Searched for: subject%3A%22Long%255C+Short%255C-term%255C+Memory%22
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Shi, Xuyang (author), Chen, Shuzhao (author), Wang, Qiang (author), Lu, Yijun (author), Ren, S. (author), Huang, Jiandong (author)
As an environmentally responsible alternative to conventional concrete, geopolymer concrete recycles previously used resources to prepare the cementitious component of the product. The challenging issue with employing geopolymer concrete in the building business is the absence of a standard mix design. According to the chemical composition of...
journal article 2024
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Kashifi, M.T.K. (author)
Road traffic crash is a global tragedy that leads to economic loss, injury, and fatalities. Understanding the severity of a road crash at the early stages is vital to timely providing emergency medical services to crash victims. This study developed a crash emergency response management framework that requires basic crash information for...
journal article 2024
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Xie, yukun (author)
Research pertaining to end-use water analysis plays a pivotal role in enabling local communities to enhance their management of pipelines, water resources, and associated policies. Nowadays, various end-use models have been developed based on diverse databases and measurements. Nonetheless, a predominant drawback prevalent in most of these...
master thesis 2023
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Çil, Ata (author)
Autonomous driving is a complex problem that can potentially be solved using artificial intelligence. The complexity stems from the system's need to understand the surroundings and make appropriate decisions. However, there are various challenges in constructing such a sophisticated system. One of the main challenges is to make the agent learn...
bachelor thesis 2023
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Nachev, Nikola (author)
Accurate traffic forecasts are a key element in improving the traffic flow of urban cities. An efficient approach to this problem is to use a deep learning Long Short Term Memory (LSTM) model. Including weather data in the model can improve prediction accuracy because traffic volumes are sensitive to weather changes. The aim of this study is to...
bachelor thesis 2023
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Zhang, Xinqi (author), Shi, Jihao (author), Yang, M. (author), Huang, Xinyan (author), Usmani, Asif Sohail (author), Chen, Guoming (author), Fu, Jianmin (author), Huang, Jiawei (author), Li, Junjie (author)
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions. This study proposes a leakage detection and localization approach by integrating the attention...
journal article 2023
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Chen, Qinyu (author), Chang, Yaoxing (author), Kim, Kwantae (author), Gao, C. (author), Liu, Shih Chii (author)
Keyword spotting (KWS) is an important task on edge low-power audio devices. A typical edge KWS system consists of a front-end feature extractor which outputs mel-scale frequency cepstral coefficients (MFCC) features followed by a back-end neural network classifier. KWS edge designs aim for the best power-performance-area metrics. This work...
conference paper 2023
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Presekal, A. (author), Stefanov, Alexandru (author), Subramaniam Rajkumar, Vetrivel (author), Palensky, P. (author)
Electrical power grids are vulnerable to cyber attacks, as seen in Ukraine in 2015 and 2016. However, existing attack detection methods are limited. Most of them are based on power system measurement anomalies that occur when an attack is successfully executed at the later stages of the cyber kill chain. In contrast, the attacks on the Ukrainian...
journal article 2023
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de Alvear Cardenas, Jose Ignacio (author)
Despite the camera being ubiquitous to unmanned aerial vehicles (UAVs), it has not been used for fault detection and diagnosis (FDD) due to the nonexistence of UAV multi-sensor datasets that include actuator failure scenarios. This thesis proposes a knowledge-based FDD framework based on a lightweight Long-Short Term Memory network that fuses...
master thesis 2022
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van den Belt, Glenn (author)
Earthquakes can have tremendous effects. They can result in casualties, massive damage, and hurt the economy. Therefore, one would like to predict earthquakes as early as possible and with the highest accuracy possible. This paper contains the proposal for the optimal prediction-time, which is the time between the execution of a prediction and...
bachelor thesis 2022
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Georgiev, Gancho (author)
Earthquakes are one of the most destructive natural phenomena, both in terms of human lives, and property damage. Although they are treated as a random phenomenon, the ability to predict them, even few seconds before they occur, could be of great benefit to society. Lots of research has been done on this topic but without any significant results...
bachelor thesis 2022
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Krisiukėnas, Pijus (author)
Due to the devastating consequences of earthquakes, predicting their occurrence before the first strike has been a long standing research topic. Deep learning models have been used to facilitate prediction, using seismograph data to attempt to classify an earthquake right before it happens. However, this is a difficult task and research needs to...
bachelor thesis 2022
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Zhu, Kevin (author)
Earthquake prediction is the field of seismology concerned with predicting the time, location, and magnitude of earthquakes within a small time frame, usually defined in terms of minutes or seconds before an event. Such predictions can have a large impact on minimizing the damage caused by these seismic events, by providing early warnings to the...
bachelor thesis 2022
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Kortekaas, Steven (author)
This thesis investigates the application of machine learning models on foreign exchange data around the WM/R 4pm Closing Spot Rate (colloquially known as the WMR Fix). Due to the nature of the market dynamics around the WMR Fix, inefficiencies can occur and therefore some predictability might be expected. We aim to find these inefficiencies....
master thesis 2022
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Wilkesmann, Florian (author)
Around the world, authorities try to increase the attractiveness of multimodal public transport (PT)-related trips to reduce car usage. To achieve this, a seamless combination between the different modes is necessary. The Dutch train station operator NS tries to enhance the combination of the bike and train by providing a train station-based...
master thesis 2022
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Du, XIANGYU (author)
Earthquake prediction has raised many concerns nowadays, due to the massive loss caused by earthquakes, as well as the significance of accurate forecasting. Lots of trials have been investigated and experimented but few achieved satisfying results on short-term prediction (i.e., usually those earthquakes that will happen in three months). It is...
bachelor thesis 2022
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Hashmi, Irtaza (author)
Earthquakes are one of the most dangerous natural disasters that occur worldwide. Predicting them is one of the unsolved problems in the field of science. In the past decade, there has been an increase in seismic monitoring stations worldwide, which has allowed us to design and implement data-driven and deep learning solutions. In this paper, we...
bachelor thesis 2022
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Posthuma, Luuk (author)
Aircraft maintenance is critical to an airline's operations to ensure the reliability, availability, and safety of their assets. Recently, the approach of using component prognostics in aircraft maintenance has received increasing attention in academic- and industrial research. Predictive maintenance has demonstrated promising results in using...
master thesis 2022
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Dong, Y. (author), Patil, Sandeep (author), Farah, H. (author), van Arem, B. (author)
Reliable and accurate lane detection is of vital importance for the safe performance of Lane Keeping Assistance and Lane Departure Warning systems. However, under certain challenging peculiar circumstances (e.g., marking degradation, serious vehicle occlusion), it is quite difficult to get satisfactory performance in accurately detecting the...
poster 2022
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Tapia, Estefania Alexandra (author), Colomé, Delia Graciela (author), Rueda, José L. (author)
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental importance for the operation security of power systems. Both phenomena can be mutually influenced in weak power systems due to the proliferation of power electronic interface devices and the phase-out of conventional heavy machines (e.g., thermal power...
journal article 2022
Searched for: subject%3A%22Long%255C+Short%255C-term%255C+Memory%22
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