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An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang 2015 University of Dayton

An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang

Computer Science Faculty Publications

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …


Preface To Wi-Iat 2015 Workshops And Demo/Posters, Ah-hwee TAN, Yuefeng LI 2015 Singapore Management University

Preface To Wi-Iat 2015 Workshops And Demo/Posters, Ah-Hwee Tan, Yuefeng Li

Research Collection School Of Computing and Information Systems

This volume contains the papers selected for presentation at the workshops and demonstration/poster track as part of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15) and 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15) held from 6 to 9 December 2015 in Singapore.


When Disclosure Is Involuntary: Empowering Users With Control To Reduce Concerns, David W. Wilson, Ryan M. Schuetzler, Bradley Dorn, Jeffrey Gainer Proudfoot 2015 University of Oklahoma Norman Campus

When Disclosure Is Involuntary: Empowering Users With Control To Reduce Concerns, David W. Wilson, Ryan M. Schuetzler, Bradley Dorn, Jeffrey Gainer Proudfoot

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Modern organizations must carefully balance the practice of gathering large amounts of valuable data from individuals with the associated ethical considerations and potential negative public image inherent in breaches of privacy. As it becomes increasingly commonplace for many types of information to be collected without individuals' knowledge or consent, managers and researchers alike can benefit from understanding how individuals react to such involuntary disclosures, and how these reactions can impact evaluations of the data-collecting organizations. This research develops and empirically tests a theoretical model that shows how empowering individuals with a sense of control over their personal information can help …


Information Technology For Development In Small And Medium-Sized Enterprises, Jie Xiong, Sajda Qureshi 2015 University of Nebraska at Omaha

Information Technology For Development In Small And Medium-Sized Enterprises, Jie Xiong, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Development is a concept that is often used to describe growth in organizations and the regions in which they reside. While research in Information Systems (IS) recognizes the importance of Information Technology (IT) in improving the organizational performance, a great deal of emphasis is given towards understanding large organizations. While social-economic development and transformation relies on new technological infrastructures and organizational changes, there is still a weak link between the organization studies with Information Technology (IT) as it relates to the growth of organizations. It appears that a greater research focus is needed in understanding the use of IT in …


Mobilerp, Anthony Fata 2015 California Polytechnic State University, San Luis Obispo

Mobilerp, Anthony Fata

Computer Engineering

MobilERP is a system that increases traceability of parts in a manufacturing process in a simple paperless way. The system contains three components, a desktop application, a mobile app, and a database. The mobile application allows employees to scan (using a bar code scanner) parts that they are working/finishing on during the manufacturing process. As the part goes down the assembly line, individuals will barcode scan using the app to track the progress. These changes would get updated to the database, where then the designated person can track the progress of the part as well as any problems or concerns …


Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William YEOH, Pradeep VARAKANTHAM, Xiaoxun SUN, Sven KOENIG 2015 Singapore Management University

Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig

Research Collection School Of Computing and Information Systems

Distributed constraint optimization (DCOP) problems are well-suited for modeling multi-agent coordination problems. However, it only models static problems, which do not change over time. Consequently, researchers have introduced the Dynamic DCOP (DDCOP) model to model dynamic problems. In this paper, we make two key contributions: (a) a procedure to reason with the incremental changes in DDCOPs and (b) an incremental pseudo-tree construction algorithm that can be used by DCOP algorithms such as any-space ADOPT and any-space BnB-ADOPT to solve DDCOPs. Due to the incremental reasoning employed, our experimental results show that any-space ADOPT and any-space BnB-ADOPT are up to 42% …


Content-Based Visual Landmark Search Via Multimodal Hypergraph Learning, Lei ZHU, Jialie SHEN, Hai JIN, Ran ZHENG, Liang XIE 2015 Huazhong University of Science and Technology

Content-Based Visual Landmark Search Via Multimodal Hypergraph Learning, Lei Zhu, Jialie Shen, Hai Jin, Ran Zheng, Liang Xie

Research Collection School Of Computing and Information Systems

While content-based landmark image search has recently received a lot of attention and became a very active domain, it still remains a challenging problem. Among the various reasons, high diverse visual content is the most significant one. It is common that for the same landmark, images with a wide range of visual appearances can be found from different sources and different landmarks may share very similar sets of images. As a consequence, it is very hard to accurately estimate the similarities between the landmarks purely based on single type of visual feature. Moreover, the relationships between landmark images can be …


Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei MENG, Ah-hwee TAN, Donald C. WUNSCH 2015 Singapore Management University

Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the …


A Misspecification Test For Logit Based Route Choice Models, Tien MAI, Emma FREJINGER, Fabian BASTIN 2015 Singapore Management University

A Misspecification Test For Logit Based Route Choice Models, Tien Mai, Emma Frejinger, Fabian Bastin

Research Collection School Of Computing and Information Systems

The multinomial logit (MNL) model is often used for analyzing route choices in real networks in spite of the fact that path utilities are believed to be correlated. Yet, statistical tests for model misspecification are rarely used. This paper shows how the information matrix test for model misspecification proposed byWhite (1982) can be applied to test path-based and link-based MNL route choice models.We present a Monte Carlo experiment using simulated data to assess the size and the power of the test and to compare its performance with the IIA (Hausman and McFadden, 1984) and McFadden–Train Lagrange multiplier (McFadden and Train, …


On Neighborhood Effects In Location-Based Social Networks, Thanh-Nam DOAN, Freddy Chong-Tat CHUA, Ee-Peng LIM 2015 Singapore Management University

On Neighborhood Effects In Location-Based Social Networks, Thanh-Nam Doan, Freddy Chong-Tat Chua, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we analyze factors that determine the check-in decisions of users on venues using a location-based social network dataset. Based on a Foursquare dataset constructed from Singapore-based users, we devise a stringent criteria to identify the actual home locations of a subset of users. Using these users' check-ins, we aim to ascertain the neighborhood effect on the venues visited, compared with the activity level of users. We further formulate the check-in count prediction and check-in prediction tasks. A comprehensive set of features have been defined and they encompass information from users, venues, their neighbors, and friendship networks. We …


Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena VALERA, Hwee Xian TAN 2015 Singapore Management University

Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena Valera, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …


Flow Experience In Virtual Worlds: Individuals Versus Dyads, Fiona Fui-hoon NAH, Brenda ESCHENBRENNER 2015 Singapore Management University

Flow Experience In Virtual Worlds: Individuals Versus Dyads, Fiona Fui-Hoon Nah, Brenda Eschenbrenner

Research Collection School Of Computing and Information Systems

Flow is a state of mind in which one is deeply absorbed and immersed in an activity to the point where nothing else matters. Although flow can occur in solitary and social contexts, which context fosters greater flow is unclear. Consistent with self-determination theory, dyads working collaboratively achieved higher states of flow than individuals working alone. In other words, dyads achieved higher states of focused concentration and experienced greater temporal dissociation than individuals working alone. Surprisingly and contradictory to previous findings, dyads did not experience greater enjoyment than individuals working alone. We attributed this surprising finding to the hedonic nature …


Understanding Psychophysiological Correlates Of User Experience Using Electroencephalogram (Eeg), Fiona Fui-hoon NAH, Keng SIAU, Randall MINAS, Nathan W. TWYMAN, Nicholas A. ROLLINS, Wenbo WANG, Xi WANG 2015 Singapore Management University

Understanding Psychophysiological Correlates Of User Experience Using Electroencephalogram (Eeg), Fiona Fui-Hoon Nah, Keng Siau, Randall Minas, Nathan W. Twyman, Nicholas A. Rollins, Wenbo Wang, Xi Wang

Research Collection School Of Computing and Information Systems

The objective of this research is to understand psychophysiological correlates of user experience using electroencephalogram (EEG). We will conduct an experimental study to assess the psychophysiological differences across three states of user experience – flow, boredom, and anxiety – and compare them with the neutral state as a baseline. EEG measurement provides a plethora of data that can be decomposed using different analytical procedures. We will utilize one type of analysis, timefrequency decomposition, to examine changes in frequency (e.g., alpha/beta/theta band) over time. These frequency bands correlate with different cognitive states. In this study, we will use Event Related Spectral …


A Benchmark And Comparative Study Of Video-Based Face Recognition On Cox Face Database, Zhiwu HUANG, S. SHAN, R. WANG, H. ZHANG, S. LAO, A. KUERBAN, X. CHEN 2015 Singapore Management University

A Benchmark And Comparative Study Of Video-Based Face Recognition On Cox Face Database, Zhiwu Huang, S. Shan, R. Wang, H. Zhang, S. Lao, A. Kuerban, X. Chen

Research Collection School Of Computing and Information Systems

Face recognition with still face images has been widely studied, while the research on video-based face recognition is inadequate relatively, especially in terms of benchmark datasets and comparisons. Real-world video-based face recognition applications require techniques for three distinct scenarios: 1) Videoto-Still (V2S); 2) Still-to-Video (S2V); and 3) Video-to-Video (V2V), respectively, taking video or still image as query or target. To the best of our knowledge, few datasets and evaluation protocols have benchmarked for all the three scenarios. In order to facilitate the study of this specific topic, this paper contributes a benchmarking and comparative study based on a newly collected …


A Bayesian Recommender Model For User Rating And Review Profiling, Mingming JIANG, Dandan SONG, Lejian LIAO, Feida ZHU 2015 Singapore Management University

A Bayesian Recommender Model For User Rating And Review Profiling, Mingming Jiang, Dandan Song, Lejian Liao, Feida Zhu

Research Collection School Of Computing and Information Systems

Intuitively, not only do ratings include abundant information for learning user preferences, but also reviews accompanied by ratings. However, most existing recommender systems take rating scores for granted and discard the wealth of information in accompanying reviews. In this paper, in order to exploit user profiles' information embedded in both ratings and reviews exhaustively, we propose a Bayesian model that links a traditional Collaborative Filtering (CF) technique with a topic model seamlessly. By employing a topic model with the review text and aligning user review topics with "user attitudes" (i.e., abstract rating patterns) over the same distribution, our method achieves …


Progressive Sequence Matching For Adl Plan Recommendation, Shan GAO, Di WANG, Ah-hwee TAN, Chunyan MIAO 2015 Singapore Management University

Progressive Sequence Matching For Adl Plan Recommendation, Shan Gao, Di Wang, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

Activities of Daily Living (ADLs) are indicatives of a person’s lifestyle. In particular, daily ADL routines closely relate to a person’s well-being. With the objective of promoting active lifestyles, this paper presents an agent system that provides recommendations of suitable ADL plans (i.e., selected ADL sequences) to individual users based on the more active lifestyles of the others. Specifically, we develop a set of quantitative measures, named wellness scores, spanning the evaluation across the physical, cognitive, emotion, and social aspects based on his or her ADL routines. Then we propose an ADL sequence learning model, named Recommendation ADL ART, or …


Modeling Social Media Content With Word Vectors For Recommendation, Ying DING, Jing JIANG 2015 Singapore Management University

Modeling Social Media Content With Word Vectors For Recommendation, Ying Ding, Jing Jiang

Research Collection School Of Computing and Information Systems

In social media, recommender systems are becoming more and more important. Different techniques have been designed for recommendations under various scenarios, but many of them do not use user-generated content, which potentially reflects users’ opinions and interests. Although a few studies have tried to combine user-generated content with rating or adoption data, they mostly reply on lexical similarity to calculate textual similarity. However, in social media, a diverse range of words is used. This renders the traditional ways of calculating textual similarity ineffective. In this work, we apply vector representation of words to measure the semantic similarity between text. We …


Active Crowdsourcing For Annotation, Shuji HAO, Chunyan MIAO, Steven C. H. HOI, Peilin ZHAO 2015 Nanyang Technological University

Active Crowdsourcing For Annotation, Shuji Hao, Chunyan Miao, Steven C. H. Hoi, Peilin Zhao

Research Collection School Of Computing and Information Systems

Crowdsourcing has shown great potential in obtaining large-scale and cheap labels for different tasks. However, obtaining reliable labels is challenging due to several reasons, such as noisy annotators, limited budget and so on. The state-of-the-art approaches, either suffer in some noisy scenarios, or rely on unlimited resources to acquire reliable labels. In this article, we adopt the learning with expert~(AKA worker in crowdsourcing) advice framework to robustly infer accurate labels by considering the reliability of each worker. However, in order to accurately predict the reliability of each worker, traditional learning with expert advice will consult with external oracles~(AKA domain experts) …


Supercnn: A Superpixelwise Convolutional Neural Network For Salient Object Detection, Shengfeng HE, Rynson W.H. LAU, Wenxi LIU, Zhe HUANG, Qingxiong YANG 2015 Singapore Management University

Supercnn: A Superpixelwise Convolutional Neural Network For Salient Object Detection, Shengfeng He, Rynson W.H. Lau, Wenxi Liu, Zhe Huang, Qingxiong Yang

Research Collection School Of Computing and Information Systems

Existing computational models for salient object detection primarily rely on hand-crafted features, which are only able to capture low-level contrast information. In this paper, we learn the hierarchical contrast features by formulating salient object detection as a binary labeling problem using deep learning techniques. A novel superpixelwise convolutional neural network approach, called SuperCNN, is proposed to learn the internal representations of saliency in an efficient manner. In contrast to the classical convolutional networks, SuperCNN has four main properties. First, the proposed method is able to learn the hierarchical contrast features, as it is fed by two meaningful superpixel sequences, which …


Bring-Your-Own-Application (Byoa): Optimal Stochastic Application Migration In Mobile Cloud Computing, Jonathan David CHASE, Dusit NIYATO, Sivadon CHAISIRI 2015 Singapore Management University

Bring-Your-Own-Application (Byoa): Optimal Stochastic Application Migration In Mobile Cloud Computing, Jonathan David Chase, Dusit Niyato, Sivadon Chaisiri

Research Collection School Of Computing and Information Systems

The increasing popularity of using mobile devices in a work context, has led to the need to be able to support more powerful computation. Users no longer remain in an office or at home to conduct their activities, preferring libraries and cafes. In this paper, we consider a mobile cloud computing scenario in which users bring their own mobile devices and are offered a variety of equipment, e.g., desktop computer, smart- TV, or projector, to migrate their applications to, so as to save battery life, improve usability and performance. We formulate a stochastic optimization problem to optimize the allocation of …


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