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ARCHITECTURAL ANALYSIS OF CONTEXT-AWARE SYSTEMS IN PERVASIVE COMPUTING ENVIRONMENT
Divya Udayan J,HyungSeok Kim 한국HCI학회 2012 한국HCI학회 학술대회 Vol.2012 No.1
Context aware system are those systems that are aware about the environment and perform productive functions automatically by reducing human computer interaction(HCI). In this paper, we present common architecture principles of context-aware systems to explain the important aspects common to most context aware architectures. We introduce various existing context aware architectures and have compared those architectures based on the design principles and have done an analyses on the different elements in the context aware computing based on the presented system. We also propose a new architecture based on broker-centric middleware and using ontology reasoning mechanism together with an effective behavior based context agent that would be suitable for the design of context-aware architectures in future systems.
Divya Rana,Fathimunisa Begam Afsar Hanfy 대한산업공학회 2019 Industrial Engineeering & Management Systems Vol.18 No.3
There has been an increase in demands where businesses are now required to respond to the threat of changing technology and the gradual increase in climatic variations, on the basis of the influential position that businesses are known to enjoy within the global community. If businesses are able to integrate people, technology, strategy and procedures while implementing initiatives that respond to climatic changes, it would result in creation of value in the long-term, which is a powerful too. However, there is a need to understand the threats that are presented by changing technology and climatic variations, which is the key focus of this research. The objective was to identify the business opportunities and challenges faced by businesses in KSA in the face of changing technology and climate change and whether there was an association between the two. The research adopted a quantitative methodology where the findings revealed that climatic variations can substantially impact businesses in terms of financial reporting, organizational reputation, legal responsibilities and supply chain and operations. It also found that business performance was also positively influenced by changing technology. The findings also revealed that changes in technology could also positive influence climatic variations. Thus, it can be concluded that changing technology and climatic variations bright forth substantial risks that could present opportunities as well as significant challenges for businesses operating in KSA.
Fractal Based Method on Hardware Acceleration for Natural Environments
Divya Udayan J,HyungSeok Kim,Jun Lee,Jee-In Kim 한국정보기술융합학회 2013 JoC Vol.4 No.2
Natural scenes from the real world are highly complex, such that the modeling and rendering of natural shapes, like mountains, trees and clouds, are very difficult and time consuming and require a huge amount of memory. Intuitively, the critical characteristics of natural scenes are their selfsimilarity properties. Motivated by the self-similarity feature of the natural scenes that surround us, we present a hardware accelerated fractal based rendering method for natural environments. To illustrate the problem that classical geometry has in dealing with natural objects, we considered the basic fractal example as the Mandelbrot set which is a 2D structure. We examined the serial algorithm of this set and devised a parallel algorithm for implementation on a massive parallel graphics processing unit (GPU) using the computer unified device architecture (CUDA) programming model. We also considered the modeling of 3D fractals such as terrains and evaluated its performance both in terms of execution time and hardware acceleration. Performance is evaluated in terms of execution time and it was observed that a parallel implementation of the method on a GeForce GTX 650 GPU is on average 2X times faster than its sequential implementation. The running behavior of the system at various system states is also evaluated to strongly support our approach.
ONTOLOGY OF 3D VISUALIZATION FOR URBAN NAVIGATION
Divya Udayan J,HyungSeok Kim 한국HCI학회 2013 한국HCI학회 학술대회 Vol.2013 No.1
Mobile information systems especially navigation based systems are increasingly growing due to its popularity and availability among the common public. The drawback of the current system is that, it is not user-friendly and needs high computational resource. The same information is provided for all users without distinction of their familarity and experience with the city. Also, it requires high computational resource for visualizing highly populated city models. In this paper, we address the issues related to the urban visual simulation by proposing a formal representation of the visualization techniques in the form of ontology of semantic information. Also, we propose different level of details (LOD) mechanism for different users depending on the user intension and expected services. The final outcome of this research is believed to provide a fundamental information structure for cognitive urban navigation depending on the user.
Multiclass Least Squares Twin Support Vector Machine for Pattern Classification
Divya Tomar,Sonali Agarwal 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.6
This paper proposes a Multiclass Least Squares Twin Support Vector Machine (MLSTSVM) classifier for multi-class classification problems. The formulation of MLSTSVM is obtained by extending the formulation of recently proposed binary Least Squares Twin Support Vector Machine (LSTSVM) classifier. For M-class classification problem, the proposed classifier seeks M-non parallel hyper-planes, one for each class, by solving M-linear equations. A regularization term is also added to improve the generalization ability. MLSTSVM works well for both linear and non-linear type of datasets. It is relatively simple and fast algorithm as compared to the other existing approaches. The performance of proposed approach has been evaluated on twelve benchmark datasets. The experimental result demonstrates the validity of proposed MLSTSVM classifier as compared to the typical multi-classifiers based on ‘Support Vector Machine’ and ‘Twin Support Vector Machine’. Statistical analysis of the proposed classifier with existing classifiers is also performed by using Friedman’s Test statistic and Nemenyi post hoc techniques.