422 research outputs found

    Recognition of activities of daily living from topic model

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    Research in ubiquitous and pervasive technologies have made it possible to recognise activities of daily living through non-intrusive sensors. The data captured from these sensors are required to be classified using various machine learning or knowledge driven techniques to infer and recognise activities. The process of discovering the activities and activity-object patterns from the sensors tagged to objects as they are used is critical to recognising the activities. In this paper, we propose a topic model process of discovering activities and activity-object patterns from the interactions of low level state-change sensors. We also develop a recognition and segmentation algorithm to recognise activities and recognise activity boundaries. Experimental results we present validates our framework and shows it is comparable to existing approaches

    Inclusive education: pedagogical approach to online versus face-to-face teaching

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    In today’s educational landscape, active learning is often overlooked during lectures, seminars, and tutorials. The aim of this study was to investigate perceptions of online and face-to-face lecture formats and their impact on the learning experiences of undergraduate dental students in Years 3–5. This qualitative study was conducted to investigate the effectiveness of different lecture formats at the Institute of Dentistry for undergraduate dental students in Years 3–5. There were two specific questions asked to dental undergraduate students with additional free-text questions. In total, 120 of 221 undergraduate students participated in this study between October 2019 and February 2020, and only 42 participants included the free-text comments. Three core themes related to the blended learning approach were identified: (1) scheduled versus recorded lectures, (2) duration of academic lectures, and (3) neurodiversity and learning experiences. The results showed that the learners perceived the traditional didactic lectures as the least effective format. There is not a “one fits all” lecture format that would accommodate a neurodiversity-based approach that focuses on the strengths, abilities, and interests of students. Hybrid lecture formats in combination with online teaching coupled with small group tutorials could be suggested. There is a unique challenge in the post-COVID-19 era for both educators and learners due to the lack of clinical practice and heavy reliance on online methods of teaching in Dentistry. Therefore, the implication of these results on the planning and financing of programmes could be discussed in Higher Education

    Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes

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    Semantic technologies aim to represent information or models in formatsthat are not just machine-readable but also machine-understandable. To this effect, thispaper shows how the semantic concepts can be layered on top of the derived models toprovide a more contextual analysis of the models through the conceptualization method.Technically, the method involves augmentation of informative value of the resulting mod-els by semantically annotating the process elements with concepts that they represent inreal-time settings, and then linking them to an ontology in order to allow for a moreabstract analysis of the extracted logs or models. The work illustrates the method usingthe case study of a learning process domain. Consequently, the results show that a systemwhich is formally encoded with semantic labelling (annotation), semantic representation(ontology) and semantic reasoning (reasoner) has the capacity to lift the process miningand analysis from the syntactic to a more conceptual level

    A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment

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    In today’s working world the elderly are often classified as a set of dependent people and are sometimes neglected by society. One of the ways to determine whether an elderly person is safe in their home is to find out what activities an elderly person is carrying out and give appropriate assistance or institute safeguards. This paper describes the lower tier of a two tiered approach that is being adopted. The higher tier consists of hierarchical sets of plans that model common goals and sub-goals associated with activities in daily life. The lower tier deals with recognition of tasks from the stream of sensor events. Tasks are the lowest level component of a plan. The tasks are modelled using a form of hidden Markov modelling

    Activity Recognition using a Hierarchical Framework

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    This paper describes an approach for modelling and detecting activities of daily life based on a hierarchy of plans that contain a range of precedence relationships, representations of concurrency and other temporal relationships. Identification of activities of daily life is achieved by episode recovery models supported by using relationships expressed in the plans. The motivation is to allow people with Alzheimer’s disease to have additional years of independent living before the Alzheimer’s disease reaches the moderate and severe stages

    A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage

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    Being able to monitor everyday activities of daily life is seen as a key approach for mitigating functional decline among elderly people as it allows context sensitive support to be offered. This paper describes a hierarchal approach for modelling activities of daily life using task sequences generated by object usage data and a mechanism for recognising these activities from sensor data. The underlying motivation of this work is to allow people with early Alzheimer’s disease to have additional years of independent living before the disease reaches the moderate and severe stages. To ameliorate intrusion into personal privacy the monitoring of activities is via simple non-visual sensors with a greater emphasis placed on intelligent reasoning that exploits structures of typical behaviours

    Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home

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    The integration of RFID sensors into everyday products has become a widespread solution for increasing efficiency in supply chain management. This has also led to a way of being able to monitor everyday activities in the home based on when and how these products are used, which is less intrusive than other monitoring approaches such as visual based systems. Monitoring activities in a home environment can be seen as a good way of analyzing behavior and tracking functional decline among elderly people. This paper describes a hierarchal approach for activity recognition using object usage data generated by everyday products used around the home. The motivation of this work is to allow people with early Alzheimer’s disease to have additional years of independent living before the disease reaches a stage where the person is fully dependable on someone else

    Shadows of Empire: The Mughal and British Colonial Heritage of Lahore

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    The Pakistani city of Lahore is the capital of the Punjab province. The city itself has existed for over a thousand years. In 1947 the British rule in the Indian subcontinent ended, resulting in the partition of British India into the modern states of India and Pakistan. At the time the Punjab province was also partitioned, with the western half (including Lahore) going to Pakistan and the eastern half being awarded to India. Prior to partition, Lahore served as an important administrative and commercial center under the Mughal Empire (1526–1799), the Sikh Empire (1799–1849), the British East India Company (1849–1858), and the British government (1858–1947) when it took direct control of India. Several of the monuments built in and around Lahore under the Mughals, the Sikhs, and the British have survived. They are reminders of the vital role the city has played throughout the history of the Indian subcontinent. The Mughals were patrons of architecture, who left behind a rich heritage. Through an examination of select buildings, this paper will show that the Mughals built impressive structures in and around Lahore, as they did throughout the Indian subcontinent, not only for utilitarian purposes but also to impress their subjects with their power, influence, and importance. By examining a building from the Sikh–era and comparing it with the Mughal–era buildings, this paper will show how the architectural style of the Mughals lived on after their influence had ended. Like the Mughals, the British considered infrastructure essential for projection of power and maintenance of control. By examining the architecture of select buildings from the British period, this paper will demonstrate how the British combined the elements of the Mughal architectural style with European architectural elements as well as appropriated Mughal cultural symbols, in order to seek legitimacy and present themselves to the Indians as almost indigenous rulers and logical heirs to the great Mughals. Lahore’s monuments are reminders of the roles various rulers have played in the city’s history. They represent Pakistan’s equally important Mughal and British legacies. Pakistanis readily identify themselves with the Mughals because they were Muslim rulers. However, Lahore and Pakistan’s British legacy includes infrastructure, an education system, and the court system, among others. Therefore, all of Lahore’s monuments are an important part of the city’s history. They are all worth preserving

    A hybrid approach to recognising activities of daily living from object use in the home environment

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    Accurate recognition of Activities of Daily Living (ADL) plays an important role in providing assistance and support to the elderly and cognitively impaired. Current knowledge-driven and ontology-based techniques model object concepts from assumptions and everyday common knowledge of object use for routine activities. Modelling activities from such information can lead to incorrect recognition of particular routine activities resulting in possible failure to detect abnormal activity trends. In cases where such prior knowledge are not available, such techniques become virtually unemployable. A significant step in the recognition of activities is the accurate discovery of the object usage for specific routine activities. This paper presents a hybrid framework for automatic consumption of sensor data and associating object usage to routine activities using Latent Dirichlet Allocation (LDA) topic modelling. This process enables the recognition of simple activities of daily living from object usage and interactions in the home environment. The evaluation of the proposed framework on the Kasteren and Ordonez datasets show that it yields better results compared to existing techniques

    Improving Student Engagement and Performance in Computing Final Year Projects

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    There has been a seismic shift in the UK higher education landscape during the last decade. This has been driven by the formation of the Office for Students (OfS) and the introduction of the Teaching Excellence Framework (TEF), where the emphasis has been on programmes offering students higher value when it comes to employability, retention and overall student experience. One of the critical challenges that impact student experience is being able to enhance student engagementwithin a learning environment. Final year individual projects, which are generally unstructured in nature, is a significant contributor to programmes of study, yet remains an area where this problem is exacerbated. In an attempt to address this issue, our earlier work lays the foundation for a teaching & learning framework covering computing final year projects. In this paper, we present an extension to the framework and its implementation in 2016/17 following its first trial run within a Computer Science department at a UK university in 2015/16. We discuss the two implementations in practice and provide operational guidance. A large-scale longitudinal empirical study considering the performance of 625 final year undergraduate students over a period of five years is presented to ascertain the effectiveness of the framework. The study finds a consistent and significant positive impact on both student performance and engagement as a result of the original framework and further gains from the enhancements
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