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Krishna Raj Raghavendran and Ahmed Elragal
In the context of developing machine learning models, until and unless we have the required data engineering and machine learning development competencies as well as the time to train and test different machine learning models and tune their hyperparamet...
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Khaled Chahine
Machine learning (ML) techniques have permeated various domains, offering intelligent solutions to complex problems. ML has been increasingly explored for applications in active power filters (APFs) due to its potential to enhance harmonic compensation, ...
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Antonio Jesús Banegas-Luna and Horacio Pérez-Sánchez
As machine learning (ML) transforms industries, the need for efficient model development tools using high-performance computing (HPC) and ensuring interpretability is crucial. This paper presents SIBILA, an AutoML approach designed for HPC environments, ...
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Afnan Alotaibi and Murad A. Rassam
Concerns about cybersecurity and attack methods have risen in the information age. Many techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs), that help achieve security goals, such as detecting malicious attacks befo...
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Chongchong Xu, Zhicheng Liao, Chaojie Li, Xiaojun Zhou and Renyou Xie
In recent years, machine learning, especially deep learning, has developed rapidly and has shown remarkable performance in many tasks of the smart grid field. The representation ability of machine learning algorithms is greatly improved, but with the inc...
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Despoina Mouratidis and Katia Lida Kermanidis
Machine translation is used in many applications in everyday life. Due to the increase of translated documents that need to be organized as useful or not (for building a translation model), the automated categorization of texts (classification), is a pop...
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Despoina Mouratidis and Katia Lida Kermanidis
Machine translation is used in many applications in everyday life. Due to the increase of translated documents that need to be organized as useful or not (for building a translation model), the automated categorization of texts (classification), is a pop...
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Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
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Vinícius F. Santos, Célio Albuquerque, Diego Passos, Silvio E. Quincozes and Daniel Mossé
Cyber-physical systems (CPS) are vital to key infrastructures such as Smart Grids and water treatment, and are increasingly vulnerable to a broad spectrum of evolving attacks. Whereas traditional security mechanisms, such as encryption and firewalls, are...
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Sheng Jiang, Ziyi Liu, Jiajun Hua, Zhenyu Zhang, Shuai Zhao, Fangnan Xie, Jiangbo Ao, Yechen Wei, Jingye Lu, Zhen Li and Shilei Lyu
Fruit maturity is a crucial index for determining the optimal harvesting period of open-field loofah. Given the plant?s continuous flowering and fruiting patterns, fruits often reach maturity at different times, making precise maturity detection essentia...
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Ghada El-khawaga, Mervat Abu-Elkheir and Manfred Reichert
Predictive Process Monitoring (PPM) has been integrated into process mining use cases as a value-adding task. PPM provides useful predictions on the future of the running business processes with respect to different perspectives, such as the upcoming act...
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Gomathy Ramaswami, Teo Susnjak and Anuradha Mathrani
Learning Analytics (LA) refers to the use of students? interaction data within educational environments for enhancing teaching and learning environments. To date, the major focus in LA has been on descriptive and predictive analytics. Nevertheless, presc...
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Nisha Rawindaran, Ambikesh Jayal and Edmond Prakash
In many developed countries, the usage of artificial intelligence (AI) and machine learning (ML) has become important in paving the future path in how data is managed and secured in the small and medium enterprises (SMEs) sector. SMEs in these developed ...
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Haokun Fang and Quan Qian
Privacy protection has been an important concern with the great success of machine learning. In this paper, it proposes a multi-party privacy preserving machine learning framework, named PFMLP, based on partially homomorphic encryption and federated lear...
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Jie Lei, Tousif Rahman, Rishad Shafik, Adrian Wheeldon, Alex Yakovlev, Ole-Christoffer Granmo, Fahim Kawsar and Akhil Mathur
The emergence of artificial intelligence (AI) driven keyword spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current neural network...
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Shanza Abbas, Muhammad Umair Khan, Scott Uk-Jin Lee and Asad Abbas
Natural language interfaces to databases (NLIDB) has been a research topic for a decade. Significant data collections are available in the form of databases. To utilize them for research purposes, a system that can translate a natural language query into...
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Shayan Taheri, Aminollah Khormali, Milad Salem and Jiann-Shiun Yuan
In this work, we propose a novel defense system against adversarial examples leveraging the unique power of Generative Adversarial Networks (GANs) to generate new adversarial examples for model retraining. To do so, we develop an automated pipeline using...
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Navdeep Gill, Patrick Hall, Kim Montgomery and Nicholas Schmidt
This manuscript outlines a viable approach for training and evaluating machine learning systems for high-stakes, human-centered, or regulated applications using common Python programming tools. The accuracy and intrinsic interpretability of two types of ...
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Xianglong Wei, Huaixiang Liu, Xiaojian She, Yongjun Lu, Xingnian Liu and Siping Mo
The stability number of a breakwater can determine the armor unit?s weight, which is an important parameter in the breakwater design process. In this paper, a novel and simple machine learning approach is proposed to evaluate the stability of rubble-moun...
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Dmitry Namiot,Eugene Ilyushin
Pág. 43 - 60
Artificial intelligence systems in this work refer to machine learning systems. It is machine learning (deep learning) systems that are, today, the main examples of the use of Artificial Intelligence in a wide variety of areas. From a practical point of ...
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