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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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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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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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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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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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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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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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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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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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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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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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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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Eugene Ilyushin,Dmitry Namiot,Ivan Chizhov
Pág. 17 - 22
The paper deals with the problem of adversarial attacks on machine learning systems. Such attacks are understood as special actions on the elements of the machine learning pipeline (training data, the model itself, test data) in order to either achieve t...
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Tanmaya Mahapatra and Syeeda Nilofer Banoo
Machine Learning (ML) has gained prominence and has tremendous applications in fields like medicine, biology, geography and astrophysics, to name a few. Arguably, in such areas, it is used by domain experts, who are not necessarily skilled-programmers. T...
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Hyejeong Choi and Sejin Park
Recently, the machine learning research trend expands to the system performance optimization field, where it has still been proposed by researchers based on their intuitions and heuristics. Compared to conventional major machine learning research areas s...
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Gaurang Sonkavde, Deepak Sudhakar Dharrao, Anupkumar M. Bongale, Sarika T. Deokate, Deepak Doreswamy and Subraya Krishna Bhat
The financial sector has greatly impacted the monetary well-being of consumers, traders, and financial institutions. In the current era, artificial intelligence is redefining the limits of the financial markets based on state-of-the-art machine learning ...
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Hongyu Liu and Bo Lang
Networks play important roles in modern life, and cyber security has become a vital research area. An intrusion detection system (IDS) which is an important cyber security technique, monitors the state of software and hardware running in the network. Des...
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