Forthcoming articles


International Journal of Autonomic Computing


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International Journal of Autonomic Computing (5 papers in press)


Regular Issues


  • Sliding mode approach for performance improvement of slow and fast dynamic uncertain systems   Order a copy of this article
    by Subhash Sankeswari, Rajan Chile 
    Abstract: In this paper, an extended sliding mode control(SMC) method is proposed for applications of general class of control systems based on low order model obtained from slow or fast dynamics systems. In the proposed method, the sliding mode controllers(SMCr)are designed based on the three term controller (PID) with first order filter sliding surface.The contribution of the work proposed in this paper is that the designed controller methodology is applicable to general uncommon class of single input and single output (SISO) systems having lower or higher order dynamics, oscillatory or monotonic behavior and with or without delay time in the behavior of the systems. The developed controller performs well under parametric variations and uncertainty in the system. The robust property of the proposed method is verified by applying an external fixed and variable load disturbances. The stability and robustness properties of the proposed controller are proved by means of Lyapunov stability theorem.The high frequency chattering phenomenon which commonly occurs in SMC laws,is significantly reduced by adopting the switching gain with the known parameters of the system.The performance of the proposed SM control method is validated with the help of simulation examples and results are compared with other control methods available in the literature.
    Keywords: Sliding Mode Control; Higher order; Performance Analysis; Systems andrnDynamics; Reduced Order Model; Parametric Uncertainty.
    DOI: 10.1504/IJAC.2018.10016146
  • Particle Swarm Optimization Algorithm Based Intrusion Detection System (PSO-IDS) for Mobile Ad-hoc Network   Order a copy of this article
    by Shruti Dixit, Rakesh Singhai 
    Abstract: Ad-hoc Network is the category of cooperative wireless mobile nodes with the absence of centralized authority or infrastructure. It is vulnerable to different types of attacks such as passive and active because of open environment, speedily varying topology and decentralized nodes. An attack by a malicious node known as black hole attack can considerably diminishes ad-hoc network performance and results in disintegration of network, inaccessible nodes and severely degrades network performance. Evaluation of the additional effect due to existence of malicious nodes and determination of the suitable measures to detect these nodes in the network is the prime objective of the research work. In order to overcome this misbehaviour activity in the network, a Particle Swarm Optimization algorithm (PSO) based intrusion detection system (PSO-IDS) for ad-hoc networks is proposed. Swarm agents are effectively used to detect the malicious node by evaluating their packet behaviour based on Packet delivery fraction (PDF), average delay, number of packets dropped and packet capture. A defence technique called IDS is deployed for prevention against black hole attack due to malicious nodes. The simulation study establishes that the proposed PSO-IDS algorithm improves the performance metrics like throughput and packet delivery ratio.
    Keywords: MANET; Particle swarm optimization (PSO); Intrusion detection systems (IDS); malicious nodes; black hole attack.

  • Soft Computing Optimization Study of Fuzzy Parametric Uncertain System For Real Time Process Control   Order a copy of this article
    by Ajay Patil 
    Abstract: This paper deals with analysis and design of optimal robust controller for fuzzy parametric uncertain system using soft computing techniques. Fuzzy system is used to handle the uncertainty in the system. The response of fuzzy systems depends on tuning of fuzzy system parameters. Optimization in designing of fuzzy membership function improves system response. These optimization algorithms may have their own advantages and limitations. The proposed methodology uses different evolutionary algorithms to optimize the fuzzy membership function. A comparative study is done for modern non-traditional optimization algorithms in improving the controller response.An optimal control design is used to obtain the control law.The system is converted into state space controllable canonical form with the α-cut property of fuzzy. Kharitonov theorem is used for fuzzy polynomial and stability analysis is done by using the Lyapunov-Popov method. The proposed method applied to a real-time process control. Experimental setup of Continuous Stirred Tank Reactor (CSTR) is used for it.
    Keywords: Fuzzy parametric uncertain system (FPUS); α-cut set; optimal control Kharitonov theorem; Lyapunov-Popov stability; Continuous Stirred Tank Reactor (CSTR).

  • Improved Cyberbully Detection Techniques using Multiple Correlation Coefficient from Forum Corpus   Order a copy of this article
    by Sheeba Immanuvel Rajkumar, Pradeep Devaneyan S, Prathyusha Tata 
    Abstract: Today, there are many prominent online sites where people share their experiences regarding crimes and anti-social behavior. In this regard, a major unaddressed and even unidentified problem that is experienced in the social network websites is Cyberbully. This proposed framework primarily targets the cyberbullying in the crime investigation forum since a high degree of cyberbully is common in crime forums. In this paper, a highly furnished representational framework is proposed that is specific to cyberbully detection using hybrid techniques (MCC (Multiple Correlation Coefficient) & SVM (Support Vector Machine)). The bag of words are given individual weights to examine their correlations using MCC algorithm before feeding them into a linear SVM classifier that identifies and classifies the cyberbully words. The efficiency of the system developed can be enhanced by analyzing the evaluation metrics and the dataset validation metrics
    Keywords: Cyberbully Detection; Cyberbully Classification; Multiple Correlation Coefficients; Support Vector Machines; Data Analytics;.

  • AIR-IA: An Analogous Image Removal approach using the Intelligent Archive   Order a copy of this article
    by Jyoti Malhotra, Jagdish Bakal 
    Abstract: Deduplication is maturing as a standard attribute on backup and archives, whereby the aim is to free the storage space by removing the duplicates. Considering the storage room demand and justifiable deletion, this paper proposes a multi-container intelligent deduplication image archive system; where analogous images are disposed from the system based on the similarity approach. Similarity-aware image deduplication is achieved by calculating image fingerprints and the images are deleted when their hamming distance matches the predefined threshold. A probability model is addressed for the overall probability of getting similar images on the respective containers based on their relative storage and similarity scores of the images. In addition, the linear optimization model is formulated to target data minimization and storage space maximization; which is further verified with the dataset. We perform experimentation of our work on the existing as well as synthesized datasets and various accuracy metrics are calculated in terms of precision, recall, f-score and deduplication ratio. It is observed that binary hashes used in our system give the fair contribution in removing similar images.
    Keywords: deduplication; image; fingerprints; similarity; storage space; optimization.