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Form the time of its invention, microarray technology is continuously growing and has been taking major role in biological research. This technology generates huge amount of gene expression data for biological analysis. Parallel computation methods are required to find functional associations from this large amount of biological data. An unsupervised machine learning technique, clustering algorithm...
This paper presents a Pose Invariant Face Recognition algorithm for pose-variance in face databases, which is one of the toughest challenges of any face recognition based biometrics, using a novel feature extraction technique. The feature extraction of the raw images is based upon a novel patch-wise self-similarity measure within an image. The algorithm has been tested upon a Far-infrared (FIR) imaging...
Pancreatic ductal adenocarcinoma (PDAC) is one of most aggressive malignancy. The identification of Biomarker for PDAC is an ongoing challenge. The high dimensional PDAC gene expression dataset in Gene Expression Omnibus(GEO) database, is analyzed in this work. To select those genes which are relevant as well as with least redundancy among them, we use successive approaches like Filter methods and...
Machine learning classifiers help physicians to make near-perfect diagnoses, minimizing costs and time. Since medical data usually contains a high degree of uncertainty and ambiguity, proper ordering and classification require a proper comparative performance analysis of machine learning classifiers. Machine learning classifiers are applied on the Ovarian Cancer Dataset. Ovarian cancer is the fifth...
The practice of using divide and conquer techniques to solve complex, time-consuming problems has been in use for a very long time. Here we evaluate the performance of centroid-based clustering techniques, specifically k-means and its two approximation algorithms, the k-means++ and k-means|| (also known as Scalable k-means++), as divide and conquer paradigms applied for the creation of minimum spanning...
Multi-Scale Retinex (MSR) algorithm enhances images that are taken in nonlinear lighting conditions. In this paper, we propose an automated approach for image enhancement using MSR and Flower Pollination Algorithm (FPA) to select the optimal weights to the different scales of Gaussian filters from the desired image for MSR. The experiments are carried out using blood cell microscopic imaging to investigate...
Identification of the correct medicinal plants that goes in to the preparation of a medicine is very important in ayurvedic medicinal industry. The main features required to identify a medicinal plant is its leaf shape, colour and texture. Colour and texture from both sides of the leaf contain deterministic parameters to identify the species. This paper explores feature vectors from both the front...
In this modern era of communication, people are always connected to the internet. Hence, everyone tends to express their opinions on social media or e-commerce websites about commercial products, movies, sports, social and geopolitical matters and even on government policies. These opinions reflect the corresponding person's view or sentiment about that particular matter, which ultimately leads to...
Though accident data have been collected across industries, they may inherently contain uncertainty of randomness and fuzziness which in turn leads to misleading interpretation of the analysis. To handle the issue of uncertainty within accident data, the present work proposes a rough set theory (RST)-based approach to provide rule-based solution to the industry to minimize the number of accidents...
Recent times have seen an exponential increase in the use of artificial intelligence in numerous regions. Fields like education, transport, finance, and health have made drastic improvements in the last decade; from predicting the stock market prices and driverless cars to predicting cancer cells in human body. Artificial intelligence and Machine learning combined, have shaped the world to be a better...
In this work a machine learning approach is proposed for prediction of volatile substance abuse. Machine learning technique used in this work is artificial neural networks (ANN). Two ANN modules are designed, ANN-D to predict whether a person is using VSA or not and ANN-C to predict the time of use. Input features used are age, gender, country, ethnicity, education, neuroticism, openness to experience,...
Feature selection is an important task in data mining, which aims to reduce the dimensionality of the data sets while at least maintaining the classification performance. Chicken swarm optimization algorithm (CSO) has been widely applied to feature selection because of its efficiency and effectiveness. However, since feature selection is a challenging task with a complex search space, CSO quickly...
This work proposes an ANN based method for fetal heart rate monitoring. Various measurements are taken and given as input to the ANN based classifier to detect fetal health such as ‘Normal’, ‘Suspect’ and ‘Pathologic’. All the design and simulation works are carried out with MATLAB software. ANN based classifier is trained with data from various recordings of cardiotocography. After the network is...
Machine learning is widely used in various applications such as data mining, computer vision, and bioinformatics owing to the explosion of available data. However, in practice, many data have some missing attributes. The graphic theory serves as a powerful tool for modeling and analyzing many such practical problems, such as networks of communication and data organization. This paper focuses on semi-supervised...
Power system stabilizer (PSS) is extensively used to enhance the angular stability by providing damping to the generator's oscillation. An electric torque is enforced in the rotor shaft in phase with the speed variation to provide this damping. In this paper a PSO based Robust Power System Stabilizer (RPSS) design has been proposed depending upon mixed sensitivity based H output feedback control in...
Present work introduces a most popular evolution based algorithm and applied in two degree of freedom proportional integral Derivative (TDOFPID) Controller based multi area power system. Differential Evolution (DE) optimization technique is applied here to tune the TDOFPID gains. In each area of system consists of Automatic generation control with addition of non-linarites. In this model time delay,...
Clustering, a well-known technique, is used to divide a data set into number of groups, called clusters. Differential evolution and particle swarm optimization are robust, fast and very effective search techniques. To increase computational capability, two different quantum inspired meta-heuristics for automatic clustering, have been proposed here. An application of quantum inspired techniques has...
Millions of users harvest their personal information (photo, video, status) on different online social networks (OSNs). Hence, these rich repositories of sensitive information attract the eyes of adversary to launch variety of cyber attacks on OSN. Here we have identified all crucial threats on social network that may lead to severe risks. In this paper, we have formalized possible social network...
Cloud computing technology is gaining rapid growth in popularity. Mostly it is web based service and some private modules are built on intranet or virtual private network. Network security is a major concern for both cloud users and hosts of data centers. In addition to this, clients are also concerned about the infrastructure and service quality offered by cloud service providers. Cloud service providers...
The present work proposes an unsupervised approach for recognising relations between named entities from a large corpora based on crime in Indian states and union territories. Initially, named entities have been identified from the extracted crime corpus and certain pair of entities have been chosen that facilitates the crime analysis. Then the entity pairs with their intermediate context words have...
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