mCAT: Development of a Generic mHealth Tool for Continuous Assessment, Automatic Intervention, and Analysis

Use of mobile health (mHealth) technology for behavioral and psychological studies through continuous assessment and intervention is found to be effective. Also, the use of smartphone has increased rapidly last few years, as well as its uses for health support. mHealth research is applied for smoking cessation, motivating cancer survivors and mentoring peers for social engagement. While in most settings researchers are developing their own intervention and assessment tool for each different research. In this study mHealth research is applied and generalized across a range of applications, including smoking cessation, motivating cancer survivors and mentoring peers to improve social engagement. Here at Ubicomp Lab, Marquette University we have developed similar tool – Mobile peer-mentoring: An approach to making veterans seek mental health care support a normality, and Walking Forward for Physical Activity: The mHealth Tool for Motivating Cancer Survivors. This study analyzed these research, and proposed a design and implemented it as a generic mHealth tool, named mCAT (Mobile Continuous Assessment Tool). We also have shown the complexity to design challenges to develop an effective smartphone application that meets user expectation. The goal of this generic mHealth tool is to help future research designed for continuous assessment and intervention. This tool provides the initial building block as modules, customizable features, and API to start with the actual implementation. mCAT expects to be cost effective, easily customizable, leverage learning curve on the open standard

COMPARATIVE ADSORPTION STUDY ON RICE HUSK AND RICE HUSK ASH BY USING AMARANTHUS GANGETICUS PIGMENTS AS DYE

Low cost adsorbents such as Rice Husk (RH) and Rice Husk Ash (RHA) were used for removing dyes from aqueous medium and later Linear, Langmuir and Freundlich adsorption isotherms have been verified by using adsorption data. RH was activated by treating with nitric acid and RHA was prepared from RH by dolomite process. Natural dyes were extracted from the vegetable Amaranthus gangeticus by using a standard method. The removal efficiency of adsorbents was measured for the variation of parameters pH, contact time and adsorbents concentration. It has been noted that after changing time for same amount of adsorbent (1g/100ml) and dyes (10 ml) RH gave no efficiency trend but increased to 43.91% whereas for RHA efficiency was gradually increased to 59.62%. A reverse trend was noted when adsorption amounts were changed and others were put constant where RHA efficiency gradually increased to 99.30% but RH gave no trend with highest efficiency was close to 61.85%. The RH removal efficiency was good for pH 11 close to 62.86% and it was continuous from 3.95% at pH 2. Alternately, RHA gave 80.21% at pH 2 and later was decreased to 1.5% at pH 9 and again increased from pH 11. It is noted that RHA removal efficiency is better than RH and adsorptions are well fitted with isotherms

COMPARATIVE ADSORPTION STUDY ON RICE HUSK AND RICE HUSK ASH BY USING AMARANTHUS GANGETICUS PIGMENTS AS DYE

Low cost adsorbents such as Rice Husk (RH) and Rice Husk Ash (RHA) were used for removing dyes from aqueous medium and later Linear, Langmuir and Freundlich adsorption isotherms have been verified by using adsorption data. RH was activated by treating with nitric acid and RHA was prepared from RH by dolomite process. Natural dyes were extracted from the vegetable Amaranthus gangeticus by using a standard method. The removal efficiency of adsorbents was measured for the variation of parameters pH, contact time and adsorbents concentration. It has been noted that after changing time for same amount of adsorbent (1g/100ml) and dyes (10 ml) RH gave no efficiency trend but increased to 43.91% whereas for RHA efficiency was gradually increased to 59.62%. A reverse trend was noted when adsorption amounts were changed and others were put constant where RHA efficiency gradually increased to 99.30% but RH gave no trend with highest efficiency was close to 61.85%. The RH removal efficiency was good for pH 11 close to 62.86% and it was continuous from 3.95% at pH 2. Alternately, RHA gave 80.21% at pH 2 and later was decreased to 1.5% at pH 9 and again increased from pH 11. It is noted that RHA removal efficiency is better than RH and adsorptions are well fitted with isotherms

PARMA-CC: Parallel Multiphase Approximate Cluster Combining

Clustering is a common component in data analysis applications. Despite the extensive literature, the continuously increasing volumes of data produced by sensors (e.g. rates of several MB/s by 3D scanners such as LIDAR sensors), and the time-sensitivity of the applications leveraging the clustering outcomes (e.g. detecting critical situations, that are known to be accuracy-dependent), demand for novel approaches that respond faster while coping with large data sets. The latter is the challenge we address in this paper. We propose an algorithm, PARMA-CC, that complements existing density-based and distance-based clustering methods. PARMA-CC is based on approximate, data parallel cluster combining, where parallel threads can compute summaries of clusters of data (sub)sets and, through combining, together construct a comprehensive summary of the sets of clusters. By approximating clusters with their respective geometrical summaries, our technique scales well with increased data volumes, and, by computing and efficiently combining the summaries in parallel, it enables latency improvements. PARMA-CC combines the summaries using special data structures that enable parallelism through in-place data processing. As we show in our analysis and evaluation, PARMA-CC can complement and outperform well-established methods, with significantly better scalability, while still providing highly accurate results in a variety of data sets, even with skewed data distributions, which cause the traditional approaches to exhibit their worst-case behaviour. In the paper we also describe how PARMA-CC can facilitate time-critical applications through appropriate use of the summaries

Indoor location identification technologies for real-time IoT-based applications: an inclusive survey

YesThe advent of the Internet of Things has witnessed tremendous success in the application of wireless sensor networks and ubiquitous computing for diverse smart-based applications. The developed systems operate under different technologies using different methods to achieve their targeted goals. In this treatise, we carried out an inclusive survey on key indoor technologies and techniques, with to view to explore their various benefits, limitations, and areas for improvement. The mathematical formulation for simple localization problems is also presented. In addition, an empirical evaluation of the performance of these indoor technologies is carried out using a common generic metric of scalability, accuracy, complexity, robustness, energy-efficiency, cost and reliability. An empirical evaluation of performance of different RF-based technologies establishes the viability of Wi-Fi, RFID, UWB, Wi-Fi, Bluetooth, ZigBee, and Light over other indoor technologies for reliable IoT-based applications. Furthermore, the survey advocates hybridization of technologies as an effective approach to achieve reliable IoT-based indoor systems. The findings of the survey could be useful in the selection of appropriate indoor technologies for the development of reliable real-time indoor applications. The study could also be used as a reliable source for literature referencing on the subject of indoor location identification.Supported in part by the Tertiary Education Trust Fund of the Federal Government of Nigeria, and in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement H2020-MSCA-ITN-2016 SECRET-72242

Prevalence and associated risk factors for mental health problems among young adults in Fiji Island during COVID-19: a cross-sectional study

IntroductionThe COVID-19 pandemic has had a significant impact on mental health globally. To understand the impact of the pandemic on mental health in Fiji, this study aimed to investigate the prevalence of anxiety disorder and depression among the young adults.MethodAn online survey was conducted to assess the prevalence of anxiety disorder and depression among the general population in Suva, Fiji during the COVID-19 pandemic. A total of 1,119 Fiji adults participated in the study. The study was conducted between May 20 to June 30, 2022, using a snowball sampling via social media platforms. The Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) scales were used to measure anxiety and depression, respectively. The COVID-19 related stressors was evaluated using the adapted SARS stressors assessment. Univariate and multivariate logistic regression analysis was performed to determine the factors influencing mental health among respondents.ResultsThe result shows that a significant portion of individuals experienced each of the stressors, with the highest prevalence seen for hearing information about the severity of COVID-19. The prevalence of anxiety and depression was found to be 45% and 49%, respectively. Being female, having pre-existing illness and COVID-19 stressors were a risk factor to develop anxiety and depression. On the other hand, employed individuals and having high BMI was a protective factor against developing depression during COVID-19 lockdown.ConclusionThese findings highlight the importance of addressing the mental health needs of the Fijian population during the COVID-19 pandemic and beyond