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Manuel Lopez-Martin, Antonio Sanchez-Esguevillas, Luis Hernandez-Callejo, Juan Ignacio Arribas and Belen Carro
This work brings together and applies a large representation of the most novel forecasting techniques, with origins and applications in other fields, to the short-term electric load forecasting problem. We present a comparison study between different cla...
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Siyu Qi, Minxue He, Raymond Hoang, Yu Zhou, Peyman Namadi, Bradley Tom, Prabhjot Sandhu, Zhaojun Bai, Francis Chung, Zhi Ding, Jamie Anderson, Dong Min Roh and Vincent Huynh
Salinity management in estuarine systems is crucial for developing effective water-management strategies to maintain compliance and understand the impact of salt intrusion on water quality and availability. Understanding the temporal and spatial variatio...
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Jialun Zhang, Donglin Dong and Longqiang Zhang
Estimating groundwater level (GWL) changes is crucial for the sustainable management of water resources in the face of urbanization and population growth. Existing prediction methods for GWL variations have limitations due to their inability to account f...
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Sumayh S. Aljameel, Manar Alzahrani, Reem Almusharraf, Majd Altukhais, Sadeem Alshaia, Hanan Sahlouli, Nida Aslam, Irfan Ullah Khan, Dina A. Alabbad and Albandari Alsumayt
Preeclampsia is one of the illnesses associated with placental dysfunction and pregnancy-induced hypertension, which appears after the first 20 weeks of pregnancy and is marked by proteinuria and hypertension. It can affect pregnant women and limit fetal...
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Jawaher Alghamdi, Yuqing Lin and Suhuai Luo
Efforts have been dedicated by researchers in the field of natural language processing (NLP) to detecting and combating fake news using an assortment of machine learning (ML) and deep learning (DL) techniques. In this paper, a review of the existing stud...
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Niraj Thapa, Zhipeng Liu, Dukka B. KC, Balakrishna Gokaraju and Kaushik Roy
The development of robust anomaly-based network detection systems, which are preferred over static signal-based network intrusion, is vital for cybersecurity. The development of a flexible and dynamic security system is required to tackle the new attacks...
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Merlijn Blaauw and Jordi Bonada
We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This a...
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Yijin Kim, Hong Joo Lee and Junho Shim
In online commerce systems that trade in many products, it is important to classify the products accurately according to the product description. As may be expected, the recent advances in deep learning technologies have been applied to automatic product...
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Mihael Gudlin, Miro Hegedic, Matija Golec and Davor Kolar
In the quest for industrial efficiency, human performance within manufacturing systems remains pivotal. Traditional time study methods, reliant on direct observation and manual video analysis, are increasingly inadequate, given technological advancements...
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Lucas Lopes Oliveira, Xiaorui Jiang, Aryalakshmi Nellippillipathil Babu, Poonam Karajagi and Alireza Daneshkhah
Early identification of acute gout is crucial, enabling healthcare professionals to implement targeted interventions for rapid pain relief and preventing disease progression, ensuring improved long-term joint function. In this study, we comprehensively e...
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Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap...
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Yang Zhang, Yuan Feng, Shiqi Wang, Zhicheng Tang, Zhenduo Zhai, Reid Viegut, Lisa Webb, Andrew Raedeke and Yi Shang
Waterfowl populations monitoring is essential for wetland conservation. Lately, deep learning techniques have shown promising advancements in detecting waterfowl in aerial images. In this paper, we present performance evaluation of several popular superv...
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Navid Khalili Dizaji and Mustafa Dogan
Brain tumors are one of the deadliest types of cancer. Rapid and accurate identification of brain tumors, followed by appropriate surgical intervention or chemotherapy, increases the probability of survival. Accurate determination of brain tumors in MRI ...
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Monika Rybczak and Krystian Kozakiewicz
Today, specific convolution neural network (CNN) models assigned to specific tasks are often used. In this article, the authors explored three models: MobileNet, EfficientNetB0, and InceptionV3 combined. The authors were interested in investigating how q...
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Yuhwan Kim, Chang-Ho Choi, Chang-Young Park and Seonghyun Park
In today?s society, where people spend over 90% of their time indoors, indoor air quality (IAQ) is crucial for sustaining human life. However, as various indoor activities such as cooking generate diverse types of pollutants in indoor spaces, IAQ has eme...
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Dejiang Wang, Quanming Jiang and Jinzheng Liu
In the field of building information modeling (BIM), converting existing buildings into BIM by using orthophotos with digital surface models (DSMs) is a critical technical challenge. Currently, the BIM reconstruction process is hampered by the inadequate...
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Fadwa Alrowais, Saud S. Alotaibi, Anwer Mustafa Hilal, Radwa Marzouk, Heba Mohsen, Azza Elneil Osman, Amani A. Alneil and Mohamed I. Eldesouki
Big Data analytics is a technique for researching huge and varied datasets and it is designed to uncover hidden patterns, trends, and correlations, and therefore, it can be applied for making superior decisions in healthcare. Drug?drug interactions (DDIs...
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Daudi Mashauri Migayo, Shubi Kaijage, Stephen Swetala and Devotha G. Nyambo
Applying deep learning models requires design and optimization when solving multifaceted artificial intelligence tasks. Optimization relies on human expertise and is achieved only with great exertion. The current literature concentrates on automating des...
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Gui Ren and Tao Meng
This paper proposes two data-driven models (including LSTM pricing model, WGAN pricing model) and an improved model of LSM based on GAN to analyze the pricing of convertible bonds. In addition, the LSM model with higher precision in traditional pricing m...
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Maisarah Mohd Sufian, Ervin Gubin Moung, Mohd Hanafi Ahmad Hijazi, Farashazillah Yahya, Jamal Ahmad Dargham, Ali Farzamnia, Florence Sia and Nur Faraha Mohd Naim
COVID-19, an infectious coronavirus disease, has triggered a pandemic that has claimed many lives. Clinical institutes have long considered computed tomography (CT) as an excellent and complementary screening method to reverse transcriptase-polymerase ch...
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