Papers by KIRAN RAVULAKOLLU
Decision Analytics Journal
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Artificial Intelligence Review
Advancements in cloud technologies have increased the infrastructural needs of data centers due t... more Advancements in cloud technologies have increased the infrastructural needs of data centers due to storage needs and processing of extensive dimensional data. Many service providers envisage anomaly detection criteria to guarantee availability to avoid breakdowns and complexities caused due to large-scale operations. The streaming log data generated is associated with multi-dimensional complexity and thus poses a considerable challenge to detect the anomalies or unusual occurrences in the data. In this research, a hybrid model is proposed that is motivated by deep belief criteria and meta-heuristics. Using Search-and-Rescue—BrainStorm Optimization (SAR-BSO), a hybrid feature selection (FS) and deep belief network classifier is used to localize and detect anomalies for streaming data logs. The significant contribution of the research lies in FS, which is carried out using SAR-BSO which increases the detection power of the model as it selects the most significant variables by minimizi...
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2022 9th International Conference on Computing for Sustainable Global Development (INDIACom)
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Int. J. Netw. Secur., 2018
This paper proposes Hybrid Feature Selection Approach – Heterogeneous Ensemble of Intelligent Cla... more This paper proposes Hybrid Feature Selection Approach – Heterogeneous Ensemble of Intelligent Classifiers (HyFSA-HEIC) for intelligent lightweight network intrusion detection system (NIDS). The purpose is to classify for anomaly from the incoming traffic. This system hierarchically integrates HyFSA and HEIC. The HyFSA will obtain the optimal number of features and then HEIC is built using these optimal features. HyFSA helps to decrease the computation time of the system and make it lightweight to work in real time. The aim of HEIC is to obtain accurate and robust classifier and enhance overall performance of the system. The results demonstrate that proposed system outperforms other ensemble and single classifier methods used in this paper. It has true positive rate (99.9%), accuracy (99.91%), precision (99.9%), receiver operating characteristics (99.9%), low false positive rate (0.1%) and lower root mean square error rate (3.06%) with a minimum number of selected 6 features. It also...
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2022 9th International Conference on Computing for Sustainable Global Development (INDIACom)
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2022 9th International Conference on Computing for Sustainable Global Development (INDIACom)
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2022 9th International Conference on Computing for Sustainable Global Development (INDIACom)
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2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2020
Latent fingerprints are (un)intentional finger skin impressions left as ridge patterns at crime s... more Latent fingerprints are (un)intentional finger skin impressions left as ridge patterns at crime scenes. The significant challenge in latent fingerprint segmentation is extracting complex, multiple, noisy foreground fingermarks while maintaining the performance of the system. The work presented in this paper provides a method to extract fingerprints from the latent fingerprint images dataset (IIIT-D) using a stack of convolutional auto-encoders. The idea is to early detect the structure of interest from the image using a color-based mask. These structures are divided into equal-sized patches and classification of these patches into fingermark or background class-labeling is achieved using staked convolutional autoencoders. To establish stable layered architecture and an optimal amount of information in patches as input to these layers, the impact of different patch-size is analyzed on various stacks of the layered architecture of the underlying deep neural network. Reduced feature le...
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Cloud Computing is a new resource platform that offers abundant amount of services for organizati... more Cloud Computing is a new resource platform that offers abundant amount of services for organizations to meet furthermore satisfies the needs without huge and prior investment. When it comes to the development of a cloud, architecture plays a critical role. Architectural design is the primary step to meet the client demands. The purpose of this paper is to design a feasible and low-cost architecture that can be adapted for small-scale academic organizations. However, the architecture is expected to provide reliable and qualitative services such as SaaS, PaaS considering risk analysis into account. During the process, customization is carried out at possible stages of cloud development, such that the chances of generating a low-cost architecture maximizes. Proposed architecture considers limitations on hardware, middle ware, open source platforms, additional modules and client requirements during the development process. Novelty in proposed architecture lies in addition of group handl...
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— Millions of children need to be peregrinating from home to school and vice versa every day. For... more — Millions of children need to be peregrinating from home to school and vice versa every day. For parents, obtaining a safe convey for their children is a critical issue. Many children find themselves missing the school bus, stepping into the erroneous bus, or leaving at the erroneous station with no method to track them. This research tested the applicability of radio frequency identification (RFID) technology in tracking and monitoring children during their peregrination to and from school on school busses. The child safety system developed in this research utilized the passive RFID tracking technology due to its efficient tracking capabilities, low cost, and facile maintenance. These experiments showed that the RFID tags were efficacious and stable enough to be utilized for prosperously tracking and monitoring children utilizing the bus.
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2013 International Conference on Intelligent Systems and Signal Processing (ISSP), 2013
ABSTRACT Localization is very essential for interaction when it comes to multisensory integration... more ABSTRACT Localization is very essential for interaction when it comes to multisensory integration. Based on Superior Colliculus (SC) motivation, the audio and visual signal processing during the stimuli integration is investigated. A novel methodology is proposed using neural network architecture that can localize effectively, especially in integrating stimuli of varied intensities in lower order audio and visual signals. During the integration, cases arise where the SC is unable to localize the source due to simultaneous arrival of too weak or too strong stimuli, causing enhancement and depression phenomena. This phenomena arise when the SC is not able to localize the source based on the given stimuli intensities. This paper provides a dual layered neural network model that integrates visual and audio sensory stimuli and also drives a way to track the stimuli source. This behavior is applicable for guided robots that help humans to track or cooperate for tasks like personal assistance, route guidance and incident tracking applications.
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Studies in Computational Intelligence, 2009
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Procedia Computer Science, 2012
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www.his.sunderland.ac.uk Abstract. Information processing and responding to sensory input with ap... more www.his.sunderland.ac.uk Abstract. Information processing and responding to sensory input with appropriate actions are among the most important capabilities of the brain and the brain has specific areas that deal with auditory or visual processing. The auditory information is sent first to the cochlea, then to the inferior colliculus area and then later to the auditory cortex where it is further processed so that then eyes, head or both can be turned towards an object or location in response. The visual information is processed in the retina, various subsequent nuclei and then the visual cortex before again actions will be performed. However, how is this information integrated and what is the effect of auditory and visual stimuli arriving at the same time or at different times? Which information is processed when and what are the responses for multimodal stimuli? Multimodal integration is first performed in the Superior Colliculus, located in a subcortical part of the midbrain. In t...
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India being the second most populated country in the world with over a billion population and ove... more India being the second most populated country in the world with over a billion population and over a million hearing impaired and diabetes disease patients, a translation system which can translate a given input into sign languages can be used to disseminate information to the million hearing impaired patients. Such people find it difficult to access information in common places like hospitals and railway stations. A translation system which can convert English into Indian Sign Languages can be developed to help such people. Machine Translation (MT) is an innovative paradigm that promotes the advancement of science and technology to built smart environments. It advocates an invisible technological support layer of information processing to improve the quality of life. In this paper we discuss. Present study contains possibilities of integrating concept related to natural language processing (NLP) certain aspects of integrating English languages to sign language.
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Sign language is used by deaf and hard hearing people to exchange information between their own c... more Sign language is used by deaf and hard hearing people to exchange information between their own community and with other people. Computer recognition of sign language deals from sign gesture acquisition and continues till text/speech generation. Sign gestures can be classified as static and dynamic. However static gesture recognition is simpler than dynamic gesture recognition but both recognition systems are important to the human community. The sign language recognition steps are described in this survey. The data acquisition, data preprocessing and transformation, feature extraction, classification and results obtained are examined. Some future directions for research in this area also suggested.
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Making software adaptable to evolving requirements is a challenge for the software industry. The ... more Making software adaptable to evolving requirements is a challenge for the software industry. The reason behind it is that adaptation compels software developers to follow almost all software developmental stages, from code development to software deployment. Due to this, any change in requirements, the iteration should be re-initiated. Thereby, adaptation requires software reconfiguration and redeployment. However, adaptation can be automated by giving the ability for software to evolve dynamically with evolving requirements. Hence, during the initial stages of software development, requirements adaptation has to be incorporated. This paper presents a solution as a novel intelligent agent-based architecture as a concept to support runtime adaptation. The focus lies in determining the feasibility and potential of having an intelligent agent facilitating acquisition and capturing of dynamic requirements within the architecture to obtain evolutionary mechanism in software. Fuzzy reason...
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Int. J. Perform. Eng., 2021
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This paper presents the offline handwritten character recognition for Devnagari, a major script o... more This paper presents the offline handwritten character recognition for Devnagari, a major script of India. The main objective of this work is to develop a handwritten dataset (CPAR-2012) for Devnagari character and further develop a character recognition scheme for benchmark study. The present dataset is a new development in Devnagari optical document recognition. The dataset includes 78,400 samples collected from 2,000 heterogeneous strata of Hindi speaking persons. These dataset is further divided into 49,000 as training set and 29,400 as test set. The evaluated feature extraction includes: direct pixel, image zoning, wavelet transformation and Gaussian image transformation techniques. These features were classified by using KNN and neural network classifier. The experiment shows that Gaussian image transformation (level 1) using KNN classifier has achieved highest recognition 72.18 % than other feature extraction methods. Further classification result obtained from KNN classifier ...
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International Journal of Technology Enhanced Learning, 2021
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Papers by KIRAN RAVULAKOLLU