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Analyzing Barriers in Adoption of Artificial Intelligence for Resilient Health Care Services to Society

Global Journal of Flexible systems management 2024年第1期25卷 179-197页

作者： Kumar, Girish Singh, Rajesh Kumar Arya, Vedpal Mishra, Shivam Kumar Department of Mechanical Engineering Delhi Technological University Delhi 110042 India Management Development Institute (MDI) Gurgaon India Department of Industrial Systems Engineering and Management National University of Singapore Singapore Singapore

Artificial intelligence (AI) is emerging as an alternative solution in the healthcare sector, offering opportunities to enhance efficiency and optimize the utilization of precious resources. The nascent stage of AI application in the Indian healthcare sector has gained momentum during COVID-19, witnessing a surge in AI-based startups and companies specializing in diagnostic and prescriptive healthcare. This paper systematically analyzes barriers to AI application in the Indian context, incorporating the concept of flexibility, and proposes insights for fostering its adoption for resilient and sustainable healthcare practices. The identified barriers are drawn from literature and experts’ inputs. These are further investigated using the decision-making trial and evaluation and laboratory methodology. This analysis not only categorizes barriers into cause-and-effect groups but also emphasizes the need for flexibility to adapt AI solutions to the dynamic healthcare sector. The paper underscores foundational barriers, including inadequate regulations, lack of awareness, high adaptation costs, and a scarcity of skilled AI expertise. In addition to managerial and social implications concerning regulation, implementation, economic viability, and data privacy, the study promotes flexibility as a key factor in addressing the evolving challenges in healthcare. © The Author(s) under exclusive licence to Global Institute of Flexible systems management 2024.

关键词： Artificial intelligence Barriers DEMATEL Flexibility Healthcare Resilience Sustainability

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Distributed Energy and Reserve Scheduling in Local Energy Communities Using L-BFGS Optimization

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CSEE Journal of Power and Energy systems 2024年第3期10卷 942-952页

作者： Mohammad Dolatabadi Alireza Zakariazadeh Alberto Borghetti Pierluigi Siano Department of Management&Innovation Systems University of SalernoSalernoItaly Department of Electrical Electronicand Information EngineeringUniversity of BolognaBolognaItaly University of Science and Technology of Mazandaran BehshahrIran Department of Power Systems National University of Science and Technology POLITEHNICA BucharestBucharestRomania IEEE

Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy *** energy communities(LECs)are expected to play a vital role in this ***,energy scheduling in LECs presents various challenges,including the preservation of customer privacy,adherence to distribution network constraints,and the management of computational *** paper introduces a novel approach for energy scheduling in renewable-based LECs using a decentralized optimization *** proposed approach uses the Limitedmemory Broyden–Fletcher–Goldfarb–Shanno(L-BFGS)method,significantly reducing the computational effort required for solving the mixed integer programming(MIP)*** incorporates network constraints,evaluates energy losses,and enables community participants to provide ancillary services like a regulation reserve to the grid *** assess its robustness and efficiency,the proposed approach is tested on an 84-bus radial distribution *** indicate that the proposed distributed approach not only matches the accuracy of the corresponding centralized model but also exhibits scalability and preserves participant privacy.

关键词： Distributed optimization flexibility services L-BFGS method local energy community renewables reserve

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Resilience indices from a family of recovery functions

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Fundamental Research 2024年第1期4卷 13-20页

作者： Loon Ching Tang Lijuan Shen Department of Industrial Systems Engineering and Management National University of Singapore117576 Singapore ETH Zurich Future Resilient SystemsSingapore-ETH Centre138602 Singapore

Defining and measuring resilience using a unified framework has been a topic of intense *** article presents a perspective on how resilience could be quantitatively assessed through a set of *** starts with a brief explanation of resilience in the context of supply chain and a quick summary of existing quantitative measures of *** then discusses how resilience could be quantified in a constructive manner so that the resulting metrics are representative of the performance throughout the system's life *** particular,it is proposed that resilience should be evaluated according to different time periods,***,during and after a disruption has *** dimensions of resilience,namely reliability,robustness,recovery and reconfigurability,can then be used to make up a set of indices for *** numerical illustration,these indices are computed based on recovery data arising from Hurricane Sandy in October ***,it is postulated that resilience will be the performance metric that complements productivity and sustainability as the third pillar for measuring success of organizations,and in turn,that of sovereign countries in their quests for developing smart cities.

关键词： systems resilience Recovery function Recovery index Robustness index Reconfigurability

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Machine Learning-Based Channel State Estimators for 5G Wireless Communication systems

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Computer Modeling in engineering & Sciences 2023年第4期135卷 755-778页

作者： Mohamed Hassan Essai Ali Fahad Alraddady Mo’ath Y.Al-Thunaibat Shaima Elnazer Department of Electrical Engineering Faculty of EngineeringAl-Azhar UniversityQena83513Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Management Information Systems Taif UniversityTaif21944Saudi Arabia

For a 5G wireless communication system,a convolutional deep neural network(CNN)is employed to synthesize a robust channel state estimator(CSE).The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state ***,it utilizes pilots to offer more helpful information about the communication *** proposedCNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory(BiLSTM/LSTM)NNs-based *** CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based *** three different loss function-based classification layers and the Adam optimization algorithm,a comparative study was conducted to assess the performance of the presented DNNs-based *** BiLSTM-CSE outperforms LSTM,CNN,conventional least squares(LS),and minimum mean square error(MMSE)*** addition,the computational and learning time complexities for DNN-CSEs are *** estimators are promising for 5G and future communication systems because they can analyze large amounts of data,discover statistical dependencies,learn correlations between features,and generalize the gotten knowledge.

关键词： DLNNs channel state estimator 5G and beyond communication systems robust loss functions

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Just-in-time and supply chain finance: a hierarchal model development

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International Journal of Industrial and systems engineering 2024年第4期47卷 518-556页

作者： Zaman, Syed Imran Ali, Md. Ramjan Khan, Sharfuddin Ahmed School of Economics and Management Southwest Jiaotong University China Department of Business Administration Jinnah University for Women Karachi Pakistan Department of Mechanical and Production Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh Industrial Systems Engineering Department Faculty of Engineering and Applied Sciences University of Regina SK Canada

This study aims to investigate whether or not just-in-time (JIT) and supply chain finance (SCF) have a synergistic impact on overall organisation performance. The purpose of this study is to help address this knowledge gap and shed light on the role that JIT tools plays in optimising the benefits that SCF offers to an organisation as a whole. Interpretive structural modelling (ISM) and decision making trial and evaluation laboratory (DEMATEL) has been used to explore relationship, contextual link and hierarchical interpretation between JIT and SCF characteristics. Results shows that, the variables with the highest rankings in ISM and DEMATEL are employee attitude, embeddedness of continuity practice, and changing level and position of inventory maintained by businesses. Integration of JIT and SCF will help organisations to increase in revenues, a reduction in waste, an improvement in cash flow, and a reduction in supply chain hazards. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Decision making

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High-precision CAD-based simulation for turning considering tool microgeometry

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International Journal of Mechatronics and Manufacturing systems 2023年第1期16卷 83-95页

作者： Tzotzis, Anastasios Tsagaris, Apostolos Tapoglou, Nikolaos Kyratsis, Panagiotis Department of Product and Systems Design Engineering University of Western Macedonia Kila Kozani50100 Greece Department of Industrial Engineering and Management International Hellenic University Sindos Thessaloniki57400 Greece

Surface roughness is considered to be a critical parameter when evaluating the machinability of a material, as well as the surface quality of a machined part. Thus, a number of studies exist in the literature, that deal with the simulation and prediction of the surface roughness generation during machining. This paper presents a 3D simulation method for turning, considering the full geometrical aspects of a cutting-tool, leading to high-precision simulation of the process. For the purposes of the study, a commercially available, generic CAD system was utilised, namely SolidWorks™. Specifically, the application programming interface (API) of the software was used, to write code that is capable of simulating the kinematics of the turning process. In addition, the surface roughness profile, topography, as well as typical measurements were generated, with respect to machining conditions such as, depth of cut, feed and cutting speed. For the verification of the accuracy of the code, a set of nine turning experiments were carried out, for a specified range of conditions. Finally, a comparison between the experimental and the simulated measurements for the Ra, Rz and Rt was made, showing an increased correlation. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Surface roughness

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Proposal of a Tourist Attractions' Introduction Creating Tool Using Deep Learning 16

Proposal of a Tourist Attractions' Introduction Creating Too...

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16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Hasuike, Takashi Liang, Youheng Katagiri, Hideki Tsuda, Hiroshi Waseda University Industrial and Management Systems Engineering Tokyo Japan Kanagawa University Department of Industrial Engineering and Management Kanagawa Japan Doshisha University Faculty of Science and Engineering Kyoto Japan

ISBN: (纸本)9798350377903

By describing images of tourist attractions from different angles and generating descriptions, it is expected to make them more easily searchable by users. In this study, a system, which automatically generates attractive descriptions and introductions of tourist attractions for landscape images, is constructed. The approach is to use convolutional neural networks (CNN), recurrent neural networks (RNN), and Transformer to create factual and sensory descriptions for images, and to use CNN to identify 30 tourist attractions and output introductions. The study considered the accuracy rate of identification by tourist attraction quantity, and automatic and subjective evaluation by the machine of the descriptions. The system can propose a system to create an attractive introduction and a text to introduce tourist attractions by combining facts and sensible descriptions from landscape images. © 2024 IEEE.

关键词： Adversarial machine learning

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Analysis of Energy Performances of Trombe Walls Varying the Main Construction Parameters

Analysis of Energy Performances of Trombe Walls Varying the ...

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2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024

作者： Cristaudo, Antonio Ferraro, Vittorio Nicoletti, Francesco Palermo, Giulia Kaliakatsos, Dimitrios University of Calabria Energy and Management Engineering Department CS Rende Italy University of Calabria Department of Computer Engineering Modeling Electronics and Systems Engineering CS Rende Italy

ISBN: (纸本)9798350385014

The energy transition represents an essential process necessary to drive a shift towards a sustainable and balanced human-environment interaction. Within the residential building sector, this obj ective can be pursued by promoting both the utilization of renewable sources and the energy efficiency improvement of technical systems and the building envelope. In this regard, this article conducts an energy analysis to assess the reduction in energy requirements achieved by installing two Trombe walls on the south-facing wall of the variable orientation test station at the University of Calabria. The two passive systems were symmetrically positioned on either side of the existing window system. The evaluation of monthly energy requirements during the heating period was performed using the dynamic simulation software DesignBuilder. To define the optimal configuration of the Trombe walls, the influence on energy requirements associated with the materials used to construct the support structure of the Trombe walls, the type and number of glass panels forming the solar space, the size of the solar space, and the dimensions of the vents were assessed. The results show that the installation of the two Trombe walls, each consisting of two vents with an area of 0.1 m2 and a solar space depth of 0.20 m, supported by a PVC structure and vertically bounded by three glass walls with double low-emissivity glazing (two lateral and one frontal facing south), allows for a 60.62% reduction in winter energy requirements. © 2024 IEEE.

关键词： Energy efficiency

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A branch-and-price algorithm for emergency humanitarian logistics with a mixed truck-drone fleet

A branch-and-price algorithm for emergency humanitarian logi...

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IISE Annual Conference and Expo 2024

作者： Sobhanan, Abhay Mahmoudinazlou, Sasan Charkhgard, Hadi Kwon, Changhyun Department of Industrial and Management Systems Engineering University of South Florida TampaFL33620 United States Department of Industrial and Systems Engineering KAIST Daejeon34141 Korea Republic of

ISBN: (纸本)9781713877851

Humanitarian aid distribution often prioritizes rapid relief operations or emergency services under time constraints, as opposed to commercial transportation problems, where the primary objective is to minimize operational costs. Drones can offer immense potential to achieve this goal by leveraging their aerial mobility. Specifically, drones can surpass ground transportation and navigate directly through disrupted or inaccessible roads, ensuring the quickest path to deliver aid where the ground vehicle may face obstacles. However, drones have limitations in terms of flying range and load capacity. To effectively provide time-sensitive emergency services, combining a ground vehicle with one or more aerial vehicles enhances coverage. Our approach integrates a truck as a mobile depot for multiple drones, where a drone battery is replenished on landing after a flight, and the fleet operates in tandem to serve the locations visited. We formulate a mixed-integer linear programming (MILP) model to maximize the weighted sum of locations served by this mixed truck-drone fleet under time constraints. We further develop a branch-and-price algorithm to solve this problem, where the pricing subproblem is solved using dynamic programming recursions with dominance rules. Our results demonstrate the computational superiority of this method compared to a commercial optimization solver and its potential for expediting aid distribution during an emergency. © IISE Annual Conference and Expo *** rights reserved.

关键词： Integer programming

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Sentiment analysis in social internet of things using contextual representations and dilated convolution neural network

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Neural Computing and Applications 2024年第20期36卷 12357-12370页

作者： Abid, Fazeel Rasheed, Jawad Hamdi, Mohammed Alshahrani, Hani Al Reshan, Mana Saleh Shaikh, Asadullah Department of Information Systems Dr. Hassan Murad School of Management University of Management and Technology Lahore Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim University Istanbul34303 Turkey Department of Software Engineering Istanbul Nisantasi University Istanbul34394 Turkey Department Computer Science College of Computer Science and Information Systems Najran University Najran61441 Saudi Arabia Department Information Systems College of Computer Science and Information Systems Najran University Najran61441 Saudi Arabia

The methodologies based on neural networks are substantial to accomplish sentiment analysis in the Social Internet of Things (SIoT). With social media sentiment analysis, significant insights can produce efficient and intelligent applications. Neural networks such as recurrent neural networks (RNNs) and convolution neural networks (CNNs) have been considered widely in many text classification tasks. However, RNNs are computationally expensive and require complex training to capture contextual information and long-term dependencies. Similarly, traditional CNNs must stack multiple convolutional layers, requiring massive computations and additional parameters. To address these problems, this work initialized the novel architecture, in which contextual representations (CRs) based on the textual framework are proposed at the initial step. In CRs, state-of-the-art word representation models, such as GloVe (global vectors) and FastText (subword information), collectively produce word representations upon the input sequence using a weight mechanism. Secondly, a unique way is introduced: a three-parallel layered dilated convolutional network with global mean pooling. The experimental results show that the proposed methods when compared with baseline methods, the dilation in CNNs following CRs significantly increases the accuracy from 72.45 to 98.98% and reduces computational resources. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Sentiment analysis

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