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Jizhao Wang, Yunyi Liang, Jinjun Tang and Zhizhou Wu
This research contributes to the development of a technological method to obtain highly accurate vehicle trajectory data. The reconstructed trajectory data play a key role in traffic state prediction, traffic management and the decision making of autonom...
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Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon and Sajjan Shiva
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infrastru...
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Woo-Hyun Choi and Jung-Ho Lewe
This study proposes a deep learning model utilizing the BACnet (Building Automation and Control Network) protocol for the real-time detection of mechanical faults and security vulnerabilities in building automation systems. Integrating various machine le...
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Liqiu Chen, Chongshi Gu, Sen Zheng and Yanbo Wang
Real and effective monitoring data are crucial in assessing the structural safety of dams. Gross errors, resulting from manual mismeasurement, instrument failure, or other factors, can significantly impact the evaluation process. It is imperative to elim...
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Károly Héberger
Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread wi...
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Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana and Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply sy...
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Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
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Thimo F. Schindler, Simon Schlicht and Klaus-Dieter Thoben
Within the integration and development of data-driven process models, the underlying process is digitally mapped in a model through sensory data acquisition and subsequent modelling. In this process, challenges of different types and degrees of severity ...
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Ganjar Alfian, Muhammad Qois Huzyan Octava, Farhan Mufti Hilmy, Rachma Aurya Nurhaliza, Yuris Mulya Saputra, Divi Galih Prasetyo Putri, Firma Syahrian, Norma Latif Fitriyani, Fransiskus Tatas Dwi Atmaji, Umar Farooq, Dat Tien Nguyen and Muhammad Syafrudin
Analyzing customer shopping habits in physical stores is crucial for enhancing the retailer?customer relationship and increasing business revenue. However, it can be challenging to gather data on customer browsing activities in physical stores as compare...
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Shengwei Jia, Nianyu Zou, Songhai Xu and Min Cheng
In this paper, an illumination measurement system is proposed and experimentally demonstrated. The system consists of two parts, including the illumination acquisition module mounted on the UAV and the real-time display interface of the cloud platform wi...
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