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4th Inter.a.ional Conference on Sustainable Expert Systems, ICSES 2024

作者： Sathya, V. Bhadula, Shuchi Srinivasan, r. Bhar.a., H.K. Panda, Bhavani Sankar Barve, Amit Department of Computer Science Vallam Tamil Nadu Thanjavur613403 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248 002 India Veltech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Department of Computer Science and Engineering Avadi Tiruvallur Tamil Nadu Chennai600054 India Shridevi Institute of Engineering and Technology Department of Computer Science and Engineering Karnataka Tumakuru572106 India Raghu Engineering College Department of Computer Science and Engineering Andhra Pradesh Visakhapatnam531162 India Parul Institute of Technology Parul University Faculty of Engineering and Technology Department of Computer Science and Engineering P.O.Limda Gujarat 391760 India

ISBN: (纸本)9798331540364

Disasters can be mitigated by an early warning signal and proper communication within the hazardous environment using the MANET technology. However, the exact prediction of disaster situation is needed for the timely disaster management. Hence in addition to MANET technology, deep learning algorithms and Inter of Things (IoT) can also be integrated into disaster detection and communication systems. The presented research developed a novel parallely distributed slimmable neural network with orchard algorithm for the accurate flood disaster prediction. The model processed the dataset containing various measurements such as temperature, humidity, precipitation, air, soil moisture and rainfall level that are collected by the IoT sensor deployed in the various location of the hazardous environment. The gathered data are initially pre-processed using the correlation coefficient min-max nor.a.ization appr.a.h. Further, the relevant characteristics of the flood disaster from the data are extracted through spike driven transformer process. These refined and dimensionality reduced data are then entered into the proposed framework for the disaster prediction. Here the integrated orchard algorithm incr.a.ed the disaster monitoring accuracy on the basis of better optimized parameters. The model resulted 95% accuracy, 93% precision, 94% recall and 96% f-score. Therefore, the presented method is an effective prediction mechanism for the disaster management in IoT MANET. © 2024 IEEE.

关键词： Soil moisture

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An Intelligent Appr.a.h for retinal Vessels Extraction Based on Transfer Learning

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SN computer Science 2024年第8期5卷 1-16页

作者： Ver.a. Prem Kumari Kaur, Jagdeep Singh, Nagendra Pratap Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar 144008 India

An essential step in diagnosing ocular illnesses is automatically segmenting retinal blood vessels. Although current deep-learning techniques have attained excellent accuracy in artery segmentation, maintaining vascular structural connections is still tricky. The most frequent consequence of diabetes, and the main factor in adult blindness, is diabetic retinopathy. Currently, diagnosing fundus pictures is the primary method clinicians use to pinpoint the origin of diabetic retinopathy. Conducting manual screening on a large scale for retinal health is challenging. Therefore, the objective of my article is to state the segmentation of retinal blood vessels for early retinal disease detection and diagnosis. The proposed research method includes a U-net network with VGG19 and ImageNet is the backbone for extracting retinal vessels, and the extraction perfor.a.ce is found to be better with respect to another existing appr.a.h in the literature. The proposed methodology includes pre-processing, augmentation, patching, and model setup and implementation. First, pre-processing the available data to enhance the vessels of retinal image. The skip connections, the semantic gap left by a direct simple connection is filled using the nested connection method to combine the feature maps obtained from the intermediate decoder with the original features from the encoder. Data augmentation is also done on the original image to incr.a.e resilience and avoid the overfitting issue brought on by insufficient data. A mixed loss function is suggested to address the class imbalance in vascular pictures. After exhaustive experimental analysis observed, the Accuracy, Ar.a.Under Curve (AUC), and Jaccard index values are 0.9728, 0.9961, and 0.9175 for the DrIVE Date-set and) 0.9668, 0.9851, and 0.8975 for STArE Date-set respectively. Compared to the DrIVE data set, the proposed strategy performed better.a. the beginning but worse towards the end for the STArE data set. For the DrIVE and STArE

关键词： retinal blood vessels Segmentation UNet

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Steganography Methods for GIF Images: A review 4th

Steganography Methods for GIF Images: A Review

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4th Inter.a.ional Conference on Computing, Communications, and Cyber-Security, IC4S 2022

作者： Gupta, Anjali Awasthi, Lalit K. Singh, Samayveer Department of Computer Science and Engineering Dr. B R Ambedkar National Institute of Technology Punjab Jalandhar India Department of Computer Science and Engineering National Institute of Technology Uttarakhand Srinagar India

ISBN: (纸本)9789819914784

Steganography is the art of hiding secret messages within a non-secret object. It helps hide infor.a.ion in images such as graphics interchange for.a. (GIF) images, text, audio, and video. In GIFs, animated GIFs are a common form of media. GIF images are mainly classified into two types: GIF87a and GIF89a. GIF87a is a type of palette-based image, and GIF89a is the improved version of GIF87a because the GIF89a image has more than one frame. Furthermore, it allows the GIF image to play simple animations. In addition, message hiding in palette-based graphics can be accomplished in two significant ways: firstly, by embedding messages into the frame, and secondly, by embedding messages into the palette. The primary goal of this paper is to review and describe numerous methodologies for hiding data within the GIF images and make a detailed comparison of these methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Embeddings

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Software Cost Estimation: A Literature review and Current Trends 3

Software Cost Estimation: A Literature Review and Current Tr...

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3rd Inter.a.ional Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Singh, Suneeta Kumar, Kuldeep Dr B R Ambedkar National Institute of Technology Jalandhar Department of Computer Science and Engineering Punjab Jalandhar India National Institute of Technology Kurukshetra Department of Computer Engineering Haryana Kurukshetra India

ISBN: (纸本)9798350300710

Software cost estimation is a challenging and complex task during software development. It directs project managers and developers to analyze and predict costs at the beginning of the software development life cycle. The most impor.a.t job for developing software projects is correctly estimating cost, time duration, and needed effort. This paper.a.ms to review different models used for software cost estimation, including algorithmic, non-algorithmic, and learning-oriented models, which have been published over the last ten years (i.e., from 2011 to 2022). The comparison is done based on the methods, selected datasets, and metrics used in different techniques. We observed that machine learning-based models perform better compared to other existing methods. However, to the best of our knowledge, analysis, and literature survey, we found that no technique in the literature provides a fit-all solution. © 2023 IEEE.

关键词： Cost estimating

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Code word Based Bi-Server.a.thentication and Key Exchange Encryption Technique 1

Code word Based Bi-Server Authentication and Key Exchange En...

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1st Inter.a.ional Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Thangarasan, T. Karthikeyan, V. Arunkumar, G. Arul Prakash, A. Keerthana, r. Gouthami, Kamsala Madanapalle Institute of Technology & Science Department of Computer Science & Engineering AndhraPradesh Madanapalle India Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Department of Computer Science & Engineering Tamilnadu Chennai India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Tamilandu Chennai India K.S.R.College of Engineering Department of Computer Science and Engineering Tamilnadu Tiruchengode India

ISBN: (纸本)9798350328042

The data transfer.a.d communication happening between the client and server or the source to destination should be made in some secure way. It must be protected and authenticated. the passwords related to that all will be stored in a centralized database. The majority of codeword-based user.a.thentication systems assume complete reliance in the authentication server, this refers to the location where centralized databases store passwords in plain text or easily inferred code verification infor.a.ion. System defenses against server-side offline dictionary attacks are nonexistent. In the event that insiders or outsiders hack the authentication server, all user code words become public. which could have severe legal and financial ramifications for.a.business. A codeword-based client authentication and confidential key exchange system using cutting-edge bi-server.a.chitecture serves as the answer to the aforementioned problems. The sever providing the front-end service communicates directly with users in this setup;the control server remains in the background. The proposed system provides security against the offline dictionary attacks that can happen from any of the servers. The proposed work has been implemented by using java and netbeans IDE 6.1. © 2023 IEEE.

关键词： Data transfer

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Knowledge-Driven Possibilistic Clustering with Automatic Cluster Elimination

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computers, Mater.a.s & Continua 2024年第9期80卷 4917-4945页

作者： Xianghui Hu Yiming Tang Witold Pedrycz Jiuchuan Jiang Yichuan Jiang The School of Computer Science and Engineering Southeast UniversityNanjing211189China The School of Computer and Information Hefei University of TechnologyHefei230601China The Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R 2V4Canada The Systems Research Institute Polish Academy of SciencesWarsaw00-901Poland The School of Information Engineering Nanjing University of Finance and EconomicsNanjing210023China

Traditional Fuzzy C-Means(FCM)and Possibilistic C-Means(PCM)clustering algorithms are data-driven,and their objective function minimization process is based on the available numeric ***,knowledge hints have been introduced to formknowledge-driven clustering algorithms,which reveal a data structure that considers not only the relationships between data but also the compatibility with knowledge ***,these algorithms cannot produce the optimal number of clusters by the clustering algorithm itself;they require the assistance of evaluation ***,knowledge hints are usually used as part of the data structure(directly replacing some clustering centers),which severely limits the flexibility of the algorithm and can lead to *** solve this problem,this study designs a newknowledge-driven clustering algorithmcalled the PCM clusteringwith High-density Points(HP-PCM),in which domain knowledge is represented in the form of so-called high-density ***,a newdatadensitycalculation function is *** Density Knowledge Points Extraction(DKPE)method is established to filter out high-density points from the dataset to form knowledge ***,these hints are incorporated into the PCM objective function so that the clustering algorithm is guided by high-density points to discover the natural data ***,the initial number of clusters is set to be gr.a.er than the true one based on the number of knowledge ***,the HP-PCM algorithm automatically determines the final number of clusters during the clustering process by considering the cluster elimination *** experimental studies,including some comparative analyses,the results highlight the effectiveness of the proposed algorithm,such as the incr.a.ed success rate in clustering,the ability to determine the optimal cluster number.a.d the faster convergence speed.

关键词： Fuzzy C-Means(FCM) possibilistic clustering optimal number of clusters knowledge-driven machine learning fuzzy logic

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Hybrid Algorithm for Secure routing in MANET Using Cryptographic Applications

Hybrid Algorithm for Secure Routing in MANET Using Cryptogra...

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2024 IEEE Inter.a.ional Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Muruganandam, S. Gnanavel, S. Narayana, K.E. Jaeyalakshmi, M. Antony Kumar, K. Panimalar Engineering College Department of Computer Science and Business Systems Chennai India SRM Institute of Science and Technology Kattankulathur Campus Faculty of Engineering and Technology Department of Computing Technologies Chengalpattu India Rajalakshmi Engineering College Department of Information Technology Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331522988

In Mobile sensor Networks, Each and every wireless node dynamically changes its location due to its mobility nature. The routing infor.a.ion is maintained by the master node to deliver.a.data packet from source to destination. The attackers easily hack this wireless network. The perfor.a.ce of the complete networks is dropped by packets transmission attacks. Attacker node drops the packet. An enhanced protection technique in response to packets transmission misbehaviour.a.tacks is provided to incr.a.e the energy efficiency of mobile nodes. This paper proposed the Cryptographic formed Malicious Node Detection and Secure routing framework (CMNDSr). This model incorporates three various strategies specially algorithm for control of access, to protects initial illegal node in the network. The suspected identification and prevention techniques based on hop count value. Secure routing method with a private key generated at random like one time password (OTP). The proposed methods are power efficient, by operating a minimum number of nodes in challenging environment. The misbehaviour nodes are promptly identified and isolated using this proposed appr.a.h. The Cryptographic based Secure routing algorithm is applied to provide secure transmission in wireless networking environment. The outcomes of the simulation display how effectively the recommended appr.a.h can identify malicious nodes in a MANET. In comparison with previous methods, the energy consumption is 10% lower.a.d the suspicious node detection rate is incr.a.ed by 95%. © 2024 IEEE.

关键词： Encryption algorithms

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4th Inter.a.ional Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： roselinkiruba, r. Jude Moses Anto Devakanth, J. Sharmila, L. Vasumathy, M. Misba, M. Saranya Jothi, C. Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology Chennai Avadi India Madanapalle Institute of Technology and Science Department of Computer Applications Andra Pradesh India Department of Information Technology Kingston Engineering College Vellore India

ISBN: (纸本)9798331515720

Steganography is the method that convert data into bits to make it suitable for hiding. While embedding data the factors such as stego image quality and distortion which cannot be observed by the human eyes. The aim of this study is to incr.a.e the stego image with good quality. Initially, the image pixels are separated into different bit planes then it is compared with the secret data bit planes using Fruitfly Optimization Improved Hybridized Algorithm Pixel Similarity (FOIS-PS). For that similar pixel Fitness Function (FF) is applied based on the three impor.a.t criter.a.such as edge, entropy and correlation. Finally, the data is embedded in the LSB bits based on their Embedding Capacity (EC). Using this method, the size of the input is reduced. Then, the data is embedded based on difference of pixels within each group of similar pixels. Evaluation metrics shows the quality of the stego image is boosted and also reduces the processing time. © 2024 IEEE.

关键词： Image quality

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Transfer Function Based Feature Selection Using Harris Hawk Optimization for Biomedical Applications

Transfer Function Based Feature Selection Using Harris Hawk ...

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2024 Inter.a.ional Conference on Smart Electronics and Communication Systems, ISENSE 2024

作者： Jayachitra, S. Prasanth, A. Prasannakiruba, G.S. Abbineni, Srichandana PSNA College of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Bannari Amman Institute of Technology Department of Computer Technology Sathyamangalam India Hyderabad India

ISBN: (纸本)9798331528126

Feature Selection plays key role to truncate the high dimensionality in the datasets through eradicating the unwanted and noisy attributes to improve the perfor.a.ce of classification. The Meta-heuristic technique is one of the most optimistic search techniques to travel the feature space to locate finest feature subset. The Harris Hawk Optimization (HHO) excited from hunting appr.a.h of hawk in nature. The cost effectiveness and simplicity formulates the algorithm prominent and superior in solving optimization problems. The binary version of the optimization is accountable for delineating continuous searching space to discrete feature space. Here, 6 transfer functions with S-Shaped and V-Shaped families were interposed and analyzed. Twelve benchmark datasets from UCI repository has been introduced to examine the transfer functions and choose the best feature per.a.ning to mitigate local minima and high speed of convergence. To analyze the efficacy of transfer function, the proposed method was compared over exiting algorithms and the proposed results attain higher classification accuracy in many of the datasets. © 2024 IEEE.

关键词： Heuristic methods

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An Efficient Fog Computing Platform Through Genetic Algorithm-Based Scheduling 1st

An Efficient Fog Computing Platform Through Genetic Algorith...

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1st Inter.a.ional Conference on Machine Intelligence for research and Innovations, MAiTrI 2023

作者： Chauhan, Shivam Swain, Chinmaya Kumar Behera, Lalatendu Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar India Department of Computer Science and Engineering SRM University Andhra Pradesh Amaravati India

ISBN: (纸本)9789819981281

The Internet of Things (IoT) has led to the adoption of fog computing for data-intensive applications that require low-latency processing. Fog computing uses distributed nodes near the network edge to reduce delays and save bandwidth. To optimize resource usage and achieve goals in fog computing, task scheduling plays a crucial role. To tackle this challenge, we propose an appr.a.h based on genetic algorithms, inspired by genetics and natural selection. We evaluate GA algorithm based on their.a.ility to complete tasks and prioritize them effectively. The results show that the genetic algorithm performs exceptionally well, completing more tasks and handling priorities efficiently. Its adaptability to changing situations enables optimal resource usage and task completion. Our findings underscore the significance of genetic algorithms in fog computing systems. The insights gained from this study contribute to the advancement of fog computing systems, benefiting IoT applications and services. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fog

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