318 20 11858 https://archives.christuniversity.in/files/original/e85e102bdba2e33cb19766a46c33b5d2.pdf bebdb0deb37050f223948275614277e6 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Thesis PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved deep learning model for detection and classification of pneumonia from x ray images / Subject The topic of the resource Computer Science Creator An entity primarily responsible for making the resource Sarwath Unnisa - 1981319 Publisher An entity responsible for making the resource available CHRIST (Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2024-07-11 Language A language of the resource English Type The nature or genre of the resource PhD Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PHD PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Relation A related resource 61000327 Title A name given to the resource Improved Deep Learning Model for Detection and Classification of Pneumonia from X-Ray Images Subject The topic of the resource Computer Science Description An account of the resource Pneumonia is a severe respiratory disease that can lead to inflammation, fluid accumulation in lungs and breathing difficulties, which needs immediate and accurate diagnosis. Chest X-Ray images are a necessary tool to diagnose pneumonia because manual interpretation poses challenges, particularly for radiologists with less expertise. Artificial intelligence (AI), specifically Convolutional Neural Networks (CNNs), has become a significant in the field of pneumonia detection within chest X-Ray images in recent years. This research presents SarNet, a neural network model developed for the identification of pneumonia in chest X-Ray images. The study involved the compilation of dataset containing chest X-Ray images categorized as normal, pneumonia, and COVID-19 pneumonia cases, each accompanied by appropriate annotations. This dataset was employed as the basis for training and assessing SarNet's performance, underscoring its promise in transforming the diagnosis of pneumonia. SarNet proved highly effective, achieving good accuracy, sensitivity, and specificity compared to traditional diagnostic methods. The model's simplicity, with 41 layers, strikes a balance between depth and computational complexity, enhancing efficiency and ensuring accurate pneumonia detection. Furthermore, the study expanded its scope to include COVID-19 pneumonia detection. SarNet achieved an accuracy of 99.15% in binary classification and 94.9% in multiclass classification, including healthy, pneumonia, and COVID-19 pneumonia cases. Creator An entity primarily responsible for making the resource Sarwath, Unnisa Source A related resource from which the described resource is derived Author's Submission Publisher An entity responsible for making the resource available Christ(Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Contributor An entity responsible for making contributions to the resource Vijayalakshmi, A Rights Information about rights held in and over the resource Open Access Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource PhD Identifier An unambiguous reference to the resource within a given context <a href="http://hdl.handle.net/10603/570001" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/570001</a> Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved dhoa-fuzzy based load scheduling in iot cloud environment Subject The topic of the resource Cloud computing; Fuzzy logic; Internet of things; Load scheduling; Metaheuristics Description An account of the resource Internet of things (IoT) has been significantly raised owing to the development of broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The development of IoT technologies has resulted in a massive quantity of data due to the existence of several people linking through distinct physical components, indicating the status of the CC environment. In the IoT, load scheduling is realistic technique in distinct data center to guarantee the network suitability by falling the computer hardware and software catastrophe and with right utilize of resource. The ideal load balancer improves many factors of Quality of Service (QoS) like resource performance, scalability, response time, error tolerance, and efficiency. The scholar is assumed as load scheduling a vital problem in IoT environment. There are many techniques accessible to load scheduling in IoT environments.With this motivation, this paper presents an improved deer hunting optimization algorithm with Type II fuzzy logic (IDHOA-T2F) model for load scheduling in IoT environment. The goal of the IDHOA-T2F is to diminish the energy utilization of integrated circuit of IoT node and enhance the load scheduling in IoT environments. The IDHOA technique is derived by integrating the concepts of Nelder Mead (NM) with the DHOA. The proposed model also synthesized the T2L based on fuzzy logic (FL) systems to counterbalance the load distribution. The proposed model finds useful to improve the efficiency of IoT system. For validating the enhanced load scheduling performance of the IDHOA-T2F technique, a series of simulations take place to highlight the improved performance. The experimental outcomes demonstrate the capable outcome of the IDHOA-T2F technique over the recent techniques. 2022 Tech Science Press. All rights reserved. Creator An entity primarily responsible for making the resource Joshua Samuel Raj R.; Ilango V.; Thomas P.; Uma V.R.; Al-Wesabi F.N.; Marzouk R.; Hilal A.M. Source A related resource from which the described resource is derived Computers, Materials and Continua, Vol-71, No. 2, pp. 4101-4114. Publisher An entity responsible for making the resource available Tech Science Press Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.32604/cmc.2022.022063" target="_blank" rel="noreferrer noopener">https://doi.org/10.32604/cmc.2022.022063</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120801301&doi=10.32604%2Fcmc.2022.022063&partnerID=40&md5=0a6c802914a3da1d57738db9a03f8aed" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120801301&doi=10.32604%2fcmc.2022.022063&partnerID=40&md5=0a6c802914a3da1d57738db9a03f8aed</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 15462218 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Joshua Samuel Raj R., Department of Information Science and Engineering, CMR Institute of Technology, Bengaluru, 560037, India; Ilango V., Department of Computer Application, CMR Institute of Technology, Bangalore, 560037, India; Thomas P., School of Computing, Woldia Institute of Technology, Woldia University, Ethiopia, Ethiopia; Uma V.R., Department of Commerce, School of Commerce. Finance and Accountancy, Christ University, Bangalore, 560029, India; Al-Wesabi F.N., Department of Computer Science, College of Science and Art at Mahayil, King Khalid University, Saudi Arabia, Faculty of Computer and IT, Sana'a University, Yemen, Yemen; Marzouk R., Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Saudi Arabia; Hilal A.M., Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, Alkharj, Saudi Arabia Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved diabetes disease prediction IWFO model using machine learning algorithms Description An account of the resource Diabetic disease is the mostly affected and massive disease on a global level. Diagnosing the diabetic earlier will help the medicalist to give the improved and latest clinical treatment. The healthcare specialist unit uses many machine learning techniques, methodologies and tools for decision making in diabetic field. The machine learning techniques are utilized for the prediction of the diabetic diseases in the initial level. To eliminate such issues, optimized detection techniques are proposed. First of all, the training samples are increased using the sliding window protocol. Further, class imbalanced training data classes are balanced and resolved using the adaptive and gradient booster technique. Further, the diabetic feature selection process is improved by the Intensity Weighted Firefly Optimization firefly techniques (IWFO), in which irrelevant features are reduced based on the correlation between the features that deducts the unwanted features involved in the diabetic disease process. Then the feature transformation problem is faced by the PCA technique, which manages the several types of features. Finally, the improved and optimal hybrid random forest is applied into the normal and diabetes classes respectively. The proposed system predicts the diabetic disease efficiently and maximizes its precision of the prediction system. The present paper is compared with different classifiers to determine the efficiency of the work. Overall, the initiated system improved the present studies accuracy level. 2024 Author(s). Creator An entity primarily responsible for making the resource Gunavathi R.; Sivakumar V.; Kumar B.S.; Vijayalakshmi S. Source A related resource from which the described resource is derived AIP Conference Proceedings, Vol-3161, No. 1 Publisher An entity responsible for making the resource available American Institute of Physics Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1063/5.0229494" target="_blank" rel="noreferrer noopener">https://doi.org/10.1063/5.0229494</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203957539&doi=10.1063%2F5.0229494&partnerID=40&md5=72023ea6c153c360ab409219e1ca248a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203957539&doi=10.1063%2f5.0229494&partnerID=40&md5=72023ea6c153c360ab409219e1ca248a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 0094243X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gunavathi R., School of Science, Department of Data Science, Christ University, Pune, India; Sivakumar V., School of Computing, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Kumar B.S., Department of Computer Science, Sree Narayana Guru College, Coimbatore, India; Vijayalakshmi S., School of Science, Department of Data Science, Christ University, Pune, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved dragonfly optimizer for intrusion detection using deep clustering CNN-PSO classifier Subject The topic of the resource Binning normalization; Convolutional neural network; Deep clustering; Dragonfly optimizer; Information gain; Intrusion detection system Description An account of the resource With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because of the features space grows while detecting the intruders. In this paper, deep clustering based CNN have been used to detect the intruders with the help of Meta heuristic algorithms for feature selection and preprocessing. The proposed system includes three phases such as preprocessing, feature selection and classification. In the first phase, KDD dataset is preprocessed by using Binning normalization and Eigen-PCA based discretization method. In second phase, feature selection is performed by using Information Gain based Dragonfly Optimizer (IGDFO). Finally, Deep clustering based Convolutional Neural Network (CCNN) classifier optimized with Particle Swarm Optimization (PSO) identifies intrusion attacks efficiently. The clustering loss and network loss can be reduced with the optimization algorithm. We evaluate the proposed IDS model with the NSL-KDD dataset in terms of evaluation metrics. The experimental results show that proposed system achieves better performance compared with the existing system in terms of accuracy, precision, recall, f-measure and false detection rate. 2022 Tech Science Press. All rights reserved. Creator An entity primarily responsible for making the resource Bhuvaneshwari K.S.; Venkatachalam K.; HubovskS.; TrojovskP.; Prabu P. Source A related resource from which the described resource is derived Computers, Materials and Continua, Vol-70, No. 3, pp. 5949-5965. Publisher An entity responsible for making the resource available Tech Science Press Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.32604/cmc.2022.020769" target="_blank" rel="noreferrer noopener">https://doi.org/10.32604/cmc.2022.020769</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116961790&doi=10.32604%2Fcmc.2022.020769&partnerID=40&md5=4d98f0abf4c09995af53fc9293f2ae63" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116961790&doi=10.32604%2fcmc.2022.020769&partnerID=40&md5=4d98f0abf4c09995af53fc9293f2ae63</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 15462218 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Bhuvaneshwari K.S., Department of Computer Sceince and Engineering, Karpagam College of Engineering, Coimbatore, 641032, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; HubovskS., Department of Applied Cybernetics, Faculty of Science, University of Hradec Krov Hradec Krov 50003, Czech Republic; TrojovskP., Department of Mathematics, Faculty of Science, University of Hradec Krov Hradec Krov 50003, Czech Republic; Prabu P., Department of Computer Sceince, CHRIST(Deemed to be University), Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved Feature Selection Method for the Identification of Soil Images Using Oscillating Spider Monkey Optimization Subject The topic of the resource Feature selection; Perturbation rate; smart agriculture; Soil prediction; Spider monkey optimization Description An account of the resource Precision agriculture is the process that uses information and communication technology for farming and cultivation to improve overall productivity, efficient utilization of resources. Soil prediction is one of the primary phases in precision agriculture, resulting in good quality crops. In general, farmers perform the soil prediction manually. However, the efficiency of soil prediction may be enhanced by using current digital technologies. One effective way to automate soil prediction is image processing techniques in which soil images may be analyzed to determine the soil. This paper presents an efficient image analysis technique to predict the soil. For the same, a robust feature selection technique has been incorporated in the image analysis of soil images. The developed feature selection technique uses a new oscillating spider monkey optimization algorithm (OSMO) for the selection of features that are relevant and non-redundant. The new oscillating spider monkey optimization algorithm increases precision and convergence behavior by using an oscillating perturbation rate. A set of standard benchmark functions was deployed to visualize the performance of the new optimization technique (OSMO), and results were compared based on mean and standard deviation. Furthermore, the soil prediction approach is validated on a soil dataset, having seven categories. The proposed feature selection method selects the 41% relevant features, which provide the highest accuracy of 82.25% with 2.85% increase. 2013 IEEE. Creator An entity primarily responsible for making the resource Agarwal R.; Shekhawat N.S.; Kumar S.; Nayyar A.; Qureshi B. Source A related resource from which the described resource is derived IEEE Access, Vol-9, pp. 167128-167139. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ACCESS.2021.3135536" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACCESS.2021.3135536</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121809681&doi=10.1109%2FACCESS.2021.3135536&partnerID=40&md5=14b4ba5a8369d9e11cbc03c17ad96887" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121809681&doi=10.1109%2fACCESS.2021.3135536&partnerID=40&md5=14b4ba5a8369d9e11cbc03c17ad96887</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 21693536 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Agarwal R., Department of Computer Science and Engineering, Engineering College Bikaner, Bikaner, 334004, India; Shekhawat N.S., Department of Computer Science and Engineering, Engineering College Bikaner, Bikaner, 334004, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560074, India; Nayyar A., Graduate School, Duy Tan University, Da Nang, 550000, Viet Nam, Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Viet Nam; Qureshi B., Department of Computer Science, Prince Sultan University, Riyadh, 11586, Saudi Arabia Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved File Security System Using Multiple Image Steganography Subject The topic of the resource Batch Steganography; File security; Image Steganography; Multiple image steganography Description An account of the resource Steganography is the process of hiding a secret message within an ordinary message extracting it at its destination. Image steganography is one of the most common and secure forms of steganography available today. Traditional steganography techniques use a single cover image to embed the secret data which has few security shortcomings. Therefore, batch steganography has been adopted which stores data on multiple images. In this paper, a novel approach is proposed for slicing the secret data and storing it on multiple cover images. In addition, retrieval of this secret data from the cover images on the destination side has also been discussed. The data slicing ensures secure transmission of the vital data making it merely impossible for the intruder to decrypt the data without the encrypting details. 2019 IEEE. Creator An entity primarily responsible for making the resource Benedict A.G. Source A related resource from which the described resource is derived 2019 International Conference on Data Science and Communication, IconDSC 2019 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IconDSC.2019.8816946" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IconDSC.2019.8816946</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072780086&doi=10.1109%2FIconDSC.2019.8816946&partnerID=40&md5=24495efc3be314480bb76fd623b0da6f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072780086&doi=10.1109%2fIconDSC.2019.8816946&partnerID=40&md5=24495efc3be314480bb76fd623b0da6f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-153869319-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Benedict A.G., Computer Science and Engineering, Faculty of Engineering, Christ, Deemed to be University, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved Henon Chaotic Map-based Progressive Block-based visual cryptography strategy for securing sensitive data in a cloud EHR system Subject The topic of the resource Henon maps; Improved henon chaotic map; Lorentz maps; Progressive visual cryptography; Secret sharing Description An account of the resource The core objective of secret sharing concentrates on developing a novel technique that prevents the destruction and leakage of original data during the distribution and encoding processes. Progressive Visual Cryptography (VC) is considered for the potential over the traditional VC schemes since the former does not require and does not suffer from the limitations of requiring a minimum number of participants during the process of encryption and sharing. The chaotic map-based Progressive VC is superior in facilitating predominant secrecy under sharing and encryption. In this paper, an Improved Henon Chaotic Map-based Progressive Block-based VC (IHCMPBVC) scheme is proposed to prevent the leakage and destruction of sensitive information during an exchange and encryption. This proposed IHCMPBVC technique uses the merits of Henon and Lorentz maps for effective encryption since it introduces the option of deriving non-linear behavior that results in sequence generation that covers the complete range with proper distribution in order to minimize the degree of leaks in sharing. The simulation results of the proposed IHCMPBVC technique investigated using entropy, PSNR, and Mean Square Error were improved at an average rate of 27%, 23%, and 31%, predominant to the baseline VC approaches considered in the comparison. 2022 The Authors Creator An entity primarily responsible for making the resource Mohanasundaram A.; Aruna S.K. Source A related resource from which the described resource is derived International Journal of Intelligent Networks, Vol-3, pp. 109-112. Publisher An entity responsible for making the resource available KeAi Communications Co. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.ijin.2022.08.004" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ijin.2022.08.004</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138500541&doi=10.1016%2Fj.ijin.2022.08.004&partnerID=40&md5=c06307b2ae517d72b0f57d8278b1b671" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138500541&doi=10.1016%2fj.ijin.2022.08.004&partnerID=40&md5=c06307b2ae517d72b0f57d8278b1b671</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 26666030 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mohanasundaram A., Department of Applied Computer Science, Vrije Universiteit Brussel, Belgium; Aruna S.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved image denoising with the integrated model of Gaussian filter and neighshrink SURE Subject The topic of the resource Gaussian filter; Image denoising; NeighShrink SURE me; Wavelet thresholding Description An account of the resource Image denoising, being an important preprocessing stage in image processing, minimizes the noise interfering with the information content of the image. The denoising problems are addressed by various techniques starting from the Fourier transforms to wavelets. Because of the localized time frequency features and advantages of multi resolution capabilities, the wavelets have been extensively used in the denoising process. The development of algorithms for the wavelet thresholding or shrinkage strategies along with different filters have resulted in the betterment of image quality after the denoising. Even though the image denoising algorithm based on a combination of Gaussian and Bilateral filters, shows good performance but lacks in consistency with respect to the noise levels and also the type of images used. This paper discusses the advantages of NeighShrink SURE rule in developing an effective thresholding strategy, thereby proposing a improved denoising method incorporating the NeighShrink SURE rule along with combination of Gaussian filter model. The methodology employs the use of subband thresholding derived from the NeighShrink SURE rule. The outcome of the proposed method exhibits a comparatively improved performance in Peak Signal to Ratio (PSNR) and Image Quality Index (IQI) values of the test images. BEIESP. Creator An entity primarily responsible for making the resource Naragund M.N.; Jagadale B.N.; Priya B.S.; Panchaxri; Hegde V. Source A related resource from which the described resource is derived International Journal of Engineering and Advanced Technology, Vol-8, No. 6, pp. 3010-3015. Publisher An entity responsible for making the resource available Blue Eyes Intelligence Engineering and Sciences Publication Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.35940/ijeat.F9020.088619" target="_blank" rel="noreferrer noopener">https://doi.org/10.35940/ijeat.F9020.088619</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072009890&doi=10.35940%2Fijeat.F9020.088619&partnerID=40&md5=fa0103ba38db746ba41967c59b2e0051" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072009890&doi=10.35940%2fijeat.F9020.088619&partnerID=40&md5=fa0103ba38db746ba41967c59b2e0051</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 22498958 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Naragund M.N., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, India; Jagadale B.N., Department of PG studies and research in Electronics, Kuvempu University, Shimoga, India; Priya B.S., Department of Electronics, Kuvempu University, Shimoga, India; Panchaxri, Department of Electronics, SSA Govt. First grade College, Ballari, India; Hegde V., Department of Electronics, MESMM Arts and Science College, Sirsi, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved Photocatalytic Activity of g-C3N4/ZnO: A PotentialDirect Z-Scheme Nanocomposite Subject The topic of the resource Energy conversion; g-C3N4/ZnO; Malachite green degradation; Nanocomposite; Z-scheme photocatalysis Description An account of the resource In this study, a Z-scheme g-C3N4/ZnO nanocomposite was synthesized using exfoliation process, which was further characterized using XRD, FT-IR, UV-DRS, SEM-EDAX, PL, EIS, and TGA techniques. The properties of g-C3N4 were enhanced when fabricated with ZnO resulting in a better electron mobility, high redox potential, and excellent semiconducting properties. The performance of this heterostructure was evaluated by photocatalytic degradation of malachite green (MG) under visible light irradiation. The g-C3N4/ZnO heterostructure achieved a degradation of 84.3 % within 60 min under visible light irradiation. The degradation reaction follows a pseudo first-order kinetic model with a reaction rate constant of 0.0329 min?1. The nanocomposite demonstrated outstanding stability and recyclability. 2020 Wiley-VCH GmbH Creator An entity primarily responsible for making the resource Ramachandra M.; Devi Kalathiparambil Rajendra Pai S.; Resnik Jaleel UC J.; Pinheiro D. Source A related resource from which the described resource is derived ChemistrySelect, Vol-5, No. 38, pp. 11986-11995. Publisher An entity responsible for making the resource available Wiley-Blackwell Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1002/slct.202003166" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/slct.202003166</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092563140&doi=10.1002%2Fslct.202003166&partnerID=40&md5=1c0d9a1fdc2cb4cdd32c86b2e61186e4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092563140&doi=10.1002%2fslct.202003166&partnerID=40&md5=1c0d9a1fdc2cb4cdd32c86b2e61186e4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23656549 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ramachandra M., Department of Chemistry CHRIST, Deemed to be University), Hosur road, Bengaluru, 560029, Karnataka, India; Devi Kalathiparambil Rajendra Pai S., Department of Chemistry CHRIST, Deemed to be University), Hosur road, Bengaluru, 560029, Karnataka, India; Resnik Jaleel UC J., Department of Chemistry CHRIST, Deemed to be University), Hosur road, Bengaluru, 560029, Karnataka, India; Pinheiro D., Department of Chemistry CHRIST, Deemed to be University), Hosur road, Bengaluru, 560029, Karnataka, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved Random Forest Algorithm for Cognitive Radio Networks' Distributed Channel and Resource Allocation Performance Subject The topic of the resource Channel Allocation; Cognitive Radio Networks; Random Forest; Routing; Throughput Description An account of the resource Modified Random Forest (MRF) machine learning algorithm aimed at improving the distributed channel allocation and resource allocation performance in cognitive radio networks (CRNs). The purpose of this research is to enhance the efficiency and effectiveness of CRNs by optimizing the allocation of channels and resources. The proposed MRF algorithm is developed by adapting and modifying the random forest technique to address the specific challenges of CRN allocation. Experimental evaluations demonstrate that the MRF algorithm achieves higher accuracy and efficiency compared to existing routing techniques and channel allocation algorithms like ACO and PSO. It exhibits a high packet delivery ratio, increased throughput, and reduced delay in channel selection, thus improving the overall performance of CRNs.The implications of this research are twofold. On a theoretical level, this study contributes to the field by extending the capabilities of the random forest algorithm and adapting it to the domain of CRNs. The modified algorithm demonstrates the potential of machine learning techniques in addressing allocation challenges in wireless communication systems. The findings emphasize the importance of advanced algorithms in improving the efficiency and effectiveness of channel and resource allocation processes. 2023, Success Culture Press. All rights reserved. Creator An entity primarily responsible for making the resource Rajesh Kanna R.; Mohana Priya T.; Rohini V.; Ashok Immanuel V.; Senthilnathan T.; Kirubanand V.B.; Ibrahim A. Source A related resource from which the described resource is derived Journal of Logistics, Informatics and Service Science, Vol-10, No. 3, pp. 98-106. Publisher An entity responsible for making the resource available Success Culture Press Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.33168/JLISS.2023.0308" target="_blank" rel="noreferrer noopener">https://doi.org/10.33168/JLISS.2023.0308</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167429928&doi=10.33168%2FJLISS.2023.0308&partnerID=40&md5=cd5f32598ce55cc095f1da1e1fd3d492" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167429928&doi=10.33168%2fJLISS.2023.0308&partnerID=40&md5=cd5f32598ce55cc095f1da1e1fd3d492</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 24092665 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajesh Kanna R., Christ (Deemed to be University), India; Mohana Priya T., Christ (Deemed to be University), India; Rohini V., Christ (Deemed to be University), India; Ashok Immanuel V., Christ (Deemed to be University), India; Senthilnathan T., Christ (Deemed to be University), India; Kirubanand V.B., Christ (Deemed to be University), India; Ibrahim A., Department of Computer Science, College of Computer, Qassim University, Buraydah, Saudi Arabia Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved reptile search algorithm with sequential assignment routing based false packet forwarding scheme for source location privacy protection on wireless sensor networks Subject The topic of the resource false data forwarding; fitness function; metaheuristics; routing; source location privacy preserving; Wireless sensor networks Description An account of the resource Source Location Privacy (SLP) in Wireless Sensor Networks (WSNs) refers to a set of techniques and strategies used to safeguard the anonymity and confidentiality of the locations of sensor nodes (SNs) that are the source of transmitted data within the network. This protection is important in different WSN application areas like environmental monitoring, surveillance, and healthcare systems, where the revelation of the accurate location of SNs can pose security and privacy risks. Therefore, this study presents metaheuristics with sequential assignment routing based false packet forwarding scheme (MSAR-FPFS) for source location privacy protection (SLPP) on WSN. The contributions of the MSAR-FPFS method revolve around enhancing SLP protection in WSNs through the introduction of dual-routing, SAR technique with phantom nodes (PNs), and an optimization algorithm. In the presented MSAR-FPFS method, PNs are used for the rotation of dummy packets using the SAR technique, which helps to prevent the adversary from original data transmission. Next, the MSAR-FPFS technique uses an improved reptile search algorithm (IRSA) for the optimal selection of routes for real packet transmission. Moreover, the IRSA technique computes a fitness function (FF) comprising three parameters namely residual energy (RE), distance to BS (DBS), and node degree (ND). The experimental evaluation of the MSAR-FPFS system was investigated under different factors and the outputs show the promising achievement of the MSAR-FPFS system compared to other existing models. 2024-IOS Press. All rights reserved. Creator An entity primarily responsible for making the resource Sankaralingam R.P.; Arunachalaperumal C.; Mary Anita E.A. Source A related resource from which the described resource is derived Journal of Intelligent and Fuzzy Systems, Vol-46, No. 1, pp. 1801-1812. Publisher An entity responsible for making the resource available IOS Press BV Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.3233/JIFS-233541" target="_blank" rel="noreferrer noopener">https://doi.org/10.3233/JIFS-233541</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184150251&doi=10.3233%2FJIFS-233541&partnerID=40&md5=ed7d76cb3c0d64b4e007fc3aca821c9b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184150251&doi=10.3233%2fJIFS-233541&partnerID=40&md5=ed7d76cb3c0d64b4e007fc3aca821c9b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 10641246 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sankaralingam R.P., Department of MCA, Madha Engineering College, Tamil Nadu, Chennai, India; Arunachalaperumal C., Department of ECE, Ramco Institute of Technology, Tamil Nadu, Rajapalayam, India; Mary Anita E.A., Department of CSE, CHRIST University, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved Security of the Data Communication in VANET Environment Using ASCII-ECC Algorithm Subject The topic of the resource American standard code for information interchange based elliptic curve cryptography (ASCII-ECC); Authentication; Cluster head (CH); Median based K-means (MKM); Modified cockroach swarm optimization (MCSO); On-board unit (OBU); Road side units (RSUs); Trusted authority (TA); Vehicular ad-hoc network (VANET) Description An account of the resource Now-a-days, with the augmenting accident statistics, the Vehicular Ad-hoc Networks (VANET) are turning out to be more popular, helping in prevention of accidents in addition to damage to the vehicles together with populace. In VANET, message can well be transmitted within a pre-stated region to attain systems safety and also improveits efficacy. Ensuring authenticity of messages is a challenge in such dynamic environment. Though few researchers worked on this, security level is very less. Hence enhanced communicationsecurity on the VANET environment utilizing the American Standard Code for Information Interchange centred Elliptic Curve Cryptography (ASCII-ECC) is proposedin this paper. The network design is definedinitially. Subsequently, the entire vehicles get registered to the Trusted Authority (TA); similarly, all vehicle users areregistered with their On-Board Unit (OBU). This is followed byMedian-centred K-Means (MKM) performs the cluster formation together with Cluster Head Selection (CHS). Next, TA takes care of the verification procedure. Modified Cockroach Swarm Optimization (MCSO) calculates the shortest path and the ASCII-ECC carries out the secure data communication if the vehicle is an authorized one. If not, TA sends the alert message for discarding the request. The system renders better performance when it was weighed against the top-notch methods. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. Creator An entity primarily responsible for making the resource Sajini S.; Anita E.A.M.; Janet J. Source A related resource from which the described resource is derived Wireless Personal Communications, Vol-128, No. 2, pp. 759-776. Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s11277-022-09974-7" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11277-022-09974-7</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139456385&doi=10.1007%2Fs11277-022-09974-7&partnerID=40&md5=34bb562853d35ff9b8352ad96aebb534" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139456385&doi=10.1007%2fs11277-022-09974-7&partnerID=40&md5=34bb562853d35ff9b8352ad96aebb534</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9296212; CODEN: WPCOF Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sajini S., Anna University, Chennai, India, SRM Institute of Science and Technology, Ramapuram, India; Anita E.A.M., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Bengaluru, India; Janet J., Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved tweets in English text classification by LSTM neural network Subject The topic of the resource English tweets; LSTM; Mendeley Data; Neural network; Word2Vec Description An account of the resource This paper analyzes the performance of an LSTM-type neural network in the sentiment analysis task in tweets in English about the COVID-19 pandemic. Primarily, the organization and cleaning a database of tweets about the COVID-19 pandemic is performed. From the original database, two other databases through different discretizations of the polarities of the tweets using Heaviside-type functions are created. Vectorization of tweets using the Word2Vec word embedding technique is carried out. Computational implementations of LSTM neural networks to the context of our research problem are adapted. Analyzes and discussions on the feasibility of the proposed solution taking into account different types of hyperparametric adjustments in the neural network models is carried out. Publicly available databases organized through the Mendeley Data public data repository are used. 2023 IEEE. Creator An entity primarily responsible for making the resource Yashasvi B.N.; Samson Lsaac J.; Raghavendra S.; Tiwari M.; Ananthi K. Source A related resource from which the described resource is derived 2023 1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICAEECI58247.2023.10370893" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAEECI58247.2023.10370893</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183557680&doi=10.1109%2FICAEECI58247.2023.10370893&partnerID=40&md5=dbec87fe8b9fff9c18cc6389e2f6ad72" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183557680&doi=10.1109%2fICAEECI58247.2023.10370893&partnerID=40&md5=dbec87fe8b9fff9c18cc6389e2f6ad72</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034279-6 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Yashasvi B.N., R N S Institute of Technology, Bangalore, India; Samson Lsaac J., Karunya Lnstitute of Technology and Sciences, Department of Biomedical Engineering, Tamilnadu, Coimbatore, India; Raghavendra S., Christ Deemed to Be University, Department of Computer Science Engineering, Benguluru, India; Tiwari M., Bharati Vidyapeeth's College of Engineering, Department of Computer Science and Engineering, Delhi, India; Ananthi K., Sri Eshwar College of Engineering, Department of Computer Science and Business Systems, Tamilnadu, Kinathukadavu, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improvement in food preservation with nanozymes Subject The topic of the resource Antimicrobial activity; Food preservation; Food quality; Nanozymes; Smart packaging Description An account of the resource To ensure safety, quality, and extended shelf life of perishable food products, food preservation is a critical aspect of food industries. Concerns regarding the potential health risks and loss of nutritional value of food because of traditional methods of preservation such as using chemical additives and high temperatures have set the need for finding alternative methods of preservation, for the betterment of health and the environment. Enzymes have the potential to kill microorganisms. Enzymes such as oxidases, peroxidases, hydrolases, catalases, and others have been extensively studied for their microbicidal activities. However, natural enzymes have shortfalls as they can be easily denatured and cannot be recycled. Nanozymes have gained the limelight in recent years as they can be applied in food industries to overcome the shortfalls of natural enzymes. They embody the highly beneficial properties of both enzymes and nanoparticles at the same time. Due to their enzyme-mimicking properties and versatile applications, nanozymes have become more popular in the last few years. Nanozymes have evolved as a promising alternative for food preservation and the detection of various contaminants in food. However, before the integration of nanozymes into the food industry, several factors such as their stability, biocompatibility, longevity, toxicity, cost-effectiveness, scalability, and regulatory approval need to be addressed. This chapter discusses the concept of nanozymes, its classification, and various applications in food industries specially designed for preservation of food products. 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. Creator An entity primarily responsible for making the resource Sridhar A.; Sunil C.K.; Al-Khayri J.M.; Nagella P. Source A related resource from which the described resource is derived Nanozymes: Approachable Bio-applications, pp. 361-383. Publisher An entity responsible for making the resource available Elsevier Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-443-13788-4.00014-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-443-13788-4.00014-5</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202888106&doi=10.1016%2FB978-0-443-13788-4.00014-5&partnerID=40&md5=a323fe133e228dc385a2e261d87318dd" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202888106&doi=10.1016%2fB978-0-443-13788-4.00014-5&partnerID=40&md5=a323fe133e228dc385a2e261d87318dd</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-044313788-4; 978-044313789-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sridhar A., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Sunil C.K., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Al-Khayri J.M., Department of Agricultural Biotechnology, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, Saudi Arabia; Nagella P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improvement of Automatic Glioma Brain Tumor Detection Using Deep Convolutional Neural Networks Subject The topic of the resource convolutional neurol networks; deep learning; higher grade gliomas; image segmentation; lower grade gliomas; voxel Description An account of the resource This article introduces automatic brain tumor detection from a magnetic resonance image (MRI). It provides novel algorithms for extracting patches and segmentation trained with Convolutional Neural Network (CNN)'s to identify brain tumors. Further, this study provides deep learning and image segmentation with CNN algorithms. This contribution proposed two similar segmentation algorithms: one for the Higher Grade Gliomas (HGG) and the other for the Lower Grade Gliomas (LGG) for the brain tumor patients. The proposed algorithms (Intensity normalization, Patch extraction, Selecting the best patch, segmentation of HGG, and Segmentation of LGG) identify the gliomas and detect the stage of the tumor as per taking the MRI as input and segmented tumor from the MRIs and elaborated the four algorithms to detect HGG, and segmentation to detect the LGG works with CNN. The segmentation algorithm is compared with different existing algorithms and performs the automatic identification reasonably with high accuracy as per epochs generated with accuracy and loss curves. This article also described how transfer learning has helped extract the image and resolution of the image and increase the segmentation accuracy in the case of LGG patients. Copyright 2022, Mary Ann Liebert, Inc., publishers 2022. Creator An entity primarily responsible for making the resource Altameem A.; Mallikarjuna B.; Saudagar A.K.J.; Sharma M.; Poonia R.C. Source A related resource from which the described resource is derived Journal of Computational Biology, Vol-29, No. 6, pp. 530-544. Publisher An entity responsible for making the resource available Mary Ann Liebert Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1089/cmb.2021.0280" target="_blank" rel="noreferrer noopener">https://doi.org/10.1089/cmb.2021.0280</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131665529&doi=10.1089%2Fcmb.2021.0280&partnerID=40&md5=86242a97b59a579c63394dfb7f07852c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131665529&doi=10.1089%2fcmb.2021.0280&partnerID=40&md5=86242a97b59a579c63394dfb7f07852c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 10665277; PubMed ID: 35235381; CODEN: JCOBE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Altameem A., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, Saudi Arabia; Mallikarjuna B., School of Computing Science and Engineering, Galgotias University, Greater Noida, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia; Sharma M., School of Computing Science and Engineering, Galgotias University, Greater Noida, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improvement of Speech Emotion Recognition by Deep Convolutional Neural Network and Speech Features Subject The topic of the resource Data augmentation; Deep convolutional neural network; Emotion recognition; Speech dataset; Speech features Description An account of the resource Speech emotion recognition (SER) is a dynamic area of research which includes features extraction, classification and adaptation of speech emotion dataset. There are many applications where human emotions play a vital role for giving smart solutions. Some of these applications are vehicle communications, classification of satisfied and unsatisfied customers in call centers, in-car board system based on information on drivers mental state, human-computer interaction system and others. In this contribution, an improved emotion recognition technique has been proposed with Deep Convolutional Neural Network (DCNN) by using both speech spectral and prosodic features to classify seven human emotionsanger, disgust, fear, happiness, neutral, sadness and surprise. The proposed idea is implemented on different datasets such as RAVDESS, SAVEE, TESS and CREMA-D with accuracy of 96.54%, 92.38%, 99.42% and 87.90%, respectively, and compared with other pre-defined machine learning and deep learning methods. To test the real-time accuracy of the model, it has been implemented on the combined datasets with accuracy of 90.27%. This research can be useful for development of smart applications in mobile devices, household robots and online learning management system. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mohanty A.; Cherukuri R.C.; Prusty A.R. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-608, pp. 117-129. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-19-9225-4_10" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9225-4_10</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150975414&doi=10.1007%2F978-981-19-9225-4_10&partnerID=40&md5=ccd307e798754cbf15f75de5027a1671" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150975414&doi=10.1007%2f978-981-19-9225-4_10&partnerID=40&md5=ccd307e798754cbf15f75de5027a1671</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981199224-7 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mohanty A., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Cherukuri R.C., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Prusty A.R., DGT, RDSDE, NSTI(W), West Bengal, Kolkata, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improvement to Recommendation system using Hybrid techniques Subject The topic of the resource Collaborative Filtering method; Content-based filtering method; Hybrid Recommendation; Limitation; Movie Recommendation; User ratings Description An account of the resource Currently, recommendation systems are a common tool for providing individualized recommendations and item information to users. For personalization in the recommendation system, there are a variety of strategies that can be used. To improve system performance and offset the shortcomings of individual recommendation strategies, a hybrid recommender system integrates two or even more recommendation techniques. The demand to summarize all of the knowledge on actual methods and algorithms utilized in hybrid recommended systems necessitates the need for a systematic review in the domain. These materials will be employed to aid in the development of an auto-switching hybrid recommender system. In the content-based filtering technique, the algorithm is based on the contents of items and the collaborative filtering technique algorithm combines the relationship between user and item. Both of the approaches of recommendation system are suffers from some limitations, this is a big issue to predict better recommendations to the user. Hybrid systems are introduced to overcome the main limitations of both techniques. These systems are made with a combination of content-based and collaborative filtering techniques and have advantages of both techniques. With the use of hybrid systems, the quality of recommendations is improved. Hybrid recommendation systems use previous data of a user to find his/her interest and then they target the set of an adjacent user which is similar with that user and according to adjacent user recommend things to the user. Hybrid systems offer the items that share the common things that a user rated highly (Content-based filtering) and make suggestions by comparing the interest of a similar user (Collaborative filtering). 2022 IEEE. Creator An entity primarily responsible for making the resource Ramesh R.; Vijayalakshmi S. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 778-782. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823879" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823879</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135492454&doi=10.1109%2FICACITE53722.2022.9823879&partnerID=40&md5=c6569f4ff71fcb2f09fb9d7977dfd85d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135492454&doi=10.1109%2fICACITE53722.2022.9823879&partnerID=40&md5=c6569f4ff71fcb2f09fb9d7977dfd85d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ramesh R., Christ (Deemed to Be University), Department of Data Science, Maharashtra, Pune, India; Vijayalakshmi S., Christ (Deemed to Be University), Department of Data Science, Maharashtra, Pune, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improving Consumer Engagement with AI Chatbots: Exploring Perceived Humanness, Social Presence, and Interactivity Factors Subject The topic of the resource AI chatbots; Artificial intelligence; Consumer engagement; Customer interaction; Human-computer interaction; Interactivity; Perceived humanness; Social presence; User experience Description An account of the resource In many consumer industries, AI robots are becoming more and more popular because they let businesses communicate with their customers in a cheap and quick way. However, how well these measures work rests on how real and present people think they are in social situations. The main things that affect how customers deal with AI chatbots are looked into in this research. These are interaction, social presence, and perceived humanity.A wide range of users will be asked to fill out quantitative polls that will be used to judge how humanlike AI chatbots are, how well they can interact with others, and how much they interact with people. Additionally, performing qualitative interviews will give you a fuller picture of what customers want and how they interact with AI chatbots. Companies can make their chatbot exchanges with customers better by figuring out what makes the bots act like humans: friendly, interested, and sociable. This will allow them to make chatbots that are very specific to their customers' needs and tastes. The goal of this researchprogramme is to make customers happier, more loyal to brands, and have better experiences by creating AI chatbots that can have conversations with people like real people. 2024 IEEE. Creator An entity primarily responsible for making the resource Tripathi A.P.; Dhaundiyal P.; Sharma K.; Sukheswala J.; Dhiman A.; Sharma A.K. Source A related resource from which the described resource is derived Proceedings - 3rd International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ACCAI61061.2024.10601926" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACCAI61061.2024.10601926</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200559335&doi=10.1109%2FACCAI61061.2024.10601926&partnerID=40&md5=ecec965d4af409edc0320da4b08432c7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200559335&doi=10.1109%2fACCAI61061.2024.10601926&partnerID=40&md5=ecec965d4af409edc0320da4b08432c7</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038943-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tripathi A.P., Christ Deemed to Be University, Uttar Pradesh, India; Dhaundiyal P., Christ Deemed to Be University, Uttar Pradesh, India; Sharma K., K P B Hinduja College of Commerce, Maharashtra, India; Sukheswala J., K P B Hinduja College of Commerce, Maharashtra, India; Dhiman A., Manipal University Jaipur, Rajasthan, India; Sharma A.K., University of Technology and Applied Sciences, College of Economics and Business Administration, Salalah, Oman Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improving crop production using an agro-deep learning framework in precision agriculture Subject The topic of the resource Agricultural technology; Agro deep learning framework; Artificial intelligence in agriculture; Crop monitoring; Crop yield prediction; Data analysis; Deep learning; Neural networks; Precision agriculture; Smart farming Description An account of the resource Background: The study focuses on enhancing the effectiveness of precision agriculture through the application of deep learning technologies. Precision agriculture, which aims to optimize farming practices by monitoring and adjusting various factors influencing crop growth, can greatly benefit from artificial intelligence (AI) methods like deep learning. The Agro Deep Learning Framework (ADLF) was developed to tackle critical issues in crop cultivation by processing vast datasets. These datasets include variables such as soil moisture, temperature, and humidity, all of which are essential to understanding and predicting crop behavior. By leveraging deep learning models, the framework seeks to improve decision-making processes, detect potential crop problems early, and boost agricultural productivity. Results: The study found that the Agro Deep Learning Framework (ADLF) achieved an accuracy of 85.41%, precision of 84.87%, recall of 84.24%, and an F1-Score of 88.91%, indicating strong predictive capabilities for improving crop management. The false negative rate was 91.17% and the false positive rate was 89.82%, highlighting the framework's ability to correctly detect issues while minimizing errors. These results suggest that ADLF can significantly enhance decision-making in precision agriculture, leading to improved crop yield and reduced agricultural losses. Conclusions: The ADLF can significantly improve precision agriculture by leveraging deep learning to process complex datasets and provide valuable insights into crop management. The framework allows farmers to detect issues early, optimize resource use, and improve yields. The study demonstrates that AI-driven agriculture has the potential to revolutionize farming, making it more efficient and sustainable. Future research could focus on further refining the model and exploring its applicability across different types of crops and farming environments. The Author(s) 2024. Creator An entity primarily responsible for making the resource Logeshwaran J.; Srivastava D.; Kumar K.S.; Rex M.J.; Al-Rasheed A.; Getahun M.; Soufiene B.O. Source A related resource from which the described resource is derived BMC Bioinformatics, Vol-25, No. 1 Publisher An entity responsible for making the resource available BioMed Central Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1186/s12859-024-05970-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1186/s12859-024-05970-9</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208290747&doi=10.1186%2Fs12859-024-05970-9&partnerID=40&md5=5837d9936542670bbdfb60cfd5b797c8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208290747&doi=10.1186%2fs12859-024-05970-9&partnerID=40&md5=5837d9936542670bbdfb60cfd5b797c8</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 14712105; PubMed ID: 39487390; CODEN: BBMIC Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Logeshwaran J., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Srivastava D., Department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, Rajpura, India; Kumar K.S., Department of Computing Technologies, SRM Institute of Science and Technology, Tamil Nadu, Kattankulathur, 603203, India; Rex M.J., Department of Computing Technologies, SRM Institute of Science and Technology, Tamil Nadu, Kattankulathur, 603203, India; Al-Rasheed A., Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia; Getahun M., Department of Computer Science and Information Technology, College of Engineering and Technology, Kebri Dehar University, Kebri Dehar, Ethiopia; Soufiene B.O., PRINCE Laboratory Research, ISITcom, Hammam Sousse, University of Sousse, Sousse, Tunisia