Browsing by Author "Chen, Feng"

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    Agent-based Web services evolution for pervasive computing
    (IEEE, 2005-01-17) Liu, Ruimin; Chen, Feng; Yang, Hongji; Chu, William Cheng-chung; Lai, Yu-Bin
    Pervasive computing will be a fertile source of challenging research problems in computer systems for many years to come. The ability to obtain services and information from an environment anywhere at anytime is part of pervasive computing. The problem is that most of existing services and applications are designed for stationary PCs. How to evolve these so called legacy system towards those mobile users in a controlled manner is vital for that pervasive computing can become more widespread. In this paper, we report our efforts on the PerEvo project. After discussing the basic features and challenges of pervasive computing, we present an agent-based Web services evolution approach, which is well suited to building software solutions for pervasive computing, and illustrate our solutions through a booking scenario.
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    Agentification for web services
    (IEEE, 2004-10-18) Chen, Feng; Yang, Hongji; Guo, He; Xu, Baowen
    We report our effort on the AgenEvo project, which develops an evolution approach to re-engineer legacy systems into agent-based Web services. We first survey the key technologies, which are adopted in this paper. After discussing the basic features of the Web services and agent, we focus on agent-based Web services, which are hot spot in web-based research area. We argue that agent-based Web services are well suited to building software solutions for distributed, open and dynamic web-based systems. Next, we introduce our approach on re-engineering framework and working flow. The method that integrates agents with Web services for legacy system evolution is proposed and an example on how to use agent-based Web services software evolution framework and methodology to re-engineer the legacy system is illustrated. Finally, we conclude the paper and suggest the directions of the possible future research.
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    An Approach to Evolving Legacy Software System into Cloud Computing Environment
    (IGI Global, 2013) Zheng, S.; Chen, Feng; Yang, Hongji; Li, Jianzhi
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    As-rigid-as-possible shape deformation and interpolation
    (Elsevier, 2008) Guo, He; Fu, Xinyuan; Chen, Feng; Yang, Hongji; Wang, Yuxin; Li, Han
    We provide a detailed analysis of the 2D deformation algorithm based on non-linear least squares optimization, and prove that different mesh structure is of critical importance to deforming result. Based on triangle mesh, preserving the length of edges during deforming is enough to preserve the local, global and boundary properties of the shape. Sufficient theoretical analysis and experiments proved the advantage of the algorithm: (1) It is more stable. The constraint of edges length is strong enough to preserve the stability of triangle, thus the local and global structure are stable. (2) Due to less constraints, the calculating cost is reduced and the performance is improved. (3) The problem of parameter adjusting is solved in the approach. Further more, the algorithm has the ability to control facial expression and to adjust the area of shape etc. In addition, a new approach to shape interpolation is presented. The inputs of the shape interpolation algorithm are bitmap represented images without any topology information in both the original and the target shapes. The strategy is to extract the topology of the original shape, and set up the correspondence between the original and the target shapes, which is to find the matching contour vertices between the original and target shapes. And the shape deformation algorithm is applied using the interpolation of the matching vertices as controlling points. The algorithm guarantees as-rigid-as-possible and rotation invariant shape interpolation. The interpolated shapes have the same topology structure with the original and the target shapes. Experiments indicate that the algorithm is stable and well performed.
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    An Assistive Augmented Reality-based Smartglasses Solution for Individuals with Autism Spectrum Disorder
    (IEEE, 2019-11-04) Machado, Eduardo; Carrillo, Ivan; Saldana, David; Chen, Feng; Chen, Liming
    Acquiring daily living skills can be difficult for children and adults with autism spectrum disorders (ASD). Increasing evidences indicate that classic occupational interventions approaches such as Discrete Trial Teaching(DTT) results to be boring and frustrating to individuals with ASD. As consequence, they spend most of the time off task and face difficulties to sustaining their selective attention. Moreover, in-person interventions are both costly and difficult to access. Evidence-based research shows that the use of augmented reality(AR) strengthens and attracts the attention of individuals with ASD, enhancing their engagement and user's task performance. However, despite of the benefits, the use of AR as an assistive technology by this segment of population, still presents low rates of adaption. Platforms such as smartphone and tablet, used to run AR technologies provokes an head-down posture that decrease the user's awareness to the physical environment putting themselves in risk of injury. Moreover, they are forced to have their hands occupied and most of the existent applications are lacks to be personalized to different user's needs. This paper introduces a conceptual framework for developing real-time personalized assistive AR-based smartglasses system. The solution aims to solve the issues related to in-person occupational interventions i.e constant need for professional supervision during intervention as well as limited intervention duration and frequency. In addition, we also target issues related to classic AR-based platforms i.e head-down postures and task-specific design.
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    Component Profiling and Prediction Models for QoS-Aware Self-Adapting DSMS Framework
    (Association for Computing Machinery, 2021-08-20) Yagnik, Tarjana; Chen, Feng; Kasraian, Laleh
    Quality of Service (QoS) has been identified as an important attribute of system performance of Data Stream Management Systems (DSMS). A DSMS should have the ability to allocate physical computing resources between different submitted queries and fulfil QoS specifications in a fair and square manner. System scheduling strategies need to be adjusted dynamically to utilise available physical resources to guarantee the end-to-end quality of service levels. In this paper, we present a proactive method that utilises a multi-level component profiling approach to build prediction models that anticipate several QoS violations and performance degradations. The models are constructed using several incremental machine learning algorithms that are enhanced with ensemble learning and abnormal detection techniques. The approach performs accurate predictions in near real-time with accuracy up to 85% and with abnormal detection techniques, the accuracy reaches 100%. This is a major component within a proposed QoS-Aware Self-Adapting Data Stream Management Framework.
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    Context-aware Cloud Computing for Personal Learning Environment
    (IGI Global, 2016) Chen, Feng; Al-Bayatti, Ali Hilal; Siewe, Francois
    Virtual learning means to learn from social interactions in a virtual platform that enables people to study anywhere and at any time. Current Virtual Learning Environments (VLEs) are a range of integrated web based applications to support and enhance the education. Normally, VLEs are institution centric; are owned by the institutions and are designed to support formal learning, which do not support lifelong learning. These limitations led to the research of Personal Learning Environments (PLEs). PLEs are learner-centric and provide lifelong access as well as the ability of a user to produce (share) and consume information resources easily. This requires the user to handle the context information and make decisions for personal learning. Context-aware PLEs can support these requirements. However, too much information and resource is a big challenge for building the context-aware PLEs, In this research, a context-aware cloud based PLE architecture is proposed, which is driven by a Context-Aware Engine to acquire, filter and interpret context information based on the preferences defined in user profile, where cloud computing is taken as service infrastructure. An illustrative personal learning scenario is investigated to demonstrate the proof of concept implementation. The Context-Aware Engine collects context information as input and generates a set of suggested learning resources of current interest to the user. The results show the benefits of the proposed architecture on resource utilisation and user experience.
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    A deep learning approach for privacy preservation in assisted living
    (IEEE, 2018-10-08) Psychoula, Ismini; Merdivan, Erinc; Singh, Deepika; Chen, Liming; Chen, Feng; Hanke, Sten; Kropf, Johannes; Holzinger, Andreas; Geist, Matthieu
    In the era of Internet of Things (IoT) technologies the potential for privacy invasion is becoming a major concern especially in regards to healthcare data and Ambient Assisted Living (AAL) environments. Systems that offer AAL technologies make extensive use of personal data in order to provide services that are context-aware and personalized. This makes privacy preservation a very important issue especially since the users are not always aware of the privacy risks they could face. A lot of progress has been made in the deep learning field, however, there has been lack of research on privacy preservation of sensitive personal data with the use of deep learning. In this paper we focus on a Long Short Term Memory (LSTM) Encoder-Decoder, which is a principal component of deep learning, and propose a new encoding technique that allows the creation of different AAL data views, depending on the access level of the end user and the information they require access to. The efficiency and effectiveness of the proposed method are demonstrated with experiments on a simulated AAL dataset. Qualitatively, we show that the proposed model learns privacy operations such as disclosure, deletion and generalization and can perform encoding and decoding of the data with almost perfect recovery.
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    A Dynamic Grid-Based Algorithm for Taxi Ridesharing in Multiple Road Condition
    (IEEE, 2020-04-09) Wang, Yuxin; Wu, Bing; Xv, Tongkun; Shen, Yanming; Chen, Feng
    As the way of easing urban traffic congestion, taxi ridesharing can effectively protect the environment and solve the difficulty of passengers taking taxis when taxi demand is high. In this paper, we formally define the dynamic ride-sharing problem and propose a taxi candidates-reduction ride-sharing scheduling algorithm based on dynamic grid. Regarding the congestion situation of the multiple road condition, the concept of speed decay zone was purposed to simulate this area. To solve the problem of low satisfaction in the congested situation, we devise a dynamic grid division strategy that reduces the grid size of the hotspot area to satisfy the specific needs of passengers in rush hour, and efficiently screen candidate taxis by dynamic grid index. We perform the experiments using the request dataset generated by the taxi request simulator of Beijing Chaoyang district. The performance shows that our approach reduce 35.5% computation without losing average satisfaction compared with existing ridesharing algorithm.
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    Enforcing Role-Based Access Controls in Software Systems with an Agent Based Service Oriented Approach
    (IEEE, 2007-06-25) Chen, Feng; Li, Shaoyun; Yang, Hongji
    Access control is often used to make restrictions to the resources in a system so that these resources can only be accessed by those who have the corresponding privilege. Role-based access controls (RBAC) model introduces roles into access control so that the privilege is assigned to role and access control can be managed easily by defining the role of the users and inheritance structure of the roles. Although the RBAC model has been well accepted, it turns out to have some problems in applying RBAC to an existing system: an existing system is generally not organised in roles; it is very hard to add the access control functions to each module of an existing system. In this paper, an agent-based service oriented approach that helps existing systems be migrated to RBAC for software evolution is proposed. The architecture and working flow of the approach are presented and an example showing how to use the proposed framework and methodology is illustrated.
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    Enhanced Multi-Source Data Analysis for Personalized Sleep-Wake Pattern Recognition and Sleep Parameter Extraction
    (Springer, 2020) Fallmann, S.; Chen, Liming; Chen, Feng
    Sleep behavior is traditionally monitored with polysomnography, and sleep stage patterns are a key marker for sleep quality used to detect anomalies and diagnose diseases. With the growing demand for personalized healthcare and the prevalence of the Internet of Things, there is a trend to use everyday technologies for sleep behavior analysis at home, having the potential to eliminate expensive in-hospital monitoring. In this paper, we conceived a multi-source data mining approach to personalized sleep-wake pattern recog-nition which uses physiological data and personal information to facilitate fine-grained detection. Physiological data includes actigraphy and heart rate variability and personal data makes use of gender, health status and race infor-mation which are known influence factors. Moreover, we developed a personal-ized sleep parameter extraction technique fused with the sleep-wake approach, achieving personalized instead of static thresholds for decision-making. Results show that the proposed approach improves the accuracy of sleep and wake stage recognition, therefore, offers a new solution for personalized sleep-based health monitoring.
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    An enhanced use case diagram to model Context Aware Systems
    (2013) Almutairi, Saad; Abu-Samaha, A.; Bell, G.; Chen, Feng
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    An Experimental Study of Learning Behaviour in an ELearning Environment
    (IEEE, 2019-01-24) Alhasan, K.; Chen, Liming; Chen, Feng
    To reach an adaptive eLearning course, it is crucial to control and monitor the student behaviour dynamically to implicitly diagnose the student learning style. Eye tracing can serve that purpose by investigate the gaze data behaviour to the learning content. In this study, we conduct an eye tracking experiment to analyse the student pattern of behaviour to output his learning style as an aspect of personalisation in an eLearning course. We use the electroencephalography EEG Epoc that reflects users emotions to improve our result with more accurate data. Our objective is to test the hypothesis whether the verbal and visual learning Styles reflect actual preferences according to Felder and Silverman Learning Style Model in an eLearning environment. Another objective is to use the outcome presented in this experiment as the starting point for further exhaustive experiments. In this paper, we present the actual state of our experiment, conclusions, and plans for future development.
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    An Extended Stable Marriage Problem Algorithm for Clone Detection
    (International Journal of Software Engineering & Applications (IJSEA), 2014) Alhakami, H.; Chen, Feng; Janicke, Helge
    Code cloning negatively affects industrial software and threatens intellectual property. This paper presents a novel approach to detecting cloned software by using a bijective matching technique. The proposed approach focuses on increasing the range of similarity measures and thus enhancing the precision of the detection. This is achieved by extending a well-known stable-marriage problem (SMP) and demonstrating how matches between code fragments of different files can be expressed. A prototype of the proposed approach is provided using a proper scenario, which shows a noticeable improvement in several features of clone detection such as scalability and accuracy.
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    Feasibility study of software reengineering towards role-based access control.
    (Inderscience Enterprises, 2011) Li, H.; Yang, Hongji; Chen, Feng; Guo, He; Yang, Yuansheng
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    Feature analysis for service-oriented reengineering
    (IEEE, 2006-03-20) Chen, Feng; Li, Shaoyun; Yang, Hongji; Wang, Ching-Huey; Chu, William Cheng-chung
    Web services together with service-oriented architectures (SOA) are playing an important role in the future of distributed computing, significantly impacting software development and evolution. With the adoption to Web services technology, more and more existing non-service-oriented software systems turn to be legacy systems. They require a service-oriented reengineering process in order to survive in service-oriented computing environment. If the reengineering goal is to expose the services of a single object or any underlying function-oriented middleware, many problems will arise including semantic mismatches, service granularity issues and state management. Attempting to masquerade software assets from a lower level of abstraction can often cause significant mismatch and exposure problems. In this paper, by using feature analysis, an approach to supporting service-oriented reengineering is presented. Service identification and packaging process are performed and resulted into a service delegation.
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    Fine-Grained Sleep-Wake Behaviour Analysis
    (IEEE, 2020-04-09) Fallmann, Sarah; Chen, Liming; Chen, Feng
    Sleep stages are traditionally assessed by experts from polysomnography measurements following specific guidelines. Sleep stage behaviour is subsequently used to detect anomalies and diagnose diseases in a laboratory setting. Recently, with the development of Internet of Things, there is a trend to use everyday technologies for sleep behaviour analysis at home, having the potential to eliminate expensive in-hospital monitoring. We propose a fine-grained sleep-wake behaviour analysis approach, which takes into consideration the influences of various factors, such as gender, health status and race. In addition, we investigate the combination of multiple data sources, in particular, actigraphy and heart rate variability, for enhancing model accuracy. Initial results show the proposed approach is recognising sleep and wake stages accurately and is providing a flexible recognition approach towards personalised sleep-based health monitoring.
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    A Formal Model Driven Approach to Dependable Software Evolution
    (IEEE, 2006-12-04) Chen, Feng; Yang, Hongji; Qiao, Bing; Chu, William Cheng-chung
    The paper proposes a unified formal model driven approach to software evolution based on both program transformation and model transformation of legacy systems. A formal model definition ensures a consistent interpretation of the legacy system and provides a theoretical foundation for dependable software evolution. The theoretical foundation is based on the construction of a wide spectrum language for reengineering, known as WSL, which enjoys a sound formal semantics. The architecture and working flow of the approach are proposed, and the mappings between WSL and PSL in MDA provide an engaging combination of traditional program transformation and modern model transformation, which shows that the proposed approach is feasible and promising in its domain. A prototype tool is developed to test the approach and a case study is used for experiments with the proposed approach and the prototype tool. Conclusion is drawn based on analysis and further research directions are also discussed
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    A Framework for Minimising Data Leakage from Non-Production Systems
    (Chapman and Hall, 2017-03-03) Cope, Jacqueline; Maglaras, Leandros; Siewe, Francois; Chen, Feng; Janicke, Helge
    There is much research and advice around de-identification techniques and data governance. This brings together the practical aspects to propose a simplified business model and framework for informed decision making for the minimisation of data leakage from non-production systems using the topology of data classification, data protection and the requirements of non-production environments. The simplified model details the influences of legal and regulatory and business requirements on business systems and non-production environments. The framework identifies six stages, and the interactions required to progress from the legal and regulatory standards applicable to political and geographical areas, through organisational requirements and business system to the purpose of the non-production environment to data treatment and protection, with a demonstration of compliance which occurs throughout each stage of the framework. A table top exercise following a hypothetical, but realistic, scenario validates the model and framework.