitments are competitively impacted with any loss of efficiency. These challenges, against a backdrop of Singapore, can essentially be addressed in selected industry sectors through a better understanding of logistics structures; innovative supply chain designs and coordination of services, operations and processes coupled with concerted policies and supply chain strategies.

Two Correspondence Problems Easier Than One, Aaron Michaux, Zygmunt Pizlo

MODVIS Workshop

Computer vision research rarely makes use of symmetry in stereo reconstruction despite its established importance in perceptual psychology. Such stereo reconstructions produce visually satisfying figures with precisely located points and lines, even when input images have low or moderate resolution. However, because few invariants exist, there are no known general approaches to solving symmetry correspondence on real images. The problem is significantly easier when combined with the binocular correspondence problem, because each correspondence problem provides strong non-overlapping constraints on the solution space. We demonstrate a system that leverages these constraints to produce accurate stereo models from pairs of binocular images …

Formal Aspects Of Non-Rigid-Shape-From-Motion Perception, Vicky Froyen, Qasim Zaidi

MODVIS Workshop

Our world is full of objects that deform over time, for example animals, trees and clouds. Yet, the human visual system seems to readily disentangle object motions from non-rigid deformations, in order to categorize objects, recognize the nature of actions such as running or jumping, and even to infer intentions. A large body of experimental work has been devoted to extracting rigid structure from motion, but there is little experimental work on the perception of non-rigid 3-D shapes from motion (e.g. Jain, 2011). Similarly, until recently, almost all formal work had concentrated on the rigid case. In the last fifteen …

Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker

MODVIS Workshop

Visual attention models can explain a rich set of physiological data (Reynolds & Heeger, 2009, Neuron), but can rarely link these findings to real-world tasks. Here, we would like to narrow this gap with a novel, physiologically grounded model of visual attention by demonstrating its objects recognition abilities in noisy scenes.

To base the model on physiological data, we used a recently developed microcircuit model of visual attention (Beuth & Hamker, in revision, Vision Res) which explains a large set of attention experiments, e.g. biased competition, modulation of contrast response functions, tuning curves, and surround suppression. Objects are represented by …

Object-Based Classification Of Earthquake Damage From High-Resolution Optical Imagery Using Machine Learning, James Bialas

Dissertations, Master's Theses and Master's Reports - Open

Object-based approaches to the segmentation and supervised classification of remotely-sensed images yield more promising results compared to traditional pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods and trial and error are often used, but time consuming and yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time sensitive applications such as earthquake induced damage assessment.

Our research takes a systematic approach to evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely-sensed imagery using Trimble’s eCognition …

Potential Of Cognitive Computing And Cognitive Systems, Ahmed K. Noor

Computational Modeling & Simulation Engineering Faculty Publications

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The …

A Taste Of Armageddon: When Warring Is Done By Drones And Robots, Brian Stiltner

Philosophy, Theology and Religious Studies Faculty Publications

Discusses the increasing use of drones and weaponized robots. Argues that the international community must put firm ethical guidelines in place before the technology becomes rampant.

Metadata And Linked Data In Word Sense Disambiguation, Matthew Corsmeier

Library Philosophy and Practice (e-journal)

Word Sense Disambiguation (WSD) can be assisted by taking advantage of the metadata embedded in the various ontologies, lexica, databases, etc… that exist in the Semantic Web. Automated processes that exploit the links already present in the Semantic Web can strengthen parsing of word senses by using user-contributed and semantically-linked data. These processes are only possible because of a commitment to interoperability and the creation of shared standards. This paper will review some of the most heavily used Linguistic Linked Open Data (LLOD) tools and models which show the most promise for using metadata to alleviate problems caused by polysemous …

Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l₁/l_q regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

Non-Myopic Negotiators See What's Best, Yair Zick, Yoram Bachrach, Ian Kash, Peter Key

Yair Zick

No abstract provided.