Forthcoming articles


International Journal of Intelligent Systems Design and Computing


These articles have been peer-reviewed and accepted for publication in IJISDC, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.


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International Journal of Intelligent Systems Design and Computing (6 papers in press)


Regular Issues


  • Ontology Based Approach for Document Semantic Similarity Using Concept Map   Order a copy of this article
    by Poonam Chahal, Manjeet Singh 
    Abstract: Ontology plays an important role in the process of semantic similarity computation. To extract the relevant and important information from a given document it is necessary to understand the semantic associated with the document. This understanding of semantic information comes through the concepts representing the words that are present in the given documents. These concepts and relationships between these concepts are used to construct the concept map which is the first step in the construction of ontology of a document. However, to extract the concepts and their relationships, the document set of words needs to be considered. These set of words further represents the concepts which are then used in the document ontology construction process. Finally, the matching process of constructed document ontology is applied to find the semantic similarity between any two given documents. However, it can be possible that a concept present in different ontologies may give different meaning depending upon the domain of the document. In our approach of document similarity, we provide a novel method of construction of document ontology based on concept map for computation of similarity between any two given documents.
    Keywords: Concept Map; Ontology; Concepts; Relationships; Semantic; Similarity.

  • Hardware and Software Load Power Control in Smart Home applications Based on Taguchi Optimization Technique   Order a copy of this article
    by Yasmina Azzougui, Abdelmadjid Recioui 
    Abstract: Power control is one of the concerns in smart grid implementation. The balance between the supplied power and the demand must be maintained so that blackouts are avoided. Smart meters play an important role in establishing this balance. On the other hand, power control implementation is a challenge as one would have to find the right mix between the hardware and the software parts. The purpose of this work is to optimize and implement a small power control system of home appliances. The objective of the optimization is to reschedule some tasks if the power demand exceeds a certain peak level. The optimization is based on Taguchi method which is known of its robustness and relatively fast convergence. The system casts a real life situation and can be considered as a small-scale prototype that can be extended to larger systems.
    Keywords: Load side management; Software; Hardware; Optimization; Taguchi method.

Special Issue on: Machine Learning in Multi Modality Recognition System

  • A Novel Multi-Objective Hybrid QoS Optimization Technique for MANETs   Order a copy of this article
    by Rangaraj Jayavenkatesan, Anitha Mariappan 
    Abstract: Mobile Ad-Hoc Network (MANET) requires the support of optimization techniques for improving the Quality of Service (QoS) it delivers. Optimization becomes mandatory due to the autonomous and infrastructure less characteristics of the network. In order to improve the performance of the network, this manuscript formulates a hybrid optimization by assimilating Ant Colony Optimization (ACO) and Fitness Distance Ratio (FDR) based Particle Swarm Optimization (PSO). In order to ensure better QoS, ACO is aimed at optimal solution based on throughput maximization. Contrarily, the FDR PSO considers overhead and residual energy for precising the optimal solution further. The proposed hybrid technique is implemented in a scenario consisting of 100 mobile nodes and the performance of the proposed technique is investigated using the metrics throughput, packet delivery ratio, delay, overhead and energy.
    Keywords: ACO; FDR PSO; QoS Routing; MANET; Hybrid optimization.

Special Issue on: IJISDC ICCASP2018 Next-Generation Technologies in Computing, Communication and Signal Processing

  • Selection of Energy Efficient Path by Applying Particle Swarm Optimization Method in Wireless Sensor Networks   Order a copy of this article
    by Nada Al-Humidi, Girish Chowdhary 
    Abstract: Power and resource limitations of the sensor nodes, the possibility of packet loss and delay are the requirements should be considered while designing routing protocol for the wireless sensor network. To meet and achieve these requirements, several routing techniques have been proposed. Clustering-based routing protocol puts a network structure to satisfy energy efficiency, stability, and scalability of the network. In such protocols, the network is organized into clusters in which one node will be selected as a cluster head for the cluster. Selecting cluster head and forming the clusters are the key issues in these protocols, as a result, many routing protocols based clustering have been proposed. With the objective of solving of these issues, reducing the energy consumption and extending the lifetime of the network, in this paper, Energy Efficiency based Clustering and Particle Swarm Optimization (EECPSO) method is proposed. EECPSO performance is evaluated and justified through extensive analysis, comparison, and implementation. The results show that the proposed method is highly efficient and effective in term of balancing the consumption of energy and prolonging network lifetime.
    Keywords: WSN; Routing Protocol; Hierarchical Cluster-based; Network Lifetime; Clustering; Optimization; PSO.

  • Web Phishing Detection: Feature Selection using Rough Sets and Ant Colony Optimization   Order a copy of this article
    by Ravi Kiran Varma Penmatsa, Padmaprabha K 
    Abstract: Abstract: Phishing has become a global issue which is doing fraud by stealing online data. Because of Phishing, many users may lose trust in online services which cause a negative effect on organizations. Predictive, Preventive and Counteractive measures taken for phishing is a crucial step towards protecting online business transactions. The accuracy of classifying any website as phished necessarily depends on the goodness of features selected. Using Feature selection algorithms combined with Optimization techniques, appropriate features can be identified. Removal of a feature should not affect the accuracy of classification. This paper proposes Rough-set and Ant colony optimization technique for attribute minimization on standardized phishing data set. Experiment results show improvement in performance with reduced attributes for web Phishing detection.
    Keywords: Phishing; web phishing detection; feature selection; rough sets; ant colony optimization; classification accuracy; feature reduction.

    by SUNIL HIREKHAN, Ramchandra Manthalkar 
    Abstract: The Detrended Fluctuation Analysis(DFA) and Detrended Cross-Correlation Analysis(DCCA) are the widely used methods for analysis of non-stationary time series. The Detrended Fluctuation and Cross-Correlation Analysis of the EEG signals Pre- and Post-meditation (mindfulness) intervention are compared. It is observed that the EEG data obtained from 7 subjects out of total 11 subjects shows reduction in the DFA and DCCA exponent values. The reduction in DFA exponent values represents the lower intrinsic fluctuations in the EEG time series, which is a measure of better (higher) complexity of these vital rhythms. The reduced DFA exponent values after 8-weeks of Focused Attention (mindfulness) meditation practice in more number of subjects, indicate that the meditation practice enhances the ability to handle complexity. The Detrended Cross Correlation Analysis(DCCA) of EEG signals shows that the EEG signals of electrode pair of two brain lobe hemispheres obeys the power-law relationship, and the DCCA exponent is reduced in value after the meditation intervention. The reduced DFA and DCCA exponents indicate improved neuronal functioning of these subjects.
    Keywords: Detrended Fluctuation Analysis(DFA); Detrended Cross-Correlation Analysis; power-law correlation; mindfulness meditation; complexity indicator.