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25th European Conference on Knowledge Management, ECKM 2024

作者： Baakir, Houssam Ellioua, Hanane LAMSAD Research Laboratory Systems Analysis and Modeling Laboratory Decision Support National School of Applied Sciences BERRECHID Hassan 1st University Morocco

ISBN: (纸本)9781917204101

In the dynamic landscape of contemporary global industries, the imperative to foster innovation has been recognized as an indispensable key to corporate growth. Nowhere is this more pronounced than in the pharmaceutical sector, where the pursuit of groundbreaking advancements in research and development is deemed indispensable. Understanding the factors that influence innovative behavior (IB) among employees is of utmost importance, and this paper seeks to study the influence of knowledge sharing (KS) within the pharmaceutical sector in Morocco, specifically focusing on two essential dimensions: knowledge donating (KD) and knowledge collecting (KC). The study aims to collect and analyze data from a diverse sample of 100 engineers in the Moroccan pharmaceutical industry. We used quantitative methodology by employing correlation and multiple regression methodologies, the research endeavors to unravel the intricate association linking knowledge sharing and pharmaceutical engineers’ Innovative behavior. Preliminary findings reveal a positive influence of the dimensions of knowledge sharing on workers' innovative behavior. This suggests that a climate of knowledge exchange and actively seeking knowledge plays a crucial role in driving innovation within the pharmaceutical workplace. Notably, the study places a nuanced emphasis on the efficacy of knowledge donating, underscoring its pivotal role in fostering a dynamic and innovative environment. These findings contribute valuable insights to the broader discourse on organizational innovation. By highlighting the positive correlation between KS and IB, the investigation provides actionable information for practitioners in the pharmaceutical firms. Grasping the effect of KD and KC can empower firms to sustain a culture that encourages collaboration, continuous learning, and ultimately, groundbreaking innovations. As industries continue to evolve, this exploration serves as a timely contribution to the ongoing dialogue on org

关键词： Knowledge representation

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Leveraging Machine Learning for Anomaly Detection Methods in Cryptocurrency: A Data-Driven Study 10

Leveraging Machine Learning for Anomaly Detection Methods in...

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10th International Conference on Optimization and Applications, ICOA 2024

作者： Yahia, Achraf Mouhssine, Yassine Elalaoui, Abdelkader Ouatik Elalaoui, Said National School of Applied Sciences Ibn Tofail University Engineering Sciences Laboratory Kenitra Morocco University Hassan I Laboratory of Analyzing and Modeling Systems for Decision Support Settat Morocco Rabat Business School International University of Rabat Rabat Morocco

ISBN: (纸本)9798350387353

Cryptocurrencies like Bitcoin and Ethereum have experienced remarkable growth but also high volatility, making anomaly detection crucial for predictive modeling and risk management. This study evaluates three unsupervised machine learning algorithms - Local Outlier Factor, One-Class support Vector Machine, and Isolation Forest - for detecting anomalies in Bitcoin and Ethereum prices and returns from January 2017 to May 2024. Local Outlier Factor is benchmarked against One-Class support Vector Machine and Isolation Forest using mean absolute error (MAE), root mean squared error (RMSE), and explained variance score (EVS) as performance metrics. Results demonstrate Local Outlier Factor outperforms One-Class support Vector Machine and Isolation Forest in detecting return anomalies for both cryptocurrencies. While Local Outlier Factor and Isolation Forest exhibit similar global anomaly detection capability, Local Outlier Factor achieves lower RMSE, indicating superior efficiency in capturing cryptocurrency market dynamics. One-Class support Vector Machine lagged the other two methods across all metrics. The findings highlight the efficacy of density-based local outlier detection techniques like Local Outlier Factor for cryptocurrency applications. This study provides valuable insights for developing robust anomaly detection systems to enhance risk management and trading strategies in the highly volatile cryptocurrency market. © 2024 IEEE.

关键词： Risk management

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On-Orbit Test Range Visualization Software

On-Orbit Test Range Visualization Software

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2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023

作者： Gonzalez-Huertas, Carlos D. Mata, Roxana Birge, Jonathan R. Space Systems Analysis & Test Mit Lincoln Laboratory LexingtonMA United States Information Integration & Decision Support Mit Lincoln Laboratory LexingtonMA United States Advanced Capabilities & Technologies Mit Lincoln Laboratory LexingtonMA United States

ISBN: (纸本)9781733509633

There is a growing need to support both government and private on-orbit experiments with a variety of coordinated sensors, both optical and RF, to provide both real-time safety-of-flight as well as high-fidelity orbital truth for offline analysis. However, many of the tools designed to command and control sensors are designed for the few-sensors-to-many-targets mission characteristic of space surveillance, rather than the many-to-few mission of range testing. To address this gap, MIT Lincoln laboratory has developed a web services software architecture designed to reliably support command and control of a heterogeneous distributed network of sensors supporting an on-orbit test range. © 2023 ACES.

关键词： Space surveillance

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An Overview of Blockchain Consensus Algorithms: Comparison, Challenges and Future Directions 1st

An Overview of Blockchain Consensus Algorithms: Comparison, ...

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1st International Conference of Advanced Computing and Informatics, ICACIN 2020

作者： Azbeg, Kebira Ouchetto, Ouail Jai Andaloussi, Said Fetjah, Laila Computer Science Modeling Systems and Decision Support Laboratory Faculty of Sciences Ain-Chok Hassan II University of Casablanca Casablanca Morocco

ISBN: (纸本)9789811560477

Like any other distributed system, the Blockchain technology relies on consensus algorithms in order to reach agreement and secure its network. Over the past few years, several kinds of consensus algorithms were created in the Blockchain ecosystem. In this paper, we present some main consensus algorithms used by the Blockchain technology. We also provide a comparison summary of their advantages and weaknesses as well as in which Blockchain type can be used. Furthermore, we present some challenges and possible directions related to the trendiest domains. With this work, for a given situation, we hope to help to choose the right algorithm to use. In addition, we hope to give directions to new possible algorithms propositions. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Automated Binary Classification of Diabetic Retinopathy by Convolutional Neural Networks 1st

Automated Binary Classification of Diabetic Retinopathy by C...

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1st International Conference of Advanced Computing and Informatics, ICACIN 2020

作者： Skouta, Ayoub Elmoufidi, Abdelali Jai-Andaloussi, Said Ochetto, Ouail Computer Science Modeling Systems and Decision Support Department of Mathematics and Computer Science Faculty of Science Aïn Chock Hassan II University Casablanca Morocco Laboratory of Information Processing and Decision Support Department of Computer Science Faculty of Sciences and Technics Sultan Moulay Slimane University Beni Mellal Morocco Laboratory of Computer Science Modeling Systems and Decision Support FSJES Ain-Chock Hassan II University Casablanca Morocco

ISBN: (纸本)9789811560477

This paper proposes a binary classification method for high-resolution retinal images by using convolutional neural networks. The convolutional neural network is first, formed to recognize and classify the fundus images of the eye as normal retina or proliferative diabetic retina. We are training proposed network by using a graphics processor and a public dataset available on the Kaggle Web site. An increase in data makes possible the identification of complex characteristics involved in the classification task. Our proposed convolutional neural networks achieve an accuracy of 95.5% on 1000 images of the normal retina and 1000 images of proliferative diabetic retina for training and 200 images of the normal retina and 200 images of proliferative diabetic retina for testing. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks

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On-Orbit Test Range Visualization Software

On-Orbit Test Range Visualization Software

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International Review of Progress in Applied Computational Electromagnetics (ACES)

作者： Carlos D. Gonzalez-Huertas Roxana Mata Jonathan R. Birge Space Systems Analysis & Test MIT Lincoln Laboratory Lexington MA Information Integration & Decision Support MIT Lincoln Laboratory Lexington MA Advanced Capabilities & Technologies MIT Lincoln Laboratory Lexington MA

关键词： Command and control systems Laser radar Web services Space missions Surveillance Sensor phenomena and characterization Software

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Leveraging Machine Learning for Anomaly Detection Methods in Cryptocurrency: A Data-Driven Study

Leveraging Machine Learning for Anomaly Detection Methods in...

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International Conference on Optimization and Applications (ICOA)

作者： Achraf Yahia Yassine Mouhssine Abdelkader Elalaoui Said Ouatik Elalaoui Engineering Sciences Laboratory National School of Applied Sciences Ibn Tofail University Kenitra Morocco Laboratory of Analyzing and Modeling Systems for Decision Support University Hassan I Settat Morocco Rabat Business School International University of Rabat Rabat Morocco

ISBN: (数字)9798350387353

ISBN: (纸本)9798350387360

关键词： support vector machines Measurement Machine learning algorithms decision making Forestry Bitcoin Machine learning Predictive models Risk management Anomaly detection

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Student Achievement in Moroccan Student Achievement in Moroccan Educational Reforms: A Significant Gap Between Aspired Outcomes and Current Practices

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Interchange 2020年第2期51卷 117-136页

作者： Saoudi, Khadija Chroqui, Razane Okar, Chafik Laboratory of Analysis and Modeling Systems for Decision Support (LAMSAD) National School for Applied Sciences of Berrechid (ENSA) Hassan 1st University Settat Morocco

Despite successive reforms and a high percentage of the national budget devoted to education, Morocco ranks among last in terms of student achievement. This article reviews the definition of student achievement, examines the measures targeting the improvement of student achievement in the last Moroccan educational reforms based on the three drivers identified by Masino and Niño-Zarazúa (Int J Educ Dev 48:53–65, 2015). In addition, it identifies the main difficulties encountered in the implementation of these measures and puts forward some recommendations. It thus concludes that there is a growing gap between the reforms’ aspirations and daily practices at regional and school levels. It also shows that despite the significant progress in infrastructure and enrolment, additional efforts are needed to pragmatically raise student achievement in Morocco. © 2019, Springer Nature B.V.

关键词： Educational reform School education Student achievement

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Applied CNN for Automatic Diabetic Retinopathy Assessment Using Fundus Images 6th

Applied CNN for Automatic Diabetic Retinopathy Assessment Us...

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6th International Conference on Business Intelligence, CBI 2021

作者： El Hossi, Amine Skouta, Ayoub Elmoufidi, Abdelali Nachaoui, Mourad Mathematics Applications Laboratory Faculty of Sciences and Technics Sultan Moulay Slimane University Beni Mellal Morocco Computer Science Modeling Systems and Decision Support Laboratory Faculty of Science Aïn Chock Hassan II University Casablanca Morocco Information Processing and Decision Support Laboratory Faculty of Sciences and Technics Sultan Moulay Slimane University Beni Mellal Morocco

ISBN: (纸本)9783030765071

In the area of ophthalmology, diabetic retinopathy affects an increasing number of people. Early detection avoids severe diabetic proliferative retinopathy complications. In this paper, we propose a method for binary classification of retinal images using convolutional neural networks architecture. This method is formed to recognize and classify a retinal image as normal or abnormal retina. The paper setup is, first of all a preprocessing step is applied, next by data augmentation, and then a CNN formed, and applied. To train, validate and test the proposed model, we have used a public dataset "Resized version of the Diabetic Retinopathy Kaggle competition dataset" from Kaggle web site. Proposed model has trained using 4000 images of the normal retina and 4000 images of abnormal diabetic retina, and 500 images of the normal retina and 500 images of abnormal diabetic retina for testing. The accuracy Achieves 89% in 100 images of single prediction words. © 2021, Springer Nature Switzerland AG.

关键词： Ophthalmology

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Stochastic SICA Epidemic Model with Jump Lévy Processes

arXiv

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arXiv 2022年

作者： Zine, Houssine Danane, Jaouad Torres, Delfim F.M. Department of Mathematics University of Aveiro Aveiro3810-193 Portugal Laboratory of Systems Modelization and Analysis for Decision Support National School of Applied Sciences Hassan First University Berrechid Morocco

We propose and study a shifted SICA epidemic model, extending the one of Silva and Torres (2017) to the stochastic setting driven by both Brownian motion processes and jump Lévy noise. Lévy noise perturbations are usually ignored by existing works of mathematical modelling in epidemiology, but its incorporation into the SICA epidemic model is worth to consider because of the presence of strong fluctuations in HIV/AIDS dynamics, often leading to the emergence of a number of discontinuities in the processes under investigation. Our work is organised as follows: (i) we begin by presenting our model, by clearly justifying its used form, namely the component related to the Lévy noise;(ii) we prove existence and uniqueness of a global positive solution by constructing a suitable stopping time;(iii) under some assumptions, we show extinction of HIV/AIDS;(iv) we obtain sufficient conditions assuring persistence of HIV/AIDS;(v) we illustrate our mathematical results through numerical simulations. Copyright © 2022, The Authors. All rights reserved.

关键词： Differential equations

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