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An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

computer Systems science & engineering 2023年第2期44卷 1309-1324页

作者： Junaid Rashid Sumera Kanwal Muhammad Wasif Nisar Jungeun Kim Amir Hussain Department of Computer Science and Engineering Kongju National UniversityCheonan31080Korea Department of Computer Science COMSATS University IslamabadWah CampusIslamabad47040Pakistan Centre of AI and Data Science Edinburgh Napier UniversityEdinburghEH114DYUK

In project management,effective cost estimation is one of the most cru-cial activities to efﬁciently manage resources by predicting the required cost to fulﬁll a given ***,ﬁnding the best estimation results in software devel-opment is ***,accurate estimation of software development efforts is always a concern for many *** this paper,we proposed a novel soft-ware development effort estimation model based both on constructive cost model II(COCOMO II)and the artiﬁcial neural network(ANN).An artiﬁcial neural net-work enhances the COCOMO model,and the value of the baseline effort constant A is calibrated to use it in the proposed model *** state-of-the-art publicly available datasets are used for *** backpropagation feed-forward procedure used a training set by iteratively processing and training a neural *** proposed model is tested on the test *** estimated effort is compared with the actual effort *** results show that the effort estimated by the proposed model is very close to the real effort,thus enhanced the reliability and improving the software effort estimation accuracy.

关键词： Software cost estimation neural network backpropagation forward neural networks software effort estimation artiﬁcial neural network

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Enhancing the blockchain interoperability through federated learning with directed acyclic graph

IET Blockchain

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IET Blockchain 2023年第4期3卷 238-248页

作者： Xia, Feng Kaiye, Li Songze, Wu yan, Xin Faculty of Data Science City University of Macau Avenida Padre Tomás Pereira China School of Computer Science and Communication Engineering Jiangsu Univestity Zhenjiang China

The use of federated learning to achieve blockchain interoperability has become a hot topic in research, because it enables data exchange without revealing any private information. However, the previous work, such as ScaleSFL (Asia-CCS, 2022), that has implemented federated learning for blockchain interoperability, the throughput of the framework still cannot support the practical applications. Therefore, a federated learning framework based on Directed Acyclic Graph (DAG) is proposed which utilizes sharding mechanism to enhance the blockchain interoperability. By constructing a weighted context graph based on data correlation, reasonable sharding of the dataset is achieved, thereby improving the efficiency of blockchain interoperability. The experimental results show that the federated framework reduces global computation in federated learning by 30% compared with other schemes, while increasing blockchain throughput by nearly 40%. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Blockchain

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A Digital Twin and Consensus Empowered Cooperative Control Framework for Platoon-Based Autonomous Driving

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1096-1111页

作者： Jiayu Cao Supeng Leng Kai Xiong Xiaosha Chen School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110China College of Computer Science and Technology and also with College of Data Science Taiyuan University of TechnologyTaiyuan 030024China

Platoon-based autonomous driving is indispensable for traffic automation,but it confronts substantial constraints in rugged terrains with unreliable links and scarce communication *** paper proposes a novel hierarchical Digital Twin(DT)and consensus empowered cooperative control framework for safe driving in harsh ***,leveraging intra-platoon information exchange,one platoon-level DT is constructed on the leader and multiple vehicle-level DTs are distributed among platoon *** leader first makes critical platoon-driving decisions based on the platoon-level ***,considering the impact of unreliable links on the platoon-level DT accuracy and the consequent risk of unsafe decision-making,a distributed consensus scheme is proposed to negotiate critical decisions *** successful negotiation,vehicles proceed to execute critical decisions,relying on their vehicle-level ***,a Space-Air-Ground-Integrated-Network(SAGIN)enabled information exchange is utilized to update the platoon-level DT for subsequent safe decision-making in scenarios with unreliable links,no roadside units,and obstructed ***,based on this framework,an adaptive platooning scheme is designed to minimize total delay and ensure driving *** results indicate that our proposed scheme improves driving safety by 21.1％and reduces total delay by 24.2％in harsh areas compared with existing approaches.

关键词： platoon autonomous driving distributed consensus digital twin space-air-ground integrated network

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Secure UPI: Machine Learning-Driven Fraud Detection System for UPI Transactions 2

Secure UPI: Machine Learning-Driven Fraud Detection System f...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Rani, Rupa Alam, Adnan Javed, Abdul Ajay Kumar Garg Engineering College Ghaziabad Department of Computer Science & Engineering U.P. Ghaziabad India Banasthali Vidyapith Department of Computer Science & Engineering Rajasthan India Abes Institute of Technology Department of Computer Science & Engineering-Data Science U.P. Ghaziabad India

ISBN: (纸本)9798350371055

Secure UPI specializes in developing an advanced fraud detection gadget the usage of the effective XGBoost device getting to know set of rules to create an advanced fraud identity device. XGBoost is a properly-proper alternative for enhancing the precision of fraud detection fashions because of its reputation for dealing with tricky datasets with efficiency and its music record of success throughout multiple industries. In order to extract pertinent records, like transaction quantity, frequency, and place, our approach preprocesses UPI transaction facts. This article makes use of a labelled dataset to train the XGBoost version in order that we may also take gain of its sturdy prediction talents and capacity to handle imbalanced datasets. To help create a system that is less difficult to apprehend and use, feature importance evaluation is used to discover essential symptoms of feasible fraud. After training, the model is covered right into a real-time UPI transaction tracking device, in which it maintains an eye fixed out for any suspicious traits in incoming transactions. In order to lessen the results of fraudulent activity, the system is constructed with 98.2 % accuracy to send out instant notifications and take preventive steps. This challenge allows in improving UPI transaction security and advancing economic era are accomplished through demonstrating the performance of machine learning in fraud detection. © 2024 IEEE.

关键词： Dimensionality Reduction Fraud Detection Imbalanced datasets Machine Learning PCA SMOTE UPI XGBoost

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SMMGCL: A novel multi-level graph contrastive learning framework for integrating spatial multi-omics data

SMMGCL: A novel multi-level graph contrastive learning frame...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Wang, Bo Liu, Wei Luo, Jiawei Chen, Xiangtao Kwoh, Chee Keong Hunan University College of Computer Science and Electronic Engineering China Nanyang Technological University College of Computing and Data Science Singapore

ISBN: (纸本)9798350386226

Recent advances in spatial omics technologies have allowed various omics data to be obtained from a single tissue section. To fully explore the relationships among these different types of omics data, it is urgent to develop more effective methods for spatial multi-omics data integration. In this work, we propose a novel Multi-level Graph Contrastive Learning framework, named SMMGCL, to simultaneously mine complementary information at both spot and graph levels for integrating Spatial Multi-omics data. Specifically, to adaptively fuse multi-omics modalities, we first design a multi-modality autoencoder that integrates spatial locations with spot omic expressions to extract modality-specific embeddings. These embeddings are then fused into a consensus representation using an attention mechanism to capture spot-level cross-omics representations. Next, to explore the complex inter-omic structural information, we connect corresponding spots across different omics adjacency graphs into a heterogeneous graph. We then employ a graph convolutional network (GCN) to extract spatial correlations across the omics, learning a graph-level cross-omics global representation. Finally, SMMGCL aligns feature similarity matrixes between spot-level and graph-level representations with their pseudo-label similarity matrix, ensuring multi-level clustering consistency and leading to more accurate spatial multi-omics integration. Experimental results on simulated and real datasets from across tissues show that SMMGCL consistently outperforms other state-of-the-art methods in spatial multi-omics integration performance. The code for SMMGCL is available for download from the GitHub repository at https://***/cs-wangbo/SMMGCL. © 2024 IEEE.

关键词： Contrastive Learning

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Secure multimedia communication: advanced asymmetric key authentication with grayscale visual cryptography

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Mathematical Biosciences and engineering 2024年第3期21卷 4762-4778页

作者： Liu, Tao Vairagar, Shubhangi Adagale, Sushadevi Karthick, T. Karunya, Catherine Esther Blesswin, A. John Mary, G. Selva Tianjin Sino-German University of Applied Sciences Tianjin300350 China Department of Artificial Intelligence and Data Science Dr. D. Y. Patil Institute of Technology Pimpri Pune411018 India Department of Computer Engineering KJEI's Trinity Academy of Engineering Pune411048 India Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur603203 India Computer Science and Engineering School of Computing SRM Institute of Science and Technology Kattankulathur603203 India Directorate of Learning and Development SRM Institute of Science and Technology Kattankulathur603203 India

The secure authentication of user data is crucial in various sectors, including digital banking, medical applications and e-governance, especially for images. Secure communication protects against data tampering and forgery, thereby bolstering the foundation for informed decision-making, whether managing traffic, enhancing public safety, or monitoring environmental conditions. Conventional visual cryptographic protocols offer solutions, particularly for color images, though they grapple with challenges such as high computational demands and reliance on multiple cover images. Additionally, they often require third-party authorization to verify the image integrity. On the other hand, visual cryptography offers a streamlined approach. It divides images into shares, where each pixel represented uniquely, thus allowing visual decryption without complex computations. The optimized multi-tiered authentication protocol (OMTAP), which is integrated with the visual sharing scheme (VSS), takes secure image sharing to the next level. It reduces share count, prioritizes image fidelity and transmission security, and introduces the self-verification of decrypted image integrity through asymmetric key matrix generators, thus eliminating external validation. Rigorous testing has confirmed OMTAP's robustness and broad applicability, thereby ensuring that decrypted images maintain their quality with a peak signal-to-noise ratio (PSNR) of 40 dB and full integrity at the receiver's end. © 2024 American Institute of Mathematical sciences. All rights reserved.

关键词： Medical applications

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Deep Learning-Based Holistic Speaker Independent Visual Speech Recognition

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第6期4卷 1705-1713页

作者： Nemani, Praneeth Krishna, Ghanta Sai Ramisetty, Nikhil Sai, B Digvijay Sri Kumar, Santosh IIIT Naya Raipur Department of Computer Science and Engineering Raipur493661 India IIIT Naya Raipur Department of Data Science and Artificial Intelligence Raipur493661 India

From a broader perspective, the objective of visual speech recognition (VSR) is to comprehend the speech spoken by an individual using visual deformations. However, some of the significant limitations of existing solutions include the dearth of training data, improper end-to-end deployed solutions, lack of holistic feature representation, and less accuracy. To resolve these limitations, this study proposes a novel, scalable, and robust VSR system that uses the videotape of the user to determine the word which is being spoken. In this regard, a customized 3-D convolutional neural network (3-D CNN) architecture is proposed by extracting the spatio-temporal features and eventually mapping the prediction probabilities of the elements in the corpus. We have created a customized dataset resembling the metadata contained in the MIRACL-VC1 dataset to validate the concept of person-independence. While being robust to a broad spectrum of lighting conditions across multiple devices, our model achieves a training accuracy of 80.2% and a testing accuracy of 77.9% in predicting the word spoken by the user. © 2020 IEEE.

关键词： Speech recognition

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Revisiting 30 years of the Network Time Protocol 24

Revisiting 30 years of the Network Time Protocol

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33rd Companion of the ACM World Wide Web Conference, WWW 2023

作者： Woo, Simon S. Computer Science and Engineering Department Applied Data Science Department Department of Artificial Intelligence Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798400701726

Since the inception of the Internet and WWW, providing the time among multiple nodes on the Internet has been one of the most critical challenges. David Mills is the pioneer to provide time on the Internet, inventing the Network Time Protocol (NTP), and synchronizing the clocks in computer systems. Now, the NTP is predominantly used on the Internet and WWW. In this paper, we revisit the NTP, and present the overview of the NTP. In particular, we highlight the advanced research effort, the SpaceNTP, to synchronize the clocks among assets and entities in space. The SpaceNTP designed for space environments will be the fundamental medium and enabling block to provide the future web services in space. © 2024 Copyright held by the owner/author(s).

关键词： Web services

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Word-of-Mouth Promotion: How to Attract Consistent Consumers as a Promoter for the B2C Model 2

Word-of-Mouth Promotion: How to Attract Consistent Consumers...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Gunavathi, R. Vijayalakshmi, S. Savithri, M. Thamarai Selvi, S.B. Christ University School of Data Science India K.S.Rangasamy College of Technology Computer Science and Engineering India

ISBN: (纸本)9798350384277

The primary goal of this research article is to discover the consumers' behaviour while spending time on the e-commerce platform and to use the consumers who have positive Word-of-Mouth on the products to motivate them as promoters through positive Word of Mouth behaviour. The behavioural factors considered in this study are Relationship value, Trust value, Satisfaction level and Word of Mouth. The trial model includes the consumers who use an e-commerce platform for their online shopping in India. A proper questionnaire with four components was created and used to collect the sample data. Totally 300 responses have been received and analysed with the help of structured equation model and SPSS and AMOS software. The findings suggest that the 'Word of Mouth' technique can be used as a tool to increase the number of consumers in an online platform, particularly e-commerce. We investigated how Relationship Value and Trust Value can be used as key factors to motivate consumers' positive WoM behaviour. This research would be more beneficial to the B2C model. The research has done only for Indian e-commerce portals for survey. There is a scope to do research for the global level e-commerce market. Future study focuses on dynamic attributes for relationship values. This research work will help the researchers who is working on B2C model and consumer behavioural models. This model would be used for any online transactions-based services. As best of the knowledge of the authors' this study is the novel idea to understand the consumers' behaviour for purchasing items through the positive WoM. This work can be adopted for any e-commerce platform. © 2024 IEEE.

关键词： Marketplaces

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Optimizing Supply Chain Operations in the Electronics Industry Using Machine Learning and Integer Linear Programming 3rd

Optimizing Supply Chain Operations in the Electronics Indust...

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3rd International Conference on Advanced Computing and Intelligent Technologies, ICACIT 2023

作者： Padhi, Spandan Marken, Gagandeep Data Science Department of Mathematics Chandigarh University Gharuan India Department of Computer Science Engineering Chandigarh University Gharuan India

ISBN: (纸本)9789819719600

Efficient operations, within the supply chain are vital for the electronics industry. In this study, we focus on optimizing the supply chain network of a hypothetical company ABC Electronics, an entity crafted for the purposes of this research paper. The company faces challenges related to production, inventory management, and transportation logistics. To address these challenges we employ machine learning (ML) and integer linear programming (ILP) techniques. Our primary objectives include enhancing demand predictions through ML, optimizing production schedules and inventory using ILP, and devising strategies for transportation logistics. Our research makes a contribution toward reducing costs and improving efficiency at ABC Electronics enabling them to stay competitive in the electronics market. Furthermore, our findings have implications, for industry standards, sustainability practices, and customer satisfaction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning

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