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Reliability of electric vehicle charging infrastructure:A cross-lingual deep learning approach

Communications in Transportation Research 2023年第1期3卷 81-91页

作者： Yifan Liu Azell Francis Catharina Hollauer M.Cade Lawson omar shaikh Ashley Cotsman Khushi Bhardwaj Aline Banboukian Mimi Li Anne Web omar Isaac Asensio School of Public Policy Georgia Institute of TechnologyAtlanta30332USA Sam Nunn School of International Affairs Georgia Institute of TechnologyAtlanta30332USA School of Civil&Environmental Engineering Georgia Institute of TechnologyAtlanta30332USA H.Milton Stewart School of Industrial and Systems Engineering Georgia Institute of TechnologyAtlanta30332USA School of Computer Science Georgia Institute of TechnologyAtlanta30332USA School of Computer Science Stanford UniversityPalo Alto94305USA School of Economics Georgia Institute of TechnologyAtlanta30332USA Institute for Data Engineering&Science(IDEaS) Georgia Institute of TechnologyAtlanta30332USA

Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation *** of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across *** this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including *** investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously *** find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of *** evidence contrasts with predictions in the *** European markets,where the performance is closer to *** also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.

关键词： Electric vehicles Consumer behavior Charging infrastructure Public policy Machine learning Natural language processing Transformer algorithms

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Thalassemia Screening by Sentiment Analysis on Social Media Platform Twitter

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Computers, Materials & Continua 2023年第7期76卷 665-686页

作者： Wadhah Mohammed M.Aqlan Ghassan Ahmed Ali Khairan Rajab Adel Rajab Asadullah shaikh Fekry Olayah Shehab Abdulhabib Saeed Alzaeemi Kim Gaik Tay Mohd Adib omar Ernest Mangantig School of Computer Sciences Universiti Sains MalaysiaUSM11800PenangMalaysia College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia86400JohorMalaysia IPPT Universiti Sains MalaysiaUSM11800PenangMalaysia

Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood *** severe forms,it can lead to *** genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for ***,controlling thalassemia is extremely important and is made by promoting screening to the general population,particularly among thalassemia *** Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like people’s health conditions and major public health *** individuals’sentiments in these tweets helps the research centers to formulate strategies to promote thalassemia screening to the *** effective Lexiconbased approach has been introduced in this study by highlighting a classifier called valence aware dictionary for sentiment reasoning(VADER).In this study applied twitter intelligence tool(TWINT),Natural Language Toolkit(NLTK),and VADER constitute the three main *** represents a gold-standard sentiment lexicon,which is basically tailored to attitudes that are communicated by using social *** contribution of this study is to introduce an effective Lexicon-based approach by highlighting a classifier calledVADERto analyze the sentiment of the general population,particularly among thalassemia carriers on the social media platform *** this study,the results showed that the proposed approach achieved 0.829,0.816,and 0.818 regarding precision,recall,together with F-score,*** tweets were crawled using the search keywords,“thalassemia screening,”thalassemia test,“and thalassemia diagnosis”.Finally,results showed that India and Pakistan ranked the highest in mentions in tweets by the public’s conversations on thalassemia screening with 181 and 164 tweets,respectively.

关键词： Social media platform Twitter screening thalassemia lexicon-based VADER

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Quantitative Analysis of Geomorphometric Parameters of Wadi Kerak, Jordan, Using Remote Sensing and GIS

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Journal of Water Resource and Protection 2015年第6期7卷 456-475页

作者： Yahya Farhan Ali Anbar omar Enaba Nisrin Al-shaikh Department of Geography University of Jordan Amman Jordan

Geomorphometric analysis was carried out to illustrate the drainage characteristics and morphology of Wadi Kerak watershed, southern Jordan. The basic and derived morphometric parameters (linear, areal and relief aspects of drainage network) for the basin were determined using ASTER DEM (30 m resolution) and Geographic Information System (GIS). These parameters describe the basin drainage network, geometry, texture, and relief characteristics. The hypsometric curve, hypsometric integral and clinographic curve were also prepared using topographic maps of 1:50,000 scale. Findings have revealed that W. Kerak is in the youth-age stage of geomorphic evolution. Fluvial erosion associated with successive phases of rejuvenation plays a significant role in drainage basin development, whereas structure and tectonics, lithology and relief dictate the drainage pattern and morphological setting of the catchment. The drainage area of the watershed is 190.9 km2 and constitutes a 5th-order drainage basin. The commonly observed drainage patterns are the trellis type, with sub-dendritic pattern recognized in the upper catchment. The drainage pattern, and the semi-linear alignment of main and branching drainage indicate the prominent influence of the Kerak-Al-fiha fault system on the drainage network. High dissection, relative relief, relief ratio, steep slopes and breaks of slopes are characteristic of W. Kerak. Morphometric analysis reveals that four rejuvenation phases caused severe erosion and down cutting activity in the past, and it is still susceptible to surface erosion at present.

关键词： ASTER DEM Drainage Morphometry Dissection Index Rejuvenation Hypsometric Analysis Clinographic Curve

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Use of instantaneous energy of ABR signals for fast detection of wave V

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Journal of Biomedical Science and Engineering 2010年第8期3卷 816-821页

作者： Adeela Arooj Mohd Rushaidin Muhamed Sheikh Hussain shaikh Salleh Mohd Hafizi omar 不详

Brainstem evoked response audiometry is a powerful diagnostic technique in audiology, otology and neurology. ABR(Auditory Brainstem Response) machine has been very useful and popular in past two decades for detection of hearing defects and pathologies in newborns and children. In ABR, wave V is the most prominent and robust wave that has been used as indicator of hearing loss. However, a fast detection of the wave V is necessary in order to implement newborn hearing screening. Researchers have introduced different kind of signal processing technique in order to achieve this target and one of this is Fast Fourier Transform (FFT) and Wavelet Transform. In this study, the instantaneous energy of ABR signal had been introduced as a marker to identify the ABR waves. Study showed that the instantaneous energy of auditory brainstem response can be used as a marker to identify the ABR waves. This study had proposed a platform for fast hearing screening system.

关键词： Auditory Brainstem Response Neonate Hearing Screening Instantaneous Energy

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