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Nasrin Elhassan, Giuseppe Varone, Rami Ahmed, Mandar Gogate, Kia Dashtipour, Hani Almoamari, Mohammed A. El-Affendi, Bassam Naji Al-Tamimi, Faisal Albalwy and Amir Hussain
Social media networks have grown exponentially over the last two decades, providing the opportunity for users of the internet to communicate and exchange ideas on a variety of topics. The outcome is that opinion mining plays a crucial role in analyzing u...
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Omar Serghini, Hayat Semlali, Asmaa Maali, Abdelilah Ghammaz and Salvatore Serrano
Spectrum sensing is an essential function of cognitive radio technology that can enable the reuse of available radio resources by so-called secondary users without creating harmful interference with licensed users. The application of machine learning tec...
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Jian Chen, Yaowei Li and Shanju Zhang
Rapid prediction of urban flooding is an important measure to reduce the risk of flooding and to protect people?s property. In order to meet the needs of emergency flood control, this paper constructs a rapid urban flood prediction model based on a machi...
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Huan-Yu Chen, Chuen-Horng Lin, Jyun-Wei Lai and Yung-Kuan Chan
This paper proposes a multi?convolutional neural network (CNN)-based system for the detection, tracking, and recognition of the emotions of dogs in surveillance videos. This system detects dogs in each frame of a video, tracks the dogs in the video, and ...
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Hyunsun Song and Hyunjun Choi
Various deep learning techniques have recently been developed in many fields due to the rapid advancement of technology and computing power. These techniques have been widely applied in finance for stock market prediction, portfolio optimization, risk ma...
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Jiyuan Tan, Limin Zhang and Zhaogen Zhong
Aiming to solve the problem of the distinction of scrambled linear block codes, a method for identifying the scrambling types of linear block codes by combining correlation features and convolution long short-term memory neural networks is proposed in th...
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Mário Antunes, Luís Oliveira, Afonso Seguro, João Veríssimo, Ruben Salgado and Tiago Murteira
Network security encloses a wide set of technologies dealing with intrusions detection. Despite the massive adoption of signature-based network intrusion detection systems (IDSs), they fail in detecting zero-day attacks and previously unseen vulnerabilit...
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Konstantina Fotiadou, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Dimitrios Skias, Sofia Tsekeridou and Theodore Zahariadis
Network intrusion detection is a key pillar towards the sustainability and normal operation of information systems. Complex threat patterns and malicious actors are able to cause severe damages to cyber-systems. In this work, we propose novel Deep Learni...
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Muhammed Zahid Karakusak, Hasan Kivrak, Hasan Fehmi Ates and Mehmet Kemal Ozdemir
Wireless Local Area Network (WLAN) positioning is a challenging task indoors due to environmental constraints and the unpredictable behavior of signal propagation, even at a fixed location. The aim of this work is to develop deep learning-based approache...
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Zhijing Ye, Zheng O?Neill and Fei Hu
Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors? data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber...
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Yue Zhang, Zimo Zhou, Jesse Van Griensven Thé, Simon X. Yang and Bahram Gharabaghi
Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance...
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Martin Paralic, Kamil Zelenak, Patrik Kamencay and Robert Hudec
The paper introduces an approach for detecting brain aneurysms, a critical medical condition, by utilizing a combination of 3D convolutional neural networks (3DCNNs) and Convolutional Long Short-Term Memory (ConvLSTM). Brain aneurysms pose a significant ...
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Huafeng Qin and Peng Wang
Finger-vein biometrics has been extensively investigated for personal verification. A challenge is that the finger-vein acquisition is affected by many factors, which results in many ambiguous regions in the finger-vein image. Generally, the separability...
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Ammar Yahya Daeef, Ali Al-Naji, Ali K. Nahar and Javaan Chahl
Malware is the primary attack vector against the modern enterprise. Therefore, it is crucial for businesses to exclude malware from their computer systems. The most responsive solution to this issue would operate in real time at the edge of the IT system...
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Yaping Hao and Qiang Gao
In the stock market, predicting the trend of price series is one of the most widely investigated and challenging problems for investors and researchers. There are multiple time scale features in financial time series due to different durations of impact ...
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Min Zhang and Guohua Geng
Social media and health-related forums, including the expression of customer reviews, have recently provided data sources for adverse drug reaction (ADR) identification research. However, in the existing methods, the neglect of noise data and the need fo...
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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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Zhihao Zhang, Yong Han, Tongxin Peng, Zhenxin Li and Ge Chen
Accurate subway passenger flow prediction is crucial to operation management and line scheduling. It can also promote the construction of intelligent transportation systems (ITS). Due to the complex spatial features and time-varying traffic patterns of s...
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Ishaani Priyadarshini
Autism spectrum disorder (ASD) has been associated with conditions like depression, anxiety, epilepsy, etc., due to its impact on an individual?s educational, social, and employment. Since diagnosis is challenging and there is no cure, the goal is to max...
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Cesar Davila Hernandez, Jungseok Ho, Dongchul Kim and Abdoul Oubeidillah
During every Atlantic hurricane season, storms represent a constant risk to Texan coastal communities and other communities along the Atlantic coast of the United States. A storm surge refers to the abnormal rise of sea water level due to hurricanes and ...
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