Divya P. Vijayan¹, Tokani Ghuhato¹, Eslavath Rajkumar^2,*, Allen Joshua George³, Romate John¹, John Abraham⁴

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 389-398, 2024, DOI:10.32604/ijmhp.2024.023032

Abstract ‘Selfie’ taking was introduced to the common people by smartphones and has become a common practice across the globe in no time. With technological advancement and the popularity of smartphones, selfie-taking has grown rapidly within a short time. In light of the new trend set by the generation, this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults. A purposive sampling method was adopted to select 20 Indian citizens, between 18 and 24 years. The data were collected through semi-structured More >

Anindita Das¹, Kanu Murmu², Biplab Mitra³, Pintoo Bandopadhyay², Ritesh Kundu⁴, Moupiya Roy⁵, Saleh Alfarraj⁶, Mohammad Javed Ansari⁷, Marian Brestic⁸, Akbar Hossain^9,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 763-776, 2024, DOI:10.32604/phyton.2024.049473

Abstract Nutrient management plays a crucial role in the yield and quality of sweet corn. A field experiment was conducted in consecutive two kharif seasons in 2018 and 2019 to investigate the effect of various organic sources of nutrients in combination with inorganic sources on the yield and quality of sweet corn under new alluvial soils of West Bengal, India. Treatments were: T: Control (without fertilizers); T: 100% recommended dose (RDF) of chemical fertilizers (CF) (RDF CF); T: 100% recommended dose of N (RDN) through vermicompost (VC) (RDN VC); T: 50 RDN through CF + 50%… More >

Shaik Thaseentaj, S. Sudhakar Ilango^*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3593-3618, 2023, DOI:10.32604/cmc.2023.042496

Abstract The South Indian mango industry is confronting severe threats due to various leaf diseases, which significantly impact the yield and quality of the crop. The management and prevention of these diseases depend mainly on their early identification and accurate classification. The central objective of this research is to propose and examine the application of Deep Convolutional Neural Networks (CNNs) as a potential solution for the precise detection and categorization of diseases impacting the leaves of South Indian mango trees. Our study collected a rich dataset of leaf images representing different disease classes, including Anthracnose, Powdery… More >

POOJA BHADORIYA¹, RICHA SHARMA¹, REKHA MEHROTRA¹, SIMRAN KAUR¹, ISHA SRIVASTAVA¹, MUKUL JAIN², PRASHANT KAUSHIK^3,*

BIOCELL, Vol.47, No.9, pp. 1915-1930, 2023, DOI:10.32604/biocell.2023.029564

Abstract In the present medicine world antibiotic resistance is one of the key threats to universal health coverage. Researchers continue to work hard to combat this global health concern. Phage therapy, an age-old practice during the early twentieth century, was outshined by the discovery of antibiotics. With the advent of widespread antibiotic resistance, phage therapy has again redeemed itself as a potential alternative owing to its adeptness to target bacteria precisely. Limited side effects, the ability to migrate to different body organs, a distinct mode of action, and proliferation at the infection site, make phages a… More > Graphic Abstract

Seema Sabharwal^1,2,*, Priti Singla¹

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2567-2582, 2023, DOI:10.32604/iasc.2023.035497

Abstract Sign language is used as a communication medium in the field of trade, defence, and in deaf-mute communities worldwide. Over the last few decades, research in the domain of translation of sign language has grown and become more challenging. This necessitates the development of a Sign Language Translation System (SLTS) to provide effective communication in different research domains. In this paper, novel Hybrid Adaptive Gaussian Thresholding with Otsu Algorithm (Hybrid-AO) for image segmentation is proposed for the translation of alphabet-level Indian Sign Language (ISLTS) with a 5-layer Convolution Neural Network (CNN). The focus of this… More >

Anahita Ali^*, Santosh Kumar

International Journal of Mental Health Promotion, Vol.25, No.7, pp. 833-845, 2023, DOI:10.32604/ijmhp.2023.028799

Abstract Since the coronavirus pandemic, many factors led to the change in the mental well-being of hospital administrators and their staff. The pandemic negatively impacted the availability and capability of health professionals to deliver essential services and meet rising demand. Therefore, this study aimed to understand the perspective of hospital administrators about issues and challenges that negatively impacted their staff’s mental health and hospital administrators’ coping response to mitigate those challenges and issues. An exploratory qualitative study was conducted with 17 hospital administrators (superintendents, deputy superintendents, nursing in charge and hospital in charge) working in a… More > Graphic Abstract

SUBHASH CHANDRA^1,2, SANTWANA PALAI³, EDINARDO FAGNER FERREIRA-MATIAS⁴, IVO CAVALCANTE PITA-NETO⁴, CíCERO LUCAS GOMES-RAMALHO⁴, EDLANE MARTINS DE ANDRADE⁴, RAY SILVA DE ALMEIDA⁵, MARCELLO IRITI^6,7,*, HENRIQUE DOUGLAS MELO-COUTINHO^5,*

BIOCELL, Vol.47, No.4, pp. 677-695, 2023, DOI:10.32604/biocell.2023.026081

Abstract Indian medicinal plants are referred to as the “nectar of life” owing to their phytochemicals and bioactive complexes that are beneficial in treating diseases. Coronavirus disease 2019 (COVID-19) is a global health issue without any proper medication. The indigenous plants of India can be exploited to control the precise signs of SARS-CoV-2. The Ministry of AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy) has advised routine usage of medicinal plants for COVID-19. Medicinal plants like Zingiber officinalis, Azadirachta indica, Ocimum sanctum, Nigella sativa, Withania somnifera, Curcuma longa, Piper nigrum, Allium sativum, Tinospora cordifolia, etc. have More >

Nitin Sharma¹, Mohd Anul Haq², Pawan Kumar Dahiya³, B. R. Marwah⁴, Reema Lalit⁵, Nitin Mittal⁶, Ismail Keshta^7,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 881-895, 2023, DOI:10.32604/cmc.2023.027899

Abstract Every developing country relies on transportation, and there has been an exponential expansion in the development of various sorts of vehicles with various configurations, which is a major component strengthening the automobile sector. India is a developing country with increasing road traffic, which has resulted in challenges such as increased road accidents and traffic oversight issues. In the lack of a parametric technique for accurate vehicle recognition, which is a major worry in terms of reliability, high traffic density also leads to mayhem at checkpoints and toll plazas. A system that combines an intelligent domain… More >

A. Naresh Kumar^1,*, G. Geetha²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2619-2637, 2023, DOI:10.32604/iasc.2023.028349

Abstract Recognizing signs and fonts of prehistoric language is a fairly difficult job that requires special tools. This stipulation make the dispensation period overriding, difficult and tiresome to calculate. This paper present a technique for recognizing ancient south Indian languages by applying Artificial Neural Network (ANN) associated with Opposition based Grey Wolf Optimization Algorithm (OGWA). It identifies the prehistoric language, signs and fonts. It is an apparent from the ANN system that arbitrarily produced weights or neurons linking various layers play a significant role in its performance. For adaptively determining these weights, this paper applies various More >

Vani A. Hiremani^*, Kishore Kumar Senapati

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2603-2618, 2023, DOI:10.32604/csse.2023.027612

Abstract The inter-class face classification problem is more reasonable than the intra-class classification problem. To address this issue, we have carried out empirical research on classifying Indian people to their geographical regions. This work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India, referring to human vision. We have created an Automated Human Intelligence System (AHIS) to evaluate human visual capabilities. Analysis of AHIS response showed that face shape is a discriminative feature among the other facial features. We have developed a modified convolutional… More >