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2nd International Conference on Computing Advancements: Age of Computing and Augmented Life, ICCA 2022

作者： Biswas, Ananna Mashrur, Fazla Rabbi Rahman, Khandoker Mahmudur Miya, Mohammad Tohidul Islam Sarker, Farhana Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab United International University Dhaka Bangladesh School of Business and Economics United International University Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Dhaka Bangladesh

ISBN: (纸本)9781450397346

Neuromarketing has opened a new door in marketing research understanding behavioral economics with the help of Neuroscience. Over the past decade, Neuroscientists, Psychiatrists, Engineers, and Market-researchers have conducted several groundbreaking studies aiming to understand consumers' motivations, preferences, and decisions. However, these studies and practices are mainly based on developed countries. In this study, we outline the opportunities, real-life applications, future scenarios and shed light on the challenges faced by the researchers, marketers, and policymakers in developing countries including Bangladesh. Moreover, we have focused on the significant brain lobe involving neuromarketing research with the explanation of current technologies used in this area. We have concluded with some feasible recommendations to continue and sustain the growth of the neuromarketing field in developing countries. We expect that this study will give the directions on the inauguration of neuromarketing research in developing countries like Bangladesh that will help technologists, researchers, and marketers understand the advantages, challenges, and state-of-art of neuromarketing research. © 2022 ACM.

关键词： Brain computer interface

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An EEG-based intelligent Neuromarketing System for Predicting Consumers’ Choice 4th

An EEG-based Intelligent Neuromarketing System for Predicti...

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International Conference on 4th Industrial Revolution and Beyond, IC4IR 2021

作者： Mashrur, Fazla Rabbi Rahman, Khandoker Mahmudur Miya, Mohammad Tohidul Islam Vaidyanathan, Ravi Anwar, Syed Ferhat Sarker, Farhana Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab Institute of Advanced Research United International University Dhaka Bangladesh School of Business and Economics United International University Dhaka Bangladesh Department of Mechanical Engineering Imperial College London London United Kingdom Institute of Business Administration University of Dhaka Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh

ISBN: (纸本)9789811980312

Marketers use different marketing strategies to elicit the desired response from the target customers. To measure customer engagement, they usually conduct one-on-one interviews, surveys, broad polls, and focus group discussions. However, these are costly and sometimes unreliable. On the other hand, neuromarketing measures customer response to marketing stimuli by measuring the electrical activity of the brain and has the potential to address these drawbacks. which can be overcome by neuromarketing. In this work, we proposed a prediction algorithm that can identify consumer affective attitude (AA) and purchase intention (PI) from EEG signals from the brain. At first, the raw EEG signals are initially preprocessed to remove noise. After that, three features are extracted: time, frequency, and time frequency domain features. Wavelet packet transform is used to separate the EEG bands in time-domain feature extraction. Then, for feature selection, wrapper-based SVM-RFE is utilized. Finally, we use SVM to distinguish the classes in AA and PI. Results show that for SVM with radial basis function kernel performs better to classify positive and negative AA with an accuracy of 90 ± 4.33 and PI with an accuracy of 75 ± 2.5. So, EEG-based neuromarketing solutions can assist companies and organizations in accurately predicting future consumer preferences. As a result, neuromarketing based-solutions have the potential to increase sales by overcoming the constraints of traditional marketing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

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The Importance of Prescription Audits: Navigating Complexities and AI-Driven Advancement

The Importance of Prescription Audits: Navigating Complexiti...

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IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health

作者： Ferdous Wahid Anik Fahmid Al Rifat Marzia Zaman Farhana Sarkar Khondakar A. Mamun Advanced Intelligent Multidisciplinary Systems (AIMS) Lab IRIIC United International University Dhaka Bangladesh Department of Computer Science and Engineering United International University Dhaka Bangladesh CMED Health Limited Dhaka Bangladesh

ISBN: (数字)9798331534356

ISBN: (纸本)9798331534363

By detecting and reducing pharmaceutical prescription errors, prescription audits aim to ensure patient safety and efficiency in healthcare. Manual and artificial intelligence (AI) driven prescription audit with methods are the primary focus of the discussion, which also addresses the challenges and potential of prescription audits. Prescription audits will also be labour-intensive, time-consuming, and entail a range of prescribing modes. Automation keeps up with rapid changes thanks to well-established infrastructure and data quality. This might stand alone in reducing pharmaceutical errors, building up professional responsibility, and improving patient outcomes in an increasingly digital health arena. However, several developing technologies in sectors such as CDSSs, ML, and hybrid models hold enormous potential for solving such obstacles. Such technology will help health organisations streamline audits, automatically detect errors in real-time, and enhance overall prescription precision. To ensure safety and effectiveness, the deployment of such automated systems relies on a comprehensive analysis of ethical concerns and adherence to regulatory requirements. The research reveals that these technologies are expanding for application in various healthcare settings, leading to more effective and reliable therapy.

关键词： Navigation Telemedicine Precision medicine Manuals Real-time systems Safety Reliability Artificial intelligence Medical diagnostic imaging Pharmaceuticals

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AI Reception: An intelligent Bengali Receptionist System Integrating with Face, Speech, and Interaction Recognition 1

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1st International Conference on Bangabandhu and Digital Bangladesh, ICBBDB 2021

作者： Nabid, Rahad Arman Pranto, Shehan Irteza Mohammed, Nabeel Sarker, Farhana Huda, Mohammad Nurul Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab United International University Dhaka Bangladesh Department of CSE North South University Dhaka Bangladesh Department of CSE University of Liberal Arts Bangladesh Dhaka Bangladesh Department of CSE United International University Dhaka Bangladesh

ISBN: (数字)9783031171819

ISBN: (纸本)9783031171802

Artificial Intelligence enabled automated reception to perform as a human receptionist to avoid face-to-face interaction among mass people regarding their daily service in the current pandemic. Inspired by their current problem of mass congestion, our proposed AI-based Smart Reception can authenticate users and interact in Bangla language with humans by responding to university-domain-related queries, resulting in better business service and outcomes. We used OpenFace face recognition for authentication, having an accuracy of 92.92% with 1 × 10- 5 second training time for a new image by saving the image dataset as a collection of an array file. The Interaction Recognition system consists of three modules: Automatic Speech Recognition (ASR), Interactive Agent, and Text-to-Speech (TTS) Synthesis. We used the OpenSLR- Large Bengali ASR Training Data to train the Deep Speech 2 model for ASR with a Word Error Rate (WER) of 42.15%. We tested our developed database management architecture for the Interaction Recognition system with the three-step evaluation using BERT sentence transformer (paraphrase-mpnet-base-v2) that provided satisfactory responses with 92% accuracy, increasing the receptionist performance significantly. TTS module relays on WavNet gTTS model. Our research also demonstrated that a developed AI-based system could be an adaptive solution for any domain-specific reception system responsible for systematic and efficient customer service offline and online. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Speech synthesis

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BlinkFruity: A real-time EEG based neurofeedback game for brain-computer interface 2

BlinkFruity: A real-time EEG based neurofeedback game for br...

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2nd International Conference on advanced Information and Communication Technology, ICAICT 2020

作者： Parbez, Rana Md Shahariar Mamun, Khondaker A. United International University Advanced Intelligent Multidisciplinary Systems Lab Dhaka Bangladesh

ISBN: (纸本)9780738123233

The Brain-Computer Interface (BCI) is a communication channel between the brain and the computer. It works by detecting the production of currents due to brain cell activity. Among many non-invasive brain signal recording methods, Electroencephalography (EEG) is one of the most popular methods. EEG controlled applications widely range from strictly medical to non-medical applications. Non-medical applications can not only be used for entertainment purposes, but also can help a subject to experience BCI application, achieve better control with rehabilitation systems and can be a strong motivation to practice BCI system. Brain signals are weak and contain lots of artifacts like muscle movements, cardiac, eye blink, power source, and amplitude artifacts. Although eye blink is considered as one of the strongest artifacts, this study uses eye blink as a tool to control signal to play BlinkFruity game, where users collect fruits into a basket using eye blink only. To attain this objective, at first, the brain activity was recorded using OpenBCI device and 500ms window data was taken to process in real-time. Then the notch filter was applied to remove powerline noise. The eye blink was detected by using signal thresholding method reading from EEG data. Blink detection accuracy of 86.23% was obtained using blink control applying on first three subjects. © 2020 IEEE.

关键词： Electroencephalography

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BlinkFruity: A Real-Time EEG Based Neurofeedback Game for Brain-Computer Interface

BlinkFruity: A Real-Time EEG Based Neurofeedback Game for Br...

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advanced Information and Communication Technology (ICAICT), International Conference on

作者： Rana Md Shahariar Parbez Khondaker A. Mamun Advanced Intelligent Multidisciplinary Systems Lab United International University Dhaka Bangladesh

ISBN: (数字)9780738123233

ISBN: (纸本)9781665422406

关键词： Entertainment industry Games Tools Electroencephalography Real-time systems Brain-computer interfaces Reliability

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Predictive analysis of the effects of personality traits on an academic program 2

Predictive analysis of the effects of personality traits on ...

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2nd International Conference on advanced Information and Communication Technology, ICAICT 2020

作者： Kamal, Nabila Sarker, Farhana Mukta, Md. Saddam Hossain Mamun, Khondaker A. United International University Advanced Intelligent Multidisciplinary Systems Lab Department of Computer Science and Enginnering Dhaka Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh United International University Department of Computer Science and Enginnering Dhaka Bangladesh

ISBN: (纸本)9780738123233

The choice of academic program is a crucial selection as this decision plays a major role in enhancing opportunities in career path. Young adolescents often experience indecisions while choosing their academic major, which may lead to uncertainty in future. Therefore, to assist students to find the right field of study, several researches related to personality dynamics have been conducted in recent years to determine correlation between academic fields and personalities of students and the result showed evident association. Consequently, this increases the productivity and success rate in comparison. This study determines the differences amongst the students of three popular academic programs in Bangladesh and envisage the appropriate academic choice for the prospective students by analyzing their personality traits. For this study, we have collected data from a total of 135 participants. We used students' Big5 Personality Factors (Extraversion, Openness, Agreeableness, Emotional Stability, and Conscientiousness), and academic information to develop the prediction model. Using Gaussian Classifier along with 10-fold cross-validation method, we have achieved an accuracy of 91.1%. The findings of this study demonstrate that the proposed framework has a great potential in assisting prospective students to make an informed decision to determine the suitable higher study options while increasing academic motivation ratio. © 2020 IEEE.

关键词： Students

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A Comparative Study of Machine Learning Approaches for Recommending University Faculty

A Comparative Study of Machine Learning Approaches for Recom...

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Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Nabila Kamal Farhana Sarker Khondaker A. Mamun Advanced Intelligent Multidisciplinary Systems Lab United International University Dhaka Bangladesh University of Liberal Arts Bangladesh (ULAB) Dhaka Bangladesh

ISBN: (数字)9781665404891

ISBN: (纸本)9781665404907

Academic program selection is a vital decision as it plays a substantial role in enhancing opportunities in career paths. Numerous researches utilizing psychometrics have been conducted in recent years, and result reveals an evident association between academic fields and personality traits of students. To assist students in making an informed academic decision, this study analyzes the differences amongst the students of nine study programs in Bangladesh and envisages the appropriate academic choice among these nine fields for the prospective students by analyzing their academic grades, personality traits, and intelligence. For the experiment, we have collected data from 103 participants and used students' academic grades, Big-5 personality traits, and Factor B (Reasoning) of 16PF to develop classification models by utilizing two classification approaches. Results show that the Hierarchical classification approach using Random Forest Classifier outperformed the One-level Random Forest classifier approach by obtaining 96.1% accuracy for the 1st-level and 92.86%, 89.29%, and 94.74% respectively for 2nd-level. The findings of this study demonstrate that the proposed framework has great potential in assisting prospective students to make an informed decision to determine the suitable higher study options while unlocking human potential.

关键词： Industries Engineering profession Heuristic algorithms Forestry Data models Cognition Random forests

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Technological advancements and opportunities in Neuromarketing: a systematic review

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Brain Informatics 2020年第1期7卷 1-19页

作者： Rawnaque, Ferdousi Sabera Rahman, Khandoker Mahmudur Anwar, Syed Ferhat Vaidyanathan, Ravi Chau, Tom Sarker, Farhana Mamun, Khondaker Abdullah Al Advanced Intelligent Multidisciplinary Systems Lab Institute of Advanced Research United International University Dhaka Bangladesh School of Business and Economics United International University Dhaka Bangladesh Institute of Business Administration University of Dhaka Dhaka Bangladesh Department of Mechanical Engineering Imperial College London London United Kingdom Institute of Biomaterials & Biomedical Engineering University of Toronto Toronto Canada Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering United International University Dhaka Bangladesh

Neuromarketing has become an academic and commercial area of interest, as the advancements in neural recording techniques and interpreting algorithms have made it an effective tool for recognizing the unspoken response of consumers to the marketing stimuli. This article presents the very first systematic review of the technological advancements in Neuromarketing field over the last 5 years. For this purpose, authors have selected and reviewed a total of 57 relevant literatures from valid databases which directly contribute to the Neuromarketing field with basic or empirical research findings. This review finds consumer goods as the prevalent marketing stimuli used in both product and promotion forms in these selected literatures. A trend of analyzing frontal and prefrontal alpha band signals is observed among the consumer emotion recognition-based experiments, which corresponds to frontal alpha asymmetry theory. The use of electroencephalogram (EEG) is found favorable by many researchers over functional magnetic resonance imaging (fMRI) in video advertisement-based Neuromarketing experiments, apparently due to its low cost and high time resolution advantages. Physiological response measuring techniques such as eye tracking, skin conductance recording, heart rate monitoring, and facial mapping have also been found in these empirical studies exclusively or in parallel with brain recordings. Alongside traditional filtering methods, independent component analysis (ICA) was found most commonly in artifact removal from neural signal. In consumer response prediction and classification, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) have performed with the highest average accuracy among other machine learning algorithms used in these literatures. The authors hope, this review will assist the future researchers with vital information in the field of Neuromarketing for making novel contributions. © 2020, The Author(s).

关键词： Independent component analysis

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Communication Support Utilizing AAC for Verbally Challenged Children in Developing Countries During COVID-19 Pandemic 22nd

Communication Support Utilizing AAC for Verbally Challenged ...

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22nd International Conference on Human-Computer Interaction, HCI International 2020

作者： Farzana, Walia Sarker, Farhana Vaidyanathan, Ravi Chau, Tom Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Department of Mechanical Engineering Imperial College London London United Kingdom Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Canada

ISBN: (纸本)9783030607029

Functional communication is indispensable for child development at all times but during this COVID-19, non-verbal children become more anxious about social distancing and self-quarantine due to sudden aberration on daily designed practices and professional support. These verbally challenged children require the support of Augmentative and Alternative Communication (AAC) for intercommunication. Therefore, during COVID-19, assistance must be provided remotely to these users by a AAC team involving caregivers, teachers, Speech Language Therapist (SLT) to ensure collaborative learning and development of non-verbal child communication skills. However, most of the advanced AAC, such as Speech Generating Devices (SGD), Picture Exchange Communication System (PECS) based mobile applications (Android & iOS) are designed considering the scenario of developed countries and less accessible in developing countries. Therefore, in this study, we are focusing on representing feasible short term strategies, prospective challenges and as long term strategy, a cloud based framework entitled as "Bolte Chai+", which is an intelligent integrated collaborative learning platform for non-verbal children, parents, caregivers, teachers and SLT. The intelligent analytics within the platform monitors child overall progress by tracking child activity in mobile application and conversely support parents and AAC team to concentrate on individual child ubiquitous abilities. We believe, the proposed framework and strategies will empower non-verbal children and assist researchers, policy makers to acknowledge a definitive solution to implement AAC as communication support in developing countries during COVID-19 pandemic. © 2020, Springer Nature Switzerland AG.

关键词： intelligent systems

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