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Articles 4351 - 4380 of 8495
Full-Text Articles in Computer Sciences
A Metrics Suite Of Cloud Computing Adoption Readiness, Robert J. Kauffman, Dan Ma, Martin Yu
A Metrics Suite Of Cloud Computing Adoption Readiness, Robert J. Kauffman, Dan Ma, Martin Yu
Research Collection School Of Computing and Information Systems
Recent research on cloud computing adoption suggests the lack of a deep understanding of its benefits by managers and organizations. We present a firm-level cloud computing readiness metrics suite and assess its applicability for various cloud computing service types. We propose four relevant categories for firm-level adoption readiness, including technology and performance, organization and strategy, economic and valuation, and regulatory and environmental dimensions. We further define sub-categories and measures for each. Our evidence of the appropriateness of the metrics suite is derived based on a series of empirical cases developed from our project work, which encompasses input from field interviews, …
Sequential Recommendation With User Memory Networks, Xu Chen, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Yixin Cao, Zheng Qin, Hongyuan Zha
Sequential Recommendation With User Memory Networks, Xu Chen, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Yixin Cao, Zheng Qin, Hongyuan Zha
Research Collection School Of Computing and Information Systems
User preferences are usually dynamic in real-world recommender systems, and a user»s historical behavior records may not be equally important when predicting his/her future interests. Existing recommendation algorithms -- including both shallow and deep approaches -- usually embed a user»s historical records into a single latent vector/representation, which may have lost the per item- or feature-level correlations between a user»s historical records and future interests. In this paper, we aim to express, store, and manipulate users» historical records in a more explicit, dynamic, and effective manner. To do so, we introduce the memory mechanism to recommender systems. Specifically, we design …
Identifying Self-Admitted Technical Debt In Open Source Projects Using Text Mining, Qiao Huang, Emad Shihab, Xin Xia, David Lo, Shanping Li
Identifying Self-Admitted Technical Debt In Open Source Projects Using Text Mining, Qiao Huang, Emad Shihab, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Technical debt is a metaphor to describe the situation in which long-term code quality is traded for short-term goals in software projects. Recently, the concept of self-admitted technical debt (SATD) was proposed, which considers debt that is intentionally introduced, e.g., in the form of quick or temporary fixes. Prior work on SATD has shown that source code comments can be used to successfully detect SATD, however, most current state-of-the-art classification approaches of SATD rely on manual inspection of the source code comments. In this paper, we proposed an automated approach to detect SATD in source code comments using text mining. …
Scalable Urban Mobile Crowdsourcing: Handling Uncertainty In Worker Movement, Shih-Fen Cheng, Cen Chen, Thivya Kandappu, Hoong Chuin Lau, Archan Misra, Nikita Jaiman, Randy Tandriansyah Daratan, Desmond Koh
Scalable Urban Mobile Crowdsourcing: Handling Uncertainty In Worker Movement, Shih-Fen Cheng, Cen Chen, Thivya Kandappu, Hoong Chuin Lau, Archan Misra, Nikita Jaiman, Randy Tandriansyah Daratan, Desmond Koh
Research Collection School Of Computing and Information Systems
In this article, we investigate effective ways of utilizing crowdworkers in providing various urban services. The task recommendation platform that we design can match tasks to crowdworkers based on workers’ historical trajectories and time budget limits, thus making recommendations personal and efficient. One major challenge we manage to address is the handling of crowdworker’s trajectory uncertainties. In this article, we explicitly allow multiple routine routes to be probabilistically associated with each worker. We formulate this problem as an integer linear program whose goal is to maximize the expected total utility achieved by all workers. We further exploit the separable structures …
Early Detection Of Mild Cognitive Impairment In Elderly Through Iot: Preliminary Findings, Hwee-Xian Tan, Hwee-Pink Tan
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 …
Long Term Key Management Architecture For Scada Systems, Hendra Saputra, Zhigang Zhao
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 …
Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points, Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi
Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points, Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Locally Linear Support Vector Machine (LLSVM) has been actively used in classification tasks due to its capability of classifying nonlinear patterns. However, existing LLSVM suffers from two drawbacks: (1) a particular and appropriate regularization for LLSVM has not yet been addressed; (2) it usually adopts a three-stage learning scheme composed of learning anchor points by clustering, learning local coding coordinates by a predefined coding scheme, and finally learning for training classifiers. We argue that this decoupled approaches oversimplifies the original optimization problem, resulting in a large deviation due to the disparate purpose of each step. To address the first issue, …
Technologies For Ageing-In-Place: The Singapore Context, Nadee Goonawardene, Pius Lee, Hwee Xian Tan, Alvin C. Valera, Hwee-Pink Tan
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 …
Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham
Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Effective emergency (medical, fire or criminal) response iscrucial for improving safety and security in urban environments. Recent research in improving effectiveness of emergency management systems (EMSs) has utilized data-drivenoptimization models for efficient allocation of emergency response vehicles (ERVs) to base locations. However, thesedata-driven optimization models either ignore the dispatchstrategy of ERVs (typically the nearest available ERV is dispatched to serve an incident) or employ myopic approaches(e.g., greedy approach based on marginal gain). This resultsin allocations that are not synchronised with the real evolution dynamics on the ground or can be improved significantly.To bridge this gap, we make the following contributions: …
Vt-Revolution: Interactive Programming Video Tutorial Authoring And Watching System, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo
Vt-Revolution: Interactive Programming Video Tutorial Authoring And Watching System, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
Procedural knowledge describes actions and manipulations that are carried out to complete programming tasks. An effective way to document procedural knowledge is programming video tutorials. Existing solutions to adding interactive workflow and elements to programming videos have a dilemma between the level of desired interaction and the efforts required for authoring tutorials. In this work, we tackle this dilemma by designing and building a programming video tutorial authoring system that leverages operating system level instrumentation to log workflow history while tutorial authors are creating programming videos, and the corresponding tutorial watching system that enhances the learning experience of video tutorials …
Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization For Text Data Co-Clustering, Aghiles Salah, Melissa Ailem, Mohamed Nadif
Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization For Text Data Co-Clustering, Aghiles Salah, Melissa Ailem, Mohamed Nadif
Research Collection School Of Computing and Information Systems
Text data co-clustering is the process of partitioning the documents and words simultaneously. This approach has proven to be more useful than traditional one-sided clustering when dealing with sparsity. Among the wide range of co-clustering approaches, Non-Negative Matrix Tri-Factorization (NMTF) is recognized for its high performance, flexibility and theoretical foundations. One important aspect when dealing with text data, is to capture the semantic relationships between words since documents that are about the same topic may not necessarily use exactly the same vocabulary. However, this aspect has been overlooked by previous co-clustering models, including NMTF. To address this issue, we rely …
Two Birds With One Stone: Classifying Positive And Unlabeled Examples On Uncertain Data Streams, Donghong Han, Shuoru Li, Fulin Wei, Yuying Tang, Feida Zhu, Guoren Wang
Two Birds With One Stone: Classifying Positive And Unlabeled Examples On Uncertain Data Streams, Donghong Han, Shuoru Li, Fulin Wei, Yuying Tang, Feida Zhu, Guoren Wang
Research Collection School Of Computing and Information Systems
An important feature characteristic of the data streams in many of today's big data applications is the intrinsic uncertainty, which could happen for both item occurrence and attribute value. While this has already posed great challenges for fundamental data mining tasks such as classification, things are made even more complicated by the fact that completely-labeled examples are usually unavailable in such settings, leaving researchers the only option to learn classifiers on partially-labeled examples on uncertain data streams. Furthermore, there will be concept drift on evolving data streams. To address these challenges, this paper therefore focuses on the study of learning …
Sparse Modeling-Based Sequential Ensemble Learning For Effective Outlier Detection In High-Dimensional Numeric Data, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu
Sparse Modeling-Based Sequential Ensemble Learning For Effective Outlier Detection In High-Dimensional Numeric Data, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu
Research Collection School Of Computing and Information Systems
The large proportion of irrelevant or noisy features in reallife high-dimensional data presents a significant challenge to subspace/feature selection-based high-dimensional outlier detection (a.k.a. outlier scoring) methods. These methods often perform the two dependent tasks: relevant feature subset search and outlier scoring independently, consequently retaining features/subspaces irrelevant to the scoring method and downgrading the detection performance. This paper introduces a novel sequential ensemble-based framework SEMSE and its instance CINFO to address this issue. SEMSE learns the sequential ensembles to mutually refine feature selection and outlier scoring by iterative sparse modeling with outlier scores as the pseudo target feature. CINFO instantiates SEMSE …
Upping The Game Of Taxi Driving In The Age Of Uber, Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Wai Hin Wong, Rajendram Rishikeshan Rajendram, Trong Khiem Tran, Pradeep Varakantham, Nghia Truong Trong, Firmansyah Abd Rahman
Upping The Game Of Taxi Driving In The Age Of Uber, Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Wai Hin Wong, Rajendram Rishikeshan Rajendram, Trong Khiem Tran, Pradeep Varakantham, Nghia Truong Trong, Firmansyah Abd Rahman
Research Collection School Of Computing and Information Systems
In most cities, taxis play an important role in providing point-to-point transportation service. If the taxi service is reliable, responsive, and cost-effective, past studies show that taxi-like services can be a viable choice in replacing a significant amount of private cars. However, making taxi services efficient is extremely challenging, mainly due to the fact that taxi drivers are self-interested and they operate with only local information. Although past research has demonstrated how recommendation systems could potentially help taxi drivers in improving their performance, most of these efforts are not feasible in practice. This is mostly due to the lack of …
Sparse Passive-Aggressive Learning For Bounded Online Kernel Methods, Jing Lu, Doyen Sahoo, Peilin Zhao, Steven C. H. Hoi
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 …
Integrated Cooperation And Competition In Multi-Agent Decision-Making, Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein
Integrated Cooperation And Competition In Multi-Agent Decision-Making, Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Observing that many real-world sequential decision problems are not purely cooperative or purely competitive, we propose a new model—cooperative-competitive process (CCP)—that can simultaneously encapsulate both cooperation and competition.First, we discuss how the CCP model bridges the gap between cooperative and competitive models. Next, we investigate a specific class of group-dominant CCPs, in which agents cooperate to achieve a common goal as their primary objective, while also pursuing individual goals as a secondary objective. We provide an approximate solution for this class of problems that leverages stochastic finite-state controllers.The model is grounded in two multi-robot meeting and box pushing domains that …
Resource-Constrained Scheduling For Maritime Traffic Management, Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau
Resource-Constrained Scheduling For Maritime Traffic Management, Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We address the problem of mitigating congestion and preventing hotspots in busy water areas such as Singapore Straits and port waters. Increasing maritime traffic coupled with narrow waterways makes vessel schedule coordination for just-in-time arrival critical for navigational safety. Our contributions are: 1) We formulate the maritime traffic management problem based on the real case study of Singapore waters; 2) We model the problem as a variant of the resource-constrained project scheduling problem (RCPSP), and formulate mixed-integer and constraint programming (MIP/CP) formulations; 3) To improve the scalability, we develop a combinatorial Benders (CB) approach that is significantly more effective than …
Cross-Language Learning For Program Classification Using Bilateral Tree-Based Convolutional Neural Networks, Duy Quoc Nghi Bui, Lingxiao Jiang, Yijun Yu
Cross-Language Learning For Program Classification Using Bilateral Tree-Based Convolutional Neural Networks, Duy Quoc Nghi Bui, Lingxiao Jiang, Yijun Yu
Research Collection School Of Computing and Information Systems
Towards the vision of translating code that implements an algorithm from one programming language into another, this paper proposes an approach for automated program classification using bilateral tree-based convolutional neural networks (BiTBCNNs). It is layered on top of two tree-based convolutional neural networks (TBCNNs), each of which recognizes the algorithm of code written in an individual programming language. The combination layer of the networks recognizes the similarities and differences among code in different programming languages. The BiTBCNNs are trained using the source code in different languages but known to implement the same algorithms and/or functionalities. For a preliminary evaluation, we …
Compressive Representation For Device-Free Activity Recognition With Passive Rfid Signal Strength, Lina Yao, Quan Z. Sheng, Xue Li, Tao Gu, Mingkui Tan, Xianzhi Wang, Sen Wang, Wenjie Ruan
Compressive Representation For Device-Free Activity Recognition With Passive Rfid Signal Strength, Lina Yao, Quan Z. Sheng, Xue Li, Tao Gu, Mingkui Tan, Xianzhi Wang, Sen Wang, Wenjie Ruan
Research Collection School Of Computing and Information Systems
Understanding and recognizing human activities is a fundamental research topic for a wide range of important applications such as fall detection and remote health monitoring and intervention. Despite active research in human activity recognition over the past years, existing approaches based on computer vision or wearable sensor technologies present several significant issues such as privacy (e.g., using video camera to monitor the elderly at home) and practicality (e.g., not possible for an older person with dementia to remember wearing devices). In this paper, we present a low-cost, unobtrusive, and robust system that supports independent living of older people. The system …
Food Photo Recognition For Dietary Tracking: System And Experiment, Zhao-Yan Ming, Jingjing Chen, Yu Cao, Ciarán Forde, Chong-Wah Ngo, Tat Seng Chua
Food Photo Recognition For Dietary Tracking: System And Experiment, Zhao-Yan Ming, Jingjing Chen, Yu Cao, Ciarán Forde, Chong-Wah Ngo, Tat Seng Chua
Research Collection School Of Computing and Information Systems
Tracking dietary intake is an important task for health management especially for chronic diseases such as obesity, diabetes, and cardiovascular diseases. Given the popularity of personal hand-held devices, mobile applications provide a promising low-cost solution to tackle the key risk factor by diet monitoring. In this work, we propose a photo based dietary tracking system that employs deep-based image recognition algorithms to recognize food and analyze nutrition. The system is beneficial for patients to manage their dietary and nutrition intake, and for the medical institutions to intervene and treat the chronic diseases. To the best of our knowledge, there are …
Things You May Not Know About Android (Un)Packers: A Systematic Study Based On Whole-System Emulation, Yue Duan, Mu Zhang, Abhishek Vasist Bhaskar, Heng Yin, Xiaorui Pan, Tongxin Li, Xueqiang Wang, Xiaofeng Wang
Things You May Not Know About Android (Un)Packers: A Systematic Study Based On Whole-System Emulation, Yue Duan, Mu Zhang, Abhishek Vasist Bhaskar, Heng Yin, Xiaorui Pan, Tongxin Li, Xueqiang Wang, Xiaofeng Wang
Research Collection School Of Computing and Information Systems
The prevalent usage of runtime packers has complicated Android malware analysis, as both legitimate and malicious apps are leveraging packing mechanisms to protect themselves against reverse engineer. Although recent efforts have been made to analyze particular packing techniques, little has been done to study the unique characteristics of Android packers. In this paper, we report the first systematic study on mainstream Android packers, in an attempt to understand their security implications. For this purpose, we developed DROIDUNPACK, a whole-system emulation based Android packing analysis framework, which compared with existing tools, relies on intrinsic characteristics of Android runtime (rather than heuristics), …
R3: Reinforced Ranker-Reader For Open-Domain Question Answering, Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerald Tesauro, Bowen Zhou, Jing Jiang
R3: Reinforced Ranker-Reader For Open-Domain Question Answering, Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerald Tesauro, Bowen Zhou, Jing Jiang
Research Collection School Of Computing and Information Systems
In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results in simplified closed-domain settings such as the SQuAD (Rajpurkar et al. 2016) dataset, which provides a pre-selected passage, from which the answer to a given question may be extracted. More recently, researchers have begun to tackle open-domain QA, in which the model is given a question and access to a large corpus (e.g., wikipedia) instead of a pre-selected passage (Chen et al. 2017a). This setting is more complex as it requires large-scale search for relevant …
Utilizing Hypervisor To Enhance Trustzone’S Introspection Capabilities On Non-Secure World, Zhang-Kai Zhang, Zhou-Jun Li, Chun-He Xia, Jin-Xin Ma, Jinhua Cui
Utilizing Hypervisor To Enhance Trustzone’S Introspection Capabilities On Non-Secure World, Zhang-Kai Zhang, Zhou-Jun Li, Chun-He Xia, Jin-Xin Ma, Jinhua Cui
Research Collection School Of Computing and Information Systems
Widely used on the Android phones, the technology of ARM TrustZone divides the hardware resources of Android phones into two worlds:non-secure world and secure world. The Android operating system used by user is running in the non-secure world, while the non-secure world's introspection systems (e.g., KNOX, Hypervisor) that are based on TrustZone are running in the secure world. These introspection systems have the high privilege. They can dynamically check Android kernel integrity and perform memory management of non-secure world instead of Android kernel. But TrustZonecan can not completely introspect the hardware resources (e.g., Cache) of non-secure world because of the …
Integrated Reward Scheme And Surge Pricing In A Ride Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye
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 …
Real-World Large-Scale Iot Systems For Community Eldercare: A Comparative Study On System Dependability, Hwee-Pink Tan, Austin Zhang
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 …
Social Collaborative Media In Software Development, Didi Surian, David Lo
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.
Competency Analytics Tool: Analyzing Curriculum Using Course Competencies, Swapna Gottipati, Venky Shankararaman
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 …
Tinyvisor: An Extensible Secure Framework On Android Platforms, Dong Shen, Zhoujun Li, Xiaojing Su, Jinxin Ma, Deng, Robert H.
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 …
Exact And Heuristic Approaches For The Multi-Agent Orienteering Problem With Capacity Constraints, Wenjie Wang, Hoong Chuin Lau, Shih-Fen Cheng
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 …
An Iterated Local Search Algorithm For The Team Orienteering Problem With Variable Profits, Aldy Gunawan, Kien Ming Ng, Graham Kendall, Junhan Lai
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 …