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7th International Conference on Advanced Communication Technologies and Networking, CommNet 2024

作者： Ouaddi, Charaf Benaddi, Lamya Naimi, Lahbib Bouziane, El Mahi Jakimi, Abdeslam Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Sciences and Technologies Errachidia Morocco

ISBN: (纸本)9798350367027

The development of chatbots utilizing artificial intelligence (AI) techniques represents a significant advancement in Natural Language Processing (NLP). Numerous studies employ deep learning and NLP methodologies to construct sophisticated chatbot systems. Additionally, developers and companies often utilize APIs provided by intent recognition services like Dialogflow and Amazon Lex to easily create chatbots using graphical forms, which enhance chatbot functionality. However, these APIs have limitations, such as potential dependency on specific NLP service providers and associated high costs. To address these limitations, the proposed work addresses critical gaps in chatbot development tools by constructing a Domain-Specific Language (DSL) for chatbot development. This DSL aims to simplify the chatbot development process and reduce costs. Specifically, the paper introduces a graphical DSL designed to accelerate chatbot development. We use code generation templates to easily generate the source code for chatbots of the Rasa framework, simplifying the development process and reducing the time spent on manual coding. © 2024 IEEE.

关键词： Bot (Internet)

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Use Cases and Scenarios engineering in Smart software Application Development Services 7

Use Cases and Scenarios Engineering in Smart Software Applic...

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7th International Conference on Advanced Communication Technologies and Networking, CommNet 2024

作者： Bouziane, El Mahi Naimi, Lahbib Ouaddi, Charaf Benaddi, Lamya Jakimi, Abdeslam Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Sciences and Technologies Errachidia Morocco

ISBN: (纸本)9798350367027

Unified Modeling Language (UML) is a versatile tool for specifying, visualizing, and documenting software systems through diagrams. In the early stages of development, addressing design issues is critical to improving software quality and reducing costs. Use case modeling and UML scenario engineering are key techniques in requirements elicitation and specification development. This paper presents best practices for applying these techniques, highlighting their role in constructing accurate sequence diagrams and integrating formal specifications with user interface prototyping. Additionally, it explores extending scenarios to manage complex requirements like time and security constraints and offers a framework for visualizing business interactions in B2B environments to improve communication among stakeholders. © 2024 IEEE.

关键词： Requirements engineering

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Code Generation Templates for Accelerating Chatbot Development in Smart Tourism 7

Code Generation Templates for Accelerating Chatbot Developme...

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7th International Conference on Advanced Communication Technologies and Networking, CommNet 2024

作者： Benaddi, Lamya Ouaddi, Charaf Souha, Adnane Jakimi, Abdeslam Ouchao, Brahim Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Sciences and Technologies Errachidia Morocco

ISBN: (纸本)9798350367027

The rapid advancement of Artificial Intelligence (AI) and Natural Language Processing (NLP) has positioned chatbots as essential tools across various industries, particularly in the tourism sector. These agents are computer programs designed to interact with users naturally. They can access services at any time, such as booking hotels, getting information about local attractions, or managing their travel itineraries. These chatbots enhance the customer experience by providing quick responses 24/7. However, developing chatbots tailored to specific tourism needs can be a time-consuming and complex process due to the use of a wide range of platforms like Dialogflow and *** providing NLP services, which can often be locked and require high costs for access. This paper proposes a solution using code generation templates and domain-specific language (DSL) that accelerates the development of chatbots in smart tourism. With this approach, both developers and non-Technical users can easily create chatbots, significantly reducing the need for manual coding efforts. © 2024 IEEE.

关键词： Chatbots

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Multi Agent Path Finding Under Obstacle Uncertainty 33

Multi Agent Path Finding Under Obstacle Uncertainty

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33rd International Conference on Automated Planning and Scheduling, ICAPS 2023

作者： Shofer, Bar Shani, Guy Stern, Roni Software and Information Systems Engineering Ben Gurion University Israel

ISBN: (纸本)1577358813

In multi-agent path finding (MAPF), agents must move from their current positions to their target positions without colliding. Prior work on MAPF commonly assumed perfect knowledge of the environment. We consider a MAPF setting where this is not the case, and the planner does not know a-priori whether some positions are blocked or not. To sense whether such a position is traversable, an agent must move close to it and adapt its behavior accordingly. In this work we focus on solving this type of MAPF problem, for cases where planning is centralized but cannot be done during execution. In this setting, a solution can be formulated as a plan tree for each agent, branching on the observations. We propose algorithms for finding such plans trees for two modes of executions: centralized, where the agents share information concerning observed obstacles during execution, a decentralized, where such communication is not allowed. The proposed algorithms are complete and can be configured to optimize solution cost, measured for either the best case or the worst case. We implemented these algorithms and provide experimental results demonstrating how our approach scales with respect to the number of agents and the number of positions we are uncertain about. The results show that our algorithms can solve non-trivial problems, but also highlight that this type of MAPF problems is significantly harder than classical MAPF. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Multi agent systems

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Leader-Following Consensus of Multi-Agent systems via Fully Distributed Event-Based Control

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 640-645页

作者： GENG Zongsheng ZHAO Dongdong ZHOU Xingwen YAN Lei YAN Shi School of Information Science and Engineering Lanzhou UniversityLanzhou730000China Engineering Research Center of Open-Source Software and Real-Time Systems of Ministry of Education Lanzhou UniversityLanzhou730000China

This paper aims to study the leader-following consensus of linear multi-agent systems on undirected ***,we construct an adaptive event-based protocol that can be implemented in a fully distributed way by using only local relative *** protocol is also resource-friendly as it will be updated only when the agent violates the designed event-triggering function.A sufficient condition is proposed for the leader-following consensus of linear multi-agent systems based on the Lyapunov approach,and the Zeno-behavior is ***,two numerical examples are provided to illustrate the effectiveness of the theoretical results.

关键词： consensus multi-agent systems event-based control adaptive control fully distributed protocol

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HistoDX: Revolutionizing Breast Cancer Diagnosis Through Advanced Imaging Techniques

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IEEE Access 2025年 13卷 94416-94436页

作者： Arshad, Wishal Masood, Tehreem Shahzad, H.M. Ahmed, Hassan A. Ahmed, Syed Hamza Khushi, Hafiz Muhammad Tayyab University of Central Punjab Faculty of Software Engineering and Information Technology Lahore54000 Pakistan Superior University Faculty of Computer Science and Information Technology Lahore54000 Pakistan Superior University Department of Software Engineering Lahore54000 Pakistan Cleveland State University Monte Ahuja College of Business Department of Information Systems ClevelandOH44114 United States

Breast cancer is the second leading cause of mortality among women worldwide, highlighting the need for efficient histopathology-based screening methods for early diagnosis. This study introduces HistoDX, a deep learning framework to classify Invasive Ductal Carcinoma (IDC) using 277,524 histopathology image patches ( 50 x 50 pixels) from Paul Mooney’s IDC dataset on Kaggle, comprising No Cancer and IDC(+) classes. HistoDX employs a preprocessing pipeline with normalization, data augmentation, and class balancing via oversampling and weighted loss to address the class imbalance. A customized convolutional neural network, built on EfficientNetV2-B3 with additional layers, achieves 97% accuracy and a 0.91 ROC-AUC score on the test set. Validation on BreakHis (97% accuracy) and BACH (90% accuracy) datasets confirm generalizability, though detecting under sampled IDC(+) cases remains challenging. Low training and test losses underscore reliability. HistoDX empowers pathologists by enhancing diagnostic efficiency and minimizing subjectivity through effective class imbalance mitigation. Its robust performance across diverse datasets like BreakHis and BACH suggests readiness for clinical integration. Future research into advanced augmentation techniques, ensemble models, and whole-slide image analysis could further optimize accuracy, sensitivity, and scalability, paving the way for broader adoption in precision oncology. © 2013 IEEE.

关键词： Diseases

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Bidirectional attentional mechanism for Arabic chatbot

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International Journal of information Technology (Singapore) 2024年第5期16卷 3109-3120页

作者： Youness, Farida Elshenawy, Ayman Makour, Mohamed Ashraf Systems and Computer Engineering Department Faculty of Engineering Al-Azhar University Cairo Egypt Software Engineering and Information Technology Department Faculty of Engineering and Technology Egyptian Chinees University Cairo Egypt

A chatbot is an intelligent agent that developed based on Natural language processing (NLP) to interact with people in a natural language. The development of multiple deep NLP models has allowed for the creation of a vector representation of words and sentences that captures meaning in context. In this paper, a generative Arabic chatbot is trained with the Sequence to Sequence (Seq2Seq) model based on encoder-decoder architecture. It utilizes both the bi-directional encoder types of Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM). The chatbot was trained using preprocessed dataset of 12 k conversations that were translated from English to Arabic. An attention layer was provided to the RNNs to focus on the important data between the input and output sequences. The obtained results showed that the proposed chatbot performed well with long sentences and elicited positive responses. In addition to that BiLSTM with attention performs better than BiGRU without attention. To assess the model, the Bilingual Evaluation Understudy (BLEU) Score is employed. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Arabic chatbot Attention mechanism Deep learning RNN

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Impact of Artificial Intelligence on Decision-Making in information systems 5

Impact of Artificial Intelligence on Decision-Making in Info...

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5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Rajasinghe, Rwmr Dharani Faculty of Computing Nsbm Green University Dept. of Software Engineering & Information Systems Homagama Sri Lanka

ISBN: (纸本)9798331530983

The study examines how artificial intelligence (AI) affects information systems (IS) decision-making, emphasizing how AI improves precision, speed, and flexibility in a range of industries. AI presents potential and problems, including ethical, legal, and societal ramifications, as it revolutionizes organizational decision-making. In order to demonstrate AI's function in intricate IS systems, this paper examines a variety of AI strategies used in decision-making, assesses their efficacy using accepted metrics, and examines real-world case studies. Key findings address issues including data bias, lack of transparency, and job displacement while highlighting the advantages of AI in processing massive information and producing useful insights. The recommendations highlight the necessity of worker reskilling, sector-specific adaptability, explainable AI (XAI) models, and regulatory frameworks. In order to facilitate sustainable AI integration in IS for improved organizational and social results, this research emphasizes the significance of striking a balance between AI-driven innovation and ethical issues. © 2025 IEEE.

关键词： Risk perception

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A Decision Support System for Enhancing Transportation Services Using Aspect-Based Sentiment Analysis

A Decision Support System for Enhancing Transportation Servi...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Benaddi, Lamya Ouaddi, Charaf Naimi, Lahbib Souha, Adnane Jakimi, Abdeslam Ouchao, Brahim Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Science and Technology Errachidia Department of Computer Sciences Morocco

ISBN: (纸本)9798350369106

This paper proposes an innovative decision support system based on sentiment analysis, specifically designed for the transportation sector. The system employs an aspect-based sentiment analysis approach, which accurately identifies and classifies customer opinions on key transportation service aspects such as comfort, driver behavior, punctuality, and vehicle condition. By integrating the BERT model, known for its advanced natural language processing capabilities, our system provides an in-depth and reliable analysis of customer sentiments. This analysis enables managers and decision-makers to better understand the strengths and weaknesses of the provided transportation services and to precisely target areas that require improvement. By offering actionable insights, our approach aims to enhance the user experience, improve service quality, and increase overall customer satisfaction. © 2024 IEEE.

关键词： Customer satisfaction

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A Metamodel for a DSL to Design Decision Support systems in Smart Tourism

A Metamodel for a DSL to Design Decision Support Systems in ...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ouaddi, Charaf Benaddi, Lamya Souha, Adnane Naimi, Lahbib Bouziane, El Mahi Jakimi, Abdeslam Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Science and Technology Errachidia Department of Computer Sciences Morocco

ISBN: (纸本)9798350369106

The development of Decision Support systems (DSS) for several companies operating in sectors such as tourism, healthcare, or others, presents significant challenges due to the nature of their multi-component architecture. A typical DSS consists of a data component, a model component incorporating machine learning and deep learning techniques, and a user interface component, each one requires diverse technologies. This complexity increases development time and effort, hindering the efficient design of DSS tailored to specific domains like tourism, where real-time decision-making is essential. One promising approach to overcome these challenges is the use of Domain-Specific Languages (DSLs). DSLs allow developers to model and generate code more efficiently by providing high-level abstractions suited to the domain. By leveraging DSLs, it is possible to simplify the design process and automate the generation of code or parts of the DSS, thereby reducing the overall complexity and time required for development. This paper proposes a metamodel for designing DSS, specifically for the Smart Tourism sector. The metamodel serves as a foundation for the creation of DSL. The goal is to provide a solution to facilitate the development of DSS for the demands of tourism. The paper outlines the key concepts, approach, and results, presenting the first element of the proposed DSL which is the metamodel capturing the essential components and relationships for DSS in Smart Tourism. © 2024 IEEE.

关键词： Digital subscriber lines

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