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Articles 8401 - 8430 of 63010
Full-Text Articles in Computer Sciences
A Survey On Training Challenges In Generative Adversarial Networks For Biomedical Image Analysis, Muhammad Muneeb Saad, Ruairi O'Reilly, Mubashir Husain Rehmani
A Survey On Training Challenges In Generative Adversarial Networks For Biomedical Image Analysis, Muhammad Muneeb Saad, Ruairi O'Reilly, Mubashir Husain Rehmani
Department of Computer Science Publications
In biomedical image analysis, the applicability of deep learning methods is directly impacted by the quantity of image data available. This is due to deep learning models requiring large image datasets to provide high-level performance. Generative Adversarial Networks (GANs) have been widely utilized to address data limitations through the generation of synthetic biomedical images. GANs consist of two models. The generator, a model that learns how to produce synthetic images based on the feedback it receives. The discriminator, a model that classifies an image as synthetic or real and provides feedback to the generator. Throughout the training process, a GAN …
Triberta And Beyond: Redefining Entity Resolution With Large Language Models, Bi Foua
Triberta And Beyond: Redefining Entity Resolution With Large Language Models, Bi Foua
Theses and Dissertations
Entity resolution (ER) plays a pivotal role across domains by enabling data integration and quality improvement. This dissertation delves into the evolving landscape of ER, introducing innovative approaches that redefine this fundamental task. The first contribution is TriBERTa, a novel representation learning model tailored for ER. TriBERTa sets new benchmarks in entity matching and demonstrates versatility across ER processes like data blocking and resolution. Empirical evaluations on diverse datasets showcase TriBERTa’s superior performance over existing representations, including from large language models. The second contribution explores the use generative language models like GPT-3.5 and Dolly 2.0 for cross-domain entity matching using …
De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian
De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …
Advancing Cognitive Accessibility: The Role Of Artificial Intelligence In Enhancing Inclusivity, Rukiya Deetjen-Ruiz, Marjorie P Daniel, Jennie Telus, Lodz Deetjen
Advancing Cognitive Accessibility: The Role Of Artificial Intelligence In Enhancing Inclusivity, Rukiya Deetjen-Ruiz, Marjorie P Daniel, Jennie Telus, Lodz Deetjen
All Works
This editorial examines the transformative role of Artificial Intelligence (AI) in enhancing cognitive accessibility for neurodiverse individuals. It explores the evolution from conventional assistive technologies to sophisticated AI-driven solutions, highlighting how these advancements are reshaping inclusivity in education and the workplace. The piece critically analyzes the benefits and challenges of AI in this context, considering ethical implications, user-centered design, and the need for equitable access. It concludes with a call to action for continued innovation and collaboration in developing AI technologies that truly cater to the diverse needs of neurodiverse individuals.
Natural Language Processing Analysis Of Online Reviews For Small Business: Extracting Insight From Small Corpora, Benjamin J. Mccloskey, Phillip M. Lacasse, Bruce A. Cox
Natural Language Processing Analysis Of Online Reviews For Small Business: Extracting Insight From Small Corpora, Benjamin J. Mccloskey, Phillip M. Lacasse, Bruce A. Cox
Faculty Publications
Receiving and acting on customer input is essential to sustaining and growing any service organization, particularly a small family business whose livelihood depends on strong relationships with its customers. The competitive advantage offered by advanced analytical approaches for supporting decisions is not trivial, and enterprises across virtually all domains of society are investing heavily in this emerging discipline. Natural Language Processing (NLP) is a subset of computer science that employs computational approaches to analyze human language; it is effective at extracting insight from text data but frequently requires large corpora to train its models, in the scale of thousands or …
A Multi-Criteria Decision Making Model For Sustainable And Resilient Supplier Selection And Management, Samah Ibrahim Abdel Aal
A Multi-Criteria Decision Making Model For Sustainable And Resilient Supplier Selection And Management, Samah Ibrahim Abdel Aal
Neutrosophic Systems with Applications
Sustainable and resilient supplier selection and management are essential to building environmentally responsible and resilient supply chains. Selecting sustainable and resilient suppliers enables organizations to ensure the long-term viability of the supply chain. To do that, there is a need to identify suitable suppliers that align with sustainability and resilience goals. This study aims to provide an overview of the requirements and criteria for selecting and managing sustainable and resilient suppliers and emphasizes the significance of integrating sustainability and resilience principles throughout the supply chain. Multi-criteria decision-making (MCDM) is used to deal with various criteria. The double normalization-based multi-aggregation (DNMA) …
Foundation Of Appurtenance And Inclusion Equations For Constructing The Operations Of Neutrosophic Numbers Needed In Neutrosophic Statistics, Florentin Smarandache
Foundation Of Appurtenance And Inclusion Equations For Constructing The Operations Of Neutrosophic Numbers Needed In Neutrosophic Statistics, Florentin Smarandache
Neutrosophic Systems with Applications
We introduce for the first time the appurtenance equation and inclusion equation, which help in understanding the operations with neutrosophic numbers within the frame of neutrosophic statistics. The way of solving them resembles the equations whose coefficients are sets (not single numbers).
A Multi-Criteria Decision Making Model For Sustainable And Resilient Supplier Selection And Management, Samah Ibrahim Abdel Aal
A Multi-Criteria Decision Making Model For Sustainable And Resilient Supplier Selection And Management, Samah Ibrahim Abdel Aal
Neutrosophic Systems with Applications
Sustainable and resilient supplier selection and management are essential to building environmentally responsible and resilient supply chains. Selecting sustainable and resilient suppliers enables organizations to ensure the long-term viability of the supply chain. To do that, there is a need to identify suitable suppliers that align with sustainability and resilience goals. This study aims to provide an overview of the requirements and criteria for selecting and managing sustainable and resilient suppliers and emphasizes the significance of integrating sustainability and resilience principles throughout the supply chain. Multi-criteria decision-making (MCDM) is used to deal with various criteria. The double normalization-based multi-aggregation (DNMA) …
Foundation Of Appurtenance And Inclusion Equations For Constructing The Operations Of Neutrosophic Numbers Needed In Neutrosophic Statistics, Florentin Smarandache
Foundation Of Appurtenance And Inclusion Equations For Constructing The Operations Of Neutrosophic Numbers Needed In Neutrosophic Statistics, Florentin Smarandache
Neutrosophic Systems with Applications
We introduce for the first time the appurtenance equation and inclusion equation, which help in understanding the operations with neutrosophic numbers within the frame of neutrosophic statistics. The way of solving them resembles the equations whose coefficients are sets (not single numbers).
Anthropomorphism And Human-Robot Interaction, Rae Yule Kim
Anthropomorphism And Human-Robot Interaction, Rae Yule Kim
Department of Economics Faculty Scholarship and Creative Works
Exploring how human appreciation for and interactions with robots are influenced by anthropomorphic features.
Unveiling Efficiency: Investigating Distance Measures In Wastewater Treatment Using Interval-Valued Neutrosophic Fuzzy Soft Set, Muhammad Saeed, Kinza Kareem, Fatima Razzaq, Muhammad Saqlain
Unveiling Efficiency: Investigating Distance Measures In Wastewater Treatment Using Interval-Valued Neutrosophic Fuzzy Soft Set, Muhammad Saeed, Kinza Kareem, Fatima Razzaq, Muhammad Saqlain
Neutrosophic Systems with Applications
To reduce the threats that wastewater poses to human health and the environment, water treatment techniques must be improved. The use of a procedure that includes preparation, testing, primary and secondary treatments, filtration, disinfection, and continuous monitoring is therefore required. The objective of this research is to create a hybrid notion that extends the idea of an interval-valued neutrosophic fuzzy soft set (IVNFSS) to an interval-valued neutrosophic fuzzy set. Operations like complement, union, and integration are included in the idea. To improve decision-making accuracy, a quality-assessment distance measure is incorporated, offering a numerical representation of the disparity between various factors. …
Deep Learning Model Compression On Edge Devices For Audio, Afsana Rahman Mou
Deep Learning Model Compression On Edge Devices For Audio, Afsana Rahman Mou
Theses and Dissertations
Audio classification plays a crucial role in interpreting and understanding soundscapes, enabling applications like voice assistants, sound event detection, and music analysis. However, deploying deep learning models for audio classification on edge devices presents significant challenges. These models often require substantial computational resources and memory, which are limited on edge devices. Balancing performance, efficiency, and accuracy remains a key hurdle in this field. In this research, we explore various deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Audio Spectrogram Transformer (AST), for the purpose of audio classification on the ESC 50 and Audio Set datasets. …
Unveiling Efficiency: Investigating Distance Measures In Wastewater Treatment Using Interval-Valued Neutrosophic Fuzzy Soft Set, Muhammad Saeed, Kinza Kareem, Fatima Razzaq, Muhammad Saqlain
Unveiling Efficiency: Investigating Distance Measures In Wastewater Treatment Using Interval-Valued Neutrosophic Fuzzy Soft Set, Muhammad Saeed, Kinza Kareem, Fatima Razzaq, Muhammad Saqlain
Neutrosophic Systems with Applications
To reduce the threats that wastewater poses to human health and the environment, water treatment techniques must be improved. The use of a procedure that includes preparation, testing, primary and secondary treatments, filtration, disinfection, and continuous monitoring is therefore required. The objective of this research is to create a hybrid notion that extends the idea of an interval-valued neutrosophic fuzzy soft set (IVNFSS) to an interval-valued neutrosophic fuzzy set. Operations like complement, union, and integration are included in the idea. To improve decision-making accuracy, a quality-assessment distance measure is incorporated, offering a numerical representation of the disparity between various factors. …
Yolov8-Cab: Improved Yolov8 For Real-Time Object Detection, Moahaimen Talib, Ahmed H. Y. Al-Noori, Jameelah Suad
Yolov8-Cab: Improved Yolov8 For Real-Time Object Detection, Moahaimen Talib, Ahmed H. Y. Al-Noori, Jameelah Suad
Karbala International Journal of Modern Science
This study presents a groundbreaking approach to enhance the accuracy of the YOLOv8 model in object detection, focusing mainly on addressing the limitations of detecting objects in varied image types, particularly for small objects. The proposed strategy of this work incorporates the Context Attention Block (CAB) to effectively locate and identify small objects in images. Furthermore, the proposed work improves the feature extraction capability without increasing model complexity by increasing the thickness of the Coarse-to-Fine(C2F) block. In addition, Spatial Attention (SA) has been modified to accelerate detection performance. The enhanced YOLOv8 model (Namely YOLOv8-CAB) strongly emphasizes the performance of detecting …
Crack-Ers (Crack Riddles Applying Cybersecurity Knowledge - Escape Room Scenario), Benjamin Acuff
Crack-Ers (Crack Riddles Applying Cybersecurity Knowledge - Escape Room Scenario), Benjamin Acuff
Posters-at-the-Capitol
CRACK-ERS (Crack Riddles Applying Cybersecurity Knowledge - Escape Room Scenario) is a unique, beginner's level CTF game with riddle-based challenges on various cybersecurity topics. The game is driven by an adventure story-based escape room format. Existing literature indicates that traditional CTFs pose challenges for beginners with no cybersecurity background. The novelty of CRACK-ERS lies in its non-traditional design as an unplugged CTF with an adventure scenario-driven script, encouraging participants to solve cybersecurity-related riddles. CRACK-ERS targets beginner-level learners, fostering teamwork, explorative research, cybersecurity problem-solving, and riddle-cracking skills. Prior cybersecurity educational research notes limited instances of escape room-style CTF games and fewer …
2019: Designing A Wikia Fandom Page, Brandon Carl
2019: Designing A Wikia Fandom Page, Brandon Carl
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
No abstract provided.
Scene Graph Generation: A Comprehensive Survey, Hongsheng Li, Guangming Zhu, Liang Zhang, Youliang Jiang, Yixuan Dang, Haoran Hou, Peiyi Shen, Xia Zhao, Syed A. A. Shah, Mohammed Bennamoun
Scene Graph Generation: A Comprehensive Survey, Hongsheng Li, Guangming Zhu, Liang Zhang, Youliang Jiang, Yixuan Dang, Haoran Hou, Peiyi Shen, Xia Zhao, Syed A. A. Shah, Mohammed Bennamoun
Research outputs 2022 to 2026
Deep learning techniques have led to remarkable breakthroughs in the field of object detection and have spawned a lot of scene-understanding tasks in recent years. Scene graph has been the focus of research because of its powerful semantic representation and applications to scene understanding. Scene Graph Generation (SGG) refers to the task of automatically mapping an image or a video into a semantic structural scene graph, which requires the correct labeling of detected objects and their relationships. In this paper, a comprehensive survey of recent achievements is provided. This survey attempts to connect and systematize the existing visual relationship detection …
Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu
Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu
Journal of System Simulation
Abstract: A K neighbor-RElim (KNR) algorithm and a sequential KNbr-RElim (SKNR) algorithm are proposed to mine traffic congestion association rules and congestion propagation spatio-temporal association rules by vehicle trajectory data in a large-scale road network. The KNR algorithm extends the spatial topology constraint based on the RElim algorithm. The KNR can be used to mine the road links prone to congestion from the large-scale trajectory dataset in a large-scale road network and quantify the strength of association for congested road links. The SKNR algorithm expands the time dimension in the form of sliding window and can be applied for mining …
Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan
Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan
Journal of System Simulation
Abstract: As the combat systems develop towards clustering, coordination, unmanned, and intelligent direction, traditional combat system modeling methods are unable to reflect the complexity and intelligence of the combat systems. By drawing on symbiosis theory, this paper models and analyzes complex combat systems, and decomposes the complex combat system into various subsystems according to combat missions. The combat units, interaction modes, and combat environments in the subsystems are analyzed. The paper builds mathematical models to capture the collaborative interaction relationships between combat units, finally constructing a symbiotic model of complex combat systems. By the symbiosis principles and methods, quantitative analysis …
Ai4r: The Fifth Scientific Research Paradigm, Guojie Li
Ai4r: The Fifth Scientific Research Paradigm, Guojie Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
This article refers to “AI for Research（AI4R）” as the fifth research paradigm and summarizes its characteristics, including: (1) the fully integration of artificial intelligence into various scientific and technology researches; (2) machine intelligence has become an integral part of scientific research; (3) effectively handles the combinatorial explosion problem with high computational complexity; (4) probability and statistical models play a greater role in scientific research; (5) realize the integration of four existing research paradigms, cross disciplinary cooperation has become the mainstream research method; (6) scientific research relies more on large research platforms characterized by large models. This article points out that …
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Journal of System Simulation
Abstract: Aiming at the lack of directionality of traditional dot product attention, this paper proposes a directed attention model (DAM) based on cosine similarity. To effectively represent the direction relationship between the spatial and temporal features of video frames, the paper defines the relationship function in the attention mechanism using the cosine similarity theory, which can remove the absolute value of the relationship between features. To reduce the computational burden of the attention mechanism, the operation is decomposed from two dimensions of time and space. The computational complexity is further optimized by combining linear attention operation. The experiment is divided …
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Journal of System Simulation
Abstract: Hardware-in-the-loop simulation system is a complex distributed simulation system, and its design and integration directly affect the system performance and construction goals. Based on years of experience, this paper first summarizes the design of the overall scheme and analyzes the performance requirements of real-time, compatibility, scalability, and security. Then, the paper describes the overall scheme of a typical hardware-in-the-loop simulation system, including the functional hierarchy, operation mechanism, and structural composition. Finally, it summarizes the contents and steps of the system integration testing, acceptance testing, and credibility evaluation method.
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang
Journal of System Simulation
Abstract: A mathematical model of emergency material scheduling after earthquakes is built. The model evaluates the emergency degree of each disaster area based on the disaster situation and designs a method to split the demand of the disaster area, improving the efficiency of vehicle utilization. To solve the model, this paper proposes a discrete shuffled frog leaping algorithm with multi-resource learning. The multiple information sources introduced by the proposed algorithm can expand the search direction and reduce the assimilation speed of the population in the algorithm. Second, the worst individual in each subgroup can learn the effective information in the …
Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang
Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang
Journal of System Simulation
Abstract: The equipment system is the reflection of the combat system from the perspective of equipment. The research on the combat effectiveness evaluation of the equipment system is of great practical significance for the optimization, construction, and development of the equipment system. Cluster equipment combat system confrontation is characterized by large-scale, highly dynamic and strong confrontation, and it is difficult to directly evaluate combat effectiveness with traditional methods. Aiming at the single task homogeneous cluster equipment system (such as UAV reconnaissance swarm and ground unmanned platform fire assault cluster), this paper regards the confrontation process of equipment system as the …
Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang
Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang
Journal of System Simulation
Abstract: As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization, this paper builds a path optimization model to minimize the comprehensive distribution cost. The model combines with the characteristics of fresh distribution, and comprehensively considers the transportation cost, carbon emission, refrigeration, cargo damage and time window constraints during cold chain transportation. Then, an improved ant colony algorithm is designed to solve this model. At the initial stage, the genetic algorithm is adopted to generate the initial pheromone, and then the ant colony algorithm is applied to conduct the subsequent optimization search. The …
Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu
Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu
Journal of System Simulation
Abstract: Due to factors such as simplified assumptions or equipment characteristic deviation, modeling errors are inevitable in the mechanism modeling of thermal power units. To deal with the problem, this paper proposes a novel model refinement method based on recursive subspace for the digital twin of thermal power units. Firstly, the digital twin models are built based on mechanism analysis and combined with small sample data of typical conditions, ensuring interpretability and generalization performance. Secondly, based on the recursive subspace identification method, the refinement model is built and updated online in real time to compensate for the modeling error, improving …
Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou
Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou
Journal of System Simulation
Abstract: To meet the needs of virtual multi-person collaborative disassembly and assembly system for different disassembly and assembly tasks, this paper proposes a data-driven method with configurable task sequence. Taking an aeroengine prototype as the research object, the paper studies the task elements of multi-person collaborative disassembly and assembly. It parameterizes and expresses the task based on JSON (JavaScript object notation) and drives the task sequence by JSON parametrical files, defining the interactive operation of each task step. The practice shows that this method is applied to the multi-person collaborative disassembly and assembly system, which makes the system configurable and …
Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye
Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye
Journal of System Simulation
Abstract: Verification, validation, and accreditation (VV&A) is a key means to ensure the credibility of simulation models, and model validation is the core link. In view of the unavailability of reference data, various sources of reference data, and strong subjectivity of expert validation in the result validation of the missile flight simulation model, a result validation method for the missile flight simulation model based on piecewise feature extraction of time series was proposed. Specifically, a comprehensive piecewise linear method for time series was first proposed. The method consisted of a linear piecewise algorithm based on the second-order derivative for extracting …
Building New Paradigm Of Digital Intelligence Security For New Development Pattern, Xiaoguang Yang, Yang Wu, Xingwei Zhang, Xiaolong Zheng
Building New Paradigm Of Digital Intelligence Security For New Development Pattern, Xiaoguang Yang, Yang Wu, Xingwei Zhang, Xiaolong Zheng
Bulletin of Chinese Academy of Sciences (Chinese Version)
After the 20th National Congress of the Communist Party of China, China has entered a new era of development. Simultaneously, the rapid advancement and extensive application of artificial intelligent technologies have activated a new wave of economic potential and brought about new security challenges to socioeconomic development. This study firstly analyzes the characteristics of the new development pattern in global contexts, and examines the risks and challenges of digital intelligence security (DIS) under the new pattern, encompassing technological security and personal security at the micro-level, as well as economic security, social security, and cultural security at the macro-level. Based on …
Analysis And Reflections On Key Platform Facilities Construction Of Global Biomanufacturing Industry, Xiaoyan Wu, Fang Chen, Yaoying Shan, Anjing Lu
Analysis And Reflections On Key Platform Facilities Construction Of Global Biomanufacturing Industry, Xiaoyan Wu, Fang Chen, Yaoying Shan, Anjing Lu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Biomanufacturing, an emerging production method, is becoming a significant trend in global economic development and has garnered widespread international attention. Platform facilities are vital to the biomanufacturing industry’s development, serving as both the foundation for technological innovation and the bridge between research outcomes and practical applications. This study analyzes three key types of platform facilities and their operational mechanisms: technology innovation platforms (exemplified by the U.S. Agile BioFoundry), pilot-scale platforms (represented by European Bio Base Europe Pilot Plant), and industry incubation platforms (illustrated by the UK SynbiCITE). Drawing from these successful examples and examining China’s current platform infrastructure, this paper …