Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (3441)
- Software Engineering (2143)
- Artificial Intelligence and Robotics (1664)
- Information Security (1056)
- Numerical Analysis and Scientific Computing (1024)
-
- Graphics and Human Computer Interfaces (921)
- Engineering (857)
- Social and Behavioral Sciences (661)
- Business (625)
- Theory and Algorithms (493)
- Computer Engineering (431)
- Operations Research, Systems Engineering and Industrial Engineering (399)
- Programming Languages and Compilers (379)
- OS and Networks (322)
- Communication (297)
- Social Media (240)
- Public Affairs, Public Policy and Public Administration (207)
- Transportation (185)
- Medicine and Health Sciences (178)
- Education (164)
- Management Information Systems (164)
- Data Storage Systems (160)
- E-Commerce (146)
- Health Information Technology (107)
- International and Area Studies (107)
- Asian Studies (106)
- Technology and Innovation (100)
- Digital Communications and Networking (96)
- Keyword
-
- Deep learning (122)
- Machine learning (121)
- Social media (74)
- Artificial intelligence (70)
- Reinforcement learning (69)
-
- Data mining (64)
- Privacy (61)
- Cloud computing (58)
- Deep Learning (56)
- Empirical study (54)
- Optimization (53)
- Security (53)
- Visualization (51)
- Software engineering (49)
- Training (49)
- Neural networks (48)
- Online learning (48)
- Task analysis (48)
- Anomaly detection (47)
- Singapore (47)
- Twitter (46)
- Feature extraction (45)
- Blockchain (44)
- Collaboration (44)
- Large Language Models (43)
- Semantics (43)
- Access control (41)
- Algorithms (40)
- Android (39)
- Machine Learning (38)
- Publication Year
- File Type
Articles 5581 - 5610 of 8479
Full-Text Articles in Computer Sciences
Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu
Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu
Research Collection School Of Computing and Information Systems
Typically a user prefers an item (e.g., a movie) because she likes certain features of the item (e.g., director, genre, producer). This observation motivates us to consider a feature-centric recommendation approach to item recommendation: instead of directly predicting the rating on items, we predict the rating on the features of items, and use such ratings to derive the rating on an item. This approach offers several advantages over the traditional item-centric approach: it incorporates more information about why a user chooses an item, it generalizes better due to the denser feature rating data, it explains the prediction of item ratings …
Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman
Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman
Research Collection School Of Computing and Information Systems
The title of this year;s special section of selected papers, whose initial versionswere presented at the “Economics and Electronic Commerce,” and “Information Technologyand Competitive Strategy” mini-tracks of the 2001 Hawaii International Conferenceon Systems Science (HICSS), reflects the increasing convergence of ideas fromEconomics and Information Systems (IS) research. This convergence has been occurringover the last several years and is related to the developments in e-commerce. ISresearch has been rapidly coming of age, driven by the ever-increasing importance ofinformation technology (IT) in the marketplace, and the need for managers, investors,policy-makers, and the public to understand how to more effectively navigate in ourhighly …
Ambiguous Optimistic Fair Exchange: Definition And Constructions, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Ambiguous Optimistic Fair Exchange: Definition And Constructions, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange (OFE) is a protocol for solving the problem of exchanging items or services in a fair manner between two parties, a signer and a verifier, with the help of an arbitrator which is called in only when a dispute happens between the two parties. In almost all the previous work on OFE, after obtaining a partial signature from the signer, the verifier can present it to others and show that the signer has indeed committed itself to something corresponding to the partial signature even prior to the completion of the transaction. In some scenarios, this capability given …
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Research Collection School Of Computing and Information Systems
Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon …
Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C. Valera, Hwee Xian Tan, Natarajan Gautam
Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C. Valera, Hwee Xian Tan, Natarajan Gautam
Research Collection School Of Computing and Information Systems
Abstract: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 …
Low Effort Crowdsourcing: Leveraging Peripheral Attention For Crowd Work, Vaish Rajan, Peter Organisciak, Kotaro Hara, Jeffrey P. Bigham, Haoqi Zhang
Low Effort Crowdsourcing: Leveraging Peripheral Attention For Crowd Work, Vaish Rajan, Peter Organisciak, Kotaro Hara, Jeffrey P. Bigham, Haoqi Zhang
Research Collection School Of Computing and Information Systems
Crowdsourcing systems leverage short bursts of focusedattention from many contributors to achieve a goal. Byrequiring people’s full attention, existing crowdsourcingsystems fail to leverage people’s cognitive surplus in themany settings for which they may be distracted, performingor waiting to perform another task, or barely payingattention. In this paper, we study opportunities for loweffortcrowdsourcing that enable people to contribute toproblem solving in such settings. We discuss the designspace for low-effort crowdsourcing, and through a seriesof prototypes, demonstrate interaction techniques, mechanisms,and emerging principles for enabling low-effortcrowdsourcing.
Ciphercard: A Token-Based Approach Against Camera-Based Shoulder Surfing Attacks On Common Touchscreen Devices, Teddy Seyed, Xing-Dong Yang, Anthony Tang, Saul Greenberg, Jiawei Gu, Bin Zhu, Xiang Ciao
Ciphercard: A Token-Based Approach Against Camera-Based Shoulder Surfing Attacks On Common Touchscreen Devices, Teddy Seyed, Xing-Dong Yang, Anthony Tang, Saul Greenberg, Jiawei Gu, Bin Zhu, Xiang Ciao
Research Collection School Of Computing and Information Systems
We present CipherCard, a physical token that defends against shoulder-surfing attacks on user authentication on capacitive touchscreen devices. When CipherCard is placed over a touchscreen’s pin-pad, it remaps a user’s touch point on the physical token to a different location on the pin-pad. It hence translates a visible user password into a different system password received by a touchscreen, but is hidden from observers as well as the user. CipherCard enhances authentication security through Two-Factor Authentication (TFA), in that both the correct user password and a specific card are needed for successful authentication. We explore the design space of CipherCard, …
Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter
Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter
Research Collection School Of Computing and Information Systems
Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, much fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic …
Mechanism Design For Near Real-Time Retail Payment And Settlement Systems, Zhiling Guo, Robert John Kauffman, Mei Lin, Dan Ma
Mechanism Design For Near Real-Time Retail Payment And Settlement Systems, Zhiling Guo, Robert John Kauffman, Mei Lin, Dan Ma
Research Collection School Of Computing and Information Systems
have made extensive use of interbank netting systems, in which payments are accumulated for end-of-day settlement. This approach, known as deferred net settlement (DNS), reduces the liquidity needs of a payment system, but bears inherent operational risks. As large dollar volumes of retail payments accumulate swiftly, real-time gross settlement (RTGS) is an attractive option. It permits immediate settlement of transactions during the day, but it brings up other risks that require consideration. We propose a hybrid payment management system involving elements of both DNS and RTGS. We explore several hybrid system mechanism designs to allow payment prioritization, reduce payment delays, …
Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim
Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In e-commerce environments, the trustworthiness of a seller is utterly important to potential buyers, especially when a seller is not known to them. Most existing trust evaluation models compute a single value to reflect the general trustworthiness of a seller without taking any transaction context information into account. With such a result as the indication of reputation, a buyer may be easily deceived by a malicious seller in a transaction where the notorious value imbalance problem is involved—in other words, a malicious seller accumulates a high-level reputation by selling cheap products and then deceives buyers by inducing them to purchase …
Software Puzzle: A Countermeasure To Resource-Inflated Denial-Of-Service Attacks, Yongdong Wu, Zhigang Zhao, Bao Feng, Robert H. Deng
Software Puzzle: A Countermeasure To Resource-Inflated Denial-Of-Service Attacks, Yongdong Wu, Zhigang Zhao, Bao Feng, Robert H. Deng
Research Collection School Of Computing and Information Systems
Denial-of-service (DoS) and distributed DoS (DDoS) are among the major threats to cyber-security, and client puzzle, which demands a client to perform computationally expensive operations before being granted services from a server, is a well-known countermeasure to them. However, an attacker can inflate its capability of DoS/DDoS attacks with fast puzzle-solving software and/or built-in graphics processing unit (GPU) hardware to significantly weaken the effectiveness of client puzzles. In this paper, we study how to prevent DoS/DDoS attackers from inflating their puzzle-solving capabilities. To this end, we introduce a new client puzzle referred to as software puzzle. Unlike the existing client …
Recovering Household Preferences For Digital Entertainment, Jin Li, Zhiling Guo, Robert J. Kauffman
Recovering Household Preferences For Digital Entertainment, Jin Li, Zhiling Guo, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
Cable TV return path data made possible by current generation set-top boxes present a new opportunity to analyze household viewing behavior and recover household viewing preferences from it. This research develops a model of household viewing preference that supports quantifying a household's valuation for different categories of digital content within the constraints of the programs to which it subscribes. This study uses a data set of more than 1 million observations on households from a digital entertainment firm that offers basic and premium services. Our estimation is via a Bayesian hierarchical model that employs the Gibbs sampler. The results show …
Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu
Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu
Research Collection School Of Computing and Information Systems
With the increase of mobile computation ability and the development of wireless network transmission technology, mobile devices not only are the important tools of personal life (e.g., education and entertainment), but also emerge as indispensable "secretary" of business activities (e.g., email and phone call). However, since mobile devices could work under complex and dynamic local and network conditions, they are vulnerable to local and remote security attacks. In real applications, different kinds of data protection are required by various local contexts. To provide appropriate protection, we propose a multidimensional context (MContext) scheme to comprehensively model and characterize the scene and …
Travel Recommendation Via Author Topic Model Based Collaborative Filtering, Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei
Travel Recommendation Via Author Topic Model Based Collaborative Filtering, Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei
Research Collection School Of Computing and Information Systems
While automatic travel recommendation has attracted a lot of attentions, the existing approaches generally suffer from different kinds of weaknesses. For example, sparsity problem can significantly degrade the performance of traditional collaborative filtering (CF). If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information. Motivated by this concern, we propose an Author Topic Collaborative Filtering (ATCF) method to facilitate comprehensive Points of Interest (POIs) recommendation for social media users. In our approach, the topics about user preference (e.g., cultural, cityscape, or landmark) are extracted from the textual description of …
Improving Internet Security Through Mandatory Information Disclosure, Qian Tang, Andrew B. Whinston
Improving Internet Security Through Mandatory Information Disclosure, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Although disclosure has long been considered as a solution to internalize externalities, mandatory security information disclosure is still in debate. We propose a mandatory disclosure mechanism based on existing data. The information is disclosed as straightforward rankings of organizations for users to understand, interpret, and make comparisons. As a result, the disclosure can influence organizations through reputational effects. We created a public website to disclose information regularly and conducted a quasi-experiment on outgoing spam to test the effectiveness of our mechanism on four matched country groups. For each treated country, we released the ranking list of top 10 most spamming …
An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
Research Collection School Of Computing and Information Systems
Learning for maximizing AUC performance is an important research problem in machine learning. Unlike traditional batch learning methods for maximizing AUC which often suffer from poor scalability, recent years have witnessed some emerging studies that attempt to maximize AUC by single-pass online learning approaches. Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple stochastic gradient descent approaches, which fail to exploit the geometry knowledge of the data observed in the online learning process, and thus could suffer from relatively slow convergence. To overcome the limitation of the existing studies, in this paper, we propose a …
The Knowledge Accumulation And Transfer In Open-Source Software (Oss) Development, Youngsoo Kim, Lingxiao Jiang
The Knowledge Accumulation And Transfer In Open-Source Software (Oss) Development, Youngsoo Kim, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
We examine the learning curves of individual software developers in Open-Source Software (OSS) Development. We collected the dataset of multi-year code change histories from the repositories for 20 open source software projects involving more than 200 developers. We build and estimate regression models to assess individual developers' learning progress (in reducing the likelihood they make a bug). Our estimation results show that developer's coding and indirect bug-fixing experiences do not decrease bug ratios while bug-fixing experience can lead to the decrease of bug ratio of learning progress. We also find that developer's coding and bug-fixing experiences in other projects do …
Multi-User Multiple Input Multiple Output (Mimo) Communication With Distributed Antenna Systems In Wireless Networks, Karthikeyan Sundaresan, Mohammad Khojastepour, Sampath Rangarajan, Jie Xiong
Multi-User Multiple Input Multiple Output (Mimo) Communication With Distributed Antenna Systems In Wireless Networks, Karthikeyan Sundaresan, Mohammad Khojastepour, Sampath Rangarajan, Jie Xiong
Research Collection School Of Computing and Information Systems
A system and a method are provided. The method includes deploying a plurality of antennas of an access point or a base station as a distributed antenna system. The method further includes configuring the distributed antenna system for multi-user wireless transmissions by applying medium access techniques and power-balanced pre-coding at the access point or the base station. The method also includes providing device localization for devices communicating with the distributed antenna system by applying time-difference-of-arrival techniques to antenna pairs from among the plurality of antennas at the access point or the base station.
Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Research Collection School Of Computing and Information Systems
The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …
Automatic, High Accuracy Prediction Of Reopened Bugs, Xin Xia, David Lo, Emad Shihab, Xinyu Wang, Bo Zhou
Automatic, High Accuracy Prediction Of Reopened Bugs, Xin Xia, David Lo, Emad Shihab, Xinyu Wang, Bo Zhou
Research Collection School Of Computing and Information Systems
Bug fixing is one of the most time-consuming and costly activities of the software development life cycle. In general, bugs are reported in a bug tracking system, validated by a triage team, assigned for someone to fix, and finally verified and closed. However, in some cases bugs have to be reopened. Reopened bugs increase software maintenance cost, cause rework for already busy developers and in some cases even delay the future delivery of a software release. Therefore, a few recent studies focused on studying reopened bugs. However, these prior studies did not achieve high performance (in terms of precision and …
Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma
Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma
Research Collection School Of Computing and Information Systems
Really simple syndication (RSS) technology enables an alternative delivery mechanism for online content. Instead of waiting passively for users to pull online content out, websites can push it to potential users through RSS. This is expected to significantly affect user behavior, website profitability, and market equilibrium. This research uses an economic model to study the impact of RSS adoption and examine whether it increases a website’s profit and competitive advantage. The findings are intriguing: they demonstrate that RSS can either increase or decrease website profit. In a competitive context, RSS adoption can actually be a disadvantage; in some cases, it …
Human Action Classification Based On Sequential Bag-Of-Words Model, Hong Liu, Qiaoduo Zhang, Qianru Sun
Human Action Classification Based On Sequential Bag-Of-Words Model, Hong Liu, Qiaoduo Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
Recently, approaches utilizing spatial-temporal features have achieved great success in human action classification. However, they typically rely on bag-of-words (BoWs) model, and ignore the spatial and temporal structure information of visual words, bringing ambiguities among similar actions. In this paper, we present a novel approach called sequential BoWs for efficient human action classification. It captures temporal sequential structure by segmenting the entire action into sub-actions. Each sub-action has a tiny movement within a narrow range of action. Then the sequential BoWs are created, in which each sub-action is assigned with a certain weight and salience to highlight the distinguishing sections. …
Online Learning On Incremental Distance Metric For Person Re-Identification, Yuke Sun, Hong Liu, Qianru Sun
Online Learning On Incremental Distance Metric For Person Re-Identification, Yuke Sun, Hong Liu, Qianru Sun
Research Collection School Of Computing and Information Systems
Person re-identification is to match persons appearing across non-overlapping cameras. The matching is challenging due to visual ambiguities and disparities of human bodies. Most previous distance metrics are learned by off-line and supervised approaches. However, they are not practical in real-world applications in which online data comes in without any label. In this paper, a novel online learning approach on incremental distance metric, OL-IDM, is proposed. The approach firstly modifies Self-Organizing Incremental Neural Network (SOINN) using Mahalanobis distance metric to cluster incoming data into neural nodes. Such metric maximizes the likelihood of a true image pair matches with a smaller …
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …
From Cells To Streets: Estimating Mobile Paths With Cellular-Side Data, Qatar Computing Research Institute, University Of Birmingham, Seattle University Of Washington, Haewoon Kwak
From Cells To Streets: Estimating Mobile Paths With Cellular-Side Data, Qatar Computing Research Institute, University Of Birmingham, Seattle University Of Washington, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Through their normal operation, cellular networks are a repository of continuous location information from their subscribed devices. Such information, however, comes at a coarse granularity both in terms of space, as well as time. For otherwise inactive devices, location information can be obtained at the granularity of the associated cellular sector, and at infrequent points in time, that are sensitive to the structure of the network itself, and the level of mobility of the device. In this paper, we are asking the question of whether such sparse information can help to identify the paths followed by mobile connected devices throughout …
Sensor-Free Corner Shape Detection By Wireless Networks, Yuxi Wang, Zimu Zhou, Kaishun Wu
Sensor-Free Corner Shape Detection By Wireless Networks, Yuxi Wang, Zimu Zhou, Kaishun Wu
Research Collection School Of Computing and Information Systems
Due to the rapid growth of the smartphone applications and the fast development of the Wireless Local Area Networks (WLANs), numerous indoor location-based techniques have been proposed during the past several decades. Floorplan, which defines the structure and functionality of a specific indoor environment, becomes a hot topic nowadays. Conventional floorplan techniques leverage smartphone sensors combined with WiFi signals to construct the floorplan of a building. However, existing approaches with sensors cannot detect the shape of a corner, and the sensors cost huge amount of energy during the whole floorplan constructing process. In this paper, we propose a sensor-free approach …
Pads: Passive Detection Of Moving Targets With Dynamic Speed Using Phy Layer Information, Kun Qian, Chenshu Wu, Zheng Yang, Yunhao Liu, Zimu Zhou
Pads: Passive Detection Of Moving Targets With Dynamic Speed Using Phy Layer Information, Kun Qian, Chenshu Wu, Zheng Yang, Yunhao Liu, Zimu Zhou
Research Collection School Of Computing and Information Systems
Device-free passive detection is an emerging technology to detect whether there exists any moving entities in the area of interests without attaching any device to them. It is an essential primitive for a broad range of applications including intrusion detection for safety precautions, patient monitoring in hospitals, child and elder care at home, etc. Despite of the prevalent signal feature Received Signal Strength (RSS), most robust and reliable solutions resort to finer-grained channel descriptor at physical layer, e.g., the Channel State Information (CSI) in the 802.11n standard. Among a large body of emerging techniques, however, few of them have explored …
I’Ve Heard You Have Problems: Cellular Signal Monitoring Through Ue Participatory Sensing, Huiguang Liang, Hyong Kim, Hwee-Pink Tan, Wai-Leong Yeow
I’Ve Heard You Have Problems: Cellular Signal Monitoring Through Ue Participatory Sensing, Huiguang Liang, Hyong Kim, Hwee-Pink Tan, Wai-Leong Yeow
Research Collection School Of Computing and Information Systems
The operating environment of cellular networks can be in a constant state of change. One Singaporean operator expressed difficulty with the coverage assertion (CA) problem of whether regulated minimum coverage is met, especially in urban areas. Currently, the operator manually appraises coverage through laborious and expensive walk/drive-tests. In this paper, we propose Tattle, a distributed, low-cost and comprehensive cellular network measurement collection and processing framework. We exemplify Tattle by leveraging on participating UEs to report on network coverage in real-time. Tattle exploits wireless local-area interfaces to exchange RSCP measurements amongst devices to preserve the co-locality of readings and conserve power. …
Unisense: A Unified And Sustainable Sensing And Transport Architecture For Large Scale And Heterogeneous Sensor Networks, Yunye Jin, Hwee-Pink Tan
Unisense: A Unified And Sustainable Sensing And Transport Architecture For Large Scale And Heterogeneous Sensor Networks, Yunye Jin, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
In this paper, we propose UNISENSE, a unified and sustainable sensing and transport architecture for large scale and heterogeneous sensor networks. The proposed architecture incorporates seven principal components, namely, application profiling, node architecture, intelligent network design, network management, deep sensing, generalized participatory sensing, and security. We describe the design and implementation for each component. We also present the deployment and performance of the UNISENSE architecture in four practical applications.
Orchestrating Service Innovation Using Design Moves: The Dynamics Of Fit Between Service And Enterprise It Architectures, Narayan Ramasubbu, Charles Jason Woodard, Sunil Mithas
Orchestrating Service Innovation Using Design Moves: The Dynamics Of Fit Between Service And Enterprise It Architectures, Narayan Ramasubbu, Charles Jason Woodard, Sunil Mithas
Research Collection School Of Computing and Information Systems
Service science perspectives highlight the central role of information technology (IT) in transforming the design and delivery of services. To discern the mechanisms through which IT impacts service innovation, we explore the dynamics of the relationship between enterprise IT and service architectures, and how these dynamics influence the performance of service innovation projects. We conducted six case studies to investigate how firms orchestrated service innovation, focusing on the design of the service architecture and its relationship to enterprise systems. We synthesize the case findings to develop a set of propositions on the antecedents and consequences of fit (or misfit) between …