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Digital Transformation and Society 2025年第2期4卷 128-152页

作者： Omol, Edwin Juma Mburu, Lucy Waruguru Abuonji, Paul Anyango Department of Software Development and Information Systems (SDIS) School of Technology KCA University Nairobi Kenya Chair of Department - Networks and Applied Computing (NAC) School of Technology KCA University Nairobi Kenya KCA University Nairobi Kenya

Purpose: This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business challenges to establishing a comparative analysis framework grounded in Resource Dependence Theory (RDT). Design/methodology/approach: DMAM is based on positivist philosophy and objectivist epistemology, supported by Design Science Research (DSR) and Capability Maturity Model Integration (CMMI). The methodology involves iterative development, from problem identification to creating a practical solution for assessing SMEs' digital maturity and guiding digitalization efforts. Findings: DMAM offers a clear and specific methodology, distinguishing itself by addressing the unique needs of SMEs, particularly resource-dependent ones. The model’s development fills critical gaps in existing literature and provides a practical artifact for SMEs' digitalization. Originality/value: DMAM is original in its focus on the specific needs of resource-dependent SMEs, offering actionable recommendations and addressing shortcomings in existing models. It serves as a foundational framework for SMEs' digital transformation, making a significant contribution to the digital maturity assessment literature. © 2024, Edwin Juma Omol, Lucy Waruguru Mburu and Paul Anyango Abuonji.

关键词： Capability Maturity Model Integration (CMMI) Design Science Research (DSR) Digital Maturity Assessment Model (DMAM) Goal Question Metric (GQM) Proof-of-Concept (POC) & Minimum Viable Product (MVP) Resource Dependence Theory (RDT)

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Discovery of Permian N-MORB in the Garze–Litang Ophiolitic Mélange Belt and Its Implications for the Evolutionary Transition of MOR Mantle

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Journal of Earth Science 2025年

作者： Songtao Yan Lidong Zhu Meng Qin Ailing Ding Qingsong Wu Hu Li Research Center of Applied Geology of China Geological Survey Institute of Sedimentary Geology， Chengdu University of Technology School of Software Engineering， Chengdu University of Information Technology School of Earth and Planetary Sciences， Chengdu University of Technology

The Garze–Litang ophiolitic mélange belt is located at the junction of the Tethyan tectonic domain and the Eurasian Plate. The age， petrogenesis， and tectonic setting of the Garze–Litang Ocean remain controversial， primarily due to the lack of studies on Late Paleozoic ophiolites. This study presents detailed field investigations， as well as petrological， geochemical， Sr-Nd isotopic， and U-Pb geochronological analyses of the newly identified Permian Zhuqing ophiolite. The Zhuqing ophiolite consists of olivine pyroxenite， diabase， basalt， breccia lava， tuff， and siliceous rocks， forming lens- or clast-shaped blocks within a strongly schistose silty slate matrix. Zircon U-Pb dating indicates basalt formed at 266 ± 2 Ma， during the Middle Permian. The volcanic rocks belong to the low-K tholeiitic series， exhibiting typical N-MORB characteristics with LREE depletion， no negative Nb， Ta， or Eu anomalies， and positive εNd（t） values. Geochemical analysis suggests a depleted spinel lherzolite mantle source， with 8%–15% partial melting and fractional crystallization of olivine and clinopyroxene， without contamination from crustal or subducted material. Based on these findings and previous data， a multi-stage evolutionary model for the Garze–Litang Ocean is proposed. During the Carboniferous initial expansion， the mantle source exhibited E-MORB characteristics， influenced by ridge expansion， mantle plume， and Paleo-Tethys Ocean subduction. In the Permian to Early Triassic， the mantle source showed N-MORB characteristics. During the Middle to Late Triassic intra-oceanic subduction， the mantle source was contaminated and exhibited E-MORB characteristics.

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Recent advances in breathable electronics

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Nano Research 2023年第3期16卷 4130-4142页

作者： Zhuocheng Yan Jian Xiong Bin Wang Min Gao Guangqiang Yin Tao Hu Taisong Pan Xinzhong Wang Yuan Lin Department of Electronic Communication and Technology Shenzhen Institute of Information TechnologyShenzhen 518172China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 610054China School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054China Engineering Cooperation on Applied Medicine Research Center University of Electronic Science and Technology of ChinaChengdu 610054China

The successful implementation of bioelectronic devices attached to living organism hinges on a number of material and device characteristics,including not only electrical and mechanical performances to gather physiological signals from living organism thus enabling status monitoring,but also permeability or breathability for gas/nutrient exchange between living organisms and surroundings to ensure minimum perturbation of the intrinsic biological ***,most bioelectronic devices built on planar polymeric substrates,such as polydimethylsiloxane(PDMS),polyurethane(PU),and polyimide(PI),lack efficient gas permeability,which may hinder the emission of volatile compounds from the surface of living organism,affecting the natural metabolism and reducing the comfort of ***,achieving permeability or breathability in bioelectronic devices is a significant ***,the devices made of gas-permeable materials with porous structures,that combine electronic components with daily garments,such as fibric and textile,offer exciting opportunities for breathable *** this review,several types of gas-permeable materials with their synthesis and processing routes are ***,two methods for measuring water vapor transmission rate of materials are discussed in ***,recent progress in the use of gaspermeable materials for the applications of plant-and skin-attached electronics is summarized systematically.

关键词： breathability gas permeability porous sponge foam nano materials plant electronics wearable electronics

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A Survey of LLM Datasets:From Autoregressive Model to AI Chatbot

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Journal of Computer Science & technology 2024年第3期39卷 542-566页

作者：杜非马新建杨婧如柳熠罗超然王学斌姜海鸥景翔 National Key Laboratory of Data Space Technology and System Beijing 100195China Advanced Institute of Big Data Beijing 100195China Fu Foundation School of Engineering and Applied Science Columbia UniversityNY 10027U.S.A. School of Software and Microelectronics Peking UniversityBeijing 100091China CCF IEEE

Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs given that most of the LLMs are produced by industries and the training details are typically *** datasets are an important setup of LLMs,this paper does a holistic survey on the training datasets used in both the pre-train and fine-tune *** paper first summarizes 16 pre-train datasets and 16 fine-tune datasets used in the state-of-the-art ***,based on the properties of the pre-train and fine-tune processes,it comments on pre-train datasets from quality,quantity,and relation with models,and comments on fine-tune datasets from quality,quantity,and *** study then critically figures out the problems and research trends that exist in current LLM *** study helps public researchers train and investigate LLMs by visual cases and provides useful comments to the research community regarding data *** the best of our knowledge,this paper is the first to summarize and discuss datasets used in both autoregressive and chat *** survey offers insights and suggestions to researchers and LLM developers as they build their models,and contributes to the LLM study by pointing out the existing problems of LLM studies from the perspective of data.

关键词： large language model(LLM) autoregressive model AI chatbot natural language processing(NLP)corpora OpenAI

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A novel combination belief rule base model for mechanical equipment fault diagnosis

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Chinese Journal of Aeronautics 2022年第5期35卷 158-178页

作者： Manlin CHEN Zhijie ZHOU Bangcheng ZHANG Guanyu HU You CAO High-Tech Institute of Xi’an Xi’an 710025China School of Applied Technology Changchun University of TechnologyChangchun 130000China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China

Due to the excellent performance in complex systems modeling under small samples and uncertainty,Belief Rule Base(BRB)expert system has been widely applied in fault ***,the fault diagnosis process for complex mechanical equipment normally needs multiple attributes,which can lead to the rule number explosion problem in BRB,and limit the efficiency and *** solve this problem,a novel Combination Belief Rule Base(C-BRB)model based on Directed Acyclic Graph(DAG)structure is proposed in this *** dispersing numerous attributes into the parallel structure composed of different sub-BRBs,C-BRB can effectively reduce the amount of calculation with acceptable *** the same time,a path selection strategy considering the accuracy of child nodes is designed in C-BRB to obtain the most suitable ***,a fusion method based on Evidential Reasoning(ER)rule is used to combine the belief rules of C-BRB and generate the final *** illustrate the effectiveness and reliability of the proposed method,a case study of fault diagnosis of rolling bearing is conducted,and the result is compared with other methods.

关键词： Fault diagnosis Belief rule base Directed acyclic graph Evidential reasoning Mechanical equipment

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Enhancing Classification Algorithm Recommendation in Automated Machine Learning: A Meta-Learning Approach Using Multivariate Sparse Group Lasso

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Computer Modeling in Engineering & Sciences 2025年第2期142卷 1611-1636页

作者： Irfan Khan Xianchao Zhang Ramesh Kumar Ayyasamy Saadat M.Alhashmi Azizur Rahim School of Software Dalian University of TechnologyDalian116620China Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKampar31900Malaysia College of Computing and Informatics University of SharjahSharjah27272United Arab Emirates Department of Computer Systems Engineering University of Engineering and Applied SciencesSwat19200Pakistan

The rapid growth of machine learning(ML)across fields has intensified the challenge of selecting the right algorithm for specific tasks,known as the Algorithm Selection Problem(ASP).Traditional trial-and-error methods have become impractical due to their resource *** Machine Learning(AutoML)systems automate this process,but often neglect the group structures and sparsity in meta-features,leading to inefficiencies in algorithm recommendations for classification *** paper proposes a meta-learning approach using Multivariate Sparse Group Lasso(MSGL)to address these *** method models both within-group and across-group sparsity among meta-features to manage high-dimensional data and reduce multicollinearity across eight meta-feature *** Fast Iterative Shrinkage-Thresholding Algorithm(FISTA)with adaptive restart efficiently solves the non-smooth optimization *** validation on 145 classification datasets with 17 classification algorithms shows that our meta-learning method outperforms four state-of-the-art approaches,achieving 77.18%classification accuracy,86.07%recommendation accuracy and 88.83%normalized discounted cumulative gain.

关键词： Meta-learning machine learning automated machine learning classification meta-features

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Research on Scattering Characteristics of Swarm Targets

Research on Scattering Characteristics of Swarm Targets

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Sun, Jingyue Guo, Kunyi Sheng, Xinqing Cong, Wei Beijing Institute of Technology Institute of Radio Frequency Technology and Software School of Integrated Circuits and Electronics Beijing100081 China Chengde Vocational College of Applied Technology Department of Automotive Engineering Chengde14632 China

ISBN: (纸本)9798350375909

Swarm targets are becoming increasingly prevalent in both military and civilian domains. Research on the electromagnetic scattering characteristics of swarm targets holds significant value for the development of countermeasure strategies. Obtaining dynamic measurement data for swarm targets is challenging and costly, exacerbated by the complex coupling interactions among the target group. Consequently, due to data scarcity, there is currently an insufficiency in the research on the scattering characteristics of swarm targets. This paper begins by conducting a detailed investigation into the coupling effects among metallic sphere clusters, focusing on the fluctuation of radar cross section and time-frequency features. Furthermore, a parametric modeling study is conducted to investigate the coupling phenomenon, and the influence of distance and azimuth on the intensity of coupling between targets is further analyzed in terms of the coupling mechanism. The results presented in this paper can offer valuable insights for subsequent research on the scattering characteristics of swarm targets. © 2024 IEEE.

关键词： Radar cross section

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Usability Heuristics for VR-Based Education: A Case Study of Science Experiment Laboratory Simulator 8

Usability Heuristics for VR-Based Education: A Case Study of...

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8th International Conference on Information technology, InCIT 2024

作者： Putjorn, Pruet Thein, Wai Yan Min Sricha-Ann, Patthadon Horikoshi, Taiki Thiyod, Saksiri Tongpaeng, Yootthapong Pyae, Nang Hsu Mon Intayoad, Wacharawan Mae Fah Luang University School of Applied Digital Technology Chiang rai Thailand Mae Fah Luang University Software Engineering Chiang rai Thailand

ISBN: (纸本)9798350366303

Usability analysis is essential in VR-based education as it ensures that virtual learning environments are intuitive, accessible, and effective for all users. This study focuses on evaluating the usability of a VR-based science experiment lab prototype, applying Nielsen's Usability Heuristics throughout its design, implementation, and assessment. By identifying and addressing user experience challenges, the research highlights the impact of usability heuristics on enhancing user engagement. The study contributes valuable data on how usability improvements can optimize the effectiveness of VR in education, promoting a more immersive and efficient learning experience. © 2024 IEEE.

关键词： Virtual environments

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Modern Build Automation for an Insurance Company Tool Selection

Modern Build Automation for an Insurance Company Tool Select...

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2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022

作者： Lange, Moritz Tran, Kim Chi Grunewald, Alexander Koschel, Arne Pakosch, Anna Astrova, Irina Hochschule Hannover University of Applied Sciences and Arts Hannover Germany Department of Software Science School of IT Tallinn University of Technology Tallinn Estonia

In this paper we describe the selection of a modern build automation tool for an industry research partner of ours, namely an insurance company. Build automation has become increasingly important over the years. Today, build automation became one of the central concepts in topics such as cloud native development based on microservices and DevOps. Since more and more products for build automation have entered the market and existing tools have changed their functional scope, there is nowadays a large number of tools on the market that differ greatly in their functional scope. Based on requirements from our partner company, a build server analysis was conducted. This paper presents our analysis requirements, a detailed look at one of the examined tools and a summarized comparison of two tools. c. © 2023 Elsevier B.V.. All rights reserved.

关键词： Automation

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Underwater Object Detection from Sonar Images Using Transfer Learning 21

Underwater Object Detection from Sonar Images Using Transfer...

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21st International Bhurban Conference on applied Sciences and technology, IBCAST 2024

作者： Mehmood, Saba Irfan, Muhammad Hamid, Umar Ali, Shahid CESAT-Islamabad Center of Excellence in Science and Applied Technologies Pakistan School of Software Northwestern Polytechnical University Xian China COMSATS Institute of Information Technology CIIT-Islamabad Pakistan

ISBN: (纸本)9798331516680

Underwater systems are always prone to complex environmental conditions and various interferences that is the reason why Sonar images are filled up with contamination, noise, and blurriness. Collection of real-world underwater images data is very costly with respect to human resources, time, equipment and logistics. Due to these challenges, there are very few publicly available datasets of underwater sonar images and only few datasets are available for underwater images which are scarce because of lack of resources. Precise and fast detection of objects in underwater sonar images is very less explored and still an open challenge for underwater systems. This paper evaluates performance of state-of-the-art object detection deep learning network YOLO (You Only Look Once) for underwater sonar images through transfer learning on publicly available benchmark Marine Debris dataset and custom-tailored dataset captured in real sea environment. Experimental results shows that YOLOv8n was able to achieve high mAP score of 95.3% on Marine Debris dataset with inference speed of 1.3ms. © 2024 IEEE.

关键词： Underwater imaging

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