Journal of Intelligent & Fuzzy Systems - Volume 32, issue 4

Authors: Dhanya, N.M. | Kousalya, G. | Balakrishnan, P.

Article Type: Research Article

Abstract: Due to the advancement of mobile technology, a large number of computationally intensive applications are created for smart phones. But the limitations of battery and processing power of smart phones are making it inferior to laptops and desktop computers. Mobile Cloud Offloading (MCO) allows the smart phones to offload computationally intensive tasks to the cloud, making it more effective in terms of energy, speed or both. Increased networking capacity due to the availability of high speed Wi-Fi and cellular connections like 3G/4G makes offloading more efficient. Even then, the choice of offloading is not always advisable, because of the highly …dynamic context information of mobile devices and clouds. In this paper, we propose a dynamic decision making system, which will decide whether to offload or do the tasks locally, depending on the current context information and the optimization choice of the user. Metrics are developed for time, energy and combination of time and energy to assess the proposed system. A test bed is implemented and the results are showing improvements from the currently existing methods. Show more

Keywords: Mobile cloud, context aware offloading, decision making, application partitioning, offloading prediction

DOI: 10.3233/JIFS-169251

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3081-3089, 2017

Authors: Mathaba, Sizakele | Adigun, Matthew | Oladosu, John | Oki, Okikayode

Article Type: Research Article

Abstract: Radio Frequency Identification (RFID) uses sensors to enable communication among things or objects in what is called Internet of Things (IoT) technology. Web 2.0 tools, on the other hand, are used on electronic devices (phones, PDAs, computers, etc.) to transmit data contents over the internet. In this study, we used a synergy of both technologies to enhance inventory control. We proposed software architecture which combined RFID and Web 2.0 tool advantages. The proposed architecture was used to develop an inventory management software prototype focused on enterprises in developing countries in Africa, specifically South Africa. The inventory management prototype was developed …and was able to detect misplaced products and low stock levels, and send notification on Twitter to update inventory managers on mobile phone. Scalability measurements of the software were taken to validate the performance of the software prototype. The findings show that the system scaled reliably with increasing numbers of items read. The contribution of this work was compared to existing literature and our findings are presented in this paper. Real- life evaluation for a specific industry will be necessary to further reveal what improvements would be required to make this architecture more relevant. Behavioural study of users will also be required to further determine the economic and social benefits of this approach. Show more

Keywords: Internet of Things (IoT), Radio Frequency Identifier (RFID), inventory management, software architecture, social network

DOI: 10.3233/JIFS-169252

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3091-3101, 2017

Authors: Oki, Olukayode A. | Olwal, Thomas O. | Mudali, Pragasen | Adigun, Matthew

Article Type: Research Article

Abstract: Spectrum decision is the capability of Secondary Users to choose the best accessible spectrum band to satisfy a user’s Quality of Service (QoS) requirements. Spectrum decision comprises three primary functions; spectrum characterization, spectrum selection and dynamic reconfiguration of cognitive radio. The study of dynamic reconfiguration of transceiver parameters in spectrum decision making has been motivated because of its importance to the realization of efficient spectrum utilization and management in distributed mobile cognitive radio networks. Spectrum decision making in a distributed cognitive radio network is crucial, so as to ensure that an appropriate frequency and channel bandwidth are selected to meet …the QoS requirements of different types of applications and to maintain the spectrum quality. In attempting to address the issue of dynamic reconfiguration of transceiver parameters in decision making for cognitive radio networks, different approaches can be found in the literature. However, due to some of the challenges associated with these approaches such as high computational complexity, ambiguity, non-repeatability and non-deplorability of these classical approaches, researchers are still trying to explore other techniques that will be less ambiguous, more efficient, more understandable and easier to deploy in a highly dynamic environment like distributed cognitive radio networks. Hence, this paper reviews the existing approaches, identifies the challenges and proposes a biologically inspired optimal foraging approach to address the decision making problem and other problems relating to the existing approaches. Show more

Keywords: Cognitive radio, distributed, foraging, spectrum, reconfiguration

DOI: 10.3233/JIFS-169253

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3103-3110, 2017

Authors: Rajarajeswari, PL. | Karthikeyan, N.K.

Article Type: Research Article

Abstract: The lifetime of a Wireless Sensor Network (WSN) depends on the efficiency of the Cluster Head (CH) selection techniques that address most of the significant issues related to network management. The existing energy based CH selection mechanisms consider that all the participating sensors are trustworthy. Conversely, the trust-based CH selection schemes assume that the sensor nodes are energy efficient. But, these assumptions of energy factor or trust assessment made by the CH selection mechanisms may not be true and the Residual Energy (RE) of the sensors may not be the sole factor to identify an effective CH in a WSN. …Hence, this paper presents hybrid integrated energy and trust assessment based forecasting model known as Hyper-geometric Energy Factor based Semi-Markov Prediction Mechanism (HEFSPM) for effective CH election so as to improve the lifetime of the network. From the simulation results, it is inferred that HEFSPM is superior in improving the lifetime of the network to a maximum extent of 22% than the existing CH election mechanisms considered for investigation. Show more

Keywords: Semi-markov process, Cluster Head, Hyper-geometric distribution, energy, trust assessment, prediction probability

DOI: 10.3233/JIFS-169254

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3111-3120, 2017

Authors: Kalra, Bhawna | Sharma, J.B.

Article Type: Research Article

Abstract: In multi carrier OFDM systems parameters like speed, throughput and hardware area can be improved by using efficient Fast Fourier Transform approach. In this paper an area efficient and high speed 32 bit floating point FFT processor for OFDM using Vedic multiplication process is presented. Proposed FFT processor is based on memory based architecture and utilizing Urdhavatiraykbhyam sutra for Vedic multiplication. As the number of inbuilt multipliers available in FPGAs are limited, hence external multiplication module are required in the multicarrier OFDM systems, in order to reduce the complexity of FPGA implementation. By the use of Vedic multiplication process in …FFT of OFDM high throughput with smaller area can be achieved. Simulation results explain that the proposed scheme is having high speed and throughput. Show more

Keywords: FFT, OFDM, Vedic multiplication

DOI: 10.3233/JIFS-169255

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3121-3128, 2017

Authors: Bhullar, Rohit K. | Pawar, Lokesh | Bajaj, Rohit | Manocha, Amit K.

Article Type: Research Article

Abstract: Parallel Processing has been a widely studied field, used and implemented in computational systems. Many different types of topologies of processors have been implemented and their performance has been analyzed. The processor technology keeps evolving so their computational capability must be utilized accordingly when employed in parallel systems. In this article, new intra-parallel processor architectures (segmented/heterogeneous) has been used and an intelligent co-operative protocol has been implemented to optimally utilize the parallel components of the parallel processor design. More precisely a friendship based intelligent load balancing strategy has been designed and implemented to maximally utilize the parallel processor, which takes …care of overloading and starvation problems and makes intelligent decisions regarding job scheduling. Context switching policies must also be designed carefully to stop performance degradation and with intelligent techniques this switching time can be reduced considerably. Work proposed in this article performs and executes load stability with feasible priori information about processors utilization, depending upon and based on this metric value the entire process space is partitioned among different categories. Based on the load status and state of affairs, processors are categorized and labeled and a suitable set out of those is figured-out that act as buddy for others and handles incoming process queue for overloaded processors. Further history and statistics of each processors is maintained and is utilized to make intelligent future scheduling decisions. Show more

Keywords: Intelligent systems, parallel environment, intra-processor parallelism, load stability, job scheduling strategy

DOI: 10.3233/JIFS-169256

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3129-3142, 2017

Authors: Soumya, T. | Thampi, Sabu M.

Article Type: Research Article

Abstract: The night video fusion algorithms integrate the visuals captured by a security surveillance camera, which in turn improve the visual perception. The recent development in night fusion research focused on fusing both illuminated and non-illuminated areas simultaneously however, the natural color of the light area may be lost. Moreover, the contrast of the illuminated regions decreases because of the dark pixels surrounding those regions. Hence, the color and contrast should be improved to obtain the actual color of the illuminated regions. We propose a fuzzy inference system based wavelet fusion to enhance the light regions of a nonuniform illuminated night …video surveillance system. To include spatial and temporal variations of the illuminated regions, a spatio-temporal illumination approach is used. A contribution index of the illuminated regions is generated using a fuzzy membership function. Subsequently, the stationary wavelets are used to decompose high-frequency and low-frequency coefficients of both night and day background frames for frame fusion. The contribution index selects the illuminated regions presented in these wavelet coefficients for fusion. Finally, the inverse wavelet transform is applied to reconstruct the illumination enhanced frame. The proposed approach effectively highlights the illuminated regions and provides a better visual perception. Show more

Keywords: Night video surveillance, stationary wavelet transform, frame fusion, fuzzy inference system

DOI: 10.3233/JIFS-169257

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3143-3149, 2017

Authors: Vishnu Pradeep, V. | Sowmya, V. | Soman, K.P.

Article Type: Research Article

Abstract: Remote sensing satellites are proficient in taking earth images across various regions in visible part of electromagnetic spectrum. The images can be panchromatic image of a single band, multispectral image of three to seven different bands, and hyperspectral image taken from about 220 contiguous spectral bands. These images are used together or on its own, depending on the significance and usage of the preferred application. Pan-sharpening is one method which is used to improve the quality of a low resolution multispectral image by fusion with a high resolution panchromatic image. This paper proposes a method based on M-band wavelets for …the pan-sharpening of a low resolution multispectral image. The method tries to improve the spatial characteristics while preserving the spectral quality of the data. The proposed technique uses weighted fusion rule and average fusion rule. The data used for the experiment were acquired by high resolution optical imagers onboard QuickBird, WorldView-3, WorldView-2 and GeoEye-1. A comparison with existing fusion techniques is done based on image quality metrics and visual interpretation. The experimental results and analysis suggests that the proposed pan-sharpening technique outperforms other compared pre-existing pan-sharpening methods. Show more

Keywords: M-band wavelets, pan sharpening, average fusion rule, weighted fusion rule, image quality metrics

DOI: 10.3233/JIFS-169258

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3151-3158, 2017

Authors: Kaur, Arshvir | Sood, Nitakshi | Aggarwal, Naveen | Vij, Dinesh | Sachdeva, Bhavdeep

Article Type: Research Article

Abstract: Traffic congestion occurs when the number of the vehicles increases more than the existing space of the road. This deleterious problem is increasing at an alarming rate in the whole world. For any effective Intelligent Transportation System, early detection of traffic congestion is very important to take corrective action. Several techniques have been developed to detect traffic congestion, most of which are infrastructure based. Even though these techniques are widely used, but they have many downsides as well. They require large capital input for installation as well as for maintenance. In this paper, we propose an efficient and cost-effective method …using smartphones to determine the traffic state of the road. The acoustic data collected from commuter’s smartphone is segmented into fixed size frames. Various time and frequency based features such as (MFCC, Delta & Delta-Delta, ZCR, STE, and RMS) are extracted from each frame and used for detecting traffic state as ’busy street’ or ’quiet street’. We have compared the accuracy of two classifiers Support Vector Machines and Neural Network by using acoustic data collected from 320 different recording sessions. Experiments have shown that feature set having features MFCC, STE and RMS, results in better classification accuracy of 91.8% with Neural Network and 93% with SVM. Furthermore, various relevant factors affecting the classification accuracy are also tested like frame size, window functions, overlapping size and different combination of features. The frame size of 8192 and hamming window function proved to be more efficient than others. Show more

Keywords: Acoustic signal, traffic state, temporal features, spectral features, support vector machine, Neural Network

DOI: 10.3233/JIFS-169259

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3159-3166, 2017

Authors: Dewasthale, Mugdha | Kharadkar, R.D.

Article Type: Research Article

Abstract: Least Mean Square (LMS) and Normalized-Least Mean Square (NLMS) algorithms are very popular and frequently used algorithms for noise cancellation in speech. But selecting the step size for updating the weight of adaptive filter is the big issue in LMS and NLMS algorithms. So as to meet disagreeing requirements of quick convergence and less MSE, step size needs to be correctly controlled. Along with step size, length of adaptive filter also plays major role in the effective noise cancellation. These two factors greatly affect the performance of the ANC. To get the best possible solution, a variety of trials of …filter length and step size are required. The main motivation behind the development of proposed High Performance Self Tuning (HPST) adaptive filter algorithm is to adaptively determine the step size. The selection of length of adaptive filter is based on the distance between two microphones in the ANC system. The proposed algorithm works very well, as shown in the experiments which are carried out on NOIZEUS speech corpus as well as actually recorded noisy speech signals. Results indicate that proposed algorithm is superior to referred algorithms in terms of Mean- Square- Error (MSE), Peak- Signal to Noise ratio (PSNR), convergence time and complexity. Show more

Keywords: Convergence time, complexity, filter length, LMS, MSE, NLMS, step size, PSNR

DOI: 10.3233/JIFS-169260

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3167-3176, 2017

Authors: Vidyadharan, Divya S. | Thampi, Sabu M.

Article Type: Research Article

Abstract: Detecting forged digital image has been an active research area in recent times. Tampering introduces artifacts within images that differentiate tampered images from authentic images. Forgery detection techniques try to identify these artifacts by analyzing differences in the texture properties of the image. In this paper, we propose a multi-texture description based method to detect tampering. Different texture descriptors considered are Local Binary Pattern, Local Phase Quantization, Binary Statistical Image Features and Binary Gabor Pattern. The method captures subtle texture variations at different scales and orientation using Steerable Pyramid Transform (SPT) decomposition of image. The different texture descriptors extracted from …each subband image after SPT decomposition is combined to form the multi-texture representation. Then, ReliefF feature selection method is applied on this high dimensional multi-texture representation to generate a compact representation. This compact multi-texture representation is classified using Random Forest classifier. We have evaluated the performance of individual texture descriptors and multiple textures in detecting image forgery. Experimental results show that the compact multi-texture description has improved detection accuracy. Show more

Keywords: Image forgery detection, multi-texture description, image tampering detection

DOI: 10.3233/JIFS-169261

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3177-3188, 2017

Authors: Sarkhel, Ritesh | Chowdhury, Tithi Mitra | Das, Mayuk | Das, Nibaran | Nasipuri, Mita

Article Type: Research Article

Abstract: Evolutionary Algorithms (EA) are robust optimization approaches which have been successfully applied to a wide range of problems. However, these well-established metaheuristic strategies are computationally expensive because of their slow convergence rate. Opposition Based Learning (OBL) theory has managed to alleviate this problem to some extent. Through simultaneous consideration of estimates and counter estimates of a candidate solution within a definite search space, better approximation of the candidate solution can be achieved. Although it addresses the slow convergence rate to some extent, it is far from alleviating it completely. The present work proposes a novel approach towards improving the performance …of OBL theory by allowing the exploration of a larger search space when computing the candidate solution. Instead of considering all the components of the candidate solution simultaneously, the proposed method considers each of component individually and attempts to find the best possible combination by using a metaheuristic technique. In the present work, this improved Opposition learning theory has been integrated with the classical HS algorithm, to accelerate its convergence rate. A comparative analysis of the proposed method against classical Opposition Based Learning has been performed on a comprehensive set of benchmark functions to prove its superior performance. Show more

Keywords: Evolutionary Algorithms, Opposition Based Learning, Harmony Search algorithm, optimization

DOI: 10.3233/JIFS-169262

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3189-3199, 2017

Authors: Tsuya, Kohei | Takaya, Mayumi | Yamamura, Akihiro

Article Type: Research Article

Abstract: The firefly algorithm is applied to the uncapacitated facility location problem which is a well known optimization problem. The light absorption coefficient parameter γ of the firefly algorithm is examined to obtain better performance and suitable values of γ are explored for the uncapacitated facility location problem. Effectiveness of local search in the firefly algorithm is also investigated. In addition, the firefly algorithm equipped with local search is compared with the artificial bee colony algorithm with respect to average relative percent error and hit to optimum rate.

Keywords: Metaheuristic, swarm intelligence, firefly algorithm, artificial bee colony algorithm, uncapacitated facility location problem

DOI: 10.3233/JIFS-169263

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3201-3208, 2017

Authors: Nair, Jyothisha J. | Thomas, Susanna

Article Type: Research Article

Abstract: Graphs are considered to be one of the best studied data structures in discrete mathematics and computer science. Hence, data mining on graphs has become quite popular in the past few years. The problem of finding frequent itemsets in conventional data mining on transactional databases, thus transformed to the discovery of subgraphs that frequently occur in the graph dataset containing either single graph or multiple graphs. Most of the existing algorithms in the field of frequent subgraph discovery adopts an Apriori approach based on generation of candidate set and test approach. The problem with this approach is the costlier candidate …set generation, particularly when there exist more number of large subgraphs. The research goals in frequent subgraph discovery are to evolve (i) mechanisms that can effectively generate candidate subgraphs excluding duplicates and (ii) mechanisms that find best processing techniques that generate only necessary candidate subgraphs in order to discover the useful and desired frequent subgraphs. In this paper, a two phase approach is proposed by integrating Apriori algorithm on graphs to frequent subgraph (FS) tree to discover frequent subgraphs in graph datasets. Show more

Keywords: Frequent subgraph mining, Apriori, graph mining, frequent subgraph tree

DOI: 10.3233/JIFS-169264

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3209-3219, 2017

Authors: Abhishek, S.N. | Balakirithikaa, R.B. | Madhan, C. | Vasudevan, Shriram K.

Article Type: Research Article

Abstract: Life is nothing less than a hell without any entertainment in it. Thanks to mobile phones that let us entertain ourselves on the go. Mobile phones that are being launched nowadays, come with super impressive features that revolve around entertainment. Mobile manufacturers know it pretty well that entertainment has become an indispensable part of human life in the current era. This is the reason why mobile phones are nothing but a complete portable entertainment package. The main source of portable entertainment is music. A very common but irritating problem faced by the youngsters of this era is missing their favorite …beat, or pausing a song frequently while conversing with someone. This seems to be negligible, but irritates most as they have to rewind the song or even restart it from beginning for the single beat. So think about a system that stops playing when the buds are taken off, and automatically continues when it is placed back. This seems to be simple but it is not so. This will change the whole experience of enjoying media, making a new mile stone in the entertainment world. This system will bring a new generation of media players that not only allows us to listen to our favorite music whenever we want but also allows automatic access without having to unlock our phones every now and then for the same. Show more

Keywords: Earphone, intelligent earphones, auto pause, auto play, ear plug controller

DOI: 10.3233/JIFS-169265

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3221-3228, 2017