National Journals

Permanent URI for this collectionhttps://dspace.psgrkcw.com/handle/123456789/160

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Start date: 2020End date: 2022

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Now showing 1 - 5 of 5
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    RECURRRENT NEURAL NETWORK BASED MODEL FOR AUTISM SPECTRUM DISORDER PREDICTION USING CODON ENCODING
    (Journal of The Institution of Engineers (India): Series B, 2022-09) Sudha V, Pream; Vijaya, M S
    Deep learning methods are noteworthy tools that go together with traditional machine learning techniques to enable computers learn from data and create smarter applications. Deleterious gene classification is an important task in a standard computational framework for biomedical data analysis. As gene sequences are high dimensional and do not represent explicit attributes for computational modelling, extracting features from them becomes a complex task. Recently neural deep learning architectures automatically extract valuable features from input patterns. The principal idea of this work is to exploit the power of Recurrent Neural Networks (RNN) to learn sequential patterns through high-level information associated with observed signals which in turn can be used for classification. Classification of affected genes that cause disease like Autism-spectrum disorder (ASD) is a noteworthy challenge in biomedical research. Long Short Term Memory (LSTM) units go well with sequence-based tasks with long-term dependencies and hence this work examines a stacked LSTM architecture for classifying genes causing ASD. The model is trained and tested with two hand crafted datasets and a codon encoded dataset. Experiments revealed the superiority of these advanced recurrent units compared to the traditional Deep Neural Networks and Bi-directional RNNs distinctively with codon encoded dataset
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    RIVER WATER QUALITY PREDICTION AND INDEX CLASSIFICATION USING MACHINE LEARNING
    (IOP Science, 2022) Jitha, P Nair; M S, Vijaya
    Various pollutants have had a substantial impact on the quality of water in recent years. The quality of water directly impacts human health and the environment. The water quality index (WQI) is an indicator of effective water management. Water quality modelling and prediction have become essential in the fight against water pollution. The research aims to build an efficient prediction model for river water quality and to categorize the index value according to the water quality standards. The data has been collected from eleven sampling stations located in various locations across the Bhavani River, which flows through Kerala and Tamilnadu. The water quality index is determined by 27different parameters affecting water quality like dissolved oxygen, temperature, pH, alkalinity, hardness, chloride, coliform, etc. Data normalization and feature selection are done to construct the dataset to develop machine learning models. Machine learning algorithms such as linear regression, MLP regressor, support vector regressor and random forest has been employed to build a water quality prediction model. Support vector machines (SVM), naïve bayes, decision trees, MLP classifiers, have been used to develop a classification model for classifying water quality index. The experimental results revealed that the MLP regressor efficiently predicts the water Quality index with root mean squared error as 2.432, MLP classifier classifies the water quality index with 81% accuracy. The developed models show promising output concerning water quality index prediction and classification.
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    ANTI-DIABETIC POTENTIAL OF INDIAN MEDICINAL PLANTS WITH GARCINIA KOLA AND SYZYGIUM CUMINI
    (A & V Publications, 2021) K J, Sharmila; L, Kanimozhi; Priya, J Shanmuga; G V, Vidhya; Caroline, R Jeba; R, Kowsalya
    Diabetes mellitus is a group of metabolic disease in which a person experiences high blood glucose levels either because the body produces inadequate insulin in the body. Though there are several treatment options available there are limitations such as high costs and side effects, weight gain etc. For this reason, the use of medicinal plants has increased to be used as an anti-diabetic agent with less side-effect and more efficient. In this regard, this study analyzed the anti-diabetic potential of Garcinia kola and Syzygium cumini using alpha amylase inhibition assay and glucose uptake by yeast cells. It was observed that Ethanol extract of Garcinia kola increased anti-diabetic potential compared to Syzygium cumini.
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    SECURE AND EFFICIENT FIRE-FLY DATA ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS IN IOT MONITORING SYSTEMS
    (IOP Publishing, 2021) Kowsalya R; Rosiline Jeetha B
    In the Electronics world the sensor is used in IoT applications. The sensed data need to be transfer to the appropriate devices as input for further processing. Clustering used to group the sensors which could form cluster and select the nodes head from the cluster. The head of each cluster receives the forwarded data through the cluster member and pass on to nearest permanent fixed station. Identifying cluster head and shortest route identification is a major challenge. This paper proposed a novelty on hybrid decision making algorithm with firefly routing algorithm (HDMFRA) for Cluster Head selection. This research work focusing of three main criteria which could save the energy and extend the life activation of the node, through the usage of energy, amount of nodes adjacent and energy consumption from permanent fixed station. To aggregate the data in optimized manner and to transfer the data in efficient manner Fire Fly routing algorithm was used. Simulation results show that proposed algorithm HDMFRA network in homogeneous environment is effective and prolonging the life time of the node by 25%.
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    AN ENERGY COMPACTION USING OPTIMIZED DSR AND BRANCH AND BOUND ALGORITHM IN MANET
    (The Mattingley Publishing Co.Inc, 2020-04) Sasikala S; Ponmuthuramalingam P
    Mobile Ad-hoc Network (MANET) is used for wireless communication, in that mobile nodes forms a communication without infrastructure. In the wireless communication, Routing has been the most decisive area of research in ad hoc network. The prominent type of MANET protocol is DSR protocol. Dynamic Source Routing (DSR) is used for the effective route discovery. The DSR protocol is incorporated with Branch and Bound algorithm for the optimal route discovery. The proposed algorithm, Modify DSR with Modify Branch and Bound aims at increasing the energy utilizing level in Discover Routing, Packet forwardingand Collision avoidance. It helps to progress the efficiency of the energy level in MANET. One of the chief impact of this research work is to ensure Packet forwarding with efficient utilization of Energy attributes in MANET. Performance metrics like End to end Delay, Packet Delivery Ratio (PDR), Nodes Energy, Network Life time, Routing Overhead and Throughput has used for the evaluation of performance of the proposed algorithm.