Trusted Application Using Biometrics for Android Environment

Nandhini, A. Sunitha; Helmi, Rabab Alayham Abbas; Ashour, Marwan Abdul Hameed; Jamal, Arshad

doi:10.1109/cspa48992.2020.9068715

Cited by 13 publications

(5 citation statements)

References 11 publications

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“…It was revealed that 0.2% concentration for 10 minutes had no efficacy versus coronavirus while 0.05% was very efficient [23]. In contrast, 0.02% chlorhexidine digluconate was fundamentally inadequate [24][25][26][27].…”

Section: Resultsmentioning

confidence: 99%

2019 Novel Coronavirus Disease (Covid-19): Toward a Novel Design for Disinfection Robot to Combat Coronavirus (Covid-19) Using IoT Based Technology

Mohammed

Hazairin

Arif

et al. 2021

2021 IEEE 12th Control and System Graduate Research Colloquium (ICSGRC)

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Coronavirus Disease 19 or well known asCovid-19 is infectious disease that attack human respirator system. This virus is contagious due to its fast transmission from small droplets that come to people that sneezing, coughing, or even talking. This virus can stay in air for long time and it also can survive on the inanimate surface things. During this time, some places like hospital, mall, and station are places where crowds gathered. People in those places have possibility to spread the virus not only through close contact but also due to touching the infected surfaces. That is why device that able to clean the infected surfaces needed. The Internet of Things based robots may give big impact in combating the coronavirus that stay on inanimate surfaces. The proposed system is the robot that able to disinfect the surfaces of things using UV-C lights. The implementation of UV disinfectant robot will indeed help health authorities in reducing the transmission.

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Section: Resultsmentioning

confidence: 99%

2019 Novel Coronavirus Disease (Covid-19): Toward a Novel Design for Disinfection Robot to Combat Coronavirus (Covid-19) Using IoT Based Technology

Mohammed

Hazairin

Arif

et al. 2021

2021 IEEE 12th Control and System Graduate Research Colloquium (ICSGRC)

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show abstract

“…To forecast data with trends, Holt expanded single exponential smoothing to linear exponential smoothing with trends. Holt's linear exponential smoothing consists of two constants, α and β (with values between 0,1), and three equations [2,8,13]:…”

Section: Exponential Smoothing Modelmentioning

confidence: 99%

“…A variable's future value is supposed to be a linear function of many past observations and random errors in an autoregressive integrated moving average model. As a result, a nonseasonal time series can be modeled as a mixture of past values and errors, which can be expressed as ARIMA (p,d,q) or as follows [1], [3], [6], [13]:…”

Section: Arima Modelmentioning

confidence: 99%

“…The accuracy of the future forecast is the most important thing. The most common measure of error accuracy is [1], [13], [19]:…”

Section: Measuring Forecast Accuracymentioning

confidence: 99%

“…Studies relating to predicting Bitcoin have been relatively scanty (few) and there is no study focusing on the hybrid model [1], [3], [6], [13]. Previous studies have primarily concentrated on Comparison between traditional (exponential smoothing, ARIMA) and modern models (artificial neural network ANN) of forecasting methods to determine the best model, without interest in the fluctuations in time series behavior that may arise in the future [4,6,7,9,12,14,17].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bitcoin Prediction with a hybrid model

Ashour¹,

Ahmed²

2023

PEN

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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction accuracy criterion and matching curve-fitting in this work demonstrated that if the residuals of the revised model are white noise, the forecasts are unbiased. Future work investigating robust hybrid model forecasting using fuzzy neural networks would be very interesting.

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Electricity Consumption Forecasting in Iraq with Artificial Neural Network

Ashour

Alashari

2021

Lecture Notes in Networks and Systems

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Trusted Application Using Biometrics for Android Environment

Cited by 13 publications

References 11 publications

2019 Novel Coronavirus Disease (Covid-19): Toward a Novel Design for Disinfection Robot to Combat Coronavirus (Covid-19) Using IoT Based Technology

2019 Novel Coronavirus Disease (Covid-19): Toward a Novel Design for Disinfection Robot to Combat Coronavirus (Covid-19) Using IoT Based Technology

Bitcoin Prediction with a hybrid model

Electricity Consumption Forecasting in Iraq with Artificial Neural Network

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