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Decision Making: Applications in Management and engineering 2025年第1期8卷 401-418页

作者： Al-Safarini, Maram Y. Baashirah, Rania A. Computer Science Department Zarqa University Jordan Software Engineering Department University of Business & Technology Saudi Arabia

Artificial Intelligence (AI) is transforming numerous domains, including bioinformatics and information extraction systems, by advancing data processing capabilities, enhancing precision, and facilitating automation. The primary aim of this research is to examine the function of AI within the realms of bioinformatics and information extraction through a combination of quantitative and qualitative approaches. The quantitative component involved a sample of 152 participants, recognised as experts in bioinformatics and data science. The survey findings underscore the prevalent integration of AI in bioinformatics, particularly through the utilisation of reinforcement learning, neural networks, and natural language processing (NLP). Furthermore, AI substantially improves the analysis of biological data;however, it encounters challenges such as limited model interpretability and the lack of data standardisation. Notwithstanding these obstacles, AI-driven innovations in disease prognosis, personalised healthcare, and pharmaceutical development are anticipated to shape the future trajectory of bioinformatics. The qualitative findings, derived through thematic analysis encompassing core themes and sub-themes, reveal that AI significantly contributes to accelerating and refining information extraction processes. Technologies such as machine learning, NLP, and neural networks are instrumental in enhancing data processing efficiency. Nonetheless, issues such as inadequate data quality, elevated computational expenses, and the intricacy of AI models remain persistent. Looking ahead, AI is projected to integrate more effectively with big data infrastructures, enable real-time information extraction, and deliver increasingly tailored solutions. The study concludes with several policy recommendations to guide future implementation strategies. © 2025 Regional Association for Security and crisis management. All rights reserved.

关键词： Data integration

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A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1412-1434页

作者： Shoaib Hassan Qianmu Li Khursheed Aurangzeb Affan Yasin Javed Ali Khan Muhammad Shahid Anwar School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingJiangsuChina Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Software Northwestern Polytechnical UniversityXianShaanxiChina Department of Computer Science School of PhysicsEngineering&Computer ScienceUniversity of HertfordshireHatfieldUK Department of AI and Software Gachon University Seongnam-siSeongnamSouth Korea

Over the past few years,the application and usage of Machine Learning(ML)techniques have increased exponentially due to continuously increasing the size of data and computing *** the popularity of ML techniques,only a few research studies have focused on the application of ML especially supervised learning techniques in Requirement engineering(RE)activities to solve the problems that occur in RE *** authors focus on the systematic mapping of past work to investigate those studies that focused on the application of supervised learning techniques in RE activities between the period of 2002–*** authors aim to investigate the research trends,main RE activities,ML algorithms,and data sources that were studied during this ***-five research studies were selected based on our exclusion and inclusion *** results show that the scientific community used 57 *** those algorithms,researchers mostly used the five following ML algorithms in RE activities:Decision Tree,Support Vector Machine,Naïve Bayes,K-nearest neighbour Classifier,and Random *** results show that researchers used these algorithms in eight major RE *** activities are requirements analysis,failure prediction,effort estimation,quality,traceability,business rules identification,content classification,and detection of problems in requirements written in natural *** selected research studies used 32 private and 41 public data *** most popular data sources that were detected in selected studies are the Metric Data Programme from NASA,Predictor Models in software engineering,and iTrust Electronic Health Care System.

关键词： data sources machine learning requirement engineering supervised learning algorithms

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An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for engineering Problems and Its Applications in Breast Cancer Problem

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computer Modeling in engineering & Sciences 2024年第11期141卷 1067-1110页

作者： Feyza AltunbeyÖzbay ErdalÖzbay Farhad Soleimanian Gharehchopogh Department of Software Engineering Firat UniversityElazig23119Turkey Department of Computer Engineering Firat UniversityElazig23119Turkey Department of Computer Engineering Urmia BranchIslamic Azad UniversityUrmia44867-57159Iran

Artificial rabbits optimization(ARO)is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in ***,for solving optimization problems,the ARO algorithm shows slow convergence speed and can fall into local *** overcome these drawbacks,this paper proposes chaotic opposition-based learning ARO(COARO),an improved version of the ARO algorithm that incorporates opposition-based learning(OBL)and chaotic local search(CLS)*** adding OBL to ARO,the convergence speed of the algorithm increases and it explores the search space *** maps in CLS provide rapid convergence by scanning the search space efficiently,since their ergodicity and non-repetitive *** proposed COARO algorithm has been tested using thirty-three distinct benchmark *** outcomes have been compared with the most recent optimization ***,the COARO algorithm’s problem-solving capabilities have been evaluated using six different engineering design problems and compared with various other *** study also introduces a binary variant of the continuous COARO algorithm,named *** performance of BCOARO was evaluated on the breast cancer *** effectiveness of BCOARO has been compared with different feature selection *** proposed BCOARO outperforms alternative algorithms,according to the findings obtained for real applications in terms of accuracy performance,and fitness *** experiments show that the COARO and BCOARO algorithms achieve promising results compared to other metaheuristic algorithms.

关键词： Artificial rabbit optimization binary optimization breast cancer chaotic local search engineering design problem opposition-based learning

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Design and Optimization of Self-Supporting Surfaces with Arch Beams

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IEEE Transactions on Visualization and computer Graphics 2024年 PP卷 1-14页

作者： Wei, Guangshun Ma, Long Zhou, Yuanfeng Wang, Chen Zheng, Jianmin He, Ying School of Software Shandong University China School of Computer Science and Engineering Nanyang Technological University Singapore

The paper presents a new method for constructing self-supporting surfaces using arch beams that are designed to convert their thrust into supporting force, thereby eliminating shear stress and bending moments. Our method allows for the placement of the arch beams on the boundary or within a surface and partitions the surface into multiple self-supporting parts. The use of arch beams enhances stability and durability, adds aesthetic appeal, and allows for greater flexibility in the design process. We develop an iterative algorithm for designing selfsupporting surfaces with arch beams that enables the user to control the shape of the beams and surface through intuitive parameters and specify the desired location of the arch beams. We verify the physical stability of the structure using finite element analysis. Experimental results show that our method can produce visually pleasing self-supporting surfaces that satisfy the equilibrium equation with high accuracy. IEEE

关键词： Surface treatment

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CLIP-Flow:Decoding images encoded in CLIP space

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Computational Visual Media 2024年第6期10卷 1157-1168页

作者： Hao Ma Ming Li Jingyuan Yang Or Patashnik Dani Lischinski Daniel Cohen-Or Hui Huang Visual Computing Research Center College of Computer Science and Software EngineeringShenzhen UniversityShenzhen 518060China Department of Computer Science Tel Aviv UniversityTel Aviv 6997801Israel School of Computer Science and Engineering the Hebrew University of JerusalemJerusalem 91904Israel

This study introduces CLIP-Flow,a novel network for generating images from a given image or *** effectively utilize the rich semantics contained in both modalities,we designed a semantics-guided methodology for image-and text-to-image *** particular,we adopted Contrastive Language-Image Pretraining(CLIP)as an encoder to extract semantics and StyleGAN as a decoder to generate images from such ***,to bridge the embedding space of CLIP and latent space of StyleGAN,real NVP is employed and modified with activation normalization and invertible *** the images and text in CLIP share the same representation space,text prompts can be fed directly into CLIP-Flow to achieve text-to-image *** conducted extensive experiments on several datasets to validate the effectiveness of the proposed image-to-image synthesis *** addition,we tested on the public dataset Multi-Modal CelebA-HQ,for text-to-image *** validated that our approach can generate high-quality text-matching images,and is comparable with state-of-the-art methods,both qualitatively and quantitatively.

关键词： image-to-image text-to-image contrastive language-image pretraining(CLIP) flow StyleGAN

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Modeling contextual goals and detecting context conflicts from BDD-based user stories

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International Journal of computers and Applications 2024年第12期46卷 1057-1068页

作者： Zheng, Liwei Wang, Yan Cui, Zhanqi Computer School Software Engineering Research Center Beijing Information Science and Technology University Beijing China

Behavior-Driven Development (BDD) user stories are widely used in agile methods for capturing user requirements and acceptance criteria due to their simplicity and clarity. However, the concise structure of BDD-based user stories prevents capturing contextual information and connections between them, which help stakeholders understand requirements and uncover potential issues. The contextual goal models (CGMs) can provide explicit relationships between goals and contexts, but manually constructing models is effort-intensive. This paper proposes an automated approach called BUS2C to model contextual goals and detect context conflicts from BDD-based user stories. The aim is to improve requirements analysis by systematically eliciting goals and dependencies. BUS2C approach involves: (1) mapping BDD-based user story elements to CGMs, and (2) merging related models based on similarity. The context conflict detection algorithm checks if contexts associated with different goals are compatible using natural language metrics. We evaluated BUS2C approach through three experiments. First, we showed the effectiveness in merging scattered CGMs with common features. Second, we demonstrated the capability to construct CGMs from BDD-based user stories quickly, assisting modelers. Our merging method also produced models closer to manually built ones versus without merging. Third, we validated that the context conflict detection can successfully identify inconsistencies in small datasets, enhancing requirements quality. Further validation on larger datasets is needed. In conclusion, this work contributes automated techniques to systematically model and analyze contextual goals from BDD-based user stories. By providing unified goal understanding and detecting issues like conflicts, BUS2C approach aims to improve requirements analysis and support adaptive systems development. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： BDD-based user stories contextual goal model context conflict detection

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Code Re-use Recommendation Based on software Requirements Using Natural Language Processing in Python 13

Code Re-use Recommendation Based on Software Requirements Us...

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13th International Conference on computer Technologies and Development, TechDev 2024

作者： Farooqi, Hareem Butt, Wasi Haider Khan, Obaid Ullah Department of Computer and Software Engineering Islamabad Pakistan TEO International Department of Software Engineering Islamabad Pakistan

ISBN: (纸本)9798331539771

Code reuse is a pivotal practice in software development, promoting efficiency, reducing redundancy, and ensuring higher quality software products. Recommender systems play a crucial role in this process by suggesting relevant code snippets or components based on specific requirements, thus easing the task of code reuse for developers. In this research paper, we present a Python code re-use recommendation system based on software requirements using Natural Language Processing (NLP). By employing the BERT model, we assess the similarity between software requirements in the e-commerce domain. The resulting software is then pre-processed and evaluated using the CodeBERT model to determine code similarity. Our findings show that similar requirements can indeed produce similar software, promoting efficient code reuse. This system can significantly benefit requirement engineers and developers by enabling the re-utilization of existing code within the same domain, demonstrating the broader applicability of our approach. © 2024 IEEE.

关键词： software quality

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Real-time all-frequency global llumination with radiance caching

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Computational Visual Media 2024年第5期10卷 923-936页

作者： Youxin Xing Gaole Pan Xiang Chen Ji Wu Lu Wang Beibei Wang School of Software Shandong UniversityJinan 250101China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China

Global illumination(GI)plays a crucial role in rendering realistic results for virtual exhibitions,such as virtual car *** scenarios usually include all-frequency bidirectional reflectance distribution functions(BRDFs),although their geometries and light configurations may be *** allfrequency BRDFs in real time remains challenging due to the complex light *** approaches,including precomputed radiance transfer,light probes,and the most recent path-tracing-based approaches(ReSTIR PT),cannot satisfy both quality and performance requirements ***,we propose a practical hybrid global illumination approach that combines ray tracing and cached GI by caching the incoming radiance with *** approach can produce results close to those of ofline renderers at the cost of only approximately 17 ms at runtime and is robust over all-frequency *** approach is designed for applications involving static lighting and geometries,such as virtual exhibitions.

关键词： real-time global illumination all-frequency BRDFs Haar wavelets radiance caching

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Integrating Ontology-Based Approaches with Deep Learning Models for Fine-Grained Sentiment Analysis

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computers, Materials & Continua 2024年第10期81卷 1855-1877页

作者： Longgang Zhao Seok-Won Lee The Knowledge-Intensive Software Engineering(NiSE)Research Group Department of Artificial IntelligenceAjou UniversitySuwon City16499Republic of Korea Department of Software and Computer Engineering Ajou UniversitySuwon City16499Republic of Korea

Although sentiment analysis is pivotal to understanding user preferences,existing models face significant challenges in handling context-dependent sentiments,sarcasm,and nuanced *** study addresses these challenges by integrating ontology-based methods with deep learning models,thereby enhancing sentiment analysis accuracy in complex domains such as film reviews and restaurant *** framework comprises explicit topic recognition,followed by implicit topic identification to mitigate topic interference in subsequent sentiment *** the context of sentiment analysis,we develop an expanded sentiment lexicon based on domainspecific corpora by leveraging techniques such as word-frequency analysis and word ***,we introduce a sentiment recognition method based on both ontology-derived sentiment features and sentiment *** evaluate the performance of our system using a dataset of 10,500 restaurant reviews,focusing on sentiment classification *** incorporation of specialized lexicons and ontology structures enables the framework to discern subtle sentiment variations and context-specific expressions,thereby improving the overall sentiment-analysis *** results demonstrate that the integration of ontology-based methods and deep learning models significantly improves sentiment analysis accuracy.

关键词： Deep learning ontology fine-grained sentiment analysis online reviews

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MI-BMPI motor imagery brain–mobile phone dataset and performance evaluation of voting ensembles utilizing QPDM

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Neural Computing and Applications 2025年第6期37卷 4679-4696页

作者： Yilmaz, Cagatay Murat Yilmaz, Bahar Hatipoglu Kose, Cemal Department of Software Engineering Karadeniz Technical University Trabzon61080 Turkey Department of Computer Engineering Karadeniz Technical University Trabzon61080 Turkey

EEG-based interfaces are an active research area with great potential. We, therefore, focused on classifying motor imaging (MI) tasks from various problem areas. Because of that, we applied MI patterns to voting ensembles differently and constructed voters. They employ quasi-probabilistic distribution models based on sub-classifiers of different frequency bands and time segments. Much previous work focused on just a few MI tasks for BCIs. To that end, we constructed a new mobile EEG dataset, abbreviated as MI-BMPI, containing two significant gestures for mobile phone interfaces. The research experiments used a consumer market EEG system, the mobile wireless Emotiv EPOC Flex neuroheadset. Experiments were carried out on the BCI Competition IV Dataset 2a and MI-BMPI. On the BCI and BMPI datasets, promising results were obtained in classifying various MI tasks. In conclusion, new solutions were introduced for tougher EEG-based interfaces, which have the potential to classify MI tasks and develop EEG-based interfaces. In addition to the average performance improvements, more stable results were achieved for subject and task variations. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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