Search results for: Jihen%20Ben%20Smida

Authors: Aymen Bouzid, Jihen Ben Smida

Abstract:

In this paper, we propose to prove the importance of the application of blind source separation methods on remote sensing data in order to index multispectral images. The proposed method starts with Gabor Filtering and the application of a Blind Source Separation to get a more effective representation of the information contained on the observation images. After that, a feature vector is extracted from each image in order to index them. Experimental results show the superior performance of this approach.

Keywords: blind source separation, content based image retrieval, feature extraction multispectral, satellite images

Procedia PDF Downloads 374

Authors: Jihen Bennaceur, Wissem Zouaghi, Ali Mabrouk

Abstract:

The major aim of cyber threat intelligence (CTI) is to provide sophisticated knowledge about cybersecurity threats to ensure internal and external safeguards against modern cyberattacks. Inaccurate, incomplete, outdated, and invaluable threat intelligence is the main problem. Therefore, data analysis based on AI algorithms is one of the emergent solutions to overcome the threat of information-sharing issues. In this paper, we propose a supervised machine learning-based algorithm to improve threat information sharing by providing a sophisticated classification of cyber threats and data. Extensive simulations investigate the accuracy, precision, recall, f1-score, and support overall to validate the designed algorithm and to compare it with several supervised machine learning algorithms.

Keywords: threat information sharing, supervised learning, data classification, performance evaluation

Procedia PDF Downloads 115

Authors: jihen ayadi sellami

Abstract:

The rapid evolution of the global financial landscape has led to increased attention to corporate tax policies and the need to understand the factors that influence their tax behavior. In order to mitigate any residual loss for shareholders resulting from tax aggressiveness and resolve the agency problem, appropriate systems that separate the function of management from that of controlling are needed. In this context of growing concerns to limit aggressive corporate taxation practices through governance, this study discusses. Its aims is to examine the influence of six key characteristics of the board of directors (board size, diligence, CEO duality, presence of audit committees, gender diversity and independence of directors), given a governance mechanism, on the tax decisions of non-financial corporations in the United State. In fact, using a sample of 90 non-financial US firms from S&P 500 over a period of 4 years going from 2014 to 2017, the results based on a multivariate linear regression highlight significant associations between these characteristics and corporate tax policy. Notably, larger board, gender diversity, diligence and increased director independence appear to play an important role in reducing aggressive taxation. While duality has a positive and significant correlation with tax aggressiveness, that can be explained by the fact that the manager did properly exploit his specific position within the company. These findings contribute to a deeper understanding of how board characteristics can influence corporate tax management, providing avenues for more effective corporate governance and more responsible tax decision-making

Keywords: tax aggressiveness, board of directors, board size, CEO duality, audit committees, gender diversity, director independence, diligence, corporate governance, united states

Procedia PDF Downloads 35