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Determining the financial performance of the firms in the Borsa Istanbul sustainability index:integrating multi criteria decision making methods with simulation

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Financial Innovation 2024年第1期10卷 3592-3635页

作者： Ahmet Kaya Dragan Pamucar Hasan Emin Gürler Mehmet Ozcalici Department of Banking-Finance Applied Sciences FacultyAkdeniz UniversityAntalyaTurkey Faculty of Organizational Sciences University of BelgradeBelgradeSerbia College of Engineering Yuan Ze UniversityTaoyuanTaiwan Department of Computer Science and Mathematics Lebanese American UniversityByblosLebanon Department of International Trade and Logistics Applied Sciences FacultyAkdeniz UniversityAntalyaTurkey Department of International Trade and Logistics Faculty of Economics and Administrative SciencesKilis 7 Aralık UniversityKilisTurkey

Regardless of the industry in which a company operates,evaluating corporate performance is one of the most critical and vital processes;the most essential and prominent performance evaluation is related to financial *** performance analysis is complex and critical for decision-makers in different financial performance factors;thus,a methodological framework is needed to solve such complex decision ***,this research aims to rank the companies included in the sustainability index(excluding banks)in Turkey by considering their financial *** criteria weights were determined using the full consistency method(FUCOM)by considering the evaluations of four *** firms were ranked using nine multi-criteria decision-making *** consensus among the nine rankings was ensured with the Copeland *** decision matrix includes financial ratios and the stock market performance of the firms;100,000 FUCOM weights were created with random evaluations to validate the *** results indicate that the most crucial criterion is the current ratio by considering expert *** simulation indicates that alternative 16(alternative 21)is superior(inferior)to the other alternatives,even though the weights are determined with random *** with expert evaluations is similar to the mean of the weight simulation *** results demonstrate that the proposed framework can be performed as a basis for financial performance ranking.

关键词： Financial performance BIST sustainability index Simulation MCDM techniques

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Classification of Bacterial Skin Disease Images Using Modified Convolutional Neural Network 7th

Classification of Bacterial Skin Disease Images Using Modifi...

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7th International Conference on Smart Trends in Computing and Communications, SmartCom 2023

作者： Sharma, Aditi Franklin Vinod, D. Faculty of Engineering and Technology Department of Computer Science and Engineering SRM Institute of Science and Technology Modinagar NCR Campus Delhi-NCR Campus Delhi-Meerut Road UP Ghaziabad India

ISBN: (纸本)9789819907687

The skin of the human body serves as the strongest barrier for critical organs. It serves as a barrier to prevent injury to our interior organs. But this vital area of the body can experience such severe diseases brought on by fungi, viruses, or even dust. Numerous skin conditions affect millions of individuals worldwide. People endure a lot of suffering, from eczema to acne issues. A minor skin ailment, such as a boil, can occasionally worsen or even become infected, leading to serious health problems. Some skin conditions are so contagious that they can spread by a handshake or the use of a handkerchief. A thorough diagnosis can lead to a proper course of treatment, which can lessen the suffering of those who are ill and raise awareness. A bacterial, viral, or fungal infection called pneumonia targets the respiratory system. Lung air sacs become irritated and enlarged as a result of the illness. It causes the lungs to become fluid and mucus-filled. In this study, convolutional neural networks are used to detect skin diseases using image classification and segmentation. Two different models that can be used for this research are VGG16 and VGG19. Although, this article used single-layer CNN model to compare with existing models. The testbed made use of openly available data from Kaggle’s Dermnet images. The dataset was built using 23 categories of diseases and 19,500 images which can be segregated into two distinct classes such as acne, melanoma, Eczema, Seborrheic Keratoses, Tinea, etc. Further, the dataset is segregated for acne and Eczema which is categorized as bacterial and fungal infection. The performance measures for the VGG16 results are accuracy (95.2%), specificity (95.8%), and sensitivity (93.7%). The VGG19 result has a 97.2% sensitivity, 95.4% specificity, and 94.6% accuracy. Sensitivity, specificity, and accuracy for CNN single-layer are 96.3, 97.6, and 96.5%, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte

关键词： Convolution

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A Data-Driven Analytical Approach on Digital Adoption and Digital Policy for Pharmaceutical Industry in India 7th

A Data-Driven Analytical Approach on Digital Adoption and Di...

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7th International Conference on Microelectronics and Telecommunication engineering, ICMETE 2023

作者： Rana, Anup Sarkar, Bikramjit Parida, Raj Kumar Adhikari, Saurabh Anandha Lakshmi, R. Akila, D. Pal, Souvik Liverpool Business School Liverpool John Moores University Liverpool United Kingdom Department of Computer Science and Engineering JIS College of Engineering Kalyani India School of Computing Science and Engineering Galgotias University Greater Noida India School of Engineering Swami Vivekananda University Kolkata India Department of Computer Application Anna Adarsh College for Women Chennai India Department of Computer Applications Saveetha College of Liberal Arts and Sciences SIMATS Deemed University Chennai India Department of Management Information Systems Saveetha College of Liberal Arts and Sciences Saveetha Institute of Medical and Technical Sciences Chennai India Kolkata India

ISBN: (纸本)9789819995615

The Indian pharmaceutical industry has witnessed exponential growth over the past few decades to become the third largest globally in volume terms and a leading supplier of affordable generics. This paper provides a comprehensive assessment of the industry’s evolution, structure, performance metrics, priorities, challenges and future outlook. Secondary data from government reports, industry associations, company documents and academic literature is synthesized to develop a holistic perspective. The analysis indicates that innovation, research productivity, clinical trials, ethical practices and sustainability shape the industry’s development. Strategic priorities include strengthening R&D capabilities, expanding exports, leveraging digital technologies across operations, ensuring robust supply chains and adopting global quality and ESG standards. Investments in innovation have risen but remain below international benchmarks. While generics account for majority revenues, emerging segments like biosimilars and complex drugs offer growth opportunities. Digital adoption is increasing with data analytics and AI gaining prominence. However, issues related to regulations, pricing control, IP protection, skill shortages and environmental impact need resolution through appropriate reforms and public–private collaboration. India’s vision to become a leading pharmaceutical innovation and manufacturing hub would require reinforcing policy frameworks around IP protection, pricing, regulatory efficiency, skill building and technology adoption. Overall, the industry holds immense potential for beneficial growth but realizing it would necessitate concentrated efforts from stakeholders to build organizational capabilities, foster collaboration and imbibe global best practices. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Supply chains

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An IoT Machine Learning Model-Based Real-Time Diagnostic and Monitoring System 4th

An IoT Machine Learning Model-Based Real-Time Diagnostic and...

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4th International Conference on Machine Intelligence and Signal Processing, MISP 2022

作者： Awotunde, Joseph Bamidele Misra, Sanjay Ajagbe, Sunday Adeola Ayo, Femi Emmanuel Gurjar, Ramchandra Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin240003 Nigeria Department of Computer Science and Communication Ostfold University College Halden Norway Department of Computer Engineering Ladoke Akintola University of Technology Ogbomosho Nigeria Department of Mathematical Sciences Olabisi Onabanjo University Ago-Iwoye Ogun State Nigeria Shri Govindram Seksaria Institute of Technology and Science Indore India

ISBN: (纸本)9789819900848

Internet of things (IoT) and machine learning (ML) have recently changed the paradigm in the area of applications in health-care systems with significant results. The ML-based models enabled with IoT-based systems have greatly expedited the medical diagnosis, real-time monitoring, and treatment in the health-care system, thus reducing the burden of health-care processes and the cost of taking care of patients by caregivers and physicians. Therefore, in this paper, a framework is proposed based on an ML model-enabled IoT-based system for real-time diagnosis of various diseases using data collected from wearable devices and sensors attached within the body of patients. The captured data are stored using an integrated cloud database for further preprocessing and processes using ML-based models. ML model was used to select the most relevant features from the cloud database and thus use the preprocessed data for the diagnosis of various diseases. The findings from the study show that the XGBoost performs reliably better when compared with other existing ML-based models with an accuracy of 95.7%, recall of 95.9%, precision of 96.0%, F1-score of 94.8%, and Receiver Operating Characteristic Curve (ROC) of 94.3%. The results proposed a framework to show that the system can be widely used to diagnose various diseases and can be used in remote areas for better monitoring of patients. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

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computers, Materials & Continua 2022年第1期70卷 847-874页

作者： Mohamed Abdel-Basset Ahmed Sleem Asmaa Atef Yunyoung Nam Mohamed Abouhawwash Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast Lansing48824MIUSA

Project scheduling is a key objective of many models and is the proposed method for project planning and *** scheduling problems depend on precedence relationships and resource constraints,in addition to some other limitations for achieving a subset of *** scheduling problems are dependent on many limitations,including limitations of precedence relationships,resource constraints,and some other limitations for achieving a subset of *** project scheduling models consider all information about the scheduling problem such as activity durations and precedence relationships information resources available and required,which are known and stable during the implementation *** concept of deterministic project scheduling conflicts with real situations,in which in many cases,some data on the activity’s durations of the project and the degree of availability of resources change or may have different modes and strategies during the process of project implementation for dealing with multi-mode conditions surrounded by projects and their activity *** the multi-mode resource-constrained project problem is an optimization problem whose minimum project duration subject to the availability of resources is of particular interest to *** use the multi-mode resource allocation and schedulingmodel that takes into account the dynamicity features of all parameters,that is,the scheduling process must be flexible to dynamic environment *** this paper,we propose five priority heuristic rules for scheduling multi-mode resource-constrained projects under dynamicity features for more realistic situations,in which we apply the proposed heuristic rules(PHR)for scheduling multi-mode resource-constrained *** projects are considered test problems for the *** obtained results rendered by these priority rules for the test problems are compared by the results obtained from 10 well-known heuristics rules rendered for

关键词： Constrained resource scheduling multi-mode durations dynamic scheduling resource allocation heuristic rules

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Retrieval-Augmented Generation and In-Context Prompted Large Language Models in Aircraft engineering

Retrieval-Augmented Generation and In-Context Prompted Large...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Silva, Edmar A. Marsh, Robert Yong, Hau Kit Middleton, Stuart E. Sóbester, András Faculty of Engineering and Physical Sciences University of Southampton SouthamptonSO17 United Kingdom School of Electronics and Computer Science University of Southampton SouthamptonSO17 United Kingdom

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

With the aerospace industry taking its first steps towards exploiting the rapidly evolving technology of Large Language Models (LLMs), this study explores the potential of the latest generation of LLMs to become an effective link in the aircraft design tool chain of the future. Our focus is on the task of Question Answering (QA) in engineering, which has the potential to augment future aircraft design team meetings with an intelligent LLM-based agent able to engage with the team via a chatbot interface. We compare three of the most effective and popular classes of LLM QA prompting today – LLM zero-shot prompting, LLM in-context prompting and LLM-based Retrieval-Augmented Generation (RAG). We describe a new, low volume, high quality benchmark aircraft design QA dataset (AeroEngQA) and use it to qualitatively evaluate each class of LLM and exploring properties including answer accuracy and answer simplicity of the answer. We provide domain-specific insights into the usefulness of today’s LLMs for engineering design tasks such as aircraft design, and a view on how this might evolve in the future as the next generation of LLMs emerges. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aerospace industry

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Lithographic printing inspired in-situ transfer of MXene-based films with localized topo-electro tunability for high-performance flexible pressure sensors

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Nano Research 2023年第11期16卷 12670-12679页

作者： Qiuyang Yan Yi Zhou Yin Cheng Liangjing Shi Ranran Wang Lian Gao Jing Sun State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of ScienceShanghai 200050China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore School of Chemistry and Materials Science Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China School of Materials Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

MXene-based films have been intensively explored for construction of piezoresistive flexible pressure sensors owing to their excellent mechanical and electrical *** pressure sensitivity relies on pre-molding a flexible substrate,or regulating the micromorphology of MXene sheets,to obtain a micro-structured ***,the two avenues usually require complicated and time-consuming microfabrication or wet chemical processing,and are limited to non-adjustable topographicelectrical(topo-electro)***,we propose a lithographic printing inspired in-situ transfer(LIPIT)strategy to fabricate MXene-ink films(MIFs).In LIPIT,MIFs not only inherit ridge-and-valley microstructure from paper substrate,but also achieve localized topo-electro tunability by programming ink-writing patterns and *** MIF-based flexible pressure sensor with periodical topo-electro gradient exhibits remarkably boosted sensitivity in a wide sensing range(low detection limit of 0.29 Pa and working range of 100 kPa).The MIF sensor demonstrates versatile applicability in both subtle and vigorous pressuresensing fields,ranging from pulse wave extraction and machine learning-assisted surface texture recognition to piano-training glove(PT-glove)for piano *** LIPIT is quick,low-cost,and compatible with free ink/substrate combinations,which promises a versatile toolbox for designing functional MXene films with tailored morphological-mechanical-electrical properties for extended application scenarios.

关键词： MXene film transfer printing surface tunability flexible pressure sensor

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A Continual Learning System with Self Domain Shift Adaptation for Fake News Detection 10

A Continual Learning System with Self Domain Shift Adaptatio...

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10th IEEE International Conference on Data science and Advanced Analytics, DSAA 2023

作者： Basterrech, Sebastian Kasprzak, Andrzej Platos, Jan Wozniak, Michal Technical University of Denmark Department of Applied Mathematics and Computer Science Kongens Lyngby Denmark Wroclaw University of Science and Technology Department of Systems and Computer Networks Wroclaw Poland VŠB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Ostrava Czech Republic

ISBN: (纸本)9798350345032

Detecting fake news is currently one of the critical challenges facing modern societies. The problem is particularly relevant, as disinformation is readily used for political warfare but can also cause significant harm to the health of citizens, such as by promoting false data on the harmfulness of selected therapies. One way to combat disinformation is to treat fake news detection as a machine learning task. This paper presents such an approach, which additionally addresses an important problem related to the non-stationarity characteristics of the fake news. We elaborated a stream data with the simulation of domain shift based on two popular benchmark datasets dedicated to the fake news classification problem (Kaggle Fake News and Constraint@AAAI2021-COVID19 Fake News Detection). The proposed learning system works in a Continual Learning (CL) framework and integrates a self domain shift adaptation in a machine learning scheme. The method was built following state-of-the-art techniques, that includes Word2Vec as a feature extractor and the LSTM model as a classifier. The performance of the approach has been evaluated over the generated data stream. The convenience of our approach is showed in the results, where the accuracy gain with respect to a CL approach without domain adaptation is observed to be significant. © 2023 IEEE.

关键词： Long short-term memory

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Data Protection in the Era of Big Data Advanced Encryption Standard VS Data Encryption Standard 2

Data Protection in the Era of Big Data Advanced Encryption S...

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2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Mageshwaran, M.K. Sri Ramya, P. Saveetha University Saveetha School of Engineering Saveetha Institution of Medical and Technical Sciences Department of Information Technology Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institution of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364699

This research is to seek to know which algorithm between the DES (Data Encryption Standard) and AES (Advanced Encryption Standard) is faster in encryption and decryption as well as determine which is safer The data set used in this research was an online dataset with a data capacity of one lakh. A program is created to determine which algorithm between AES and DES has a faster encryption and decryption time, it uses a sample size of 20 where 10 for group 1 and 10 for group 2 It is ran through Google colab. The sentiments for the proposed AES are (1. 8/1. 9 seconds for encryption and 1 second for decryption) whereas for DES it is (0. 112/0. 128 seconds for encryption and decryption respectively). This is a showing of the difference between the AES and DES for both encryption and decryption time. The new AES Algorithm for Encryption and decryption in the Evaluation of data security in the Big Data has a better scope, safeness, and speed as compared to the DES Algorithm. © 2024 IEEE.

关键词： AES (Advanced Encryption Standard) Big Data Data Protection Decryption Time DES (Data Encryption Standard) Encryption Algorithms Encryption Time Google Colab Research Dataset Security Measures

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Atomizing E-Government Facilities Using Big Data Analytic 1

Atomizing E-Government Facilities Using Big Data Analytic

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Hemalatha, S. Kanimozhi, K.V. Nagappan, G. Mahesh, P.C. Senthil Priya, R. Vidhya, M. Department of Computer Science and Engineering Panimalar Institute of Technology Tamil Nadu Chennai600123 India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Saveetha Engineering College TamilNadu Chennai600127 India Department of Computer Science and Engineering Annamacharya Institute Of Technology & Sciences New Boyanapalli Rajampet Andhra Pradesh 516126 India Department of Computer Science and Enginerring Panimalar Engineering College Poonamaller Tamil Nadu Chennai India

ISBN: (纸本)9781607685395

During the last two decades, technical advancements in data bases and query processing have replaced hard copy maintenance in government sectors, resulting in an increase in the use of software applications to simplify human tasks in a matter of seconds. Any official task that has to be more efficient requires improvement and quick *** demographic information is also a major concern for government authorities. This article offers a method for gathering people's data and organising it as a hierarchy using a tree structure, which may be used to produce unique data and reduce redundant data. The Hadoop Map Reduction function can be used to complete this expected task. © The Electrochemical Society

关键词： Big data Big Data Analytics E-Governance Hadoop Map Reduction function MapReduce - Algorithm

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