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Alessio Ferone and Antonio Maratea
Data streams are ubiquitous and related to the proliferation of low-cost mobile devices, sensors, wireless networks and the Internet of Things. While it is well known that complex phenomena are not stationary and exhibit a concept drift when observed for...
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Xuan Wu and Yafei Song
In recent years, the presence of malware has been growing exponentially, resulting in enormous demand for efficient malware classification methods. However, the existing machine learning-based classifiers have high false positive rates and cannot effecti...
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Aisha Adel, Nazlia Omar, Salwani Abdullah and Adel Al-Shabi
The process of eliminating irrelevant, redundant and noisy features while trying to maintain less information loss is known as a feature selection problem. Given the vast amount of the textual data generated and shared on the internet such as news report...
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Shuai Dong, Zhihua Yang, Wensheng Li and Kun Zou
Conveyors are used commonly in industrial production lines and automated sorting systems. Many applications require fast, reliable, and dynamic detection and recognition for the objects on conveyors. Aiming at this goal, we design a framework that involv...
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Limin Shen, Hui Li, Hongyi Wang, Yihuan Wang, Jiayin Feng and Yuqing Jian
On the Android platform, information leakage can use an application-layer privilege escalation attack composed of multi-app collusion. However, the detection effect of a single app that can construct privilege escalation attacks is not good. Furthermore,...
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Bo Ai, Decheng Sun, Yanmei Liu, Chengming Li, Fanlin Yang, Yong Yin and Huibo Tian
When it comes to feature retention in multi-scale representations of ocean flow fields, not all data points are equal. Therefore, this paper proposes a method of selecting data points based on their importance. First, an autocorrelation analysis is perfo...
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Sunwoo Han and Hyunjoong Kim
Random forest is an ensemble method that combines many decision trees. Each level of trees is determined by an optimal rule among a candidate feature set. The candidate feature set is a random subset of all features, and is different at each level of tre...
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Chenjing Tian, Huadong Du, Pinglv Yang, Zeming Zhou and Libin Weng
The auroral ovals around the Earth?s magnetic poles are produced by the collisions between energetic particles precipitating from solar wind and atoms or molecules in the upper atmosphere. The morphology of auroral oval acts as an important mirror reflec...
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Jianghua Ge, Guibin Yin, Yaping Wang, Di Xu and Fen Wei
To improve the accuracy of rolling-bearing fault diagnosis and solve the problem of incomplete information about the feature-evaluation method of the single-measurement model, this paper combines the advantages of various measurement models and proposes ...
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George D. O?Mahony, Kevin G. McCarthy, Philip J. Harris and Colin C. Murphy
Classifying fluctuating operating wireless environments can be crucial for successfully delivering authentic and confidential packets and for identifying legitimate signals. This study utilizes raw in-phase (I) and quadrature-phase (Q) samples, exclusive...
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Jozef Zurada
The paper broadly discusses the data reduction and data transformation issues which are important tasks in the knowledge discovery process and data mining. In general, these activities improve the performance of predictive models. In particular, the pape...
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Zhiguo Chen and Xuanyu Ren
In previous years, cybercriminals have utilized various strategies to evade identification, including obfuscation, confusion, and polymorphism technology, resulting in an exponential increase in the amount of malware that poses a serious threat to comput...
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Khalid Alkhatib, Huthaifa Khazaleh, Hamzah Ali Alkhazaleh, Anas Ratib Alsoud and Laith Abualigah
Stock price prediction is a significant research field due to its importance in terms of benefits for individuals, corporations, and governments. This research explores the application of the new approach to predict the adjusted closing price of a specif...
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Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem and John D. Kelleher
In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly d...
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Hye-Jin Lee, Yongjin Kwon and Sun-Young Ihm
In this paper, we propose the duality-based image sequence matching method, which is called Dual-ISM, a subsequence matching method for searching for similar images. We first extract feature points from the given image data and configure the feature vect...
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Xuyi Yuan, Yugang Fan, Chengjiang Zhou, Xiaodong Wang and Guanghui Zhang
The check valve is the core part of high-pressure diaphragm pumps. It has complex operation conditions and has difficulty characterizing fault states completely with its single feature. Therefore, a fault signal diagnosis model based on the kernel extrem...
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Jiahao Guo, Xiaohuo Yu and Lu Wang
Industrial quality control is an important task. Most of the existing vision-based unsupervised industrial anomaly detection and segmentation methods require that the training set only consists of normal samples, which is difficult to ensure in practice....
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Chengyan Zhong, Guanqiu Qi, Neal Mazur, Sarbani Banerjee, Devanshi Malaviya and Gang Hu
Due to the variation in the image capturing process, the difference between source and target sets causes a challenge in unsupervised domain adaptation (UDA) on person re-identification (re-ID). Given a labeled source training set and an unlabeled target...
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Mengran Zhou, Xiaokang Yao, Ziwei Zhu and Feng Hu
A prerequisite for refined load management, crucial for intelligent energy management, is the precise classification of electric loads. However, the high dimensionality of electric load samples and poor identification accuracy of industrial scenarios mak...
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Ayman Taha, Bernard Cosgrave and Susan Mckeever
Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to evaluate risk. Machine learning techniques are increasingly used in the effective management of insurance risk. Insurance datasets by their nature, however, are o...
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