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Articles 2941 - 2970 of 4266
Full-Text Articles in Entire DC Network
Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan
Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
While community detection is an active area of research in social network analysis, little effort has been devoted to community detection using time-evolving social network data. We propose an algorithm, Persistent Community Detection (PCD), to identify those communities that exhibit persistent behavior over time, for usage in such settings. Our motivation is to distinguish between steady-state network activity, and impermanent behavior such as cascades caused by a noteworthy event. The results of extensive empirical experiments on real-life big social networks data show that our algorithm performs much better than a set of baseline methods, including two alternative models and the …
Technique For Authenticating H.264/Svc And Its Performance Evaluation Over Wireless Mobile Networks, Yifan Zhao, Swee Won Lo, Robert H. Deng, Xuhua Ding
Technique For Authenticating H.264/Svc And Its Performance Evaluation Over Wireless Mobile Networks, Yifan Zhao, Swee Won Lo, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, a bit stream-based authentication scheme for H.264/Scalable Video Coding (SVC) is proposed. The proposed scheme seamlessly integrates cryptographic algorithms and Erasure Correction Codes (ECCs) to SVC video streams such that the authenti- cated streams are format compliant with the SVC specifications and preserve the three- dimensional scalability (i.e., spatial, quality and temporal) of the original streams. We implement our scheme on a smart phone and study its performance over a realistic bursty packet-lossy wireless mobile network. Our analysis and experimental results show that the scheme achieves very high verification rates with lower communication overhead and much smaller …
Exploring Video Streaming In Public Settings: Shared Geocaching Over Distance Using Mobile Video Chat, Jason Procyk, Carman Neustaedter, Carolyn Pang, Anthony Tang, Tejinder K. Judge
Exploring Video Streaming In Public Settings: Shared Geocaching Over Distance Using Mobile Video Chat, Jason Procyk, Carman Neustaedter, Carolyn Pang, Anthony Tang, Tejinder K. Judge
Research Collection School Of Computing and Information Systems
Our research explores the use of mobile video chat in public spaces by people participating in parallel experiences, where both a local and remote person are doing the same activity together at the same time. We prototyped a wearable video chat experience and had pairs of friends and family members participate in 'shared geocaching' over distance. Our results show that video streaming works best for navigation tasks but is more challenging to use for fine-grained searching tasks. Video streaming also creates a very intimate experience with a remote partner, but this can lead to distraction from the 'real world' and …
Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni
Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni
Research Collection School Of Computing and Information Systems
Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …
Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu
Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu
Research Collection School Of Computing and Information Systems
Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. …
Identity-Based Encryption Secure Against Selective Opening Chosen-Ciphertext Attack, Junzuo Lai, Robert H. Deng, Shengli Liu, Jian Weng, Yunlei Zhao
Identity-Based Encryption Secure Against Selective Opening Chosen-Ciphertext Attack, Junzuo Lai, Robert H. Deng, Shengli Liu, Jian Weng, Yunlei Zhao
Research Collection School Of Computing and Information Systems
Security against selective opening attack (SOA) requires that in a multi-user setting, even if an adversary has access to all ciphertexts from users, and adaptively corrupts some fraction of the users by exposing not only their messages but also the random coins, the remaining unopened messages retain their privacy. Recently, Bellare, Waters and Yilek considered SOA-security in the identity-based setting, and presented the first identity-based encryption (IBE) schemes that are proven secure against selective opening chosen plaintext attack (SO-CPA). However, how to achieve SO-CCA security for IBE is still open. In this paper, we introduce a new primitive called extractable …
Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang
Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang
Research Collection School Of Computing and Information Systems
Due to the fast development of social media on the Web, Twitter has become one of the major platforms for people to express themselves. Because of the wide adoption of Twitter, events like breaking news and release of popular videos can easily catch people’s attention and spread rapidly on Twitter, and the number of relevant tweets approximately reflects the impact of an event. Event identification and analysis on Twitter has thus become an important task. Recently the Recurrent Chinese Restaurant Process (RCRP) has been successfully used for event identification from news streams and news-centric social media streams. However, these models …
Predictive Analytics For Outpatient Appointments, Nang Laik Ma, Khataniar Seemanta, Dan Wu, Serene Seng Ying Ng
Predictive Analytics For Outpatient Appointments, Nang Laik Ma, Khataniar Seemanta, Dan Wu, Serene Seng Ying Ng
Research Collection School Of Computing and Information Systems
Healthcare is a very important industry where analytics has been applied successfully to generate insights about patients, identify bottleneck and to improve the business efficiency. In this paper, we aim to look at the patient appointment process as the hospital is experiencing high volume of ?no shows. ?No shows have a high impact on longer appointment lead time for patients, poor patient satisfaction and loss of revenue for hospital. We use data analytics to identify pattern of ?no shows, develop a statistical model to predict the probability of ?no shows and finally operationalizing the model to embed the analytics solution …
Teaching Analysis Of Software Designs Using Dependency Graph, Kevin Steppe
Teaching Analysis Of Software Designs Using Dependency Graph, Kevin Steppe
Research Collection School Of Computing and Information Systems
We present the use of a new type of dependency graph to aid students in analyzing the modifiability of software designs. Though a variety of software design concepts, such as information hiding, separation of concerns and patterns are taught to undergraduate students, they often have difficulty applying these concepts to the analysis of designs and particularly to comparing designs, perhaps due to the subjective nature of these concepts. Our new technique complements design structure matrix and ‘uses’ techniques to handle asymmetric dependency impacts and provide a deterministic approach to comparing alternative designs. A major goal of this technique was for …
Machine Learning In Wireless Sensor Networks: Algorithms, Strategies, And Applications, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
Machine Learning In Wireless Sensor Networks: Algorithms, Strategies, And Applications, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are …
On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim
On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …
Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak
Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak
Research Collection School Of Computing and Information Systems
One problem facing players of competitive games is negative, or toxic, behavior. League of Legends, the largest eSport game, uses a crowdsourcing platform called the Tribunal to judge whether a reported toxic player should be punished or not. The Tribunal is a two stage system requiring reports from those players that directly observe toxic behavior, and human experts that review aggregated reports. While this system has successfully dealt with the vague nature of toxic behavior by majority rules based on many votes, it naturally requires tremendous cost, time, and human efforts. In this paper, we propose a supervised learning approach …
Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft
Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet who are passionate about supporting others' projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for …
Are Timed Automata Bad For A Specification Language? Language Inclusion Checking For Timed Automata, Ting Wang, Jun Sun, Yang Liu, Xinyu Wang, Shanping Li
Are Timed Automata Bad For A Specification Language? Language Inclusion Checking For Timed Automata, Ting Wang, Jun Sun, Yang Liu, Xinyu Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Given a timed automaton P modeling an implementation and a timed automaton S as a specification, language inclusion checking is to decide whether the language of P is a subset of that of S. It is known that this problem is undecidable and “this result is an obstacle in using timed automata as a specification language” [2]. This undecidability result, however, does not imply that all timed automata are bad for specification. In this work, we propose a zone-based semi-algorithm for language inclusion checking, which implements simulation reduction based on Anti-Chain and LU-simulation. Though it is not guaranteed to terminate, …
Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh
Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh
Research Collection School Of Computing and Information Systems
Indoor maps, as crucial prerequisites for many indoor localization and navigation systems, are sometimes inaccessible. The absence of an indoor map database and the high cost of manually constructing an indoor map produce a need for an inexpensive and efficient way to dynamically construct indoor maps. The ubiquity of sensor-equipped mobile devices enables us to crowdsource user trajectories, out of which indoor digital maps can be automatically constructed at low costs. Similar to other crowdsourced data, the collected user trajectories are often noisy and of low fidelity, which poses a challenge to the accurate map construction. To alleviate this problem, …
Robust Tracking With Discriminative Ranking Middle-Level Patches, Hong Liu, Zilin Liang, Qianru Sun
Robust Tracking With Discriminative Ranking Middle-Level Patches, Hong Liu, Zilin Liang, Qianru Sun
Research Collection School Of Computing and Information Systems
The appearance model has been shown to be essential for robust visual tracking since it is the basic criterion to locating targets in video sequences. Though existing tracking-by-detection algorithms have shown to be greatly promising, they still suffer from the drift problem, which is caused by updating appearance models. In this paper, we propose a new appearance model composed of ranking middle-level patches to capture more object distinctiveness than traditional tracking-by-detection models. Targets and backgrounds are represented by both low-level bottom-up features and high-level top-down patches, which can compensate each other. Bottom-up features are defined at the pixel level, and …
A Hybrid Scheme For Authenticating Scalable Video Codestreams, Zhuo Wei, Yongdong Wu, Robert H. Deng, Xuhua Ding
A Hybrid Scheme For Authenticating Scalable Video Codestreams, Zhuo Wei, Yongdong Wu, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
A scalable video coding (SVC) codestream consists of one base layer and possibly several enhancement layers. The base layer, which contains the lowest quality and resolution images, is the foundation of the SVC codestream and must be delivered to recipients, whereas enhancement layers contain richer contour/texture of images in order to supplement the base layer in resolution, quality, and temporal scalabilities. This paper presents a novel hybrid authentication (HAU) scheme. The HAU employs both cryptographic authentication and content-based authentication techniques to ensure integrity and authenticity of the SVC codestreams. Our analysis and experimental results indicate that the HAU is able …
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
Research Collection School Of Computing and Information Systems
Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …
Clonepedia: Summarizing Code Clones By Common Syntactic Context For Software Maintenance, Yun Lin, Zhenchang Xing, Xin Peng, Yang Liu, Jun Sun, Wenyun Zhao, Jin Song Dong
Clonepedia: Summarizing Code Clones By Common Syntactic Context For Software Maintenance, Yun Lin, Zhenchang Xing, Xin Peng, Yang Liu, Jun Sun, Wenyun Zhao, Jin Song Dong
Research Collection School Of Computing and Information Systems
Code clones have to be made explicit and be managed in software maintenance. Researchers have developed many clone detection tools to detect and analyze code clones in software systems. These tools report code clones as similar code fragments in source files. However, clone-related maintenance tasks (e.g., refactorings) often involve a group of code clones appearing in larger syntactic context (e.g., code clones in sibling classes or code clones calling similar methods). Given a list of low-level code-fragment clones, developers have to manually summarize from bottom up low-level code clones that are relevant to the syntactic context of a maintenance task. …
Keystroke Biometrics: The User Perspective, Chee Meng Tey, Payas Gupta, Kartik Muralidaran, Debin Gao
Keystroke Biometrics: The User Perspective, Chee Meng Tey, Payas Gupta, Kartik Muralidaran, Debin Gao
Research Collection School Of Computing and Information Systems
Usability is an important aspect of security, because poor usability motivates users to find shortcuts that bypass the system. Existing studies on keystroke biometrics evaluate the usability issue in terms of the average false rejection rate (FRR). We show in this paper that such an approach underestimates the user impact in two ways. First, the FRR of keystroke biometrics changes for the worse under a range of common conditions such as background music, exercise and even game playing. In a user study involving 111 participants, the average penalties (increases) in FRR are 0.0360 and 0.0498, respectively, for two different classifiers. …
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo
Research Collection School Of Computing and Information Systems
Auto face annotation, which aims to detect human faces from a facial image and assign them proper human names, is a fundamental research problem and beneficial to many real-world applications. In this work, we address this problem by investigating a retrieval-based annotation scheme of mining massive web facial images that are freely available over the Internet. In particular, given a facial image, we first retrieve the top n similar instances from a large-scale web facial image database using content-based image retrieval techniques, and then use their labels for auto annotation. Such a scheme has two major challenges: 1) how to …
A Comparative Study On The Effectiveness Of Part-Of-Speech Tagging Techniques On Bug Reports, Yuan Tian, David Lo
A Comparative Study On The Effectiveness Of Part-Of-Speech Tagging Techniques On Bug Reports, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Many software artifacts are written in natural language or contain substantial amount of natural language contents. Thus these artifacts could be analyzed using text analysis techniques from the natural language processing (NLP) community, e.g., the part-of-speech (POS) tagging technique that assigns POS tags (e.g., verb, noun, etc.) to words in a sentence. In the literature, several studies have already applied POS tagging technique on software artifacts to recover important words in them, which are then used for automating various tasks, e.g., locating buggy files for a given bug report, etc. There are many POS tagging techniques proposed and they are …
Key-Aggregate Cryptosystem For Scalable Data Sharing In Cloud Storage, Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jiangying Zhou, Robert H. Deng
Key-Aggregate Cryptosystem For Scalable Data Sharing In Cloud Storage, Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jiangying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
Data sharing is an important functionality in cloud storage. In this article, we show how to securely, efficiently, and flexibly share data with others in cloud storage. We describe new public-key cryptosystems which produce constant-size ciphertexts such that efficient delegation of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate any set of secret keys and make them as compact as a single key, but encompassing the power of all the keys being aggregated. In other words, the secret key holder can release a constant-size aggregate key for flexible choices of ciphertext set …
Towards More Accurate Multi-Label Software Behavior Learning, Xin Xia, Feng Yang, David Lo, Zhenyu Chen, Xinyu Wang
Towards More Accurate Multi-Label Software Behavior Learning, Xin Xia, Feng Yang, David Lo, Zhenyu Chen, Xinyu Wang
Research Collection School Of Computing and Information Systems
In a modern software system, when a program fails, a crash report which contains an execution trace would be sent to the software vendor for diagnosis. A crash report which corresponds to a failure could be caused by multiple types of faults simultaneously. Many large companies such as Baidu organize a team to analyze these failures, and classify them into multiple labels (i.e., multiple types of faults). However, it would be time-consuming and difficult for developers to manually analyze these failures and come out with appropriate fault labels. In this paper, we automatically classify a failure into multiple types of …
Sinabro: Opportunistic And Unobtrusive Mobile Ecg Monitoring System, Seungwoo Kang, Sungjun Kwon, Sangwon Seo, Chungkuk Yoo, Kwangsuk Park, Junehwa Song, Youngki Lee
Sinabro: Opportunistic And Unobtrusive Mobile Ecg Monitoring System, Seungwoo Kang, Sungjun Kwon, Sangwon Seo, Chungkuk Yoo, Kwangsuk Park, Junehwa Song, Youngki Lee
Research Collection School Of Computing and Information Systems
In this paper, we propose Sinabro, an opportunistic and unobtrusive mobile electrocardiogram (ECG) monitoring system that monitors the user’s ECG opportunistically during daily smartphone use. Daily ECG monitoring will open up an unprecedented opportunity for pervasive healthcare applications. It will enable the daily detection and prevention of heart problems and also allow inferences about stress, emotion, and even sleep quality. Despite its huge potential, daily ECG monitoring still has not become reality due to its obtrusiveness. In this paper, we first study the potential opportunity to capture ECGs from daily use of smartphones, without requiring the user’s explicit attention. Based …
Ropecker: A Generic And Practical Approach For Defending Against Rop Attack, Yueqiang Cheng, Zongwei Zhou, Yu Miao, Xuhua Ding, Robert H. Deng
Ropecker: A Generic And Practical Approach For Defending Against Rop Attack, Yueqiang Cheng, Zongwei Zhou, Yu Miao, Xuhua Ding, Robert H. Deng
Research Collection School Of Computing and Information Systems
Return-Oriented Programming (ROP) is a sophisticated exploitation technique that is able to drive target applications to perform arbitrary unintended operations by constructing a gadget chain reusing existing small code sequences (gadgets). Existing defense mechanisms either only handle specific types of gadgets, require access to source code and/or a customized compiler, break the integrity of application binary, or suffer from high performance overhead. In this paper, we present a novel system, ROPecker, to efficiently and effectively defend against ROP attacks without relying on any other side information (e.g., source code and compiler support) or binary rewriting. ROPecker detects an ROP attack …
Visual Typo Correction By Collocative Optimization: A Case Study On Merchandize Images, Xiao-Yong Wei, Zhen-Qun Yang, Chong-Wah Ngo, Wei Zhang
Visual Typo Correction By Collocative Optimization: A Case Study On Merchandize Images, Xiao-Yong Wei, Zhen-Qun Yang, Chong-Wah Ngo, Wei Zhang
Research Collection School Of Computing and Information Systems
Near-duplicate retrieval (NDR) in merchandize images is of great importance to a lot of online applications on e-Commerce websites. In those applications where the requirement of response time is critical, however, the conventional techniques developed for a general purpose NDR are limited, because expensive post-processing like spatial verification or hashing is usually employed to compromise the quantization errors among the visual words used for the images. In this paper, we argue that most of the errors are introduced because of the quantization process where the visual words are considered individually, which has ignored the contextual relations among words. We propose …
Identity Based Identification From Algebraic Coding Theory, Guomin Yang, Chik How Tan, Yi Mu, Willy Susilo, Duncan S. Wong
Identity Based Identification From Algebraic Coding Theory, Guomin Yang, Chik How Tan, Yi Mu, Willy Susilo, Duncan S. Wong
Research Collection School Of Computing and Information Systems
Cryptographic identification schemes allow a remote user to prove his/her identity to a verifier who holds some public information of the user, such as the user public key or identity. Most of the existing cryptographic identification schemes are based on numbertheoretic hard problems such as Discrete Log and Factorization. This paper focuses on the design and analysis of identity based identification (IBI) schemes based on algebraic coding theory. We first revisit an existing code-based IBI scheme which is derived by combining the Courtois–Finiasz–Sendrier signature scheme and the Stern zero-knowledge identification scheme. Previous results have shown that this IBI scheme is …
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …
Representative Discovery Of Structure Cues For Weakly-Supervised Image Segmentation, Luming Zhang, Yue Gao, Yingjie Xia, Ke Lu, Jialie Shen, Rongrong Ji
Representative Discovery Of Structure Cues For Weakly-Supervised Image Segmentation, Luming Zhang, Yue Gao, Yingjie Xia, Ke Lu, Jialie Shen, Rongrong Ji
Research Collection School Of Computing and Information Systems
Weakly-supervised image segmentation is a challenging problem with multidisciplinary applications in multimedia content analysis and beyond. It aims to segment an image by leveraging its imagelevel semantics (i.e., tags). This paper presents a weakly-supervised image segmentation algorithm that learns the distribution of spatially structural superpixel sets from image-level labels. More specifically, we first extract graphlets from a given image, which are small-sized graphs consisting of superpixels and encapsulating their spatial structure. Then, an ecient manifold embedding algorithm is proposed to transfer labels from training images into graphlets. It is further observed that there are numerous redundant graphlets that are not …