The relationship between density of drug outlets, crime hot spots and family factors on the consumption of drugs and delinquent behaviour of male adolescent Mexican students
Aggressive/delinquency behaviour; Community risk factors; Consumption of drugs; Family; Male adolescents; Spatial analysis
This study examined the relationship between community risk factors (drug outlets density and crime hot spots) and family factors on the risk behaviours (drugs consumption and delinquent behaviour) of male adolescent Mexican students. Results were obtained based on data bank analysis and direct collection of information regarding family factors and risk behaviours of adolescents attending school. Spatial and statistical analysis was performed. The final sample was composed of 1450 male adolescents, from 11 secondary and high schools located in marginal and violent areas of Mexico. Spatial analysis revealed that when considering only the prevalence of the risk behaviours of the adolescents, the area of highest risk was the northwestern area of the city. However, after performing conjunct analysis of all evaluated variables using density point risk (aside from confirming that the northwestern area is still the one with the greatest risk), results indicated that the southern area has a high-density point risk. All densities of the variables showed a statistically significant positive association (p < 0.05). However, the results of the structural equation model indicated than only the family factors influenced the risk behaviours of adolescents (p < 0.05). The spatial distribution of the risk behaviours in male adolescent students and community risk variables surrounding the area where schools are located allows for the description of patterns and hotspot detection that facilitate the prioritization of where interventions must be directed. Besides, the interventions should target family factors. 2021 Elsevier Ltd
Santana-Arias R.; George T.S.; Padr-Salas A.; Sanjuan-Meza X.S.; Landeros-Olvera E.A.; Coss-Torres P.E.
ISSN: 2779536; PubMed ID: 33990072; CODEN: SSMDE
https://doi.org/10.1016/j.socscimed.2021.113985 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105595537&doi=10.1016%2fj.socscimed.2021.113985&partnerID=40&md5=1a03673d982c6053c65b21262aa4ddb0
Santana-Arias R., Engineering Faculty, Autonomous University of San Luis Potosi, Dr. Manuel Nava No. 8, Col. Zona Universitaria Poniente, Zip code, San Luis Potos 78290, Mexico; George T.S., CHRIST (Deemed to be University), Hosur Road, Bangalore, India; Padr-Salas A., Public Health Department. Medicine School, Autonomous University of San Luis Potosi, Av. Venustiano Carranza 2405, Col. Los Filtros, Zip code, San Luis Potos 78210, Mexico; Sanjuan-Meza X.S., Public Health Department, Medicine School, Autonomous University of San Luis Potosi, Av. Venustiano Carranza 2405, Col. Los Filtros, Zip code, San Luis Potos 78210, Mexico; Landeros-Olvera E.A., Nursing Faculty. Autonomous University of Puebla, 25 Poniente n. 1304, Col. Volcanes, Zip code, Puebla, 72410, Mexico; Coss-Torres P.E., Public Health Department, Medicine School, Autonomous University of San Luis Potosi, Av. Venustiano Carranza 2405, Col. Los Filtros, zip code, San Luis Potos 78210, Mexico
Enhancing Human-Computer Interaction with a Low-Cost Air Mouse and Sign Language Recognition System
Air Mouse; CNN; Hand Gesture; Mediapipe; Proton Assistant; Sign Language
The purpose of this study is to investigate the development of assistive technologies that are designed to empower people with disabilities by increasing their level of freedom and accessibility. Voice assistants, air mice, and software that recognizes sign language are some of the topics that are specifically covered in this. Those who have impaired fine motor skills can benefit from using air mice since they allow controls to be made by hand gestures. Using machine learning algorithms, sign language recognition software is able to decipher signs with an accuracy rate of over 90 percent, making it easier for people who are deaf or hard of hearing to communicate themselves. By relying solely on vocal instructions, voice assistants like Alexa make it possible to control devices without using your hands. Not only do these technologies have the potential to be revolutionary, but they also confront obstacles in terms of improving identification accuracy and integrating them into common gadgets. In this study, the development and impact of voice assistants, sign language software, and air mice are discussed. More specifically, the paper highlights the potential for these technologies to help millions of people with disabilities all over the world. Additionally, it examines potential enhancements that could be made to these technologies in the future in order to further improve accessibility and inclusivity. This research integrates computer vision and machine learning to create a multimodal system blending air mouse functionality with real-time sign language translation. Achieving 95% accuracy in gesture recognition for air mouse control and 98% accuracy in sign language letter classification using a basic webcam, the system promotes accessible interaction without specialized hardware. Despite limitations in vocabulary and lighting sensitivity, future efforts aim to broaden data training and explore mobile deployment. These advancements hold promise for enhancing natural human-computer interaction, particularly for users with disabilities, by enabling intuitive, hands-free control and communication. 2024 IEEE.
Proceedings of International Conference on Circuit Power and Computing Technologies, ICCPCT 2024, pp. 93-98.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICCPCT61902.2024.10673196 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205577953&doi=10.1109%2fICCPCT61902.2024.10673196&partnerID=40&md5=9bb0cbeafa7075e3ac8caee0c543e82f
Santhan H., CHRIST (Deemed to Be University), Computer Science, Bangalore, India; Sudhakar T., CHRIST (Deemed to Be University), Computer Science, Bangalore, India; Joy H.K., CHRIST (Deemed to Be University), Computer Science, Bangalore, India
A study on the factors affecting usage of voice assistants and the interface transition from touch to voice
Barriers; Interface; Touch to voice; Transition; Voice Assistants; Voice Inputs and Outputs
The interface simplicity has always been one of the most important factors which makes any new technology or device successful. Once an individual gets attached to a particular interface it becomes easy for them to use any devices which follows the same interface pattern. But to adapt to a new interface for the same device or the same need it will take a lot of effort from both the user and the companies which advances those to support each other to make the interface shift happen. The timespan required for this interface shift depends on the mindset of each individual and the simplicity of the proposed interface. Voice Assistants (VA) are an important achievement, which have become an inseparable and integral part of many smart devices. The mobile penetration in India has allowed rapid acceleration among metropolitan Indian adults in the usage of the wearable devices and other such smart technologies. Voice as an interface is going to improve the next generation of social conversation, content searches and medium of commerce. The rapidly increasing competition in this segment has led to several improvements. We already have many such voice-enabled devices that help us to set routines, automate the home appliances and provides us on-demand information. Also, the smart speakers category in Indiagrew 43 per cent in the second quarter of 2018.Many big corporates like Amazon, Apple, Google and Microsoft offers an entire digital platform infrastructure that can be controlled by voice assistants. The future of Voice Assistants depends to a large extent on how natural and fluid the communication with the user can take place. The interface transition from touch to voice has several factors involved in it. This study is majorly to find out what are the major factors which are influencing this transition and how relevant are these identified factors for the transition to happen in Indian market. 2020 SERSC.
International Journal of Advanced Science and Technology, Vol-29, No. 5, pp. 3084-3102.
Science and Engineering Research Support Society
Santhanaraj K., School of Business and Management, Christ (Deemed to be University), Bengaluru, India; Barkathunissa A., School of Business and Management, Christ (Deemed to be University), Bengaluru, India
Deep learning-driven correction of motion-induced artifacts in microfluidic on-chip fluorescence microscopy for robust cell classification
Cancer cell screening; Deep learning; GAN; Microfluidic fluorescence microscopy; Motion artifact correction; Vision transformer
Fluorescence microscopy combined with microfluidic platforms allows for the analysis of single cells and the whole biomedical process to be done at high speed, however, it is often a very delicate method that can be heavily affected by motion-induced distortions during the high-speed flow. These artifacts, such as motion blur, misalignment, and shape deformation significantly lower automatical accuracy of the cell classification. The suggested research suggests that on-chip fluorescence microscopy employs an AI-based framework of distortion correction using Vision Transformers (ViT) and Generative Adversarial Networks (GAN) to remove motion artifacts in real-time. The combination of the GAN-ViT architecture does not only manage to reconstruct image quality but also to preserve fine cellular features when flowing system rates increase to 200 4L/min, which provide PSNR = 38.6 dB and SSIM = 0.98. When the system was used in both synthetic and experimental microfluidic data, it was able to reach a classification accuracy of 99.9, thereby indicating consistency in the system despite varying flow rates. The speed of the framework is 950 frames per second (fps), almost equal to the 1000-fps smartphone camera acquisition rate, thereby, demonstrating its suitability to the real-time, high-throughput imaging. As opposed to the past CNN or transformer techniques, a hybrid GAN-ViT architecture offered by the authors of this study directly implements in the imaging pipeline, thus enabling the simultaneous motion correction and diagnostic classification to occur immediately. The study results highlight the fact that AI-based distortion correction not only increases the accuracy of the diagnosis, but also personnel and laboratory response in microfluidic fluorescence microscopy. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026.
Santhi, K.; Shrichandran, G.V.; Indhumathi, K.; Warrier, Gayathry S.; Sudha, S.; Rajaram, A.
Microfluidics and Nanofluidics;Volume;30;Issue;3;Article No.;25;
Springer Science and Business Media Deutschland GmbH
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1007/s10404-026-02880-5 https://www.scopus.com/pages/publications/105030932400?origin=resultslist
Santhi K., Information Technology, Easwari Engineering College, Tamil Nadu, Chennai, 600089, India; Shrichandran G.V., Department of Computer Science and Engineering, School of Computer Science Engineering, SRM Institute of Science and Technology, Tamil Nadu, Ramapuram, Chennai, 600089, India; Indhumathi K., Assistant Professor, Department of Computer Applications, Kalasalingam Academy of Research and Education, Tamil Nadu, Krishnankoil, Srivilliputhur, 626126, India; Warrier G.S., Department of Computer Science, Christ (Deemed to be University, Karnataka, Bangalore, 560073, India; Sudha S., Professor,Department of Electronics and Communication Engineering, sri Ranganathar Institute of Engineering and Technology, Tamil Nadu, Coimbatore, 641110, India; Rajaram A., Department of Electronics and Communication Engineering, E.G.S Pillay Engineering College, Tamilnadu, Nagapattinam, 611002, India
Early Detection of Cervical Cancer using Machine Learning Classifiers for Improved Diagnosis in Underserved Regions
Benign; Cervical Cancer; Logistic Regression; Malignant; ML; Random Forest
One of the incurable diseases that affect women is cervical cancer. It is brought on by a protracted infection of the skin and the vaginal mucous membrane cells. The Human Papilloma Virus (HPV), is the main factor causing aberrant cell proliferation in the area around the cervix. There are no symptoms present when the illness first appears. Early detection of this malignancy may be used to prevent death. People in less developed countries cannot afford to periodically examine themselves due to a lack of awareness, poor medical infrastructure, and expensive medication. The EDA technique is applied to examine the data and understand its characteristics. Machine Learning algorithm has been used to diagnose cervical cancer. In order to spot the existence of cervical cancer, five machine learning classifiers are utilized, the algorithms to begin earlier. The Logistic Regression classifier's results validate the correct stage prediction. 2023 IEEE.
Santhiya S.; Mapari S.; Abinaya N.; Jayadharshini P.; Priyanka S.; Krishnasamy L.
2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023, pp. 582-587.
Santhiya S., Kongu Engineering College, Department of Artificial Intelligence, TamilNadu, Erode, India; Mapari S., Symbiosis International (Deemed University), Symbiosis Institute of Computer Studies and Research (SICSR), Pune, India; Abinaya N., Kongu Engineering College, Department of Artificial Intelligence, TamilNadu, Erode, India; Jayadharshini P., Kongu Engineering College, Department of Artificial Intelligence, TamilNadu, Erode, India; Priyanka S., Kongu Engineering College, Department of Artificial Intelligence, TamilNadu, Erode, India; Krishnasamy L., Christ (Deemed to Be) University, School of Engineering and Technology, Department of Computer Science and Engineering, Bengaluru, India
Biodegradable Organic Polymers for Environmental Protection and Remediation
Agro-waste; Biopolymers; Cellulose; Chitin; Chitosan; Keratin; Levan; Polyhydroxyalkanoates; Remediation; Starch
As the era of urbanization and industrialization progressed, non-biodegradable polymers became a severe threat to the environment and the world's rapidly growing population. These synthetic polymers possess flexible applications and cost effectiveness which makes their usage more feasible and convenient. Today they are used from simple packaging to critical biomedical tools. Although these polymers possess many merits, all come to halt when it comes to biodegradability. The inherent mechanisms in nature are unable to degrade and decompose these synthetic polymers leading to their accumulation and persistence in nature for decades causing calamitous effects. In search of solutions for the adverse effects caused by synthetic polymers, the world turned toward biologically synthesized biodegradable organic polymers. These biopolymers have a diverse set of physical and chemical characteristics that can be easily manipulated, allowing for a wide range of applications. Biopolymers like polyhydroxyalkanoates and levan have adaptable qualities that resemble those of synthetic plastics which makes them a promising alternative to synthetic plastics. However, the setback in the large-scale usage of biopolymers is their high cost of production and commercialization. The biopolymers are broadly classified into three major classes based on their origin: plant-based biopolymers (cellulose, starch), animal-based biopolymers (chitin, chitosan, keratin), and microbial biopolymers (polyhydroxyalkanoates, levan). The extraction or synthesis of these biopolymers from their biological sources varies significantly from each other; however, in order to bring out the sustainable production, these polymers should be produced by coupling with waste valorization approaches. The waste materials from plants and animals, particularly agro-industrial wastes, can be used as inexpensive substrates for the commercial manufacture of these crucial biopolymers, thereby reducing the accumulation in the environment. Another field of biopolymer usage is in remediation of pollutants. Many biopolymers are currently being used in the active removal of heavy metal, dye, and other similar pollutants. The numerous physical, chemical, and biological processes for extraction or synthesis of industrially valuable biopolymers from the waste raw materials are discussed in this chapter, along with their application in remediation of pollutants and environmental protection. 2025 WILEY-VCH GmbH, Boschstra 12, 69469 Weinheim, Germany. All rights reserved.
Santhosh A.S.; Suresh S.; Umesh M.; Stanly L.M.; Grigary S.; James N.
Organic Polymers in Energy-Environmental Applications, pp. 381-402.
Santhosh A.S., CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bangalore, 560029, India; Suresh S., CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bangalore, 560029, India; Umesh M., CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bangalore, 560029, India; Stanly L.M., CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bangalore, 560029, India; Grigary S., CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bangalore, 560029, India; James N., CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bangalore, 560029, India
Valorization of waste chilli stalks (Capsicum annuum) as a sustainable substrate for cellulose extraction: insights into its thermomechanical, film forming and biodegradation properties
Biodegradation; Biopolymer; Cellulose; Cellulose sheet; Chilli waste; Valorization
Rising global population accelerates food waste generation, thereby creating a crisis in food waste management. A solution involves deriving value-added products like cellulose biopolymer from food waste. Chilli stalk wastes are one such food waste which are generated in large quantities and are unsuitable for field use or incineration due to health and environmental challenges. A greener alternative is extracting cellulose biopolymer from chilli stalk waste. The extraction of cellulose biopolymer from chilli stalk results in a renewable, biodegradable and economically efficient biomaterial with a broad range of applications. The extraction process involving alkali treatment (NaOH) and bleaching (alkaline H2O2), resulted in a yield of 29.85% cellulose biopolymer. The extracted cellulose was subjected to quantification and functional property analysis followed by characterization (FTIR, XRD, TGA, DSC and SEM) to analyse functional groups, crystallinity, thermal properties and surface morphology. Functional property analysis resulted in higher values when compared with commercial cellulose. The characterization techniques confirmed the effective removal of impurities such as lignin, hemicellulose and pectin by the chemical treatments. Cellulose sheets, fabricated using solvent casting, exhibited exceptional biodegradability (85.36%) within 20days, surpassing conventional food packaging materials, commercial food packaging paper (15.95 0.12% [%w/w]) and plastic sheets (7.89 0.33% [%w/w]) over the same time period. The novelty of this research lies in the innovative valorization of chilli stalk waste, which often remains unused in large quantities globally. This study introduces a cost-effective method to convert it into a value-added, highly biodegradable biopolymer. The resulting cellulose sheets provide an eco-friendly substitute for traditional food packaging materials. 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Santhosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India
A Strategic Review on Use of Polyhydroxyalkanoates as an Immunostimulant in Aquaculture
Agricultural waste; Anti-biofilm activity; Aquaculture; Aquafeed additive; Immunostimulant; Polyhydroxyalkanoates
Background and Objective: Increasing concerns over the use of antibiotics in aquaculture have emerged researchers to focus on short chain fatty acids and other biocompatible molecules as alternatives for disease prophylaxis and treatment. Polyhydroxyalkanoates well studied as biopolymeric materials for using in packaging and biomedicine were not focused much for their abilities to act as antimicrobial agents in aquaculture until recent years. Application studies of polyhydroxyalkanoates as aquafeed additives have highlighted their promising roles as ecofriendly alternatives for commercial antibiotics with strong immunomodulatory effects in fish-es and shrimps. The major aim of this review was to explore up-to-date scientific research studies on use of polyhydroxyalkanoates as aquafeed additives and their immunomodulatory effects. Results and Conclusion: Up-to-date, limited scientific literatures have been published on the use of polyhydroxyalkanoates and their copolymers as alternatives to antibiotics in aquaculture. This research field includes a great scope of development due to the promising immu-nomodulatory and antimicrobial activity of polyhydroxyalkanoates against common pathogens in aquaculture, as reported in literatures. Although several hypothesis and research data for explaining the mechanisms behind their immunostimulatory effects were suggested by various researchers, genetic and molecular bases underlying these phenomena are yet to be explored. Further research and development in this area can introduce these biopolymers as the most promising eco-friendly alternatives for antibiotics in aquaculture. Conflict of interest: The authors declare no conflict of interest. 2021. All Rights Reserved.
Applied Food Biotechnology, Vol-8, No. 1, pp. 1-18.
National Nutrition and Food Technology Research Institute
https://doi.org/10.22037/afb.v8i1.31255 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115107342&doi=10.22037%2fafb.v8i1.31255&partnerID=40&md5=c567bbadba14837d18fb352a1de2db85
Santhosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India
Earliness of SME internationalizationand performance: Analyzing the role of CEO attributes
CEO attributes; Earliness of SME internationalization; Emerging economy; Performance; SMEs
Purpose: The purpose of this paper is to understand the mediating effects of Chief Executive officer (CEO) attributes on the earliness of internationalization and performance in context of Indian small and medium enterprises (SMEs). Design/methodology/approach: The proposed framework is tested through analysis of a sample of 102 internationalized SMEs of the engineering industry in the Bangalore city region of India. Findings: Results highlight that CEOs age and educational background moderates between early internationalization and performance in the Indian SME context. Practical implications: Overall results facilitate in leveraging the decision-makers capabilities to successfully formulate and strategize their international marketing efforts to achieve higher performance. Originality/value: The study enriches the importance of CEO attributes in influencing the early internationalization and degree of internationalization in the context of an emerging economy where studies are limited. 2019, Emerald Publishing Limited.
Journal of Entrepreneurship in Emerging Economies, Vol-11, No. 4, pp. 537-549.
https://doi.org/10.1108/JEEE-11-2018-0132 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068191876&doi=10.1108%2fJEEE-11-2018-0132&partnerID=40&md5=a1f91e3195686a427361be2ae4ec7539
Santhosh C., Department of Economics, Christ University, Bangalore, India
Impact of determinants on early internationalization: An exploratory study of Indian engineering SMEs
Determinants; Early internationalization; Emerging economy; Engineering industry; Exploratory study; SMEs
Purpose: The purpose of this paper is to analyze the influence of determinants on early internationalization in the context of an emerging economy, i.e. India. Design/methodology/approach: The study is based on an ex post facto exploratory research using primary data collected from a sample of 102 exporting small- and medium-sized enterprises (SMEs) in Bangalore. Findings: The overall results reveal that it is the proactive entrepreneurs and their previous experience that determine the early internationalization of SMEs. Further, competitive constraint was a major obstacle to enter the international market at an early age for late internationalized SMEs. Practical implications: The policy initiatives should aim to develop the international orientation of the entrepreneurs in the firm as a precursor for the formulation and subsequent implementation of internationalization strategies. Originality/value: Although studies have been conducted on determinants and early internationalization, these are confined to a few dimensions, and none of the studies have looked into the issues affecting the early internationalization holistically and with respect to SMEs in India. 2019, Emerald Publishing Limited.
Journal of Engineering, Design and Technology, Vol-17, No. 5, pp. 1018-1034.
https://doi.org/10.1108/JEDT-01-2019-0001 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067067904&doi=10.1108%2fJEDT-01-2019-0001&partnerID=40&md5=c7feaacc46cd4ba6067483abb5d7c2ee
Market Openness and Price Volatility: Evidence from Major Cash Crops of India
JIM Quest: Journal of Management and Technology, Vol-8 (2), pp. 01-10. ISSN-0975-6280
JIM Quest: Journal of Management and Technology
Twin deficit hypothesis: Some recent evidence from India
ARDL; Autoregressive distributed lag; Budget deficit; Cointegration; India; Trade deficit; Twin deficits
The purpose of this study is to examine the relationship between budget deficit and trade deficit commonly known as 'twin deficits hypotheses' in Indian economy. We used time series data for the period of 1970 to 2013. The empirical results of this study follow the autoregressive distributed lag (ARDL) cointegration technique for long run and short run estimates and error correction mechanism (ECM). In this study, we check the hypotheses that trade deficit is the determinant of budget deficit with its current values or the lag values. The results of the ARDL model confirm that there is the positive and significant relationship between trade deficit and budget deficit. So twin deficits hypothesis is valid for India. The ARDL results of the short run confirm the hypothesis that trade deficit can determine the budget deficit in the case of India. The results of the long run estimates are also significant. The error correction specification is used to find evidence of long-run causality running from budget deficit to trade deficit and vice versa. The empirical results suggest that trade deficit can determine the budget deficit in case of India. 2016 Inderscience Enterprises Ltd.
Global Business and Economics Review, Vol-18, No. 45750, pp. 487-495.
https://doi.org/10.1504/GBER.2016.076283 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969253505&doi=10.1504%2fGBER.2016.076283&partnerID=40&md5=b148c1c32e22a018ac2b788ab97fa0d7
Santhosh Kumar P.K., Department of Economics, Christ University, Bangalore, 560076, India
Highly mixed high-energy d-orbital states enhance oxygen evolution reactions in spinel catalysts
Anion modification; Electronic structure modulation; Oxygen evolution reaction; Spinel catalyst; Trigonal distortion
Design, synthesis, and engineering of electrocatalysts for the oxygen evolution reaction (OER) are essential for attaining desirable electrocatalytic performance towards practical implementation. Emerging spinel-type OER catalysts have not reached the desirable activity and durability, thus demanding critical research to advance the field. To achieve enhanced OER performance for spinel-type OER catalysts, we present an efficient strategy of electronic structure modulation of central metal atoms. Modulation of the electronic properties of the Zn and Co atoms through the counter anionic components (O, S, and Se) regulates the adsorption of oxygen intermediates and thus enhances OER activity, which is systematically demonstrated using Density Functional Theory (DFT) calculation. Although the zinc cobalt selenide catalyst showed the less pronounced trigonal distortion, the mixing of eg orbitals with selenium accounts for the experimentally observed enhancement in OER activity. The result is, in contrast to the benchmark catalyst made of RuO2, ZnCo2Se4@rGO demonstrated lower OER overpotential (?10 = 302 mV) and Tafel slope (58 mV dec?1) as well as greater durability at 10 mA cm?2 for 50 h. The implementation of this strategy in several spinel-type catalysts could improve their electrocatalytic performance. 2023 Elsevier B.V.
Santhosh Kumar R.; Muthu Austeria P.; Sagaya Selvam Neethinathan C.; Ramakrishnan S.; Sekar K.; Kim A.R.; Kim D.H.; Yoo P.J.; Yoo D.J.
https://doi.org/10.1016/j.apsusc.2023.158469 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172364796&doi=10.1016%2fj.apsusc.2023.158469&partnerID=40&md5=9f6a18358243b99d1bc91acb5f6ab451
Santhosh Kumar R., Department of Energy Storage/Conversion Engineering of Graduate School (BK21 FOUR), Hydrogen and Fuel Cell Research Center, Jeonbuk National University, Jeollabuk-do, Jeonju, 54896, South Korea; Muthu Austeria P., Division of Science Education, Jeonbuk National University, 54896 Jeonbuk, Jeonju, South Korea; Sagaya Selvam Neethinathan C., School of Chemical Engineering and SKKU Institute of Energy Science and Technology (SIEST), Sungkyunkwan University (SKKU), Suwon, 16419, South Korea, Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Ramakrishnan S., Department of Energy Storage/Conversion Engineering of Graduate School (BK21 FOUR), Hydrogen and Fuel Cell Research Center, Jeonbuk National University, Jeollabuk-do, Jeonju, 54896, South Korea, School of Engineering, Newcastle University, Merz Court, Newcastle Upon Tyne, NE17RU, United Kingdom; Sekar K., Department of Earth Resources Engineering, Kyushu University, Fukuoka, 819-0395, Japan, Sustainable Energy and Environmental Research Laboratory, Department of Chemistry, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603 203, India; Kim A.R., Department of Energy Storage/Conversion Engineering of Graduate School (BK21 FOUR), Hydrogen and Fuel Cell Research Center, Jeonbuk National University, Jeollabuk-do, Jeonju, 54896, South Korea, Department of Life Science, Jeonbuk National University, Jeollabuk-do, Jeonju, 54896, South Korea; Kim D.H., Division of Science Education, Jeonbuk National University, 54896 Jeonbuk, Jeonju, South Korea; Yoo P.J., School of Chemical Engineering and SKKU Institute of Energy Science and Technology (SIEST), Sungkyunkwan University (SKKU), Suwon, 16419, South Korea; Yoo D.J., Department of Energy Storage/Conversion Engineering of Graduate School (BK21 FOUR), Hydrogen and Fuel Cell Research Center, Jeonbuk National University, Jeollabuk-do, Jeonju, 54896, South Korea, Department of Life Science, Jeonbuk National University, Jeollabuk-do, Jeonju, 54896, South Korea
Emerging trends and security in IoT devices
AI integration; Anomaly detection; Blockchain; Connectivity; Data privacy; Device authentication; Edge computing; Emerging trends; IoT; Secure communication; Security
The Internet of Things has rapidly evolved, connecting billions of devices and transforming various industries. This chapter explores the latest emerging trends in IoT devices, focusing on advancements in connectivity, edge computing, and artificial intelligence (AI) integration. As IoT adoption grows, so does the importance of security, given the increasing vulnerabilities and potential threats. This chapter delves into key security challenges, including data privacy, secure communication protocols, and device authentication. It also discusses cutting-edge security solutions, such as blockchain technology and AI-driven anomaly detection, to safeguard IoT ecosystems. By examining both technological advancements and security considerations, this chapter provides a comprehensive overview of the current landscape and future directions for IoT devices. 2026 Elsevier Inc. All rights reserved..
Santhosh Kumar, P.; Etemi, Blerta Prevalla; Rajesh Kanna, R.
IoT Security: Fundamentals and Key Enabling Technologies;pp.275-290
https://doi.org/10.1016/B978-0-443-34125-0.00012-X https://www.scopus.com/pages/publications/105027071557?origin=resultslist
Santhosh Kumar P., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Etemi B.P., Department of Computing and Information Technologies, RIT Kosovo (A.U.K), Rochester Institute of Technology-RIT Global Campus, Kosovo, Prishtina; Rajesh Kanna R., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India
Enhancing Stock Market Forecasting with LLMs, Sentiment Analysis and Technical Indicators
Gemini-1.5-flash; multimodal data; sentiment analysis; Stock market prediction; technical indicators
Forecasting stock market trends remains a complex and demanding endeavor due to the intricate and dynamic nature of financial markets. This study explores the combination of sentiment analysis with technical indicators to improve the accuracy of stock price predictions. The research incorporates stock market and news data spanning from January 2015 to June 2023, ensuring a well-aligned and comprehensive dataset. Data was sourced using the Google News API and the Bombay Stock Exchange (BSE), followed by rigorous preprocessing, which involved handling missing values and standardizing sentiment scores for accuracy and consistency. To analyze sentiment, tools like VADER, TextBlob, and the Gemini-1.5-Flash API were employed, with sentiment scores aggregated at the stock level. Simultaneously, key technical indicators including the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Exponential Moving Averages were derived from stock price patterns. These diverse data points were integrated to predict 14-day closing stock prices, leveraging the Gemini1.5-Flash model for forecasting. The model s performance was assessed using various error metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and Symmetric Mean Absolute Percentage Error (SMAPE). The results indicated strong predictive accuracy for stable stocks while pointing out challenges in forecasting highly volatile stocks. Ultimately, the findings suggest that combining sentiment analysis with technical indicators strengthens stock market trend predictions, offering a solid foundation for future advancements in real-time financial analytics. 2025 IEEE.
Santhosh Kumar, S.; Manjunatha Swamy, C.; Balamurugan, M.
Proceedings of 2025 IEEE International Conference on Contemporary Computing and Communications, InC4 2025;
https://doi.org/10.1109/InC465408.2025.11256269 https://www.scopus.com/pages/publications/105030333276?origin=resultslist
Santhosh Kumar S., Christ University, Dept. of CSE, Bangalore, India; Manjunatha Swamy C., Christ University, Dept. of CSE, Bangalore, India; Balamurugan M., Christ University, Dept. of CSE, Bangalore, India
Stalling angle predictions of symmetric aero foil by flow analysis
aerofoils; angle; NACA 0012; predictions; stalling; symmetric
The computational examination of the 2D subsonic stream over a National Advisory Committee for Aeronautics (NACA) 0012 airfoil at different approaches is done in an ANSYS R14.5 software. The stream elements are acquired by computing the fluid stream conditions of coherence and energy, momentum conservation with the K- model. The present investigation is fundamentally significant, ascribed to the way that the considered aero foil creates lift by moving rapidly through the air, and the examination of the flow over aero foil helps in execution assessment of the flight of the aero foil. In the current work, for a given stream speed with the aero foil set at an approach to the airstream, a pressure gradient among upper and lower wing surfaces exists, which involves the generation of lift, and the lift generated increases up to a certain angle of attack, beyond which the lift decreases, this particular point gives rise to stalling. The distinction in these pressing factor is very important to understand the effect of angle of attack on the lift of the wing. Consequently lift is a significant aspect to be evaluated for stalling angle predictions. The steps associated with assessment of the lift includes forecast of stalling angle at different flow conditions over a symmetric aero foil by modeling the NACA0012 aero foil using the co-ordinates provided by the NACA database and henceforth bringing in it to the ANSYS work bench for meshing, preprocessing followed by the interaction of post processing for different angles of attack. 2022 Author(s).
Santhosh N.; Harish H.V.; Sunil G.S.; Huddar V.B.; Gowda A.C.; Manjunath N.; Afzal A.; Razzak A.; Praveena B.A.
https://doi.org/10.1063/5.0076724 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123981904&doi=10.1063%2f5.0076724&partnerID=40&md5=69c27c5212ec62d6df60a3cdec29e3e0
Santhosh N., Department Of Mechanical Engineering, Mvj College Of Engineering, Near Itpb, Whitefield, Karnataka, Bangalore, 560 067, India; Harish H.V., Department Of Mechanical Engineering, Debre Markos University, Ethiopia; Sunil G.S., Mercedes Benz Research And Development India, Epip Zone, Whitefield, Karnataka, Bangalore, India; Huddar V.B., Department Of Mechanical Engineering, Mvj College Of Engineering, Near Itpb, Whitefield, Karnataka, Bangalore, 560 067, India; Gowda A.C., Department Of Pg Studies, Visvesvaraya Technological University, Muddenahalli, Karnataka, Chikkaballapur, India; Manjunath N., Sciences And Humanities (Engineering), School Of Engineering And Technology, Christ (Deemed To Be University), India; Afzal A., Department Of Mechanical Engineering, P.A. College Of Engineering, Mangalore, Affiliated To Visvesvaraya Technological University, Karnataka, Belagavi, India; Razzak A., Department Of Mechanical Engineering, P.A. College Of Engineering, Mangalore, Affiliated To Visvesvaraya Technological University, Karnataka, Belagavi, India; Praveena B.A., Department Of Mechanical Engineering, Nitte Meenakshi Institute Of Technology, Yelahanka, Karnataka, Bangalore, India
Turbulent Flow in Forced Convection Heat Transfer-Numerical Validation
Correlation; Forced Convection; Heat transfer; Numerical validation; Wind tunnel
Forced convective heat transfer of airflow through circular pipe with constant heat input and different free stream velocities is numerically validated. The significance of the present work is that the suction flow has been employed in the forced convection set up domain kept in the wind tunnel. From first law of thermodynamics and applying the energy balance equation, experimental heat transfer coefficient is determined. Further correlations are used to validate the experimental results. Although correlations provide reasonable estimates from the point of feasibility and accuracy, computational methods are used to estimate the convective heat transfer coefficient. Hence in this paper experimental, theoretical and computational analysis is carried out. The results reveal that the numerical validation is an effective tool from the point of feasibility and accuracy to determine the convective heat transfer coefficient. 2022. MechAero Foundation for Technical Research & Education Excellence.
Santhosh N.; Harish H.V.; Sunil G.S.; Manjunath N.; Manjunath K.; Gowda A.C.; Huddar V.B.
International Journal of Vehicle Structures and Systems, Vol-14, No. 1, pp. 18-21.
MechAero Found. for Techn. Res. and Educ. Excellence
https://doi.org/10.4273/ijvss.14.1.05 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124154006&doi=10.4273%2fijvss.14.1.05&partnerID=40&md5=164bd2833b9aeeb3e0545046a415e368
Santhosh N., Dept. of Mech. Engg, MVJ College of Engg, Karnataka, Bangalore, India; Harish H.V., Dept. of Mech. Engg, Debre Markos University, Ethiopia; Sunil G.S., Mercedes Benz Research and Development India, Karnataka, Bangalore, India; Manjunath N., Dept. of Sci. and Humanities Engg, School of Engg. and Tech, CHRIST (Deemed to be University), Karnataka, India; Manjunath K., Dept. of Mech. Engg, Govt. Engg. College, Karnataka, Hassan, India; Gowda A.C., Dept. of PG Studies, Visvesvaraya Tech. Univ, Chickaballapura, Muddenahalli, India; Huddar V.B., Dept. of Mech. Engg, MVJ College of Engg, Karnataka, Bangalore, India
Predicting Coal Prices: A Machine Learning Approach for Informed Decision-Making
ARIMA; Coal Price; Forecasting; Prediction; Random forest
This research addresses the critical need for accurate coal price prediction in the dynamic global market, crucial for informing strategic decisions and investment choices. With coal playing a vital role in the world energy mix, its price fluctuations impact industries and economies worldwide. The study employs advanced machine learning models, including Linear Regression, Random Forest, SVM, Adaboost, and ARIMA, to enhance prediction precision. Key features such as S&P 500, Crude Oil Price, CPI, Exchange Rates, and Total Electricity Consumption are identified through feature importance analysis. The Random Forest model emerges as the most effective, emphasizing the significance of key variables. Leveraging explainable AI techniques, the study provides transparent insights into model decision-making, offering valuable information for risk management and strategic decision-making in the volatile coal market 2024 IEEE.
Santhosh N.; Mahajan J.; Sharma M.; Hussain D.; Kakani R.; Saxena A.
TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024
Santhosh N., Christ University, Bengaluru, India; Mahajan J., Christ University, Bengaluru, India; Sharma M., Christ University, Bengaluru, India; Hussain D., Christ University, India; Kakani R., Sg Analytics, India; Saxena A., Christ University, Bengaluru, India
Experimental Investigations on Static, Dynamic, and Morphological Characteristics of Bamboo Fiber-Reinforced Polyester Composites
The use of natural fiber-reinforced polymer composites has increased over a period of time, majorly due to the ecosustainability and biodegradability of the composites. Among several grades of natural fibers, bamboo fibers offer numerous environmental and cost benefits and possess excellent mechanical characteristics. The superior properties of the bamboo fibers have triggered the research interests in the domain of bamboo fiber-reinforced polymer composites. Among the polymers, polyesters are long chain molecules made up of atoms arranged in various ways with other elements to form the basic building blocks of a polymeric chain. Polyester is being increasingly employed in today's industrial products due to its inherent advantages. As a result, based on the potential properties of bamboo fibers as reinforcing materials and polyester resin as matrix material, the biocomposites are synthesized by hand lay-up technique and the specimens cut as per the standard dimensions and subjected to mechanical investigations, vibration, and morphological characterization as per the ASTM test methods. The increase in fiber weight content has enhanced flexural, tensile, and impact characteristics and improved the damping characteristics of the composite specimens. The microstructural evaluations have revealed the uniform distribution of the bamboo fibers in the resin, and the morphological studies of the fractured specimens have revealed that the fracture is majorly due to the matrix cracks rather than the fiber debonding, which is a major attribute ascertaining the strong coherent strengthening mechanism brought about by the inclusion of bamboo fiber in the polyester resin. 2022 N. Santhosh et al.
Santhosh N.; Praveena B.A.; Srikanth H.V.; Angadi S.; Gunge A.; Rudra Naik M.; Shankar G.; Ramesha K.; Ravichandran G.
International Journal of Polymer Science, Vol-2022
Santhosh N., Department of Mechanical Engineering, MVJ College of Engineering, Bengaluru, 560067, India; Praveena B.A., Department of Mechanical Engineering, Nitte Meenakshi Institute of Technology, Yelahanka, Bengaluru, 560064, India; Srikanth H.V., Department of Aeronautical Engineering, Nitte Meenakshi Institute of Technology, Yelahanka, Bengaluru, 560064, India; Angadi S., Department of Mechanical Engineering, Nitte Meenakshi Institute of Technology, Yelahanka, Bengaluru, 560064, India; Gunge A., Department of Mechanical Engineering, Nagarjuna College of Engineering & Technology, Bengaluru, 562164, India; Rudra Naik M., Department of Electro-Mechanical Engineering, Arba Minch University, Sawla Campus, Ethiopia; Shankar G., Department of Mechanical Engineering, MVJ College of Engineering, Bengaluru, 560067, India; Ramesha K., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST, Deemed to Be University, Kengeri Campus, Karnataka, Bangalore, India; Ravichandran G., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST, Deemed to Be University, Kengeri Campus, Karnataka, Bangalore, India
Data acquisition using NI LabVIEW for test automation
In a fighter aircraft, the pilot's safety is of utmost importance, and the pressure sensing in the pilot's mask is essential for ensuring the pilot's safety. This innovative solution ensures the swift and accurate measurement of pressure, minimizing the risk of potential hazards and enhancing military aviation safety. Additionally, it provides a robust and reliable solution that can withstand the harsh and challenging conditions often encountered in the field. This chapter explores the advanced capabilities and benefits of utilizing the National Instrument USB-6363, programmed with LabVIEW, in military aviation, highlighting its potential for revolutionizing pressure measurement processes in this critical field. It describes a research study on developing a pressure-sensing system for pilot masks using NI USB 6363 and LabVIEW. 2023, IGI Global.
Santhosh P.; John D.C.; Kodigandla P.; Uma Maheswari V.M.; Sujatha S.
Advances in Artificial and Human Intelligence in the Modern Era, pp. 95-108.
Santhosh P., CHRIST University (Deemed), India; John D.C., CHRIST University (Deemed), India; Kodigandla P., CHRIST University (Deemed), India; Uma Maheswari V.M., Defence Research and Development Organisation (DRDO), India; Sujatha S., CHRIST University (Deemed), India