检索结果-内蒙古大学图书馆

Systematic comparison between a research-grade EEG device and a consumer-grade BCI device for predicting consumer preference using an ML framework

引用

Multimedia Tools and Applications 2025年 1-19页

作者： Ishtiaque, Farhan Miya, Mohammad Tohidul Islam Mashrur, Fazla Rabbi Rahman, Khandoker Mahmudur Vaidyanathan, Ravi Anwar, Syed Ferhat Sarker, Farhana Tat, Huam Hon Hamid, Abu Bakar Abdul Mamun, Khondaker A. AIMS Lab IIRIC UIU Dhaka Bangladesh School of Business and Economics United International University Dhaka Bangladesh Department of Biomedical Engineering University of Rochester RochesterNY United States Department of Mechanical Engineering Imperial College London London United Kingdom Office of the Vice Chancellor BRAC University Dhaka Bangladesh and Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Faculty of Business City University of Macau Taipa China Faculty of Business Information & Human Sciences Infrastructure University Kuala Lumpur Kuala Lumpur Malaysia Department of CSE United International University Dhaka Bangladesh

Evaluation of marketing stimuli such as static advertisements, video advertisements, promotions, etc. is an important part of marketing research. Traditionally, the evaluation is done through large surveys, focus group discussions, questioner-based surveys, etc. However, these methods are time-consuming and expensive. Here, neuromarketing offers a solution that can improve marketing research. Recently, several EEG-based neuromarketing studies proved the potential of neuromarketing as a marketing research tool. However, most of these researchers used research-grade EEG devices. Research-grade EEG devices are bulky and require high setup time. This is why, despite much successful research, the technology is yet to be implemented on a day-to-day basis. On the other hand, consumer-grade BCI devices are cheap, wearable, and offer little to no setup time. So, it is ideal for day-to-day implementation. However, consumer-grade BCI lacks in terms of signal quality and available channel number, and it has not been widely tested in neuromarketing. So, in this study, we compared a research-grade EEG device and a consumer-grade BCI device for consumers’ preference prediction using a machine learning framework. We designed an experiment to record participants' EEG data while they were shown marketing stimuli. Their response has been taken as affective attitude (AA) purchase intention (PI). After that, binary classification was performed. We achieved 80.71% and 82.07% accuracy for predicting purchase intention and affective attitude using the research-grade EEG device, whereas it was 78.31% and 81.23% using the consumer-grade BCI device. These findings prove that consumer-grade BCI can be a viable option for day-to-day usage in neuromarketing. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

WIP: Integrating Green Computing Competencies Into Southern African Curricula

WIP: Integrating Green Computing Competencies Into Southern ...

引用

Frontiers in Education (FIE) Conference

作者： Vuyelwa David Ruwodo George Mufungulwa Sibonile Moyo Lannie Uwu-Khaeb Nikodemus Angula Erkki Sutinen Department of Computing University of Turku Turku Finland Department of Computer Science The Copperbelt University Kitwe Zambia Department of Information and Analytics National University of Science and Technology Buluwayo Zimbabwe Department of Commerce Human Science and Education Namibia University of Science and Technology Windhoek Namibia

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This is work-in-progress research-to-practice. computer-based solutions are viewed as key to many technological problems, especially in reducing the impact of technology on the environment. At the same time, these computing solutions have their negative impacts. Such negative impacts are not understood by many computing specialists, as computing graduates have not been made aware of these undesirable impacts of their solutions. Based on frameworks such as CC2020, most computing curricula in Southern Africa, do not incorporate sustainability concepts. This means computing graduates of these African institutions will continue to view the quality of their computing solutions as defined by curricula that lack emphasis on sustainability. However, Africa's contribution to engineering education with a green twist can address this predicament. By integrating sustainability principles into computing and engineering curricula, African higher education institutions (HEI) can pioneer a new generation of professionals equipped with knowledge and skills to develop sustainable green technological solutions. Such an approach will not only address local challenges but will also position Africa as a major contributor to green computing and sustainable engineering practices, which are increasingly crucial in the global effort to mitigate environmental degradation. Using Design science Research (DSR), incorporating Action Research, this paper discusses the process of formulating a green-friendly computing curriculum for use by five African universities, participating in a European Union-funded project, Grow Green Africa (Gr2A). This hybrid approach to curriculum development ensures the viability of the resulting curriculum and its adaptability and sustainability over time. The designed curriculum incorporates sustainability principles aimed at fostering sustainable practices in the computing sector. The competency-based learning model encompasses knowledge, skills, and dispositions req

关键词： Climate change Adaptation models Technological innovation Computational modeling Green products Curriculum development Africa Green computing Air pollution Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Universal Multimodal Representation for Language Understanding

arXiv

引用

arXiv 2023年

作者： Zhang, Zhuosheng Chen, Kehai Wang, Rui Utiyama, Masao Sumita, Eiichiro Li, Zuchao Zhao, Hai The Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China The School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Japan

Representation learning is the foundation of natural language processing (NLP). This work presents new methods to employ visual information as assistant signals to general NLP tasks. For each sentence, we first retrieve a flexible number of images either from a light topic-image lookup table extracted over the existing sentence-image pairs or a shared cross-modal embedding space that is pre-trained on out-of-shelf text-image pairs. Then, the text and images are encoded by a Transformer encoder and convolutional neural network, respectively. The two sequences of representations are further fused by an attention layer for the interaction of the two modalities. In this study, the retrieval process is controllable and flexible. The universal visual representation overcomes the lack of large-scale bilingual sentence-image pairs. Our method can be easily applied to text-only tasks without manually annotated multimodal parallel corpora. We apply the proposed method to a wide range of natural language generation and understanding tasks, including neural machine translation, natural language inference, and semantic similarity. Experimental results show that our method is generally effective for different tasks and languages. Analysis indicates that the visual signals enrich textual representations of content words, provide finegrained grounding information about the relationship between concepts and events, and potentially conduce to disambiguation. Copyright © 2023, The Authors. All rights reserved.

关键词： Modeling languages

来源：评论

学校读者我要写书评

暂无评论

BreVamiR3’: A comprehensive database for breast cancer-associated genetic variations in miRNA and 3’ UTR of their target genes

引用

computers in Biology and Medicine 2025年 186卷 109639-109639页

作者： Chhichholiya, Yogita Kumar, Vicky Hlawndo, Lalnunmawia Sangave, Kshitij Singh, Sandeep Munshi, Anjana Department of Human Genetics and Molecular Medicine Central University of Punjab Punjab Bathinda India Department of Computer Science Engineering Guru Nanak Dev DSEU Rohini Campus Delhi Skill and Entrepreneurship University Delhi Dwarka India

Breast cancer (BC) is a multifactorial disease where microRNA (miRNA)-mediated dysregulated gene expression plays a pivotal role in tumorigenesis, progression, and clinical outcomes. Genetic variation, particularly SNPs in miRNA sequences and the 3′ untranslated regions (3′UTRs) of their target genes, can disrupt miRNA-mRNA interactions, leading to altered gene expression. Despite several existing databases providing insights into various aspects of miRNAs and their target genes in association with the development of the disease. Still, there remains a critical gap in a unified, BC-specific repository that integrates SNPs in miRNAs, their target genes, and associated molecular mechanisms. To address this, we developed BreVamiR3’ (Breast cancer-associated genetic Variations in miRNA and 3′UTR of their target genes), a novel, freely accessible database (https://***/***). BreVamiR3′ features comprehensive and curated data on 500 miRNAs and 828 target genes associated with BC, including experimentally validated SNPs, chromosomal loci, expression profiles, BC subtypes, signaling pathways, and classifications of genes i.e. oncogene, tumor suppressor, or both. Unique features of BreVamiR3′ include detailed annotations of SNPs disrupting miRNA-target interactions, subtype-specific miRNA expression, visualization of miRNA-chromosomal distributions and their experimental validation. Chromosome 19 harbours the highest number of BC-associated miRNAs, while target genes such as CCND1, KRAS, and ERBB2 demonstrate extensive miRNA regulation. By integrating genetic variations with functional and clinical relevance, BreVamiR3′ provides a single platform to explore miRNA-mediated regulatory networks, their genetic variation, and downstream signaling pathways in BC. This database serves as a powerful resource for researchers, enabling exploration of miRNA-gene interactions, genetic variation, and their role in pathogenesis of BC and diverse clinical outcomes. © 20

关键词： Gene expression regulation

来源：评论

学校读者我要写书评

暂无评论

New Ontology structure for intelligent controlling of traffic signals 26

New Ontology structure for intelligent controlling of traffi...

引用

26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Mohammad, Mahmud Abdulla Manguri, Kamaran H. Abdulsamad, Taib Shamsadin Faeq Al-Talabani, Abdulbasit K. Abdulrahman, Akam Aziz Computer Science Department College of Basic Education University of Raparin Kurdistan Region Ranya Iraq College of Science and Technology University of Human Development Kurdistan Region Sulaymaniyah Iraq Department of Software Engineering Koya University Kurdistan Region Koya Iraq

This article proposes a novel ontology design for intelligent controlling of traffic signals, considering the investigated factors, crowded factors, road factors, visibility conditions, and emergency situations. Essentially, the proposed method uses video-based knowledge and key feature from a monocular video camera only, capturing footage from either a traffic signals perspective or the top of the road lane. The key factors and entities in the traffic scene are formed into an ontology, which has been evaluated using synthetic datasets to interpret challenging cases. Semantic features related to the key factors in the scene are obtained and fed to the ontology. The experimental results indicate that the proposed method is capable of controlling traffic signals more efficiently than the fixed intervals protocol. © 2022 The Authors. Published by Elsevier B.V.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Multimodal Brain Tumor Segmentation Using a Dual-Branch Vision Transformer Integrated with Region-Attention Fusion Network

Multimodal Brain Tumor Segmentation Using a Dual-Branch Visi...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Sunita Yadwad Rajeswari C D. Nirmal Raj Pravin Dange Department of Computer Science and Engineering Faculty of Engineering and Technology Parul University Gujarat India Department of Computer Science and Engineering Chennai Institute of Technology Kundrathur India Balaji Institute of Management and Human Resource Development (BIMHRD) Pune India Symbiosis Institute of Management Studies Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Accurate segmentation of brain tumors is a critical task in medical imaging, aiding diagnosis, treatment planning, and prognosis. This paper introduces a novel framework for brain tumor segmentation that leverages a Dual-Branch Vision Transformer (DB-ViT) integrated with a Region-Attention Fusion Network (RAFN) to address the limitations of conventional convolutional neural networks. The DB-ViT processes multimodal MRI sequences, including T1, T1c, T2, and FLAIR, to extract global contextual features while preserving modality-specific information. Simultaneously, the RAFN enhances segmentation precision by refining local features and focusing on critical regions of interest through an attention mechanism. The proposed method effectively combines global and local feature representations, ensuring accurate delineation of tumor boundaries. Extensive experiments were conducted on the BraTS dataset, demonstrating the superiority of our approach over existing methods such as U-Net, Attention U-Net, and TransUNet. Quantitative evaluation metrics, including Dice Score and Intersection over Union (IoU), indicate significant improvements in segmentation accuracy. The framework also achieves computational efficiency and robustness across diverse tumor morphologies. Visual results further validate its ability to enhance boundary delineation, particularly in heterogeneous tumor regions. The proposed methodology represents a significant advancement in automated medical image analysis, offering potential for real-time clinical applications. Future work aims to explore broader clinical validation and real-time deployment of this framework.

关键词： Measurement Image segmentation computer vision Accuracy Attention mechanisms Refining Brain tumors Transformers Real-time systems Planning

来源：评论

学校读者我要写书评

暂无评论

PI-VIMO: PHYSIOLOGY-INSPIRED ROBUST VITAL SIGN MONITORING USING MMWAVE RADARS

arXiv

引用

arXiv 2023年

作者： Zhang, Bo Jiang, Boyu Zheng, Rong Zhang, Xiaoping Li, Jun Xu, Qiang Dept. of Computing and Software McMaster University HamiltonON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University TorontoON Canada Huawei Human Machine Interaction Lab MarkhamON Canada

Continuous monitoring of human vital signs using non-contact mmWave radars is attractive due to their ability to penetrate garments and operate under different lighting conditions. Unfortunately, most prior research requires subjects to stay at a fixed distance from radar sensors and to remain still during monitoring. These restrictions limit the applications of radar vital sign monitoring in real life scenarios. In this paper, we address these limitations and present Pi-ViMo, a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars. We first derive a multi-scattering point model for the human body, and introduce a coherent combining of multiple scatterings to enhance the quality of estimated chest-wall movements. It enables vital sign estimations of subjects at any location in a radar’s field of view (FoV). We then propose a template matching method to extract human vital signs by adopting physical models of respiration and cardiac activities. The proposed method is capable to separate respiration and heartbeat in the presence of micro-level random body movements (RBM) when a subject is at any location within the field of view of a radar. Experiments in a radar testbed show average respiration rate errors of 6% and heart rate errors of 11.9% for the stationary subjects, and average errors of 13.5% for respiration rate and 13.6% for heart rate for subjects under different RBMs. © 2023, CC BY.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Proposing an interactive audit pipeline for visual privacy research

arXiv

引用

arXiv 2021年

作者： DeHart, Jasmine Xu, Chenguang Egede, Lisa Grant, Christan School of Computer Science University of Oklahoma United States Human Computer Interaction Institute Carnegie Mellon University

In an ideal world, deployed machine learning models will enhance our society. We hope that those models will provide unbiased and ethical decisions that will benefit everyone. However, this is not always the case;issues arise from the data curating process to the models’ deployment. The continued use of biased datasets and processes will adversely damage communities and increase the cost to fix the problem. In this work, we walk through the decision process that a researcher will need to make before, during, and after their project to consider the broader impacts of research and the community. Throughout this paper, we observe the critical decisions that are often overlooked when deploying AI, argue for the use of fairness forensics to discover bias and fairness issues in systems, assert the need for a responsible human-over-the-loop to bring accountability into the deployed system, and finally, reflect on the need to explore research agendas that have harmful societal impacts. We examine visual privacy research and draw lessons that can apply broadly to Artificial Intelligence. Our goal is to provide a systematic analysis of the machine learning pipeline for visual privacy and bias issues. With this pipeline, we hope to raise stakeholder (e.g., researchers, modelers, corporations) awareness as these issues propagate in the various machine learning phases. © 2021, CC BY.

关键词： Pipelines

来源：评论

学校读者我要写书评

暂无评论

GLaPE: Gold Label-agnostic Prompt Evaluation for Large Language Models

GLaPE: Gold Label-agnostic Prompt Evaluation for Large Langu...

引用

2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zhang, Xuanchang Zhang, Zhuosheng Zhao, Hai College of Zhiyuan Shanghai Jiao Tong University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

ISBN: (纸本)9798891761643

Despite the rapid progress of large language models (LLMs), their task performance remains sensitive to prompt design. Recent studies have explored leveraging the LLM itself as an optimizer to identify optimal prompts that maximize task accuracy. However, when evaluating prompts, such approaches heavily rely on elusive manually annotated gold labels to calculate task accuracy for each candidate prompt, which hinders its generality. To overcome the limitation, this work proposes GLaPE, a gold label-agnostic prompt evaluation method to alleviate dependence on gold labels. GLaPE is composed of two critical aspects: self-consistency evaluation of a single prompt and mutual-consistency refinement across multiple prompts. Experimental results on 8 widely-recognized reasoning tasks demonstrate that GLaPE can produce more effective prompts, achieving performance comparable to those derived from manually annotated gold labels. Analysis shows that GLaPE provides reliable evaluations aligned with accuracy, even in the absence of gold labels. Code is publicly available at https://***/thunderous77/GLaPE. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

The Role of Expertise in Effectively Moderating Harmful Social Media Content 25

The Role of Expertise in Effectively Moderating Harmful Soci...

引用

2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Abdelkadir, Nuredin Ali Yang, Tianling Kapania, Shivani Estefanos, Meron Gebrekidan, Fasica Berhane Zelalem, Zecharias Ali, Messai Berhe, Rishan Baker, Dylan Talat, Zeerak Miceli, Milagros Hanna, Alex Gebru, Timnit Computer Science and Engineering University of Minnesota Minneapolis MN United States The Distributed AI Research Institute Minneapolis MN United States Weizenbaum Institute Technische Universität Berlin Berlin Germany Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States The Distributed AI Research Institute Stockholm Sweden Independent Researcher Nairobi Kenya Freelance Journalist Montreal QC Canada Independent Researcher Stockholm Sweden Independent Researcher New York NY United States University of Edinburgh Edinburgh United Kingdom

Social media platforms played a significant role in spreading genocidal content in the 2020-2022 Tigray war, where the deadliest genocide of the 21st century was committed. While linguistic expertise is clearly needed... 详细信息

ISBN: (纸本)9798400713941

Social media platforms played a significant role in spreading genocidal content in the 2020-2022 Tigray war, where the deadliest genocide of the 21^st century was committed. While linguistic expertise is clearly needed to adequately moderate such content, we ask: What additional expertise is needed? Why and to what extent do experts disagree on what constitutes harmful content, and what is the best way to resolve these disagreements? What do social media platforms do instead? We examine these questions through a 4-month study with 7 experts labeling 340 X (formerly Twitter) posts, and by interviewing 15 commercial content moderators. We find in-depth cultural knowledge and dialects to be most important for accurate hate speech annotation - knowledge which social media platforms do not prioritize. Even amongst experts, disagreements are high (71%), dropping to 40% after deliberation meetings. Based on these results, we present 7 recommendations to improve hate speech annotation and moderation practices. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Content Moderation Data Annotation Expert Disagreement Expertise Harmful Content Social Media Platforms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：