Article
Environmental Studies
Amol Paithankar, Snehamoy Chatterjee, Ryan Goodfellow
Summary: The study introduces a global optimization model that effectively addresses the mining complex problem, helping to enhance the economic value of the entire mining project and reduce risks.
Article
Environmental Studies
Asif Khan, Mohammad Waqar Ali Asad
Summary: The mineral supply chain in an ideal open-pit mining operation includes sequential stages such as a surface mine, a processing plant, and a refinery or market, with the cut-off grade playing a significant role in material flow. This article introduces a new mathematical model based on mixed integer programming to optimize the cut-off grade policy for mining multiple metal products, showing better performance compared to existing heuristic methods in three case studies, with a higher net present value.
Article
Automation & Control Systems
Benny Avelin, Anders Karlsson
Summary: We explore the dynamical and geometrical aspects of deep learning. By quantifying differences between data or decision functions, we present semi-invariant metrics that are applicable to many standard choices of layer maps. By considering random layer maps and employing non-commutative ergodic theorems, we are able to deduce the existence of certain limits as the number of layers tends to infinity. Additionally, we investigate the random initialization of standard networks and discover a surprising cutoff phenomenon in terms of the depth of the network. This cutoff phenomenon may be an important parameter for choosing an appropriate number of layers or a good initialization procedure. In conclusion, we hope that the concepts and results in this paper can provide a geometric framework for the theoretical understanding of deep neural networks.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Rheumatology
Oh Chan Kwon, Min-Chan Park
Summary: This study determined the cut-off values of BASDAI for determining disease activity states in ankylosing spondylitis patients. The study found that BASDAI values of 1.9, 3.5, and 4.9 corresponded to ASDAS-CRP values of 1.3, 2.1, and 3.5, respectively. The agreement between disease activity states based on BASDAI and ASDAS-CRP cut-off values was good.
Article
Green & Sustainable Science & Technology
Timothy Rijsdijk, Micah Nehring
Summary: This paper examines the effect of carbon pricing on the economic viability of a high grade copper-cobalt mine in the Democratic Republic of the Congo. The results show that carbon pricing can increase mining and processing costs, and the choice between hydroelectric and coal-fired power generation also affects the processing costs and ore economics.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Chemical
Farzad Sotoudeh, Micah Nehring, Mehmet Kizil, Peter Knights, Amin Mousavi
Summary: Determining a cut-off grade is crucial in mining operations due to its role in separating waste material from valuable ore, especially with lower grades in an uncertain market. Implementing pre-concentration systems before main processing can increase sustainability and resource utilization, potentially leading to a reduction in mine cut-off grade. The integration of pre-concentration systems and a novel method for calculating underground cut-off grade are shown to improve profitability, efficiency, and sustainability in underground operations.
MINERALS ENGINEERING
(2021)
Article
Geosciences, Multidisciplinary
Lloyd Windrim, Arman Melkumyan, Richard J. Murphy, Anna Chlingaryan, Raymond Leung
Summary: Remote mapping of minerals and discrimination of ore and waste on surfaces are important tasks in geological applications. However, mapping mineral spectra on an open-cut mine face is challenging due to subtle differences in spectral absorption features and variability in scene illumination. This article proposes an unsupervised pipeline that combines recent advances in hyperspectral machine learning to map minerals on a mine face without annotated training data. The pipeline produces a superior map and demonstrates consistent mapping capability using data acquired at different times of day.
GEOSCIENCE FRONTIERS
(2023)
Article
Geochemistry & Geophysics
Ntshiri Batlile Tsae, Tsuyoshi Adachi, Youhei Kawamura
Summary: Accurate prediction of ore grade is crucial in various mining activities. Conventional methods often fail to capture the complexity of orebodies, resulting in incorrect estimations and costly decisions. In this study, an artificial neural network (ANN) model was proposed and evaluated using performance metrics such as MAE, MSE, RMSE, R, and R-2. The ANN model outperformed traditional machine learning methods with high accuracy. The feature importance analysis showed that lithology had the highest influence on grade prediction. This approach holds promise for ore grade estimation.
Review
Environmental Studies
Pritam Biswas, Rabindra Kumar Sinha, Phalguni Sen
Summary: In terms of global mining, most non-metallic minerals (95%), metallic minerals (90%), and coal (about 60%) are extracted through surface mining methods. It is crucial to accurately identify ore and waste elements due to the grade-tonnage distribution in mining operations. With the expected increase in global population from 8 billion in 2022 to over 9.7 billion in 2050, along with a yearly 3.2% increase in metal consumption, the optimization of cut-off grade (COG) is key to ensure a continuous supply of minerals and maximize resource recovery.
Article
Geosciences, Multidisciplinary
Farzad Sotoudeh, Micah Nehring, Mehmet Kizil, Peter Knights, Amin Mousavi
Summary: The mining industry is facing challenges of lower grades and cost reduction, leading to increased exploration of underground deposits. Integrating pre-concentration systems into underground mining can greatly improve operational efficiency and sustainability. A new mathematical formulation for determining underground cut-off grade shows economic potential in reducing grade and increasing NPV.
NATURAL RESOURCES RESEARCH
(2021)
Article
Environmental Studies
Tom Ogwang, Frank Vanclay
Summary: The investigation of the Uganda section of the East African Crude Oil Pipeline (EACOP) focused on the social and livelihood impacts of land acquisition. Although the pipeline construction had not yet started by late 2020, the route planning and land acquisition had already caused various environmental and social impacts, including displacement, disputed valuations, delayed compensation, and livelihood disruption. The project potentially offers benefits such as employment opportunities, improved infrastructure, and oil revenue to the nation, but delays have worsened anxiety and livelihood impacts.
ENERGY RESEARCH & SOCIAL SCIENCE
(2021)
Article
Engineering, Chemical
Nikhil Dhawan, Ubaid Manzoor, Shrey Agrawal
Summary: This study investigates the hydrogen reduction of low-grade iron ore to improve its metallization degree. The temperature and time were found to have significant effects on the reduction rate, while the flow rate and particle size had minimal effects. The optimal conditions for high saturation magnetization and reduction rate were found to be a temperature of 600 degrees C, a time of 60 minutes, a hydrogen flow rate of 0.5 LPM, and a particle size of 3.3 x 2 mm.
MINERALS ENGINEERING
(2022)
Article
Computer Science, Information Systems
Xunhong Wang, Yonglin Tan, Lan Yang
Summary: This research considered both the technical indicators and the spatial distribution of ore grade in optimizing metal mine production, and applied an adaptive differential evolution algorithm for optimization. Experimental results showed that compared to other algorithms, this model had better convergence rate and global search ability in optimizing the technical indicators of metal mine production.
Article
Engineering, Chemical
Wissam Muhsin, Jie Zhang
Summary: This paper presents a data-driven multi-objective optimization method for crude oil hydrotreating process and distillation unit. By utilizing bootstrap aggregated neural networks, reliable data-driven models are developed, and the widths of model prediction confidence bounds are minimized as additional objectives in the optimization process. The proposed method is validated using Aspen HYSYS simulation, demonstrating its effectiveness.
Article
Geochemistry & Geophysics
Fabrizzio Rodrigues Costa, Cleyton de Carvalho Carneiro, Carina Ulsen
Summary: In a multivariate database, missing data can be obtained through several imputation techniques, particularly useful for difficult-to-obtain data or data with high uncertainties or scarce variables. A Self-Organizing Maps (SOM) neural network was used for imputation in this study, and the performance was evaluated using drilling data. The results showed determination coefficients of 85% and 93% when 50% and 10% of the data were omitted, respectively.
Article
Agronomy
Zhen-Zhen Li, Fei Deng, Chi Zhang, Li Zhu, Lian-Hua He, Tao Zhou, Hui Lu, Shi-Lin Zhu, Yu-Ling Zeng, Xiao-Yuan Zhong, Wei Zhou, Yong Chen, Wan-Jun Ren, Jian-Feng Hu
Summary: A simple and low-cost index, called relative culm wall thickness (RCWT), is proposed to evaluate the lodging resistance of rice. Through a field experiment, RCWT was found to be significantly correlated with various lodging-related indexes. Rice plants with high RCWT were characterized by lower plant height and center of gravity, as well as shorter basal internodes, thicker culm wall thickness, and smaller pith diameter. These features increased the fullness of the stem, resulting in higher cellulose and lignin content, enhanced bending resistance, and decreased lodging index.
ARCHIVES OF AGRONOMY AND SOIL SCIENCE
(2023)
Article
Biochemistry & Molecular Biology
Yuhua Fu, Hong Liu, Jingwen Dou, Yue Wang, Yong Liao, Xin Huang, Zhenshuang Tang, JingYa Xu, Dong Yin, Shilin Zhu, Yangfan Liu, Xiong Shen, Hengyi Liu, Jiaqi Liu, Xin Yang, Yi Zhang, Yue Xiang, Jingjin Li, Zhuqing Zheng, Yunxia Zhao, Yunlong Ma, Haiyan Wang, Xiaoyong Du, Shengsong Xie, Xuewen Xu, Haohao Zhang, Lilin Yin, Mengjin Zhu, Mei Yu, Xinyun Li, Xiaolei Liu, Shuhong Zhao
Summary: IAnimal is a cross-species, multi-omics knowledgebase that aims to improve the utilization of multi-omics data and simplify data integration for better understanding of gene regulation mechanisms and comprehensive analyses of biological systems.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Engineering, Chemical
Hongli Zhang, Yiling Zheng, Hongwei Zhou, Shilin Zhu, Jie Yang
Summary: Two-dimensional (2D) nanomaterial-based membranes hold great promise for various applications due to their attractive properties in molecular separation and transport. However, the swelling problem of 2D membranes has hindered their performance. In this study, the insertion of flexible and hydrophilic carboxylated cellulose nanofibers (CNFs) effectively stabilized the Ti3C2Tx MXene laminar architecture, enhancing mechanical strength, fixing interlayer distance, and improving anti-swelling properties. Furthermore, the intercalation of nanocelluloses increased interlayer spacing and created open gaps for fast and selective molecular transport. When applied in antibiotics separative filtration process, the resulting membrane exhibited excellent anti-swelling properties and high selectivity of antibiotics, making it ideal for various applications.
SEPARATION AND PURIFICATION TECHNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Xin Guo, Hong Zhao, Xiaohu Qiang, Chengwei Ouyang, Zhehui Wang, Dajian Huang
Summary: Biomass-based aerogel materials have great development potential in packaging, cushioning and green building insulation due to their low thermal conductivity and non-toxicity. However, their application is limited by low mechanical strength and poor fire safety. This study developed a composite aerogel modified by the magnesium hydroxide/sodium alginate composite flame retardant system, which significantly enhanced mechanical and thermal stability. The composite showed improved fire resistance and achieved a more complete carbon structure after burning.
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
(2023)
Review
Physics, Multidisciplinary
Hua-Xing Chen, Wei Chen, Xiang Liu, Yan-Rui Liu, Shi-Lin Zhu
Summary: The past decades have seen significant advancements in hadron physics, particularly in the observation of excited open heavy flavor mesons and baryons since 2017. This review provides updated information on the recent experimental and theoretical developments in this field, including the observation of unconventional heavy hadrons, tetraquark states, and hidden heavy flavor multiquark states. Additionally, the review covers progress in understanding glueballs and light hybrid mesons, which are manifestations of the non-Abelian SU(3) gauge interaction in Quantum Chromodynamics at low energies.
REPORTS ON PROGRESS IN PHYSICS
(2023)
Review
Environmental Sciences
Tong Wu, Shan-Shan Yang, Le Zhong, Ji-Wei Pang, Luyan Zhang, Xue-Fen Xia, Fan Yang, Guo-Jun Xie, Bing-Feng Liu, Nan-Qi Ren, Jie Ding
Summary: This paper provides a comprehensive review of studies on simultaneous nitrogen and phosphorus removal. The most promising process is found to be simultaneous nitrification, denitrification, and phosphorus removal (SNDPR). Factors influencing SNDPR are analyzed and future research directions are suggested, including balancing microbial competition, achieving continuous flow operation, and maximizing phosphorus recovery.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Green & Sustainable Science & Technology
Yong He, Zhiyu Lai, Nuo Liao
Summary: Evaluating the effect of low-carbon city pilot (LCCP) policy on urban air pollutant PM2.5 is important for urban ecological construction. This study used China's prefecture-level panel data and the difference-in-difference model to assess the impact of LCCP policy on urban PM2.5, considering the heterogeneity of the policy effect based on urban resource endowment and industrial characteristics. The results revealed that the LCCP policy significantly reduced urban PM2.5, with varying effects observed in different types of cities.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Mathematics
Guosheng Jiang, Zhehui Wang, Jintian Zhu
Summary: In this study, we investigate the minimal surface equation in the unbounded convex domain 12 C Rn (n >= 2) with boundary value given by the sum of a linear function and a bounded uniformly continuous function in Rn. We prove that the solution is unique if 12 is not a half space and the graphs of all solutions form a foliation of 12 x R if 12 is a half space. This result can be considered as a stability type theorem for Edelen-Wang's Bernstein type theorem in [10]. Additionally, we establish a comparison principle for the minimal surface equation in 12.
JOURNAL OF FUNCTIONAL ANALYSIS
(2023)
Article
Physics, Fluids & Plasmas
Y. C. Hu, L. Ye, X. Z. Gong, A. M. Garofalo, J. P. Qian, J. Huang, B. Zhang, P. F. Zhao, Y. J. Hu, Q. L. Ren, J. Y. Zhang, X. X. Zhang, R. R. Liang, Z. H. Wang
Summary: The properties of core turbulence and thermal transport are investigated for EAST high-beta(P) plasmas with dominant electron heating via gyrokinetic simulation. Linear simulations demonstrate the dominance of electrostatic eta(e)-driven trapped electron mode in the core region and the ion temperature gradient mode in the outer region, consistent with linear threshold analysis. Nonlinear simulations show that the electron thermal internal transport barrier in EAST high-beta(P) plasma is determined by the TEM-induced turbulence. A higher zonal flow shearing rate facilitates the formation of e-ITB.
PLASMA PHYSICS AND CONTROLLED FUSION
(2023)
Proceedings Paper
Physics, Particles & Fields
Bo Wang, Lu Meng, Shi-Lin Zhu
Summary: In this study, we investigated di-hadron interactions including D (D) over bar*/D*(D) over bar, D*(D) over bar, DsD*/D*D-s, BB*/BB* and B*B* in chiral effective field theory (chi EFT) up to next-to-leading (NLO) order. The tetraquark states Z(c)(3900), Z(c)(4020), Z(cs)(3985), Z(b)(10610), Z(b)(10650) above threshold can be explained as corresponding di-hadron resonances. We also studied the interactions of Sigma(()(c)*) (D) over bar(*) to investigate the three hidden-charm pentaquarks Pc(4312), Pc(4440) and Pc(4457). Using the parameters fixed from the Pc states, we predicted possible molecular states in Xi D-c* Xi cD* and Xi & lowast; c recently observed by the LHCb Collaboration. Our predictions of the Xi D-c(*) bound states are in good agreement with two new near-threshold structures.
NUCLEAR AND PARTICLE PHYSICS PROCEEDINGS
(2023)
Article
Public, Environmental & Occupational Health
Yuncong He, Leonardo Martinez, Yang Ge, Yan Feng, Yewen Chen, Jianbin Tan, Adrianna Westbrook, Changwei Li, Wei Cheng, Feng Ling, Huimin Cheng, Shushan Wu, Wenxuan Zhong, Andreas Handel, Hui Huang, Jimin Sun, Ye Shen
Summary: SARS-CoV-2 spreads quickly among humans through social networks, and social mixing and network characteristics may facilitate transmission. Limited data on network structural features has hindered in-depth studies, but comparing network characteristics over time can provide additional insights into transmission dynamics.
EPIDEMIOLOGY AND INFECTION
(2023)
Article
Thermodynamics
Yong He, Ruipeng Jiang, Nuo Liao
Summary: The Chinese Certified Emission Reduction (CCER) scheme is of great significance for China to achieve its dual carbon targets. A tripartite evolutionary game model is constructed to analyze the evolutionary stability of each subject's strategy choice. The results show that strict government regulation, proper pricing, penalties, and subsidies can promote the development of CCER projects in the carbon market.
Article
Astronomy & Astrophysics
Jian-Bo Cheng, Du-xin Zheng, Zi-Yang Lin, Shi-Lin Zhu
Summary: We investigate the double-charm and hidden-charm hexaquarks as molecular states using the one-boson-exchange potential model. We consider multichannel coupling and S-D wave mixing and use the complex scaling method to study quasibound states. We find a quasibound state in the double-charm system, but not in the hidden-charm system.
Article
Physics, Particles & Fields
Bo-Lin Huang, Zi-Yang Lin, Kan Chen, Shi-Lin Zhu
Summary: We calculate the complete T matrices of elastic light pseudoscalar meson and heavy meson scattering to the third order in heavy meson chiral perturbation theory. We determine the low-energy constants by fitting the phase shifts and scattering lengths from lattice QCD simulations simultaneously, and predict the phase shifts at the physical meson masses. The strong phase shifts in various channels suggest the presence of bound states or resonances, including the well-known exotic state D-s0*(2317).
EUROPEAN PHYSICAL JOURNAL C
(2023)
Article
Astronomy & Astrophysics
Lu Meng, Bo Wang, Shi-Lin Zhu
Summary: The LHCb Collaboration has recently observed the first hidden-charm pentaquark with strangeness, P?,yso4338 thorn 0. The state is close to the Xi 0c over bar D0 and Xi thorn c D- thresholds, raising concerns about the bias of the Breit-Wigner parametrization and its coupling to these double thresholds. Through qualitative and formalism-based analyses, it is shown that the peak of P?,yso4338 thorn 0 could originate from either an o-; thorn thorn sheet pole above the Xi thorn c D- threshold or an o-; - thorn sheet pole below the Xi 0c over bar D0 threshold. The authors suggest a refined experimental analysis considering unitarity and analyticity.
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
