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Articles 4891 - 4920 of 9025

Full-Text Articles in Computer Sciences

Delving Into Salient Object Subitizing And Detection, Shengfeng He, Jianbo Jiao, Xiaodan Zhang, Guoqiang Han, Rynson W.H Lau Oct 2017

Delving Into Salient Object Subitizing And Detection, Shengfeng He, Jianbo Jiao, Xiaodan Zhang, Guoqiang Han, Rynson W.H Lau

Research Collection School Of Computing and Information Systems

Subitizing (i.e., instant judgement on the number) and detection of salient objects are human inborn abilities. These two tasks influence each other in the human visual system. In this paper, we delve into the complementarity of these two tasks. We propose a multi-task deep neural network with weight prediction for salient object detection, where the parameters of an adaptive weight layer are dynamically determined by an auxiliary subitizing network. The numerical representation of salient objects is therefore embedded into the spatial representation. The proposed joint network can be trained end-to-end using backpropagation. Experiments show the proposed multi-task network outperforms existing …

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Pic2dish: A Customized Cooking Assistant System, Yongsheng An, Yu Cao, Jingjing Chen, Chong-Wah Ngo, Jia Jia, Huanbo Luan, Tat-Seng Chua Oct 2017

Pic2dish: A Customized Cooking Assistant System, Yongsheng An, Yu Cao, Jingjing Chen, Chong-Wah Ngo, Jia Jia, Huanbo Luan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The art of cooking is always fascinating. Nevertheless, reproducing a delicious dish that one has never encountered before is not easy. Even if the name of dish is known and the corresponding recipe could be retrieved, the right ingredients for cooking the dish may not be available due to factors such as geography region or season. Furthermore, knowing how to cut, cook and control timing may be challenging for one whose has no cooking experience. In this paper, an all-around cooking assistant mobile app, named Pic2Dish, is developed to help users who would like to cook a dish but neither …

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Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua Oct 2017

Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of …

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O2o Service Composition With Social Collaboration, Wenyi Qian, Xin Peng, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao Oct 2017

O2o Service Composition With Social Collaboration, Wenyi Qian, Xin Peng, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao

Research Collection School Of Computing and Information Systems

In Online-to-Offline (O2O) commerce, customer services may need to be composed from online and offline services. Such composition is challenging, as it requires effective selection of appropriate services that, in turn, support optimal combination of both online and offline services. In this paper, we address this challenge by proposing an approach to O2O service composition which combines offline route planning and social collaboration to optimize service selection. We frame general O2O service composition problems using timed automata and propose an optimization procedure that incorporates: (1) a Markov Chain Monte Carlo (MCMC) algorithm to stochastically select a concrete composite service, and …

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Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng Oct 2017

Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng

Research Collection School Of Computing and Information Systems

Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial and valuable to mobile users, wireless carriers and city authorities. Predicting cellular traffic in modern metropolis is particularly challenging because of the tremendous temporal and spatial dynamics introduced by diverse user Internet behaviours and frequent user mobility citywide. In this paper, we characterize and investigate the root causes of such dynamics in cellular traffic through a big cellular usage dataset covering 1.5 million users and 5,929 cell towers in a major city of China. We reveal intensive spatio-temporal dependency even among distant cell towers, which is largely overlooked in …

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Strong Authenticated Key Exchange With Auxiliary Inputs, Rongmao Chen, Yi Mu, Guomin Yang, Willy Susilo, Fuchun Guo Oct 2017

Strong Authenticated Key Exchange With Auxiliary Inputs, Rongmao Chen, Yi Mu, Guomin Yang, Willy Susilo, Fuchun Guo

Research Collection School Of Computing and Information Systems

Leakage attacks, including various kinds of side-channel attacks, allow an attacker to learn partial information about the internal secrets such as the secret key and the randomness of a cryptographic system. Designing a strong, meaningful, yet achievable security notion to capture practical leakage attacks is one of the primary goals of leakage-resilient cryptography. In this work, we revisit the modelling and design of authenticated key exchange (AKE) protocols with leakage resilience. We show that the prior works on this topic are inadequate in capturing realistic leakage attacks. To close this research gap, we propose a new security notion named leakage-resilient …

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Spatiotemporal Identification Of Anomalies In A Wildlife Preserve, Bharadwaj Kishan, Jason Guan Jie Ong, Yanrong Zhang, Tin Seong Kam Oct 2017

Spatiotemporal Identification Of Anomalies In A Wildlife Preserve, Bharadwaj Kishan, Jason Guan Jie Ong, Yanrong Zhang, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The datasets released for the VAST Challenge 2017 comprise vehicle movement data captured with RFID sensors, chemical emission data from factories captured by gas sensors, and image attributes of the wildlife plant health obtained from satellites, all pertaining to a fictional wildlife preserve. Using visual analytics, a compelling hypothesis is established to link the spatiotemporal datasets to the phenomenon, where the count of a bird specimen is found to decline over a given year. Anomalies in vehicle traffic patterns are linked to proximal factory emissions, and further associated with satellite imagery that show proof of degradation in plant quality in …

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A Conceptual Framework For Analyzing Students' Feedback, Venky Shankararaman, Swapna Gottipati, Sandy Gan Oct 2017

A Conceptual Framework For Analyzing Students' Feedback, Venky Shankararaman, Swapna Gottipati, Sandy Gan

Research Collection School Of Computing and Information Systems

In academic institutions it is normal practice that at the end of each term,students are required to complete a questionnaire that is designed to gather students’perceptions of the instructor and their learning experience in the course. This questionnaire comprises of Likert-scale questions and qualitative questions.One of the important goals of this exercise is to enable the instructor and the senior management to examine the feedback and then enhance students’ learning experience. In most universities, including our own, a lot of attention is paid to the quantitative feedback, which is summarized and statistical comparisons are computed, analysed and presented. However, the …

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Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam Oct 2017

Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The Visual Analytics Science and Technology (VAST) Challenge 2017 Mini-Challenge 1 dataset mirrored the challenging scenarios in analysing large spatiotemporal movement tracking datasets. The datasets provided contains a 13-month movement data generated by five types of sensors, for six types of vehicles passing through the Boonsong Lekagul Nature Preserve. We present an application developed with the market leading visualisation software Tableau to provide an interactive visual analysis of the multi-dimensional spatiotemporal datasets. Our interactive application allows the user to perform an interactive analysis to observe movement patterns, study vehicle trajectories and identify movement anomalies while allowing them to customise the …

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Combinatorial Auction For Transportation Matching Service: Formulation And Adaptive Large Neighborhood Search Heuristic, Baoxiang Li, Hoong Chuin Lau Oct 2017

Combinatorial Auction For Transportation Matching Service: Formulation And Adaptive Large Neighborhood Search Heuristic, Baoxiang Li, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper considers the problem of matching multiple shippers and multi-transporters for pickups and drop-offs, where the goal is to select a subset of group jobs (shipper bids) that maximizes profit. This is the underlying winner determination problem in an online auction-based vehicle sharing platform that matches transportation demand and supply, particularly in a B2B last-mile setting. Each shipper bid contains multiple jobs, and each job has a weight, volume, pickup location, delivery location and time window. On the other hand, each transporter bid specifies the vehicle capacity, available time periods, and a cost structure. This double-sided auction will be …

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Fastshrinkage: Perceptually-Aware Retargeting Toward Mobile Platforms, Zhenguang Liu, Zepeng Wang, Luming Zhang, Rajiv Ratn Shah, Yingjie Xia, Yi Yang, Wei Liu Oct 2017

Fastshrinkage: Perceptually-Aware Retargeting Toward Mobile Platforms, Zhenguang Liu, Zepeng Wang, Luming Zhang, Rajiv Ratn Shah, Yingjie Xia, Yi Yang, Wei Liu

Research Collection School Of Computing and Information Systems

Retargeting aims at adapting an original high-resolution photo/video to a low-resolution screen with an arbitrary aspect ratio. Conventional approaches are generally based on desktop PCs, since the computation might be intolerable for mobile platforms (especially when retargeting videos). Besides, only low-level visual features are exploited typically, whereas human visual perception is not well encoded. In this paper, we propose a novel retargeting framework which fast shrinks photo/video by leveraging human gaze behavior. Specifically, we first derive a geometry-preserved graph ranking algorithm, which efficiently selects a few salient object patches to mimic human gaze shifting path (GSP) when viewing each scenery. …

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Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang Oct 2017

Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang

Research Collection School Of Computing and Information Systems

Target imaging and material identification play an important role in many real-life applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commercial of-the-shelf (COTS) RFID devices. The key intuition is that different materials and target sizes cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system including (i) indoor environments exhibit rich multipath which breaks the linear relationship between …

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Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw Oct 2017

Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Online reviews are prevalent. When recounting their experience with a product, service, or venue, in addition to textual narration, a reviewer frequently includes images as photographic record. While textual sentiment analysis has been widely studied, in this paper we are interested in visual sentiment analysis to infer whether a given image included as part of a review expresses the overall positive or negative sentiment of that review. Visual sentiment analysis can be formulated as image classification using deep learning methods such as Convolutional Neural Networks or CNN. However, we observe that the sentiment captured within an image may be affected …

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Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li Oct 2017

Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li

Research Collection School Of Computing and Information Systems

Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …

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Which Packages Would Be Affected By This Bug Report?, Qiao Huang, David Lo, Xin Xia, Qingye Wang, Shanping Li Oct 2017

Which Packages Would Be Affected By This Bug Report?, Qiao Huang, David Lo, Xin Xia, Qingye Wang, Shanping Li

Research Collection School Of Computing and Information Systems

A large project (e.g., Ubuntu) usually contains a large number of software packages. Sometimes the same bug report in such project would affect multiple packages, and developers of different packages need to collaborate with one another to fix the bug. Unfortunately, the total number of packages involved in a project like Ubuntu is relatively large, which makes it time-consuming to manually identify packages that are affected by a bug report. In this paper, we propose an approach named PkgRec that consists of 2 components: a name matching component and an ensemble learning component. In the name matching component, we assign …

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Sol: A Library For Scalable Online Learning Algorithms, Yue Wu, Steven C. H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu Oct 2017

Sol: A Library For Scalable Online Learning Algorithms, Yue Wu, Steven C. H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu

Research Collection School Of Computing and Information Systems

SOL is an open-source library for scalable online learning with high-dimensional data. The library provides a family of regular and sparse online learning algorithms for large-scale classification tasks with high efficiency, scalability, portability, and extensibility. We provide easy-to-use command-line tools, python wrappers and library calls for users and developers, and comprehensive documents for both beginners and advanced users. SOL is not only a machine learning toolbox, but also a comprehensive experimental platform for online learning research. Experiments demonstrate that SOL is highly efficient and scalable for large-scale learning with high-dimensional data.

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Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li Oct 2017

Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li

Research Collection School Of Computing and Information Systems

Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …

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Design And Implementation Of An Enterprise Integrated Project Environment: Experience From An Information Systems Program, Swapna Gottipati, Venky Shankararaman Oct 2017

Design And Implementation Of An Enterprise Integrated Project Environment: Experience From An Information Systems Program, Swapna Gottipati, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Real world information technology projects cut acrossmultiple business domains and processes, involve large amounts of data and anassortment of different technologies. Advancedcourses within an IS programs must include projects that help students gain aholistic view of an enterprise by exposing them to business domains,business processes and technical knowledge and skills that will help them design and deliver enterpriseprojects. In order to guide the instructor to effectively design and implementsuch enterprise project experiences, in this paper, we propose an enterpriseintegrated project environment (EIPE) framework based on business domains andbusiness processes. Additionally, we share our experience in implementing thisframework in the Data …

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Target Material Identification With Commodity Rfid Devices, Xinyi Li, Chao Feng, Nana Ding, Ju Wang, Jie Xiong, Yuhui Ren, Xiaojiang Chen, Dingyi Fang Oct 2017

Target Material Identification With Commodity Rfid Devices, Xinyi Li, Chao Feng, Nana Ding, Ju Wang, Jie Xiong, Yuhui Ren, Xiaojiang Chen, Dingyi Fang

Research Collection School Of Computing and Information Systems

Target material identification plays an important role in many reallife applications. This paper introduces a system that can identify the material type with cheap commercial off-the-shelf (COTS) RFID devices. The key intuition is that different materials cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. However, without knowing either material type, trying to obtain the information is challenging. We propose a method to address this challenge and evaluate the method's performance in real-world environment. The results show that we achieve higher than 94% material identification accuracies for 10 liquids …

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Tensor Factorization For Low-Rank Tensor Completion, Pan Zhou, Canyi Lu, Zhouchen Lin, Chao Zhang Oct 2017

Tensor Factorization For Low-Rank Tensor Completion, Pan Zhou, Canyi Lu, Zhouchen Lin, Chao Zhang

Research Collection School Of Computing and Information Systems

Recently, a tensor nuclear norm (TNN) based method [1] was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the lowrank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method …

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New Framework Of Password-Based Authenticated Key Exchange From Only-One Lossy Encryption, Haiyang Xue, Bao Li, Jingnan He Oct 2017

New Framework Of Password-Based Authenticated Key Exchange From Only-One Lossy Encryption, Haiyang Xue, Bao Li, Jingnan He

Research Collection School Of Computing and Information Systems

In this paper, we introduce a new framework of password-based key exchange (PAKE). Until now, most PAKEs are based on smooth projective hash function on secure encryption. Our PAKE does not rely on smooth projective hash function, and consists of a variate lossy encryption, called only-one lossy encryption, and indistinguishable plaintext checkable secure encryption. We also give construction of only-one lossy encryption based decisional Diffie Hellman (DDH) and learning with errors (LWE) assumptions. Although the instantiation based on DDH assumption does not improve efficiency of precious works, our framework provides more easier and elegant way to construct PAKE from LWE …

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Artificial Intelligence Research In Singapore: Assisting The Development Of A Smart Nation, Pradeep Varakantham, Bo An, Bryan Low, Jie Zhang Oct 2017

Artificial Intelligence Research In Singapore: Assisting The Development Of A Smart Nation, Pradeep Varakantham, Bo An, Bryan Low, Jie Zhang

Research Collection School Of Computing and Information Systems

Artificial Intelligence (AI) research in Singapore is focused on accelerating the country’s development into a Smart Nation. Specifically, AI has been employed extensively in either augmenting the intelligence of humans or in developing automated methods and systems to improve quality of life in Singapore.

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Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer Oct 2017

Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer

Research Collection Lee Kong Chian School Of Business

The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry, once a customer enters the network, an ad-serving decision must be made in a matter of milliseconds. In this work, we describe the design and implementation of an ad-serving algorithm that incorporates machine-learning methods to make personalized ad-serving decisions within milliseconds. We developed this algorithm for Vungle Inc., one of the largest global mobile ad networks. Our approach also …

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A Validated Set Of Smells In Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Arie Van Deursen, Marco Aurélio Gerosa Oct 2017

A Validated Set Of Smells In Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Arie Van Deursen, Marco Aurélio Gerosa

Research Collection School Of Computing and Information Systems

Code smells are symptoms of poor design and implementation choices that may hinder code comprehension, and possibly increase change-and defect-proneness. A vast catalogue of smells has been defined in the literature, and it includes smells that can be found in any kind of system (e.g., God Classes), regardless of their architecture. On the other hand, software systems adopting specific architectures (e.g., the Model-View-Controller pattern) can be also affected by other types of poor practices. We surveyed and interviewed 53 MVC developers to collect bad practices to avoid while working on Web MVC applications. Then, we followed an open coding procedure …

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Semantic Reasoning In Zero Example Video Event Retrieval, M. H. T. De Boer, Yi-Jie Lu, Hao Zhang, Klamer Schutte, Chong-Wah Ngo, Wessel Kraaij Oct 2017

Semantic Reasoning In Zero Example Video Event Retrieval, M. H. T. De Boer, Yi-Jie Lu, Hao Zhang, Klamer Schutte, Chong-Wah Ngo, Wessel Kraaij

Research Collection School Of Computing and Information Systems

Searching in digital video data for high-level events, such as a parade or a car accident, is challenging when the query is textual and lacks visual example images or videos. Current research in deep neural networks is highly beneficial for the retrieval of high-level events using visual examples, but without examples it is still hard to (1) determine which concepts are useful to pre-train (Vocabulary challenge) and (2) which pre-trained concept detectors are relevant for a certain unseen high-level event (Concept Selection challenge). In our article, we present our Semantic Event Retrieval Systemwhich (1) shows the importance of high-level concepts …

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Graphh: High Performance Big Graph Analytics In Small Clusters, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao Sep 2017

Graphh: High Performance Big Graph Analytics In Small Clusters, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

It is common for real-world applications to analyze big graphs using distributed graph processing systems. Popular in-memory systems require an enormous amount of resources to handle big graphs. While several out-of-core approaches have been proposed for processing big graphs on disk, the high disk I/O overhead could significantly reduce performance. In this paper, we propose GraphH to enable highperformance big graph analytics in small clusters. Specifically, we design a two-stage graph partition scheme to evenly divide the input graph into partitions, and propose a GAB (GatherApply-Broadcast) computation model to make each worker process a partition in memory at a time. …

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Joanaudit: A Tool For Auditing Common Injection Vulnerabilities, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand Sep 2017

Joanaudit: A Tool For Auditing Common Injection Vulnerabilities, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand

Research Collection School Of Computing and Information Systems

JoanAudit is a static analysis tool to assist security auditors in auditing Web applications and Web services for common injection vulnerabilities during software development. It automatically identifies parts of the program code that are relevant for security and generates an HTML report to guide security auditors audit the source code in a scalable way. JoanAudit is configured with various security-sensitive input sources and sinks relevant to injection vulnerabilities and standard sanitization procedures that prevent these vulnerabilities. It can also automatically fix some cases of vulnerabilities in source code — cases where inputs are directly used in sinks without any form …

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Sequential Schemes For Frequentist Estimation Of Properties In Statistical Model Checking, Cyrille Jegourel, Jun Sun, Jin Song Dong Sep 2017

Sequential Schemes For Frequentist Estimation Of Properties In Statistical Model Checking, Cyrille Jegourel, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Statistical Model Checking (SMC) is an approximate verification method that overcomes the state space explosion problem for probabilistic systems by Monte Carlo simulations. Simulations might be however costly if many samples are required. It is thus necessary to implement efficient algorithms to reduce the sample size while preserving precision and accuracy. In the literature, some sequential schemes have been provided for the estimation of property occurrence based on predefined confidence and absolute or relative error. Nevertheless, these algorithms remain conservative and may result in huge sample sizes if the required precision standards are demanding. In this article, we compare some …

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An Efficient Privacy-Preserving Outsourced Computation Over Public Data, Ximeng Liu, Baodong Qin, Robert H. Deng, Yingjiu Li Sep 2017

An Efficient Privacy-Preserving Outsourced Computation Over Public Data, Ximeng Liu, Baodong Qin, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

In this paper, we propose a new efficient privacy preserving outsourced computation framework over public data, called EPOC. EPOC allows a user to outsource the computation of a function over multi-dimensional public data to the cloud while protecting the privacy of the function and its output. Specifically, we introduce three types of EPOC in order to tradeoff different levels of privacy protection and performance. We present a new cryptosystem called Switchable Homomorphic Encryption with Partial Decryption (SHED) as the core cryptographic primitive for EPOC.We introduce two coding techniques, called message pre-coding and message extending and coding respectively, for messages encrypted …

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Micro-Review Synthesis For Multi-Entity Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas Sep 2017

Micro-Review Synthesis For Multi-Entity Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Location-based social networks (LBSNs), exemplified by Foursquare, are fast gaining popularity. One important feature of LBSNs is micro-review. Upon check-in at a particular venue, a user may leave a short review (up to 200 characters long), also known as a tip. These tips are an important source of information for others to know more about various aspects of an entity (e.g., restaurant), such as food, waiting time, or service. However, a user is often interested not in one particular entity, but rather in several entities collectively, for instance within a neighborhood or a category. In this paper, we address the …

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