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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Sumanto Sumarna Nurdin, Hafis Asra, Taufik Sobari, Irwan Agus Kuswanto, Herman Chaidir, Indra Akil, Ibnu Handono, Felix Wuryo Universitas Bina Sarana Informatika Informatics Faculty of Engineering and Informatics Jakarta Indonesia Universitas Nusa Mandiri Information System Faculty of Engineering and Informatics Jakarta Indonesia Universitas Bina Sarana Informatika Software Engineering Faculty of Engineering and Informatics Jakarta Indonesia Universitas Nusa Mandiri Universitas Bina Sarana Informatika Information System Faculty of Engineering and Informatics Indonesia Universitas Nusa Mandiri Universitas Bina Sarana Informatika Computer Engineering Faculty of Engineering and Informatics Indonesia

ISBN: (纸本)9798331528799

Supplier selection is a critical component of Supply Chain Management (SCM), as suppliers provide raw materials or services essential for supporting a company's operations. Traditional supplier selection methods often rely on subjective assessments to determine the weighting of criteria, which can lead to biases and suboptimal decision making. To address this issue, this study combines the Logarithmic Percentage Change of Weight (LOPCOW) method with the Simple Additive Weighting (SAW) method to enhance objectivity in the supplier selection process. The LOPCOW method is used to assign criterion weights objectively based on logarithmic percentage changes, which helps minimize subjectivity, These weights are then applied using the SAW method to evaluate and rank suppliers. The results of the study show that this combined approach is more reliable for selecting suppliers objectively and accurately. The study suggests integrating other Multi-Criteria Decision-Making (MCDM) methods to further strengthen the results while recommending the inclusion of real-time data analytics to improve the model's adaptability to dynamic market conditions. The LOPCOW-SAW approach can be applied across various industries for more effective and efficient SCM supplier selection. © 2024 IEEE.

关键词： Supply chain management

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Identifying and Documenting Best Practices in Digital Transformation 28

Identifying and Documenting Best Practices in Digital Transf...

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28th European Conference on Pattern Languages of Programs, EuroPLoP 2023

作者： Momand, Mohammad Yusuf Vranic, Valentino Institute of Informatics Information System and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9798400700408

Digital transformation allows organizations to maintain sustainable development and address ongoing challenges. The current digital transformation and advanced technology mega-trend significantly impact society and organizations, making digital technology crucial for public and private organizations, universities, and daily life. Despite the rising demand, there is often a lack of standard policies governing the use of digital technology. Practical experience and literature reveal key challenges in transitioning from traditional to digital systems, including limited public awareness, mindset, ICT skills, government support, and collaboration between organizations and software engineering societies. Governments must establish digital transformation policies and offer software development guidelines for public organizations to digitalize their systems. Additionally, they should provide or support research projects funded by governmental and nongovernmental organizations to identify infrastructure and regulatory issues within Afghanistan’s digital transformation context. This study documents six organizational patterns observed during the transformation of traditional systems into digital systems, illustrating their sequence and explaining the development of a pattern language from these patterns. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： software design

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Lockstep Vs Microarchitecture: A Comparison 37

Lockstep Vs Microarchitecture: A Comparison

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37th IEEE International System-on-Chip Conference, SOCC 2024

作者： Mach, Jan Kohutka, Lukas Cicak, Pavel Slovak University of Technology Institute of Computer Engineering and Applied Informatics Bratislava842 16 Slovakia Slovak University of Technology Institute of Informatics Information Systems and Software Engineering Bratislava842 16 Slovakia

ISBN: (纸本)9798350377569

Safety/mission-critical applications require high dependability of the control systems. Their state-of-the-art protection approach is a system-level lockstep. This paper compares the system-level dual and triple lockstep technique to the microarchitecture-level protection of the Hardisc RISC-V core. For a fair comparison, each system is based on the same core(s) and integrates protection against bit-flips in memory and transient faults in the bus. We propose a fault injection methodology, combining pre-synthesis simulation with synthesis data to analyse the vulnerability of a system to faults. The fault injection campaigns show that the Hardisc can withstand fault rates orders of magnitude higher than the dual-core lockstep system while preserving the same area and power consumption. It comes with a 5% frequency penalty. We have shown that system failures are more frequent once the fault rate reaches an application-specific threshold (one fault in 100 clock cycles). © 2024 IEEE.

关键词： Failure rate

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Outsourced Privacy-Preserving kNN Classifier Model Based on Multi-Key Homomorphic Encryption

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Intelligent Automation & Soft Computing 2023年第8期37卷 1421-1436页

作者： Chen Wang Jian Xu Jiarun Li Yan Dong Nitin Naik Software College Northeastern UniversityShenyang110169China School of Informatics and Digital Engineering Aston UniversityBirminghamB152TTUK

Outsourcing the k-Nearest Neighbor(kNN)classifier to the cloud is useful,yet it will lead to serious privacy leakage due to sensitive outsourced data and *** this paper,we design,implement and evaluate a new system employing an outsourced privacy-preserving kNN Classifier Model based on Multi-Key Homomorphic Encryption(kNNCM-MKHE).We firstly propose a security protocol based on Multi-key Brakerski-Gentry-Vaikuntanathan(BGV)for collaborative evaluation of the kNN classifier provided by multiple model *** the operations of kNN and extract basic operations,such as addition,multiplication,and *** supports the computation of encrypted data with different public *** the same time,we further design a new scheme that outsources evaluation works to a third-party evaluator who should not have access to the models and *** the evaluation process,each model owner encrypts the model and uploads the encrypted models to the *** receiving encrypted the kNN classifier and the user’s inputs,the evaluator calculated the aggregated *** evaluator will perform a secure computing protocol to aggregate the number of each class ***,it sends the class labels with their associated counts to the *** model owner and user encrypt the result *** information will be disclosed to the *** experimental results show that our new system can securely allow multiple model owners to delegate the evaluation of kNN classifier.

关键词： Outsourced privacy-preserving multi-key HE machine learning kNN

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A DSL-based Approach for Code Generation and Navigation Process Management in a Single Page Application 14

A DSL-based Approach for Code Generation and Navigation Proc...

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14th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 13th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2023

作者： Naimi, Lahbib Abdelmalek, Hamza Jakimi, Abdeslam Software Engineering and Information Systems Engineering Team Department of Informatics Faculty of Sciences Techniques of Errachidia University of Moulay Ismail Errachidia52000 Morocco

Single page applications (SPAs) are web applications that offer a fast and responsive user experience, but also pose some challenges in terms of navigation process management and platform compatibility. In this paper, we propose a DSL-based approach for code generation and management of SPA navigation process, based on the visual vocabulary proposed by Garrett. We use a Domain-Specific Language (DSL) to describe the elements of the SPA, such as pages, connectors, and transitions, in a concise and abstract way. We also propose a metamodel for Garrett vocabulary, which defines the concepts and relationships of the DSL. Then, we apply a Model-Driven engineering (MDE) technique to transform the DSL specification into a platform-specific project architecture and basic code for an SPA. We present a case study of using our DSL to generate an Angular SPA and evaluate the benefits of our approach in terms of productivity, maintainability, and reusability. © 2024 Elsevier B.V.. All rights reserved.

关键词： Reusability

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Enhancing Intent Detection Through ChatGPT-Driven Data Augmentation 5th

Enhancing Intent Detection Through ChatGPT-Driven Data Augme...

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5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Tesfagergish, Senait Gebremichael Damasevicius, Robertas Kapociute-Dzikiene, Jurgita Department of Software Engineering Kaunas University of Technology Kaunas Lithuania Department of Applied Informatics Vytautas Magnus University Kaunas Lithuania

ISBN: (纸本)9789819771776

This study investigates the improvement of intent detection tasks, focusing on the Facebook Multilingual Task Oriented Dataset, which encompasses 12 classes, including specific intents like weather and alarms. To address the scarcity of datasets in the Amharic language for intent detection, we first translated the English dataset into Amharic using Google Translator. Additionally, we expanded the dataset to include Lithuanian, German, French, and Czech languages. Next, we balance the dataset through data augmentation using ChatGPT, particularly targeting the four least-covered classes by adding 50 sentences to each. For text vectorization, the language-agnostic BERT sentence embedding model was used for its multilingual capabilities and Amharic language support. The classification was based on Cosine similarity, incorporating a majority voting mechanism from the most similar training instances. We conducted multilingual experiments to evaluate the performance of intent detection across various languages, both before and after data augmentation. Our findings highlight the effectiveness of using ChatGPT for data augmentation in intent detection tasks across all investigated languages, particularly in enhancing underrepresented languages and specific intents. We achieved improvement in intent detection performance for minority classes. This shows the benefit of using ChatGPT with imbalanced datasets for multilingual tasks and applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Translation (languages)

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Deep Feature Extraction of Pap Smear Images Based on Convolutional Neural Network and Vision Transformer for Cervical Cancer Classification

Deep Feature Extraction of Pap Smear Images Based on Convolu...

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2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

作者： Sholik, Mohammad Fatichah, Chastine Amaliah, Bilqis Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Software Engineering Universitas Telkom Surabaya Indonesia

ISBN: (纸本)9798350353464

Cervical cancer is a malignant disease that women commonly experience. This cancer can be prevented if screening is carried out early using the pap smear method. The pap smear technique yields a subjective diagnosis. An appropriate decision-making method is needed to overcome this obstacle, such as using a computer-based diagnosis method and applying machine learning. We apply a combination of deep feature extraction using transfer learning from convolutional neural network models and vision transformers to obtain local and global features. Local and global features can represent an image's more comprehensive variety of features. The combined features are then reduced using two steps, principal component analysis and linear discriminant analysis, to obtain a representation of the essential features of the data. The reduced features are then analyzed using several classifiers, including SVM, K-NN, MLP, and LR. The proposed framework was evaluated on three publicly accessible datasets, namely Herlev, Mendeley LBC, and SIPaKMeD, achieving classification accuracies of 97.83% (SVM, K-NN, MLP, and LR), 100% (SVM, K- NN, MLP, and LR), and 98.52% (SVM, K-NN, and LR) respectively. ©2024 IEEE.

关键词： Cervical Cancer Classification Deep Feature Extraction Feature Reduction

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An experimental study on fire characteristics of urban complex underground space based on BIM

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1403-1414页

作者： Jinrong Cui Hao Mei Haosen Sun Ye Jingqi Wei Hu Yong Xu College of Mathematics and Informatics(College of Software Engineering) South China Agricultural UniversityGuangzhouChina The University of Manchester ManchesterUK Harbin Institute of Technology(Shenzhen) ShenzhenChina

Compared with the space on the ground,if there is a fire in the urban complex underground space,the loss will be greatly *** addition,the complex underground space is usually connected with other large space areas and densely *** a fire occurs in the complex underground space,it will cause huge property losses and *** order to reduce the risk of fire,it is necessary to deeply understand the development rules and characteristics of fire in the complex underground space of the *** article has mainly carried on the following work:(I)A particularly complex model of the multi‐storey subway station was *** this basis,three groups of comparative experiments were conducted to study the effects of fire power,fire location and smoke control system on fire development,and the conclusion that fire location is the most important factor for fire development was obtained;(II)In order to explore the entire space fire and the local space fire,CFD(Computational Fluid Dynamics)is used to build a large‐size fire model and a small‐size fire model respectively;(III)Multiple detector data as temperature slices were built,and it is expected to make full use of the simulation data to deduce the important index of fire location in the early stage of *** of the works in this paper will provide reference experimental data for the prevention and firefighting of a sudden fire in the complex underground space.

关键词： fire simulation underground multi‐storey subway station urban complex underground space

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Artificial Intelligence Chatbots and Social Robots in Education: FEPER Framework for Efficiency, Pedagogical and Ethical Requirements 15

Artificial Intelligence Chatbots and Social Robots in Educat...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Virvou, Maria Tsihrintzis, George A. University of Piraeus Software Engineering Laboratory Department of Informatics Piraeus Greece Machine Learning Image Processing and Multimedia Applications Laboratory University of Piraeus Department of Informatics Piraeus Greece

ISBN: (纸本)9798350368833

Artificial Intelligence (AI) chatbots and social robots, when incorporated into educational settings, have the potential to significantly transform the learning experience, particularly by providing more personalised, one-on-one attention to students. However, deploying such technology in classrooms also presents challenges. These include unresolved issues related to human-AI interaction, pedagogy and theories, human oversight, data privacy, transparency, accuracy and trust. This paper explores the development of a comprehensive framework aimed at enhancing the efficiency, pedagogical effectiveness, and ethical use of AI-driven educational tools, focusing on social robots and chatbots. The framework addresses important factors such as interaction quality, requirements engineering strategies, and the alignment of AI functionalities with educational goals. It also examines ethical concerns, including data security, user transparency, and trustworthiness. By reviewing recent literature on social robots and chatbots and incorporating emerging ethical considerations alongside long-standing educational objectives, this research aims at establishing a holistic framework, FEPER, of best practices and requirements. The findings offer valuable insights for educators, policymakers, and developers aiming to create more dynamic, personalised, and ethical educational environments using AI technology. © 2024 IEEE.

关键词： Adversarial machine learning

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MTN: A Multi-Scale Transformer Network for Different Resolution Remote Sensing Images Change Detection

MTN: A Multi-Scale Transformer Network for Different Resolut...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Zhu, Hongming Wu, Guodong Wang, Zeju Xu, Manxin Liu, Qin Liu, Sicong Du, Bowen School of Software Engineering China College of Surveying and Geo-Informatics Tongji University Shanghai China

ISBN: (纸本)9798350337020

In the field of change detection, detecting changes in images with different resolutions is crucial for both long-term interval scenes and scenarios that require rapid detection. However, existing methods face two main issues. Firstly, they require more stringent prior knowledge. The SPM-based methods require pixel-level class labeling of high-resolution(HR) images, while the approaches based on image super-resolution require HR images corresponding to low-resolutionr(LR) images. Such prior knowledge is either costly for labeling or difficult to meet in realistic scenarios. The second is that redundant error accumulation affects detection accuracy. Whether in traditional sub-pixel mapping(SPM) methods or deep learning methods based on image super-resolution, the final detection results are obtained after generating HR images from LR images. The redundant error produced in this step will be accumulated and affect the final detection results. Although the unsupervised methods do not have this problem, the detection accuracy is not as good as that of the supervised. To address these issues, we propose a multi-scale Transformer network(MTN). This model first uses a multi-scale feature extractor(MFE) to extract multi-scale features and perform scale matching at the feature level. Then, the Transformer is used to extract long-range relationships of ground objects on the multi-scale features to enhance the features. Finally, the multi-scale features are fused, and a classifier composed of a convolutional network is used to obtain binary change detection results. In addition, we consider that the edges of objects may be affected during the scale matching process, and introduce a CEBoundary Loss to better detect object edges. The results on the LEVIR and Google datasets demonstrate the effectiveness of our proposed method. The source code of MTN is available at https://***/Gavin-debug/MultiResolutionCD. © 2023 IEEE.

关键词： Change detection(CD) different resolution remote sensing images scale-matching

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