A novel machine learning approach for portfolio optimization by Saman Haratizadeh, Fatemeh Rezaee

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Machine learning in medicine: what clinicians should know by Jordan Zheng Ting Sim, Qi Wei Fong, Weimin Huang, Cher Heng Tan

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Recent Machine Learning Progress in Image Analysis and Understanding by Shengping Zhang, Huiyu Zhou, Lei Zhang

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APPLICATION OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN ACADEMIC LIBRARIES by Adedeji Daniel GBADEBO

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Identification on the structures of block ciphers using machine learning by Ruiqi XIA, Manman LI, Shaozhen CHEN

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Behavior authentication of Web users based on machine learning by Zenan WU, Liqin TIAN, Zhigang WANG

“…According to the security problem of Web user information,the user behavior was analyzed and authenticated by the method of machine learning.First of all,through the principal component analysis to reduce the dimension of the original data set,then use the SVM algorithm to allow the computer to learn the history of user behavior evidence,to get a model to identify the user's identity.The practical application and theoretical analysis show that the model in user behavior identification authentication,can be more accurate and efficient classification of dangerous users and trusted users,analysis lay a solid theoretical and practical basis for the high performance user behavior such as electronic commerce,network finance and other key of Internet applications.…”
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Predicting Heart Diseases by Selective Machine Learning Algorithms by N. Umar, S. K. Hassan, A. Umar, S. S. Ahmed

“…Consequently, the objective of this paper was to predict heart diseases using selective machine learning algorithms.  The leverage technique was evaluated using the Cleveland heart disease dataset. …”
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Machine Learning Classifiers Based Classification For IRIS Recognition by Bahzad Taha Chicho, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, Dilovan Assad Zebari

“…Classification is the most widely applied machine learning problem today, with implementations in face recognition, flower classification, clustering, and other fields. …”
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Artificial Intelligence and Machine Learning at the Intersection of Privacy and Archives by Iori Khuhro, Erin Gilmore, Jim Suderman, Darra L. Hofman

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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

Subjects: “…Machine Learning…”
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Prediction of earthquake by machine learning models and neural network by Xu Bohong

“…Earthquake prediction, in this article, is executed with a neural network and machine learning models. After reading many articles, the author discovered that not many articles use a fully connected neural network to predict earthquake magnitude. …”
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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…Predictive maintenance, utilizing advanced technologies like data analytics, machine learning, and IoT devices, offers real-time equipment data monitoring and analysis. …”
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Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics by Vladimir S. Kublanov, Anton Yu. Dolganov, David Belo, Hugo Gamboa

“…The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. …”
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Symmetry-invariant quantum machine learning force fields by Isabel Nha Minh Le, Oriel Kiss, Julian Schuhmacher, Ivano Tavernelli, Francesco Tacchino

Subjects: “…geometric quantum machine learning…”
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Machine Learning Approaches for Developing Land Cover Mapping by Ali Alzahrani, Awos Kanan

“…However, it is well known in machine learning literature that some of the extracted features are irrelevant to the classification process with a negative or no effect on its accuracy. …”
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Machine Learning-Based Network Detection Research for SDNs by Lai Jiayue

“…This research endeavors to fortify the security posture of Software-Defined Networks (SDN) through the strategic utilization of intelligent machine learning techniques, with a primary focus on mitigating detrimental Denial of Service (DoS) attacks. …”
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The Use of Machine Learning to Support the Diagnosis of Oral Alterations by Rosana Leal do Prado, Juliane Avansini Marsicano, Amanda Keren Frois, Jacques Duílio Brancher

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Application of adversarial machine learning in network intrusion detection by Qixu LIU, Junnan WANG, Jie YIN, Yanhui CHEN, Jiaxi LIU

“…In recent years, machine learning (ML) has become the mainstream network intrusion detection system(NIDS).However, the inherent vulnerabilities of machine learning make it difficult to resist adversarial attacks, which can mislead the models by adding subtle perturbations to the input sample.Adversarial machine learning (AML) has been extensively studied in image recognition.In the field of intrusion detection, which is inherently highly antagonistic, it may directly make ML-based detectors unavailable and cause significant property damage.To deal with such threats, the latest work of applying AML technology was systematically investigated in NIDS from two perspectives: attack and defense.First, the unique constraints and challenges were revealed when applying AML technology in the NIDS field; secondly, a multi-dimensional taxonomy was proposed according to the adversarial attack stage, and current work was compared and summarized on this basis; finally, the future research directions was discussed.…”
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AIPerf: Automated Machine Learning as an AI-HPC Benchmark by Zhixiang Ren, Yongheng Liu, Tianhui Shi, Lei Xie, Yue Zhou, Jidong Zhai, Youhui Zhang, Yunquan Zhang, Wenguang Chen

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Survey of application of machine learning in wireless channel modeling by Liu LIU, Jianhua ZHANG, Yuanyuan FAN, Li YU, Jiachi ZHANG

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