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7th International Conference on Soft Computing and Signal Processing, ICSCSP 2024

作者： Kumar, Gotte Ranjith Babu, K. Suresh Research Scholar Department of Computer Science and Engineering Jawaharlal Nehru Technological University Kukatpally Telangana Hyderabad500085 India Assistant Professor School of CS&AI SR University Telangana Warangal506371 India Professor Department of Computer Science and Engineering Jawaharlal Nehru Technological University Kukatpally Telangana Hyderabad500085 India

ISBN: (纸本)9789819799251

Mobile devices, empowered by advanced wireless networks, have revolutionized information sharing and productivity across industries. However, this ubiquitous connectivity exposes user privacy and security to risks. The core vulnerability lies in the lack of authentication between mobile devices and DHCP (Dynamic Host Configuration Protocol) servers, which assign network configurations. This research explored existing authentication mechanisms in wireless networks to address these DHCP-related security concerns, highlighting the essence of secure data communication in mobile environments. The majority of the authentication mechanisms rely on centralized environments. Some rely on a cryptographic security key, which needs to be exchanged during authentication. Blockchain-based authentication is proposed. This technology is distributed, scalable, and robust. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mobile security

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Deep Learning-Based Non-Intrusive Multi-Objective Speech Assessment Model with Cross-Domain Features

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IEEE/ACM Transactions on Audio Speech and Language Processing 2023年 31卷 54-70页

作者： Zezario, Ryandhimas E. Fu, Szu-Wei Chen, Fei Fuh, Chiou-Shann Wang, Hsin-Min Tsao, Yu National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115024 Taiwan Microsoft VancouverBCV6B 5C6 Canada Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen518055 China Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan Chung Yuan Christian University Jointly Appointed Professor with the Department of Electrical Engineering Taoyuan32023 Taiwan

This study proposes a cross-domain multi-objective speech assessment model, called MOSA-Net, which can simultaneously estimate the speech quality, intelligibility, and distortion assessment scores of an input speech signal. MOSA-Net comprises a convolutional neural network and bidirectional long short-Term memory architecture for representation extraction, and a multiplicative attention layer and a fully connected layer for each assessment metric prediction. Additionally, cross-domain features (spectral and time-domain features) and latent representations from self-supervised learned (SSL) models are used as inputs to combine rich acoustic information to obtain more accurate assessments. Experimental results show that in both seen and unseen noise environments, MOSA-Net can improve the linear correlation coefficient (LCC) scores in perceptual evaluation of speech quality (PESQ) prediction, compared to Quality-Net, an existing single-Task model for PESQ prediction, and improve LCC scores in short-Time objective intelligibility (STOI) prediction, compared to STOI-Net, an existing single-Task model for STOI prediction. Moreover, MOSA-Net can be used as a pre-Trained model to be effectively adapted to an assessment model for predicting subjective quality and intelligibility scores with a limited amount of training data. Experimental results show that MOSA-Net can improve LCC scores in mean opinion score (MOS) predictions, compared to MOS-SSL, a strong single-Task model for MOS prediction. We further adopt the latent representations of MOSA-Net to guide the speech enhancement (SE) process and derive a quality-intelligibility (QI)-Aware SE (QIA-SE) approach. Experimental results show that QIA-SE outperforms the baseline SE system with improved PESQ scores in both seen and unseen noise environments over a baseline SE model. © 2014 IEEE.

关键词： Speech enhancement

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A Lightweight Encryption Method for Preserving E-Healthcare Data Privacy Using Dual Signature on Twisted Edwards Curves 1

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5th International Conference on computer and Communication Technologies, IC3T 2023

作者： Farhat, Suryya Kumar, Manoj Vaish, Arti Dewangan, Bhupesh Kumar Choudhury, Tanupriya Kotecha, Ketan Department of Applied Science and Humanities ADGITM Delhi110053 India Department of Mathematics and Statistics Gurukula Kangri Vishwavidyalaya Haridwar249404 India Department of Computer Science and Engineering OP Jindal University Raigarh496109 India Lavale Campus Maharashtra Pune412115 India Pune412115 India Research Professor CSE Dept. Graphic Era Deemed to be University Uttarakhand Dehradun248002 India

ISBN: (数字)9789819997077

ISBN: (纸本)9789819997060

Due to covid-19 pandemic, research in e-healthcare system is gaining popularity because in most of the cases e-healthcare system does not require to present patient physically at doctor’s door. The reason behind this is that e-healthcare system eliminates the necessity for patient to travel at healthcare centres for doctor’s prescription or to collect their diseases diagnostic reports. In the present paper, we have proposed an algorithm, which may be capable to provide integrity for e-healthcare data and preserve its privacy also. The proposed scheme combines dual signature with EdDSA. Dual signature looks similar to double signature but it is quite different;it is a technique of coupling to different values of varied natures preserving them anonymous to varied objects securely. From recent research, it has been proved that elliptic curve cryptography is more suitable for resource constraint (lightweight) device when compared with RSA. Being an improvement of ECDSA, EdDSA signature generation is egregious and affordable. Moreover, EdDSA signature verification, being computationally very hard task, cannot be carried out by e-healthcare devices. Although edge computing devices having no operational constraints can easily perform this task. These characteristics make our proposal more elegant, perky, and efficient strategy for e-healthcare system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Diagnosis

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Secured Cloud Data Migration Technique by Competent Probabilistic Public Key Encryption

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China Communications 2020年第5期17卷 168-190页

作者： M.G.Aruna K.G.Mohan Aassociate professor department of computer science and engineeringm s engineering collegeaffiliated to vtubengalurukarnataka562110india professor and head department of computer science and engineeringpresidency universitybengalurukarnataka560064india

Cloud computing, a recently emerged paradigm faces major challenges in achieving the privacy of migrated data, network security, etc. Too many cryptographic technologies are raised to solve these issues based on identity, attributes and prediction algorithms yet;these techniques are highly prone to attackers. This would raise a need of an effective encryption technique, which would ensure secure data migration. With this scenario, our proposed methodology Efficient Probabilistic Public Key Encryption(EPPKE) is optimized with Covariance Matrix Adaptation Evolution Strategies(CMA-ES). It ensures data integrity through the Luhn algorithm with BLAKE 2b encapsulation. This enables an optimized security to the data which is migrated through cloud. The proposed methodology is implemented in Open Stack with Java Language. It achieves better results by providing security compared to other existing techniques like RSA, IBA, ABE, PBE, etc.

关键词： Luhn algorithm encryption efficient probabilistic public key encryption(EPPKE) covariance matrix adaptation evolution strategies(CMA-ES) trusted third party(TTP)

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A Multi-criteria Decision-Making Approach to Analyze Python Code Smells 1

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International Conference on Advances in Electrical and computer Technologies, ICAECT 2021

作者： Gupta, Aakanshi Sharma, Deepanshu Phulli, Kritika Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Noida India Executive Branch-IT Indian Navy New Delhi India Application Development Associate Accenture India

ISBN: (数字)9789811911118

ISBN: (纸本)9789811911101

Frequent modifications in the software leads to the issues in the code which deteriorates software quality. The suitable approach to rectify it is to refactor it. Consequently, this research devises a ranking using the MCDM approach for prioritizing Python-based code smells. This order ranking has been studied over 10,552 classes for five generic code smells diffused in 20 Python software. The software metrics extracted over these python classes have been considered as multiple criteria which are processed using rule-based machine learning approach. In this study, an approach providing compromised solution—VIKOR have been practiced along with TOPSIS and WASPAS methods. Additionally, the MCDM approaches have utilized Shannon’s Entropy and CRITIC method as weight estimation techniques. The extracted vital software metrics achieved over 90% accuracy. The prominent outcome portrays that the most dominant smell is Collapsible "IF" which needs to be refactored at the early stage. This should be accompanied by Cognitive Complexity smell so as to attain sustainable development environment. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Python

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Free vibration analysis of functionally graded porous curved nanobeams on elastic foundation in hygro-thermo-magnetic environment

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Frontiers of Structural and Civil engineering 2023年第4期17卷 584-605页

作者： Quoc-Hoa PHAM Parviz MALEKZADEH Van Ke TRAN Trung NGUYEN-THOI Faculty of Engineering and Technology Nguyen Tat Thanh UniversityHo Chi Minh City 700000Vietnam Department of Mechanical Engineering Persian Gulf UniversityBushehr ***Iran Faculty of Mechanical Engineering Le Quy Don Technical UniversityHanoi 100000Vietnam Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 700000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 700000Vietnam Bualuang ASEAN Chair Professor Thammasat School of EngineeringThammasat UniversityPathumtani 12120Thailand

Herein,a two-node beam element enriched based on the Lagrange and Hermite interpolation function is proposed to solve the governing equation of a functionally graded porous(FGP)curved nanobeam on an elastic foundation in a hygro–thermo–magnetic *** material properties of curved nanobeams change continuously along the thickness via a power-law distribution,and the porosity distributions are described by an uneven porosity *** effects of magnetic fields,temperature,and moisture on the curved nanobeam are assumed to result in axial loads and not affect the mechanical properties of the *** equilibrium equations of the curved nanobeam are derived using Hamilton’s principle based on various beam theories,including the classical theory,first-order shear deformation theory,and higher-order shear deformation theory,and the nonlocal elasticity *** accuracy of the proposed method is verified by comparing the results obtained with those of previous reliable ***,the effects of different parameters on the free vibration behavior of the FGP curved nanobeams are investigated comprehensively.

关键词： functionally graded porous material curved nanobeam hygro-thermo-magnetic enriched finite element method

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Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Redundant Weighted Clustered Scheme with Dynamic Weights Adj...

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IEEE International Conference on Communications (ICC)

作者： Grace Khayat Constandinos X Mavromoustakis Andreas Pitsillides Jordi Mongay Batalla Evangelos K. Markakis Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor) Warsaw University of Technology Warsaw Poland Department of Electrical and Computer Engineering Hellenic Mediteranean University Estavromenos Heraklion Greece

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Swarm of UAVs (S-UAVs) is the term used to describe an unplanned gathering of un-manned aerial vehicles (UAVs) that collaborate to complete predefined missions. Any UAV has a risk of being damaged in crisis situations like fire. Clustering is one of the most often used routing algorithms in S-UAVs. The clustering scheme divides the UAVs into clusters, with a cluster head (CH) and cluster members (CM) in each cluster. The CH plays a critical role within inter-cluster communication, and because of this, its selection is an ongoing area of study. A clustered weighted scheme with redundancy and dynamic weight adjustment is proposed in this paper. The selection of the principal CH, redundant CHs, and CMs is based on a weighted formula composed of distance, speed, and rewarding index. Whenever the primary CH is damaged, the redundant CH takes its place immediately. After the first clustering process, the proposed scheme dynamically and autonomously adjusts the weights to optimize the UAV role selection. According to the outcomes of the carried-out simulation, this is a promising scheme that reduces data loss in a crisis-case scenario and optimizes the time delay through the dynamic adjustments of the weights.

关键词： Delay effects Redundancy Clustering algorithms Routing Autonomous aerial vehicles Indexes Vehicle dynamics

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Next-Generation Diagnostic Tools: The Role of Hybrid CNN-Transformer Models in Liver Cancer Detection

Next-Generation Diagnostic Tools: The Role of Hybrid CNN-Tra...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Satvik Vats Choudhary Ravi Singh Shiva Mehta Computer Science and Engineering Graphic Era Hill University Adjunct professor Graphic Era Deemed to be University Dehradun India Computer Science And Engineering Department Invertis University Bareilly Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The content of this paper describes a novel CNN-Transformer hybrid model that detects, classifies, and differentiates focal liver lesions into various categories using contrast-enhanced ultrasound (CEUS). A model, a harmonious convolutional neural network (CNN) integration and a decoder enable us to achieve a tremendous diagnostic performance (AUC of 0.8237 and an accuracy of 0.78). It outperforms the conventional baseline models. Merging local and global patio-temporal data aids the model designed for FLL categorizing. It allows the model to detect early at diagnosis and improves diagnostic confidence. The proposed methodology may do away with the previous health care practices that were heavy and complicated yet bring back the desired patient outcomes. Future studies should be oriented towards understanding the technology better, specifically its usability, and conducting clinical validation trials. Another element should be studied to determine its suitability for different medical imaging techniques. Efficient CNN-Transformer architecture is a significant milestone in developing an efficient liver cancer detection method that might become a robust clinical practice tool allowing emerging precision medicine.

关键词： Frequency locked loops Liver cancer Ultrasonic imaging Accuracy Computational modeling Liver Lesions Convolutional neural networks Usability Biomedical imaging

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Multiple Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Multiple Redundant Weighted Clustered Scheme with Dynamic We...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Grace Khayat Constandinos X Mavromoustakis Jordi Mongay Batalla Andreas Pitsillides Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Warsaw University of Technology Warsaw Poland Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor)

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay.

关键词： Measurement Conferences Computational modeling Redundancy Clustering algorithms Autonomous aerial vehicles Routing Routing protocols Delays Vehicle dynamics

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Profit aware Resource Allocation in Fog Computing: A Stackelberg Game Approach

Profit aware Resource Allocation in Fog Computing: A Stackel...

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2023 IEEE International Conference on computer, Information, and Telecommunication Systems, CITS 2023

作者： Doad, Akshita Gupta, Nitin Obaidat, Mohammad S. Jadon, Kuldeep Singh Rawat, Piyush Hsiao, Kuie-Fang National Institute of Technology Department of Computer Science and Engineering HP Hamirpur India Distinguished Professor at the King Abdullah Ii School of Information Technology The University of Jordan Amman11942 Jordan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The Amity University UP Noida201301 India University of Texas-Permain Basin OdessaTX United States

ISBN: (纸本)9798350336092

Recently, Internet of Things (IoT) based smart systems have led to more latency-sensitive and bandwidth hungry IoT applications. Fog computing as an extension of Cloud computing fulfills those requirements more effectively. However, a key challenge for the fog computing is multiple resources allocation between heterogeneous Data Service Operators (DSOs) and End Users (EUs). The DSOs want to increase their revenues, however, due to lack of efficient resource allocation mechanisms, they often end up compromising Quality of Service (QoS) and violating Service Level Agreements (SLAs). It is very important for them to make a balance among user's expectations, expenses of providers and penalties for not providing services within the deadline. Hence, a profit-aware resource allocation policy using Stackelberg game is proposed in the work where DSO acts as leaders and EU as followers. The DSOs being the leaders, set the prices first, send it to the followers, and then the followers can compute their best demand for resources accordingly. Next, Stackelberg equilibrium for each type of resource is obtained to find the best resource demand strategy for an EU. The simulation results demonstrate the superiority of the proposed algorithm. © 2023 IEEE.

关键词： Resource allocation

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