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Articles 4381 - 4410 of 8495
Full-Text Articles in Computer Sciences
Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu
Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu
Research Collection School Of Computing and Information Systems
Smart metering allows Substation Automation System (SAS) to remotely and timely read smart meters. Despite its advantages, smart metering brings some challenges. a) It introduces cyber attack risks to the metering system, which may lead to user privacy leakage or even the compromise of smart metering systems. b) Although the majority of meters are located within a regional power supply area, some hard-to-reach nodes are geographically far from the clustered area, which account for a big portion of the entire smart metering operation cost. Facing the above challenges, we propose a secure smart metering infrastructure based on LoRa technology which …
Securing Display Path For Security-Sensitive Applications On Mobile Devices, Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu, Yangyang Li
Securing Display Path For Security-Sensitive Applications On Mobile Devices, Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu, Yangyang Li
Research Collection School Of Computing and Information Systems
While smart devices based on ARM processor bring us a lot of convenience, they also become an attractive target of cyber-attacks. The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities. Nowadays, adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application. A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device. In this work, we present a scheme named SecDisplay for trusted display service, it …
Efficient And Privacy-Preserving Outsourced Calculation Of Rational Numbers, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng, Rongxing Lu, Jian Weng
Efficient And Privacy-Preserving Outsourced Calculation Of Rational Numbers, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng, Rongxing Lu, Jian Weng
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for efficient and privacy-preserving outsourced calculation of rational numbers, which we refer to as POCR. Using POCR, a user can securely outsource the storing and processing of rational numbers to a cloud server without compromising the security of the (original) data and the computed results. We present the system architecture of POCR and the associated toolkits required in the privacy preserving calculation of integers and rational numbers to ensure that commonly used outsourced operations can be handled on-the-fly. We then prove that the proposed POCR achieves the goal of secure integer and rational …
Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong
Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for hybrid privacy-preserving clinical decision support system in fog cloud computing, called HPCS. In HPCS, a fog server uses a lightweight data mining method to securely monitor patients' health condition in real-time. The newly detected abnormal symptoms can be further sent to the cloud server for high-accuracy prediction in a privacy-preserving way. Specifically, for the fog servers, we design a new secure outsourced inner-product protocol for achieving secure lightweight single-layer neural network. Also, a privacy-preserving piecewise polynomial calculation protocol allows cloud server to securely perform any activation functions in multiple-layer neural network. Moreover, …
Multi-Target Deep Neural Networks: Theoretical Analysis And Implementation, Zeng Zeng, Nanying Liang, Xulei Yang, Steven C. H. Hoi
Multi-Target Deep Neural Networks: Theoretical Analysis And Implementation, Zeng Zeng, Nanying Liang, Xulei Yang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In this work, we propose a novel deep neural network referred to as Multi-Target Deep Neural Network (MT-DNN). We theoretically prove that different stable target models with shared learning paths are stable and can achieve optimal solutions respectively. Based on GoogleNet, we design a single model with three different targets, one for classification, one for regression, and one for masks that is composed of 256 × 256 sub-models. Unlike bounding boxes used in ImageNet, our single model can draw the shapes of target objects, and in the meanwhile, classify the objects and calculate their sizes. We validate our single MT-DNN …
Smartwatch-Based Early Gesture Detection & Trajectory Tracking For Interactive Gesture-Driven Applications, Tran Huy Vu, Archan Misra, Quentin Roy, Kenny Tsu Wei Choo, Youngki Lee
Smartwatch-Based Early Gesture Detection & Trajectory Tracking For Interactive Gesture-Driven Applications, Tran Huy Vu, Archan Misra, Quentin Roy, Kenny Tsu Wei Choo, Youngki Lee
Research Collection School Of Computing and Information Systems
The paper explores the possibility of using wrist-worn devices (specifically, a smartwatch) to accurately track the hand movement and gestures for a new class of immersive, interactive gesture-driven applications. These interactive applications need two special features: (a) the ability to identify gestures from a continuous stream of sensor data early–i.e., even before the gesture is complete, and (b) the ability to precisely track the hand’s trajectory, even though the underlying inertial sensor data is noisy. We develop a new approach that tackles these requirements by first building a HMM-based gesture recognition framework that does not need an explicit segmentation step, …
Dictionary Learning With Structured Noise, Pan Zhou, Cong Fang, Zhouchen Lin, Chao Zhang, Y. Edward Chang
Dictionary Learning With Structured Noise, Pan Zhou, Cong Fang, Zhouchen Lin, Chao Zhang, Y. Edward Chang
Research Collection School Of Computing and Information Systems
Recently, lots of dictionary learning methods have been proposed and successfully applied. However, many of them assume that the noise in data is drawn from Gaussian or Laplacian distribution and therefore they typically adopt the 2 or 1 norm to characterize these two kinds of noise, respectively. Since this assumption is inconsistent with the real cases, the performance of these methods is limited. In this paper, we propose a novel dictionary learning with structured noise (DLSN) method for handling noisy data. We decompose the original data into three parts: clean data, structured noise, and Gaussian noise, and then characterize them …
Improved Construction For Inner Product Functional Encryption, Qingsong Zhao, Qingkai Zeng, Ximeng Liu
Improved Construction For Inner Product Functional Encryption, Qingsong Zhao, Qingkai Zeng, Ximeng Liu
Research Collection School Of Computing and Information Systems
Functional encryption (FE) is a vast new paradigm for encryption scheme which allows tremendous flexibility in accessing encrypted data. In a FE scheme, a user can learn specific function of encrypted messages by restricted functional key and reveals nothing else about the messages. Besides the standard notion of data privacy in FE, it should protect the privacy of the function itself which is also crucial for practical applications. In this paper, we construct a secret key FE scheme for the inner product functionality using asymmetric bilinear pairing groups of prime order. Compared with the existing similar schemes, our construction reduces …
Simulation-Based Security Of Function-Hiding Inner Product Encryption, Qingsong Zhao, Qingkai Zeng, Ximeng Liu, Huanliang Xu
Simulation-Based Security Of Function-Hiding Inner Product Encryption, Qingsong Zhao, Qingkai Zeng, Ximeng Liu, Huanliang Xu
Research Collection School Of Computing and Information Systems
Functional encryption (FE) [1,2] is a modern type of encryption scheme that extends several previous notions and allows tremendous flexibility in controlling and computing on encrypted data. FE enables an authority to derive constrained decryption keys that are used by a user to obtain specific functions of encrypted messages. Informally, the authority generates a secret key skf for a function f from a master secret key. Then, the user can only learn f(x) from a ciphertext Enc(x) with skf and reveal nothing else about x.
Modeling Engagement Of Programming Students Using Unsupervised Machine Learning Technique, Hua Leong Fwa, Lindsay Marshall
Modeling Engagement Of Programming Students Using Unsupervised Machine Learning Technique, Hua Leong Fwa, Lindsay Marshall
Research Collection School Of Computing and Information Systems
Engagement is instrumental to students’ learning and academic achievements. In this study, we model the engagement states of students who are working on programming exercises in an intelligent tutoring system. Head pose, keystrokes and action logs of students automatically captured within the tutoring system are fed into a Hidden Markov Model for inferring the engagement states of students. With the modeling of students’ engagement on a moment by moment basis, intervention measures can be initiated automatically by the system when necessary to optimize the students’ learning. This study is also one of the few studies that bypass the need for …
Strong Identity-Based Proxy Signature Schemes, Revisited, Weiwei Liu, Yi Mu, Guomin Yang, Yangguang Tian
Strong Identity-Based Proxy Signature Schemes, Revisited, Weiwei Liu, Yi Mu, Guomin Yang, Yangguang Tian
Research Collection School Of Computing and Information Systems
Proxy signature is a useful cryptographic primitive that has been widely used in many applications. It has attracted a lot of attention since it was introduced. There have been lots of works in constructing efficient and secure proxy signature schemes. In this paper, we identify a new attack that has been neglected by many existing proven secure proxy signature schemes. We demonstrate this attack by launching it against an identity-based proxy signature scheme which is proven secure. We then propose one method that can effectively prevent this attack. The weakness in some other proxy signature schemes can also be fixed …
Anatomy Of Online Hate: Developing A Taxonomy And Machine Learning Models For Identifying And Classifying Hate In Online News Media, Joni Salminen, Hind Almerekhi, Milica Milenkovic, Soon-Gyu Jung, Haewoon Kwak, Haewoon Kwak, Bernard J. Jansen
Anatomy Of Online Hate: Developing A Taxonomy And Machine Learning Models For Identifying And Classifying Hate In Online News Media, Joni Salminen, Hind Almerekhi, Milica Milenkovic, Soon-Gyu Jung, Haewoon Kwak, Haewoon Kwak, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
Online social media platforms generally attempt to mitigate hateful expressions, as these comments can be detrimental to the health of the community. However, automatically identifying hateful comments can be challenging. We manually label 5,143 hateful expressions posted to YouTube and Facebook videos among a dataset of 137,098 comments from an online news media. We then create a granular taxonomy of different types and targets of online hate and train machine learning models to automatically detect and classify the hateful comments in the full dataset. Our contribution is twofold: 1) creating a granular taxonomy for hateful online comments that includes both …
Skylens: Visual Analysis Of Skyline On Multi-Dimensional Data, Xun Zhao, Yanhong Wu, Weiwei Cui, Xinnan Du, Yuan Chen, Yong Wang, Dik Lun Lee, Huamin Qu
Skylens: Visual Analysis Of Skyline On Multi-Dimensional Data, Xun Zhao, Yanhong Wu, Weiwei Cui, Xinnan Du, Yuan Chen, Yong Wang, Dik Lun Lee, Huamin Qu
Research Collection School Of Computing and Information Systems
Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e.. the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points …
Pagesense: Toward Stylewise Contextual Advertising Via Visual Analysis Of Web Pages, Tao Mei, Lusong Li, Xinmei Tian, Dacheng Tao, Chong-Wah Ngo
Pagesense: Toward Stylewise Contextual Advertising Via Visual Analysis Of Web Pages, Tao Mei, Lusong Li, Xinmei Tian, Dacheng Tao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The Internet has emerged as the most effective and a highly popular medium for advertising. Current contextual advertising platforms need publishers to manually change the original structure of their Web pages and predefine the position and style of embedded ads. Although publishers spend significant effort optimizing their Web page layout, a large number of Web pages contain noticeable blank regions. We present an innovative stylewise advertising platform for contextual advertising, called PageSense. The "style" of Web pages refers to the visual appearance of a Web page, such as color and layout. PageSense aims to associate style-consistent ads with Web pages. …
Collaborative Fall Detection Using Smartphone And Kinect, Xue Li, Lanshun Nie, Hanchuan Xu, Xianzhi Wang
Collaborative Fall Detection Using Smartphone And Kinect, Xue Li, Lanshun Nie, Hanchuan Xu, Xianzhi Wang
Research Collection School Of Computing and Information Systems
Humanfall detection has attracted broad attentions as sensors and mobile devices are increasingly adopted in real-life scenarios such as smart homes. The complexity of activities in home environments pose severe challenges to the fall detection research with respect to the detection accuracy. We propose a collaborative detection platform that combines two subsystems: a threshold-based fall detection subsystem using mobile phones and a support vector machine (SVM)-based fall detection subsystem using Kinects. Both subsystems have their respective confidence models and the platform detects falls by fusing the data of both subsystems using two methods: the logical rules-based and D-S evidence fusion …
User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yingjiu Li, Zhan. Wang
User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yingjiu Li, Zhan. Wang
Research Collection School Of Computing and Information Systems
Mobile devices are prevalently used to process sensitive data, but traditional encryption may not work when an adversary is able to coerce the device owners to disclose the encryption keys. Plausibly Deniable Encryption (PDE) is thus designed to protect sensitive data against this powerful adversary. In this paper, we present MobiPluto, a user-friendly PDE scheme for denying the existence of sensitive data stored on mobile devices. A salient difference between MobiPluto and the existing PDE systems is that any block-based file systems can be deployed on top of it. To further improve usability and deniability of MobiPluto, we introduce a …
Smart Monitoring Via Participatory Ble Relaying, Meeralakshmi Radhakrishnan, Sougata Sen, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Smart Monitoring Via Participatory Ble Relaying, Meeralakshmi Radhakrishnan, Sougata Sen, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
We espouse the vision of a smart object/campus architecture where sensors attached to smart objects use BLE as communication interface, and where smartphones act as opportunistic relays to transfer the data. We explore the feasibility of the vision with real-world Wi-Fi based location traces from our university campus. Our feasibility studies establish that redundancy exists in user movement within the indoor spaces, and that this redundancy can be exploited for collecting sensor data in an opportunistic, yet fair manner. We develop a couple of alternative heuristics that address the BLE energy asymmetry challenge by intelligently duty-cycling the scanning actions of …
Identifying And Computing The Exact Core-Determining Class, Ye Luo, Hai Wang
Identifying And Computing The Exact Core-Determining Class, Ye Luo, Hai Wang
Research Collection School Of Computing and Information Systems
The indeterministic relations between unobservable events andobserved outcomes in partially identified models can be characterized bya bipartite graph. Given a probability measure on observed outcomes, theset of feasible probability measures on unobservable events can be definedby a set of linear inequality constraints, according to Artstein’s Theorem.This set of inequalities is called the “core-determining class”. However, thenumber of inequalities defined by Artstein’s Theorem is exponentially increasing with the number of unobservable events, and many inequalitiesmay in fact be redundant. In this paper, we show that the “exact coredetermining class”, i.e., the smallest possible core-determining class, canbe characterized by a set of …
Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou
Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou
Research Collection School Of Computing and Information Systems
Crowdsourcing has been shown to be effective in a wide range of applications, and is seeing increasing use. A large-scale crowdsourcing task often consists of thousands or millions of atomic tasks, each of which is usually a simple task such as binary choice or simple voting. To distribute a large-scale crowdsourcing task to limited crowd workers, a common practice is to pack a set of atomic tasks into a task bin and send to a crowd worker in a batch. It is challenging to decompose a large-scale crowdsourcing task and execute batches of atomic tasks, which ensures reliable answers at …
Code: Coherence Based Decision Boundaries For Feature Correspondence, Wen-Yan Lin, Fan Wang, Ming-Ming Cheng, Sai-Kit Yeung, Philip H. S. Torr, Jiangbo Lu
Code: Coherence Based Decision Boundaries For Feature Correspondence, Wen-Yan Lin, Fan Wang, Ming-Ming Cheng, Sai-Kit Yeung, Philip H. S. Torr, Jiangbo Lu
Research Collection School Of Computing and Information Systems
A key challenge in feature correspondence is the difficulty in differentiating true and false matches at a local descriptor level. This forces adoption of strict similarity thresholds that discard many true matches. However, if analyzed at a global level, false matches are usually randomly scattered while true matches tend to be coherent (clustered around a few dominant motions), thus creating a coherence based separability constraint. This paper proposes a non-linear regression technique that can discover such a coherence based separability constraint from highly noisy matches and embed it into a correspondence likelihood model. Once computed, the model can filter the …
Online/Offline Traceable Attribute-Based Encryption [In Chinese], Kai Zhang, Jianfeng Ma, Junwei Zhang, Zuobin Ying, Tao Zhang, Ximeng Liu
Online/Offline Traceable Attribute-Based Encryption [In Chinese], Kai Zhang, Jianfeng Ma, Junwei Zhang, Zuobin Ying, Tao Zhang, Ximeng Liu
Research Collection School Of Computing and Information Systems
Attribute-based encryption (ABE), as a public key encryption, can be utilized for fine-grained access control. However, there are two main drawbacks that limit the applications of attribute-based encryption. First, as different users may have the same decryption privileges in ciphertext-policy attribute-based encryption, it is difficult to catch the users who sell their secret keys for financial benefit. Second, the number of resource-consuming exponentiation operations required to encrypt a message in ciphertext-policy attribute-based encryption grows with the complexity of the access policy, which presents a significant challenge for the users who encrypt data on mobile devices. Towards this end, after proposing …
Collaboration Patterns In Software Developer Network, Didi Surian, Ee-Peng Lim, David Lo
Collaboration Patterns In Software Developer Network, Didi Surian, Ee-Peng Lim, David Lo
Research Collection School Of Computing and Information Systems
In this entry, we mine collaboration patterns from a large software developer network (Surian et al. 2010). We consider high- and low-level patterns. High-level patterns correspond to various network-level statistics that we observe to hold in this network. Low-level patterns are topological subgraph patterns that are frequently observed among developers collaborating in the network. Mining topological subgraph patterns are difficult as it is an NP-hard problem. To address this issue, we use a combination of frequent subgraph mining and graph matching by leveraging the power law property exhibited by a large collaboration graph. The technique is applicable to any software …
A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui
A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui
Research Collection School Of Computing and Information Systems
Electronic Health Record (EHR) is a digital health documentary. It contains not only the health-related records but also the personal sensitive information. Therefore, how to reliably share EHR through the cloud is a challenging issue. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography prototype, which can achieve fine-grained access control as well as one-to-many encryption. In CP-ABE, access policy is attached to the ciphertext, and however, the access policy is not protected, which will also cause some privacy leakage. In this paper, we propose a policy preserving EHR system on the basis of CP-ABE. Specifically, we designed an algorithm, which …
Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu
Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu
Research Collection School Of Computing and Information Systems
Privacy-preserving outsourcing algorithms for feature extraction not only reduce users' storage and computation overhead but also preserve the image privacy. However, the existing schemes still suffer from deficiencies induced by security, applications, efficiency and storage. To solve the problems, we implement a consortium chain-based outsourcing feature extraction scheme over encrypted images by using the smart contract, distributed autonomous corporation (DAC), sharding technique, and device to device (D2D) communication, which is secure, widely applied, highly efficient, and has less storage overhead. First, the effectiveness, security, and performance of our scheme are analyzed. Then, the efficiency and storage overhead of our scheme …
User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yanju Liu, Zhan Wang
User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yanju Liu, Zhan Wang
Research Collection School Of Computing and Information Systems
Mobile devices are prevalently used to process sensitive data, but traditional encryption may not work when an adversary is able to coerce the device owners to disclose the encryption keys. Plausibly Deniable Encryption (PDE) is thus designed to protect sensitive data against this powerful adversary. In this paper, we present MobiPluto, a user-friendly PDE scheme for denying the existence of sensitive data stored on mobile devices. A salient difference between MobiPluto and the existing PDE systems is that any block-based file systems can be deployed on top of it. To further improve usability and deniability of MobiPluto, we introduce a …
Pricing For A Last-Mile Transportation System, Yiwei Chen, Hai Wang
Pricing For A Last-Mile Transportation System, Yiwei Chen, Hai Wang
Research Collection School Of Computing and Information Systems
The Last-Mile Problem refers to the provision of travel service from the nearest public transportation node to a home or other destination. Last-Mile Transportation System (LMTS), which has recently emerged, provide on-demand shared transportation. We consider an LMTS with multiple passenger types—adults, senior citizens, children, and students. The LMTS designer determines the price for the passengers, last-mile service vehicle capacity, and service fleet size (number of vehicles) for each last-mile region to maximize the social welfare generated by the LMTS. The level of last-mile service (in terms of passenger waiting time) is approximated by using a batch arrival, batch service, …
Discriminant Analysis On Riemannian Manifold Of Gaussian Distributions For Face Recognition With Image Sets, W. Wang, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Discriminant Analysis On Riemannian Manifold Of Gaussian Distributions For Face Recognition With Image Sets, W. Wang, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Research Collection School Of Computing and Information Systems
To address the problem of face recognition with image sets, we aim to capture the underlying data distribution in each set and thus facilitate more robust classification. To this end, we represent image set as the Gaussian mixture model (GMM) comprising a number of Gaussian components with prior probabilities and seek to discriminate Gaussian components from different classes. Since in the light of information geometry, the Gaussians lie on a specific Riemannian manifold, this paper presents a method named discriminant analysis on Riemannian manifold of Gaussian distributions (DARG). We investigate several distance metrics between Gaussians and accordingly two discriminative learning …
Compact Hierarchical Ibe From Lattices In The Standard Model, Daode Zhang, Fuyang Fang, Bao Li, Haiyang Xue, Bei Liang
Compact Hierarchical Ibe From Lattices In The Standard Model, Daode Zhang, Fuyang Fang, Bao Li, Haiyang Xue, Bei Liang
Research Collection School Of Computing and Information Systems
At Crypto’10, Agrawal et al. proposed a lattice-based selectively secure Hierarchical Identity-based Encryption (HIBE) scheme (ABB10b) with small ciphertext on the condition that (the length of identity at each level) is small in the standard model. In this paper, we present another lattice-based selectively secure HIBE scheme with depth d, using a gadget matrix with enough large to replace the matrix in the HIBE scheme proposed by Agrawal et al. at Eurocrypt’10. In our HIBE scheme, not only the size of ciphertext at level is larger than the size in ABB10b and at least smaller than the sizes in the …
Extracting Implicit Suggestions From Students’ Comments: A Text Analytics Approach, Venky Shankararaman, Swapna Gottipati, Jeff Rongsheng Lin, Sandy Gan
Extracting Implicit Suggestions From Students’ Comments: A Text Analytics Approach, Venky Shankararaman, Swapna Gottipati, Jeff Rongsheng Lin, Sandy Gan
Research Collection School Of Computing and Information Systems
At the end of each course, students are required to give feedback on the course and instructor. This feedback includes quantitative rating using Likert scale and qualitative feedback as comments. Such qualitative feedback can provide valuable insights in helping the instructor enhance the course content and teaching delivery. However, the main challenge in analysing the qualitative feedback is the perceived increase in time and effort needed to manually process the textual comments. In this paper, we provide an automated solution for analysing comments, specifically extracting implicit suggestions from the students’ qualitative feedback comments. The implemented solution leverages existing text mining …
Btci: A New Framework For Identifying Congestion Cascades Using Bus Trajectory Data, Meng-Fen Chiang, Ee Peng Lim, Wang-Chien Lee, Agus Trisnajaya Kwee
Btci: A New Framework For Identifying Congestion Cascades Using Bus Trajectory Data, Meng-Fen Chiang, Ee Peng Lim, Wang-Chien Lee, Agus Trisnajaya Kwee
Research Collection School Of Computing and Information Systems
The knowledge of traffic health status is essential to the general public and urban traffic management. To identify congestion cascades, an important phenomenon of traffic health, we propose a Bus Trajectory based Congestion Identification (BTCI) framework that explores the anomalous traffic health status and structure properties of congestion cascades using bus trajectory data. BTCI consists of two main steps, congested segment extraction and congestion cascades identification. The former constructs path speed models from historical vehicle transitions and design a non-parametric Kernel Density Estimation (KDE) function to derive a measure of congestion score. The latter aggregates congested segments (i.e., those with …