The role of telecom industry towards a new vision to make India Digitally powerful in the age of globalization

The Telecom Sector of India has grown over the years and emerged as the second largest today. The reliance Jio has planned to launch 5G in the second half of the 2021. since the launch of Jio we have seen a rapid penetration of Internet services in India. India has the 2nd largest telecom industry in India and the cheapest net provider to its people. There are 500 million active data users and by 2024 it is estimated to have more than 800 million active users and manufacture of 1 billion smart phones in the upcoming years. India is also working towards its objective to empower people digitally. We have seen a rise in the use of digital platform during the pandemic period and also India is taking it steps ahead towards digital economy. The sad reality behind this is even where India is about to launch 5G service in India 90% of the population in India are digitally illiterate with only 8% of the population have access to a laptop or a computer. India also has a poor cyber security system and the data is vulnerable of every user. We also have poor tower connection in many areas with only 25 % of the net is connected by fiber. India needs to upgrade its telecom industry and provide net facilitates to all its people as the Internet is going to dominate the future. India’s Telecom industry contributes to 6.5% of the GDP.

(Hyper)active Data Curation: A Video Case Study from Behavioral Science

Video data are uniquely suited for research reuse and for documenting research methods and findings. However, curation of video data is a serious hurdle for researchers in the social and behavioral sciences, where behavioral video data are obtained session by session and data sharing is not the norm. To eliminate the onerous burden of post hoc curation at the time of publication (or later), we describe best practices in active data curation—where data are curated and uploaded immediately after each data collection to allow instantaneous sharing with one button press at any time. Indeed, we recommend that researchers adopt “hyperactive” data curation where they openly share every step of their research process. The necessary infrastructure and tools are provided by Databrary—a secure, web-based data library designed for active curation and sharing of personally identifiable video data and associated metadata. We provide a case study of hyperactive curation of video data from the Play and Learning Across a Year (PLAY) project, where dozens of researchers developed a common protocol to collect, annotate, and actively curate video data of infants and mothers during natural activity in their homes at research sites across North America. PLAY relies on scalable standardized workflows to facilitate collaborative research, assure data quality, and prepare the corpus for sharing and reuse throughout the entire research process.

ECOCAPTURE@HOME: Protocol for the Remote Assessment of Apathy and Its Everyday-Life Consequences

Apathy, a common neuropsychiatric symptom associated with dementia, has a strong impact on patients’ and caregivers’ quality of life. However, it is still poorly understood and hard to define. The main objective of the ECOCAPTURE programme is to define a behavioural signature of apathy using an ecological approach. Within this program, ECOCAPTURE@HOME is an observational study which aims to validate a method based on new technologies for the remote monitoring of apathy in real life. For this study, we plan to recruit 60 couples: 20 patient-caregiver dyads in which patients suffer from behavioral variant Fronto-Temporal Dementia, 20 patient-caregiver dyads in which patients suffer from Alzheimer Disease and 20 healthy control couples. These dyads will be followed for 28 consecutive days via multi-sensor bracelets collecting passive data (acceleration, electrodermal activity, blood volume pulse). Active data will also be collected by questionnaires on a smartphone application. Using a pool of metrics extracted from these passive and active data, we will validate a measurement model for three behavioural markers of apathy (i.e., daytime activity, quality of sleep, and emotional arousal). The final purpose is to facilitate the follow-up and precise diagnosis of apathy, towards a personalised treatment of this condition within everyday life.

(Hyper)active Data Curation: A Video Case Study from Behavioral Science

Video data are uniquely suited for research reuse and for documenting behavioral research methods and findings. However, curation of video data is a serious hurdle for researchers in the behavioral sciences, where data sharing is not the norm. To eliminate the onerous burden of post-hoc curation at the time of publication (or later), we describe best practices in active data curation—curation “as you go”—where data are uploaded immediately after each data collection to allow instantaneous sharing with one button press at any time. We address how to prepare for collecting and sharing identifiable video data; train researchers for accurate and efficient video data curation; and offer solutions when active curation of research video is impossible.

Correction in Active Cases Data of COVID-19 for the US States by Analytical study

The total COVID-19 (SARS-CoV-2) infected cases have reached 139 million worldwide and nearing 3 million deaths on April 16, 2021. The availability of accurate data is crucial as it makes it possible to analyze correctly the infection trends and make better forecasts. The reported recovered cases for many US states are surprisingly low. This could be due to difficulties in keeping track of recoveries and resulted in higher numbers for the reported active cases than the actual numbers on the ground. In this work, based on the typical range of recovery rate for COVID-19, we estimate the active data from the total cases and death cases and bring out a correction for the data for all the US states reported on worldometer.

Protocol for Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH) (Preprint)

BACKGROUND Chronic Lung disorders like COPD and IPF are characterised by exacerbations which are a significant problem: unpleasant for patients, and sometimes severe enough to cause hospital admission (and therefore NHS pressures) and death. Reducing the impact of exacerbations is very important. Moreover, due to the COVID-19 pandemic, the vulnerable populations with these disorders are at high risk and hence their routine care cannot be done properly. Remote monitoring offers a low cost and safe solution of gaining visibility into the health of people in their daily life. Thus, remote monitoring of patients in their daily lives using mobile and wearable devices could be useful especially in high vulnerability groups. A scenario we consider here is to monitor patients and detect disease exacerbation and progression and investigate the opportunity of detecting exacerbations in real-time with a future goal of real-time intervention. OBJECTIVE The primary objective is to assess the feasibility and acceptability of remote monitoring using wearable and mobile phones in patients with pulmonary diseases. The aims will be evaluated over these areas: Participant acceptability, drop-out rates and interpretation of data, Detection of clinically important events such as exacerbations and disease progression, Quantification of symptoms (physical and mental health), Impact of disease on mood and wellbeing/QoL and The trajectory-tracking of main outcome variables, symptom fluctuations and order. The secondary objective of this study is to provide power calculations for a larger longitudinal follow-up study. METHODS Participants will be recruited from 2 NHS sites in 3 different cohorts - COPD, IPF and Post hospitalised Covid. A total of 60 participants will be recruited, 20 in each cohort. Data collection will be done remotely using the RADAR-Base mHealth platform for different devices - Garmin wearable devices, smart spirometers, mobile app questionnaires, surveys and finger pulse oximeters. Passive data collected includes wearable derived continuous heart rate, SpO2, respiration rate, activity, and sleep. Active data collected includes disease-specific PROMs, mental health questionnaires and symptoms tracking to track disease trajectory in addition to speech sampling, spirometry and finger Pulse Oximetry. Analyses are intended to assess the feasibility of RADAR-Base for lung disorder remote monitoring (include quality of data, a cross-section of passive and active data, data completeness, the usability of the system, acceptability of the system). Where adequate data is collected, we will attempt to explore disease trajectory, patient stratification and identification of acute clinically interesting events such as exacerbations. A key part of this study is understanding the potential of real-time data collection, here we will simulate an intervention using the Exacerbation Rating Scale (ERS) to acquire responses at-time-of-event to assess the performance of a model for exacerbation identification from passive data collected. RESULTS RALPMH study provides a unique opportunity to assess the use of remote monitoring in the study of lung disorders. The study is set to be started in mid-May 2021. The data collection apparatus, questionnaires and wearable integrations have been set up and tested by clinical teams. While waiting for ethics approval, real-time detection models are currently being constructed. CONCLUSIONS RALPMH will provide a reference infrastructure for the use of wearable data for monitoring lung diseases. Specifically information regarding the feasibility and acceptability of remote monitoring and the potential of real-time remote data collection and analysis in the context of chronic lung disorders. Moreover, it provides a unique standpoint to look into the specifics of novel coronavirus without burdensome interventions. It will help plan and inform decisions in any future studies that make use of remote monitoring in the area of Respiratory health. CLINICALTRIAL https://www.isrctn.com/ISRCTN16275601

Development of Football technique Skills Test Instruments for U-17 Players

To find out the technical ability of football for U-17 football players, a precise and permanent test is needed. However, in the field, the forms used by the teaching staff and trainers who use standardized tests or those that already have standards have not been maximized to measure the skill level. The population of this study was 103 people in the U-17 group, which were taken from officially registered football coaching at the PSSI Padang City Association (Askot) and the Padang City SSB League Agency who were still active. Data were collected by implementing passing tests, long passing tests, shooting tests and heading tests. The data analysis technique uses the product moment correlation technique to find validity and reliability using the alpha correlation coefficient formula. To determine the football technique scoring norms, use the Scale 5 formula. Based on the results of data analysis obtained; (1) Level of validity: the passing test is 0.53 (moderate), the long passing test is 0.50 (moderate), the shooting test is 0.53 (moderate) and the heading test is 0.53 (moderate). (2) Reliability level: passing test of 0.194 (acceptable), long passing test of 0.174 (acceptable), shooting test of 0.368 (acceptable) and heading test of 0.014 (unacceptable).