ORCID Profile
0000-0003-1853-4978
Current Organisation
Aurecon
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Publisher: Association for Computing Machinery (ACM)
Date: 27-11-2018
DOI: 10.1145/3217214
Abstract: Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - Human Occupancy Counter Plus Plus (DA-HOC++), a robust way to estimate the number of people within one room by using data from a carbon dioxide sensor. In our previous work, the proposed Seasonal Decomposition for Human Occupancy Counting (SD-HOC) model can accurately predict the number of in iduals when the training and labelled data are adequately available. DA-HOC++ is able to predict the number of occupants with minimal training data: as little as 1 day’s data. DA-HOC++ accurately predicts indoor human occupancy for five different rooms across different countries using a model trained from a small room and adapted to other rooms. We evaluate DA-HOC++ with two baseline methods: a support vector regression technique and an SD-HOC model. The results demonstrate that DA-HOC++’s performance on average is better by 10.87% in comparison to SVR and 8.65% in comparison to SD-HOC.
Publisher: ACM
Date: 14-02-2022
Publisher: Elsevier BV
Date: 06-2018
Publisher: JMIR Publications Inc.
Date: 21-06-2021
DOI: 10.2196/25522
Abstract: Hypertension affects over 15% of the world’s population and is a significant global public health and socioeconomic challenge. Mobile health (mHealth) services have been increasingly introduced to support hypertensive patients to improve their self-management behaviors, such as adherence to pharmacotherapy and lifestyle modifications. This study aims to explore patients’ perceptions of mHealth services and the mechanisms by which the services support them to self-manage their hypertension. A semistructured, in-depth interview study was conducted with 22 outpatients of the General Hospital of Ningxia Medical University from March to May 2019. In 2015, the hospital introduced an mHealth service to support community-dwelling outpatients with self-management of hypertension. Content analysis was conducted by following a grounded theory approach for inductive thematic extraction. Constant comparison and categorization classified the first-level codes with similar meanings into higher-level themes. The patient-perceived mechanisms by which the mHealth service supported their self-management of hypertension were summarized as 6A: access, assessment, assistance, awareness, ability, and activation. With the portability of mobile phones and digitization of information, the mHealth service provided outpatients with easy access to assess their vital signs and self-management behaviors. The assessment results gave the patients real-time awareness of their health conditions and self-management performance, which activated their self-management behaviors. The mHealth service also gave outpatients access to assistance, which included health education and self-management reminders. Both types of assistance could also be activated by abnormal assessment results, that is, uncontrolled or deteriorating blood pressure values, discomfort symptoms, or not using the service for a long period. With its scalable use to handle any possible information and services, the mHealth service provided outpatients with educational materials to learn at their own pace. This led to an improvement in self-management awareness and ability, again activating their self-management behaviors. The patients would like to see further improvements in the service to provide more useful, personalized information and reliable services. The mHealth service extended the traditional hypertension care model beyond the hospital and clinician’s office. It provided outpatients with easy access to otherwise inaccessible hypertension management services. This led to process improvement for outpatients to access health assessment and health care assistance and improved their awareness and self-management ability, which activated their hypertension self-management behaviors. Future studies can apply the 6A framework to guide the design, implementation, and evaluation of mHealth services for outpatients to self-manage chronic conditions.
Publisher: SLACK, Inc.
Date: 04-2022
DOI: 10.3928/00989134-20220309-01
Abstract: Using a suite of artificial intelligence technologies, the current study sought to determine the prevalence of agitated behaviors in people with dementia in residential aged care facilities (RACFs) in Australia. Computerized natural language processing allowed extraction of agitation instances from the free-text nursing progress notes, a component of electronic health records in RACFs. In total, 59 observable agitated behaviors were found. No difference was found in dementia prevalence between female and male clients (44.1%), across metropolitan and regional facilities (42.1% [ SD = 17.9%]), or for agitation prevalence in dementia (76.5% [ SD = 18.4%]). The top 10 behaviors were resisting, wandering, speaking in excessively loud voice, pacing, restlessness, pushing, shouting, complaining, frustration, and using profane language. Four to 17 agitated behaviors coexisted in 53% of people with dementia agitation, indicating high caregiver burden in these RACFs. Improving workforce training and redesigning care models are urgent for sustainability of dementia care in RACFs. [ Journal of Gerontological Nursing, 48 (4), 57–64.]
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AH13161
Abstract: Objective To examine the time, frequency and duration of each direct care activity conducted by personal carers in Australian residential aged care homes. Methods A time–motion study was conducted to observe 46 personal carers at two high-care houses in two facilities (14 days at Site 1 and 16 days at Site 2). Twenty-three direct care activities were classified into eight categories for analysis. Results Overall, a personal carer spent approximately 45% of their time on direct care, corresponding to 3.5 h in an 8-h daytime shift. The two sites had similar ratios of personal carers to residents, and each resident received 30 min of direct care. No significant differences between the two sites were found in the time spent on oral communication, personal hygiene and continence activities. Personal carers at Site 1 spent significantly less time on toileting and mobility activities than those at Site 2, but more time on lunch activity. Although oral communication took the longest time (2 h), it occurred concurrently with other activities (e.g. dressing) for 1.5 h. Conclusions The findings provide information that may assist decision makers in managing the operation of high-care residential aged care facilities, such as planning for task allocation and staffing. What is known about the topic? Overall, 30%–45% of the care staff’s time is spent on direct care in residential aged care facilities. What does this paper add? This paper adds knowledge about how much time is required to conduct each direct care activity and the frequency and duration of conducting these activities to meet residents’ day-to-day care needs in two high-care houses in two aged care facilities. What are the implications for practitioners? On average, a resident with high-care needs requires 30 min direct care. There may exist a basic minimum desirable ratio of personal carers to residents in high-care facilities. Residents’ toileting needs are high after meals. Communication with residents represents an essential role in providing care.
Publisher: Springer Science and Business Media LLC
Date: 06-09-2012
Abstract: The aim of the study is to describe the work pattern of personal care workers (PCWs) in nursing homes. This knowledge is important for staff performance appraisal, task allocation and scheduling. It will also support funding allocation based on activities. A time-motion study was conducted in 2010 at two Australian nursing homes. The observation at Site 1 was between the hours of 7:00 and 14:00 or 15:00 for 14 days. One PCW was observed on each day. The observation at Site 2 was from 10:00 to 17:00 for 16 days. One PCW working on a morning shift and another one working on an afternoon shift were observed on each day. Fifty-eight work activities done by PCWs were grouped into eight categories. Activity time, frequency, duration and the switch between two consecutive activities were used as measurements to describe the work pattern. Personal care workers spent about 70.0% of their time on four types of activities consistently at both sites: direct care (30.7%), indirect care (17.6%), infection control (6.4%) and staff break (15.2%). Oral communication was the most frequently observed activity. It could occur independently or concurrently with other activities. At Site 2, PCWs spent significantly more time than their counterparts at Site 1 on oral communication (Site 1: 47.3% vs. Site 2: 63.5%, P = 0.003), transit (Site 1: 3.4% vs. Site 2: 5.5%, P 0.001) and others (Site 1: 0.5% vs. Site 2: 1.8%, P 0.001). They spent less time on documentation (Site 1: 4.1% vs. Site 2: 2.3%, P 0.001). More than two-thirds of the observed activities had a very short duration (1 minute or less). Personal care workers frequently switched within or between oral communication, direct and indirect care activities. At both nursing homes, direct care, indirect care, infection control and staff break occupied the major part of a PCW’s work, however oral communication was the most time consuming activity. Personal care workers frequently switched between activities, suggesting that looking after the elderly in nursing homes is a busy and demanding job.
Publisher: Wiley
Date: 2020
DOI: 10.1002/TRC2.12061
Abstract: A large volume of clinical care data has been generated for managing agitation in dementia. However, the valuable information in these data has not been used effectively to generate insights for improving the quality of care. Application of artificial intelligence technologies offers us enormous opportunities to reuse these data. For health data science to achieve this, this study focuses on using ontology to coding clinical knowledge for non‐pharmacological treatment of agitation in a machine‐readable format. The resultant ontology—Dementia‐Related Agitation Non‐Pharmacological Treatment Ontology (DRANPTO)—was developed using a method adopted from the NeOn methodology. DRANPTO consisted of 569 concepts and 48 object properties. It meets the standards for biomedical ontology. DRANPTO is the first comprehensive semantic representation of non‐pharmacological management for agitation in dementia in the long‐term care setting. As a knowledge base, it will play a vital role to facilitate the development of intelligent systems for managing agitation in dementia.
Publisher: SLACK, Inc.
Date: 04-2022
DOI: 10.3928/00989134-20220308-02
Abstract: Applying person-centered, nonpharmacological interventions to manage psychotic symptoms of dementia is promoted for health care professionals, particularly gerontological nurses, who are responsible for care of older adults in nursing homes. A knowledge graph is a graph consisting of a set of concepts that are linked together by their interrelationship and has been widely used as a formal representation of domain knowledge in health. However, there is lack of a knowledge graph for nonpharmacological treatment of psychotic symptoms in dementia. Therefore, we developed a comprehensive, human- and machine-understandable knowledge graph for this domain, named Dementia-Related Psychotic Symptom Nonpharmacological Treatment Ontology (DRPSNPTO). This graph was built by adopting the established NeOn methodology, a knowledge graph engineering method, to meet the quality standards for biomedical knowledge graphs. This intuitive graph representation of the domain knowledge sets a new direction for visualizing and computerizing gerontological knowledge to facilitate human comprehension and build intelligent aged care information systems. [ Journal of Gerontological Nursing, 48 (4), 49–55.]
Publisher: University of New England, Armidale
Date: 12-2021
DOI: 10.14742/ASCILITE2021.0128
Abstract: There has been a steady increase in international students pursuing postgraduate coursework education in English speaking countries. Like first-year undergraduate students, these international students need assistance transitioning into the new educational environment and preparing for self-directed, collaborative learning throughout their careers. Drawing on the social constructivist pedagogical approaches, we developed learning tasks that foster self-regulation and collaboration among postgraduate coursework IT students, aligning these tasks with the learning outcomes of the subject Information Design and Content Management. This paper presents the rationale and method for the design of the learning tasks, and how these learning tasks to not only align with the subject learning outcomes but also facilitate self-regulation. A study involving preand post-subject surveys and interviews with 133 subject students will provide us with further insights into the effectiveness of the learning task design and the areas for improvement.
Publisher: IEEE
Date: 03-2016
Publisher: JMIR Publications Inc.
Date: 05-11-2020
Abstract: ypertension affects over 15% of the world’s population and is a significant global public health and socioeconomic challenge. Mobile health (mHealth) services have been increasingly introduced to support hypertensive patients to improve their self-management behaviors, such as adherence to pharmacotherapy and lifestyle modifications. his study aims to explore patients’ perceptions of mHealth services and the mechanisms by which the services support them to self-manage their hypertension. semistructured, in-depth interview study was conducted with 22 outpatients of the General Hospital of Ningxia Medical University from March to May 2019. In 2015, the hospital introduced an mHealth service to support community-dwelling outpatients with self-management of hypertension. Content analysis was conducted by following a grounded theory approach for inductive thematic extraction. Constant comparison and categorization classified the first-level codes with similar meanings into higher-level themes. he patient-perceived mechanisms by which the mHealth service supported their self-management of hypertension were summarized as 6A: access, assessment, assistance, awareness, ability, and activation. With the portability of mobile phones and digitization of information, the mHealth service provided outpatients with easy access to assess their vital signs and self-management behaviors. The assessment results gave the patients real-time awareness of their health conditions and self-management performance, which activated their self-management behaviors. The mHealth service also gave outpatients access to assistance, which included health education and self-management reminders. Both types of assistance could also be activated by abnormal assessment results, that is, uncontrolled or deteriorating blood pressure values, discomfort symptoms, or not using the service for a long period. With its scalable use to handle any possible information and services, the mHealth service provided outpatients with educational materials to learn at their own pace. This led to an improvement in self-management awareness and ability, again activating their self-management behaviors. The patients would like to see further improvements in the service to provide more useful, personalized information and reliable services. he mHealth service extended the traditional hypertension care model beyond the hospital and clinician’s office. It provided outpatients with easy access to otherwise inaccessible hypertension management services. This led to process improvement for outpatients to access health assessment and health care assistance and improved their awareness and self-management ability, which activated their hypertension self-management behaviors. Future studies can apply the 6A framework to guide the design, implementation, and evaluation of mHealth services for outpatients to self-manage chronic conditions.
Publisher: Springer Singapore
Date: 2018
Publisher: Elsevier BV
Date: 12-2018
Publisher: ACM
Date: 08-11-2017
Publisher: Springer International Publishing
Date: 2019
Location: No location found
Location: Taiwan, Province of China
No related grants have been discovered for Zhenyu Zhang.