ALED System to Provide Mobile IoT Assistance for Elderly and Disabled

Nikhil Chaudhari,Akash Gupta,SSV Raju 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.8

The United Nations estimates that about 15 percent of the world’s population lives with some type of disability. Equally important is the increasing life expectancy rate of elderly people. People falling in any of these categories face great difficulty in living an independent life and have to be dependent on others. Internet-of-Things (IoT) presents immense potential in solving these problems. IoT is a concept by which everyday objects can communicate with each other via a network. This enables us to collect and store the data from these devices in the Cloud. Although there are existing systems that help to solve some of these problems; however, a comprehensive system is missing. In this paper, we propose a unified system ALED (Assisted Living for the Elderly and Disabled) using Google Brillo and Weave platform to solve both of these problems. The system provides a solution by collecting data from IoT devices (e.g., smart sensors, wearable devices, tags) and utilizes the Cloud to process the information from database. The system enables the elderly and disabled to live their life independently and at the same time make it more pleasing.

Predictive Breast Cancer Statistical Modelling for Early Diagnosis

Amit Kumar Gupta,Ankit Verma,Vipin Kumar,Nikhil Kumar,Dowon Kim,Young-Jin Jung,Mangal Sain 한국자기학회 2023 Journal of Magnetics Vol.28 No.4

Breast cancer is a significant global health concern, stressing the urgent need for early detection. Early diagnosis improves access to varied treatments and significantly enhances patient outcomes. This study explores breast cancer detection over two days, aiming to create a precise and efficient machine learning model. The research uses a diverse dataset, combining clinical, genetic, and imaging data, including magnetic resonance imaging (MRI), X-ray, and electromagnetic data. Rigorous data preprocessing, including variable normalization and feature identification, enhances dataset quality. Predictive models use statistical techniques like logistic regression, decision trees, and random forest. Key metrics, such as accuracy, precision, recall, and area under the curve (AUC), assess model efficacy. Results reveal high accuracy and AUC scores, indicating potential for precise breast cancer detection. The study enhances our understanding of breast cancer dynamics, showcasing the effectiveness of machine learning for accurate and efficient early diagnosis. The research underscores diverse datasets and careful statistical modeling as crucial for predictive breast cancer capabilities.

Enhanced Particle Swarm Optimization for Short-Term Non-Convex Economic Scheduling of Hydrothermal Energy Systems

Vinay Kumar Jadoun,Nikhil Gupta,Khaleequr Rehman Niazi,Anil Swarnkar 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.5

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

Enhanced Particle Swarm Optimization for Short-Term Non-Convex Economic Scheduling of Hydrothermal Energy Systems

Jadoun, Vinay Kumar,Gupta, Nikhil,Niazi, K. R.,Swarnkar, Anil The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.5

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

Impact of Hearing Loss and Rehabilitation on the Psychological Well-Being of the Elderly

Namit Kant Singh,Nikhil Gupta,Kasagani Veerabhadra Rao 한국청각언어재활학회 2023 Audiology and Speech Research Vol.19 No.1

Purpose: Hearing loss in the elderly is a common disorder which range from an undetectable degree of disability to profound alteration in the ability to function in society. Hence, this study was undertaken to assess the impact of hearing loss and rehabilitation on the psychological well-being of the elderly. Method: Patients above 60 years complaining of hearing loss were evaluated for the otoscopic examination, audiological assessment, psychological assessment Hearing Handicap Inventory for the Elderly Screening (HHIE-S) version, and Global Mental Health Assessment (GMHA) tool. Data was statistically analyzed to determine the relationship between the hearing loss and psychological affection and the benefit after use of hearing aids and rehabilitation. Results: A total of 60 males and 50 females were taken into consideration. HHIE-S showed a significant relation with the severity of hearing loss in the initial assessment and also after remedial measures. GMHA also showed a significant statistical relationship with the severity of hearing loss after initial assessment and after remedial measures. Conclusion: The significant relation of HHIE-S and GMHA with the severity of hearing loss suggest that as the hearing loss increases there is a higher probability of an individual having psychological affection causing the social and emotional situational adjustments producing depression and anxiety. It is also concluded that early remedial measures provide substantial improvement in their quality of life.

The impact of yoga on stress, metabolic parameters, and cognition of Indian adolescents: A cluster randomized controlled trial

Ranjani Harish,Jagannathan Narayanaswamy,Rawal Tina,Vinothkumar Radhakrishnan,Tandon Nikhil,Vidyulatha Jayaram,Mohan Viswanathan,Gupta Yashdeep,Anjana Ranjit Mohan 한국한의학연구원 2023 Integrative Medicine Research Vol.12 No.3

Background: This project aimed to assess the impact of yoga on stress, metabolic parameters and cognition (attention & concentration) in adolescents, aged 13–15 years from public and private schools in two cities (Chennai and New Delhi) in India. Methods: The study recruited 2000 adolescents from 24 schools in a cluster randomized controlled trial design. The yoga group participants underwent 17 yoga sessions, which included: pranayama, basic asanas, meditation and relaxation exercises. Yoga sessions, were held in the school premises once a week. A total of five awareness talks on healthy lifestyle were delivered once a month to the education group. ADOlescence Stress Scale (ADOSS), salivary cortisol, metabolic and clinical parameters and Letter Cancellation Test (LCT) score were measured at baseline and post-intervention (5–6 months). Results: The yoga group showed statistically significant differences in the mean ADOSS score, metabolic parameters, salivary cortisol, and LCT scores compared to the education group. In the intention- to- treat analysis, a significant reduction [5.11, 95% CI (4.78, 5.36), p = 0.001] in ADOSS score was seen in the yoga group compared to education. Conclusion: Implementation of a 17-week standardized yoga program at the school level significantly decreased stress, improved attention and concentration, metabolic and clinical parameters in Indian adolescents.