A study of resistome of Candidozyma auris from 20 year genomic datasets D. Elantamilan, Jyotismita Rajbongshi, V. Mangayarkarasi Indian Journal of Medical Microbiology, 2026 PURPOSE: To conduct a comprehensive retrospective analysis of antimicrobial resistance (AMR) gene distribution in publicly available Candidozyma auris genomes to characterize global prevalence, temporal trends, geographic distribution patterns, and co-occurrence of resistance determinants over a 20-year period. METHODS: A cross-sectional genomic analysis was performed using 538 unique C. auris genome assemblies retrieved from the European Nucleotide Archive (2004-2024). AMR gene detection was conducted using ChroQueTas computational tool with the FungAMR database. Statistical analyses examined resistance gene frequencies, temporal trends, geographic distribution across 32 countries, co-occurrence patterns, and predicted antifungal resistance profiles. RESULTS: Of 538 genomes analysed, 460 (85.50%) harbored at least one AMR gene. Cyp51 was the most prevalent resistance gene (455 genomes, 84.57%), followed by Tac1 (109 genomes, 20.26%), Erg6 (12 genomes, 2.23%), and Fks (11 genomes, 2.04%). The majority of genomes (61.9%) contained a single resistance gene type, while 23.42% carried two distinct gene types. Temporal analysis revealed increasing detection of Cyp51 and Tac1 from 2019 onwards, peaking in 2022-2023. Geographic hotspots included Pakistan, Turkey, and Hong Kong. The most common gene co-occurrence was Cyp51 and Tac1 (105 genomes). Predicted resistance to fluconazole (85.32%) and voriconazole (83.83%) was most prevalent, with 313 genomes showing predicted pan-drug resistance. CONCLUSIONS: This study confirms high prevalence of AMR determinants in C. auris globally, with increasing temporal trends and significant co-occurrence of multiple resistance mechanisms. The findings emphasize the escalating therapeutic challenge posed by multidrug-resistant C. auris and highlight the critical need for enhanced genomic epidemiology studies.
Feature Group Extraction for Rice Disease Prediction using VGG-16 Model B. Gohin, C. Thinkal Dayana, D. Elantamilan, A.P. Praveen Kumar 2nd International Conference on Sustainable Computing and Smart Systems Icscss 2024 Proceedings, 2024 Rice plants have been the focus of significant attention from agricultural specialists. However., there has not been any comprehensive inquiry into the matter of plant diseases. It is crucial to accurately identify rice infections to prevent the major adverse effects of the disease on crop yield. The current diagnostic procedures for rice diseases are neither exact nor effective., and additional apparatus is sometimes required. It is essential to detect any sickness in its earliest stages to ensure the rice plants continue to develop normally and healthily. Manual detection of disease involves significant time and effort; hence., creating an automated system makes sense. This paper presents a machine learning technique for diagnosing rice leaf tissue illnesses. According to the findings., the three diseases known as leaf smut., bacterial leaf blight., and brown spot harm rice plants the most often. The data was presented as high-quality images of rice leaves with various types of damage superimposed on a white background. This paper proposes a novel feature-clustering based VGG-16 model for rice disease detection. Initially., the crop images are preprocessed with a Wiener filter and color enhancement techniques. Then., the features are grouped using a density-based technique known as DBSCAN. Finally., the VGG-16 model is used for classifying rice diseases. The decision tree approach achieved an accuracy of more than 97% on the test dataset with 10-fold cross-validation.
EDPP: Intelligent and Robust Data Sharing Framework using Enhanced Data Preserving Paradigm D Elantamilan, R. Gnanavel, D. Vinod, M. K. Nalini, K Dhinakaran Proceedings IEEE International Conference on Advances in Computing Communication and Applied Informatics Accai 2022, 2022 Growing amounts of information sources are required as the quantity of available information from various sources, both self governing and heterogeneous data maintenance requirement increases. A major component of the increased interest in big data is the heterogeneity of the data itself. In this work, data communications is researched, in which it is the method of constructing a specific case of direct instruction from an illustration of reference conceptual framework, so that when the eventually results entity conforms with target schema configuration. The logic of schema mappings are high-level expressions used to specify relationships across databases and are often used in this process. The experimental results of this paper provide proper proof to the efficiency of research and the results are acquired based on the real-time working emulations.
Evaluation and Design of Robotic Hand Picking Operations using Intelligent Motor Unit R. Gnanavel, D. Vinod, M. K. Nalini, K Dhinakaran, D Elantamilan Proceedings IEEE International Conference on Advances in Computing Communication and Applied Informatics Accai 2022, 2022 Picking actions performed by industrial robots may be evaluated using a new architecture in this article. It has always been a goal of humankind to imbue their products with lifelike characteristics in an effort to create a substitute for themselves to carry out their commands and to work in difficult environments like the present. The most common image of a robot is that of a machine that resembles a human person in both appearance and operation. Automation is being replaced by robotics in an effort to boost output and ensure consistency in product quality. Despite the fact that every effort is being made to provide industrial robots increasingly anthropomorphic and humanlike traits and superhuman skills, today's industrial robots may not resemble humans in the slightest. A robotic manipulator, more generally known as a robotic arm, is a typical form of industrial robot. Moving joints connect stiff chains in either an open or closed kinematic structure. It is possible to think of a link's structure as a human torso with the waist, upper arm and forearm as joints [1]. The wrist joint at the end of the arm connects end effectors such as a tool and its mounting fixture, or a gripper or any other device for functioning. This workstation features a 6-axis Force/Torque pick and place robot for loading and packaging products. A six-axis Force/Torque design was used to properly evaluate and account for all of the possible loading process concerns when building the pick and place robot.
A Hybrid Algorithm for Secure Image based Encryption and Steganographic Technique in combination with DET and AES Algorithms D. Vinod, M. K. Nalini, K Dhinakaran, D Elantamilan, R. Gnanavel Proceedings IEEE International Conference on Advances in Computing Communication and Applied Informatics Accai 2022, 2022 Instead of using a complex mathematical equation to key a host image, this Image Encryption algorithm uses a hybrid wavelet algorithm to increase the host image's possibilities. Here, we split different regions of the host image and the fusing image by using DWT and intermixing those regions to achieve another vision processed by DWT of the same format, which inversion results in an encrypted image. Even a brute force assault can't break the association between this original image and the fused image using a basic keying strategy. When decrypting this picture, we need to know the key and dummy image used to connect it. It would be hard to decrypt this Image matrix without knowing its layout, and the decryption time is supposedly longer than the encryption period. And Using steganography, data may be made to appear as if they never existed in another media, allowing for secure communication. Secure communication is achieved through the use of steganography. Steganography utilizing the DWT (Discrete Wavelet Transform) is proposed in this study, which uses a coefficient replacement technique to boost security while maintaining high capacity. The cover picture is encrypted using the Advanced Encryption Standard (AES) with a modification, while the payload image is encrypted using Haar and biorthogonal DWT. The payload image's high-frequency bands contain the resulting coefficients of the payload picture. A new concept is being introduced to create an intermediate stage picture: using encrypted payload to replace the HH sub-band coefficients. The suggested approach outperforms current ones in terms of both capacity and security.
Implementation of Indexing Techniques to Prevent Data Leakage and Duplication in Internet M. K. Nalini, Dhinakaran K, Elantamilan D, R. Gnanavel, D. Vinod Proceedings IEEE International Conference on Advances in Computing Communication and Applied Informatics Accai 2022, 2022 Research in this area aims to create a new and efficient method for detecting near-duplicates in online content. Web pages that a search engine has scoured are first parsed to remove HTML elements and java scripts. After this phase, remove common keywords or stop words from the crawled pages. The affixes (prefix and suffix) from crawled pages are drawn by extracting keywords from the text. Finally, the collected keywords generate the similarity score between two papers. This research has proved that the suggested algorithms outperform earlier ones by conducting an extensive experimental investigation on several actual datasets. New algorithms outperform those already in use, according to the test findings. Since there are so many documents on the internet, web search engines have had difficulty finding relevant results for their customers. Overhead costs for search engines have risen dramatically due to an overabundance of almost similar or identical documents somehow. The web crawling community has long been aware of duplicate and near-identical online pages. Users want search engines to return relevant results for their searches on the first page, free of duplicates and redundancies. This is an important criterion. An essential enabler in the health industry is record or data linking, as connected data is an economic resource that may aid enhance research into health policy, detecting bad medication responses, and cutting expenses while uncovering health system fraud. Recent years have seen significant progress in several record linking approaches, mostly due to breakthroughs in data mining and machine learning. Most of these novel technologies have not yet been incorporated in current record linking systems or are disguised in commercial software as ‘black boxes.’ When it comes to learning about new record linking strategies and comparing old methods with new ones, this makes it difficult for users to do so. Innovative record-linking systems must be tested and implemented at low costs using flexible tools. FEBRL (Freely Extensible Biomedical Record Linkage), a free, open-source software license system, is described in this work. Data cleansing and standardization, indexing (blocking), field comparisons, and record pair categorization are all included in this user-friendly graphical interface. When used as a training tool, practitioners may use Febrl to connect data sets with up to several hundred thousand records and learn about both old and novel description linking approaches.
A Hybrid Algorithm to Perform Dynamic Node Energy and Link Stability through invoking Data from 5G Wireless Sensor based Network K Dhinakaran, D Elantamilan, R. Gnanavel, D. Vinod, M. K. Nalini Proceedings IEEE International Conference on Advances in Computing Communication and Applied Informatics Accai 2022, 2022 When it comes to WSN, routing is the most difficult and time-consuming part. For WSN, there are a variety of routing protocols. Routing techniques for mobile sensor networks include Ad hoc On-Demand Distance Vector (AODV). The use of less energy. NAODV is a new routing protocol that incorporates an energy-aware algorithm and the shortest route into the current Ad hoc On-demand Distance Vector Routing (NAODV) protocol in order to save battery consumption and WSN lifespan. Research challenges including packet loss and energy consumption have been taken into consideration when developing new routing protocols for mobile nodes. The simulation results demonstrate that a combination of both bandwidth and energy management works better than the present methods. According to this study, the suggested cluster-based routing algorithms for mobile wireless sensor networks are compared among themselves. According to the simulation results, the suggested energy-efficient routing algorithm consumes very little energy and provides a high level of performance. A study of the AODV protocol's throughput, packet rate, coverage area, and the number of packets has been conducted in this work. With 11 nodes, our simulation findings demonstrate that the network's lifespan is increased greatly without affecting packet delivery speed. Cells, the smallest unit of geographic division in the 5G network, will be used to connect providers' service areas. There are still certain locations that don't yet have access to 5G. Thus new gadgets may still connect to 4G LTE networks. Data aggregation methods are crucial to network efficiency. Accumulating and effectively condensing data packets is the fundamental goal of a data aggregation technique. This study created a hybrid clustering and routing strategy for data aggregation in 5G wireless sensor networks.
An artificial neural network based iris authentication using back propagation Journal of Green Engineering, 2020
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Combining artificial neural network with image data partitioning for personal iris recognition system International Journal of Applied Engineering Research, 2016
Prevalence of prehypertension and its correlation with indian diabetic risk score in rural population Indian Journal of Science and Technology, 2013
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