80 20 11858 https://archives.christuniversity.in/files/original/20b5dfb6e6ee6150c04fa1d58f28cc70.pdf 86f1b0a6dc8cca82d28078ef724e973e 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 MPHIL Mphil Mphil 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 An Empirical Study on the psychographic factors influencing financial decisions of informed individual investors, with special reference to Bangalore financial market Creator An entity primarily responsible for making the resource J Lakshmi Date A point or period of time associated with an event in the lifecycle of the resource 2012 Source A related resource from which the described resource is derived Commerce Description An account of the resource Behavioural finance has been emerging as a significant discipline in academia as it speaks about the irrational behaviour of investors. Behavioural finance is the combination of classic economics and finance with psychology and decision making sciences. It is the study of how investors systematically make errors in judgment, or mental mistakes.Specifically, behavioral finance has two blocks: cognitive psychology and the limits to arbitrage. Cognitive refers to how people think. There is a huge psychology literature documenting that people make systematic errors in the way they think: they are over confident they put too much weight on recent experience etc. Their preference may also create distortions. Behavioural finance uses this body of knowledge, rather than taking arrogant approach that it should be ignored. Limits to arbitrage refer to in what circumstances arbitrage force will be effective, and they wont be. An Empirical Study on the psychographic factors influencing financial decisions of informed individual investors, with special reference to Bangalore financial market, has done with the objective of identifying the effect of three major anomalies namely over confidence, fear of loss, and effect of information and media and relationship of age and fear of loss on the investment decisions. Primary Data collection has been done with the help of questionnaire and had a sample size of 242. The above three aspects have studied and proved using various statistical tools like chi square, one sample t test, ANOVA and correlation. From the study it was proved that investors are overconfident but at the same time there is high fear of loss as well. Study shows that effect of information and news stories plays a major role in investment decisions. Age and fear of loss also have a significant relationship. Only 3 Anomalies has been considered for the study, considering the remaining will give further scope of research. 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 An energy efficient approach of deep learning based soft sensor for air quality management Subject The topic of the resource Artificial ant colony optimization; CNN; Contour extraction and edge detection; Gradient vector flow Description An account of the resource Monitoring environmental pollution is emerging as a recent study area especially in urban and highly polluted industrial areas. This field deploys many chemical analysis models and data driven models through soft sensors. But bio indicators are a more feasible, cost effective and precise monitoring model, which are rarely explored. This paper is based on growth monitoring of Cryptogams, a bio indicator which is capable of directly reflecting the pollution levels in the region of growth. A novel enhanced and energy efficient deformable active contour model is introduced to trace the development of transplanted Cryptogams at various sites with diverse pollution levels. The vegetative development of Cryptogams is monitored for duration of two weeks. The proposed energy efficient contour tracing model proves its superiority in precise tracing of the Cryptogam development, thus aiding in accurate pollution monitoring. The VGG 16 architecture built using deep convolutional neural network by constructing stacks of filters. VGG 16 architecture showed high performance when compared with other existing models. The accuracy is compared with the Ant colony optimization using GVF. 2022 The Authors Creator An entity primarily responsible for making the resource P K.; Selvaraj P.; Burugari V.K.; K C.P.; S S.P. Source A related resource from which the described resource is derived Measurement: Sensors, Vol-24 Publisher An entity responsible for making the resource available Elsevier Ltd 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.measen.2022.100460" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.measen.2022.100460</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139055810&doi=10.1016%2Fj.measen.2022.100460&partnerID=40&md5=41a6ef6c74b30ccc6bb08284f895831e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139055810&doi=10.1016%2fj.measen.2022.100460&partnerID=40&md5=41a6ef6c74b30ccc6bb08284f895831e</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 26659174 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 P K., Department of DSBS, SRM Institute of Science and Technology, Chennai, India; Selvaraj P., School of CSE, VIT-AP University, Amaravati, India; Burugari V.K., Department of CSE, Koneru Lakshmaiah Education Foundation, K L University, Guntur, India; K C.P., Department of Information Technology, Bannari Amman Institute of Technology, Erode, India; S S.P., Department of CSE, 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 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 An energy efficient authentication scheme based on hierarchical ibds and eibds in grid-based wireless sensor networks Subject The topic of the resource Clustering; ECC; Elliptic curve cryptography; Grid-based WSN; Hierarchical identity-based digital signature; Routing; Security Description An account of the resource Wireless sensor network is a peculiar kind of ad hoc network, consists of hundreds of tiny, resource constrained as sensor nodes. Clustering is a demanding task in such environment mainly due to the unique constraints such as energy efficiency and dynamic topology. In this paper, a novel energy efficient cluster-based routing algorithm is proposed on which hierarchical identity-based digital signature (IBDS) and enhanced-identity-based digital signature (EIBDS) scheme is concerning in grid-based wireless sensor networks. Firstly we form clusters using multi-parameters-based type-2 fuzzy logic algorithm. This paper proposes an improved ant colony optimisation algorithm, which optimises the energy consumption on data transfer in a WSN. Each node in a sensor network is authenticated using elliptic curve cryptography (ECC). After a set of simulation tests on NS-3 simulator, our proposed work achieves good performance for various metrics. Copyright 2020 Inderscience Enterprises Ltd. Creator An entity primarily responsible for making the resource Kantharaju H.C.; Narasimha Murthy K.N. Source A related resource from which the described resource is derived International Journal of Information and Computer Security, Vol-13, No. 1, pp. 48-72. Publisher An entity responsible for making the resource available Inderscience Publishers 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/10.1504/IJICS.2020.108127" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJICS.2020.108127</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088248317&doi=10.1504%2FIJICS.2020.108127&partnerID=40&md5=c778af6533aafcbfbd1f3e5fc1f76288" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088248317&doi=10.1504%2fIJICS.2020.108127&partnerID=40&md5=c778af6533aafcbfbd1f3e5fc1f76288</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 17441765 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 Kantharaju H.C., Department of CSE, Vemana Institute of Technology, Bengaluru, Karnataka, India; Narasimha Murthy K.N., Faculty of Engineering, Christ (Deemed to be University), Mysore Road, Bengaluru, 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 An Energy Efficient Node Scheduling based Congestion Control Scheme for WSN Multicasting Subject The topic of the resource Congestion Control; Energy Efficiency; Node Scheduling; Wireless Sensor Network; WSN Multicast Description An account of the resource Wireless Sensor Network (WSN) is the most preferred technology for communication in resource constrained environments. They offer high-quality data propagation with limited delay. Sensor Network can be established with the help of self-configurable nodes to monitor various physical phenomenon. Multicasting in WSN results in low communication control overhead but may lead to congestion, which results in data loss, redundant transmissions, poor throughput and reduced network lifetime. In this paper, we propose a protocol to estimate the Degree of Congestion (CD) at each node to ensure load balance and avoid further congestion within the network. It is demonstrated that the proposed scheme is better compared with existing congestion control schemes in terms of end-to-end delay and energy efficiency. 2020 G. Raja Vikram et al., licensed to EAI Creator An entity primarily responsible for making the resource Raja Vikram G.; Shahu Chatrapati K.; Krishna A.V.N. Source A related resource from which the described resource is derived EAI Endorsed Transactions on Energy Web, Vol-2020, No. 30, pp. 1-6. Publisher An entity responsible for making the resource available European Alliance for Innovation 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/10.4108/eai.13-7-2018.164178" target="_blank" rel="noreferrer noopener">https://doi.org/10.4108/eai.13-7-2018.164178</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109957695&doi=10.4108%2Feai.13-7-2018.164178&partnerID=40&md5=965a58e5a69e3553de5472502f9b6cc6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109957695&doi=10.4108%2feai.13-7-2018.164178&partnerID=40&md5=965a58e5a69e3553de5472502f9b6cc6</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 2032944X 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 Raja Vikram G., Department of CSE, Vignan Institute of Technology & Science, Hyderabad, Telangana, India; Shahu Chatrapati K., Department of CSE, J.N.T.U.H College of Engineering, Manthani, Telangana, India; Krishna A.V.N., Department of CSE, CHRIST (Deemed to be University), Bangalore, 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 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 An Energy Optimized Clustering approach for Communication in Vehicular Cloud Systems Subject The topic of the resource dragonfly method; energy optimization; heuristics; routing; throughput; Vehicular cloud Description An account of the resource Vehicular cloud networks are considered to possess faster transitional topology and mobility thereby adhering to its features as an ad hoc network. Many times, it is difficult to monitor vehicular nodes that results in internetworking concerns as a result of power inadequacy during real computation. This leads to lots of energy wastage issues encountered during routing which degrades lifetime of nodes. Thus in this study a new clustering based energy optimization method is proposed to enhance the efficiency of vehicular communication. K-medoid cluster analysis along with dragonfly approach is applied to the system model to optimize energy. On the basis of simulation undertaken, it is recorded that the network lifetime, packets delivered, processing delay and throughput are increased using the proposed model. 2023 IEEE. Creator An entity primarily responsible for making the resource Bhaktisudha S.; Mishra S.; Nandi A.; Sharma V.; Alkhayyat A. Source A related resource from which the described resource is derived 2023 2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023, pp. 1060-1065. 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/SmartTechCon57526.2023.10391821" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/SmartTechCon57526.2023.10391821</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184808683&doi=10.1109%2FSmartTechCon57526.2023.10391821&partnerID=40&md5=d5cafaa69ff95d7ae937d7dc4e0fbb08" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184808683&doi=10.1109%2fSmartTechCon57526.2023.10391821&partnerID=40&md5=d5cafaa69ff95d7ae937d7dc4e0fbb08</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835030541-8 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 Bhaktisudha S., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Mishra S., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Nandi A., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Sharma V., CHRIST(Deemed to be University), Delhi-NCR, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq 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 An Enhanced Approximation Algorithm Using Red Black Tree and HashMap for Virtual Machine Placement Problem Subject The topic of the resource Approximation algorithm; Cloud computing; HashMap; Red Black Tree; Virtual machine; Virtual machine placement Description An account of the resource The virtual machine placement problem (VMPP) is an np-hard optimization problem in cloud computing that involves efficiently allocating virtual machines (VMs) to physical hosts in such a way that the resource wastage is minimized, and resource usage is optimal while ensuring adequate performance. This paper proposes a modified best-fit approximation algorithm using Red Black Tree (RBT) and HashMap for addressing the VMPP with enhanced computational efficiency in such a way that the active hosts in a given data center remains minimum possible. The proposed algorithm builds up on the existing best-fit approximation algorithm by using RBT and HashMap. The proposed approach considers various attributes such as CPU utilization, memory requirements, and network bandwidth while allocating virtual machines. To evaluate the performance the simulation is done in cloudsim environment with PlanetLab workload. Test cases are considered in both homogeneous and heterogeneous environments and results are taken. Comparative analyses were performed against existing benchmark algorithms in terms of time complexity and resource usage in terms of active hosts. The results demonstrate that the proposed algorithm outperforms the existing algorithms and guarantees time complexity of O(log n) and give better results compared to other algorithms. 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource John R.R.; Kanaga E.G.M.; Lovesum J.; Sandeep S.G. Source A related resource from which the described resource is derived SN Computer Science, Vol-5, No. 1 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-023-02465-x" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-023-02465-x</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181458050&doi=10.1007%2Fs42979-023-02465-x&partnerID=40&md5=8c6d509ecfebac92eac0e92f42798d16" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181458050&doi=10.1007%2fs42979-023-02465-x&partnerID=40&md5=8c6d509ecfebac92eac0e92f42798d16</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2662995X 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 John R.R., Karunya Institute of Technology and Sciences, Tamil Nadu, Coimbatore, India; Kanaga E.G.M., Karunya Institute of Technology and Sciences, Tamil Nadu, Coimbatore, India; Lovesum J., Christ (Deemed to be University), Karnataka, Bangalore, India; Sandeep S.G., Karunya Institute of Technology and Sciences, Tamil Nadu, 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 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 An Enhanced Automation Analysis for Structural Algorithm in Agro-Industries Using IoT Subject The topic of the resource agriculture; IoT; sensors; software; structural algorithm Description An account of the resource The Internet of Things (IoT) based structural algorithm for automatic agriculture refers to the system of using powerful real-time data collected from a variety of sensors with software and analytics to autonomously manage agro-ecosystems. This algorithm can be used to monitor environments, analyze data and use this knowledge to take specific actions to help farmers and producers maximize their production and profitability. This algorithm provides an unprecedented level of precision, accuracy and control over the agricultural environment, allowing greater efficiency and optimization in farming practices. It enables monitoring, scheduling, and control of different agro-ecosystem components, such as water, soil, fertilizer, light, humidity, temperature, soil pH and crop growth. The algorithm can also point to general trends and patterns in the environment, as well as offer timely advice to farmers in response to real-time conditions. The algorithm is also capable of automatically diagnosing and responding to unexpected problems, which can help prevent costly mistakes and excessive waste of water, fertilizer, energy, etc. 2023 by the authors. Creator An entity primarily responsible for making the resource Vineetha K R.; Bala N.N.; Sudha V.; Balakrishnan D. Source A related resource from which the described resource is derived Engineering Proceedings, Vol-59, No. 1 Publisher An entity responsible for making the resource available Multidisciplinary Digital Publishing Institute (MDPI) 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/10.3390/engproc2023059118" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/engproc2023059118</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186430694&doi=10.3390%2Fengproc2023059118&partnerID=40&md5=fa1c0abbe9131d8929381b3d583980fc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186430694&doi=10.3390%2fengproc2023059118&partnerID=40&md5=fa1c0abbe9131d8929381b3d583980fc</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 26734591 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 Vineetha K R., Department of Computer Science, Christ (Deemed to Be University), Bangalore, 560029, India; Bala N.N., Department of Mathematics, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, 600109, India; Sudha V., Department of Electronics and Communication Engineering, Sona College of Technology, Salem, 636201, India; Balakrishnan D., Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, 626126, 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 An enhanced biometric attendance monitoring system using queuing petri nets in private cloud computing with playfair cipher Subject The topic of the resource Biometric ID; Cloud Server; Image Recognition; Playfair Cipher; Queuing Petri Nets Description An account of the resource Every educational institutions needs to analyse and monitor participation. Educationists believe that there should be a fair number of students available in the majority of their classes. In colleges participation is used a measure of consistency. To deal with this kind of a challenging situation, biometric based participation monitoring framework is being proposed. This proposed method with the assistance of face recognition will help in maintaining every detail about the present students in a classroom save the same in the class database. The camera captures the image of students and compares them with the existing visual data available in the database. In case, the software is not able to find a match for the captured data in the student database, the particular student is marked as absent. Queuing Petri nets help in fulfilling customised demands of various institutions along with providing better performance in terms of hold up time. With the application of this technology, classroom participation is recorded and saved every hour. The database is accessed and maintained using cloud services and necessary security measured are incorporated as provided by major private cloud service providers with playfair cipher technique. 2020, Institute of Advanced Scientific Research, Inc. All rights reserved. Creator An entity primarily responsible for making the resource Kirubanand V.B. Source A related resource from which the described resource is derived Journal of Advanced Research in Dynamical and Control Systems, Vol-12, No. 5 Special Issue, pp. 459-468. Publisher An entity responsible for making the resource available Institute of Advanced Scientific Research, Inc. 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/10.5373/JARDCS/V12SP5/20201781" target="_blank" rel="noreferrer noopener">https://doi.org/10.5373/JARDCS/V12SP5/20201781</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090631835&doi=10.5373%2FJARDCS%2FV12SP5%2F20201781&partnerID=40&md5=b10275c5405c36ec3ebf134ffa54740c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090631835&doi=10.5373%2fJARDCS%2fV12SP5%2f20201781&partnerID=40&md5=b10275c5405c36ec3ebf134ffa54740c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1943023X 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 Kirubanand V.B., Department of Computer Science, 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 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 An Enhanced Data-Driven Weather Forecasting using Deep Learning Model Subject The topic of the resource Convolutional Neural Network; Deep Learning; Weather Forecasting; Weather Prediction Description An account of the resource Predicting present climate and the evolution of the ecosystem is more crucial than ever because of the huge climatic shift that has occurred in nature. Weather forecasts normally are made through compiling numerical data on from the atmospheric state at the moment and also applying scientific knowledge in the atmospheric processes to forecast on how the weather atmosphere would evolve. The most popular study subject nowadays is rainfall forecasting because of complexity in handling the data processing in addition to applications in weather monitoring. Four different state temperature data were collected and applied deep learning methods to predict the temperature level in the forthcoming months. The results brought out with the accuracy from 92.5% to 97.2% for different state temperature data. 2023 IEEE. Creator An entity primarily responsible for making the resource Krishnasamy L.; Anand D.V.; Vigneshwaran T.; Pathak L.K.; Maheswaran S. Source A related resource from which the described resource is derived 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 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/ICCCNT56998.2023.10307319" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCNT56998.2023.10307319</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179841437&doi=10.1109%2FICCCNT56998.2023.10307319&partnerID=40&md5=6d8c79ae8d95be2f6ff764096fd0a33a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179841437&doi=10.1109%2fICCCNT56998.2023.10307319&partnerID=40&md5=6d8c79ae8d95be2f6ff764096fd0a33a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033509-5 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 Krishnasamy L., Christ University, School of Engineering and Technology, Department of Cse, Bengaluru, India; Anand D.V., Kongu Engineering College, Department of Information Technology, Erode, India; Vigneshwaran T., Christ University, School of Engineering and Technology, Department of Cse, Bengaluru, India; Pathak L.K., Christ University, School of Engineering and Technology, Department of Cse, Bengaluru, India; Maheswaran S., Kongu Engineering College, Department of Electronics and Communication Engineering, Erode, 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 An Enhanced Deep Learning Model for Duplicate Question Detection on Quora Question pairs using Siamese LSTM Subject The topic of the resource FuzzyWuzzy; GloVe; Logistic Regression; Quora; Siamese Network; SVM; XgBoost Description An account of the resource The question answering platform Quora has millions of users which increases the probability of questions asked with similar intent. One question may be structured in two different ways by two users, and answering similar questions repeatedly impacts user experience. Manual filtration of such questions is a tedious task, so Quora attempts to detect and remove these duplicate questions by using the Random Forest Model, which is not completely effective. As Quora contains question answers in the form of text data, different Natural Language Processing techniques are used to transform the text data into numerical vectors. In this research, the log loss metric acts as the primary metric to evaluate different models. The primary contribution is that the Siamese network is used to process two questions parallelly and find vectors representation of each question. The vectors computed by this method enables similarity detection which is more effective than existing models. GloVe word embedding is used to understand the semantic similarity between two questions. The random classifier is built as the base model and logistic regression, linear SVM and XGBoost model are used to reduce the log loss. Finally, a Siamese LSTM is proposed which reduces the loss dramatically. 2022 IEEE. Creator An entity primarily responsible for making the resource Chandra M.; Rodrigues A.; George J. Source A related resource from which the described resource is derived IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2022 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/ICDCECE53908.2022.9792906" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDCECE53908.2022.9792906</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133412242&doi=10.1109%2FICDCECE53908.2022.9792906&partnerID=40&md5=631e1c6ced34879e0e9e2c34248f8b09" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133412242&doi=10.1109%2fICDCECE53908.2022.9792906&partnerID=40&md5=631e1c6ced34879e0e9e2c34248f8b09</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548316-2 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 Chandra M., Christ (Deemed to Be University), Department of Data Science, India; Rodrigues A., Christ (Deemed to Be University), Department of Data Science, India; George J., Christ (Deemed to Be University), Department of Data Science, 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 An enhanced framework to design intelligent course advisory systems using learning analytics Subject The topic of the resource Academic analytics; Framework; Learning analytics; Personalized system; Reference model Description An account of the resource Education for a person plays an anchor role in shaping an individuals career. In order to achieve success in the academic path, care should be taken in choosing an appropriate course for the learners. This research work is based on the framework to design a course advisory system in an efficient way. The design approach is based on overlapping of learning analytics, academic analytics, and personalized systems. This approach provides an efficient way to build course advisory system. Also, mapping of course advisory systems into the reference model of learning analytics is discussed in this paper. Course advisory system is considered as enhanced personalized system. The challenges involved in the implementation of course advisory system is also elaborated in this paper. Springer Science+Business Media Singapore 2017. Creator An entity primarily responsible for making the resource Vaidhehi V.; Suchithra R. Source A related resource from which the described resource is derived Advances in Intelligent Systems and Computing, Vol-468, pp. 723-732. Publisher An entity responsible for making the resource available Springer Verlag Date A point or period of time associated with an event in the lifecycle of the resource 2017-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-10-1675-2_71" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-10-1675-2_71</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984833756&doi=10.1007%2F978-981-10-1675-2_71&partnerID=40&md5=addb4558cefc0cf7bba32b6ff1f42ac4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984833756&doi=10.1007%2f978-981-10-1675-2_71&partnerID=40&md5=addb4558cefc0cf7bba32b6ff1f42ac4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21945357; ISBN: 978-981101674-5 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 Vaidhehi V., Department of Computer Science, Christ University, Bengaluru, Karnataka, India; Suchithra R., Department of Computer Science, Jain University, Bengaluru, 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 An enhanced network intrusion detection system for malicious crawler detection and security event correlations in ubiquitous banking infrastructure Subject The topic of the resource Bayesian network; Intrusion detection system (IDS); Malicious crawlers; Security correlations; Support vector machine Description An account of the resource Purpose: In the recent era, banking infrastructure constructs various remotely handled platforms for users. However, the security risk toward the banking sector has also elevated, as it is visible from the rising number of reported attacks against these security systems. Intelligence shows that cyberattacks of the crawlers are increasing. Malicious crawlers can crawl the Web pages, crack the passwords and reap the private data of the users. Besides, intrusion detection systems in a dynamic environment provide more false positives. The purpose of this research paper is to propose an efficient methodology to sense the attacks for creating low levels of false positives. Design/methodology/approach: In this research, the authors have developed an efficient approach for malicious crawler detection and correlated the security alerts. The behavioral features of the crawlers are examined for the recognition of the malicious crawlers, and a novel methodology is proposed to improvise the bank user portal security. The authors have compared various machine learning strategies including Bayesian network, support sector machine (SVM) and decision tree. Findings: This proposed work stretches in various aspects. Initially, the outcomes are stated for the mixture of different kinds of log files. Then, distinct sites of various log files are selected for the construction of the acceptable data sets. Session identification, attribute extraction, session labeling and classification were held. Moreover, this approach clustered the meta-alerts into higher level meta-alerts for fusing multistages of attacks and the various types of attacks. Originality/value: This methodology used incremental clustering techniques and analyzed the probability of existing topologies in SVM classifiers for more deterministic classification. It also enhanced the taxonomy for various domains. 2021, Emerald Publishing Limited. Creator An entity primarily responsible for making the resource Eswaran S.; Rani V.; Daniel D.; Ramakrishnan J.; Selvakumar S. Source A related resource from which the described resource is derived International Journal of Pervasive Computing and Communications, Vol-18, No. 1, pp. 59-78. Publisher An entity responsible for making the resource available Emerald Group Holdings Ltd. 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/10.1108/IJPCC-04-2021-0102" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/IJPCC-04-2021-0102</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114252266&doi=10.1108%2FIJPCC-04-2021-0102&partnerID=40&md5=83ba9256c6868ea550688b412c8096aa" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114252266&doi=10.1108%2fIJPCC-04-2021-0102&partnerID=40&md5=83ba9256c6868ea550688b412c8096aa</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 17427371 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 Eswaran S., Computer Science and Engineering, PES University, Bangalore, India; Rani V., Computer Applications, CMR Institute of Technology, Bangalore, India; Daniel D., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Ramakrishnan J., Department of Information Technology and Security, Jazan University, Jazan, Saudi Arabia; Selvakumar S., Computer Science and Engineering, KalaignarKarunanidhi Institute of 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 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 An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders Subject The topic of the resource Electrical distribution network; EV Charging stations; Optimization; Pathfinder algorithm; Solar systems Description An account of the resource Most low-voltage (LV) feeders have large distribution losses, poor voltage profiles, and inadequate voltage stability margins owing to their radial construction and high R/X ratio branches, and they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an extended pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the LV feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the LV feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time. The Author(s). Creator An entity primarily responsible for making the resource Pandraju T.K.S.; Janamala V. Source A related resource from which the described resource is derived Journal of Solar Energy Research, Vol-8, No. 4, pp. 1680-1690. Publisher An entity responsible for making the resource available University of Tehran 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/10.22059/jser.2023.359041.1300" target="_blank" rel="noreferrer noopener">https://doi.org/10.22059/jser.2023.359041.1300</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179329340&doi=10.22059%2Fjser.2023.359041.1300&partnerID=40&md5=de54bd7417964b9eace7699139fdc6b7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179329340&doi=10.22059%2fjser.2023.359041.1300&partnerID=40&md5=de54bd7417964b9eace7699139fdc6b7</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 25883097 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 Pandraju T.K.S., Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering and Technology, Andhra Pradesh, Vijayawada, 521139, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 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 An enhanced predictive modelling framework for highly accurate non-alcoholic fatty liver disease forecasting Subject The topic of the resource Chronic diseases; Class imbalance Classification; NAFLD; Predictive modelling; SMOTE Description An account of the resource Non-alcoholic fatty liver disease (NAFLD) is a chronic medical ailment characterized by accumulation of excessive fat in the liver of non-alcoholic patients. In absence of any early visible indications, application of machine learning based predictive techniques for early prediction of NAFLD are quite beneficial. The objective of this paper is to present a complete framework for guided development of varied predictive machine learning models and predict NAFLD disease with high accuracy. The framework employs stepby-step data quality enhancement to medical data such as cleaning, normalization, data upscaling using SMOTE (for handling class imbalances) and correlation analysis-based feature selection to predict NAFLD with high accuracy using only clinically recorded identifiers. Comprehensive comparative analysis of prediction results of seven machine learning predictive models is done using unprocessed as well as quality enhanced data. As per the observed results, XGBoost, random forest and neural network machine learning models reported significantly higher accuracies with improved AUC and ROC values using preprocessed data in contrast to unprocessed data. The prediction results are also assessed on various quality metrics such as accuracy, f1-score, precision, and recall significantly support the need for presented methodologies for qualitative NAFLD prediction modelling. 2025 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Arora N.; Srivastava S.; Tripathi A.; Gupta V. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-37, No. 1, pp. 214-222. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijeecs.v37.i1.pp214-222" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v37.i1.pp214-222</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208103725&doi=10.11591%2Fijeecs.v37.i1.pp214-222&partnerID=40&md5=a84dd07cd6cbc135d7799a85e5a88d1e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208103725&doi=10.11591%2fijeecs.v37.i1.pp214-222&partnerID=40&md5=a84dd07cd6cbc135d7799a85e5a88d1e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 25024752 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 Arora N., Department of Computer Science, Kalindi College, University of Delhi, Delhi, India; Srivastava S., School of Sciences, Christ University, Bengaluru, India; Tripathi A., Department of Data Science and Engineering, Manipal University Jaipur, Jaipur, India; Gupta V., School of Sciences, 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 An Enhanced SEIR Model for Prediction of COVID-19 with Vaccination Effect Subject The topic of the resource COVID-19; SEIR model; SEIRV; social distancing; vaccination Description An account of the resource Currently, the spread of COVID-19 is running at a constant pace. The current situation is not so alarming, but every pandemic has a history of three waves. Two waves have been seen, and now expecting the third wave. Compartmental models are one of the methods that predict the severity of a pandemic. An enhanced SEIR model is expected to predict the new cases of COVID-19. The proposed model has an additional compartment of vaccination. This proposed model is the SEIRV model that predicts the severity of COVID-19 when the population is vaccinated. The proposed model is simulated with three conditions. The first condition is when social distancing is not incorporated, while the second condition is when social distancing is included. The third one condition is when social distancing is combined when the population is vaccinated. The result shows an epidemic growth rate of about 0.06 per day, and the number of infected people doubles every 10.7 days. Still, with imparting social distancing, the proposed model obtained the value of R0 is 1.3. Vaccination of infants and kids will be considered as future work. 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Creator An entity primarily responsible for making the resource Poonia R.C.; Saudagar A.K.J.; Altameem A.; Alkhathami M.; Khan M.B.; Hasanat M.H.A. Source A related resource from which the described resource is derived Life, Vol-12, No. 5 Publisher An entity responsible for making the resource available MDPI 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/10.3390/life12050647" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/life12050647</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129768302&doi=10.3390%2Flife12050647&partnerID=40&md5=0e5d3f6c2b8f1048b799b593c3581662" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129768302&doi=10.3390%2flife12050647&partnerID=40&md5=0e5d3f6c2b8f1048b799b593c3581662</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20751729 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 Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Saudagar A.K.J., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Altameem A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Alkhathami M., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Khan M.B., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Hasanat M.H.A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, 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 An Enhanced Transfer Learning Based Classification for Diagnosis of Skin Cancer Subject The topic of the resource benign; classification; convolutional neural network; data augmentation; Kaggle; malignant; skin cancer; VGG16 Description An account of the resource Skin cancer is the most commonly diagnosed and reported malignancy worldwide. To reduce the death rate from cancer, it is essential to diagnose skin cancer at a benign stage as soon as possible. To save lives, an automated system that can detect skin cancer in its earliest stages is necessary. For the diagnosis of skin cancer, various researchers have performed tasks using deep learning and transfer learning models. However, the existing literature is limited in terms of its accuracy and its troublesome and time-consuming process. As a result, it is critical to design an automatic system that can deliver a fast judgment and considerably reduce mistakes in diagnosis. In this work, a deep learning-based model has been designed for the identification of skin cancer at benign and malignant stages using the concept of transfer learning approach. For this, a pre-trained VGG16 model is improved by adding one flatten layer, two dense layers with activation function (LeakyReLU) and another dense layer with activation function (sigmoid) to enhance the accuracy of this model. This proposed model is evaluated on a dataset obtained from Kaggle. The techniques of data augmentation are applied in order to enhance the random-ness among the input dataset for model stability. The proposed model has been validated by considering several useful hyper parameters such as different batch sizes of 8, 16, 32, 64, and 128; different epochs and optimizers. The proposed model is working best with an overall accuracy of 89.09% on 128 batch size with the Adam optimizer and 10 epochs and outperforms state-of-the-art techniques. This model will help dermatologists in the early diagnosis of skin cancers. 2022 by the authors. Licensee MDPI, Basel, Switzerland. Creator An entity primarily responsible for making the resource Anand V.; Gupta S.; Altameem A.; Nayak S.R.; Poonia R.C.; Saudagar A.K.J. Source A related resource from which the described resource is derived Diagnostics, Vol-12, No. 7 Publisher An entity responsible for making the resource available Multidisciplinary Digital Publishing Institute (MDPI) 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/10.3390/diagnostics12071628" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/diagnostics12071628</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133849397&doi=10.3390%2Fdiagnostics12071628&partnerID=40&md5=6e1f7b12eb723fbd8694fe1b30481367" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133849397&doi=10.3390%2fdiagnostics12071628&partnerID=40&md5=6e1f7b12eb723fbd8694fe1b30481367</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20754418 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 Anand V., Institute of Engineering and Technology, Chitkara University, Punjab, Rajpura, 140401, India; Gupta S., Institute of Engineering and Technology, Chitkara University, Punjab, Rajpura, 140401, India; Altameem A., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, 11533, Saudi Arabia; Nayak S.R., Amity School of Engineering and Technology, Amity University Uttar Pradesh, Uttar Pradesh, Noida, 201301, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, 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 An enhancing reversible data hiding for secured data using shuffle block key encryption and histogram bit shifting in cloud environment Subject The topic of the resource Cloud computing; Crypto analysis; Data distribution; Privacy preserving; Reversible hiding Description An account of the resource Nowadays there are numerous intruders trying to get the privacy information from cloud resources and consequently need a high security to secure our data. Moreover, research concerns have various security standards to secure the data using data hiding. In order to maintain the privacy and security in the cloud and big data processing, the recent crypto policy domain combines key policy encryption with reversible data hiding (RDH) techniques. However in this approach, the data is directly embedded resulting in errors during data extraction and image recovery due to reserve leakage of data. Hence, a novel shuffle block key encryption with RDH technique is proposed to hide the data competently. RDH is applied to encrypted images by which the data and the protection image can be appropriately recovered with histogram bit shifting algorithm. The hidden data can be embedded with shuffle key in the form of text with the image. The proposed method generates the room space to hide data with random shuffle after encrypting image using the definite encryption key. The data hider reversibly hides the data, whether text or image using data hiding key with histogram shifted values. If the requestor has both the embedding and encryption keys, can excerpt the secret data and effortlessly extract the original image using the spread source decoding. The proposed technique overcomes the data loss errors competently with two seed keys and also the projected shuffle state RDH procedure used in histogram shifting enhances security hidden policy. The results show that the proposed method outperforms the existing approaches by effectively recovering the hidden data and cover image without any errors, also scales well for large amount of data. 2018, Springer Science+Business Media, LLC, part of Springer Nature. Creator An entity primarily responsible for making the resource Senthilnathan T.; Prabu P.; Sivakumar R.; Sakthivel S. Source A related resource from which the described resource is derived Cluster Computing, Vol-22, pp. 12839-12847. 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 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s10586-018-1765-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s10586-018-1765-3</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042456229&doi=10.1007%2Fs10586-018-1765-3&partnerID=40&md5=f6d8ffb764432047873c0d28f6177f75" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042456229&doi=10.1007%2fs10586-018-1765-3&partnerID=40&md5=f6d8ffb764432047873c0d28f6177f75</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 13867857 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 Senthilnathan T., Department of Computer Science, Christ University, Bengaluru, Karnataka, India; Prabu P., Department of Computer Science, Christ University, Bengaluru, Karnataka, India; Sivakumar R., Department of Computer Science, Christ University, Bengaluru, Karnataka, India; Sakthivel S., Department of Computer Science and Engineering, Sona College of Technology, Salem, 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 An ensemble deep learning model for automatic classification of cotton leaves diseases Subject The topic of the resource Classification; Convolutional neural network; Ensemble model; Hyperparameter tuning; Machine learning Description An account of the resource Cotton plant (Gossypium herbaceum), is one of the significant fiber crop grown worldwide. However, the crop is quite prone to leaves diseases, for which deep learning (DL) techniques can be utilized for early disease prediction and prevent stakeholders from losing the harvest. The objective of this paper is to develop a novel ensemble based deep convolutional neural network (DCNN) model developed on two base pretrained models named: VGG16 and InceptionV3 for early detection of cotton leaves diseases. The proposed ensemble model trained on cotton leaves dataset reports higher training and testing prediction accuracies as compared to the base pretrained models. Given that, deep learning architectures have hyper-parameters, this paper presents exhaustive experimental evaluations on ensemble model to tune hyper-parameters named learning rate, optimizer and no of epochs. The suggested hyper-parameter settings can be directly utilized while employing the ensemble model for cotton plant leaves disease detection and prediction. With suggested hyper-parameters settings of learning rate 0.0001, 20 epochs and stochastic gradient descent (SGD) optimizer, ensemble model reported training and testing accuracies of 98% and 95% respectively, which was higher than the training and testing accuracies of VGG16 and InceptionV3 pretrained DCNN models. 2024 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Kukadiya H.; Arora N.; Meva D.; Srivastava S. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-33, No. 3, pp. 1942-1949. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science 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/10.11591/ijeecs.v33.i3.pp1942-1949" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v33.i3.pp1942-1949</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185585750&doi=10.11591%2Fijeecs.v33.i3.pp1942-1949&partnerID=40&md5=69791800f23c19717224e468349a1fbc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185585750&doi=10.11591%2fijeecs.v33.i3.pp1942-1949&partnerID=40&md5=69791800f23c19717224e468349a1fbc</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 25024752 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 Kukadiya H., Department of Computer Application, Marwadi University, Rajkot, India; Arora N., Department of Computer Science, Kalindi College, University of Delhi, Delhi, India; Meva D., Department of Computer Application, Marwadi University, Rajkot, India; Srivastava S., School of Sciences, Christ (Deemed to be University), Delhi NCR, 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 An equal split triple-band wilkinson power divider employing extended cross shaped microstrip line / Subject The topic of the resource Engineering Description An account of the resource Microwave and Optical Technology Letters, Vol.60, Issue 10, pp.2488-2492. Creator An entity primarily responsible for making the resource Rusan Kumar Barik, T.S. Laxman Deep and S.S. Katthikeyan Source A related resource from which the described resource is derived <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/mop.31386" target="_blank" title="An equal split triple-band Wilkinson power divider employing extended cross-shaped microstrip line" rel="noreferrer noopener">https://onlinelibrary.wiley.com/doi/abs/10.1002/mop.31386</a> Publisher An entity responsible for making the resource available Wiley Date A point or period of time associated with an event in the lifecycle of the resource 2018-12-29 Language A language of the resource English Type The nature or genre of the resource Journal Article 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 An ethnographic expose of Mithun-human interrelationship among the Kuki community of Northeast India Subject The topic of the resource bride price; culture; Kuki; mithun; Mithun-human interrelationship Description An account of the resource Unrestrained consumption and a lack of a proper breeding ecosystem have depleted the variety and species count of mithun (Bos frontalis). Indigenous Kuki tribes have a unique relationship with mithun, reared in the semi-domestic countryside. For the Kuki community, a mithun is used during community festivals, as a bride price in marriages, to settle disputes, in land-deed covenants, and at death ceremonies. Mithun-human interrelationship lessens poverty, empowers community survival, guarantees the completion of critical cultural obligations, and maintains marital bonds in the Kuki community. The head of a mithun signifies solemnity and celebration in many cultural underpinnings. A white cock, a dog, a goat, a pig, and a mithun were sacrificial elements to appease the unseen spirits for good health and prosperity. While some Indigenous practices have faded with the arrival of Christianity, the cultural involvement of mithun persists to this date. 2023 Informa UK Limited, trading as Taylor & Francis Group. Creator An entity primarily responsible for making the resource Haokip P.L.; Maya M.; Haokip D.B. Source A related resource from which the described resource is derived Asian Ethnicity, Vol-25, No. 3, pp. 403-416. Publisher An entity responsible for making the resource available Routledge 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/10.1080/14631369.2023.2275588" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/14631369.2023.2275588</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176147365&doi=10.1080%2F14631369.2023.2275588&partnerID=40&md5=ff3ba20b479145e28d7add38f9fb9a48" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176147365&doi=10.1080%2f14631369.2023.2275588&partnerID=40&md5=ff3ba20b479145e28d7add38f9fb9a48</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 14631369 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 Haokip P.L., Department of Sociology & Social Work, Christ University, Karnataka, Bangalore, India; Maya M., Department of Sociology & Social Work, Christ University, Karnataka, Bangalore, India; Haokip D.B., University of Amsterdam, Netherlands