RESULTS: Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.
CONCLUSIONS: Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.
RESULTS: The relationship between dimensionless moisture content and shrinkage of sweet potato in terms of volume, surface area, perimeter and illuminated area was found to be linearly correlated. The results also demonstrated that the shrinkage of sweet potato based on computer vision and backscattered optical parameters is affected by the product thickness, drying temperature and drying time. A multilayer perceptron (MLP) artificial neural network with input layer containing three cells, two hidden layers (18 neurons), and five cells for output layer, was used to develop a model that can monitor, control and predict the shrinkage parameters and moisture content of sweet potato slices under different drying conditions. The developed ANN model satisfactorily predicted the shrinkage and dimensionless moisture content of sweet potato with correlation coefficient greater than 0.95.
CONCLUSION: Combined computer vision, laser light backscattering imaging and artificial neural network can be used as a non-destructive, rapid and easily adaptable technique for in-line monitoring, predicting and controlling the shrinkage and moisture changes of food and agricultural crops during drying. © 2017 Society of Chemical Industry.
OBJECTIVE: This study aimed to determine self-monitoring practices, awareness to dietary modifications and barriers to medication adherence among physically disabled type 2 diabetes mellitus patients.
METHODS: Interview sessions were conducted at diabetes clinic - Penang general hospital. The invited participants represented three major ethnic groups of Malaysia (Malay, Chinese & Indians). An openended approach was used to elicit answers from participants. Interview questions were related to participant's perception towards self-monitoring blood glucose practices, Awareness towards diet management, behaviour to diabetes medication and cues of action.
RESULTS: A total of twenty-one diabetes patients between the ages 35 - 67 years with physical disability (P1-P21) were interviewed. The cohort of participants was dominated by Males (n=12) and also distribution pattern showed that majority of participants were Malay (n=10), followed by Chinese (n=7) and rest Indians (n=4). When the participants were asked in their opinion what was the preferred method of recording blood glucose tests, several participants from low socioeconomic status and either divorced or widowed denied to adapt telemontoring instead preferred to record manually. There were mixed responses about the barriers to control diet/calories. Even patients with high economic status, middle age 35-50 and diabetes history of 5-10 years were influenced towards alternative treatments.
CONCLUSION: Study concluded that patients with physical disability required extensive care and effective strategies to control glucose metabolism.
Method: This study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation.
Results: A visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation.
Discussion: The relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.
Methods: This open label comparative design study randomized health professional clinicians to receive "practice points" on tendinopathy management via Twitter or Facebook. Evaluated outcomes included knowledge change and self-reported changes to clinical practice.
Results: Four hundred and ninety-four participants were randomized to 1 of 2 groups and 317 responders analyzed. Both groups demonstrated improvements in knowledge and reported changes to clinical practice. There was no statistical difference between groups for the outcomes of knowledge change (P = .728), changes to clinical practice (P = .11) or the increased use of research information (P = .89). Practice points were shared more by the Twitter group (P