Empowering Cybersecurity: A Deep Dive into AI-Driven Security Intelligence Modelling
Smart Incubator for Empowering Poultry Farmers by Maximizing Egg Hatching Success
Early Disease Detection of Black Gram Plant Leaf using Cloud Computing Based YOLO V8 Model
Data Retrieval in Cancer Documents using Various Weighting Schemes
Securing Healthcare Data in Smart Cities: A Machine Learning Approach
According to a survey by world health organization (WHO), an abysmally more number of people living in rural area have access to specialist care and advice in the developing countries. This opens up the possibility of using information and communication technology effectively in the 21st century. Telemedicine is currently being used to bridge the physical distances between patients in remote areas and medical specialists around the world. The recent advances in broadband technology by facilitating anytime, anywhere access. It is not required doctor to be present physically at the hospital center. In this paper, we present an overview of traditional telemedicine system, cloud computing based framework for telemedicine. We clearly indicate the architecture of telemedicine cloud and discuss the applicability of recent wireless technologies in large-scale telemedicine systems.
This study investigated the influence of environmental dynamism in the relationship between planning process and SISP success in manufacturing and non-manufacturing SBs. Based on responses from 118 South Africa CIOs or head of IS/IT, our empirical investigation provided the following results: of all eleven hypotheses tested, nine were supported and two were not. The findings of study demonstrate that environmental dynamism is more influential in non-manufacturing enterprises than in manufacturing enterprises, the implementation of planning process is strongly leading to the success of SISP in manufacturing enterprises than in non-manufacturing and environmental dynamism influence more the relationship between planning process and SISPS in manufacturing enterprises than in non-manufacturing enterprises. The implications and limitations of this study are also discussed.
Transmission network expansion planning (TNEP) is an important component of power system planning. It determines the characteristic and performance of the future electric power network and influences the power system operation directly. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and including investment cost into the fitness function constraints using binary particle swarm optimization (BPSO) algorithm. The particle swarm optimization is a recently developed evolutionary algorithm (EA) based on the swarm behavior in the nature and has a strong ability to find the most optimistic results. The motivation for using the BPSO technique is to reduce design effort and find an optimum planning network. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. The proposed idea has been tested on the Garvers network. The results evaluation shows that the network will possess maximum efficiency economically.
The Watershed transformation has recently become a popular tool for image segmentation. The purpose of image segmentation is to divide an original image into homogeneous regions. There exist several approaches to implement image segmentation. In this paper, Modified Multi-Scale Morphological Watershed Segmentation Algorithm of 2D Images Using Hill Climbing Techniques is introduced as a method of image segmentation. It is a fast and flexible algorithm for computing watersheds in digital gray scale images. A review of watersheds and related notion is first presented and the major methods to determine watersheds are discussed. The present algorithm is based on Hill Climbing process analogy, in which the flooding of the water in the picture is efficiently simulated using a queue of pixels. It is proved that the accuracy of this algorithm is superior to that of the existing implementations. In addition, its strongest point is that it is faster than any other watershed algorithm. Mainly it reduces the over — segmentation.
Power consumption has always been a crucial factor in deciding the performance of a computing system. The existing factors that serve as a yardstick to measure the performance include Space complexity and Time complexity. However, towards a Greener era of computing, it is the need of the hour to consider High Performance Systems that are energy efficient and thereby lesser heat and carbon emitters. The conventional approach ,on the software grounds, include redefining algorithms that focus on the reduction on the time complexity and Space Complexity of the program .We, hereby, propose a novel approach that takes into consideration the Power Optimization ,with respect to making an algorithm more efficient ,as an equally important issue for a greener solution towards energy efficient programs.
Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this review paper, we present a survey of cloud computing, highlighting its key concepts and architectural principles. The aim of this review paper is to provide a better understanding of the cloud computing environment and identify important research directions in this increasingly important area.
