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