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David Suda and Luke Spiteri
We implement hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) on Bitcoin/US dollar (BTC/USD) with the aim of market phase detection. We make analogous comparisons to Standard and Poor?s 500 (S and P 500), a benchmark traditional stock in...
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Mahmoud Elmezain, Majed M. Alwateer, Rasha El-Agamy, Elsayed Atlam and Hani M. Ibrahim
Automatic key gesture detection and recognition are difficult tasks in Human?Computer Interaction due to the need to spot the start and the end points of the gesture of interest. By integrating Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs),...
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Francesca Romana Cavallo, Christofer Toumazou and Konstantin Nikolic
The modern sedentary lifestyle is negatively influencing human health, and the current guidelines recommend at least 150 min of moderate activity per week. However, the challenge is how to measure human activity in a practical way. While accelerometers a...
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Ivan Arismendi, Jason B. Dunham, Michael P. Heck, Luke D. Schultz and David Hockman-Wert
Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the desc...
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Norah Abanmi, Heba Kurdi and Mai Alzamel
The prevalence of malware attacks that target IoT systems has raised an alarm and highlighted the need for efficient mechanisms to detect and defeat them. However, detecting malware is challenging, especially malware with new or unknown behaviors. The ma...
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Daniel Fernando Tello Gamarra
Pág. 1 - 16
We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abs...
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Francesca Paradiso, Federica Paganelli, Dino Giuli and Samuele Capobianco
In this paper, we address the problem of energy conservation and optimization in residential environments by providing users with useful information to solicit a change in consumption behavior. Taking care to highly limit the costs of installation and ma...
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Félix Gélinas-Gascon and Richard Khoury
Negative social media usage during the COVID-19 pandemic has highlighted the importance of understanding the spread of misinformation and toxicity in public online discussions. In this paper, we propose a novel unsupervised method to discover the structu...
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Dina Oralbekova, Orken Mamyrbayev, Mohamed Othman, Dinara Kassymova and Kuralai Mukhsina
This article provides a comprehensive survey of contemporary language modeling approaches within the realm of natural language processing (NLP) tasks. This paper conducts an analytical exploration of diverse methodologies employed in the creation of lang...
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André B. Peres, Mário C. Espada, Fernando J. Santos, Ricardo A. M. Robalo, Amândio A. P. Dias, Jesús Muñoz-Jiménez, Andrei Sancassani, Danilo A. Massini and Dalton M. Pessôa Filho
This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one with...
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Massimo Guidolin and Manuela Pedio
In this paper, we conduct a thorough investigation of the predictive ability of forward and backward stepwise regressions and hidden Markov models for the futures returns of several commodities. The predictive performance relative a standard AR(1) benchm...
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Elie Azeraf, Emmanuel Monfrini and Wojciech Pieczynski
Practitioners have used hidden Markov models (HMMs) in different problems for about sixty years. Moreover, conditional random fields (CRFs) are an alternative to HMMs and appear in the literature as different and somewhat concurrent models. We propose tw...
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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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Shengxian Tang, Hexu Liu, Manea Almatared, Osama Abudayyeh, Zhen Lei and Alvis Fong
Construction-oriented quantity take-off (QTO) refers to the process of determining the quantities for construction items or work packages in accordance with their descriptions. However, the current construction-oriented QTO practice relies on estimators?...
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Constandina Koki, Stefanos Leonardos and Georgios Piliouras
We study the Bitcoin and Ether price series under a financial perspective. Specifically, we use two econometric models to perform a two-layer analysis to study the correlation and prediction of Bitcoin and Ether price series with traditional assets. In t...
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Mohammad Ali Humayun, Ibrahim A. Hameed, Syed Muslim Shah, Sohaib Hassan Khan, Irfan Zafar, Saad Bin Ahmed and Junaid Shuja
Automatic Speech Recognition, (ASR) has achieved the best results for English, with end-to-end neural network based supervised models. These supervised models need huge amounts of labeled speech data for good generalization, which can be quite a challeng...
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Xinli Geng, Huawei Liang, Biao Yu, Pan Zhao, Liuwei He and Rulin Huang
Driving through dynamically changing traffic scenarios is a highly challenging task for autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles? driving behaviors plays a crucial role in autonomous vehicles. Most traditional...
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Riham Ginzarly, Ghaleb Hoblos and Nazih Moubayed
Due to the accelerating pace of environmental concerns and fear of the depletion of conventional sources of energy, researchers are working on finding renewable energy sources of power for different axes of life. The transportation sector has intervened ...
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Jiangyi Liu, Chunping Wang, Wei Wang and Zheng Li
Most multi-target tracking filters assume that one target and its observation follow a Hidden Markov Chain (HMC) model, but the implicit independence assumption of the HMC model is invalid in many practical applications, and a Pairwise Markov Chain (PMC)...
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Jeong-Sik Park and Na Geng
Most conventional speech recognition systems have mainly concentrated on voice-driven control of personal user devices such as smartphones. Therefore, a speech recognition system used in a special environment needs to be developed in consideration of the...
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