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Full-Text Articles in Computer Sciences

A Unified Framework For Vehicle Rerouting And Traffic Light Control To Reduce Traffic Congestion, Zhiguang Cao, Siwei Jiang, Jie Zhang, Hongliang Guo Jul 2017

A Unified Framework For Vehicle Rerouting And Traffic Light Control To Reduce Traffic Congestion, Zhiguang Cao, Siwei Jiang, Jie Zhang, Hongliang Guo

Research Collection School Of Computing and Information Systems

As the number of vehicles grows rapidly each year, more and more traffic congestion occurs, becoming a big issue for civil engineers in almost all metropolitan cities. In this paper, we propose a novel pheromone-based traffic management framework for reducing traffic congestion, which unifies the strategies of both dynamic vehicle rerouting and traffic light control. Specifically, each vehicle, represented as an agent, deposits digital pheromones over its route, while roadside infrastructure agents collect the pheromones and fuse them to evaluate real-time traffic conditions as well as to predict expected road congestion levels in near future. Once road congestion is predicted, …

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Deshadownet: A Multi-Context Embedding Deep Network For Shadow Removal, Liangqiong Qu, Jiandong Tian, Shengfeng He, Yandong Tang, Rynson W. H. Lau Jul 2017

Deshadownet: A Multi-Context Embedding Deep Network For Shadow Removal, Liangqiong Qu, Jiandong Tian, Shengfeng He, Yandong Tang, Rynson W. H. Lau

Research Collection School Of Computing and Information Systems

Shadow removal is a challenging task as it requires the detection/annotation of shadows as well as semantic understanding of the scene. In this paper, we propose an automatic and end-to-end deep neural network (DeshadowNet) to tackle these problems in a unified manner. DeshadowNet is designed with a multi-context architecture, where the output shadow matte is predicted by embedding information from three different perspectives. The first global network extracts shadow features from a global view. Two levels of features are derived from the global network and transferred to two parallel networks. While one extracts the appearance of the input image, the …

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Deep Learning On Lie Groups For Skeleton-Based Action Recognition, Zhiwu Huang, C. Wan, T. Probst, Gool L. Van Jul 2017

Deep Learning On Lie Groups For Skeleton-Based Action Recognition, Zhiwu Huang, C. Wan, T. Probst, Gool L. Van

Research Collection School Of Computing and Information Systems

In recent years, skeleton-based action recognition has become a popular 3D classification problem. State-of-the-art methods typically first represent each motion sequence as a high-dimensional trajectory on a Lie group with an additional dynamic time warping, and then shallowly learn favorable Lie group features. In this paper we incorporate the Lie group structure into a deep network architecture to learn more appropriate Lie group features for 3D action recognition. Within the network structure, we design rotation mapping layers to transform the input Lie group features into desirable ones, which are aligned better in the temporal domain. To reduce the high feature …

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A Decidable Fragment In Separation Logic With Inductive Predicates And Arithmetic, Quang Loc Le, Makoto Tatsuta, Jun Sun, Wei-Ngan Chin Jul 2017

A Decidable Fragment In Separation Logic With Inductive Predicates And Arithmetic, Quang Loc Le, Makoto Tatsuta, Jun Sun, Wei-Ngan Chin

Research Collection School Of Computing and Information Systems

We consider the satisfiability problem for a fragment of separation logic including inductive predicates with shape and arithmetic properties. We show that the fragment is decidable if the arithmetic properties can be represented as semilinear sets. Our decision procedure is based on a novel algorithm to infer a finite representation for each inductive predicate which precisely characterises its satisfiability. Our analysis shows that the proposed algorithm runs in exponential time in the worst case. We have implemented our decision procedure and integrated it into an existing verification system. Our experiment on benchmarks shows that our procedure helps to verify the …

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Auditing Anti-Malware Tools By Evolving Android Malware And Dynamic Loading Technique, Yinxing Xue, Guozhu Meng, Yang Liu, Tian Huat Tan, Hongxu Chen, Jun Sun, Jie Zhang Jul 2017

Auditing Anti-Malware Tools By Evolving Android Malware And Dynamic Loading Technique, Yinxing Xue, Guozhu Meng, Yang Liu, Tian Huat Tan, Hongxu Chen, Jun Sun, Jie Zhang

Research Collection School Of Computing and Information Systems

Although a previous paper shows that existing antimalware tools (AMTs) may have high detection rate, the report is based on existing malware and thus it does not imply that AMTs can effectively deal with future malware. It is desirable to have an alternative way of auditing AMTs. In our previous paper, we use malware samples from android malware collection GENOME to summarize a malware meta-model for modularizing the common attack behaviors and evasion techniques in reusable features. We then combine different features with an evolutionary algorithm, in which way we evolve malware for variants. Previous results have shown that the …

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Mergeable And Revocable Identity-Based Encryption, Shengmin Xu, Guomin Yang, Yi Mu, Willy Susilo Jul 2017

Mergeable And Revocable Identity-Based Encryption, Shengmin Xu, Guomin Yang, Yi Mu, Willy Susilo

Research Collection School Of Computing and Information Systems

Identity-based encryption (IBE) has been extensively studied and widely used in various applications since Boneh and Franklin proposed the first practical scheme based on pairing. In that seminal work, it has also been pointed out that providing an efficient revocation mechanism for IBE is essential. Hence, revocable identity-based encryption (RIBE) has been proposed in the literature to offer an efficient revocation mechanism. In contrast to revocation, another issue that will also occur in practice is to combine two or multiple IBE systems into one system, e.g., due to the merge of the departments or companies. However, this issue has not …

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A Secure, Usable, And Transparent Middleware For Permission Managers On Android, Daibin Wang, Haixia Yao, Yingjiu Li, Hai Jin, Deqing Zou, Robert H. Deng Jul 2017

A Secure, Usable, And Transparent Middleware For Permission Managers On Android, Daibin Wang, Haixia Yao, Yingjiu Li, Hai Jin, Deqing Zou, Robert H. Deng

Research Collection School Of Computing and Information Systems

Android’s permission system offers an all-or-nothing choice when installing an app. To make it more flexible and fine-grained, users may choose a popular app tool, called permission manager, to selectively grant or revoke an app’s permissions at runtime. A fundamental requirement for such permission manager is that the granted or revoked permissions should be enforced faithfully. However, we discover that none of existing permission managers meet this requirement due to permission leaks, in which an unprivileged app can exercise certain permissions which are revoked or not-granted through communicating with a privileged app. To address this problem, we propose a secure, …

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Hierarchical Functional Encryption For Linear Transformations, Shiwei Zhang, Yi Mu, Guomin Yang, Xiaofen Wang Jul 2017

Hierarchical Functional Encryption For Linear Transformations, Shiwei Zhang, Yi Mu, Guomin Yang, Xiaofen Wang

Research Collection School Of Computing and Information Systems

In contrast to the conventional all-or-nothing encryption, functional encryption (FE) allows partial revelation of encrypted information based on the keys associated with different functionalities. Extending FE with key delegation ability, hierarchical functional encryption (HFE) enables a secret key holder to delegate a portion of its decryption ability to others and the delegation can be done hierarchically. All HFE schemes in the literature are for general functionalities and not very practical. In this paper, we focus on the functionality of linear transformations (i.e. matrix product evaluation). We refine the definition of HFE and further extend the delegation to accept multiple keys. …

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Privacy-Preserving K-Time Authenticated Secret Handshakes, Yangguang Tian, Shiwei Zhang, Guomin Yang, Yi Mu, Yong Yu Jul 2017

Privacy-Preserving K-Time Authenticated Secret Handshakes, Yangguang Tian, Shiwei Zhang, Guomin Yang, Yi Mu, Yong Yu

Research Collection School Of Computing and Information Systems

Secret handshake allows a group of authorized users to establish a shared secret key and at the same time authenticate each other anonymously. A straightforward approach to design an unlinkable secret handshake protocol is to use either long-term certificate or one-time certificate provided by a trusted authority. However, how to detect the misusing of certificates by an insider adversary is a challenging security issue when using those approaches for unlinkable secret handshake. In this paper, we propose a novel k-time authenticated secret handshake (k-ASH) protocol where each authorized user is only allowed to use the credential for k times. We …

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Automatically Locating Malicious Packages In Piggybacked Android Apps, Li Li, Daoyuan Li, Tegawende Bissyande, Jacques Klein, Haipeng Cai, David Lo, Yves Le Traon Jul 2017

Automatically Locating Malicious Packages In Piggybacked Android Apps, Li Li, Daoyuan Li, Tegawende Bissyande, Jacques Klein, Haipeng Cai, David Lo, Yves Le Traon

Research Collection School Of Computing and Information Systems

To devise efficient approaches and tools for detecting malicious packages in the Android ecosystem, researchers are increasingly required to have a deep understanding of malware. There is thus a need to provide a framework for dissecting malware and locating malicious program fragments within app code in order to build a comprehensive dataset of malicious samples. Towards addressing this need, we propose in this work a tool-based approach called HookRanker, which provides ranked lists of potentially malicious packages based on the way malware behaviour code is triggered. With experiments on a ground truth set of piggybacked apps, we are able to …

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Jfix: Semantics-Based Repair Of Java Programs Via Symbolic Pathfinder, Xuan Bach D. Le, Duc-Hiep Chu, David Lo, Goues Le, Willem Visser Jul 2017

Jfix: Semantics-Based Repair Of Java Programs Via Symbolic Pathfinder, Xuan Bach D. Le, Duc-Hiep Chu, David Lo, Goues Le, Willem Visser

Research Collection School Of Computing and Information Systems

Recently there has been a proliferation of automated program repair (APR) techniques, targeting various programming languages. Such techniques can be generally classified into two families: syntactic- and semantics-based. Semantics-based APR, on which we focus, typically uses symbolic execution to infer semantic constraints and then program synthesis to construct repairs conforming to them. While syntactic-based APR techniques have been shown success- ful on bugs in real-world programs written in both C and Java, semantics-based APR techniques mostly target C programs. This leaves empirical comparisons of the APR families not fully explored, and developers without a Java-based semantics APR technique. We present …

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Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Jianling Sun Jul 2017

Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

Context: Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which is also referred as just-in-time defect prediction, could not only ensure software quality in the development process, but also make the developers check and fix the defects in time [1].Objective: Ensemble learning becomes a hot topic in recent years. There have been several studies about applying ensemble learning to defect prediction [2–5]. Traditional ensemble learning approaches only have one layer, i.e., they use ensemble learning once. There are few studies that leverages ensemble learning twice or more. To bridge this research gap, we try to …

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Iupdater: Low Cost Rss Fingerprints Updating For Device-Free Localization, Liqiong Chang, Jie Xiong, Yu Wang, Xiaojiang Chen, Junhao Hu, Dingyi Fang Jul 2017

Iupdater: Low Cost Rss Fingerprints Updating For Device-Free Localization, Liqiong Chang, Jie Xiong, Yu Wang, Xiaojiang Chen, Junhao Hu, Dingyi Fang

Research Collection School Of Computing and Information Systems

While most existing indoor localization techniques are device-based, many emerging applications such as intruder detection and elderly monitoring drive the needs of device-free localization, in which the target can be localized without any device attached. Among the diverse techniques, received signal strength (RSS) fingerprint-based methods are popular because of the wide availability of RSS readings in most commodity hardware. However, current fingerprint-based systems suffer from high human labor cost to update the fingerprint database and low accuracy due to the large degree of RSS variations. In this paper, we propose a fingerprint-based device-free localization system named iUpdater to significantly reduce …

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Multi-Authority Abs Supporting Dendritic Access Structure, Ruo Mo, Jian-Feng Ma, Ximeng Liu, Qi Li Jul 2017

Multi-Authority Abs Supporting Dendritic Access Structure, Ruo Mo, Jian-Feng Ma, Ximeng Liu, Qi Li

Research Collection School Of Computing and Information Systems

Attribute-based signature (ABS), which could realize fine-grained access control, was considered to be an importantmethod for anonymous authentication in cloud computing. However, normal ABS only provided simple accesscontrol through threshold structure and thus could not cope with the large-scale attribute sets of users in the cloud. Moreover,the attribute sets were supervised by only one attribute authority, which increased the cost of computation and storage.The whole system was in danger of collapsing once the attribute authority was breached. Aiming at tackling theproblems above, a novel scheme, was proposed called multi-authority ABS supporting dendritic access structure whichsupported any AND, OR and threshold …

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Adviser+: Toward A Usable Web-Based Algorithm Portfolio Deviser, Hoong Chuin Lau, Mustafa Misir, Xiang Li Li, Lingxiao Jiang Jul 2017

Adviser+: Toward A Usable Web-Based Algorithm Portfolio Deviser, Hoong Chuin Lau, Mustafa Misir, Xiang Li Li, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

The present study offers a more user-friendly and parallelized version of a web-based algorithm portfolio generator, called ADVISER. ADVISER is a portfolio generation tool to deliver a group of configurations for a given set of algorithms targeting a particular problem. The resulting configurations are expected to be diverse such that each can perform well on a certain type of problem instances. One issue with ADVISER is that it performs portfolio generation on a single-core which results in long waiting times for the users. Besides that, it lacks of a reporting system with visualizations to tell more about the generated portfolios. …

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Attribute-Based Encryption With Expressive And Authorized Keyword Search, Hui Cui, Robert H. Deng, Joseph K. Liu, Yingjiu Li Jul 2017

Attribute-Based Encryption With Expressive And Authorized Keyword Search, Hui Cui, Robert H. Deng, Joseph K. Liu, Yingjiu Li

Research Collection School Of Computing and Information Systems

To protect data security and privacy in cloud storage systems, a common solution is to outsource data in encrypted forms so that the data will remain secure and private even if storage systems are compromised. The encrypted data, however, must be pliable to search and access control. In this paper, we introduce a notion of attribute-based encryption with expressive and authorized keyword search (ABE-EAKS) to support both expressive keyword search and fine-grained access control over encrypted data in the cloud. In ABE-EAKS, every data user is associated with a set of attributes and is issued a private attribute-key corresponding to …

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Mining Capstone Project Wikis For Knowledge Discovery, Swapna Gottipati, Venky Shankararaman, Melvrivk Goh Jul 2017

Mining Capstone Project Wikis For Knowledge Discovery, Swapna Gottipati, Venky Shankararaman, Melvrivk Goh

Research Collection School Of Computing and Information Systems

Wikis are widely used collaborative environments as sources of information and knowledge. The facilitate students to engage in collaboration and share information among members and enable collaborative learning. In particular, Wikis play an important role in capstone projects. Wikis aid in various project related tasks and aid to organize information and share. Mining project Wikis is critical to understand the students learning and latest trends in industry. Mining Wikis is useful to educationists and academicians for decision-making about how to modify the educational environment to improve student's learning. The main challenge is that the content or data in project Wikis …

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Fast Adaptation Of Activity Sensing Policies In Mobile Devices, Mohammad Abu Alsheikh, Dusit Niyato, Shaowei Lin, Hwee-Pink Tan, Dong In Kim Jul 2017

Fast Adaptation Of Activity Sensing Policies In Mobile Devices, Mohammad Abu Alsheikh, Dusit Niyato, Shaowei Lin, Hwee-Pink Tan, Dong In Kim

Research Collection School Of Computing and Information Systems

With the proliferation of sensors, such as accelerometers,in mobile devices, activity and motion tracking has become a viable technologyto understand and create an engaging user experience. This paper proposes afast adaptation and learning scheme of activity tracking policies when userstatistics are unknown a priori, varying with time, and inconsistent for differentusers. In our stochastic optimization, user activities are required to besynchronized with a backend under a cellular data limit to avoid overchargesfrom cellular operators. The mobile device is charged intermittently usingwireless or wired charging for receiving the required energy for transmission andsensing operations. Firstly, we propose an activity tracking policy …

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Fast Adaptation Of Activity Sensing Policies In Mobile Devices, Mohammad Abu Alsheikh, Dusit Niyato, Shaowei Lin, Hwee-Pink Tan, Dong In Kim Jul 2017

Fast Adaptation Of Activity Sensing Policies In Mobile Devices, Mohammad Abu Alsheikh, Dusit Niyato, Shaowei Lin, Hwee-Pink Tan, Dong In Kim

Research Collection School Of Computing and Information Systems

With the proliferation of sensors, such as accelerometers,in mobile devices, activity and motion tracking has become a viable technology to understand and create an engaging user experience. This paper proposes a fast adaptation and learning scheme of activity tracking policies when user statistics are unknown a priori, varying with time, and inconsistent for different users. In our stochastic optimization, user activities are required to be synchronized with a backend under a cellular data limit to avoid overcharges from cellular operators. The mobile device is charged intermittently using wireless or wired charging for receiving the required energy for transmission and sensing …

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How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang Jul 2017

How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang

Research Collection School Of Computing and Information Systems

In the era of Fintech innovation and e-commerce, faster settlement of massive retail transactions is crucial for business growth and financial system stability. However, speeding up payments settlement can create periodic liquidity shortfalls to banks which would incur high cost of funds in the settlement process. We propose a new hybrid settlement mechanism design that integrates features of real-time gross settlement, deferred net settlement, and central queue management structure. The hybrid mechanism is managed by an intermediary and is particularly suitable to settle large volume of small-value retail payments. We evaluate the mechanism using computer experiments and simulation. We find …

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The Role Of Different Tie Strength In Disseminating Different Topics On A Microblog, Felicia Natali, Kathleen M. Carley, Feida Zhu, Binxuan Huang Jul 2017

The Role Of Different Tie Strength In Disseminating Different Topics On A Microblog, Felicia Natali, Kathleen M. Carley, Feida Zhu, Binxuan Huang

Research Collection School Of Computing and Information Systems

The study of information flow typically does not distinguish the choices of tie strength on which the information flows. All receivers of the information are assumed to have the same potential to pass on the information. Modifying the SEIZ (susceptible, exposed, infected, skeptic) model, we discover that people choose to retweet strong or weak ties based on the topic. We made two modifications in the model. In the first modification (Model I), we assume that the contact rates of agents in different compartment and the probability of an agent transitioning from one compartment to another are different for strong ties …

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Cyber Foraging: Fifteen Years Later, Rajesh Krishna Balan, Jason Flinn Jul 2017

Cyber Foraging: Fifteen Years Later, Rajesh Krishna Balan, Jason Flinn

Research Collection School Of Computing and Information Systems

Revisiting Mahadev Satyanarayanan's original vision of cyber foraging and reflecting on the last 15 years of related research, the authors discuss the major accomplishments achieved as well as remaining challenges. They also look to current and future applications that could provide compelling application scenarios for making cyber foraging a widely deployed technology. This article is part of a special issue on pervasive computing revisited.

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Cloud-Based Query Evaluation For Energy-Efficient Mobile Sensing, Tianli Mo, Lipyeow Lim, Sougata Sen, Archan Misra, Rajesh Krishna Balan, Youngki Lee Jul 2017

Cloud-Based Query Evaluation For Energy-Efficient Mobile Sensing, Tianli Mo, Lipyeow Lim, Sougata Sen, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we reduce the energy overheads of continuous mobile sensing, specifically for the case of context-aware applications that are interested in collective context or events, i.e., events expressed as a set of complex predicates over sensor data from multiple smartphones. We propose a cloud-based query management and optimization framework, called CloQue, that can support thousands of such concurrent queries, executing over a large number of individual smartphones. Our central insight is that the context of different individuals & groups often have significant correlation, and that this correlation can be learned through standard association rule mining on historical data. …

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Incentivizing The Use Of Bike Trailers For Dynamic Repositioning In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham Jul 2017

Incentivizing The Use Of Bike Trailers For Dynamic Repositioning In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Bike Sharing System (BSS) is a green mode of transportation that is employed extensively for short distance travels in major cities of the world. Unfortunately, the users behaviour driven by their personal needs can often result in empty or full base stations, thereby resulting in loss of customer demand. To counter this loss in customer demand, BSS operators typically utilize a fleet of carrier vehicles for repositioning the bikes between stations. However, this fuel burning mode of repositioning incurs a significant amount of routing, labor cost and further increases carbon emissions. Therefore, we propose a potentially self-sustaining and environment friendly …

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Mopeye: Opportunistic Monitoring Of Per-App Mobile Network Performance, Daoyuan Wu, Rocky K. C. Chang, Weichao Li, Eric K. T. Cheng, Debin Gao Jul 2017

Mopeye: Opportunistic Monitoring Of Per-App Mobile Network Performance, Daoyuan Wu, Rocky K. C. Chang, Weichao Li, Eric K. T. Cheng, Debin Gao

Research Collection School Of Computing and Information Systems

Crowdsourcing mobile user’s network performance has become an effective way of understanding and improving mobile network performance and user quality-of-experience. However, the current measurement method is still based on the landline measurement paradigm in which a measurement app measures the path to fixed (measurement or web) servers. In this work, we introduce a new paradigm of measuring per-app mobile network performance. We design and implement MopEye, an Android app to measure network round-trip delay for each app whenever there is app traffic. This opportunistic measurement can be conducted automatically without user intervention. Therefore, it can facilitate a large-scale and long-term …

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Discovering Newsworthy Themes From Sequenced Data: A Step Towards Computational Journalism, Qi Fan, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan Tan Jul 2017

Discovering Newsworthy Themes From Sequenced Data: A Step Towards Computational Journalism, Qi Fan, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan Tan

Research Collection School Of Computing and Information Systems

Automatic discovery of newsworthy themes from sequenced data can relieve journalists from manually poring over a large amount of data in order to find interesting news. In this paper, we propose a novel k -Sketch query that aims to find k striking streaks to best summarize a subject. Our scoring function takes into account streak strikingness and streak coverage at the same time. We study the k -Sketch query processing in both offline and online scenarios, and propose various streak-level pruning techniques to find striking candidates. Among those candidates, we then develop approximate methods to discover the k most representative …

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Truly Multi-Modal Youtube-8m Video Classification With Video, Audio, And Text, Zhe Wang, Kingsley Kuan, Mathieu Ravant, Gaurav Manek, Sibo Song, Yuan Fang, Et Al Jul 2017

Truly Multi-Modal Youtube-8m Video Classification With Video, Audio, And Text, Zhe Wang, Kingsley Kuan, Mathieu Ravant, Gaurav Manek, Sibo Song, Yuan Fang, Et Al

Research Collection School Of Computing and Information Systems

The YouTube-8M video classification challenge requires teams to classify 0.7 million videos into one or more of 4,716 classes. In this Kaggle competition, we placed in the top 3% out of 650 participants using released video and audio features. Beyond that, we extend the original competition by including text information in the classification, making this a truly multi-modal approach with vision, audio and text. The newly introduced text data is termed as YouTube-8M-Text. We present a classification framework for the joint use of text, visual and audio features, and conduct an extensive set of experiments to quantify the benefit that …

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The Making Of A Successful Analytics Master Degree Program: Experiences And Lessons Drawn For A Young And Small Asian University, Michelle L. F. Cheong Jul 2017

The Making Of A Successful Analytics Master Degree Program: Experiences And Lessons Drawn For A Young And Small Asian University, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Singapore Management University's School of Information Systems is a young school within a young and small university in Asia. Being young and small, establishing a successful analytics master degree program required extensive landscape research, assessment of its own strengths and weaknesses, having a committed team, and having a clear vision to meet the ever-changing needs of the industry. The Master of IT in Business (Analytics) program, established since 2011, has grown from an annual intake of 16 to 128 students in six years. This article attempts to describe the design process, challenges faced, decisions made, and the key actions taken, …

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Does Director Interlock Impact The Diffusion Of Accounting Method Choice?, Jie Han, Nan Hu, Ling Liu, Gaoliang Tian Jul 2017

Does Director Interlock Impact The Diffusion Of Accounting Method Choice?, Jie Han, Nan Hu, Ling Liu, Gaoliang Tian

Research Collection School Of Computing and Information Systems

This paper examines the influence of director interlock on firms' discrete accounting method choices from the perspective of behavior diffusion. We argue that firm managers will imitate their interlocked-partner firm's accounting method choices when choosing their own accounting methods. We find that when there is an interlock relationship between two firms, their accounting method choices, including inventory and depreciation methods, are similar to each other, indicating that accounting method choices can diffuse across firms through director interlock. In addition, such similarity is greater the longer the interlock relationship between the two firms is and as uncertainty increases. Further, the interlock …

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A Domain Based Approach To Social Relation Recognition, Qianru Sun, Bernt Schiele, Mario Fritz Jul 2017

A Domain Based Approach To Social Relation Recognition, Qianru Sun, Bernt Schiele, Mario Fritz

Research Collection School Of Computing and Information Systems

Social relations are the foundation of human daily life. Developing techniques to analyze such relations from visual data bears great potential to build machines that better understand us and are capable of interacting with us at a social level. Previous investigations have remained partial due to the overwhelming diversity and complexity of the topic and consequently have only focused on a handful of social relations. In this paper, we argue that the domain-based theory from social psychology is a great starting point to systematically approach this problem. The theory provides coverage of all aspects of social relations and equally is …

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