Soft Computing, Artificial Intelligence and Applications

Secured Framework for Pervasive Healthcare Monitoring Systems N Rukma Rekha1 and M.S.PrasadBabu2 1University of Hyderabad, India 2Andhra University, India ABSTRACT Pervasive Healthcare Monitoring System (PHMS)’ is one of the important pervasive computingapplications aimed at providing healthcare servicesto all the people through mobile communicationdevices. Pervasive computing devices are resourceconstrained devices such as battery power, memory,processing power and bandwidth. In pervasive environment data privacy is a key issue. In thisapplication a secured frame work is developed for receiving the patient’s medical data periodically,updates automatically in Patient Record Database and generates a Checkup Reminder. In the presentwork a light weight asymmetric algorithm proposed by the authors [26] is used for encrypting the datatoensure data confidentiality for its users. Challenge response onetime password mechanism is applied forauthentication process KEYWORDS Pervasive compu...

Active Controller Design for the Hybrid Synchronization of Hyperchaotic Zheng and Hyperchaotic Yu Systems Sundarapandian Vaidyanathan Vel Tech Dr.RR & Dr.SR Technical University, India ABSTRACT This paper deals with a new research problem in the chaos literature, viz. hybrid synchronization of a pair of chaotic systems called the master and slave systems. In the hybrid synchronization design of master and slave systems, one part of the systems, viz. their odd states, are completely synchronized (CS), while the other part, viz. their even states, are completely anti-synchronized (AS) so that CS and AS coexist in the process of synchronization. This research work deals with the hybrid synchronization of hyperchaotic Zheng systems (2010) and hyperchaotic Yu systems (2012). The main results of this hybrid synchronization research work have been proved using Lyapunov stability theory. Numerical examples of the hybrid synchronization results are shown along with MATLAB simulations fo...

Multi-Population Methods with Adaptive Mutation for Multi-Modal Optimization Problems Imtiaz Korejo1, Shengxiang Yang2, Kamran Brohi3, Z.U.A.Khuhro4 1University of Sindh, Pakistan 2De Montfort University, United Kingdom ABSTRACT This paper presents an efficient scheme to locate multiple peaks on multi-modal optimization problems by using genetic algorithms (GAs). The premature convergence problem shows due to the loss of diversity, the multi-population technique can be applied to maintain the diversity in the population and the convergence capacity of GAs. The proposed scheme is the combination of multi-population with adaptive mutation operator, which determines two different mutation probabilities for different sites of the solutions. The probabilities are updated by the fitness and distribution of solutions in the search space during the evolution process. The experimental results demonstrate the performance of the proposed algorithm based on a set of benchmark problems in comp...

Advanced Human Behavioral Cues Detection: A Method in Social Signal Processing K.Sunilkumar1 and T.KishoreKumar2, 1VITS Warangal, India 2NIT Warangal, India ABSTRACT Social Signal Processing (SSP) is the new research domain that aims at understanding social interactions and social intelligence. The essence of social intelligence is the ability to recognize human social signals and behaviors cues (verbal and non-verbal). We present a unified model for non-verbal behavioral cues SSP under the categories of face detection like eyes-mouth-lips-ears-nose, emotional assessments like anger-happy-sadness-neutral and physical appearance like height (short-average-tall), attractiveness (smartness) and body shape(slim-normal-flat) in real-world cluttered images which is one of the method in social signal processing. It is rather difficult task to detect and interpret temporal patterns of nonverbal behavioral cues in a given context. Our main objective is to detect non-verbal behavioral cues ...

Digital Image Retrieval Using Combination of Texture, Shape and Colour Features Mohammad Saberi, Farshad Tajeripour and Shervan Fekri-Ershad Shiraz University, Iran ABSTRACT A robust method is proposed in this paper to retrieve digital images using combination of color, texture and shape features. The proposed method consists of three stages. Shape detection is done based on TopHat transform to detect and crop object part of the image in the first stage. The second is included a texture feature extraction algorithm using color local binary patterns (CLBP) and local variance features together. Finally, to retrieve mostly closing matching images to the query, log likelihood ratio is used as non-similarity ratio. The performance of the proposed approach is evaluated using Corel and Simplicity image sets and it compared by some of other well-known approaches in terms of precision and recall which shows the superiority of the proposed approach. Shift invariant, Low noise sensitivity, ro...

Select Optimal Chemical Detection Equipments Using Fuzzy Decision Making Method Ying Bai1 and Dali Wang2 1Johnson C. Smith University, USA 2Christopher Newport University, USA ABSTRACT The purpose of this research is to develop a universal model with a practical system to evaluate, identify and select an optimal system or device to perform the desired task from a large collection of available systems that have multiple objectives based on a fuzzy multiple criteria decision making model (FMCDMM). As an example, here we are using this research to identify and select an optimal detection system or device to detect hazardous chemical materials. KEYWORDS Fuzzy multi-criteria decision making, optimal evaluations, explosive detection equipments. Original Source URL: http://airccse.org/journal/ijscai/papers/0213scai01.pdf http://airccse.org/journal/ijscai/current2013.html

Comparing of Switching Frequency on Vector Controlled Asynchronous Motor Yılmaz Korkmaz1, Fatih Korkmaz2, Ismail Topaloglu2 and Hayati Mamur2 1Gazi University, Turkey 2Cankırı Karatekin University, Turkey ABSTRACT Nowadays, asynchronous motors have wide range use in many industrial applications. Field oriented control (FOC) and direct torque control (DTC) are commonly used methods in high performance vector control for asynchronous motors. Therefore, it is very important to identify clearly advantages and disadvantages of both systems in the selection of appropriate control methods for many industrial applications. This paper aims to present a new and different perspective regarding the comparison of the switching behaviours on the FOC and the DTC drivers. For this purpose, the experimental studies have been carried out to compare the inverter switching frequencies and torque responses of the asynchronous motor in the FOC and the DTC systems under different working conditions. Th...

Motion Planning and Controlling Algorithm for Grasping and Manipulating Moving Objects in the Presence of Obstacles Ali Chaabani1, Mohamed Sahbi Bellamine2 and Moncef Gasmi2 1University of Manar, Tunisia 2University of Carthage, Tunisia ABSTRACT Many of the robotic grasping researches have been focusing on stationary objects. And for dynamic moving objects, researchers have been using real time captured images to locate objects dynamically. However, this approach of controlling the grasping process is quite costly, implying a lot of resources and image processing.Therefore, it is indispensable to seek other method of simpler handling… In this paper, we are going to detail the requirements to manipulate a humanoid robot arm with 7 degree-of-freedom to grasp and handle any moving objects in the 3-D environment in presence or not of obstacles and without using the cameras. We use the OpenRAVE simulation environment, as well as, a robot arm instrumented with the Barrett hand. We also...

Distributed Fault-Tolerant Event Detection for Non-Symmetric Errors in Wireless Sensor Networks Nandita Das1, B. Victoria Jancee2 and S. Radha3 1,3SSN College of Engineering,India, 2St. Joseph's College of Engineering, India ABSTRACT Wireless sensor network (WSN) are powered by batteries to perform various sensing tasks in a given environment. The measurements made by the sensors are sometimes unreliable and erroneous due to noise in the sensor or hardware failure. For a large scale WSN to be economically feasible, it is important to ensure that the faulty node does not affect the overall behaviour of the system. In this paper a binary faulttolerant event detection technique has been proposed for the non-symmetric errors and its performance has been analysed. Theoretical analysis and simulation show that almost 97 percent of faults can be corrected even when 10 percent sensor nodes are faulty. KEYWORDS Non-Symmetric Errors, Fault Tolerance, Event Detection Original Source U...

Self Learning Real Time Expert System Latha B. Kaimal, Abhir Raj Metkar and Rakesh G C-DAC,India ABSTRACT In a Power plant with a Distributed Control System ( DCS ), process parameters are continuously stored in databases at discrete intervals. The data contained in these databases may not appear to contain valuable relational information but practically such a relation exists. The large number of process parameter values are changing with time in a Power Plant. These parameters are part of rules framed by domain experts for the expert system. With the changes in parameters there is a quite high possibility to form new rules using the dynamics of the process itself. We present an efficient algorithm that generates all significant rules based on the real data. The association based algorithms were compared and the best suited algorithm for this process application was selected. The application for the Learning system is studied in a Power Plant domain. The SCADA interface was develo...