Journal of Intelligent & Fuzzy Systems - Volume 35, issue 2

Authors: Kamal, Md. S. | Trivdedi, Munesh C. | Alam, Jannat B. | Dey, Nilanjan | Ashour, Amira S. | Shi, Fuqian | Tavares, João Manuel R.S.

Article Type: Research Article

Abstract: Consensus is a significant part that supports the identification of unknown information about animals, plants and insects around the globe. It represents a small part of Deoxyribonucleic acid (DNA) known as the DNA segment that carries all the information for investigation and verification. However, excessive datasets are the major challenges to mine the accurate meaning of the experiments. The datasets are increasing exponentially in ever seconds. In the present article, a memory saving consensus finding approach is organized. The principal component analysis (PCA) and independent component (ICA) are used to pre-process the training datasets. A comparison is carried out between …these approaches with the Apriori algorithm. Furthermore, the push down automat (PDA) is applied for superior memory utilization. It iteratively frees the memory for storing targeted consensus by removing all the datasets that are not matched with the consensus. Afterward, the Apriori algorithm selects the desired consensus from limited values that are stored by the PDA. Finally, the Gauss-Seidel method is used to verify the consensus mathematically. Show more

Keywords: Push down automata, principal component analysis, independent component, big data, DNA

DOI: 10.3233/JIFS-169695

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1555-1565, 2018

Authors: Sinha, Rupesh Kumar | Sahu, S.S.

Article Type: Research Article

Abstract: The augmented growing of visual cryptography in multimedia image transmission or data transmission over unsecured networks leads in safekeeping for confidential information. Generally two techniques are employed to afford secure transmission namely data hiding and cryptography. Cryptography is the main objective of recent research work in which the way of achieving secure transmission over the network be contingent on the interest of data encryption. This encryption process encrypts the constituent of data such as manuscript, image, audial, and audiovisual to make the data unconceivable or incomprehensible during transmission. A novel secret key generation based on Improved Bat Optimized Piecewise Linear …Chaotic Map is proposed for image encryption. Our proposed secret key is intended for image encryption owing to the progression of mixing, permutation, double diffusion and confusion with the size of 128 bit to perform secure transmission. The success of our proposed method is revealed by the tentative results and comparison with the existing techniques in terms of sensitivity analysis, Information Entropy, correlation coefficient and, Encryption speed. Show more

Keywords: Image encryption, cryptography, secure transmission, improved bat optimized piecewise linear chaotic map, permutation-confusion, double diffusion

DOI: 10.3233/JIFS-169696

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1567-1578, 2018

Authors: KanagaSakthivel, B. | Devaraj, D. | Banu, R. Narmatha | Selvi, V. Agnes Idhaya

Article Type: Research Article

Abstract: A hybrid renewable energy scheme comprising of the wind and solar PV electric power systems with appropriate maximum power point tracking is presented in this paper. The maximum power point tracking for the wind generator is carried out using Adaptive Neuro Fuzzy Inference System. The MPPT technique adopted for the photovoltaic power generation system is the Incremental Conductance (IC) algorithm. A power flow control scheme based on fuzzy logic is developed to regulate the power transaction from the wind and solar power sources as well as for the battery charging and discharging. Based on the available velocity of wind and …solar insolation and based on the electrical demand different modes of operation are selected automatically using the ANFIS based control strategy. Considering the non linearity’s of the converters and the unpredictable nature of the renewable sources an advanced adaptive controller is necessary. The proposed ANFIS controller performs well and the proposed idea has been validated using MATLAB/Simulink and the simulation results are reported. Show more

Keywords: Hybrid energy system, wind energy, solar PV, ANFIS, SVPWM

DOI: 10.3233/JIFS-169697

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1579-1595, 2018

Authors: Huang, Qing | Huang, Bo | Fang, Zhijun | Xiao, Meihua | Yu, Ying

Article Type: Research Article

Abstract: Benefited on the open source software movement, many code search tools are proposed to retrieve source code over the internet. However, the retrieved source code rarely meets user needs perfectly so that it has to be changed manually. This is because the retrieved source code is concretely over-specific to some particular context. To solve this problem, we propose an Abstract Change Pattern Model (ACPM) to ensure the context-specific source code general for various contexts. This model consists of the ACP abstracting and the ACP concretizing algorithms. The former exploits the abstractly context-aware change pattern from the code changes. Based on …the change pattern, the latter transforms the context-specific source code into the correct one meeting different user needs. To evaluate ACPM, we extract 7 topics and collect 5-6 code snippets per topic from the Github, while performing 5 different experiments where we explore 2 sensitivity-related rules and use them to raise the accuracy gradually. Our experimental results show that ACPM is feasible and practical with 73.84% accuracy. Show more

Keywords: Code search, program transformation, code change pattern

DOI: 10.3233/JIFS-169698

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1597-1608, 2018

Authors: Almaslukh, Bandar | Al Muhtadi, Jalal | Artoli, Abdel Monim

Article Type: Research Article

Abstract: The online smartphone-based human activity recognition (HAR) has a variety of applications such as fitness tracking, healthcare…etc. Currently, the signals generated from smartphone-embedded sensors are used for HAR systems. The smartphone-embedded sensors are utilized in order to provide an unobtrusive platform for HAR. In this paper, we propose a deep convolution neural network (CNN) model that provides an effective and efficient smartphone-based HAR system. For automatic local features extraction from the raw time-series data, we use the CNN while simple time-domain statistical features are used to extract more distinguishable features. Furthermore, we explore the impact of a novel data augmentation …on the recognition accuracy of the proposed model. The performance of the proposed method is evaluated using two public data sets (UCI and WISDM) which are collected using smartphones. Experimentally, we show how the proposed model establishes the state-of-the-art performance using these datasets. Finally, to demonstrate the applicability of the proposed model for online smartphone-based HAR, the computational cost of the model is evaluated. Show more

Keywords: Deep learning, convolutional neural network, smartphone-based human activity recognition, data augmentation, HAR

DOI: 10.3233/JIFS-169699

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1609-1620, 2018

Authors: Rathore, Arun | Patidar, N.P.

Article Type: Research Article

Abstract: Energy storage using batteries is emerging as a fundamental element of standalone power system based on non conventional energy sources like wind and solar to increase the penetration level of these sources. The planning of standalone power system incorporating renewable sources and storage necessitates a vigilant study on modeling of a storage system. In most of the planning study reported in literature pertaining to battery storage, charging efficiency (CE) of a battery is assumed to be fixed at constant value. However, CE and State of charge (SOC) of the battery both are correlated. In this paper, Interval Type(IT)-2 fuzzy logic …has been applied for determining CE of battery relative to a specific SOC. For evaluating reliability indices i.e. Expected Energy not served (EENS), probabilistic analysis using analytical method has been applied to the standalone power system, situated near Kandla Port in Gujarat, India. The effect of considering CE of battery as a function of SOC has been compared with the constant value of CE of battery for the different groups consisting of solar-battery storage, wind turbine(WT)-battery storage, and wind-solar battery storage systems. Show more

Keywords: Interval type-2 fuzzy logic, CE, SOC, reliability, EENS

DOI: 10.3233/JIFS-169700

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1621-1632, 2018

Authors: Kumar, Ashish | Bhatnagar, Roheet | Srivastava, Sumit

Article Type: Research Article

Abstract: Even though finding out distance is the central core of k-Nearest Neighbor classification techniques, similarity measures are often favored against distance in various realistic scenarios and situation. Most of the similarity measures, which are used to classify an instance, are based on geometric model. Their effectiveness decreases with the increases in the number of dimensions. This paper establishes an efficient technique called ARSkNN for finding out class of any given instance using a measure based on an unique similarity, that does no longer compute distance, for k-NN classification. Our empirical results show that ARSkNN classification technique is better than the …previous established k-NN classifiers. The performance of algorithm was verified and validated on various datasets from different domains. Show more

Keywords: Data mining, classification, nearest neighbor, similarity measure

DOI: 10.3233/JIFS-169701

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1633-1644, 2018

Authors: Kaur, Amanpreet | Sidhu, Jagroop Singh | Bhullar, Jaskarn Singh

Article Type: Research Article

Abstract: With the higher compression ratio, the decoded image produces annoying compression artifacts near block boundaries, ringing artifacts near original edges and corner outliers at block corner. These coding artifacts are caused by quantization and transformation process of discrete cosine transform (DCT). This paper proposes a novel deblocking algorithm that removes block discontinuities by taking into account the ringing, blurring and corner outlier artifacts. The proposed deblocking technique consists of two frequency related modes (smooth and detailed region mode) and corner outlier mode have been proposed and then applied median filter. The proposed technique has been applied to a number of …reconstructed images and their performance is compared with conventional methods on the basis of standard metrics such a PSNR-B, BBM and MOS. Experimental simulation results illustrate that proposed technique improves the perceptual quality of reconstructed images and thus outperforms the all existing methods. Show more

Keywords: Deblocking filter, post-processing, blocking artifacts, corner outlier, image compression

DOI: 10.3233/JIFS-169702

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1645-1656, 2018

Authors: Vig, Vidhi | Kaur, Arvinder

Article Type: Research Article

Abstract: Recently, many software companies have shifted to shorter release cycles from the traditional multi-month release cycle. Evolution and transition of release cycles may affect the test effort in the system. This paper analyses 25 traditional releases containing 1210 classes and 69 rapid releases containing 2616 classes of four Open Source Java systems. Correlations between 48 Object Oriented metrics and 2 test metrics were evaluated to identify the best indicators of test effort. The results show that (i) correlation between OO and test metrics remain irrespective of release models, (ii) test effort required in Rapid Release (RR) models (shorter release …cycles) is slightly more as compared to Traditional Release (TR) models, (iii) Out of 18 machine learning algorithms instance based machine learning algorithms IBK and K star followed by Multi-Layer Perceptron (MLP) and additive regression are able to predict the test effort accurately in classes. Show more

Keywords: Release cycles, machine learning, prediction, software metrics, test effort

DOI: 10.3233/JIFS-169703

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1657-1669, 2018

Authors: Moayedirad, Hojat | Shamsi Nejad, Mohammad Ali

Article Type: Research Article

Abstract: This paper models the single and bi-objective brain emotional intelligent controllers for the dual stator winding induction motor (DSWIM) drive. The main purpose of this paper is performance improvement of the DSWIM drive control system and power losses reduction of the inverter in the DSWIM drive at low speeds. In the vector control method, it is difficult to estimate flux at low speeds. To solve the mentioned problem, researchers have used from the free capacity of the two windings of the stator. This paper presents three proposed methods: 1. Using the idea of rotor flux compensation based on classical PI …controller at low speeds, the motor works in its standard operating mode; 2. Proposed Method 1 is reformed and improved based on the bi-objective brain emotional controller; and 3. Proposed Method 2 is improved using single-objective brain emotional controller in the speed control loops of the DSWIM drive. The proposed methods are simulated in MATLAB/Simulink software. Show more

Keywords: Bi-objective, dual stator, emotional intelligent controller, induction motor, low speeds

DOI: 10.3233/JIFS-169704

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1671-1683, 2018