Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Research Collection School Of Computing and Information Systems

2018

Articles 361 - 390 of 395

Full-Text Articles in Physical Sciences and Mathematics

Sparse Passive-Aggressive Learning For Bounded Online Kernel Methods, Jing Lu, Doyen Sahoo, Peilin Zhao, Steven C. H. Hoi Feb 2018

Sparse Passive-Aggressive Learning For Bounded Online Kernel Methods, Jing Lu, Doyen Sahoo, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

One critical deficiency of traditional online kernel learning methods is their unbounded and growing number of support vectors in the online learning process, making them inefficient and non-scalable for large-scale applications. Recent studies on scalable online kernel learning have attempted to overcome this shortcoming, e.g., by imposing a constant budget on the number of support vectors. Although they attempt to bound the number of support vectors at each online learning iteration, most of them fail to bound the number of support vectors for the final output hypothesis, which is often obtained by averaging the series of hypotheses over all the …

Go to article

Early Detection Of Mild Cognitive Impairment In Elderly Through Iot: Preliminary Findings, Hwee-Xian Tan, Hwee-Pink Tan Feb 2018

Early Detection Of Mild Cognitive Impairment In Elderly Through Iot: Preliminary Findings, Hwee-Xian Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Mild Cognitive Impairment (MCI) results in the gradual decline in a person’s cognitive abilities, and subsequently an increased risk of developing dementia. Although there is no cure for dementia, timely medical and clinical interventions can be administered to elderly who have been diagnosed with MCI, to decelerate the process of further cognitive decline and prolong the duration that they enjoy quality of life. In this paper, we present our preliminary findings of early detection of MCI in elderly who are living in the community, through the use of Internet of Things (IoT) devices for continuous, unobtrusive sensing. Multimodal sensors are …

Go to article

Long Term Key Management Architecture For Scada Systems, Hendra Saputra, Zhigang Zhao Feb 2018

Long Term Key Management Architecture For Scada Systems, Hendra Saputra, Zhigang Zhao

Research Collection School Of Computing and Information Systems

A SCADA key management is required to provide a key management protocol that will be used to secure the communication channel of the SCADA entities. The SCADA key management scheme often uses symmetric cryptography due to resource constraints of the SCADA entities. Normally the use of symmetric cryptography mechanism is in the form of pre-shared keys, which are installed manually and are fixed. Then, these pre-shared keys or long term keys are used to generate session keys. However, it is important that these long term keys can be updated and refreshed dynamically. With the nature of SCADA systems which may …

Go to article

Technologies For Ageing-In-Place: The Singapore Context, Nadee Goonawardene, Pius Lee, Hwee Xian Tan, Alvin C. Valera, Hwee-Pink Tan Feb 2018

Technologies For Ageing-In-Place: The Singapore Context, Nadee Goonawardene, Pius Lee, Hwee Xian Tan, Alvin C. Valera, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

The number of elderly citizens aged 65 and above in Singapore, is expected to double from 440,000in 2015, to 900,000 by 2030. Along with this “Silver Tsunami” is the upward trend of the numberof elderly who are living alone — which is estimated to increase from 35,000 in 2012 to 83,000 by2030. These exclude elderly who are alone at home when their family members are working.Elderly who are staying alone are at higher risk of social isolation and tend to have poorer accessto healthcare. In addition, the general elderly population is typically more susceptible to deteriorating health conditions, which can …

Go to article

Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou Jan 2018

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 …

Go to article

Social Collaborative Media In Software Development, Didi Surian, David Lo Jan 2018

Social Collaborative Media In Software Development, Didi Surian, David Lo

Research Collection School Of Computing and Information Systems

In this entry, we discuss various collaborative media which are commonly used among software developers. We start by discussing common communication channels developers used. These communication channels are discussed in two groups: public and enterprise-wide media. We then elaborate project management media in coordinating and managing project activities. Finally, we discuss a number of online knowledge resources, i.e., collaborative/individual knowledge resources and social networks.

Go to article

User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yanju Liu, Zhan Wang Jan 2018

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 …

Go to article

Modeling Engagement Of Programming Students Using Unsupervised Machine Learning Technique, Hua Leong Fwa, Lindsay Marshall Jan 2018

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 …

Go to article

Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu Jan 2018

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 …

Go to article

An Iterated Local Search Algorithm For The Team Orienteering Problem With Variable Profits, Aldy Gunawan, Kien Ming Ng, Graham Kendall, Junhan Lai Jan 2018

An Iterated Local Search Algorithm For The Team Orienteering Problem With Variable Profits, Aldy Gunawan, Kien Ming Ng, Graham Kendall, Junhan Lai

Research Collection School Of Computing and Information Systems

The orienteering problem (OP) is a routing problem that has numerous applications in various domains such as logistics and tourism. The objective is to determine a subset of vertices to visit for a vehicle so that the total collected score is maximized and a given time budget is not exceeded. The extensive application of the OP has led to many different variants, including the team orienteering problem (TOP) and the team orienteering problem with time windows. The TOP extends the OP by considering multiple vehicles. In this article, the team orienteering problem with variable profits (TOPVP) is studied. The main …

Go to article

Tinyvisor: An Extensible Secure Framework On Android Platforms, Dong Shen, Zhoujun Li, Xiaojing Su, Jinxin Ma, Deng, Robert H. Jan 2018

Tinyvisor: An Extensible Secure Framework On Android Platforms, Dong Shen, Zhoujun Li, Xiaojing Su, Jinxin Ma, Deng, Robert H.

Research Collection School Of Computing and Information Systems

As the utilization of mobile platform keeps growing, the security issue of mobile platform becomes a serious threat to user privacy. The current security measures mainly focus on the application level and the framework level, with little protection on the kernel. Virtualization technologies have been used in x86 platforms to protect the security of the kernel. With a higher privilege than the guest operating system, the hypervisor can effectively detect and defend against the malicious activity inside the guest kernel. In this paper, we build a hypervisor framework called TinyVisor leveraging the ARM virtualization extensions to protect the guest system …

Go to article

Integrated Reward Scheme And Surge Pricing In A Ride Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye Jan 2018

Integrated Reward Scheme And Surge Pricing In A Ride Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye

Research Collection School Of Computing and Information Systems

Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. In this paper, to address the …

Go to article

Discriminant Analysis On Riemannian Manifold Of Gaussian Distributions For Face Recognition With Image Sets, W. Wang, R. Wang, Zhiwu Huang, S. Shan, X. Chen Jan 2018

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 …

Go to article

Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu Jan 2018

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 …

Go to article

Online/Offline Traceable Attribute-Based Encryption [In Chinese], Kai Zhang, Jianfeng Ma, Junwei Zhang, Zuobin Ying, Tao Zhang, Ximeng Liu Jan 2018

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 …

Go to article

Exact And Heuristic Approaches For The Multi-Agent Orienteering Problem With Capacity Constraints, Wenjie Wang, Hoong Chuin Lau, Shih-Fen Cheng Jan 2018

Exact And Heuristic Approaches For The Multi-Agent Orienteering Problem With Capacity Constraints, Wenjie Wang, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This paper introduces and addresses a new multiagent variant of the orienteering problem (OP), namely the multi-agent orienteering problem with capacity constraints (MAOPCC). Different from the existing variants of OP, MAOPCC allows a group of visitors to concurrently visit a node but limits the number of visitors simultaneously being served at each node. In this work, we solve MAOPCC in a centralized manner and optimize the total collected rewards of all agents. A branch and bound algorithm is first proposed to find an optimal MAOPCC solution. Since finding an optimal solution for MAOPCC can become intractable as the number of …

Go to article

Why Are Fairness Concerns So Important? Lessons From Pricing A Shared Last-Mile Transportation System, Yiwei Chen, Hai Wang Jan 2018

Why Are Fairness Concerns So Important? Lessons From Pricing A Shared 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 the final destination. The Last-Mile Transportation System (LMTS), which has recently emerged, provides on-demand shared last-mile transportation service. While it is natural that in the last-mile supply chain, a high-value parcel should be charged a higher price and deserves service priority compared to a low-value parcel, it is not straightforward to identify an obvious pricing and service priority for an LMTS that serves passengers. In an LMTS, a special-type passenger who has a higher valuation of service usually has a lower waiting time …

Go to article

Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong Jan 2018

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, …

Go to article

Multi-Target Deep Neural Networks: Theoretical Analysis And Implementation, Zeng Zeng, Nanying Liang, Xulei Yang, Steven C. H. Hoi Jan 2018

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 …

Go to article

Real-World Large-Scale Iot Systems For Community Eldercare: A Comparative Study On System Dependability, Hwee-Pink Tan, Austin Zhang Jan 2018

Real-World Large-Scale Iot Systems For Community Eldercare: A Comparative Study On System Dependability, Hwee-Pink Tan, Austin Zhang

Research Collection School Of Computing and Information Systems

The paradigm of aging-in-place — where the elderly live and age in their own homes, independently and safely, with care provided by the community — is compelling, especially in societies that face both shortages in institutionalized eldercare resources, and rapidly-aging populations. Internet-of-Things (IoT) technologies, particularly in-home monitoring solutions, are commercially available, and can be a fundamental enabler of smart community eldercare, if they are dependable. In this paper, we present our findings on system performance of solutions from two vendors, which we have deployed at scale for technology-enabled community care. In particular, we highlight the importance of quantifying actual system …

Go to article

Pagesense: Toward Stylewise Contextual Advertising Via Visual Analysis Of Web Pages, Tao Mei, Lusong Li, Xinmei Tian, Dacheng Tao, Chong-Wah Ngo Jan 2018

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. …

Go to article

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 Jan 2018

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 …

Go to article

Strong Identity-Based Proxy Signature Schemes, Revisited, Weiwei Liu, Yi Mu, Guomin Yang, Yangguang Tian Jan 2018

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 …

Go to article

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 Jan 2018

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 …

Go to article

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 Jan 2018

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 …

Go to article

Collaboration Patterns In Software Developer Network, Didi Surian, Ee-Peng Lim, David Lo Jan 2018

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 …

Go to article

A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui Jan 2018

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 …

Go to article

Competency Analytics Tool: Analyzing Curriculum Using Course Competencies, Swapna Gottipati, Venky Shankararaman Jan 2018

Competency Analytics Tool: Analyzing Curriculum Using Course Competencies, Swapna Gottipati, Venky Shankararaman

Research Collection School Of Computing and Information Systems

The applications of learning outcomes and competency frameworks have brought better clarity to engineering programs in many universities. Several frameworks have been proposed to integrate outcomes and competencies into course design, delivery and assessment. However, in many cases, competencies are course-specific and their overall impact on the curriculum design is unknown. Such impact analysis is important for analyzing, discovering gaps and improving the curriculum design. Unfortunately, manual analysis is a painstaking process due to large amounts of competencies across the curriculum. In this paper, we propose an automated method to analyze the competencies and discover their impact on the overall …

Go to article

Pricing For A Last-Mile Transportation System, Yiwei Chen, Hai Wang Jan 2018

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, …

Go to article

User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yingjiu Li, Zhan. Wang Jan 2018

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 …

Go to article

First Prev Next Last