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Articles 4441 - 4470 of 9025

Full-Text Articles in Computer Sciences

Interpretable Multimodal Retrieval For Fashion Products, Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua Oct 2018

Interpretable Multimodal Retrieval For Fashion Products, Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Deep learning methods have been successfully applied to fashion retrieval. However, the latent meaning of learned feature vectors hinders the explanation of retrieval results and integration of user feedback. Fortunately, there are many online shopping websites organizing fashion items into hierarchical structures based on product taxonomy and domain knowledge. Such structures help to reveal how human perceive the relatedness among fashion products. Nevertheless, incorporating structural knowledge for deep learning remains a challenging problem. This paper presents techniques for organizing and utilizing the fashion hierarchies in deep learning to facilitate the reasoning of search results and user intent. The novelty of …

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Knowledge-Aware Multimodal Dialogue Systems, Lizi Liao, Yunshan Ma, Xiangnan He, Richang Hong, Tat-Seng Chua Oct 2018

Knowledge-Aware Multimodal Dialogue Systems, Lizi Liao, Yunshan Ma, Xiangnan He, Richang Hong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

By offering a natural way for information seeking, multimodal dialogue systems are attracting increasing attention in several domains such as retail, travel etc. However, most existing dialogue systems are limited to textual modality, which cannot be easily extended to capture the rich semantics in visual modality such as product images. For example, in fashion domain, the visual appearance of clothes and matching styles play a crucial role in understanding the user's intention. Without considering these, the dialogue agent may fail to generate desirable responses for users. In this paper, we present a Knowledge-aware Multimodal Dialogue (KMD) model to address the …

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Mixed-Reality For Object-Focused Remote Collaboration, Martin Feick, Anthony Tang, Scott Bateman Oct 2018

Mixed-Reality For Object-Focused Remote Collaboration, Martin Feick, Anthony Tang, Scott Bateman

Research Collection School Of Computing and Information Systems

In this paper we outline the design of a mixed-reality system to support object-focused remote collaboration. Here, being able to adjust collaborators' perspectives on the object as well as understand one another's perspective is essential to support effective collaboration over distance. We propose a low-cost mixed-reality system that allows users to: (1) quickly align and understand each other's perspective; (2) explore objects independently from one another, and (3) render gestures in the remote's workspace. In this work, we focus on the expert's role and we introduce an interaction technique allowing users to quickly manipulation 3D virtual objects in space.

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Predicting Visual Context For Unsupervised Event Segmentation In Continuous Photo-Streams, Ana García Del Molino, Joo-Hwee Lim, Ah-Hwee Tan Oct 2018

Predicting Visual Context For Unsupervised Event Segmentation In Continuous Photo-Streams, Ana García Del Molino, Joo-Hwee Lim, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Segmenting video content into events provides semantic structures for indexing, retrieval, and summarization. Since motion cues are not available in continuous photo-streams, and annotations in lifelogging are scarce and costly, the frames are usually clustered into events by comparing the visual features between them in an unsupervised way. However, such methodologies are ineffective to deal with heterogeneous events, e.g. taking a walk, and temporary changes in the sight direction, e.g. at a meeting. To address these limitations, we propose Contextual Event Segmentation (CES), a novel segmentation paradigm that uses an LSTM-based generative network to model the photo-stream sequences, predict their …

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Enabling Verifiable Multiple Keywords Search Over Encrypted Cloud Data, Yinbin Miao, Jian Weng, Ximeng Liu, Kim-Kwang Raymond Choo, Zhiquan Liu, Hongwei Li Oct 2018

Enabling Verifiable Multiple Keywords Search Over Encrypted Cloud Data, Yinbin Miao, Jian Weng, Ximeng Liu, Kim-Kwang Raymond Choo, Zhiquan Liu, Hongwei Li

Research Collection School Of Computing and Information Systems

Searchable Encryption (SE) enables a user to search over encrypted data, such as data stored in a remote cloud server. Existing certificate-, identity-, and attribute-based SE schemes suffer from certificate management or key escrow limitations. Furthermore, the semi-honest-but-curious cloud may conduct partial search operations and return a fraction of the search results (i.e., incomplete results) in order to reduce costs. In this paper, we present a secure cryptographic primitive, Verifiable Multiple Keywords Search (VMKS) over ciphertexts, which leverages the Identity-Based Encryption (IBE) and certificateless signature techniques. The VMKS scheme allows the user to verify the correctness of …

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Optimal In-Place Suffix Sorting, Zhize Li, Jian Li, Hongwei Huo Oct 2018

Optimal In-Place Suffix Sorting, Zhize Li, Jian Li, Hongwei Huo

Research Collection School Of Computing and Information Systems

The suffix array is a fundamental data structure for many applications that involve string searching and data compression. Designing time/space-efficient suffix array construction algorithms has attracted significant attentions and considerable advances have been made for the past 20 years. We obtain the first in-place linear time suffix array construction algorithms that are optimal both in time and space for (read-only) integer alphabets. Our algorithm settles the open problem posed by Franceschini and Muthukrishnan in ICALP 2007. The open problem asked to design in-place algorithms in $o(n \log n)$ time and ultimately, in $O(n)$ time for (read-only) integer alphabets with $|\Sigma| …

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Investigating Multimodal Affect Sensing In An Affective Tutoring System Using Unobtrusive Sensors, Hua Leong Fwa, Lindsay Marshall Oct 2018

Investigating Multimodal Affect Sensing In An Affective Tutoring System Using Unobtrusive Sensors, Hua Leong Fwa, Lindsay Marshall

Research Collection School Of Computing and Information Systems

Affect inextricably plays a critical role in the learning process. In this study, we investigate the multimodal fusion of facial, keystrokes, mouse clicks, head posture and contextual features for the detection of student’s frustration in an Affective Tutoring System. The results (AUC=0.64) demonstrated empirically that a multimodal approach offers higher accuracy and better robustness as compared to a unimodal approach. In addition, the inclusion of keystrokes and mouse clicks makes up for the detection gap where video based sensing modes (facial and head postures) are not available. The findings in this paper will dovetail to our end research objective of …

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Hawkeye: Towards A Desired Directed Grey-Box Fuzzer, Hongxu Chen, Yinxing Xue, Yuekang Li, Bihuan Chen, Xiaofei Xie, Xiuheng Wu, Yang Liu Oct 2018

Hawkeye: Towards A Desired Directed Grey-Box Fuzzer, Hongxu Chen, Yinxing Xue, Yuekang Li, Bihuan Chen, Xiaofei Xie, Xiuheng Wu, Yang Liu

Research Collection School Of Computing and Information Systems

Grey-box fuzzing is a practically effective approach to test real-world programs. However, most existing grey-box fuzzers lack directedness, i.e. the capability of executing towards user-specified target sites in the program. To emphasize existing challenges in directed fuzzing, we propose Hawkeye to feature four desired properties of directed grey-box fuzzers. Owing to a novel static analysis on the program under test and the target sites, Hawkeye precisely collects the information such as the call graph, function and basic block level distances to the targets. During fuzzing, Hawkeye evaluates exercised seeds based on both static information and the execution traces to generate …

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Visforum: A Visual Analysis System For Exploring User Groups In Online Forums, Siwei Fu, Yong Wang, Yi Yang, Qingqing Bi, Fangzhou Guo, Huamin Qu Oct 2018

Visforum: A Visual Analysis System For Exploring User Groups In Online Forums, Siwei Fu, Yong Wang, Yi Yang, Qingqing Bi, Fangzhou Guo, Huamin Qu

Research Collection School Of Computing and Information Systems

User grouping in asynchronous online forums is a common phenomenon nowadays. People with similar backgrounds or shared interests like to get together in group discussions. As tens of thousands of archived conversational posts accumulate, challenges emerge for forum administrators and analysts to effectively explore user groups in large-volume threads and gain meaningful insights into the hierarchical discussions. Identifying and comparing groups in discussion threads are nontrivial, since the number of users and posts increases with time and noises may hamper the detection of user groups. Researchers in data mining fields have proposed a large body of algorithms to explore user …

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Break The Dead End Of Dynamic Slicing: Localizing Data And Control Omission Bug, Yun Lin, Jun Sun, Lyly Tran, Guangdong Bai, Haijun Wang, Jin Song Dong Sep 2018

Break The Dead End Of Dynamic Slicing: Localizing Data And Control Omission Bug, Yun Lin, Jun Sun, Lyly Tran, Guangdong Bai, Haijun Wang, Jin Song Dong

Research Collection School Of Computing and Information Systems

Dynamic slicing is a common way of identifying the root cause when a program fault is revealed. With the dynamic slicing technique, the programmers can follow data and control flow along the program execution trace to the root cause. However, the technique usually fails to work on omission bugs, i.e., the faults which are caused by missing executing some code. In many cases, dynamic slicing over-skips the root cause when an omission bug happens, leading the debugging process to a dead end. In this work, we conduct an empirical study on the omission bugs in the Defects4J bug repository. Our …

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Pfix: Fixing Concurrency Bugs Based On Memory Access Patterns, Huarui Lin, Zan Wang, Shuang Liu, Jun Sun, Dongdi Zhang, Guangning Wei Sep 2018

Pfix: Fixing Concurrency Bugs Based On Memory Access Patterns, Huarui Lin, Zan Wang, Shuang Liu, Jun Sun, Dongdi Zhang, Guangning Wei

Research Collection School Of Computing and Information Systems

Concurrency bugs of a multi-threaded program may only manifest with certain scheduling, i.e., they are heisenbugs which are observed only from time to time if we execute the same program with the same input multiple times. They are notoriously hard to fix. In this work, we propose an approach to automatically fix concurrency bugs. Compared to previous approaches, our key idea is to systematically fix concurrency bugs by inferring locking policies from failure inducing memory-access patterns. That is, we automatically identify memory-access patterns which are correlated with the manifestation of the bug, and then conjecture what is the intended locking …

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Transferring Time-Series Discrete Choice To Link-Based Route Choice In Space: Estimating Vehicle Type Preference Using Recursive Logit Model, Fabian Bastin, Yan Liu, Cinzia Cirillo, Tien Mai Sep 2018

Transferring Time-Series Discrete Choice To Link-Based Route Choice In Space: Estimating Vehicle Type Preference Using Recursive Logit Model, Fabian Bastin, Yan Liu, Cinzia Cirillo, Tien Mai

Research Collection School Of Computing and Information Systems

This paper considers a sequential discrete choice problem in a time domain, formulated and solved as a route choice problem in a space domain. Starting from a dynamic specification of time-series discrete choices, we show how it is transferrable to link-based route choices that can be formulated by a finite path choice multinomial logit model. This study establishes that modeling sequential choices over time and in space are equivalent as long as the utility of the choice sequence is additive over the decision steps, the link-specific attributes are deterministic, and the decision process is Markovian. We employ the recursive logit …

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Teaching Basic Programming To Pre-University Students Through Blended Learning Pedagogy: A Descriptive Study, Vandana Ramachandra Rao, Ngee Mok Heng Sep 2018

Teaching Basic Programming To Pre-University Students Through Blended Learning Pedagogy: A Descriptive Study, Vandana Ramachandra Rao, Ngee Mok Heng

Research Collection School Of Computing and Information Systems

Students enrolling for undergraduate programmes in Singapore would have either finished their polytechnic diploma or completed Junior College (JC) studies. Most pre-university students coming through the JC pathway are not exposed to programming as computing is offered as a subject in a very few JCs. The authors of this paper conducted four runs of an introductory programing course between 2016 and 2017 for a research project funded by the Ministry of Education, Singapore. The project named “Let’s Code!” was intended to introduce fundamental programming concepts to students and guide them to consider taking a computer-science related degree for their university …

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Self-Supervised Feature Learning For Semantic Segmentation Of Overhead Imagery, Suriya Singh, Anil Batra, Guansong Pang, Lorenzo Torresani, Saikat Basu, Manohar Paluri, C. V. Jawahar Sep 2018

Self-Supervised Feature Learning For Semantic Segmentation Of Overhead Imagery, Suriya Singh, Anil Batra, Guansong Pang, Lorenzo Torresani, Saikat Basu, Manohar Paluri, C. V. Jawahar

Research Collection School Of Computing and Information Systems

Overhead imageries play a crucial role in many applications such as urban planning, crop yield forecasting, mapping, and policy making. Semantic segmentation could enable automatic, efficient, and large-scale understanding of overhead imageries for these applications. However, semantic segmentation of overhead imageries is a challenging task, primarily due to the large domain gap from existing research in ground imageries, unavailability of large-scale dataset with pixel-level annotations, and inherent complexity in the task. Readily available vast amount of unlabeled overhead imageries share more common structures and patterns compared to the ground imageries, therefore, its large-scale analysis could benefit from unsupervised feature learning …

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Wasserstein Divergence For Gans, J. Wu, Zhiwu Huang, J. Thoma, D. Acharya, Gool L. Van Sep 2018

Wasserstein Divergence For Gans, J. Wu, Zhiwu Huang, J. Thoma, D. Acharya, Gool L. Van

Research Collection School Of Computing and Information Systems

In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance. However, it is very challenging to approximate the k-Lipschitz constraint required by the Wasserstein-1 metric (W-met). In this paper, we propose a novel Wasserstein divergence (W-div), which is a relaxed version of W-met and does not require the k-Lipschitz constraint. As a concrete application, we introduce a Wasserstein divergence objective for GANs (WGAN-div), which can faithfully approximate W-div through optimization. Under various settings, including …

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Diversity In Online Advertising: A Case Study Of 69 Brands On Social Media, Jisun An, Ingmar Weber Sep 2018

Diversity In Online Advertising: A Case Study Of 69 Brands On Social Media, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Lack of diversity in advertising is a long-standing problem. Despite growing cultural awareness and missed business opportunities, many minorities remain under- or inappropriately represented in advertising. Previous research has studied how people react to culturally embedded ads, but such work focused mostly on print media or television using lab experiments. In this work, we look at diversity in content posted by 69 U.S. brands on two social media platforms, Instagram and Facebook. Using face detection technology, we infer the gender, race, and age of both the faces in the ads and of the users engaging with ads. Using this dataset, …

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Bilock: User Authentication Via Dental Occlusion Biometrics, Yongpan Zou, Meng Zhao, Zimu Zhou, Jiawei Lin, Mo Li, Kaishun Wu Sep 2018

Bilock: User Authentication Via Dental Occlusion Biometrics, Yongpan Zou, Meng Zhao, Zimu Zhou, Jiawei Lin, Mo Li, Kaishun Wu

Research Collection School Of Computing and Information Systems

User authentication on smart devices is indispensable to keep data privacy and security. It is especially significant for emerging wearable devices such as smartwatches considering data sensitivity in them. However, conventional authentication methods are not applicable for wearables due to constraints of size and hardware, which makes present wearable devices lack convenient, secure and low-cost authentication schemes. To tackle this problem, we reveal a novel biometric authentication mechanism which makes use of sounds of human dental occlusion (i.e., tooth click). We demonstrate its feasibility by comprehensive measurement study, and design a prototype-BiLock with two Android platforms. Extensive real-world experiments have …

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Concessive Online/Offline Attribute Based Encryption With Cryptographic Reverse Firewalls: Secure And Efficient Fine-Grained Access Control On Corrupted Machines, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Song, Shuzhou Sun, Yuting Xiao Sep 2018

Concessive Online/Offline Attribute Based Encryption With Cryptographic Reverse Firewalls: Secure And Efficient Fine-Grained Access Control On Corrupted Machines, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Song, Shuzhou Sun, Yuting Xiao

Research Collection School Of Computing and Information Systems

Attribute based encryption (ABE) has potential to be applied in various cloud computing applications. However, the Snowden revelations show that powerful adversaries can corrupt users’ machines to compromise the security, and many implementations of provably secure encryption schemes may present undetectable vulnerabilities that can expose secret, e.g., the scheme still works properly even some backdoors have been stealthily engineered on users’ machines. Undoubtedly, ABE is also facing the above security threats. Recently, Mironov and Stephens-Davidowitz proposed cryptographic reverse firewall (CRF) to solve the problem. Unfortunately, no CRF-based protection for ABE has been proposed so far due to the complex system …

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Rule-Based Specification Mining Leveraging Learning To Rank, Zherui Cao, Yuan Tian, Bui Tien Duy Le, David Lo Sep 2018

Rule-Based Specification Mining Leveraging Learning To Rank, Zherui Cao, Yuan Tian, Bui Tien Duy Le, David Lo

Research Collection School Of Computing and Information Systems

Software systems are often released without formal specifications. To deal with the problem of lack of and outdated specifications, rule-based specification mining approaches have been proposed. These approaches analyze execution traces of a system to infer the rules that characterize the protocols, typically of a library, that its clients must obey. Rule-based specification mining approaches work by exploring the search space of all possible rules and use interestingness measures to differentiate specifications from false positives. Previous rule-based specification mining approaches often rely on one or two interestingness measures, while the potential benefit of combining multiple available interestingness measures is not …

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Resonance Attacks On Load Frequency Control Of Smart Grids, Yongdong Wu, Zhuo Wei, Jian Weng, Xin Li, Robert H. Deng Sep 2018

Resonance Attacks On Load Frequency Control Of Smart Grids, Yongdong Wu, Zhuo Wei, Jian Weng, Xin Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Load frequency control (LFC) is widely employed to regulate power plants in modern power generation systems of smart grids. This paper presents a simple and yet powerful type of attacks, referred to as resonance attacks, on LFC power generation systems. Specifically, in a resonance attack, an adversary craftily modifies the input of a power plant according to a resonance source (e.g., rate of change of frequency) to produce a feedback on LFC power generation system, such that the state of the power plant quickly becomes instable. Extensive computer simulations on popular LFC power generation system models which consist of linear, …

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Efficient Traceable Oblivious Transfer And Its Applications, Weiwei Liu, Yinghui Zhang, Yi Mu, Guomin Yang, Yangguang Tian Sep 2018

Efficient Traceable Oblivious Transfer And Its Applications, Weiwei Liu, Yinghui Zhang, Yi Mu, Guomin Yang, Yangguang Tian

Research Collection School Of Computing and Information Systems

Oblivious transfer (OT) has been applied widely in privacy-sensitive systems such as on-line transactions and electronic commerce to protect users’ private information. Traceability is an interesting feature of such systems that the privacy of the dishonest users could be traced by the service provider or a trusted third party (TTP). However, previous research on OT mainly focused on designing protocols with unconditional receiver’s privacy. Thus, traditional OT schemes cannot fulfill the traceability requirements in the aforementioned applications. In this paper, we address this problem by presenting a novel traceable oblivious transfer (TOT) without involvement of any TTP. In the new …

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Dsh: Deniable Secret Handshake Framework, Yangguang Tian, Yingjiu Li, Yinghui Zhang, Nan Li, Guomin Yang, Yong Yu Sep 2018

Dsh: Deniable Secret Handshake Framework, Yangguang Tian, Yingjiu Li, Yinghui Zhang, Nan Li, Guomin Yang, Yong Yu

Research Collection School Of Computing and Information Systems

Secret handshake is a useful primitive that allows a group of authorized users to establish a shared secret key and authenticate each other anonymously. It naturally provides a certain degree of user privacy and deniability which are also desirable for some private conversations that require secure key establishment. The inherent user privacy enables a private conversation between authorized users without revealing their real identities. While deniability allows authorized users to later deny their participating in conversations. However, deniability of secret handshakes lacks a comprehensive treatment in the literature. In this paper, we investigate the deniability of existing secret handshakes. We …

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Question-Guided Hybrid Convolution For Visual Question Answering, Peng Gao, Pan Lu, Hongsheng Li, Shuang Li, Yikang Li, Steven C. H. Hoi, Xiaogang Wang Sep 2018

Question-Guided Hybrid Convolution For Visual Question Answering, Peng Gao, Pan Lu, Hongsheng Li, Shuang Li, Yikang Li, Steven C. H. Hoi, Xiaogang Wang

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel Question-Guided Hybrid Convolution (QGHC) network for Visual Question Answering (VQA). Most state-of-the-art VQA methods fuse the high-level textual and visual features from the neural network and abandon the visual spatial information when learning multi-modal features.To address these problems, question-guided kernels generated from the input question are designed to convolute with visual features for capturing the textual and visual relationship in the early stage. The question-guided convolution can tightly couple the textual and visual information but also introduce more parameters when learning kernels. We apply the group convolution, which consists of question-independent kernels and …

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Focusvr: Effective And Usable Vr Display Power Management, Kiat Wee Tan, Eduardo Cuervo, Rajesh Krishna Balan Sep 2018

Focusvr: Effective And Usable Vr Display Power Management, Kiat Wee Tan, Eduardo Cuervo, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In this paper, we present the design and implementation of FocusVR, a system for effectively and efficiently reducing the power consumption of Virtual Reality (VR) devices by smartly dimming their displays. These devices are becoming increasingly common with large companies such as Facebook (Oculus Rift), and HTC and Valve (Vive), recently releasing high quality VR devices to the consumer market. However, these devices require increasingly higher screen resolutions and refresh rates to be effective, and this in turn, leads to high display power consumption costs. We show how the use of smart dimming techniques, vignettes and color mapping, can significantly …

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Blockchain Based Efficient And Robust Fair Payment For Outsourcing Services In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng Sep 2018

Blockchain Based Efficient And Robust Fair Payment For Outsourcing Services In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng

Research Collection School Of Computing and Information Systems

As an attractive business model of cloud computing, outsourcing services usually involve online payment and security issues. The mutual distrust between users and outsourcing service providers may severely impede the wide adoption of cloud computing. Nevertheless, most existing payment solutions only consider a specific type of outsourcing service and rely on a trusted third-party to realize fairness. In this paper, in order to realize secure and fair payment of outsourcing services in general without relying on any third-party, trusted or not, we introduce BCPay, a blockchain based fair payment framework for outsourcing services in cloud computing. We first present the …

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Jobcomposer: Career Path Optimization Via Multicriteria Utility Learning, Richard J. Oentaryo, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo Sep 2018

Jobcomposer: Career Path Optimization Via Multicriteria Utility Learning, Richard J. Oentaryo, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

With online professional network platforms (OPNs, e.g., LinkedIn, Xing, etc.)becoming popular on the web, people are now turning to these platforms tocreate and share their professional profiles, to connect with others who sharesimilar professional aspirations and to explore new career opportunities. Theseplatforms however do not offer a long-term roadmap to guide career progressionand improve workforce employability. The career trajectories of OPN users canserve as a reference but they are not always optimal. A career plan can also bedevised through consultation with career coaches, whose knowledge may howeverbe limited to a few industries. To address the above limitations, we present anovel …

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Are You On The Right Track? Learning Career Tracks For Job Movement Analysis, Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee, Yuan Tian, Chih-Chieh Hung Sep 2018

Are You On The Right Track? Learning Career Tracks For Job Movement Analysis, Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee, Yuan Tian, Chih-Chieh Hung

Research Collection School Of Computing and Information Systems

Career track represents a vertical career pathway, where one can gradually move up to take up higher job appointments when relevant skills are acquired. Understanding the propensity of career movements in an evolving job market can enable timely career guidance to job seekers and working professionals. To this end, we harvest career trajectories from online professional network (OPN). Our focus lies on obtaining a macro view on career movements at the track granularity. Specifically, we propose a semi-supervised career track labelling framework to automatically assign career tracks for large set of jobs. To contextually label jobs, we collect example jobs …

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Assessing Carbon Pollution Standards: Electric Power Generation Pathways And Their Water Impacts, Kustini Lim-Wavde, Haibo Zhai, Robert John Kauffman, Edward S. Rubin Sep 2018

Assessing Carbon Pollution Standards: Electric Power Generation Pathways And Their Water Impacts, Kustini Lim-Wavde, Haibo Zhai, Robert John Kauffman, Edward S. Rubin

Research Collection School Of Computing and Information Systems

Highlights•Without carbon regulations, CO2 emissions and water use are highly affected by fuel prices.•Carbon regulations reduce both CO2 emissions and water use.•Without incentives, carbon capture is not competitive with cheap natural gas and renewables.•A stringent constraint on water withdrawal lowers the fleet share of once-through cooling.AbstractThis study evaluates transition pathways in electricity generation and their future water impacts. Scenarios that do or do not comply with the carbon pollution standards – based on the U.S. New Source Performance Standards and Clean Power Plan – are evaluated. Using the Electric Reliability Council of Texas region as an illustration, the scenarios with …

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Neural-Machine-Translation-Based Commit Message Generation: How Far Are We?, Zhongxin Liu, Xin Xia, Ahmed E. Hassan, David Lo, Zhenchang Xing, Xinyu Wang Sep 2018

Neural-Machine-Translation-Based Commit Message Generation: How Far Are We?, Zhongxin Liu, Xin Xia, Ahmed E. Hassan, David Lo, Zhenchang Xing, Xinyu Wang

Research Collection School Of Computing and Information Systems

Commit messages can be regarded as the documentation of software changes. These messages describe the content and purposes of changes, hence are useful for program comprehension and software maintenance. However, due to the lack of time and direct motivation, commit messages sometimes are neglected by developers. To address this problem, Jiang et al. proposed an approach (we refer to it as NMT), which leverages a neural machine translation algorithm to automatically generate short commit messages from code. The reported performance of their approach is promising, however, they did not explore why their approach performs well. Thus, in this paper, we …

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Api Method Recommendation Without Worrying About The Task-Api Knowledge Gap, Qiao Huang, Xin Xia, Zhenchang Xing, David Lo, Xinyu Wang Sep 2018

Api Method Recommendation Without Worrying About The Task-Api Knowledge Gap, Qiao Huang, Xin Xia, Zhenchang Xing, David Lo, Xinyu Wang

Research Collection School Of Computing and Information Systems

Developers often need to search for appropriate APIs for theirprogramming tasks. Although most libraries have API referencedocumentation, it is not easy to find appropriate APIs due to thelexical gap and knowledge gap between the natural language description of the programming task and the API description in APIdocumentation. Here, the lexical gap refers to the fact that the samesemantic meaning can be expressed by different words, and theknowledge gap refers to the fact that API documentation mainlydescribes API functionality and structure but lacks other types ofinformation like concepts and purposes, which are usually the keyinformation in the task description. In this …

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