Article
Management
Faycal A. Touzout, Anne-Laure Ladier, Khaled Hadj-Hamou
Summary: This paper investigates a variant of the Inventory Routing Problem called the Time-Dependent IRP. By considering time-dependent travelling time functions, the optimization results are cost-efficient but computationally challenging. A proposed solution based on the observation of the structure of optimal solutions proves to be efficient in numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Ruyang Yin, Peixia Lu
Summary: This study proposes a cluster-first route-second constructive heuristic method based on the continuous approximation for emergency logistics scheduling problems. The method simplifies the problem by transforming the vehicle routing problem into a travel salesman problem, and uses continuous approximation and the Christofides method to determine the optimal replenish schedule and routing solution. The results show that the local-based clustering method may have a lower total cost but higher motion cost.
Article
Management
Marco Casazza, Alberto Ceselli, Roberto Wolfler Calvo
Summary: The paper addresses a single commodity Pickup and Delivery Vehicle Routing Problem and proposes new theoretical insights and algorithms to mitigate the combinatorial explosion of feasible solutions by decomposing routes into sequences of simpler substructures. Experimental analysis shows that the method offers more modeling flexibility and computational effectiveness than previous attempts from the literature.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Management
Sarah K. Schaumann, Felix M. Bergmann, Stephan M. Wagner, Matthias Winkenbach
Summary: In this paper, the authors analyze the route efficiency effects of combining first-mile pickup and last-mile delivery operations. They examine the impact of time window constraints and vehicle capacity constraints, and propose adjustment factors to accurately capture these effects. The study suggests that these constraints can diminish or eliminate the expected efficiency gains from integrating pickup and delivery operations. The proposed adjustment factors are important for the strategic design and operational planning of modern distribution networks in the e-commerce industry.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Nursing
Miranda Squire, Karen Hessler
Summary: This study examines workplace violence from the perspective of nurses and nursing assistants who have experienced violent encounters with patients or visitors. The study reveals that these healthcare workers often face verbal abuse and physical violence, putting their safety at risk. The findings highlight the need for improved prevention strategies and response policies to address patient-initiated workplace violence.
AMERICAN JOURNAL OF NURSING
(2023)
Article
Operations Research & Management Science
Bismark Singh, Lena Oberfichtner, Sergey Ivliev
Summary: Motivated by a routing problem faced by banks, this study proposes a solution to the clustering version of the traveling salesman problem. Through a short survey of 13 heuristics and empirical analysis using data from Perm, the study provides statistical guarantees on the quality of the solution.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Nastaran Oladzad-Abbasabady, Reza Tavakkoli-Moghaddam
Summary: This paper presents a two-stage mathematical formulation to solve the Home Health Care Routing-Scheduling Problem (HHCRSP) over a planning horizon of multiple days. The study takes into consideration skill requirements, unexpected events, and caregiver-patient compatibility. A case study at a health center in Tehran is used to assess the validity of the proposed model and analyze the relationship between objectives and structural parameters.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Engineering, Manufacturing
Stanley Frederick W. T. Lim, Qingchen Wang, Scott Webster
Summary: Up to 20% of business-to-consumer deliveries fail on the first attempt, causing both cost implications and damage to retailers' brand reputation. This study fills the research gap by predicting failed delivery attempts using common attributes and demonstrates the importance of accounting for them in routing models. The analysis shows that not considering the probability of failed attempts may result in a significant bias in the total cost of delivery, and manipulating the delivery sequence can greatly impact the outcomes.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Environmental Sciences
Johanna Kohler, Mauvis Gore, Rupert Ormond, Timothy Austin
Summary: The study assessed the population size and individual home range of sharks using photo identification as a non-invasive alternative to tagging. The results showed that there were twice as many nurse sharks as Caribbean reef sharks in the Cayman Islands. The research also highlighted the need for better protection measures as the sharks' home ranges extend beyond marine protected areas.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Pediatrics
Astrid Batlle, Imma Boada, Santiago Thio-Henestrosa, Mariona Fernandez de Sevilla, Juan Jose Garcia-Garcia
Summary: This study aimed to compare the effectiveness of traditional manual route planning with a route optimizer in a pediatric acute home-hospitalization program. The results showed that route-planning technology saved planning time, generated better plans, and was easy to use. All participants had a positive evaluation of the route planning tool.
FRONTIERS IN PEDIATRICS
(2022)
Article
Management
Fabian Castano, Nubia Velasco
Summary: This paper proposes a mathematical model based on directed acyclic graphs to minimize personnel required for home health-care services. Results show efficient solutions for medium-sized instances up to 100 daily patient requests. The model allows for realistic characteristics and can be applied to other real-life applications.
INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT
(2021)
Article
Geriatrics & Gerontology
Jorunn Drageset, Gorill Haugan
Summary: Loneliness is common among cognitively intact nursing home residents. Nurse-patient interaction is associated with residents' loneliness, indicating that nurse interaction might play an important role in alleviating loneliness.
Article
Environmental Sciences
John P. A. Ioannidis, Cathrine Axfors, Despina G. Contopoulos-Ioannidis
Summary: In the examined countries, the age distribution of COVID-19 deaths was similar in the second wave compared to the first wave, but the contribution of COVID-19 deaths in nursing home residents to total fatalities decreased in most countries in the second wave.
ENVIRONMENTAL RESEARCH
(2021)
Article
Computer Science, Information Systems
Maryam Zolnoori, Sridevi Sridharan, Ali Zolnour, Sasha Vergez, Margaret McDonald, Zoran Kostic, Kathryn H. Bowles, Maxim Topaz
Summary: This study investigates the added value of integrating audio-recorded home healthcare patient-nurse verbal communication into a risk identification model. The findings demonstrate that incorporating verbal communication improves the accuracy of predicting hospitalizations and emergency department visits.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Article
Automation & Control Systems
Giulio Galvan, Matteo Lapucci, Chih-Jen Lin, Marco Sciandrone
Summary: This work introduces a novel way to solve sub-problems in SVM training, proving its effectiveness and efficiency in handling sub-problems with up to 50 variables. Additionally, it explores different ways to select the working set, showing that the method outperforms current software.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Management
Vittorio Nicoletta, Alessandra Guglielmi, Angel Ruiz, Valerie Belanger, Ettore Lanzarone
Summary: This study presents a Bayesian approach for predicting the number of emergency calls in ambulance service, achieving good predictive accuracy and computational efficiency through areal data modeling.
IMA JOURNAL OF MANAGEMENT MATHEMATICS
(2022)
Article
Engineering, Multidisciplinary
Semih Yalcindag, Ettore Lanzarone
Summary: Home Health Care human resource management is a complex process that needs to consider the evolution of patient demands and continuity of care. In balancing and integrating the operator-to-patient assignment problem between short-term planning and long-term perspective.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2022)
Article
Chemistry, Multidisciplinary
Elisa Scalco, Alfonso Mastropietro, Giovanna Rizzo, Ettore Lanzarone
Summary: This paper presents an improved IVIM model fitting method that combines clustering and CAR model, which can provide more reliable estimation of IVIM coefficients.
APPLIED SCIENCES-BASEL
(2022)
Review
Surgery
Giovanni Spinella, Alice Finotello, Fabio Riccardo Pisa, Michele Conti, Giovanni Pratesi, Bianca Pane, Ettore Lanzarone
Summary: This study aimed to review the available literature on different reperfusion methods for thoracoabdominal aortic aneurysm (TAAA) and analyze their effectiveness in reducing the risk of spinal cord ischemia (SCI). The analysis of 53 studies with 3095 patients showed that both type B and type C endovascular treatments are associated with a lower risk of SCI, with type C showing a greater reduction compared to type B, particularly in younger patients. Other factors such as a greater aortic diameter, a reduced aneurysm extent, and the absence of cerebrospinal fluid drainage positioning also contribute to lowering the risk of SCI. Staged endovascular treatment appears to offer advantages over single-step treatment in reducing the risk of SCI, regardless of the reperfusion method adopted.
JOURNAL OF ENDOVASCULAR THERAPY
(2023)
Article
Engineering, Biomedical
Michela Bozzetto, Luca Soliveri, Jessica Volpi, Andrea Remuzzi, Antonio Barbieri, Luigi A. A. Lanterna, Ettore Lanzarone
Summary: The feasibility of using CFD simulations to predict postoperative blood flow scenarios in the treatment of complex intracranial aneurysms was assessed. The study found that CFD modeling can provide valuable additional information for surgical planning.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
(2023)
Article
Engineering, Industrial
Alberto Loffredo, Nicla Frigerio, Ettore Lanzarone, Andrea Matta
Summary: Nowadays, there is a growing interest in improving the sustainability of manufacturing processes in the industry. One strategy that is widely supported is the energy-efficient control of machine state to find the optimal balance between production rate and energy demand. This article focuses on multi-stage production lines and proposes a novel approach using buffer level information to minimize energy demand while meeting production constraints. The effectiveness of the approach is confirmed through numerical experiments.
Article
Computer Science, Interdisciplinary Applications
Fabiola Regis-Hernandez, Ettore Lanzarone, Valerie Belanger, Angel Ruiz
Summary: This paper proposes an integrated approach to address the interrelated problems of districting and resource allocation. It focuses on the importance of districting decisions in the context of Emergency Medical Services. An iterative algorithm is proposed to jointly solve the districting and resource allocation problems, aiming to build compact and balanced districts and maximize the system's response time. Realistic instances inspired by Montreal, Canada, show that the algorithm improves both the expected response time and the quality of the districts.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Peripheral Vascular Disease
Martina Doneda, Sofia Poloni, Michela Bozzetto, Andrea Remuzzi, Ettore Lanzarone
Summary: This study used machine learning to predict blood flow volumes and vessel diameters of AVF, providing physicians with fast and accurate patient-specific predictions for AVF surgical planning decisions, aiming to improve the success rate of vascular access.
JOURNAL OF VASCULAR ACCESS
(2023)
Article
Cardiac & Cardiovascular Systems
Ettore Lanzarone, Claudia Baratto, Marco Vicenzi, Francesco Villella, Irene Rota, Celine Dewachter, Denisa Muraru, Michele Tomaselli, Mara Gavazzoni, Luigi P. Badano, Michele Senni, Jean-Luc Vachiery, Gianfranco Parati, Sergio Caravita
Summary: The HFA-PEFF algorithm is a three-step algorithm used to diagnose heart failure with preserved ejection fraction (HFpEF). It provides a likelihood score for HFpEF and includes echocardiography and natriuretic peptide levels. This study aimed to validate the algorithm against a haemodynamic diagnosis of HFpEF.
Article
Psychology, Biological
Martina Doneda, Virginia Maria Borsa, Agostino Brugnera, Angelo Compare, Maria Luisa Rusconi, Kaoru Sakatani, Ettore Lanzarone
Summary: This study investigated the impact of resting-state and task-related physiological and psychological variables on the prediction of cognitive task performance in young adults. The results showed that perfectionistic traits and autonomic and cortical activity predicted performance for most tasks.
JOURNAL OF PSYCHOPHYSIOLOGY
(2023)
Article
Engineering, Industrial
Ilenia Epifani, Ettore Lanzarone, Alessandra Guglielmi
Summary: Donor profiling and donation prediction are important tasks for blood collection centers. We propose a Bayesian model that describes the intensity function of blood donation events based on individual donor's characteristics. Our method has been validated using data from Italy and can be applied to other blood collection centers.
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL
(2023)
Article
Engineering, Industrial
Martina Doneda, Semih Yalcindag, Ettore Lanzarone
Summary: In Western countries, the management of blood collection in the Blood Donation Supply Chain (BDSC) is understudied compared to other echelons. This study proposes a new model for blood collection that allows for blood to be collected at donor's homes, addressing the need for delocalization of health services. A decision support tool is also provided, including a planning model, online allocation, and a vehicle routing problem to optimize bloodmobile routes. The tool has been successfully tested on real data and can provide effective and economically sustainable solutions.
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL
(2023)
Article
Medicine, General & Internal
Laura Giroletti, Valentina Brembilla, Ascanio Graniero, Giovanni Albano, Nicola Villari, Claudio Roscitano, Matteo Parrinello, Valentina Grazioli, Ettore Lanzarone, Alfonso Agnino
Summary: The study investigated the impact of COVID-19 on the learning curve of robotic-assisted mitral valve surgery, showing a positive impact of the learning curve on postoperative parameters and no significant effect of COVID-19 on postoperative outcomes.
MEDICINA-LITHUANIA
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Federico Bonacorsi, Serena Capelli, Fabio Locatelli, Mattia Todeschini, Stefania Marconi, Andrea Vitali, Ettore Lanzarone
Summary: The 3DSCT platform is an effective solution that simplifies the 3D printing process within hospitals, improving efficiency and reducing time wastage.
DHEALTH 2022-PROCEEDINGS OF THE 16TH HEALTH INFORMATICS MEETS DIGITAL HEALTH CONFERENCE
(2022)
Article
Biochemical Research Methods
Liliana Ironi, Ettore Lanzarone
Summary: Computational and mathematical models are essential for the analysis and design of Gene Regulatory Networks (GRN). This paper proposes a framework using nonlinear and temporal multiscale Ordinary Differential Equations (ODE) to model network dynamics. The paper also introduces algorithms to refine parameters and demonstrates the effectiveness of the approach on benchmark synthetic networks.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
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)