International Journals

Permanent URI for this collectionhttps://dspace.psgrkcw.com/handle/123456789/164

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Start date: 2020End date: 2023

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Now showing 1 - 7 of 7
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    RELAXED HYBRID ROUTING TO PREVENT CONSECUTIVE ATTACKS IN MOBILE AD-HOC NETWORKS
    (ACM Journals, 2023-06-05) Viji Gripsy J; Kanchana K R
    In the current trends, Wi-Fi networks and cellular ad-hoc community (MANET) have yielded incredible opportunity and recognition. This opportunity and popularity insisted on many forms of studies to recognition on it. This enormously bendy nature of the MANET additionally creates many community performance associated and protection associated problems. Numerous security vulnerabilities threaten the technique in MANET in diverse ways. The new and changed protocol is called Secure Route Discovery-Ad-hoc On-demand Distance Vector (SRD-AODV) protocol. This protocol includes one-of-a-kind additives and techniques to offer each proactive and reactive answers through deploying powerful authentication the use of the Modified Elliptic Curve Diffie-Hellman Algorithm (MECDHA) techniques. This additionally aims to comfort the records packets and routing desk records and subsequently the incursion detection and prevention from sequential attacks in MANET.
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    EXPERT AUTOMATED SYSTEM FOR PREDICTION OF MULTI-TYPE DERMATOLOGY SICKNESSES USING DEEP NEURAL NETWORK FEATURE EXTRACTION APPROACH
    (IJISAE, 2023) Kalaivani A; Karpagavalli S; Kamal, Gulati
    One of the most prevalent illnesses on the planet is skin issues. Due to the complexity of types of skin, and hair types, it is difficult to evaluate it despite its popularity.Consequently, skin conditions pose a serious public health danger. When they reach the invasive stage of evolution, they become harmful. Medical professionals are very concerned about dermatological disorders. The number of people who suffer from skin illnesses is growing substantially as a result of rising pollution and bad food. People frequently ignore the early indications of skin conditions. A hybrid approach can minimize human judgment, producing positive results quickly. A thorough examination suggests that frameworks for recognizingvarious skin disorders may be built using deep learning techniques. To find skin illnesses, it is necessary to distinguish between theskin and non-skin tissue. Through the use of feature extraction-baseddeep neural network approaches, a classification system for skin diseases was established in this study. The main goal of this system is to anticipate skin diseases accurately while also storing all relevant state data efficiently and effectively for precise forecasts. The significant issues have been addressed, and a unique, feature extraction-based deep learning modelis introduced to assist medical professionals in properly detecting the type of skin condition.The pre-processing stage is when the inputdataset is first supplied, helping to clear the image of any undesired elements. Then, for the training phase, the proposed Feature Extraction Based Deep Neural Network (FEB-DNN) is fed the features collected from each of the pre-processed frames. With the use of measured parameters, the classification system categorizesincoming treatment data as various skin conditions. Finding the ideal weight values to minimizetraining error is crucial while learning the proposed framework. In this study, an optimization strategy is used to optimizethe weight in the structure. Based on the feature extraction approach, the suggested multi-type framework for diagnosing skin diseases has a 91.88% of accuracyrate for the HAM image dataset and identifies several skin disorder subtypes than the earlier models thatcan aid in treatment response and decision-makingwhich alsohelp doctors make an informed decision.
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    A SURVEY: IOT BASED HOME SECURITY AND AUTOMATION SYSTEM
    (Kalahari Journals, 2022-01) Vijayalakshmi K; Rasika S; Ponmalar S; Deepa V
    Advance in knowledge from last few decades opens doors to various threats to human and his environments. Individuals with the progression in security had taken numerous measures to control the bullying for protecting their properties. From time to time numerous interruption finding systems conventional for earmark intruders from home environment and provide tangible benefits to users, but can also expose users to significant security risk. Smart home security system is gaining popularity for industry, government, and academia as well as for distinct that has the potential to bring significant private, specialized and economic benefits. This paper signifies smart home security system and response rapidly to alarm incidents and has a friendly user interface. Special emphasis is placed on the experimental security analysis of such developing smart home platform by separating into two case scenarios. The paper will conclude by discussing future perspective and challenges associated with the development of security system for home.
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    PENETRATION OF TECHNOLOGY TO VIRTUAL REALITY IN ARTIFICIAL INTELLIGENCE AND ITS CHALLENGES
    (2020-02) Reshmi S; Jawahar S; Ahamed Johnsha Ali S
    Virtual reality makes an imaginary biosphere as well as factual ecosphere which smears to mainframe imitation milieus. Virtual reality comprises the domains of applications such as training simulators, medical and physical condition centre. Second life is an art of technologies in virtual reality. It contains the influence of both positive and negative authenticity of average people in life is ventured. It is a gruelling situation by performing benign and with an erudition outlook. Artificial intelligence is a deputize turf of mainframe discipline. In AI, the advance technologies is to be pervasive with impacts and ramifications in health, security and governance. It combines with other emerging and converging technologies. In accounting field, the predictable trend brings tremendous changes and progress to the artificial intelligence technologies.
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    BIOLOGICAL SOFTWARE FOR RECOGNITION OF SPECIFIC REGIONS IN ORGANISMS
    (Bioscience Biotechnology Research Communication, 2020-03) Kavitha A.S; Viji Gripsy J; Menaka V
    The identification of specific regions in an organism of a plant, animal or a single-celled life form, or something that has interdependent parts and that is being compared to a living creature. User can choose and select any type of organism’s image such as plant or animal. After successful selection, the proposed tool automatically analyses and finds the name of the organisms and identifies the specific region with some other related information in an effective manner. In comparative and evolutionary genomics, a detailed comparison of common features between organisms is essential to evaluate genetic distance. However, identifying differences in matched and mismatched genes among multiple genomes is difficult using current comparative genomic approaches due to complicated methodologies or the generation of meager information from obtained results. This research reduces the manual activity to analyze the details. Using this software tool, it easily helps us to know all the related organisms information of specific region and also can make report effectively. This makes the system user-friendly consequently reducing the manual work. The system has been developed with advanced features. The objective of this work is to establish an identification of specific region organisms and related information. The system developed with the main intension to progress an effective and user friendly tool for identification of the specific region in organisms. From the experimental results, the proposed system grasps and more and more identification accuracy.
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    A SURVEY ON WHITE BLOOD CELL CLASSIFICATION USING MICROSCOPIC IMAGES
    (International Journal for Scientific Research and Developement (IJSRD), 2020-01) Ponmalar S; Sneha S; Sruthimol S
    White blood cells study is generally done for diagnosis of different diseases. One of those diseases is Acute lymphoblastic leukemia (ALL). ALL is detected by observing morphological changes in white blood cells. Morphological study along with categorization and segmentation techniques helps to identify leukemia at early stage and perfect detection. There are number of categorization techniques which can be used to classify WBC into different classes as per their respective features. Segmentation techniques segments nucleus and cytoplasm from each WBC and feature mining process extract features from nucleus and cytoplasm for accurate result. In this paper we suggest a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, remove suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte.
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    CANDIDATE GENE IDENTIFICATION APPROACH: PROGRESS AND CHALLENGES
    (International Journal for Scientific Research and Developement (IJSRD)., 2020-01) Deepa V; Varsha N; Varshinee M
    Gene expression profile analysis is the study of the way in which genes are transcribed to produce functional gene products (functional RNA species or protein products). There has been tremendous innovation in gene expression technologies, including high-throughput assays such as microarrays, and sequence-based techniques such as RNA-Seq. The Gene expressions are collected and analyzed for normal or disease genes. Using this project the system can diagnose types of diseases and abnormalities which may affect the user.