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  1.  3
    A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-Dimensional Knapsack Problem.Obinna Damian Adubisi, Babatunde Sulaiman Balogun, Peter Bamidele Shola, Friday Zinzendoff Okwonu & Asaju La’aro Bolaji - 2020 - Journal of Intelligent Systems 30 (1):90-103.
    The pigeon-inspired optimization algorithm is a category of a newly proposed swarm intelligence-based algorithm that belongs to the population-based solution technique. The MKP is a class of complex optimization problems that have many practical applications in the fields of engineering and sciences. Due to the practical applications of MKP, numerous algorithmic-based methods like local search and population-based search algorithms have been proposed to solve the MKP in the past few decades. This paper proposes a modified binary pigeon-inspired optimization algorithm named (...)
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  2.  2
    Discriminatively Trained Continuous Hindi Speech Recognition Using Integrated Acoustic Features and Recurrent Neural Network Language Modeling.R. K. Aggarwal & A. Kumar - 2020 - Journal of Intelligent Systems 30 (1):165-179.
    This paper implements the continuous Hindi Automatic Speech Recognition system using the proposed integrated features vector with Recurrent Neural Network based Language Modeling. The proposed system also implements the speaker adaptation using Maximum-Likelihood Linear Regression and Constrained Maximum likelihood Linear Regression. This system is discriminatively trained by Maximum Mutual Information and Minimum Phone Error techniques with 256 Gaussian mixture per Hidden Markov Model state. The training of the baseline system has been done using a phonetically rich Hindi dataset. The results (...)
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  3. Towards Developing a Comprehensive Tag Set for the Arabic Language.Muhammed Alawairdhi & Shihadeh Alqrainy - 2020 - Journal of Intelligent Systems 30 (1):287-296.
    This paper presents a comprehensive Tag set as a fundamental component for developing an automated Word Class/part-of-speech tagging system for the Arabic language. The aim is to develop a standard and comprehensive PoS tag set that based upon PoS classes and Arabic inflectional morphology useful for Linguistics and Natural Language Processing developers to extract more linguistic information from it. The tag names in the developed tag set uses terminology from Arabic tradition grammar rather than English grammar. The usability of the (...)
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  4.  2
    Hyperbolic Feature-Based Sarcasm Detection in Telugu Conversation Sentences.Korra Sathya Babu, Reddy Naidu & Santosh Kumar Bharti - 2020 - Journal of Intelligent Systems 30 (1):73-89.
    Recognition of sarcastic statements has been a challenge in the process of sentiment analysis. A sarcastic sentence contains only positive words conveying a negative sentiment. Therefore, it is tough for any automated machine to identify the exact sentiment of the text in the presence of sarcasm. The existing systems for sarcastic sentiment detection are limited to the text scripted in English. Nowadays, researchers have shown greater interest in low resourced languages such as Hindi, Telugu, Tamil, Arabic, Chinese, Dutch, Indonesian, etc. (...)
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  5. MAPSOFT: A Multi-Agent Based Particle Swarm Optimization Framework for Travelling Salesman Problem.Yusuf Benson Baha, Gregory Wajiga, Aderemi Adewumi Oluyinka & Nachamada Vachaku Blamah - 2020 - Journal of Intelligent Systems 30 (1):413-428.
    This paper proposes a Multi-Agent based Particle Swarm Optimization Framework for the Traveling salesman problem. The framework is a deployment of the recently proposed intelligent multi-agent based PSO model by the authors. MAPSOFT is made up of groups of agents that interact with one another in a coordinated search effort within their environment and the solution space. A discrete version of the original multi-agent model is presented and applied to the Travelling Salesman Problem. Based on the simulation results obtained, it (...)
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  6.  4
    Improving Grey Prediction Model and Its Application in Predicting the Number of Users of a Public Road Transportation System.Hossein Baloochian & Saeed Balochian - 2020 - Journal of Intelligent Systems 30 (1):104-114.
    The recent increase in the road transportation necessitates scheduling to reduce the adverse impacts of the road transportation and evaluate the effectiveness of previous actions taken in this context. However, it is impossible to undertake the scheduling and evaluation tasks unless previous information are available to predict the future. The grey model requires a limited volume of data for estimating the behavior of an unknown system. It provides high-accuracy predictions based on few data points. Various grey prediction models have been (...)
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  7.  6
    Google Play Content Scraping and Knowledge Engineering Using Natural Language Processing Techniques with the Analysis of User Reviews.Muhammad Farhan, Rana M. Amir Latif, Ali Adil Qureshi, Meshrif Alruily, Abdullah Bajahzar & Hamza Aldabbas - 2020 - Journal of Intelligent Systems 30 (1):192-208.
    To maintain the competitive edge and evaluating the needs of the quality app is in the mobile application market. The user’s feedback on these applications plays an essential role in the mobile application development industry. The rapid growth of web technology gave people an opportunity to interact and express their review, rate and share their feedback about applications. In this paper we have scrapped 506259 of user reviews and applications rate from Google Play Store from 14 different categories. The statistical (...)
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  8.  1
    Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network.Tao Feng, Haoxuan Zhang, Tao Wu, Nan Li & Zhuhe Wang - 2020 - Journal of Intelligent Systems 30 (1):209-223.
    In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, (...)
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  9.  1
    Soft Computing Based Compressive Sensing Techniques in Signal Processing: A Comprehensive Review.Sanjay Jain & Ishani Mishra - 2020 - Journal of Intelligent Systems 30 (1):312-326.
    In this modern world, a massive amount of data is processed and broadcasted daily. This includes the use of high energy, massive use of memory space, and increased power use. In a few applications, for example, image processing, signal processing, and possession of data signals, etc., the signals included can be viewed as light in a few spaces. The compressive sensing theory could be an appropriate contender to manage these limitations. “Compressive Sensing theory” preserves extremely helpful while signals are sparse (...)
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  10.  3
    Aircraft Gearbox Fault Diagnosis System: An Approach Based on Deep Learning Techniques.Niranjan C. Kundur, S. Manjunath, M. Sreenatha & P. B. Mallikarjuna - 2020 - Journal of Intelligent Systems 30 (1):258-272.
    Gearbox is one of the vital components in aircraft engines. If any small damage to gearbox, it can cause the breakdown of aircraft engine. Thus it is significant to study fault diagnosis in gearbox system. In this paper, two deep learning models and Bi-directional long short term memory ) are proposed to classify the condition of gearbox into good or bad. These models are applied on aircraft gearbox vibration data in both time and frequency domain. A publicly available aircraft gearbox (...)
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  11.  2
    Crowd Counting Via Multi-Scale Adversarial Convolutional Neural Networks.Chengyang Li, Baoli Yang, Sikandar Ali, Hong Zhang & Liping Zhu - 2020 - Journal of Intelligent Systems 30 (1):180-191.
    The purpose of crowd counting is to estimate the number of pedestrians in crowd images. Crowd counting or density estimation is an extremely challenging task in computer vision, due to large scale variations and dense scene. Current methods solve these issues by compounding multi-scale Convolutional Neural Network with different receptive fields. In this paper, a novel end-to-end architecture based on Multi-Scale Adversarial Convolutional Neural Network is proposed to generate crowd density and estimate the amount of crowd. Firstly, a multi-scale network (...)
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  12. Research on Target Feature Extraction and Location Positioning with Machine Learning Algorithm.Licheng Li - 2020 - Journal of Intelligent Systems 30 (1):429-437.
    The accurate positioning of target is an important link in robot technology. Based on machine learning algorithm, this study firstly analyzed the location positioning principle of binocular vision of robot, then extracted features of the target using speeded-up robust features method, positioned the location using Back Propagation Neural Networks method, and tested the method through experiments. The experimental results showed that the feature extraction of SURF method was fast, about 0.2 s, and was less affected by noise. It was found (...)
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  13.  4
    Face Recognition in Complex Unconstrained Environment with An Enhanced WWN Algorithm.Yong Luo, Jianbin Xin, Jiwen Sun, Heshan Wang & Dongshu Wang - 2020 - Journal of Intelligent Systems 30 (1):18-39.
    Face recognition is one of the core and challenging issues in computer vision field. Compared to computer vision, human visual system can identify a target from complex backgrounds quickly and accurately. This paper proposes a new network model deriving from Where-What Networks, which can approximately simulate the information processing pathways of human visual cortex and recognize different types of faces with different locations and sizes in complex background. To enhance the recognition performance, synapse maintenance mechanism and neuron regenesis mechanism are (...)
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  14.  2
    Data Anonymization Through Collaborative Multi-View Microaggregation.Abdelouahid Lyhyaoui, Nicoleta Rogovschi, Younès Bennani & Sarah Zouinina - 2020 - Journal of Intelligent Systems 30 (1):327-345.
    The interest in data anonymization is exponentially growing, motivated by the will of the governments to open their data. The main challenge of data anonymization is to find a balance between data utility and the amount of disclosure risk. One of the most known frameworks of data anonymization is k-anonymity, this method assumes that a dataset is anonymous if and only if for each element of the dataset, there exist at least k − 1 elements identical to it. In this (...)
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  15.  2
    Identification of Biomarker on Biological and Gene Expression Data Using Fuzzy Preference Based Rough Set.Ujjwal Maulik, Debasis Chakraborty, Ram Sarkar & Shemim Begum - 2020 - Journal of Intelligent Systems 30 (1):130-141.
    Cancer is fast becoming an alarming cause of human death. However, it has been reported that if the disease is detected at an early stage, diagnosed, treated appropriately, the patient has better chances of survival long life. Machine learning technique with feature-selection contributes greatly to the detecting of cancer, because an efficient feature-selection method can remove redundant features. In this paper, a Fuzzy Preference-Based Rough Set blended with Support Vector Machine has been applied in order to predict cancer biomarkers for (...)
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  16.  3
    Kinect Controlled NAO Robot for Telerehabilitation.Erin McGonigle, Ying-Chih Wang, Mohammad Habibur Rahman, Md Rasedul Islam & Md Assad-Uz-Zaman - 2020 - Journal of Intelligent Systems 30 (1):224-239.
    In this paper, we focus on the human upper limb rehabilitation scheme that utilizes the concept ofteleoperation. Teleoperation can help the therapist demonstrate different rehab exercises to a different group of people at the same time remotely. Different groups of people from a different place connected to the same network can get therapy from the same therapist at the same time using the telerehabilitation scheme. Here, we presented a humanoid robot NAO that can be operated remotely by a therapist to (...)
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  17.  4
    Variable Search Space Converging Genetic Algorithm for Solving System of Non-Linear Equations.Deepak Mishra & Venkatesh Ss - 2020 - Journal of Intelligent Systems 30 (1):142-164.
    This paper introduce a new variant of the Genetic Algorithm whichis developed to handle multivariable, multi-objective and very high search space optimization problems like the solving system of non-linear equations. It is an integer coded Genetic Algorithm with conventional cross over and mutation but with Inverse algorithm is varying its search space by varying its digit length on every cycle and it does a fine search followed by a coarse search. And its solution to the optimization problem will converge to (...)
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  18. Deep Bidirectional LSTM Network Learning-Based Sentiment Analysis for Arabic Text.El Habib Nfaoui & Hanane Elfaik - 2020 - Journal of Intelligent Systems 30 (1):395-412.
    Sentiment analysis aims to predict sentiment polarities of a given piece of text. It lies at the intersection of many fields such as Natural Language Processing, Computational Linguistics, and Data Mining. Sentiments can be expressed explicitly or implicitly. Arabic Sentiment Analysis presents a challenge undertaking due to its complexity, ambiguity, various dialects, the scarcity of resources, the morphological richness of the language, the absence of contextual information, and the absence of explicit sentiment words in an implicit piece of text. Recently, (...)
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  19.  5
    Performance Modeling of Load Balancing Techniques in Cloud: Some of the Recent Competitive Swarm Artificial Intelligence-Based.Jeremy Pitt, B. Sathish Babu & K. Bhargavi - 2020 - Journal of Intelligent Systems 30 (1):40-58.
    Cloud computing deals with voluminous heterogeneous data, and there is a need to effectively distribute the load across clusters of nodes to achieve optimal performance in terms of resource usage, throughput, response time, reliability, fault tolerance, and so on. The swarm intelligence methodologies use artificial intelligence to solve computationally challenging problems like load balancing, scheduling, and resource allocation at finite time intervals. In literature, sufficient works are being carried out to address load balancing problem in the cloud using traditional swarm (...)
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  20.  2
    Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion.Kvsvn Raju, Vatsavayi Valli Kumari & Bagadi Ravi Kiran - 2020 - Journal of Intelligent Systems 30 (1):346-360.
    The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used in the various applications such as medical imaging and observing the skylight, etc. HDR imaging techniques usually have the issue of lower efficiency due to capturing of multiple photos. In this paper, an efficient (...)
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  21. Pruning and Repopulating a Lexical Taxonomy: Experiments in Spanish, English and French.Irene Renau, Rafael Marín, Gabriela Ferraro, Antonio Balvet & Rogelio Nazar - 2020 - Journal of Intelligent Systems 30 (1):376-394.
    In this paper we present the problem of a noisy lexical taxonomy and suggest two tasks as potential remedies. The first task is to identify and eliminate incorrect hypernymy links, and the second is to repopulate the taxonomy with new relations. The first task consists of revising the entire taxonomy and returning a Boolean for each assertion of hypernymy between two nouns. The second task consists of recursively producing a chain of hypernyms for a given noun, until the most general (...)
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  22.  3
    Best Polynomial Harmony Search with Best Β-Hill Climbing Algorithm.Eugene Santos & Iyad Abu Doush - 2020 - Journal of Intelligent Systems 30 (1):1-17.
    Harmony Search Algorithm is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation when trying to solve complex problems. The algorithm relies on three operators for performing improvisation: memory consideration, pitch adjustment, and random consideration. In order to improve algorithm efficiency, we use roulette wheel and tournament selection in memory consideration, replace the (...)
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  23.  1
    Land Use Land Cover Map Segmentation Using Remote Sensing: A Case Study of Ajoy River Watershed, India.Anasua Sarkar, Subhasish Das, Rajib Das & Kalyan Mahata - 2020 - Journal of Intelligent Systems 30 (1):273-286.
    Image segmentation in land cover regions which are overlapping in satellite imagery, is one crucial challenge. To detect true belonging of one pixel becomes a challenging problem while classifying mixed pixels in overlapping regions. In current work, we propose one new approach for image segmentation using a hybrid algorithm of K-Means and Cellular Automata algorithms. This newly implemented unsupervised model can detect cluster groups using hybrid 2-Dimensional Cellular-Automata model based on K-Means segmentation approach. This approach detects different land use land (...)
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  24. Characteristic Analysis of Flight Delayed Time Series.Ou Shangheng & Ma Lan - 2020 - Journal of Intelligent Systems 30 (1):361-375.
    In order to analyze the characteristics of airport flight delayed time series, based on the construction of flight delay time series, firstly, the K-means algorithm is used to cluster the time series of delayed departures. Secondly, combining with R/s analysis method of Fractal theory, Hurst index of the series is calculated, and Fractal characteristics of the series are analyzed. Then, the VAR model is constructed, and Impulse Response Function and Variance Decomposition are conducted to explore the impact of the fluctuation (...)
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  25.  1
    A Deep Level Tagger for Malayalam, a Morphologically Rich Language.M. Sreenathan, Mary Idicula Sumam, K. J. Abrar & A. P. Ajees - 2020 - Journal of Intelligent Systems 30 (1):115-129.
    In recent years, there has been tremendous growth in the amount of natural language text through various sources. Computational analysis of this text has got considerable attention among the NLP researchers. Automatic analysis and representation of natural language text is a step by step procedure. Deep level tagging is one of such steps applied over the text. In this paper, we demonstrate a methodology for deep level tagging of Malayalam text. Deep level tagging is the process of assigning deeper level (...)
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  26.  2
    Robust Gaussian Noise Detection and Removal in Color Images Using Modified Fuzzy Set Filter.E. Srinivasa Reddy & Akula Suneetha - 2020 - Journal of Intelligent Systems 30 (1):240-257.
    In the data collection phase, the digital images are captured using sensors that often contaminated by noise. In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set (...)
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  27. A Novel Dual Image Watermarking Technique Using Homomorphic Transform and DWT.Vinay Kumar Srivastava & Priyank Khare - 2020 - Journal of Intelligent Systems 30 (1):297-311.
    In this paper a new technique of dual image watermarking is proposed for protection of ownership rights which utilizes salient properties of homomorphic transform, discrete wavelet transform, singular value decomposition and Arnold transform. In embedding algorithm host image is splitted into reflectance and illumination components using HT, DWT is further applied to the reflectance component resulting in frequency subbands which are transformed by SVD. Two image watermarks are selected for embedding process whereas security of proposed algorithm is strengthen by performing (...)
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  28.  5
    Automatic Generation and Optimization of Test Case Using Hybrid Cuckoo Search and Bee Colony Algorithm.T. V. SureshKumar & P. Lakshminarayana - 2020 - Journal of Intelligent Systems 30 (1):59-72.
    Software testing is a very important technique to design the faultless software and takes approximately 60% of resources for the software development. It is the process of executing a program or application to detect the software bugs. In software development life cycle, the testing phase takes around 60% of cost and time. Test case generation is a method to identify the test data and satisfy the software testing criteria. Test case generation is a vital concept used in software testing, that (...)
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