Accepted Papers
- STRESS BUSTER
P Ramyaa,SRM university, India
ABSTRACT
Human stress is a person's response to the demands and pressures that arise from external sources, as well as those that are self imposed. Physiologists demonstrate that symptoms of high stress levels are increased heart rate, rapid breathing, increased sweating, cool skin, cold hands and feet, tense muscles etc. According to the galvanic skin response theory, resistance and stress are inversely proportional. When the stress level increases, the skin's resistance decreases. Stress Buster is a small, wireless, networked skin conductance sensor to detect stress faced by a person. Many existing systems make use of sensors that are inflexible and often physically attached to supporting computers. In contrast, Stress buster allows an additional degree of flexibility by providing wireless networking capabilities using ZigBee module, along with the Case Based Reasoning (CBR) and fuzzy logic. The voltage signals are sent into the fuzzy logic controller which allows a the interpretation to be made based on a range. Also the CBR technique allows us to compare previous case values, thereby giving a more accurate result. Further, based on the output the computer takes a control action. This paper describes the novel design attributes of this hand-held sensor.
- SURVEY OF SOFT COMPUTING TECHNIQUES IN NEURO SCIENCE
1D.K. Sreekantha,2T.M. Girish,3R.V.Kulkarni,1NMAMIT, Nitte, Karnataka,India,2Basaveshwar Science College, Bagalkot, Karnataka,India,3CSIBER, Kolhapur, Maharastra,India
ABSTRACT
The improvement of health and nutritional status of the society has been one of the thrust areas for social developments programmes of the country. The present states of healthcare facilities in India are inadequate when compared to international standards. The average Indian spending on healthcare is much below the global average spending. Indian healthcare Industry is growing at the rapid pace of more than 18%, the fastest in the world. The prospects for Indian healthcare are to the tune of USD 40 billion, while global market is USD 1660 trillion. India has all the prospects to become medical tourism destination of the world, because it has a large pool of low-cost scientifically trained technical personal and is one of the favoured counties for cost effective healthcare. As per the reports of Global Burden of Neurological Disorders Estimations and Projections survey there is big shortage of neurologist in India and around the world. So Authors would like to develop an innovative IT based solution to help doctors in rural areas to gain expertise in Neuro Science and treat patients like expert neurologist. This paper aims to survey the Soft Computing techniques in treating neural patient's problems used throughout the world.
- Fuzzy Logic Based Image Encryption For Confidential Data Transfer Using (2,2) Secret
Sharing Scheme-Review
Miss.Hinal M. Mudia, Prof.Miss.P.V.Chavan, India
ABSTRACT
This paper introduces the fuzzy
logic based image encryption for confidential data
transfer using (2,2) secret sharing scheme. Fuzzy
means vague, uncertain, ambiguous. It makes
encryption and decryption method difficult to
guess hence fuzzy logic using secret sharing
concept is finer and enhanced way of image
encryption and data is more secure. Visual
Cryptography is a special encryption technique to
hide information in images in such a way that it
can be decrypted by the human vision. The (2,2)
secret sharing scheme provides secured
authentication. In secret sharing, random looking
shares when brought together recreate the secret.
As (2,2) divides the secret information into two
shares.
- APPLICATION OF FUZZY REGRESSION METHODOLOGY IN TRANSPORTATION ENGINEERING
Marisamynathan S,Indian Institute of Technology Bombay,India
ABSTRACT
Signalized intersection is one of the key components of road network. Its operations considerably affect the performance of the whole road system. The performance of signalized intersection measured in terms of Level of Service (LOS). Existing studies on LOS at signalized intersections are based on conventional regression model and thus the models are failed to estimate accurate LOS of signalized intersections. This paper explores the most popular fuzzy regression model and the application of fuzzy model in developing LOS model at signalized intersections. The proposed methodology derived in two steps. First step, membership function are developed and the fuzzy input values are defuzzified in crisp value by applying centroid method. Second step, fuzzy least square method is applied to develop the model. The proposed methodology is applied in two different applications in transportation engineering problem such as vehicle LOS and Pedestrian LOS model development. Finally MAPE values are compared between conventional regression model and fuzzy regression model and the results are shown that fuzzy regression models provided more precise and reliable solutions. The proposed new methodology in this paper can be used to develop LOS model transportation field.
- Fuzzy complement based PSO variant for Acoustic Echo Cancellation System
Diana D.C and Joy Vasantha Rani S.P
,Madras Institute of Technology , India
ABSTRACT
This paper proposes a particle swarm optimization(PSO) variant based on fuzzy complement to eliminate the echo and non-linearity that occur in hands-free communication scenarios which degrades the voice quality during a conversation in wired and wireless phones. The overall input/output relation of the echo path exhibits nonlinear distortions. The overall non-linearity can be removed using an adaptive filter where an adaptive algorithm is used to adjust the filter coefficients. The adaptive filter attempts to synthesize a model of the non-linearity of the speaker and echo path at its output. PSO is a structured stochastic optimization technique which is nowadays used as an adaptive algorithm to search for the optimum filter weights to minimize the mean square error (MSE). PSO is a derivative free algorithm that optimally updates the weights of the echo canceller and performs best to eliminate nonlinearities whereas the gradient based algorithms perform worst in nonlinear conditions. Inertia weight is one of the PSO's critical parameters which control the global and local search of PSO. A large inertia weight can be utilized to enhance global search capabilities of PSO and small inertia weight can enhance local search abilities of PSO for fast convergence. So choosing a proper inertia weight can improve the performance of the algorithm and reduces the nonlinearities effectively. This enhanced performance of the proposed new inertia weight updation method is proved through simulation analysis.
- FUZZY APPROACHES TO CONTEXT VARIABLES IN FUZZY GEOGRAPHICALLY WEIGHTED CLUSTERING
1Nguyen Van Minh,2Le Hoang Son,1Hanoi University of Natural Resources and Environment,Hanoi, Vietnam,2Vietnam National University,Hanoi, Vietnam
ABSTRACT
Fuzzy Geographically Weighted Clustering (FGWC) is considered as a suitable tool for the analysis of geo-demographic data that assists the provision and planning of products and services to local people. Context variables were attached to FGWC in order to accelerate the computing speed of the algorithm and to focus the results on the domain of interests. Nonetheless, the determination of exact, crisp values of the context variable is a hard task. In this paper, we propose two novel methods using fuzzy approaches for that determination. A numerical example is given to illustrate the uses of the proposed methods.
Courtesy
Technically
Sponsored by
