EEG in game user analysis: A framework for expertise classification during gameplay

Hafeez, Tehmina; Saeed, Sanay Muhammad Umar; Arsalan, Aamir; Anwar, Syed Muhammad; Ashraf, Muhammad Usman; Alsubhi, Khalid

doi:10.1371/journal.pone.0246913

Cited by 19 publications

(17 citation statements)

References 45 publications

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“…89 Hence, UX researchers apply physiological measurements to uncover the true experience of a user employing a product. 90 For instance, eye tracking technology is able to record visual attention 91,92 ; electroencephalography can detect emotional responses [93][94][95] ; galvanic skin response can measure stress and arousal through skin conductivity 96,97 ; and electrocardiogram (ECG) and electromyogram (EMG) can measure stress levels 98,99 and muscle-arousing activities that highlight the difficulties of product use on a cognitive level. 19…”

Section: Ux Research Methodsmentioning

confidence: 99%

User‐centered approaches in software development processes: Qualitative research into the practice of Hungarian companies

Szabó

Hercegfi

2022

J Software Evolu Process

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Integrating user‐centered approaches into development processes is one of the main challenges nowadays that derives from different objectives of software engineering (SE) and human‐computer interaction (HCI) fields. For SE experts, the main goal is quality code creation, whereas for HCI professionals, it is the continuous product interaction with the users. The major question is what tools and timings can be used together to achieve these goals effectively. Therefore, this article provides comparative, exploratory, and qualitative research about possible solutions on how practitioners transfer HCI values and practices to SE processes. The current practice of software companies was studied by conducting interviews on a sample of 13 Hungarian Information Technology companies to explore the SE processes in respect of several dimensions (applied development models, the integrity of user‐centered methods, and the user experience [UX] maturity). According to preliminary expectations, the development processes of the various companies proceed in different steps; nevertheless, they can be well grouped together based on the UX methods applied. The results representing the various user‐centered processes can be considered useful for future decision makers of software companies worldwide.

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Section: Ux Research Methodsmentioning

confidence: 99%

User‐centered approaches in software development processes: Qualitative research into the practice of Hungarian companies

Szabó

Hercegfi

2022

J Software Evolu Process

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“…The main strength of magnetic resonance imaging (MRI) is the ability to measure different tissue differences. To evaluate our results, we compare the number of different network depths, input features, and training topics [34][35][36][37][38].…”

Section: Literature Workmentioning

confidence: 99%

A New Framework for Accelerating Magnetic Resonance Imaging using Deep Learning along with HPC Parallel Computing Technologies

Aljahdali¹

2022

IJACSA

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MRI (magnetic resource imaging) has played a vital role in emerging technologies because of its non-invasion principle. MR equipment is traditional procedure being used for imaging biological structures. In medical domain, MRI is a most important tool being used for staging in clinical diagnosis that has ability to furnish rich physiological and functional information and radiation and non-ionizing nature. However, MRI is highly demanding in several clinical applications. In this paper, we have proposed a novel deep learning based method that accelerates MRI using a huge number of MR images. In proposed method, we used supervised learning approach that performs network training of given datasets. It determines the required network parameters that afford an accurate reconstruction of under-sampled acquisitions. We also designed offline based neural network (NN) that was trained to discover the relationship between MR images and K-space. All the experiments were performed over advanced NVIDIA GPUs (Tesla k80 and GTX Titan) based computers. It was observed that the proposed model outperformed and attained <0.2% error rate. With our best knowledge, our method is the best approach that can be considered as leading model in future.

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“…The reason for accurate results provided by this algorithm is that it produces results in the form of a tree structure with the parallel approach by remembering in mind the specification and configuration of the model [42]. It can produce state-of-the-art outcomes with minimum sources [47], [71][72][73][74][75][76][77].…”

Section: Decision Treementioning

confidence: 99%

Comparative Analysis of Machine Learning Techniques for Predicting Air Pollution

Ashraf¹,

Akram²,

Usman³

2022

Research Journal Of Computer Science And Information Technology

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The modern and motorized way of life has cultured air pollution. Air pollution has become the biggest rival of robust living. This situation is becoming more lethal in developing countries and so in Pakistan. Hence, this inquiry was carried out to propose an architecture design that could make real-time prediction of air pollution with another purpose of scanning the frequently adopted algorithm in past investigations. In addition, it was also intended to narrate the toxic effects of air pollution on human health. So, this research was carried out on a large dataset of Seoul as an adequate dataset of Pakistan was not attainable. The dataset consisted of three years (2017-2019) including 647,512 instances and 11 attributes. The four distinctive algorithms termed Random Forest, Linear Regression, Decision Tree and XGBoosting were employed. It was inferred that XGB is more promising and feasible in predicting concentration level of NO2, O3, SO2, PM10, PM2.5 and CO with the lowest RMSE and MAE values of 0.0111, 0.0262, 0.0168, 49.64, 41.68 and 0.1856 and 0.0067, 0.0096, 0.0017, 12.28, 7.63 and 0.0982 respectively. Furthermore, it was found out as well that the Random Forest was preferred mostly in the previous studies related to air pollution prophecy while many probes supported that air pollution is very detrimental to human health especially long-lasting exposure causes lung cancer, respiratory and cardiovascular diseases.

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EEG in game user analysis: A framework for expertise classification during gameplay

Cited by 19 publications

References 45 publications

User‐centered approaches in software development processes: Qualitative research into the practice of Hungarian companies

User‐centered approaches in software development processes: Qualitative research into the practice of Hungarian companies

A New Framework for Accelerating Magnetic Resonance Imaging using Deep Learning along with HPC Parallel Computing Technologies

Comparative Analysis of Machine Learning Techniques for Predicting Air Pollution

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