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Articles 7621 - 7650 of 10550
Full-Text Articles in Entire DC Network
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Research Collection School Of Computing and Information Systems
This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real …
Platform Regulation On Seller Heterogeneity, Ruhai Wu, Mei Lin
Platform Regulation On Seller Heterogeneity, Ruhai Wu, Mei Lin
Research Collection School Of Computing and Information Systems
On a "marketplace" platform, where two sides of users trade, the platform owner has an incentive to regulate its marketplace for a higher profit. This study focuses on a monopoly platform's nonpricing, regulatory strategies in governing quality heterogeneity of competing sellers. In contrast to related studies, we endogenize strategic interactions among platform users. Our model extends the circular city model to capture seller heterogeneity in both variety and quality. The closed-form equilibrium solution reveals a ripple effect that exerts competitive pressure from seller to seller at a diminishing magnitude. The equilibrium analysis enables us to connect the economic mechanisms in …
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
In software engineering, testing is a crucial activity that is designed to ensure the quality of program code. For this activity, software teams spend substantial resources constructing test cases to thoroughly assess the correctness of software functionality. What is the proportion of open source projects that include test cases? What is the effect of number of developers on the number of test cases? In this study, we explore open source projects and investigate the correlation between the presence of test cases and various project development characteristics, including the number of lines of code, the size of development teams and the …
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
Collective Diffusion Over Networks: Models And Inference, Akshat Kumar, Daniel Sheldon, Biplav Srivastava
Collective Diffusion Over Networks: Models And Inference, Akshat Kumar, Daniel Sheldon, Biplav Srivastava
Research Collection School Of Computing and Information Systems
Diffusion processes in networks are increasingly used to model the spread of information and social influence. In several applications in computational sustainability such as the spread of wildlife, infectious diseases and traffic mobility pattern, the observed data often consists of only aggregate information. In this work, we present new models that generalize standard diffusion processes to such collective settings. We also present optimization based techniques that can accurately learn the underlying dynamics of the given contagion process, including the hidden network structure, by only observing the time a node becomes active and the associated aggregate information. Empirically, our technique is …
Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi
Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Multiple kernel learning (MKL) is a promising family of machine learning algorithms using multiple kernel functions for various challenging data mining tasks. Conventional MKL methods often formulate the problem as an optimization task of learning the optimal combinations of both kernels and classifiers, which usually results in some forms of challenging optimization tasks that are often difficult to be solved. Different from the existing MKL methods, in this paper, we investigate a boosting framework of MKL for classification tasks, i.e., we adopt boosting to solve a variant of MKL problem, which avoids solving the complicated optimization tasks. Specifically, we present …
Video Concept Detection By Learning From Web Images: A Case Study On Cross Domain Learning, Shiai Zhu, Ting Yao, Chong-Wah Ngo
Video Concept Detection By Learning From Web Images: A Case Study On Cross Domain Learning, Shiai Zhu, Ting Yao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Concept detection is probably the most important research problem in the area of multimedia. The need to model with sufficient and diverse training instances, however, makes the task computationally and resourcefully expensive. Meanwhile, the popularity of social media has generated massive amount of weakly tagged images which could be leveraged for concept model learning. Therefore, in this paper, we consider exploring weakly taggedWeb images to shed some light on video concept detection. Particularly, two sets of Web images downloaded from Flickr are utilized as training data for concept detection on two real-world large-scale video datasets released by TRECVID. Our experiments …
Improving Tool Support For Software Reverse Engineering In A Security Context, Brendan Cleary, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois
Improving Tool Support For Software Reverse Engineering In A Security Context, Brendan Cleary, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois
Research Collection School Of Computing and Information Systems
Illegal cyberspace activities are increasing rapidly and many software engineers are using reverse engineering methods to respond to attacks. The security-sensitive nature of these tasks, such as the understanding of malware or the decryption of encrypted content, brings unique challenges to reverse engineering: work has to be done offline, files can rarely be shared, time pressure is immense, and there is a lack of tool and process support for capturing and sharing the knowledge obtained while trying to understand assembly code. To help us gain an understanding of this reverse engineering work, we conducted an exploratory study at a government …
Unified Modeling Language: The Teen Years And Growing Pains, J. Erickson, Keng Siau
Unified Modeling Language: The Teen Years And Growing Pains, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Unified Modeling Language (UML) is adopted by the Object Management Group as a standardized general-purpose modeling language for object-oriented software engineering. Despite its status as a standard, UML is still in a development stage and many studies have highlighted its weaknesses and challenges - including those related to human factor issues. Further, UML has grown considerably more complex since its inception. This paper traces the history of Unified Modeling Language (UML) from its formation to its current state and discusses the current state of the UML language. The paper first introduces UML and its various diagrams, and discusses its characteristics …
Gamification Of Education Using Computer Games, Fiona Fui-Hoon Nah, Venkata Telaprolu, Shashank Rallapalli, Pavani R. Venkata
Gamification Of Education Using Computer Games, Fiona Fui-Hoon Nah, Venkata Telaprolu, Shashank Rallapalli, Pavani R. Venkata
Research Collection School Of Computing and Information Systems
We review the literature on gamification and identify principles of gamification and system design elements for gamifying computer educational games. Gamification of education is expected to increase learners’ engagement, which in turn increases learning achievement. We propose a gamification framework that synthesizes findings from the literature. The gamification framework is comprised of principles of gamification, system design elements for gamification, and dimensions of user engagement.
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Performance dashboards are used as a strategic decision support tool in organizations. In this research, we examine the relationships between the usability of performance dashboards, the usefulness of operational and tactical support, and the quality of strategic support that they provide. We hypothesize that usability of performance dashboards will influence user perceptions of the usefulness of the operational and tactical support provided by the dashboards, which in turn influence the perceived quality of strategic support provided.
Keystroke Timing Analysis Of On-The-Fly Web Apps, Chee Meng Tey, Payas Gupta, Debin Gao, Yan Zhang
Keystroke Timing Analysis Of On-The-Fly Web Apps, Chee Meng Tey, Payas Gupta, Debin Gao, Yan Zhang
Research Collection School Of Computing and Information Systems
The Google Suggestions service used in Google Search is one example of an interactivity rich Javascript application. In this paper, we analyse the timing side channel of Google Suggestions by reverse engineering the communication model from obfuscated Javascript code. We consider an attacker who attempts to infer the typing pattern of a victim. From our experiments involving 11 participants, we found that for each keypair with at least 20 samples, the mean of the inter-keystroke timing can be determined with an error of less than 20%.
Anomaly Detection On Social Data, Hanbo Dai
Anomaly Detection On Social Data, Hanbo Dai
Dissertations and Theses Collection (Open Access)
The advent of online social media including Facebook, Twitter, Flickr and Youtube has drawn massive attention in recent years. These online platforms generate massive data capturing the behavior of multiple types of human actors as they interact with one another and with resources such as pictures, books and videos. Unfortunately, the openness of these platforms often leaves them highly susceptible to abuse by suspicious entities such as spammers. It therefore becomes increasingly important to automatically identify these suspicious entities and eliminate their threats. We call these suspicious entities anomalies in social data, as they often hold different agenda comparing to …
Design Capital And Design Moves: The Logic Of Digital Business Strategy, C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, V. Sambamurthy
Design Capital And Design Moves: The Logic Of Digital Business Strategy, C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, V. Sambamurthy
Research Collection Lee Kong Chian School Of Business
As information technology becomes integral to the products and services in a growing range of industries, there has been a corresponding surge of interest in understanding how firms can effectively formulate and execute digital business strategies. This fusion of IT within the business environment gives rise to a strategic tension between investing in digital artifacts for long-term value creation and exploiting them for short-term value appropriation. Further, relentless innovation and competitive pressures dictate that firms continually adapt these artifacts to changing market and technological conditions, but sustained profitability requires scalable architectures that can serve a large customer base and stable …
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston
Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Cybersecurity is a national priority in this big data era. Because of negative externalities and the resulting lack of economic incentives, companies often underinvest in security controls, despite government and industry recommendations. Although many existing studies on security have explored technical solutions, only a few have looked at the economic motivations. To fill the gap, we propose an approach to increase the incentives of organizations to address security problems. Specifically, we utilize and process existing security vulnerability data, derive explicit security performance information, and disclose the information as feedback to organizations and the public. We regularly release information on the …
Hunts: A Trajectory Recommendation System For Effective And Efficient Hunting Of Taxi Passengers, Ye Ding, Siyuan Liu, Jiansu Pu, Lionel Ni
Hunts: A Trajectory Recommendation System For Effective And Efficient Hunting Of Taxi Passengers, Ye Ding, Siyuan Liu, Jiansu Pu, Lionel Ni
Research Collection School Of Computing and Information Systems
Nowadays, there are many taxis traversing around the city searching for available passengers, but their hunts of passengers are not always efficient. To the dynamics of traffic and biased passenger distributions, current offline recommendations based on place of interests may not work well. In this paper, we define a new problem, global-optimal trajectory retrieving (GOTR), as finding a connected trajectory of high profit and high probability to pick up a passenger within a given time period in real-time. To tackle this challenging problem, we present a system, called HUNTS, based on the knowledge from both historical and online GPS data …
Introducing Programmers To Pair Programming: A Controlled Experiment, A. S. M. Sajeev, Subhajit Datta
Introducing Programmers To Pair Programming: A Controlled Experiment, A. S. M. Sajeev, Subhajit Datta
Research Collection School Of Computing and Information Systems
Pair programming is a key characteristic of the Extreme Programming (XP) method. Through a controlled experiment we investigate pair programming behaviour of programmers without prior experience in XP. The factors investigated are: (a) characteristics of pair programming that are less favored (b) perceptions of team effectiveness and how they relate to product quality, and (c) whether it is better to train a pair by giving routine tasks first or by giving complex tasks first. Our results show that: (a) the least liked aspects of pair programming were having to share the screen, keyboard and mouse, and having to switch between …
Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li
Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li
Research Collection School Of Computing and Information Systems
Event detection has been an important task for a long time. When it comes to Twitter, new problems are presented. Twitter data is a huge temporal data flow with much noise and various kinds of topics. Traditional sophisticated methods with a high computational complexity aren’t designed to handle such data flow efficiently. In this paper, we propose a mixture Gaussian model for bursty word extraction in Twitter and then employ a novel time-dependent HDP model for new topic detection. Our model can grasp new events, the location and the time an event becomes bursty promptly and accurately. Experiments show the …
Architectural Control And Value Migration In Layered Ecosystems: The Case Of Open-Source Cloud Management Platforms, Richard Tee, C. Jason Woodard
Architectural Control And Value Migration In Layered Ecosystems: The Case Of Open-Source Cloud Management Platforms, Richard Tee, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Our paper focuses on strategic decision making in layered business ecosystems, highlighting the role of cross-layer interactions in shaping choices about product design and platform governance. Based on evidence from the cloud computing ecosystem, we analyze how concerns about architectural control and expectations regarding future value migration influence the design of product interfaces and the degree of openness to external contributions. We draw on qualitative longitudinal data to trace the development of two open-source platforms for managing cloudbased computing resources. We focus in particular on the emergence of a layered "stack" in which these platforms must compete with both vertically …
Cugar: A Model For Open Innovation In Science And Technology Parks, Arcot Desai Narasimhalu
Cugar: A Model For Open Innovation In Science And Technology Parks, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper reviews key elements of a Science or Technology Park in the context of open innovation. Insights into and recommendations on key issues related to intellectual property, licensing and venture capital that would be of interest to any Science Park are presented later.
Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Discrete Time Markov Chains (DTMCs) are widely used to model probabilistic systems in many domains, such as biology, network and communication protocols. There are two main approaches for probability reachability analysis of DTMCs, i.e., solving linear equations or using value iteration. However, both approaches have drawbacks. On one hand, solving linear equations can generate accurate results, but it can be only applied to relatively small models. On the other hand, value iteration is more scalable, but often suffers from slow convergence. Furthermore, it is unclear how to parallelize (i.e., taking advantage of multi-cores or distributed computers) these two approaches. In …
A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong
A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong
Research Collection School Of Computing and Information Systems
UML is a widely used notation, and formalizing its semantics is an important issue. Here, we concentrate on formalizing UML state machines, used to express the dynamic behaviour of software systems. We propose a formal operational semantics covering all features of the latest version (2.4.1) of UML state machines specification. We use labelled transition systems as the semantic model, so as to use automatic verification techniques like model checking. Furthermore, our proposed semantics includes synchronous and asynchronous communications between state machines. We implement our approach in USM2C, a model checker supporting editing, simulation and automatic verification of UML state machines. …
Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Research Collection School Of Computing and Information Systems
In this demo, we introduce SocioPhone, a novel initiative toward everyday face-to-face interaction monitoring platform. Among diverse verbal, aural, visual cues expressed during face-to-face interaction, SocioPhone captures diverse meta-linguistic information from conversations and provides interaction-aware applications on-the-fly. Undoubtedly, conversations are a key channel for face-to-face interaction. Specifically, monitoring conversational turns, i.e., alternation of different speakers (including none speaking), is the first crucial step to derive diverse interesting aspects of conversations, e.g., who is talking right now, how long and often one talks, how quickly one responds to another, and so on. In this demo, we will show the core technique …
T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni
T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni
Research Collection School Of Computing and Information Systems
Nowadays, big cities are suffering from severe traffic congestion as a result of the continuing increase in vehicles. Taxis equipped with GPS can be viewed as sensors of the traffic situation in city. However, trajectory data generated by taxi’s GPS traces are often high-dimensional and contain large spatial and temporal attributes, which pose challenges for analysts. In this paper, based on taxi trajectory data, we present an interactive visual analytics system, T-Watcher, for monitoring and analyzing complex traffic situations in big cities. Users are able to use a carefully designed interface to monitor and inspect data interactively from three levels …
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
The execution of an agent's complex activities, comprising sequences of simpler actions, sometimes leads to the clash of conflicting functions that must be optimized. These functions represent satisfaction, short-term as well as long-term objectives, costs and individual preferences. The way that these functions are weighted is usually unknown even to the decision maker. But if we were able to understand the individual motivations and compare such motivations among individuals, then we would be able to actively change the environment so as to increase satisfaction and/or improve performance. In this work, we approach the problem of providing highlevel and intelligible descriptions …
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Research Collection School Of Computing and Information Systems
The Last Mile Problem (LMP) refers to the provision of travel service from thenearest public transportation node to a home or office. We study the supply side of thisproblem in a stochastic setting, with batch demands resulting from the arrival of groupsof passengers at rail stations or bus stops who request last-mile service. Closed-formbounds and approximations are derived for the performance of Last Mile TransportationsSystems as a function of the fundamental design parameters of such systems. An initialset of results is obtained for the case in which a fleet of vehicles of unit capacity providesthe Last Mile service and each …
Attribute-Based Access To Scalable Media In Cloud-Assisted Content Sharing, Yongdong Wu, Zhuo Wei, Robert H. Deng
Attribute-Based Access To Scalable Media In Cloud-Assisted Content Sharing, Yongdong Wu, Zhuo Wei, Robert H. Deng
Research Collection School Of Computing and Information Systems
This paper presents a novel Multi-message Ciphertext Policy Attribute-Based Encryption (MCP-ABE) technique, and employs the MCP-ABE to design an access control scheme for sharing scalable media based on data consumers’ attributes (e.g., age, nationality, gender) rather than an explicit list of the consumers’ names. The scheme is efficient and flexible because MCP-ABE allows a content provider to specify an access policy and encrypt multiple messages within one ciphertext such that only the users whose attributes satisfy the access policy can decrypt the ciphertext. Moreover, the paper shows how to support resource-limited mobile devices by offloading computational intensive perations to cloud …
Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong
Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Credit risk assessment for consumers has been a cornerstone of risk management in financial institutions and constitutes a component of the three pillars of Basel II. Traditionally, the concept of 5 ‘C’s was widely adopted by financial institutions as the key basis for credit risk assessment for loan applications by prospective borrowers. With the evolution of the credit risk management practices, more quantitative methods such as credit scorecards have been developed, which is implemented through the use of logistic regression, decision trees and neural networks. However, such approaches proved to be inadequate with the validity and effectiveness of the approaches …