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Graphical Image Rendering: Modeling, Animation of Facial or Wild Images
Full text linkIn this comparative study, we intend to analyse different methodologies to perform 3-Dimensional modeling and printing, by using raw images as input without any supervision by a human. Since the input consists of only raw images, the foundation of the methods is finding symmetry in images. But the images that seem symmetric are not symmetric due to the perspective effect and utterance of other factors. The method uses factors like depth, albedo, point of view, and lighting from the input image to formulate 3D shapes. A 3D template model with feature points is created, and by deforming the 3D template model, a 3D model of the subject is then reconstructed from orthogonal photos. The number and locations of the proper amount of feature points are derived. Procrustes Analysis and Radial Basis Functions (RBFs) are used for the deformation. Images are then mapped onto the mesh following the deformations for realistic visualization. Characterization of the input image shows an asymmetric cause of shading, lighting, and albedo rendering the symmetry of images. The experiments show that using these methods can give exact 3D shapes of objects like human faces, cars, and cats
Effect of Cyber Vulnerabilities on the Adoption of Self-Driving Vehicles – A Review
Full text linkOne of the leading disruptive technologies in the upcoming technological revolution is Self-Driving vehicles. However, the absence of security is the greatest obstacle to adoption. This study looks at how cybersecurity impacts the adoption of driverless cars. The purpose of this paper is to perform a literature review supporting the in-depth analysis of cybersecurity and its impacts on the slower adoption rate of Self-Driving Vehicles. The study\u27s primary goal is to determine the connection between worries about cybersecurity and the rate of adoption of self-driving vehicles. Driverless vehicles are the most effective and cutting-edge technology in the transportation sector, yet there are barriers to their widespread adoption because of cybersecurity worries. As a result, this study will clarify the cybersecurity issues that contributed to the slower deployment of autonomous vehicles. The NIST Cybersecurity Framework serves as the study\u27s theoretical foundation. This paradigm consistently identifies the barriers to new technology adoption in cybersecurity
Prof. Shiva Prasad U
No full textProf. Shiva Prasad U is Sr. Assistant Professor in the department of aerospace engineering at Sandip University, Nashik, Maharashtra. where he is currently associated as Teaching Faculty and research coordinator for the department of Aero engineering and he also served as a faculty for various national and international universities during his experience of 12 years. Prof. Shiva Prasad had completed his Undergraduate and Post Graduate studies in Aeronautical and Aerospace engineering course from JNTU Hyderabad, and working as research scholar at Veltech University, Chennai, he is currently holding 15 publications in scopus indexed journals and two-chapter publications (scopus) and six Elsevier indexed journal articles. He had Fifteen International Journal Publications, Two International conference papers published (Scopus). He has One Indian Patent published, Two AIP conference proceeding papers and Six Journal Articles published in Elsevier Platform. His Areas of Interest is in Fluid Dynamics, Aerodynamics, Acoustics, Computational Fluid Dynamics, Propulsion, Rockets and Missiles.https://www.interscience.in/mentors/1108/thumbnail.jp
Exploring Machine Learning Techniques for Accurate Software Quality Prediction in Software Development
Full text linkImplementation of a software product is wholly dependent on the quality of the software developed. During the development process, it is difficult for software developers to anticipate the quality of a software product prior to its implementation in real-world applications. Despite this, few studies have been conducted on this topic to date. Most researchers have focused their efforts on predicting software quality using various machine-learning techniques. In addition, software quality prediction must be performed early in the software development life cycle to minimize the developer\u27s effort in creating the software product. In this paper, we conduct an in-depth analysis of the machine-learning techniques used to predict software quality
Dr. Vijayasree
No full textDr. Vijayasree completed her MBA with HR as a specialization from Sri Krishna Devaraya University and completed her Ph.D from University of Hyderabad. She has worked as a faculty in NIT Andhra Pradesh. Her research interests include Human Resource Management, Strategic Management, Strategic Human Resource Management and Organizational Behavior. She has participated and presented papers in many national and international conferences and had published articles in journals. She has attended many workshops and seminars and she has also organized Faculty development programs, workshops and events etc. She qualified the National Eligibility Test for Lectureship and for Junior Research Fellowship conducted by University Grants Commission in India. She was awarded the DAAD fellowship from a New Passage to India Program for research in Germany. She presented a paper in International Research Conference on Business, Economics and Social Sciences in Malaysia. She received a prize in Faculty Development Program on Multivariate data analysis techniques in IIIT, Madhya Pradesh. She received the “Best Paper Award” for her research topic in National Conference on Strategic HR conducted by the Gitam University in Hyderabad.She is the member in management related professional bodies. Currently she is working as Assistant Professor in Presidency University, Bangalore.https://www.interscience.in/mentors/1114/thumbnail.jp
Multi-class Brain Tumor Detection using Convolutional Neural Network
Full text linkBrain tumour detection is one of the most critical and arduous function in the domain of healthcare. Brain tumour, if not detected at an early stage, can be fatal. At the present time, detection and classification of brain tumour is done by the method of Biopsy which is very time-consuming and complex. . By looking at the brain MRI or CT scan, it is possible for the experts to identify whether tumour is present or not and the region of the tumour, but it is difficult to identify the small dissimilarities in the structure of tumour and classify it into types. Hence this manual process gets stuck here for verification of type of tumour. For the sole purpose overcoming the above-mentioned gigantic hurdles we have pursued this research of multi-class brain tumour detection using deep learning. Our project will help doctors in quick decision-making regarding detection of the tumour and its type as well, and due to the early detection of the disease the treatment can be initiated at the right time, resulting in speedy recovery of the patient. We propose a deep learning model employing Convolutional Neural Network architecture which we have implemented using Keras and Tensorflow because it yields to a better performance than the traditional ones. In our research work, CNN gained an accuracy of 94.95%. Further, we have integrated our model with a web-app which we have built using Streamlit. Hence, users can provide their MRI scans via our web-app and get their medical results in a quick and efficient manner
Dr. S. Anand Reddy
No full textDr. Anand Reddy, is graduated in Bachelor of Arts and Bachelor of Philosophy, and post graduated in Master of Business Administration and Master of Counseling and Psychotherapy. He has done his doctoral degree (PHD) on Impact of Servant Leadership on Organizational Citizenship Behavior of an employee.
He has completed a course on Organizational Analysis from Stanford and is certified by XLRI on Leadership and Change Management, certified by Middle earth as Organizational Development Analyst and certified Learning and Development Manager, certified by Oscar Murphy life strategies on Managing Attitudes and Performance Potential, certified by Dale Carnegie for Train the Trainer and certified by Pearson on Critical thinking.
As a researcher he has published over 30 national and international research articles and paper presentations and published two books. He visits colleges and appears in TV shows to share his knowledge. He has received awards at HR tech Summit for employee empowerment, World HRD congress as top HR leaders in Telangana and at international conference for Best international research paper award and nominated for most influential person by IKON. He has 17 years of experience working in various organizations at various levels as HR and L&OD professional. And currently working as head– L&D at Hetero Labs and also is the Chairman of Indian Society for Training and Development – Hyderabad Chapter.https://www.interscience.in/mentors/1092/thumbnail.jp
Dr S Pavan Kumar
No full textDr S Pavan Kumar is an Associate Professor in the School of Humanities, Social Sciences and Management, NITK Surathkal, Karnataka. His educational qualifications include Diploma in Electrical & Electronics Engineering from Govt. Polytechnic affiliated to SBTET, Hyderabad. B.E. in Computer Science & Engineering from Amravati University. M.Tech. in Human Resource Development & Management from IIT Kharagpur in 2006. Doctorate in Human Resource Development & Management from IIT Kharagpur in 2011. He has done several other modern-day courses to keep himself updated with the technology and trend. It includes a certificate course in Business Analytics from Manipal global university and a P.G. Diploma in Geo-spatial technologies for rural development from NIRDPR, Govt of India etc. Dr Kumar has gained rich experience of approximately 25 years in academic institutions as academician, consultancy organizations as a consultant, a Govt. enterprise as a trainee etc. His notable experiences, to name a few, are as follows: He has served as Vice-principal for Kshatriya college of engineering, affiliated with JNT University Hyderabad, before joining NITK Surathkal. Dr Kumar joined NITK Surathkal in 2012 and has been serving to date. In his tenure to date, he played several academic and administrative roles. He served as Head of the department during 2018-2021. He is also serving as the secretary for NITK English medium school run by the professors of the NITK Surathkal. Regarding academic achievements, Dr S P Kumar has received many best research paper awards for his contribution in several national and international conferences. So far, he has published approximately forty research papers in referred journals. He had presented approximately 35 papers at conferences of repute. Dr Kumar completed 3 PhD guidance as on date, and six scholars are currently doing PhD under his supervision. Around 25 MBA students have completed their project work under his guidance. Dr Kumar visited international universities located in countries like Switzerland, Spain for research interaction. Dr Kumar regularly conducts workshops on contemporary topics in various universities as part of outreach activities. A few universities where Dr Kumar has conducted events are Kongu engineering college, Rajagiri college of social sciences, IIT Kharagpur extension center etc. He also serves as a member of the board of studies for management programs as an academic expert. A few notable ones are S.R. University Warangal, PSG Coimbatore etc. He is a reviewer for a few journals for repute. He is also on the advisory board of a few start-up companies. He acted as an examiner for several PhD thesis evaluations. Dr Kumar regularly sets question papers for various premier universities of the country. Dr Kumar’s research interests include organizational development, Human resource management & development, Organizational behavior etc.https://www.interscience.in/mentors/1110/thumbnail.jp
Digital Financial Inclusion in India
Full text linkDigital financial inclusion refers to the internet access to use the formal financial services by excluded and underserved population. E-Banking activity in rural India results in increased usage of financial services and improved living conditions due to the technological involvement in financial inclusion. Financial inclusion, as a result of digital financial services, also promotes economic growth. The purpose of this research is to identify the factors that influence the adoption of digital financial services, as well as people\u27s intentions to use them. This will aid in determining how the correct technology and strategy may help India achieve financial inclusion. The study also tries to identify the role of digital financial inclusion in the country\u27s economic growth. This study is exploratory in nature, with an emphasis on utilizing secondary sources of data related to financial inclusion to better understand new banking technology and people\u27s perceptions on adoption and usage of banking services
Applications of AI and ML in Construction Industry
Full text linkArtificial Intelligence is opening up new avenues in the construction industry. Machine learning is an emerging AI research paradigm, and it is important to making buildings smart. Machine learning technologies have the potential to offer up a plethora of new opportunities in the construction industry, such as site surveillance, automated detection, and intelligent maintenance. The purpose of this study was to examine the new areas where AI and ML are being employed in the construction sector and how their implementation would aid in the improvement of work sites. However, due to the difficulties in collecting annotated data, ML applications face a variety of challenges, especially when applied in a highly complicated building project. This study also looks at how machine learning grew from shallow to deep learning and how it is used in the construction industry. Following the completion of this study, it was determined conclusively that the use of AI and ML in construction projects improves work safety, increases productivity, and so on, and its implications are presently being employed to conduct research around the world