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International Journal of Advanced Intelligence Paradigms

International Journal of Advanced Intelligence Paradigms (IJAIP)

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International Journal of Advanced Intelligence Paradigms (21 papers in press)

Regular Issues

  • Big data secure storing in cloud and privacy preserving mechanism for outsourced cloud data   Order a copy of this article
    by Dr B. Renuka 
    Abstract: Big data is a buzz word in this decade it gets tremendous concentration in these days by the researchers because of the characteristics and features. And also big data gives lot of challenges to the world that is storage, processing and security. In any technology security is the prime concern in this manuscript, we map to misuse new complications of enormous information regarding security, further more, confer our thought toward viable and insurance protecting enlisting in the immense data time. Specifically, we at first formalize the general building of gigantic data examination, recognize the relating security necessities, and present a capable and assurance sparing outline for immense data which is secured in cloud.
    Keywords: Privacy Preserving; Security; Big data; Cloud Computing; outsourced data.

  • DEVELOPMENT OF ELECTRONIC PEST CONTROL IN PADDY FIELDS   Order a copy of this article
    by Ram Chandran.M, Vishnu Priya.R. 
    Abstract: Worldwide, agriculture is considered as the backbone of a countrys economy. The contribution of agriculture to Indias economy is steadily declining with Indias economic growth. Still, agriculture plays a significant role in the broadest economic sector. The major objective of the present work is to repel the pests that affect the agricultural fields especially paddy field. The pests that mainly affect the paddy fields are small insects, grasshoppers, and moths. Initially, we capture the images of the field and process these images using MATLAB software where we developed codes that find out whether the small insects are high or low. If the insects are high, then an appropriate pesticide is sprinkled over the field which is controlled by a PIC16F877A microcontroller. Further, we collected the frequency sensitivities of grasshoppers and moths to repel them. The time period of the day at which the grasshoppers and moths are maximum is obtained from previously published paper. Using this information we generate these frequencies at appropriate timings. As a result, the paddy field is free from grasshoppers and moths.
    Keywords: Frequency bandwidth; grasshoppers; image processing; moths; and pest control.

  • VLSI Realization of an Efficient Image Scalar Using Vedic Mathematics   Order a copy of this article
    by V. Ramadevi, K. Manjunatha Chari 
    Abstract: A low-complexity algorithm using Vedic Mathematics is intended for VLSI realization of an efficient image scalar. The proposed scalar comprises of a modified area pixel interpolator, edge detector and Vedic Multiplier. To decrease the obscuring and aliasing effects created by the area-pixel model and to conserve the image edge features productively an edge catching method is embraced. Moreover, a Vedic division unit is utilized for enhancing execution of the scaling processor without any rounding error correction techniques. It additionally accomplishes advancement at all levels of digital systems reducing power consumption. The proposed architecture is capable to achieve 5.28-K gates count using 200 MHZ, and computation time is 14.37 ns synthesized by 0.13-μm CMOS technology. Through comparison with previous techniques, this work can reduce gate counts by 18% and want only a one-line-buffer memory.
    Keywords: Image scalar; line buffer; sharpening filter; Vedic mathematics; VLSI;.

  • AN INNOVATIVE and SAFE TECHNOLOGY BASED ALTERNATIVE FOR LEGACY LOCKER SYSTEMS   Order a copy of this article
    by Anudeep J, Kowshik G, Giridhararajan R, Shriram KV 
    Abstract: These days, storing money, gold and other valuables in the bank lockers has become a worrying aspect to the citizens all around the world. According to the statistics on the bank robberies and loots, India almost lost $27.9 million(180 crore rupees) only on loots and burglaries in past 3 years .And there are cases being noticed where the burglars attempted to loot the bank with a disguised costume of a nun on them so as to make the bank managers believe that they are the original owners of the locker. Apart from the incidents happened all around the world, improvisations done to do the lockers safeties every year was mostly found are of only in the mechanical way i.e., lockers were given strength by manipulating the materials used. But, unlike to all those works, we come up with a system that could effectively face these kinds of problems and could even log the data like time of access to locker, changes occurred in the weight of the locker etc., and increase the security of the bank lockers making the individuals feel much safer on their property.As there is no intervention of men it will be a more accurate and safer method.The proposed system works with two levels of security, one of them is face recognition of the owner with the priorly given photo of owner during his registration in the bank.They should pass the face recognition test after which they will enter the second level of authentication where the user has to set the handles to a unique angle key(which is similar that of an ATM Pin) which is provided to them. Our system recognizes the face of the person who visits the bank for access to the locker, by using haar classifier, edge, and line detections features and the faces available in the database and activates the access to the only respective locker. One can noticeably understand that when it is said the person is given access to the locker that means all the other lockers stay deactivated for the access and any trail to open them, triggers the alarm. When the person reaches locker there is a second stage of security, where the person has to open the locker by rotating the handles to a certain angle.This action needs care and can be done perfectly by the owner alone. So, this system could effectively enhance the security of the lockers
    Keywords: Material strength; Haar cascade features,edge and linerndetections,rotating handle locker.

  • Signless Laplacian Energy of Bipolar Fuzzy Graphs with Application   Order a copy of this article
    by Hossein Rashmanlou, Muhammad Akram, Danish Saleema 
    Abstract: This paper presents certain notions, including Laplacian energy of bipolar fuzzy graphs(BFGs,rnfor short), signless Laplacian energy of BFGs, Laplacian energy of bipolar fuzzy digraphs(BFDGsrnfor short) and signless Laplacian energy of (BFDGs). Further, it describes useful propertiesrnand bounds of Laplacian energy of BFGs and signless Laplacian energy of BFGs. Moreover,rnthis article discusses an application of proposed concepts in decision-making.
    Keywords: Laplacian energy of bipolar fuzzy graphs; signless Laplacian energy; decisionmaking.

  • A Low Quality Medical Imaging Registration Technique for Indian Telemedicine Environment   Order a copy of this article
    by Syed Thouheed Ahmed, Sandhya.M Sandhya.M, Sharmila Sankar 
    Abstract: Telemedicine is growing in India and Indian environment needs to be improved for acquiring and transmitting datasets for consultation and diagnosis. These attributes are correlated with internal image quality enhancement. In this paper, a medical imaging registration and re-verification technique is proposed for low quality datasets transmitted in under-rated transmission channel. The registration approach is integrated with multiple samples of acquired datasets, sequentially processed. Thus improving the mapping, transformation time and peak signal to noise ratio. The re-verification process assures double authentication for registered image on comparison with referenced sample. The approach is tested on open medical data samples of UCL repository transmitted under low line bandwidth of Indian transmission channel and Internet standards. The proposed approach serves as a better means for diagnosis and feature extraction for tele-diagnosis and consultation in Indian rural telemedicine environment.
    Keywords: Image registration; India Telemedicine; Medical Image Processing.

  • Domination and Product Domination in Intuitionistic Fuzzy Soft Graphs   Order a copy of this article
    by R. Jahir Hussain, S. Satham Hussain, Sankar Sahoo, Madhumangal Pal, Anita Pal 
    Abstract: This manuscript deals with the domination and product domination of intuitionistic fuzzy soft graphs. By using the concept of strength of a path, strength of connectedness and strong arc, the domination set is established. The necessary and suficient condition for the minimum domination set of intuitionistic fuzzy soft graph is investigated. Further some properties of domination number of product intuitionistic fuzzy soft graphs are also obtained and the proposed concepts are described with suitable examples. The weight for a domination of intuitionistic fuzzy soft graph is also established.
    Keywords: Intuitionistic fuzzy graphs; Fuzzy soft graphs; Product domination; Strength of connectedness.
    DOI: 10.1504/IJAIP.2019.10022975
     
  • Novel Deep Learning Model with Fusion of Multiple Pipelines for Stock Market Prediction   Order a copy of this article
    by Abhishek Verma 
    Abstract: Deep learning has become a powerful tool in modeling complex relationships in data. Convolutional neural networks constitute the backbone of modern machine intelligence applications, while long short-term memory layers (LSTM) have been widely applied towards problems involving sequential data, such as text classification and temporal data. By combining the power of multiple pipelines of CNN in extracting features from data and LSTM in analyzing sequential data, we have produced a novel model with improved performance in stock market prediction by 20% upon single pipeline model and by five times upon support vector regressor model.rnWe also present multiple variations of our model to show how we have increased accuracy while minimizing the effects of overfitting. Specifically, we show how changes in the parameters of our model affect its scores for training and testing, and compare the performance of a multiple pipelines model using three different kernel sizes versus a single pipeline model.rn
    Keywords: Stock prediction; S&P500; CNN; LSTM; Deep learning.

  • A Key Pre-distribution Protocol for Node to Node and Group Communication in Wireless Sensor Networks using Key Pool Matrix   Order a copy of this article
    by PREMAMAYUDU BPM 
    Abstract: Sensor networks have huge demand in various fields like military, environment monitoring, hospitals and many hostile environments. Further, they are also used in application of internet of things where many number of sensors is connected through internet. These applications demand security issues like confidentiality, authentication, integrity, because of their deployment areas and sensitivity of the data. By considering these issues, the key management plays an important role in many information security solutions which are used information protection. The proposed work exploits the various vulnerabilities in the sensor network and addresses various kinds of solutions for vulnerabilities through proposed key distribution scheme. The key generation and distribution implemented using key pool matrix. The comparison and analytical analysis are shown that the proposed work requires less communication and storage space at each sensor. Further, the prosed work can also increase resilience, reduce key compromise and number of revocation operations compared with other schemes.
    Keywords: Key pre-distribution in wireless sensor networks; Attacks; Node capture.

  • A Novel Variant of Bat Algorithm Inspired from CATD-Pursuit Strategy & Its Performance Evaluations   Order a copy of this article
    by Shabnam Sharma, Sahil Verma, Kiran Jyoti 
    Abstract: This paper presents a novel nature inspired optimization technique, which is a variant of Standard Bat Algorithm. This optimization technique is inspired from the pursuit strategy of microchiroptera bats and their efficient way of adaptation according to dynamic environment. Here dynamic environment describes different movement strategies adopted by prey (target), during their pursuit. Accordingly, bats have to adopt different pursuit strategies to capture the prey (target). In this research work, a variant of Bat Algorithm is proposed considering the pursuit strategy Constant Absolute Target Detection (CATD), adopted by bats, while targeting preys moving erratically. The proposed algorithm is implemented in Matlab. Results obtained are validated in comparison to Standard Bat Algorithm on the basis of best, mean, median, worst and standard deviation. The results demonstrate that the proposed algorithm provides better exploration and avoid trapping in local optimal solution.
    Keywords: Bat Algorithm; Constant Absolute Target Detection (CATD); Computational Intelligence; Echolocation; Meta-heuristic; Nature-Inspired Intelligence; Optimization; Pursuit Strategy; Swarm Intelligence.
    DOI: 10.1504/IJAIP.2021.10030248
     
  • Wireless Smart Automation Using IOT Based Raspberry Pi   Order a copy of this article
    by Vasu Goel, Akash Deep, Madireddy Vivek Reddy, Yedukondala Rao Veeranki 
    Abstract: In this paper we propose a smart door lock system and lighting system for home automation. This door lock system and lighting system is controlled by Radio Frequency Identification (RFID) reader which is programmed by Raspberry Pi to detect the input swipe through our university combo card or a RFID tag and wirelessly sends the signal to the Espruino (ESP) Wi-Fi module and Node Microcontroller Unit (MCU) which in turn activates the lighting system and door lock system. The mainstream application of the system will be in hostel rooms or in our homes wherever door locks are there so that doors can be opened anytime we want without disrupting our work or getting up from our places in case of any injury with a swipe of card
    Keywords: Internet-Of-Things; Raspberry pi; Radio-Frequency Identification; Home automation; MQTT.
    DOI: 10.1504/IJAIP.2019.10026853
     
  • Data Mining Techniques and Fuzzy Logic to Build a Risk Prediction System for Stroke   Order a copy of this article
    by Farzana Islam, M. Rashedur Rahman 
    Abstract: Nowadays, by using different computational system medical sector predict diseases. These systems not only aid medical experts but also normal people. In recent years stroke becomes life threatening deadly cause and it increased at global alarming state. Early detection of stroke disease can be helpful to make decision and to change the lifestyle of people who are at high risk. There is a high demand to use computational expertise for prognosis stroke. Research has been attempted to make early prediction of stroke by using data mining techniques. This paper proposes rule based classifier along with other techniques. The dataset is collected from Dhaka medical college, situated in Dhaka, Bangladesh To build a more accurate and acceptable model the system uses different classification methods likely- Decision tree, Support vector machine, Artificial neural network and fuzzy model. K-means, EM and fuzzy C-means clustering algorithm are used to label the dataset more accurately. Fuzzy inference system is also built to generate rules. ANFIS provides the most accurate model.
    Keywords: stroke; decision tree; SVM; MLP; artificial neural network; support vector machine; fuzzy model; FIS; ANFIS; data-mining; fcm; clustering; EM clustering; k-means; Bangladeshi dataset; fuzzy rule.
    DOI: 10.1504/IJAIP.2021.10054275
     
  • An optimized fuzzy edge detector for image processing and their use in modular neural networks for pattern recognition   Order a copy of this article
    by Isidra Espinosa-Velazquez, Patricia Melin, Claudia Gonzalez, Frumen Olivas 
    Abstract: In this paper, the development of a fuzzy edge detector optimized with the metaheuristics: Genetic Algorithms and Particle Swarm Optimization is presented, based on the sum of differences method, using as inputs the absolute values of the difference from the pixels in the image. The Pratts figure of merit metric was used to know the performance of the proposed fuzzy edge detector. A modular neural network was designed for the recognition of faces in benchmark images and comparisons were made with different works carried out with other fuzzy edge detection systems. The main contribution of this research work is the development of a new fuzzy edge detector method optimized.
    Keywords: fuzzy logic; fuzzy edge detector; optimization; GA; genetic algorithm; PSO; Particle swarm Optimization; Neural networks.

  • PEBD: Performance Energy Balanced Duplication Algorithm for Cloud Computing   Order a copy of this article
    by Sharon Priya Surendran, Aisha Banu W 
    Abstract: With the increasing demand of cloud data, efficient task scheduling algorithms are required with minimal power consumption. In this paper, the Performance-Energy Balanced Duplication (PEBD) scheduling approach is proposed for energy conservation at the point of task duplication. Initially, the resources are preprocessed with the Manhattan distance based Fuzzy Clustering (MFC).Then resources are scheduled using a Novel duplication aware fault tolerant based League-BAT algorithm and faults expected during job executions can be handled proactively. The fault adaptive firefly optimization is used for minimizing faults and it keeps information about resource failure. Consequently, the optimization ensures that performance is improved with the help of task duplication with low energy consumption. The duplications are restricted and they are strictly forbidden if they provide significant enhancement of energy consumption. Finally, enhanced compress & Join algorithm is used for efficient compression processing. It considers both schedule lengths and energy savings to enhance the scheduling performance with less power consumption. The performance of energy consumption and makespan for the proposed approach is increased with 6% and 0.5 % respectively
    Keywords: Manhattan distance; Fuzzy clustering; Resource scheduling; Duplication; fault tolerance; energy conservation.

  • A Community Based Trusted Collaborative Filtering Recommender Systems Using Pareto Dominance Approach   Order a copy of this article
    by Anupama Angadi, Satya Keerthi Gorripati 
    Abstract: Recommender System algorithms provided clarification to information overload problem suffered by netizens. The Collaborative Recommender Filtering approach takes the user-item rating matrix as an input and recommends items based on the perceptions of similar neighbours. However, sparsity issue in the rating matrix leads to untrustworthy predictions. However, the conventional Collaborative Recommender Filtering method chooses ineffective descriptive users as neighbours for each target user. This hints that the recommendations made by the system remain inaccurate. The proposed approach addresses this issue by applying a pre-filtering process and integrates community detection with Pareto dominance, which considers trusted neighbours from the community into which the active user pertains and eliminates dominant users from the neighbourhood. The results on the proposed framework showed a noteworthy improvement in all the accuracy measures when related to the traditional approaches.
    Keywords: Community Detection; Recommender Systems; Sparsity; Pareto dominance; Cold Start; Trust propagation;.

  • Web Server Workload Prediction using Time Series Model   Order a copy of this article
    by Mahendra Pratap Yadav, Akanksha Kunwar, Ram Chandra Bhushan, Dharmendra Kumar Yadav 
    Abstract: In distributed systems, multi-tier storage systems and cloud data-centers are used for resource sharing among several clients. To fulfill the clients request, the cloud providers share it's resources and manage the workload, which introduces many performance challenges and issues. One of the main challenges is resource provisioning in virtual machine (VMs or Container) since VMs are subjected to meet the demand of users with different profiles and Quality of Service (QoS). This proactive resource management approach requires an appropriate workload prediction strategy for real-time series data. The time series model exhibits prominent periodic patterns for the workload that evolves from one point of time to another with some short of time in random fluctuation. In this paper, a solution for the prediction of web server load problem has been proposed, which is based on seasonal ARIMA (Autoregressive Integrated Moving Average Model) model. ARIMA is a forecasting technique which predicts the future value based on its inertia. In seasonal ARIMA, seasonal AR and MA are used to predict the value xt (CPU workload time series) with the help of data values and errors at time lags that are multiple to the span of seasonality. We have evaluated our proposed method using real-world web workload data.
    Keywords: Cloud Computing; Elasticity; Auto-scaling; Time Series; Machine Learning.
    DOI: 10.1504/IJAIP.2022.10034175
     
  • An inventive and innovative integrated home network media system - a novel approach   Order a copy of this article
    by Aswin Tekur, Shriram K. Vasudevan 
    Abstract: A common problem in TV viewing is watching programs on a single TV set as only one program can be watched at a time. Streaming is continuous and real-time, causing interruptions and clash among viewers (who wish to view different channels at the same time) which ultimately ruins the viewing experience. Our system is a hardware unit (compatible with smart TV sets) supporting multiple features including: allowing simultaneous transmission of video streams (to network connected devices over a limited area network), with pause/play options, recording for a limited time duration. Our proposed system is aimed at making huge strides in the field of television viewership, offers meaningful convenience features to enrich viewers' experience, with minimal modification to presently used television systems, effectively utilising network connected devices (such as laptops, tablets, smartphones). Our efficient system saves money, time and supports features not currently offered by present day television sets.
    Keywords: simultaneous video transmission; advanced TV system; limited area network TV; home environment television system; multi-viewer multi-program TV system.
    DOI: 10.1504/IJAIP.2025.10072032
     
  • Machine learning approach to predict purchase decision of bank products and services   Order a copy of this article
    by Saumya Chaturvedi, Vimal Mishra, Nitin Mishra 
    Abstract: We propose a machine learning approach to predict purchase decision of bank products and services. The data were collected from May 2008 to May 2014 of a Portuguese bank. This investigation will help to predict the business of the bank and financial inflation and recent trends in bank product and services. The investigation is focused on the classification and prediction of bank telemarketing calls for term deposit product. We have analysed a large dataset of 41,188 observations related with bank client, product, services and socioeconomic attributes. Initially, the dataset was having 150 features and we have selected 21 most relevant features using standard adaptive forward selection and intelligence quotient. We have also compared four machine learning approaches: conditional inference trees (Ctree), recursive partitioning (Rpart), support vector machines (SVM) and random forest. The paper contains an impact analysis of changing training dataset and training time of a model. Observatory study shows the integration of both parameters: accuracy and model learning time to form a generalised and optimised solution for predicting bank business.
    Keywords: machine learning; business intelligence; data mining; decision support systems.
    DOI: 10.1504/IJAIP.2025.10072034
     
  • Simulation and practical implementation under different scenarios of indirect incremental conductance algorithm for MPPT of PV system   Order a copy of this article
    by Noureddine Bouarroudj, Amor Fezzani, Boualam Benlahbib, Bachir Batoun, Said Drid, Djamel Boukhetala 
    Abstract: Simplicity and good tracking performance have made the incremental conductance (INC) algorithm for maximum power point tracking (MPPT) of photovoltaic (PV) systems the most widely used algorithm. This paper treats of simulation and practical implementation of the indirect INC algorithm with a conventional proportional integral (PI) controller under different scenarios. Firstly, a comparison between indirect INC algorithm and the direct one is carried out, and in which the indirect INC algorithm is shown to be superior. Secondly, a simulation using Matlab/Similink program is conducted under standard climatic conditions, immediate change of irradiance and under immediate change of resistive load value. Finally, the validated indirect INC algorithm is implemented using a real prototype under the same scenarios as in the simulation.
    Keywords: PV-module; boost converter; direct INC algorithm; indirect INC algorithm.
    DOI: 10.1504/IJAIP.2019.10021027
     
  • Optimised feature selection and categorisation of medical records with multi kernel boosted support vector machine   Order a copy of this article
    by V. Lakshmi Prasanna, E. Deepak Chowdary, S. Venkatramaphanikumar, K. Venkata Krishna Kishore 
    Abstract: With the fast growth of internet and mobile usage, huge volumes of medical documents, which contain information of patients, diagnostic, past disease history and medication, are being generated electronically. In the field of text mining, document categorisation has become one of the emerging techniques due to large volume of documents in the form of digital data. The main objective of the proposed work is to identify disease treatment relationships and predict the diseases among medical articles. In this paper, highly relevant and more correlated features have been extracted using probabilistic latent Dirichlet allocation (P-LDA) and randomised iterative feature selection approach. These features were classified with multi kernel boosted support vector machine (MKB-SVM) and then their performance was evaluated on both PubMed and MEDLINE databases. Performance evaluation of the proposed approach on DB-1 and DB-2 was 98.7% and 92%, respectively. The evaluation illustrated that the proposed approach outperformed the existing state-of-the-art classification methods.
    Keywords: latent Dirichlet allocation; medical text classification; support vector machine; AdaBoost.
    DOI: 10.1504/IJAIP.2025.10072035
     
  • Optimisation of sparse linear array using state transition algorithm   Order a copy of this article
    by Pratistha Brahma, Banani Basu 
    Abstract: State transition algorithm (STA) has been used for sparse antenna array designing. A sparse linear array consisting of different core elements has been optimised using STA. The optimal solution is searched by changing the number of sparse elements and current excitation values of the core elements under a set of practical constraints. Number and position of sparse elements are optimised in order to achieve minimum side lobe level (SLL) for a given half power beam width (HPBW) using various design examples. The paper has been studied the trade-off between SLL and directivity of the array for different numbers and positions of the sparse elements. Results obtained using STA has been statistically compared with that of the particle swarm optimisation (PSO) algorithm and artificial bee colony (ABC) algorithm and ensures improved performances.
    Keywords: sparse antenna array; state transition algorithm; STA; particle swarm optimisation; PSO; artificial bee colony; ABC; side lobe level; SLL; directivity.
    DOI: 10.1504/IJAIP.2025.10072036