Decrypting Free Expression: AMMA-WCC Conflict and Comment Culture Rattling the Malayalam Film Industry
The chapter examines the gender-power dynamics in the Malayalam film industry through an analysis of a skit, a YouTube video and trolls related to a recent controversy involving the Association of Malayalam Movies Artistes (AMMA) and the Women in Cinema Collective (WCC). This analysis is supported by an exploration of the historical roots of sexism in the industry and a discussion about how it continues to perpetuate sexism in the industry. The study also investigates the emergence of WCC as a response to the actresss molestation case and the subsequent division within the industry. The research focuses on the Sthree Shaktheekaranam skit performed at AMMAs cultural show, a YouTube video, Oru Feminichi Kadha and a sample of trolls which targeted the WCC and women who refuse to comply with AMMAs patriarchal bias. The chapter analyses the content of these representations, highlighting the power play structuring them. The study sheds light on the contradictions and hypocrisy within the industry and its portrayal of progressive values while perpetuating regressive gender norms. 2024 selection and editorial matter, Francis Philip Barclay and Kaifia Ancer Laskar; individual chapters, the contributors.
Gender and Popular Visual Culture in India: Benevolent Sexism and Disguised Discrimination, pp. 179-188.
Aiyappan A., Department of English and Cultural Studies, Christ (Deemed to be University), Bangalore, India
'Katta local' men, pork and violence: Interspatial politics in Angamaly Diaries
The Routledge Handbook of Indian Indie Cinema;pp.120-129
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.4324/9781003612902-16 https://www.scopus.com/pages/publications/105004625642?origin=resultslist
Aiyappan A., Department of English and Cultural Studies, CHRIST (Deemed to be University), Bangalore, India
Kochi Water Metro: Revisiting the Economy-Ecology Paradox of Water Transportation
Blue humanities; Hydrocapitalism; Kochi water metro; Sustainability; Transportation
Kochi, a prominent port city on the southwest coast of Kerala, India, with its waterways, has shaped the geographical and socio-cultural space, aligning them with the politics of the land-water interaction. Popular conceptions of transport have been land-oriented, but with water as the centre, our understanding of day-to-day lived realities changes, demanding new vocabulary. The Kochi Water Metros advent and success are the topics under discussion. Moving from land metro to water metro signals changes in our reading of travel, ecology, energy conservation, direction, temporality, socio-cultural and economic modalities. The article is a project-based study drawing data from interviews, documents, audio-visual images and real-time information to trace and position Kochis Water Metro. With economic and environmental sustainability as the driving forces, the transportation cum tourism aspects of the Water Metro requires an intersectional reading of hydrography, oceanic materialities, and maritime practices. Reading these against the larger context of capitalism and Blue Humanities helps explore how hydrocapitalism becomes the new discourse that positions the ecology-economy paradox. Not only does the Water Metro realign travel and geospatial mapping, but it also begets new directions in maritime developments and conservation within Kochis tourism ventures. 2024 selection and editorial matter, Dr. Sreedevi Santhosh, Dr. Samjaila T. H., Ms. Preethi S., Dr. Steffi Santhana Mary S., Dr. Uma Maheswary and Dr. L. Santhosh Kumar; individual chapters, the contributors.
Aiyappan, Arya; Karthikeyan, Sourav; Seettha, Fahim
Asia's Maritime History and Identity at Cultural Crossroads;pp.25-29
https://doi.org/10.4324/9781003725152-5 https://www.scopus.com/pages/publications/105032923720?origin=resultslist
Aiyappan A., Christ Deemed to be University, Bengaluru, India; Karthikeyan S., Christ Deemed to be University, Bengaluru, India; Seettha F., Christ Deemed to be University, Bengaluru, India
Facile construction of gefitinib-loaded zeolitic imidazolate framework nanocomposites for the treatment of different lung cancer cells
apoptosis; gefitinib; lung cancer; nanocomposites; zeolitic imidazolate framework
Gefitinib (GET) is a revolutionary targeted treatment inhibiting the epidermal growth factor receptor's tyrosine kinase action by competitively inhibiting the ATP binding site. In preclinical trials, several lung cancer cell lines and xenografts have demonstrated potential activity with GET. Response rates neared 25% in preclinical trials for non-small cell lung cancer. Here, we describe the one-pot synthesis of GET@ZIF-8 nanocomposites (NCs) in pure water, encapsulating zeolitic imidazolate framework 8 (ZIF-8). This method developed NCs with consistent morphology and a loading efficiency of 9%, resulting in a loading capacity of 20wt%. Cell proliferation assay assessed the anticancer effect of GET@ZIF-8 NCs on A549 and H1299 cells. The different biochemical staining (Calcein-AM and PI and 4?,6-Diamidino-2-phenylindole nuclear staining) assays assessed the cell death and morphological examination. Additionally, the mode of apoptosis was evaluated by mitochondrial membrane potential (??m) and reactive oxygen species. Therefore, the study concludes that GET@ZIF-8 NCs are pledged to treat lung cancer cells. 2024 International Union of Biochemistry and Molecular Biology, Inc.
Aiyasamy K.; Ramasamy M.; Hirad A.H.; Arulselvan P.; Jaganathan R.; Suriyaprakash J.; Thangavelu I.; Alarfaj A.A.
Biotechnology and Applied Biochemistry, Vol-71, No. 4, pp. 896-908.
ISSN: 8854513; PubMed ID: 38594878; CODEN: BABIE
https://doi.org/10.1002/bab.2585 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190431877&doi=10.1002%2fbab.2585&partnerID=40&md5=e9da2c579f8a809f012961728cb080cc
Aiyasamy K., Department of Biochemistry, Vivekanandha College of Arts and Sciences for Women (Autonomous), Tiruchengode, Tamil Nadu, Namakkal, India; Ramasamy M., Department of Biochemistry, Vivekanandha College of Arts and Sciences for Women (Autonomous), Tiruchengode, Tamil Nadu, Namakkal, India; Hirad A.H., Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia; Arulselvan P., Department of Chemistry, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Tamil Nadu, Chennai, India; Jaganathan R., Preclinical Department, Faculty of Medicine, Universiti Kuala Lumpur, Royal College of Medicine Perak (UniKL-RCMP), Perak, Malaysia; Suriyaprakash J., Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou, China; Thangavelu I., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Alarfaj A.A., Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
Performance analysis of OFF-GRID solar photo voltaic system
MATLAB/SIMULINK; Modeling; ON-grid systems; Performance analysis
Day by day the demand for electrical energy is increasing. We can't rely on conventional energy sources for meeting this increasing demand as they are depleting. So it is necessary to find an alternative method to harness the energy that we are lacking. Solar energy generation seems to be a promising technology for this dilemma. It is environmental friendly and infinite source of energy. Photovoltaic systems can be broadly classified into two-an on-grid system or an off-grid system. The energy generated from a solar PV system is based on several factors like irradiance, types of solar PV used and temperature. Analyzing the existing system efficiency is of prime importance for the characterization of the problems and for the improvements. This study deals with the performance analysis of an on-grid and off-grid system. The analysis is carried out by modeling an existing system in MATLAB/SIMULINK which is already in operation. It can be extended to analyze the grid stability. This study aims the quantification of various performance parameters like power output, losses in the system, system efficiency and the total energy transfer. 2015 IEEE.
IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2015
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICCPCT.2015.7159350 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84945917014&doi=10.1109%2fICCPCT.2015.7159350&partnerID=40&md5=dc157bc3b028db2015ad939ae78bcbbc
Ajan A., Electrical and Electronics Engineering, Christ University Faculty of Engineering, Bangalore, India; Kumar K.P., Research and Development Wing, ANERT, Trivandrum, India
Securing iot networks using an onion routing based approach
Anonymity; Hidden services; IoT; Onion routing; Privacy; Security; TOR
Internet of Things (IoT) comprises of small, connected, power-efficient devices with minimal to average computing power. The devices are autonomous, cyber-physical objects capable of sensing, processing, storing and networking. Due to their connected nature, they are exposed to a huge number of threats and vulnerabilities. A new gateway to ensure anonymity in IoT networks using The Onion Router (TOR) hidden services in a Single-Board Computer (SBC) is proposed in this paper. IAEME Publication.
International Journal of Mechanical Engineering and Technology, Vol-9, No. 3, pp. 987-990.
Ajay Mishael P.S., Christ University, India; Paulose J., Christ University, India
Directional solidification and characterization of InBi1?xSbx crystals
Homogeneous and stoichiometric samples of InBi1?xSbx (x=0, 0.1) crystals have been directionally solidified to explore their suitability for optoelectronic applications. Prior to the growth, the temperature distribution of an indigenously fabricated horizontal furnace has been analysed and optimized to conduct the growth experiments on the basis of phase diagram of the material. Systematic trials have been carried out for several growth runs (48, 60 and 72h) by maintaining an axial temperature gradient of 4, 6 and 8C/cm with the aid of a temperature controller mechanism. The key parameters governing the growth mechanism, composition, phase, and structure of the grown InBi1?xSbx crystals were investigated via X-ray diffraction, scanning electron and atomic force microscopy, Raman and Fourier transform infrared spectroscopy. The presence of secondary phases was ruled out and the average congruent melting points of InBi and InBi0.9Sb0.1 samples were confirmed as 109.43 and 121.13C respectively, by employing differential scanning calorimetric analysis. Investigations on the optical, electrical and mechanical properties of these materials were carried out. Vickers microhardness was found to increase with the Sb incorporation. The average optical band gap computed from the IR transmission spectra was found to be 0.165eV. The results obtained promise that InBi1?xSbx crystals grown by directional solidification are favourable candidates than those grown by other melt methods. 2016, Springer Science+Business Media New York.
Journal of Materials Science: Materials in Electronics, Vol-27, No. 7, pp. 7467-7477.
https://doi.org/10.1007/s10854-016-4724-x https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961629628&doi=10.1007%2fs10854-016-4724-x&partnerID=40&md5=d03b3ca60635591286ea87fe7ac0cbd7
Ajayakumar C.J., Department of Physics, Crystal Research Centre, Christ University, Bengaluru, 560 029, India; Kunjomana A.G., Department of Physics, Crystal Research Centre, Christ University, Bengaluru, 560 029, India
Sublimation process and physical properties of vapor grown ?-In2Se3 platelet crystals
A1. Crystal morphology; A1. X-ray diffraction; A2. Growth from vapor; B2. Semiconducting indium compounds
Indium selenide (?-In2Se3) crystals have been grown by the closed tube sublimation process in the absence of seed crystals and chemical transporting agents. The composition, structure and morphology of the samples grown under different vacuum conditions were examined by energy dispersive analysis, X-ray diffraction, and scanning electron microscope. Structural features of the crystals obtained in a vacuum of 10?3 mbar exhibited a few reflections not belonging to ? phase, whereas X-ray diffraction spectra of the crystals deposited under a vacuum of 10?6 mbar revealed evidence of sharp peaks with high intensities of ?-In2Se3 crystalline phase. When growth runs were performed for 72 h, voids were observed on the surface whereas for a duration of 120 h, platelet crystals were obtained. Optical properties of these samples were investigated using the FT-IR and photoluminescence spectroscopy. The average transmittance of the platelets in the visible and near infrared region of solar spectrum was found to be ?81% and an optical band gap of ?2.05 eV was computed from the transmission spectrum. Photoluminescence spectra of the grown In2Se3 crystals recorded at room temperature using an excitation laser of wavelength 355 nm showed a peak in the near band edge emission (NBE) corresponding to an energy of 2.01 eV. Under an illumination power of 12 mW/cm2, the photocurrent increased linearly with applied voltage and the dark current was found to be ~2.50?9 A for 10 V. These results suggest that the as-grown ?-In2Se3 platelets crystallized from vapor deposition, possess superior optoelectronic properties than the other phases for solar cell applications. 2016 Elsevier B.V.
Journal of Crystal Growth, Vol-453, pp. 99-105.
https://doi.org/10.1016/j.jcrysgro.2016.08.004 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84982107442&doi=10.1016%2fj.jcrysgro.2016.08.004&partnerID=40&md5=2fd8481fb7b7804837368b68a879f256
Ajayakumar C.J., Crystal Research Centre, Department of Physics, Christ University, Bengaluru, 560 029, India; Kunjomana A.G., Crystal Research Centre, Department of Physics, Christ University, Bengaluru, 560 029, India
Gamma irradiation effects in InBi0.8Te0.2 crystals grown by horizontal directional freezing
Crystal growth; Dielectric properties; Hardness; Irradiation; Optical properties
The high-energy gamma-ray irradiation treatment using Co-60 isotope offers the possibility of engineering mechanical and optoelectronic properties of InBi0.8Te0.2 crystals. Tellurium-doped indium bismuthide (InBi) crystals were prepared by horizontal directional freezing technique. Dose-dependent modifications in structure, composition and surface topographical features have been analyzed by X-ray powder diffraction, X-ray energy-dispersive analysis, transmission electron and atomic force microscopy, respectively. Dielectric constant and dielectric loss were found to increase with the cumulative dose of radiation, and a shift in the ferroelectric transition temperature (T0c0) from 405 to 410 K was observed for 25 kGy. Upon irradiation, there is an enhancement in microhardness (H0V0), yield stress (sigma; 0y0) and stiffness constant (C0110). The optical transmittance was decreased by 12.45%, resulting in a reduction in the optical band gap from 0.210 eV to 0.198 eV. These results indicate the suitability of InBi00.80Sb00.20 crystals for low-wavelength infrared applications. The Chinese Society for Metals and Springer-Verlag Berlin Heidelberg 2015.
Acta Metallurgica Sinica (English Letters), Vol-28, No. 10, pp. 1205-1213.
Ajayakumar C.J., Department of Physics, Crystal Research Centre, Christ University, Bangalore, 560 029, India; Kunjomana A.G., Department of Physics, Crystal Research Centre, Christ University, Bangalore, 560 029, India
Growth and characterization of InBi1-xSbx InBi1-xTex and γ-In2Se3 crystals
Theory and innovating practices of crystal growth heralded cutting edge breakthroughs in the production of proficient crystals towards the advancement of science and technology. Unique characteristics and band structure provide great flexibility for structural design and band gap engineering of indium bismuthide (InBi) compounds. Substitution of antimony and tellurium elements results in the transition of InBi to a semiconducting state with narrow energy gap, making it suitable for optoelectronic devices. Need of eco-friendly sustainable processes concerning the elimination of hazardous materials bring and#947;-In2Se3 in the forefront of photovoltaic industry, due to its wide band gap as well as n-type conductivity. Thus, realizing the immense potential attributes of InBi1-xSbx, InBi1-xTex (x = 0-0.2) and and#947;-In2Se3 crystals, the present research was focussed on pioneering their growth and characterization.Horizontal directional solidification (HDS), being the versatile, inexpensive melt growth technique, was employed for obtaining InBi1-xSbx, and InBi1-xTex (x = 0-0.2) crystals. On the other hand, closed tube sublimation (CTS) was found to be most effective for deposition of and#947;-In2Se3 crystals. Platelet and spherulitic morphologies of and#947;-In2Se3 crystals have been grown by the vapor deposition for the first time, under different growth environments. Morphology, structure and quality of the as-grown crystals were studied, employing various scientific procedures such as X-ray diffraction (XRD), energy dispersive analysis by X-rays (EDAX), scanning electron microscopy (SEM), atomic force microscopy (AFM) and transmission electron microscopy (TEM). Transport parameters, melting point and phase purity have been evaluated with the aid of Hall effect measurement, four probe set up, differential scanning calorimetry (DSC) and Raman spectroscopy. Vickers indentation testing was utilized for the evaluation of microhardness and deformation characteristics.
Zero Waste Package Free Shops in India: The Green Road Ahead
package-free shops; Sustainable development; zero-waste
Package-free stores or zero waste stores are emerging as an innovative sustainable concept these days.This paper attempts to analyze the modus operandi of package free stores in India, their main features and the challenges that they face.Data was collected from five package-free shops in India among which one store has multiple branches across the nation.As of today, these stores cover almost the entire population.The findings suggest that these stores promote sustainable consumption among the people and also meet three important sustainable development goals (SDGs).They uplift the local economy and contribute to the economic prosperity of local residents and businesses by supporting local and regional farmers.It provides toxic-free products contributing to a healthy society by renouncing plastic completely.It protects the environment thereby increasing the growth of the local economy.Since the movement towards sustainable economic practices is inadequate, proactive steps should be taken to adopt innovative practices. 2022 Scientific Publishers. All rights reserved.
Indian Journal of Environmental Protection, Vol-42, No. 12, pp. 1437-1444.
Ajayan A.C., Department of Economics, Deemed to Be University, CHRIST, Karnataka, Bangalore, 560 029, India; Varkey R.S., Department of Economics, Deemed to Be University, CHRIST, Karnataka, Bangalore, 560 029, India
Prediction of Facial Emotions using Deep Learning and Machine Learning Techniques
CK+Dataset; Deep Learning; Emotion Prediction; Machine Learning; Model Comparison; Pre-processing Techniques
Facial expression prediction has gained considerable attention in recent years, particularly because of its applications in human-computer interaction. This paper compares a wide range of deep learning and machine learning models for the prediction of face emotion using the CK+ dataset proposed by Cohn-Kanade. The dataset is characterized by seven classes of emotions represented by the labels, namely surprise, happiness, disgust, anger, sadness, fear, and contempt, on 784 training, 98 validation, and 99 testing images. To further improve model performance, preprocessing techniques were employed that enhanced data efficiency. To increase variability in the data and reduce overfitting, all images were scaled to a 48*48 pixel resolution, pixel values were scaled to be between 0 and 1 for uniformity and the following data augmentation techniques were implemented: 10-degree rotation, horizontal flip, 0.15 zoom. The five models that were tested were CNN, SVM, VGG16, InceptionV3 and VGG19. The results demonstrate the high accuracy achieved by the CNN model which showed an accuracy of 98.98%, 99% and 99% in training, validation and test respectively. The SVM classifier got an accuracy of 99%. Both InceptionV3 and VGG19 on the other hand achieved competitive testing accuracy values of 90.91% and 97.98% respectively, while VGG16 got tested and reached an accuracy of 85.86%. 2025 IEEE.
2025 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2025;
https://doi.org/10.1109/ICDSAAI65575.2025.11011786 https://www.scopus.com/pages/publications/105007976191?origin=resultslist
Ajayraj C., Christ University, Department of CSE, Bangalore, India; Ms A., Christ University, Department of CSE, Bangalore, India; Pk S., Christ University, Department of CSE, Bangalore, India
An Effective Deep Learning Classification of Diabetes Based Eye Disease Grades: An Retinal Analysis Approach
Classification; Deep learning; Densenet; Diabetes retinopathy; Feature extraction; Feature selection; Particle Swarm Optimization
Diabetic Retinopathy (DR) is a common misdiagnosis of diabetes mellitus, which damages the retina and impairs eyesight. It can lead to vision impairment if it is not caught early. Tragically, DR is an unbreakable cycle, and treatment only serves to reinforce the perception. Early detection of DR and effective treatment can significantly lower the risk of visual loss. In comparison to PC-aided conclusion frameworks, the manual analysis process used by ophthalmologists to diagnose DR retina fundus images takes a lot of time, effort, and money and is prone to error. As of late, profound learning has become quite possibly the most well-known procedure that has accomplished better execution in numerous areas, particularly in clinical picture examination and classification. Thereby, this paper brings an effective deep learning-based diabetes-based retinography in which the following are the stages: a) Data collection from MESSIDOR which contains 1200 images classified into 4 levels and graded from 03 followed by b) Preprocessing using grayscale normalized data. Then followed by c) feature extraction using Discrete Wavelet Transform (DWT), d) feature selection using Particle Swarm Optimization (PSO) and finally given for e) classification using Densenet 169. Experimental states that the proposed model outperforms and effectively classified grades compared to other state-of-art models (accuracy:0.95, sensitivity:0.96, specificity;0.97). 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Ajesh F.; Jims A.; Alapatt B.P.; Philip F.M.
Lecture Notes in Networks and Systems, Vol-649 LNNS, pp. 234-244.
Springer Science and Business Media Deutschland GmbH
Ajesh F., Department of Computer Science and Engineering, Sree Buddha College of Engineering, Kerala, Alappuzha, India; Jims A., JAIN (Deemed-to-be University), Bangalore, India; Alapatt B.P., CHRIST (Deemed to be University), Delhi-NCR, India; Philip F.M., JAIN (Deemed-to-be University), Bangalore, India
IOT Wearable Medical Device for Heart Disease Recognition Based ML and DL: A Classification Approach
deep learning; Heart Disease prediction; IoT; long short-term memory; Supervised learning
In the past few years, heart disease has become the foremost worldwide contributor to mortality. This ailment, with a profound effect on the functioning of the heart, leads to issues such as infections in the coronary arteries and diminished blood vessel performance. These complications can culminate in severe unlikely events like heart attacks and strokes. In India alone, approximately one person succumbs to heart disease every minute. To curb the fatalities stemming from cardiac disorders, there is an urgent need for a swift and efficient detection strategy. IoT sensors are utilized in conjunction with Machine Learning (ML) and Deep Learning (DL) techniques to identify heart disease. In this research, we have successfully applied IoT devices and a sensor network to detect heart diseases. This study introduces a medical IoT device designed to gather heart data from patients both before and after the onset of heart disease. This continuously transmitted data is processed using RBF, MLP, and Bi-LSTM models for predicting heart disease. The deep learning approach utilizes past analyses to learn critical features related to heart disease, achieving efficiency in handling complex data. After conducting a series of experiments, we evaluate the systems performance using metrics such as f-measure, sensitivity, specificity, loss function, and Receiver Operating Characteristic (ROC) curves. The HDRBi-LSTM method, in combination with IoT-based analysis, achieves an impressive accuracy rate of 99.5% with minimal time complexity (5 s), effectively reducing heart disease mortality by simplifying the diagnosis of this condition. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Ajesh, F.; Philip, Felix M.; Jims, Anupama; Alapatt, Bosco Paul
Lecture Notes in Networks and Systems;Volume;1243 LNNS;pp.353-363
https://doi.org/10.1007/978-3-031-81080-0_32 https://www.scopus.com/pages/publications/105004252580?origin=resultslist
Ajesh F., Department of Computer Science and Engineering, Sree Buddha College of Engineering, Kerala, Alappuzha, India; Philip F.M., Department of CS & IT Jain (Deemed-to-be University), Bangalore, India; Jims A., Department of Computer Science and Engineering, CVV Institute of Science and Technology, Kerala, India; Alapatt B.P., CHRIST (Deemed to be University), Delhi-NCR, India
Retention of a Community Healthcare Worker for Three Decades in a Rural and Remote CHC of Bolba in Jharkhand: A Case Study
Community Healthcare Worker (CHW); external; influence; internal; Retention; Rural and Remote; Scarcity
The dearth of healthcare personnel in rural areas is a global problem. Even developed countries are struggling to meet demand. In such circumstances, identifying a health worker who worked for a single CHC for three decades necessitates deeper exploration. Individual case studies were employed to investigate the phenomenon, then thematically evaluated using QAD Miner Lite following a lengthy telephonic interview. The study's findings revealed that a rural upbringing, social class, economic factors, and behaviourism influenced the altruism of Community Healthcare Workers (CHWs). As a result, external and internal factors influenced CHW to service rural areas. But extrinsic factors worked in tandem with intrinsic factors to influence CHW's willingness to serve the rural areas. Rural healthcare shortages exist despite the National Rural Health Mission (NRHM) execution. A substantial amount of the population's health is entrusted to 20 percent of health workers, who account for disproportionately 75.05 percent of rural health outcomes. The Electrochemical Society
ECS Transactions, Vol-107, No. 1, pp. 14609-14622.
https://doi.org/10.1149/10701.14609ecst https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130571048&doi=10.1149%2f10701.14609ecst&partnerID=40&md5=b40b3a2d7449e7ede5b07df3ae53bcd1
Ajit K., School of Business and Management Studies, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Raghavendra A.N., School of Business and Management Studies, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India
Enhancing the performance in education by implementing gamification
E-learning; Enhanced learning; Game elements; Gamification; Gamified learning; Tool based learning
The gaming industry is growing rapidly in the present generation along with the advancement of technology. Gaming has captured all the young minds with its high and realistic graphics. What makes the gaming industry so attractive is that the players have complete freedom in the game. Freedom to fail, they can try until they succeed another feature is that game is user-centric. Consequently, a lot of research is been in the field of education to increase student's engagement towards studies. The main aim of this paper is to combine these game elements with learning to see if it yields better results. A quantitative approach is used to analyze the student's performance and interest in learning. Using these game elements in education will encourage the students to learn as well as have the flexibility to complete the course at their own pace. Copyright 2019 American Scientific Publishers All rights reserved.
Journal of Computational and Theoretical Nanoscience, Vol-16, No. 45813, pp. 2609-2613.
https://doi.org/10.1166/jctn.2019.7938 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068554427&doi=10.1166%2fjctn.2019.7938&partnerID=40&md5=ac5122e3774e509e2ce7384bb30026a0
Ajith R., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, 560084, India; Vinay M., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, 560084, India
Basalt Fiber Composites in High-Performance Sports Equipment
This chapter explores the revolutionary role of basalt fiber composites in the development and production of high-performance sports equipment. Basalt fibers, produced from naturally occurring volcanic rocks, are a strong alternative to conventional reinforcement materials such as carbon and glass fibers. Their outstanding resistance to heat, moisture, and chemicals is complemented by their remarkable mechanical properties, including high tensile strength, impact resistance, and good vibration damping. These attributes make basalt fiber composites particularly suited for sports equipment subjected to dynamic loads and harsh environments, such as bicycles, tennis rackets, skis, snowboards, and surfboards. The chapter explores the most modern scientific and commercial advancements, demonstrating how basalt fiber composites can improve user comfort, reduce weight, and increase performance, durability, and safety. Illustrative examples compare basalt fiber composites with traditional materials to demonstrate their cost-effectiveness, reduced environmental impact, and successful applications. The manufacturing processes and potential challenges in adopting basalt fibers are discussed in detail. Finally, the chapter addresses emerging trends and prospects, positioning basalt fiber composites as a key material in the evolution of sustainable, high-performance sports equipment. This comprehensive overview provides valuable insights for researchers, manufacturers, and sports technology innovators. 2026 American Chemical Society
Ajith, Athira J; Kumaran, Reshma; Nair, Yamuna
ACS Symposium Series;Volume;1524;pp.423-457
https://doi.org/10.1021/bk-2026-1524.ch012 https://www.scopus.com/pages/publications/105037884663?origin=resultslist
Ajith A.J., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Kumaran R., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Nair Y., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India
The Lunar Gravitational-wave Antenna: mission studies and science case
gravitational wave detectors; gravitational waves / sources
The Lunar Gravitational-wave Antenna (LGWA) is a proposed array of next-generation inertial sensors to monitor the response of the Moon to gravitational waves (GWs). Given the size of the Moon and the expected noise produced by the lunar seismic background, the LGWA would be able to observe GWs from about 1 mHz to 1 Hz. This would make the LGWA the missing link between space-borne detectors like LISA with peak sensitivities around a few millihertz and proposed future terrestrial detectors like Einstein Telescope or Cosmic Explorer. In this article, we provide a first comprehensive analysis of the LGWA science case including its multi-messenger aspects and lunar science with LGWA data. We also describe the scientific analyses of the Moon required to plan the LGWA mission. 2025 The Author(s)
Ajith, Parameswaran; Seoane, Pau Amaro; Sedda, Manuel Arca; Arcodia, Riccardo; Badaracco, Francesca; Banerjee, Biswajit; Belgacem, Enis; Benetti, Giovanni; Benetti, Stefano; Bobrick, Alexey; Bonforte, Alessandro; Bortolas, Elisa; Braito, Valentina; Branchesi, Marica; Burrows, Adam; Cappellaro, Enrico; Ceca, Roberto Della; Chakraborty, Chandrachur; Subrahmanya, Shreevathsa Chalathadka; Coughlin, Michael W.; Covino, Stefano; Derdzinski, Andrea; Doshi, Aayushi; Falanga, Maurizio; Foffa, Stefano; Franchini, Alessia; Frigeri, Alessandro; Futaana, Yoshifumi; Gerberding, Oliver; Gill, Kiranjyot; Giovanni, Matteo Di; Giudice, Ines Francesca; Giustini, Margherita; Gler, Philipp; Harms, Jan; van Heijningen, Joris; Iacovelli, Francesco; Kavanagh, Bradley J.; Kawamura, Taichi; Kenath, Arun; Keppler, Elisabeth-Adelheid; Kobayashi, Chiaki; Komatsu, Goro; Korol, Valeriya; Krishnendu, N.V.; Kumar, Prayush; Longo, Francesco; Maggiore, Michele; Mancarella, Michele; Maselli, Andrea; Mastrobuono-Battisti, Alessandra; Mazzarini, Francesco; Melandri, Andrea; Melini, Daniele; Menina, Sabrina; Miniutti, Giovanni; Mitra, Deeshani; Mor-Fraile, Javier; Mukherjee, Suvodip; Muttoni, Niccol Olivieri, Marco; Onori, Francesca; Papa, Maria Alessandra; Patat, Ferdinando; Perali, Andrea; Piran, Tsvi; Piranomonte, Silvia; Pol, Alberto Roper; Pookkillath, Masroor C.; Prasad, R.; Prasad, Vaishak; Rosa, Alessandra De; Chowdhury, Sourav Roy; Serafinelli, Roberto; Sesana, Alberto; Severgnini, Paola; Stallone, Angela; Tissino, Jacopo; Tkal?i?, Hrvoje; Tomasella, Lina; Toscani, Martina; Vartanyan, David; Vignali, Cristian; Zaccarelli, Lucia; Zeoli, Morgane; Zuccarello, Luciano
Journal of Cosmology and Astroparticle Physics;Volume;2025;Issue;1;Article No.;108;
All Open Access; Green Open Access; Hybrid Gold Open Access
https://doi.org/10.1088/1475-7516/2025/01/108 https://www.scopus.com/pages/publications/85217886740?origin=resultslist
Ajith P., International Centre for Theoretical Science, Tata Institute of Fundamental Research, Bangalore, 560089, India; Seoane P.A., Universitat Politnica de Valcia, C/Vera s/n, Valcia, Spain, Max-Planck Institut f Extraterrestrische Physik, Garching, Germany, Higgs Centre for Theoretical Physics, Edinburgh, United Kingdom; Sedda M.A., Gran Sasso Science Institute (GSSI), Via Michele Iacobucci 2, L'Aquila, I-67100, Italy, INFN, Laboratori Nazionali del Gran Sasso, Via Giovanni Acitelli 22, Assergi, I-67100, Italy, INAF Osservatorio Astronomico d'Abruzzo, Via Mentore Maggini, s.n.c., Teramo, I-64100, Italy; Arcodia R., MIT Kavli Institute for Astrophysics and Space Research, 70 Vassar Street, MA, Cambridge, 02139, United States; Badaracco F., Dipartimento di Fisica, Universitdi Genova, via Dodecaneso 33, Genova, I-16146, Italy, INFN Sez. di Genova, via Dodecaneso 33, Genova, I-16146, Italy; Banerjee B., Gran Sasso Science Institute (GSSI), Via Michele Iacobucci 2, L'Aquila, I-67100, Italy, INFN, Laboratori Nazionali del Gran Sasso, Via Giovanni Acitelli 22, Assergi, I-67100, Italy; Belgacem E., Dartement de Physique Thrique, Universitde Gene, 24 quai Ansermet, Gene 4, CH-1211, Switzerland, Gravitational Wave Science Center (GWSC), Universitde Gene, Geneva, CH-1211, Switzerland; Benetti G., Dipartimento di Fisica e Astronomia Galileo Galilei, Universitdi Padova, Vicolo dellOsservatorio 3, Padova, I-35122, Italy; Benetti S., INAF - Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, Padova, I-35122, Italy; Bobrick A., Physics department, Technion, Israel Institute of Technology, Haifa, 3200002, Israel; Bonforte A., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania Osservatorio Etneo Piazza Roma, Catania, 2 95125, Italy; Bortolas E., Dipartimento di Fisica G. Occhialini, Universitdegli Studi di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, INFN, Sezione di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, INAF - Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, Padova, I-35122, Italy; Braito V., INAF Osservatorio Astronomico di Brera, via Brera 28, Milano, I-20121, Italy, Dipartimento di Fisica, Universitdi Trento, Via Sommarive 14, Trento, I-38123, Italy; Branchesi M., Gran Sasso Science Institute (GSSI), Via Michele Iacobucci 2, L'Aquila, I-67100, Italy, INFN, Laboratori Nazionali del Gran Sasso, Via Giovanni Acitelli 22, Assergi, I-67100, Italy, INAF Osservatorio Astronomico d'Abruzzo, Via Mentore Maggini, s.n.c., Teramo, I-64100, Italy; Burrows A., Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane, Princeton, 08544, NJ, United States; Cappellaro E., INAF - Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, Padova, I-35122, Italy; Ceca R.D., INAF Osservatorio Astronomico di Brera, via Brera 28, Milano, I-20121, Italy; Chakraborty C., Manipal Centre for Natural Sciences, Manipal Academy of Higher Education, Alevoor Road, Manipal, 576104, India; Subrahmanya S.C., Institute of Experimental Physics, University of Hamburg, Luruper Chaussee 149, Hamburg, 22761, Germany; Coughlin M.W., School of Physics and Astronomy, University of Minnesota, 116 Church Street SE, Minneapolis, 55455, MN, United States; Covino S., INAF Osservatorio Astronomico di Brera, via Brera 28, Milano, I-20121, Italy; Derdzinski A., Department of Life and Physical Sciences, Fisk University, 1000 17th Avenue N., Nashville, 37208, TN, United States, Department of Physics & Astronomy, Vanderbilt University, 2301 Vanderbilt Place, Nashville, 37235, TN, United States; Doshi A., Department of Physics and Astronomy, Rice University, 6100 Main St, Houston, TX, United States; Falanga M., International Space Science Institute (ISSI), Hallerstrasse 6, Bern, 3012, Switzerland, Physikalisches Institut, University of Bern, Sidlerstrasse 5, Bern, 3012, Switzerland; Foffa S., Dartement de Physique Thrique, Universitde Gene, 24 quai Ansermet, Gene 4, CH-1211, Switzerland, Gravitational Wave Science Center (GWSC), Universitde Gene, Geneva, CH-1211, Switzerland; Franchini A., INFN, Sezione di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, Institut f Astrophysik, Universit Zich, Winterthurerstrasse 190, Zich, CH-8057, Switzerland; Frigeri A., INAF Istituto di Astrofisica e Planetologia Spaziali (IAPS), Via Fosso del Cavaliere 100, Roma, I-00133, Italy; Futaana Y., Solar System Physics and Space Technology Programme, Swedish Institute of Space Physics, Kiruna, SE98128, Sweden; Gerberding O., Institute of Experimental Physics, University of Hamburg, Luruper Chaussee 149, Hamburg, 22761, Germany; Gill K., Center for Astrophysics Harvard & Smithsonian, 60 Garden Street, Cambridge, 02138-1516, MA, United States; Giovanni M.D., La Sapienza Universitdi Roma, Dipartimento di Fisica, Piazzale Aldo Moro 5, Roma, 00185, Italy, INFN, Sezione di Roma, Piazzale Aldo Moro 5, Roma, 00185, Italy; Giudice I.F., Department of Physics "Ettore Pancini", Universitdegli Studi di Napoli Federico II, Via Cinthia, 21, Napoli, I-80126, Italy, INAF, Osservatorio Astronomico di Capodimonte, Salita Moiariello 16, Naples, I-80131, Italy; Giustini M., Centro de Astrobiolog (CAB), CSIC, INTA, ESAC campus, Camino Bajo del Castillo s/n, Villanueva de la Cada, 28692, Spain; Gler P., Institute of Geodesy and Geoinformation Science, Technical University Berlin, Kaiserin-Augusta-Allee 104, Berlin, 10553, Germany; Harms J., Gran Sasso Science Institute (GSSI), Via Michele Iacobucci 2, L'Aquila, I-67100, Italy, INFN, Laboratori Nazionali del Gran Sasso, Via Giovanni Acitelli 22, Assergi, I-67100, Italy; van Heijningen J., Department of Physics and Astronomy, VU Amsterdam, De Boelelaan 1081, Amsterdam, 1081 HV, Netherlands, Nikhef, Science Park 105, Amsterdam, 1098 XG, Netherlands; Iacovelli F., Dartement de Physique Thrique, Universitde Gene, 24 quai Ansermet, Gene 4, CH-1211, Switzerland, Gravitational Wave Science Center (GWSC), Universitde Gene, Geneva, CH-1211, Switzerland; Kavanagh B.J., Instituto de Fica de Cantabria (IFCA, UC-CSIC), Av. de Los Castros s/n, Santander, 39005, Spain; Kawamura T., Institut de Physique du Globe de Paris, CNRS, UniversitParis Cit Paris, France; Kenath A., Department of Physics and Electronics, Christ University, Hosur Road, Bangalore, 560029, India; Keppler E.-A., Dipartimento di Fisica, Universitdegli Studi di Trieste, via Valerio 2, Trieste, 34127, Italy; Kobayashi C., Centre for Astrophysics Research, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, United Kingdom; Komatsu G., International Research School of Planetary Sciences, Universitd'Annunzio, Viale Pindaro 42, Pescara, 65127, Italy; Korol V., Max-Planck-Institut f Astrophysik, Karl-Schwarzschild-Stra 1, Garching, 85748, Germany; Krishnendu N.V., International Centre for Theoretical Science, Tata Institute of Fundamental Research, Bangalore, 560089, India; Kumar P., International Centre for Theoretical Science, Tata Institute of Fundamental Research, Bangalore, 560089, India; Longo F., Dipartimento di Fisica, Universitdegli Studi di Trieste, via Valerio 2, Trieste, 34127, Italy, INFN, Sezione di Trieste, via Valerio 2, Trieste, 34127, Italy; Maggiore M., Dartement de Physique Thrique, Universitde Gene, 24 quai Ansermet, Gene 4, CH-1211, Switzerland, Gravitational Wave Science Center (GWSC), Universitde Gene, Geneva, CH-1211, Switzerland; Mancarella M., Dipartimento di Fisica G. Occhialini, Universitdegli Studi di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, INFN, Sezione di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, Aix Marseille Univ, Universitde Toulon, CNRS, CPT, Marseille, France; Maselli A., Gran Sasso Science Institute (GSSI), Via Michele Iacobucci 2, L'Aquila, I-67100, Italy, INFN, Laboratori Nazionali del Gran Sasso, Via Giovanni Acitelli 22, Assergi, I-67100, Italy; Mastrobuono-Battisti A., GEPI, Observatoire de Paris, PSL Research University, CNRS, Place Jules Janssen, Meudon, 92190, France, Dipartimento di Fisica e Astronomia Galileo Galilei, Universitdi Padova, Vicolo dellOsservatorio 3, Padova, I-35122, Italy; Mazzarini F., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Via C. Battisti 53, Pisa, I-56125, Italy; Melandri A., INAF Osservatorio Astronomico di Roma, via Frascati 33, Monte Porzio Catone, Roma, I-00078, Italy; Melini D., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Roma 1, Via di Vigna Murata 605, Roma, I-00143, Italy; Menina S., SYRTE, Observatoire de Paris, UniversitPSL, CNRS, Sorbonne Universit LNE, 77 Av. Denfert Rochereau, Paris, 75014, France; Miniutti G., Centro de Astrobiolog (CAB), CSIC, INTA, ESAC campus, Camino Bajo del Castillo s/n, Villanueva de la Cada, 28692, Spain; Mitra D., Dept. of Physics, St Xavier's College (Autonomous), Kolkata, India; Mor-Fraile J., Heidelberger Institut f Theoretische Studien (HITS), Schloss-Wolfsbrunnenweg 35, Heidelberg, 69118, Germany; Mukherjee S., Department of Astronomy and Astrophysics, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai, 400005, India; Muttoni N., Dartement de Physique Thrique, Universitde Gene, 24 quai Ansermet, Gene 4, CH-1211, Switzerland, Gravitational Wave Science Center (GWSC), Universitde Gene, Geneva, CH-1211, Switzerland; Olivieri M., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, viale Berti Pichat 6-2, Bologna, I-40127, Italy, INAF Istituto di Astrofisica e Planetologia Spaziali (IAPS), Via Fosso del Cavaliere 100, Roma, I-00133, Italy; Onori F., INAF Osservatorio Astronomico d'Abruzzo, Via Mentore Maggini, s.n.c., Teramo, I-64100, Italy; Papa M.A., Max Planck Institute for Gravitational Physics, Albert Einstein Institute, Leibniz University, Callinstra 38, Hannover, D-30167, Germany; Patat F., European Southern Observatory, Karl-Schwarzschild-Str. 2, Garching b. Mchen, 85748, Germany; Perali A., School of Pharmacy, Physics Unit, University of Camerino, Via Madonna delle Carceri 9B, MC, Camerino, I-62032, Italy, INAF, Section of Camerino, Via Gentile III da Varano 7, MC, Camerino, I-62032, Italy; Piran T., Racah Institute of Physics, The Hebrew University, Givat Ram, Jerusalem, 91904, Israel; Piranomonte S., INAF Osservatorio Astronomico di Roma, via Frascati 33, Monte Porzio Catone, Roma, I-00078, Italy; Pol A.R., Dartement de Physique Thrique, Universitde Gene, 24 quai Ansermet, Gene 4, CH-1211, Switzerland, Gravitational Wave Science Center (GWSC), Universitde Gene, Geneva, CH-1211, Switzerland; Pookkillath M.C., Centre for Theoretical Physics and Natural Philosophy, Mahidol University, Nakhonsawan Campus, Phayuha Khiri, Nakhonsawan, 60130, Thailand; Prasad R., International Centre for Theoretical Science, Tata Institute of Fundamental Research, Bangalore, 560089, India; Prasad V., International Centre for Theoretical Science, Tata Institute of Fundamental Research, Bangalore, 560089, India; Rosa A.D., INAF Istituto di Astrofisica e Planetologia Spaziali (IAPS), Via Fosso del Cavaliere 100, Roma, I-00133, Italy; Chowdhury S.R., Research Institute of Physics, Southern Federal University, Rostov Oblast, Rostov on Don, 344090, Russian Federation, Department of Physics, Vidyasagar College, 39, Sankar Ghosh Lane, Kolkata, India; Serafinelli R., INAF Osservatorio Astronomico di Roma, via Frascati 33, Monte Porzio Catone, Roma, I-00078, Italy; Sesana A., Dipartimento di Fisica G. Occhialini, Universitdegli Studi di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, INFN, Sezione di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy, INAF Osservatorio Astronomico di Brera, via Brera 28, Milano, I-20121, Italy; Severgnini P., INAF Osservatorio Astronomico di Brera, via Brera 28, Milano, I-20121, Italy; Stallone A., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, viale Berti Pichat 6-2, Bologna, I-40127, Italy; Tissino J., Gran Sasso Science Institute (GSSI), Via Michele Iacobucci 2, L'Aquila, I-67100, Italy, INFN, Laboratori Nazionali del Gran Sasso, Via Giovanni Acitelli 22, Assergi, I-67100, Italy; Tkal?i? H., Research School of Earth Sciences, The Australian National University, 142 Mills Road, Canberra, Australia; Tomasella L., INAF - Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, Padova, I-35122, Italy; Toscani M., Dipartimento di Fisica G. Occhialini, Universitdegli Studi di Milano-Bicocca, Piazza della Scienza 3, Milano, I-20126, Italy; Vartanyan D., Carnegie Observatories, 813 Santa Barbara St, Pasadena, 91101, CA, United States; Vignali C., Dipartimento di Fisica e Astronomia Augusto Righi, Alma Mater Studiorum, Universitdegli Studi di Bologna, Via Gobetti 93/2, Bologna, I-40129, Italy, INAF, Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Gobetti 93/3, Bologna, I-40129, Italy; Zaccarelli L., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, viale Berti Pichat 6-2, Bologna, I-40127, Italy; Zeoli M., Centre for Cosmology, Particle Physics and Phenomenology (CP3), UCLouvain, Chemin du Cyclotron 2, Louvain-la-Neuve, B-1348, Belgium, Precision Mechatronics Laboratory, ULie, A&M Dept., All de la Douverte 9, B52/Quartier Polytec 1, Lie, B-4000, Belgium; Zuccarello L., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Via C. Battisti 53, Pisa, I-56125, Italy
A study of failure prediction of Indian banks using various machine learning algorithms - An examination of predictive accuracy
Bankruptcy; Feature selection; Logistic Regression; Machine learning; Support Vector Machines
Banks play a key role in strengthening the economy; hence their survival is very important. It is necessary to evaluate the failure probability of banks correctly based on the factors associated with it. Over half of the assets in the financial sector in India are held by the banking sector, which holds a strong position. Phased implementation of financial sector reforms has resulted in an exciting moment of rapid transformation for Indian banks. The study here focuses on the establishment of machine learning approach to compute and compare the extent of bankruptcy based on the accuracy measure-Support Vector Machine classification, Random Forest, Logistic Regression, Nae Bayes classification using the data of 250 Indian banks having qualitative variables from 2015 to 2020. The feature selection in this paper is based on correlation and relief algorithms. The explanatory features of the dataset are drawn by implementing a two-step feature selection technique and the selected features are fed and further used for prediction using the Random Forest technique, Logistic Regression, Support Vector Machine, and Nae Bayes classification techniques. The results reveal, that the support vector machine shows a score of 99.8% forecasting the highest accuracy. This research serves as a foundation for the decisions made by a variety of stakeholders, including analysts, policymakers, shareholders, and bank management, and it facilitates the comparison of the qualitative ratios of bankruptcy. The goal is to develop a prediction system that will allow the firms and businesses to be categorized according to the level of risk. 2025 Author(s).
AIP Conference Proceedings;Volume;3191;Issue;1;Article No.;40007;
https://doi.org/10.1063/5.0248387 https://www.scopus.com/pages/publications/85218678853?origin=resultslist
Ajith S., Department of Statistics and Data Science, CHRIST (Deemed to Be University), Bengaluru, India; Joshi H., Department of Statistics and Data Science, CHRIST (Deemed to Be University), Bengaluru, India
The intersection of artificial intelligence and consultancy services: Assessing adoption, ethical implications, and overcoming challenges
The integration of AI has emerged as a transformative force, reshaping how organizations operate. This research paper explores the multifaceted aspects of AI integration in consultancy, delving into the implications, ethical considerations, opportunities, and challenges it presents. Further, the study highlights the interrelations between AI adoptions, its impact on the quality and efficiency of services provided, and ethical concerns related to its implementation. A descriptive research study was conducted among 140 respondents from consultancy firms, freelancers, and AI experts. The data was analyzed using correlation and regression. The study results showed a robust advantageous correlation between factors influencing AI adoption and the excellent performance of consultancy services. This underscores the need for consultancy firms to prioritize and invest in projects that sell AI adoption to deliver advanced services to clients and underscores the transformative potential of AI integration in consultancy, with significant implications for organizational practices. 2025, IGI Global Scientific Publishing. All rights reserved.
Ajitha, H.; Dheepa, T.; Jaiwant, Sunanda Vincent
Retail Innovations in Business Models;pp.369-385
https://doi.org/10.4018/979-8-3693-7620-1.ch018 https://www.scopus.com/pages/publications/105005472808?origin=resultslist
Ajitha H., Christ University, India; Dheepa T., Christ University, India; Jaiwant S.V., Christ University, India