A geometrical-based approach to recognise structure of complex interiors

3D modelling of building interiors has gained a lot of interest recently, specifically since the rise of Building Information Modeling (BIM). A number of methods have been developed in the past, however most of them are limited to modelling non-complex interiors. 3D laser scanners are the preferred sensor to collect the 3D data, however the cost of state-of-the-art laser scanners are prohibitive to many. Other types of sensors could also be used to generate the 3D data but they have limitations especially when dealing with clutter and occlusions. This research has developed a platform to produce 3D modelling of building interiors while adapting a low-cost, low-level laser scanner to generate the 3D interior data. The PreSuRe algorithm developed here, which introduces a new pipeline in modelling building interiors, combines both novel methods and adapts existing approaches to produce the 3D modelling of various interiors, from sparse room to complex interiors with non-ideal geometrical structure, highly cluttered and occluded. This approach has successfully reconstructed the structure of interiors, with above 96% accuracy, even with high amount of noise data and clutter. The time taken to produce the resulting model is almost real-time, compared to existing techniques which may take hours to generate the reconstruction. The produced model is also equipped with semantic information which differentiates the model from a regular 3D CAD drawing and can be use to assist professionals and experts in related fields

Experiences and perceptions of nursing staff working with long-stay patients in a high secure psychiatric hospital setting

Background and Objective: Forensic psychiatric nursing is a demanding nursing specialty that deals with a highly complex group of patients who are detained in restrictive environments, often for lengthy periods. There is little information about the daily experiences of these nurses. This study sought to explore the roles and relationships of forensic psychiatric nurses with long-stay patients in a high secure hospital in England. Method and Analysis: The study obtained data via three focus groups, and thematic analysis was carried out using NVIVO 10 software. Results: Five prominent themes emerged: First, nurses elaborated on their roles with patients and the kinds of interactions they had with them. The next two themes explored the reasons why some patients are long-stay patients and the challenges nurses face while working with this group. The fourth theme was the impact of external support, such as the patient’s families, on length of stay. The final theme covered the changes that the nurses observed in these patients and in themselves over time. Conclusion: It was noticeable that those interviewed were committed professionals, eager to provide an optimistic and hopeful environment for the patients to help them progress through “the system”. The study presents a number of pertinent issues regarding long-stay patients that provide a basis for further research and to inform policy, educational reforms, and clinical practice

Integrating the use of sensing technology to detect early warning signs of relapse for those with lived experience of bipolar disorder

In the world of pervasive mobile technology, it is inevitable that novel technological solutions have been leveraged to understand symptoms of bipolar disorder (BD). Increasingly, these technologies use a combination of passive and active sensing techniques. BD is a complex condition where the sense of self is consistently in “flux”. There are questions of how much this sense of self is currently reflected in self-tracking technology for BD. Upon investigating this, we found that user involvement in self-tracking technology is variable, where high-level involvement is seldom seen in the literature. Furthermore, this technology is being developed without reference to clinical guidelines, best practice principles and with a lack of high-quality research evidence. Using a combination of participatory design methods from healthcare and human-computer interaction, the overall aim of this doctoral research is to bring the user’s personal and lived experience of BD to the forefront in order to design and assess a mobile self-tracking tool which uses passive and active sensing techniques to understand early warning signs (EWS) in BD – a clinically validated framework in understanding relapse. The research was organised into three work packages: Concept Generation and Ideation, Prototype Design and Deployment and Evaluation. In the first work package, the everyday practices of self-tracking were explored in two user-led workshops (n=18 users). The findings revealed a high degree of complexity and individual variability in self-tracking where over 50 methods of tracking were described. In the next phase, the findings were built upon using follow-up interviews (n=10) to guide the redesign of a self-tracking tool to be closely aligned to users’ needs and preferences. During the Evaluation phase, the final prototype was enrolled for a 6-month beta test in a real-world context with eight users. The findings revealed that the tool was useful in understanding EWS from both a subjective (i.e., user led) and statistical viewpoint. Frequencies in the passive data were connected to EWS via the active data, however, there were inconsistencies in how users interpreted the data compared to our statistical analysis - proving that “no one size fits all” in technology for BD. Overall, the tool was demonstrated good usability and acceptability from users, with constructive suggestions for improvement

Integrating the use of sensing technology to detect early warning signs of relapse for those with lived experience of bipolar disorder

In the world of pervasive mobile technology, it is inevitable that novel technological solutions have been leveraged to understand symptoms of bipolar disorder (BD). Increasingly, these technologies use a combination of passive and active sensing techniques. BD is a complex condition where the sense of self is consistently in “flux”. There are questions of how much this sense of self is currently reflected in self-tracking technology for BD. Upon investigating this, we found that user involvement in self-tracking technology is variable, where high-level involvement is seldom seen in the literature. Furthermore, this technology is being developed without reference to clinical guidelines, best practice principles and with a lack of high-quality research evidence. Using a combination of participatory design methods from healthcare and human-computer interaction, the overall aim of this doctoral research is to bring the user’s personal and lived experience of BD to the forefront in order to design and assess a mobile self-tracking tool which uses passive and active sensing techniques to understand early warning signs (EWS) in BD – a clinically validated framework in understanding relapse. The research was organised into three work packages: Concept Generation and Ideation, Prototype Design and Deployment and Evaluation. In the first work package, the everyday practices of self-tracking were explored in two user-led workshops (n=18 users). The findings revealed a high degree of complexity and individual variability in self-tracking where over 50 methods of tracking were described. In the next phase, the findings were built upon using follow-up interviews (n=10) to guide the redesign of a self-tracking tool to be closely aligned to users’ needs and preferences. During the Evaluation phase, the final prototype was enrolled for a 6-month beta test in a real-world context with eight users. The findings revealed that the tool was useful in understanding EWS from both a subjective (i.e., user led) and statistical viewpoint. Frequencies in the passive data were connected to EWS via the active data, however, there were inconsistencies in how users interpreted the data compared to our statistical analysis - proving that “no one size fits all” in technology for BD. Overall, the tool was demonstrated good usability and acceptability from users, with constructive suggestions for improvement

Property tax assessment incentive model for green building initiative in Malaysia

The practice of providing property tax assessment incentives for green buildings has been proven to encourage the growth of green building practices at a local level. However, the property tax assessment incentive available for green buildings in Malaysia is developed without property tax assessment basis and requires large financial expenditure from the local authority. Therefore, this scenario exhibits the incentive only relevant for local authority with strong financial budget. As a result it creates an issue for those unwilling nor do they have large financial budget to spend on the incentive program. This study aims to address the issue by developing a model of property tax assessment incentive based on improved value excluding financial expenditure from the local authority. There are three objectives outlined in this study: 1) to determine green envelope components of green building certified under Malaysian Green Building Index (GBI) rating tool: 2) to analyse the effect of the determined green envelope component on property value; and 3) to develop and validate property tax assessment incentive models for green building. The GBI certified green envelope components were determined through integrating the green benefits of identified green envelope components with GBI green criteria using meta-analysis. The sampling focuses on Malaysian property valuation practitioners with green building valuation experiences. This study comprises quantitative data involving questionnaire survey to 550 property valuation practitioners in Malaysia. The collected data were analysed using frequency analysis. The Cost-Benefits analysis between property tax assessment increment and annual energy saving conveyed by green envelope components on building was conducted to determine the appropriate baseline for percentage of reduction for the proposed incentive models. The developed models were validated through semi-structured interview with the Director of Valuation Department at Kulai Municipal Council. The findings demonstrate that out of ten green envelope components affecting property value, three green envelope components were found to increase property value, namely: solar photovoltaic, green roof and green living wall. Two property tax assessment incentive models developed are: 1) exemption model and 2) reduction model. The results indicate that the reduction baseline for solar photovoltaic, green roof and green living starts from 25%, 0% and 0% respectively. Kulai Municipal Council is willing to provide 50% reduction for each green envelope component.Through a proposed exemption model, the local authority and taxpayer do not experience any changes on their existing tax. However, through a reduction model, the local authority does experience around RM 18 to RM 40 minimum tax increment on their existing tax revenue. Meanwhile, for the taxpayer, the annual energy saving conveyed by the green envelope components is able to compensate the amount of tax increment

Somatotype and Cardiovascular Diseases Risk Factors Among Government Employees In Kuala Terengganu, Malaysia

Aim: This cross-sectional study was conducted to determine the body somatotype and risk factors for cardiovascular diseases among government employees from Kuala Terengganu, Malaysia. Methods: In this research, 308 government employees were recruited as respondents. Body somatotype was determined using the Heath and Carter (1990) method. The risk factors for cardiovascular diseases were determined by measuring fasting blood glucose, total cholesterol (TC), LDL-cholesterol level, HDL cholesterol level and triglycerides level. Results: Majority of the respondents were categorized as endomorphy (84.7%), followed by mesomorphy (11.7%) and ectomorphy (3.6%). Means of fasting blood cholesterol level, triglycerides, HDL and LDL cholesterol among respondents were 5.57 mmol/L, 1.55 mmol/L, 1.25 mmol/L and 3.63 mmol/L, respectively. The fasting blood glucose of respondents was in the normal range (5.02 mmol/L), while cholesterol, triglycerides and LDL cholesterol were on borderline high. Mean HDL level of respondents were below desirable level. Conclusion: We found that there were significant correlation between ectomorphy components with blood cholesterol, LDL, HDL and blood glucose level; mesomorphy with LDL cholesterol level; and endomorphy with HDL and blood glucose level among respondents (p<0.05). As a conclusion, this study has provided useful insights towards the relationship between somatotype components and risk factors of cardiovascular diseases.Objetivo: este estudio transversal se realizó para determinar el somatotipo corporal y los factores de riesgo de enfermedades cardiovasculares entre empleados gubernamentales de Kuala Terengganu, Malasia. Métodos: En esta investigación, se reclutó como encuestados a 308 empleados del gobierno. El somatotipo corporal se determinó mediante el método de Heath y Carter (1990). Los factores de riesgo de enfermedades cardiovasculares se determinaron midiendo la glucosa en sangre en ayunas, el colesterol total (CT), el nivel de colesterol LDL, el nivel de colesterol HDL y el nivel de triglicéridos. Resultados: La mayoría de los encuestados fueron categorizados como endomorfia (84,7%), seguida de mesomorfia (11,7%) y ectomorfia (3,6%). Las medias del nivel de colesterol en sangre en ayunas, triglicéridos, colesterol HDL y LDL entre los encuestados fueron 5,57 mmol / L, 1,55 mmol / L, 1,25 mmol / L y 3,63 mmol / L, respectivamente. La glucosa en sangre en ayunas de los encuestados estaba en el rango normal (5,02 mmol / L), mientras que el colesterol, los triglicéridos y el colesterol LDL estaban en el límite alto. El nivel medio de HDL de los encuestados estaba por debajo del nivel deseable. Conclusión: Encontramos que existe una correlación significativa entre los componentes de la ectomorfia con el colesterol en sangre, LDL, HDL y nivel de glucosa en sangre; mesomorfia con nivel de colesterol LDL; y endomorfia con HDL y nivel de glucosa en sangre entre los encuestados (p <0,05). Como conclusión, este estudio ha proporcionado información útil sobre la relación entre los componentes del somatotipo y los factores de riesgo de las enfermedades cardiovasculares

Smart thermal comfort system: a development of the fundamental control algorithm

This paper reports on the development of the fundamental algorithm for a smart thermal comfort system. Using Predictive Mean Vote (PMV) as a means of measuring thermal comfort, this system would able the user to define their own expression towards the surroundings, from slightly warm to slightly cold. Here, the operator only needs to insert its respective value ofPMV (ranging from -1 to + 1) and the system will generate the compressor and fan of the air conditioning system so that it will create a thermally comfortable environment, based on the operator's desires. This differentiates the system with the conventional air conditioning system where the operator needs to set separately fan speed and degree of cooling. The PMV value here will be calculated as input instead of the normal PMV equation where these values depend on the air temperature, relative humidity and air velocity. All these parameters values are set from the standard range allowed by the ISO 7730 of thermal comfort at a workplace for sedentary activity. Since previous researches use PMV as the output value, the help of Microsoft Excel is used to obtain air temperature and air velocity for respective values ofPMV. Finally, the fundamental stage for experimentation step is implemented by building a working region in allowing the PID (Proportional, Integrative, Derivative) controller to control its duty cycle

The gender responsiveness of social entrepreneurship in health - A review of initiatives by Ashoka fellows.

There are vocal calls to act on the gender-related barriers and inequities in global health. Still, there are gaps in implementing programmes that address and counter the relevant dynamics. As an approach that focuses on social problems and public service delivery gaps, social entrepreneurship has the potential to be a closer health sector partner to tackle and transform the influence of gender in health to achieve health systems goals better. Nevertheless, social entrepreneurs' engagement and impact on gender and health remain understudied. Using the Ashoka Fellows database as a sampling frame in November 2020 (n = 3352, health n = 129), we identified and reviewed the work of 21 organizations that implemented gender-responsive health-related programmes between 2000 and 2020. We applied the UNU-IIGH 6-I Analytic Framework to review the gender issues, interventions, included populations, investments, implementation, and impact in each organization. We found that a low proportion of fellows engage in gender-responsive health programming (<1%). Many organizations operate in low-and middle-income countries (16/21). The gender-responsive programmes include established health sector practices, to address gendered-cultural dynamics and deliver people-centred resources and services. Interestingly, most organizations self-identify as NGOs and rely on traditional grant funding. Fewer organizations (6/21) adopt market-based and income-generating solutions - a missed opportunity to actualise the potential of social entrepreneurship as an innovative health financing approach. There were few publicly available impact evaluations-a gap in practice established in social entrepreneurship. All organizations implemented programmes at community levels, with some cross-sectoral, structural, and policy-level initiatives. Most focused on sexual and reproductive health and gender-based violence for predominantly populations of women and girls. Closer partnerships between social entrepreneurs and gender experts in the health sector can provide reciprocally beneficial solutions for cross-sectorally and community designed innovations, health financing, evidence generation and impact tracking that improve the gender-responsiveness of health programmes, policies, and systems

Body somatotype and dietary intakes of government employees in Kuala Terengganu

Nutritional intake is one of the most important aspects that influence body composition and may affect body somatotype. Some previous studies conducted on somatotype in Malaysia have focussed on the aspect of sport performance and physical activities but none were on somatotype with dietary intakes. Thus, this study was conducted to determine the relationship between somatotype and dietary intakes. A total of 308 males and females of uniformed government agencies personnel in Kuala Terengganu were systematically selected to participate into this study. Somatotype was determined by using the Heath and Carter, method. Dietary intakes were measured by using 24-hour dietary recall technique. The mean age of respondents was 38.18 ± 5.23 years. Their mean BMI was 26.09 ± 5.69 kg/m2, which indicated that they were overweight. Mean somatotype components of the male respondents were (5.71, 4.73, 1.20), while of female respondents were (8.77, 4.99, 0.77). This indicated that the males belonged to mesomorph-endomorph body somatotype while the females belonged to mesomorph endomorph somatotype category. Median calories intake among respondents was 1987 kcal per day. The correlation between endomorphy component with calories, carbohydrate and protein intake were r= -0.083, r= -0.172 and r= -0.226, respectively (p<0.05). Mesomorphy component correlated negatively with protein intake of respondents (r= -0.161, p<0.05). The ectomorphy component correlated positively with calories (r= 0.151, p<0.05), carbohydrate (r= 0.113, p<0.05), protein (r= 0.191, p<0.05) and fat intake (r=0.112, p<0.05). Some vitamins and minerals intake also shows correlation with somatotype components. Generally, this study suggested that dietary intakes influence somatotype components and somatotype measurements can be useful to be used as tools for identifying obesity predispositions