Article
Computer Science, Information Systems
Hsien-Pin Hsu
Summary: This research proposes a MDFA algorithm to address the CSP and FAP problems simultaneously for SMT machines, with features like multiple swarms, adaptive and discrete moving step. Experimental results show that MDFA outperforms other algorithms in terms of assembly time.
Article
Chemistry, Multidisciplinary
Utku Emre Ali, He Yang, Vladislav Khayrudinov, Gaurav Modi, Zengguang Cheng, Ritesh Agarwal, Harri Lipsanen, Harish Bhaskaran
Summary: This article introduces a technique for reliably transferring individual nanowires onto various platforms and demonstrates their applications on different structures. The versatility of this technique enables easy integration of nanowires into previously seen cumbersome or impractical applications, including TEM studies and in situ electrical, optical, and mechanical characterization.
Article
Multidisciplinary Sciences
Tomohiro Mori, Hao Wang, Wang Zhang, Chern Chia Ser, Deepshikha Arora, Cheng-Feng Pan, Hao Li, Jiabin Niu, M. A. Rahman, Takeshi Mori, Hideyuki Koishi, Joel K. W. Yang
Summary: Two-photon polymerization lithography is a promising technique for producing three-dimensional structures with user-defined micro- and nanoscale features. However, non-uniform shrinkage is a challenge in this process. In this study, researchers develop a simple method using poly(vinyl alcohol) to achieve uniform heat shrinking of three-dimensional micro-/nano-architected materials printed by two-photon polymerization lithography.
NATURE COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Y. P. Tsang, C. H. Wu, W. H. Ip, C. K. M. Lee
Summary: This study utilizes the IIoT and federated learning to establish an intelligent decision support system for solder paste printing in the PCB assembly process. By deploying the IIoT-based squeegee blade, communication and interconnectivity between machines are improved, while a global machine intelligence model is aggregated in a decentralized and privacy-preserving manner, achieving automated and sustainable manufacturing management.
JOURNAL OF GRID COMPUTING
(2022)
Article
Engineering, Environmental
Iftikhar A. Soomro, Anser Ahmad, Rana H. Raza
Summary: This paper introduces a robust PCB classification system based on computer vision and deep learning, achieving high accuracy in e-waste recycling sorting by utilizing datasets under various conditions and a deep learning model.
RESOURCES CONSERVATION AND RECYCLING
(2022)
Article
Engineering, Environmental
Yanhe Nie, Yunxiang Jiang, Qiang Wang, Jianghao Chen, Sen Wang, Qike Zhang, Fumitake Takahashi
Summary: This study proposes the use of coal gasification slag (CGS) as an adsorbent for recovering gold from printed circuit boards (PCBs). The CGS was found to efficiently adsorb AuCl4- in solution, and the adsorption process was not significantly affected by pH, stirring speed, and temperature. The results suggest that the gold adsorption process is controlled by a chemical process and can be better described by pseudo-second-order kinetics and the Langmuir model. The recovery of gold by CGS not only helps to recycle solid waste but also enables the recycling of valuable resources in waste PCBs at a low cost.
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Wonbeom Lee, Hyunjun Kim, Inho Kang, Hongjun Park, Jiyoung Jung, Haeseung Lee, Hyunchang Park, Ji Su Park, Jong Min Yuk, Seunghwa Ryu, Jae-Woong Jeong, Jiheong Kang
Summary: An elastic printed circuit board (E-PCB) is a conductive framework used for the assembly of stretchable electronics. This study presents a method using a liquid metal particle network (LMPNet) as an elastic conductor, which satisfies all the requirements for E-PCBs. The LMPNet enables the fabrication of high-density E-PCBs, allowing the integration of numerous electronic components to create highly stretchable skin electronics.
Article
Chemistry, Multidisciplinary
Shaojie Qin, Pengkun Sun, Zhaoliang Wu, Wei Liu, Chunyan Yang
Summary: In this study, copper was successfully recovered from discarded printed circuit boards using foam fractionation, achieving high enrichment and recovery efficiencies for Cu ions under suitable conditions.
SEPARATION SCIENCE AND TECHNOLOGY
(2021)
Article
Green & Sustainable Science & Technology
Weifang Chen, Yanjun Chen, Yongkai Shu, Yinan He, Jinbo Wei
Summary: The non-metallic fraction of waste printed circuit board (WPCB) was found to be valuable after metal recovery, rich in organic polymer and inorganic materials which could serve as a source of chemicals and fuel. Through pyrolysis under different conditions, solid, liquid, and gaseous products were collected and characterized, showing that the products contained phenol, alkylated phenols, CO2, CH4, and H2. Pyrolysis pathways of WPCB disintegration were proposed based on the compositions of the products.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Biotechnology & Applied Microbiology
Sadegh Ghorbanzadeh, Seyed Morteza Naghib, Ali Sadr, Fatemeh Molaabasi, Wei Zhang
Summary: This article introduces the development of high performance and cost-effective gold screen-printed electrodes (SPEs) for electrochemical biosensing platforms. The article discusses the development procedure of the gold SPEs and presents their positive performance in electrochemical parameters. The study also demonstrates the successful fabrication of a simple breast cancer cell detection platform using the gold SPEs, showing cost-effectiveness and a linear calibration curve.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Thermodynamics
Pradeep Sahu, Prabu Vairakannu
Summary: Electronic wastes, especially printed circuit boards (PCBs), are thermally treated under N2 and CO2 conditions by pyrolysis and gasification processes. PCB pyrolysis at 500 degrees C yields 7.46% of tar with a calorific value of 31.28 MJ/kg. CO2 gasification of PCB mixture at 1000 degrees C achieves a conversion rate of 97.6%, resulting in high cold gas and exergy efficiencies. Co-gasification with high ash Indian coal increases the overall efficiency, and the residue can be used as a catalyst or additives in concrete material.
Article
Materials Science, Ceramics
Jie Tang, Xiaona Wan, Long Zhang
Summary: Hierarchically porous carbon/polyaniline electrodes derived from waste printed circuit board demonstrate exceptional electrochemical performance, including high rate capability, superior cyclic stability, and high specific capacitance. The synergistic effects between the specific surface area and porous structure contribute to the remarkable performance. Additionally, a potential mechanism explaining the superior performance is studied. This study not only offers a feasible strategy for recycling waste printed circuit boards but also provides insights for the rational synthesis and design of cost-effective electrode materials for supercapacitors.
CERAMICS INTERNATIONAL
(2023)
Article
Automation & Control Systems
Bin Xu, Xin-ke Feng, Xiao-yu Wu, Feng Luo, Lian-yu Fu, Xue-tao Zhai, Yong-hua Zhao, Hang Zhao, Jian-guo Lei
Summary: This paper proposed the use of micro electro-discharge machining (micro-EDM) for assisted machining of PCB micro-holes, studying the influence of micro-EDM voltage, pulse width, and pulse interval on hole mouth burr and hole nail head. Through experiments, it was found that high-quality PCB micro-holes could be obtained by adjusting the parameters of micro-EDM.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Zhengkai Li, Hao Sun, Xinghu Yu, Weichao Sun
Summary: This paper investigates the capacitated location routing problems (CLRP) and how to solve them using an improved Hopfield neural network (HNN). The original problem is decomposed into three subproblems and solved using a heuristic sequencing HNN approach. Experimental results demonstrate the effectiveness and efficiency of this method on practical industrial data.
Article
Engineering, Electrical & Electronic
Chuanxiao Zheng, Hao Lu, Heng Hu, Wenjun Zhao, Yuxiang Yuan, Yongzhong Xu, Yanlin Wang, Yong Hu
Summary: This study investigated the short-circuit failure and open-circuit failure of gas discharge tubes, and developed a printed circuit board external open-circuit failure gas discharge tube. The structure and working mechanism of the external open-circuit failure gas discharge tube were presented, and the relationship between the arc temperature and short-circuit current was explored. The experimental results showed that the size of the short-circuit current was positively correlated with the open-circuit response time, which was significantly affected by the power frequency and location of the trip point.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Industrial
Debiao Li, Jing Wang, Rui Qiang, Raymond Chiong
Summary: The research focuses on optimizing dyeing process in textile production, proposing an HDE algorithm combining chaos theory and local search algorithms. Special encoding and decoding scheme, along with differential evolution algorithm, are used to address parallel machine job sequencing issue, simplifying decision-making and reducing computational time.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Operations Research & Management Science
Kejia Chen, Debiao Li, Xiao Wang
JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING
(2020)
Article
Management
Shenghai Zhou, Debiao Li, Yong Yin
Summary: This study improves patient-and-physician matching and appointment scheduling in specialty care by developing a stochastic optimization model to minimize operational costs. Results show that matching significantly impacts operational costs, and the proposed algorithm provides efficient solutions for medium to large-size problems compared to traditional methods.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Debiao Li, Xiaoming Ruan, Qing Yue
Summary: This study proposed an automatic medication dispensing method based on meal orders to improve the efficiency of pharmacy care and reduce medication errors during dispensing. Using a novel three-stage assembly flowshop problem solution, the total completion times of packing prescription orders can be minimized.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Correction
Multidisciplinary Sciences
Mu Zeng, Yingyan Qiao, Zhaoying Wen, Jun Liu, Enhua Xiao, Changlian Tan, Yibin Xie, Jing An, Zishu Zhang, Zhanming Fan, Debiao Li
SCIENTIFIC REPORTS
(2022)
Article
Operations Research & Management Science
Shi Qiang Liu, Erhan Kozan, Mahmoud Masoud, Debiao Li, Kai Luo
Summary: The study introduces a critical problem in open-pit mining: how to determine appropriate sizes of mining jobs and optimize the allocation and sequencing of mining equipment. By introducing a new integrated planning-scheduling problem and combining it with the theory of parallel-machine flow shop scheduling, an innovative math-heuristic approach is proposed to solve this problem efficiently.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Automation & Control Systems
Debiao Li, Xiaoqiang Chen, Siping Chen
Summary: It is difficult for patients without medical knowledge to choose a capable physician based on nontransparent medical information, especially in specialty care. To address this problem, we propose a novel physician matching index (PMI) obtained by an analytical framework integrated with an improved multi-disease pre-diagnosing Bayesian network (BN) model. The proposed PMI can rectify misdiagnosis and guide patients in choosing physicians more appropriately based on patient preferences. Our case study in the ear, nose, and throat department demonstrates the effectiveness of the proposed approach.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Proceedings Paper
Engineering, Biomedical
Zihao Chen, Yuhua Chen, Yibin Xie, Debiao Li, Anthony G. Christodoulou
Summary: In this study, a DC non-Cartesian deep subspace learning framework for fast, accurate dynamic MR image reconstruction is proposed. Experimental results show that the proposed framework significantly improves reconstruction accuracy while accelerating the process.
2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022)
(2022)
Meeting Abstract
Gastroenterology & Hepatology
Jamil S. Samaan, Yazan Abboud, Janice E. Oh, Yi Jiang, Arsen Osipov, Jun Gong, Andrew Hendifar, Katelyn Atkins, Quin Liu, Kenneth H. Park, Rabindra Watson, Nicholas N. Nissen, Shelly C. Lu, Debiao Li, Stephen J. Pandol, Simon K. Lo, Srinivas Gaddam
Meeting Abstract
Gastroenterology & Hepatology
Jamil S. Samaan, Yazan Abboud, Janice E. Oh, Yi Jiang, Arsen Osipov, Jun Gong, Andrew Hendifar, Katelyn Atkins, Quin Liu, Kenneth H. Park, Rabindra Watson, Nicholas N. Nissen, Shelly C. Lu, Debiao Li, Stephen J. Pandol, Simon K. Lo, Srinivas Gaddam
Meeting Abstract
Gastroenterology & Hepatology
Yi Jiang, Yazan Abboud, Jeff Liang, Jenan Ghaith, Daniel Lew, Arsen Osipov, Jun Gong, Andrew Hendifar, Katelyn Atkins, Quin Liu, Kenneth H. Park, Rabindra Watson, Nicholas N. Nissen, Debiao Li, Shelly C. Lu, Stephen J. Pandol, Simon K. Lo, Srinivas Gaddam
Meeting Abstract
Gastroenterology & Hepatology
Yazan Abboud, Jamil S. Samaan, Janice E. Oh, Yi Jiang, Daniel Lew, Jenan Ghaith, Christine Leyson, Rabindra Watson, Quin Liu, Kenneth H. Park, Shirley Paski, Arsen Osipov, Brent K. Larson, Andrew Hendifar, Katelyn Atkins, Nicholas N. Nissen, Debiao Li, Shelly C. Lu, Stephen J. Pandol, Simon K. Lo, Srinivas Gaddam
Meeting Abstract
Gastroenterology & Hepatology
Yazan Abboud, Jamil S. Samaan, Navkiran K. Randhawa, Janice E. Oh, Clara Q. Chen, Yi Jiang, Jenan Ghaith, Daniel Lew, Rabindra Watson, Quin Liu, Kenneth H. Park, Arsen Osipov, Brent K. Larson, Andrew Hendifar, Nicholas N. Nissen, Debiao Li, Shelly C. Lu, Stephen J. Pandol, Simon K. Lo, Srinivas Gaddam
Article
Engineering, Industrial
Debiao Li, Siping Chen, Raymond Chiong, Liting Wang, Sandeep Dhakal
Summary: This paper introduces an SOS-based SVR ensemble model for predicting the PCB cycle time in SMT production lines. The model optimizes parameters using the SVR model and SOS algorithm to improve prediction accuracy, which has been confirmed through experiments to be more efficient than current industrial solutions and other machine learning methods.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Meeting Abstract
Clinical Neurology
Jiayu Xiao, Huijuan Miao, Song Shlee, Konrad Schlick, Tao Jiang, Shuang Xia, Tong Han, Marcel Maya, Patrick Lyden, Debiao Li, Xiuhai Guo, Qi Yang, Zhaoyang Fan
Article
Computer Science, Artificial Intelligence
Fangyu Chen, Yongchang Wei, Hongchang Ji, Gangyan Xu
Summary: This paper introduces a dual-layer network analytical framework for evaluating standard systems in construction safety management and validates its effectiveness through a case study. The research findings suggest that key standards often encompass a wider array of risks, providing suggestions for revising construction standards.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Minghao Li, Qiubing Ren, Mingchao Li, Ting Kong, Heng Li, Huijing Tian, Shiyuan Liu
Summary: This study proposes a method using digital twin technology to construct a collision early warning system for marine piling. The system utilizes a five-dimensional model and four independently maintainable development modules to maximize its effectiveness. The pile positioning algorithm and collision early warning algorithm are capable of providing warnings for complex pile groups.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Seokhyun Ryu, Sungjoo Lee
Summary: This study proposes the use of patent information to develop a robust technology tree and applies it to the furniture manufacturing process. Through methods such as clustering analysis, semantic analysis, and association-rule mining, technological attributes and their relationships are extracted and analyzed. This approach provides meaningful information to improve the understanding of a target technology and supports research and development planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Shuai Ma, Kechen Song, Menghui Niu, Hongkun Tian, Yanyan Wang, Yunhui Yan
Summary: This paper proposes a feature-based domain disentanglement and randomization (FDDR) framework to improve the generalization of deep models in unseen datasets. The framework successfully addresses the appearance difference issue between training and test images by decomposing the defect image into domain-invariant structural features and domain-specific style features. It also utilizes randomly generated samples for training to further expand the training sample.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Fang Xu, Tianyu Zhou, Hengxu You, Jing Du
Summary: This study explores the impact of AR-based egocentric perspectives on indoor wayfinding performance. The results reveal that participants using the egocentric perspective demonstrate improved efficiency, reduced cognitive load, and enhanced spatial awareness in indoor navigation tasks.
ADVANCED ENGINEERING INFORMATICS
(2024)
Review
Computer Science, Artificial Intelligence
Yujie Lu, Shuo Wang, Sensen Fan, Jiahui Lu, Peixian Li, Pingbo Tang
Summary: Image-based 3D reconstruction plays a crucial role in civil engineering by bridging the gap between physical objects and as-built models. This study provides a comprehensive summary of the field over the past decade, highlighting its interdisciplinary nature and integration of various technologies such as photogrammetry, 3D point cloud analysis, semantic segmentation, and deep learning. The proposed 3D reconstruction knowledge framework outlines the essential elements, use phases, and reconstruction scales, and identifies eight future research directions. This review is valuable for scholars interested in the current state and future trends of image-based 3D reconstruction in civil engineering, particularly in relation to deep learning methods.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper presents a novel framework for segmenting intersecting machining features using deep reinforcement learning. The framework enhances the effectiveness of intersecting machining feature segmentation by leveraging the robust feature representation, decision-making, and automatic learning capabilities of deep reinforcement learning. Experimental results demonstrate that the proposed approach successfully addresses some existing challenges faced by several state-of-the-art methods in intersecting machining feature segmentation.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Chao Zhao, Weiming Shen
Summary: This paper proposes a semantic-discriminative augmentation-driven network for imbalanced domain generalization fault diagnosis, which enhances the model's generalization capabilities through synthesizing reliable samples and optimizing representations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ching-Chih Chang, Teng-Wen Chang, Hsin-Yi Huang, Shih-Ting Tsai
Summary: Ideation is the process of generating ideas through exploring visual and semantic stimuli for creative problem-solving. This process often requires changes in user goals and insights. Using pre-designed content and semantic-visual concepts for ideation can introduce uncertainty. An adaptive workflow is proposed in this study that involves extracting and summarizing semantic-visual features, using clusters of adapted information for multi-label classification, and constructing a design exploration model with visualization and exploration.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Zhen Wang, Shusheng Zhang, Hang Zhang, Yajun Zhang, Jiachen Liang, Rui Huang, Bo Huang
Summary: This research proposes a novel approach for machining feature process planning using graph convolutional neural networks. By representing part information with attribute graphs and constructing a learning model, the proposed method achieves higher accuracy and resolves current limitations in machining feature process planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hong-Wei Xu, Wei Qin, Jin-Hua Hu, Yan-Ning Sun, You -Long Lv, Jie Zhang
Summary: Wafer fabrication is a complex manufacturing system, where understanding the correlation between parameters is crucial for identifying the cause of wafer defects. This study proposes a Copula network deconvolution-based framework for separating direct correlations, which involves constructing a complex network correlation diagram and designing a nonlinear correlation metric model. The proposed method enables explainable fault detection by identifying direct correlations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yida Hong, Wenqiang Li, Chuanxiao Li, Hai Xiang, Sitong Ling
Summary: An adaptive push method based on feature transfer is proposed to address sparsity and cold start issues in product intelligent design. By constructing a collaborative filtering algorithm model and transforming the rating model, the method successfully alleviates data sparsity and cold start problems.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hairui Fang, Jialin An, Bo Sun, Dongsheng Chen, Jingyu Bai, Han Liu, Jiawei Xiang, Wenjie Bai, Dong Wang, Siyuan Fan, Chuanfei Hu, Fir Dunkin, Yingjie Wu
Summary: This work proposes a model for real-time fault diagnosis and distance localization on edge computing devices, achieving lightweight design and high accuracy in complex environments. It also demonstrates a high frame rate on edge computing devices, providing a novel solution for industrial practice.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yujun Jiao, Xukai Zhai, Luyajing Peng, Junkai Liu, Yang Liang, Zhishuai Yin
Summary: This paper proposes a digital twin-based motion forecasting framework that predicts the future trajectories of workers on construction sites, accurately predicting workers' motions in potential risk scenarios.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ling-Zhe Zhang, Xiang-Dong Huang, Yan-Kai Wang, Jia-Lin Qiao, Shao-Xu Song, Jian-Min Wang
Summary: Time-series DBMSs based on the LSM-tree have been widely applied in various scenarios. The characteristics of time-series data workload pose challenges to efficient queries. To address issues like query latency and inaccurate range, we propose a novel compaction algorithm called Time-Tiered Compaction.
ADVANCED ENGINEERING INFORMATICS
(2024)
