Process mining allows the extraction of useful information from the event logs and historical data of business processes. Predictive business process monitoring is a sub-field of process mining and deals with runtime ...
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This paper is on customer segmentation in steel sales, whose objective is to improve profitability and customer relationship management. The current research categorizes customers based on purchasing behaviors by usin...
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Networks in enterprise scale require connectivity that runs continuously so that a backup network is needed that functions as a substitute for the main network in case of problems. Network problems can affect data tra...
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Digital revolution has transformed education, allowing students to interact, communicate, and collaborate beyond traditional classroom settings. computer-Supported Collaborative Learning (CSCL) provides opportunities ...
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In recent years, the Open Education movement has emerged as an innovative approach in the field of education. Closely connected to it are the Open Educational Resources (ΟΕRs), which are hosted in Digital Repositori...
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Advanced analytical techniques and sophisticated decision-making strategies are imperative for handling extensive volumes of data. As the quantity, diversity, and speed of data increase, there is a growing lack of con...
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The vast collections in book publishers and bookstores make it challenging for users to find books on specific topics without knowing the exact titles. An information system with a book recommendation feature can sign...
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This paper shows the development and application of a fuzzy weight model methodology for the optimization of educational environments in augmented reality. A technology-based learning process in an augmented reality l...
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Nowadays,cloud computing provides easy access to a set of variable and configurable computing resources based on user demand through the *** computing services are available through common internet protocols and netwo...
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Nowadays,cloud computing provides easy access to a set of variable and configurable computing resources based on user demand through the *** computing services are available through common internet protocols and network standards.n addition to the unique benefits of cloud computing,insecure communication and attacks on cloud networks cannot be *** are several techniques for dealing with network *** this end,network anomaly detection systems are widely used as an effective countermeasure against network *** anomaly-based approach generally learns normal traffic patterns in various ways and identifies patterns of *** anomaly detection systems have gained much attention in intelligently monitoring network traffic using machine learning *** paper presents an efficient model based on autoencoders for anomaly detection in cloud computing *** autoencoder learns a basic representation of the normal data and its reconstruction with minimum ***,the reconstruction error is used as an anomaly or classification *** addition,to detecting anomaly data from normal data,the classification of anomaly types has also been *** have proposed a new approach by examining an autoencoder's anomaly detection method based on data reconstruction *** the existing autoencoder-based anomaly detection techniques that consider the reconstruction error of all input features as a single value,we assume that the reconstruction error is a *** enables our model to use the reconstruction error of every input feature as an anomaly or classification *** further propose a multi-class classification structure to classify the *** use the CIDDS-001 dataset as a commonly accepted dataset in the *** evaluations show that the performance of the proposed method has improved considerably compared to the existing ones in terms of accuracy,recall,false-positive rate,and F1-score
Artificial intelligence (AI) and machine learning (ML) are vastly becoming key parts of today's applications, supporting diverse human activities and decision making. New training models are used requiring an expl...
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