Artificial intelligence applications in healthcare supply chain networks under disaster conditions

International Journal of Production Research, Год журнала: 2025, Номер 63(2), С. 395 - 403

Опубликована: Янв. 17, 2025

Язык: Английский

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Welfare-oriented and public health-aware disaster sheltering network design

International Journal of Production Research, Год журнала: 2025, Номер unknown, С. 1 - 27

Опубликована: Янв. 22, 2025

While evacuation along with opening public shelters is vital to save the lives of disaster survivors, many them run risk refusing thereby jeopardising their safety. The primary reason for taking such a inferior conditions commonly experienced in shelters, including noise crowds, constant lighting, privacy concerns, and safety apprehensions, combined absence other viable sheltering options. Moreover, potential transmission infectious diseases, as tuberculosis COVID-19, deters victims further from seeking refuge these shelters. In this study, we propose four-echelon network design allow small capacity that can enhance welfare health. A two-stage stochastic mixed-integer linear programming model formulated optimise selection nodes each four echelons under different scenarios, addition determining logistical operations. This considers tradeoff between maximising total welfare-enhanced occupancy minimising associated costs. novel problem-specific scenario-based cutting-plane algorithm developed efficiently solve while providing practical advantages. effectiveness our approach demonstrated through case study Texas – most disaster-prone state United States.

Язык: Английский

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Optimization of Kubernetes for the High-Performance Computing with Kubernetes, Performance Analysis, and Dynamic Workload Placement toward the Enhancement of Cloud Computing

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Transforming Supply Chain Performance Based on Electronic Data Interchange (EDI) Integration: A Detailed Analysis

Deleted Journal, Год журнала: 2025, Номер 3(2), С. 25 - 40

Опубликована: Март 1, 2025

EDI currently remains one of the most significant technological formats that respond to contemporary rapid and connected business environment by ensuring real-time, efficient accurate data exchange in supply chain management. This paper's central idea is evolution from early days standard trade papers technologies like blockchain, AI, ML, IoT. Focusing on processes where these innovations add value for EDI, providing real-time data, improving security, facilitating better decisions, this paper emphasises essential functions modernisation chains. In addition, it examines how integration can help minimise cost; manage stocks; enhance associations. Altogether, showcases EDI’s positive effects performance-enhancing aspects outlines prospective applications novel further global processes.

Язык: Английский

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An Enhanced IDBO-CNN-BiLSTM Model for Sentiment Analysis of Natural Disaster Tweets

Biomimetics, Год журнала: 2024, Номер 9(9), С. 533 - 533

Опубликована: Сен. 4, 2024

The Internet's development has prompted social media to become an essential channel for disseminating disaster-related information. Increasing the accuracy of emotional polarity recognition in tweets is conducive government or rescue organizations understanding public's demands and responding appropriately. Existing sentiment analysis models have some limitations applicability. Therefore, this research proposes IDBO-CNN-BiLSTM model combining swarm intelligence optimization algorithm deep learning methods. First, Dung Beetle Optimization (DBO) improved by adopting Latin hypercube sampling, integrating Osprey Algorithm (OOA), introducing adaptive Gaussian-Cauchy mixture mutation disturbance. DBO (IDBO) then utilized optimize Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) model's hyperparameters. Finally, constructed classify tendencies associated with Hurricane Harvey event. empirical indicates that proposed achieves 0.8033, outperforming other single hybrid models. In contrast GWO, WOA, algorithms, enhanced 2.89%, 2.82%, 2.72%, respectively. This study proves can be applied assist emergency decision-making natural disasters.

Язык: Английский

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Enhancing supply chain performance by integrating knowledge management and lean, agile, resilient, and green paradigms

Journal of Management Analytics, Год журнала: 2024, Номер unknown, С. 1 - 32

Опубликована: Окт. 7, 2024

Due to global market competition, there is an increasing emphasis on utilizing lean, agile, resilient, and green (LARG) paradigms improve Supply Chain (SC) performance. Furthermore, as technology advances, Knowledge Management (KM) essential in improving SC performance through information sharing, processes, coordination collaboration. Thus, this research proposes a novel approach integrating KM with LARG enhance Also, the decision framework presented using Multi-Criteria Decision-Making (MCDM) approaches, including Grey Step-wise Weight Assessment Ratio Analysis (SWARA-G) Measurement of Alternatives Ranking according Compromise Solution (MARCOS-G) method. The implemented automobile enterprise findings indicated that building collaboration efficiency, facilitate operations, reduce communication exchange costs was introduced most critical strategy automotive industry.

Язык: Английский

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An efficient data fusion model based on Bayesian model averaging for robust water quality prediction using deep learning strategies

Expert Systems with Applications, Год журнала: 2024, Номер 261, С. 125499 - 125499

Опубликована: Окт. 15, 2024

Язык: Английский

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Integrating Smart IoT and AI-Enhanced Systems for Predictive Diagnostics Disease in Healthcare

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Год журнала: 2024, Номер 10(6), С. 2093 - 2105

Опубликована: Дек. 26, 2024

A developing technology known as the IoT allows for connectivity of seemingly innocuous gadgets to web. The has linked millions sensors and smart devices, which transformed healthcare sector. devices driven by AI can identify diabetes continuously gathering accurate glucose values. This study addresses critical need early detection using advanced ML algorithms, leveraging Pima Indian Diabetes Dataset. An accuracy diagnosing non-diabetic cases is evaluated compared in this models such CNN, XG-Boost, DT, SVM. Show that model may improve diagnostic facilitate intervention conducting a thorough performance evaluation utilising confusion matrices measures like recall, accuracy, precision, F1-score. CNN demonstrates superior 99% with high precision 98% recall rates 99.9%, positioning it most effective study. findings underscore feasibility DL approaches data analysis, contributing improved outcomes diagnostics.

Язык: Английский

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Healthcare Supply Chain Resilience Investment Strategy Analysis Based on Evolutionary Game

Symmetry, Год журнала: 2024, Номер 16(7), С. 787 - 787

Опубликована: Июнь 22, 2024

Healthcare is considered one of the necessities for sustaining life. However, frequent emergencies raise risk supply chain disruption, seriously threatening people’s lives and health security. Therefore, building a resilient healthcare an important initiative to manage crisis effectively. Based on secondary formed by medical manufacturers retailers, this paper constructs evolution game model resilience investment decisions under non-disruption disruption symmetry scenarios analyzes stabilization strategies employed both parties based their asymmetry strategy choices. Subsequently, numerical simulation used analyze impact various parameters evolutionary results trends. The study show that additional benefits from investment, potential costs, losses, market encroachment revenue, “free-rider” benefits, benefit increase coefficient, reduction loss unit cost revenue coefficient all influence decisions. Finally, results, specific recommendations are formulated improve chain.

Язык: Английский

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Advanced Methods for Verifying Memory Controllers in Modern Computing Systems

International Journal of Advanced Research in Science Communication and Technology, Год журнала: 2024, Номер unknown, С. 377 - 388

Опубликована: Окт. 16, 2024

The primary component of the computer system that requires enhancement is memory's performance. A memory controller helps in management control between as well processor. This study gives a general outline how performance systems based on power converters may be improved using AI approaches. Among many uses for today's electrical and energy are effective conversion electric cars, renewable sources, industrial automation, among others. Complementary strategies used classical approaches, although work well, experience difficulties when it comes to complication, change, unpredictability. To overcome these restrictions, artificial intelligence methods appear rather prospective. types one can distinguish neural networks, fuzzy logic, machine learning help with enhanced efficiency by adaptive intelligent control. These approaches enhance precision, succession, reaction time effectiveness dependability. Moreover, this integration enhances most making easier predict maintenance, detect faults, optimise hence enhancing systems. paper presents new trends advanced smart converters, total techniques, advantages challenges posed strategies. It also describes future research areas achieving converter-based through Control techniques

Язык: Английский

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