检索结果-内蒙古大学图书馆

26th International Conference on Human-Computer Interaction, HCII 2024

作者： Ratul, Mohammad Arshad Hossain Yanoor Bristy, Tunisha Sayeed, Noorjahan Islam, Ashraful Chaudhry, Beenish Moalla Center for Computational and Data Sciences Independent University Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh School of Computing and Informatics University of Louisiana at Lafayette Louisiana United States

ISBN: (纸本)9783031768088

This study employs the User-Centered Design (UCD) methodology to develop a mobile health (mHealth) application (app) specifically tailored for Bangladeshi women with Gestational Diabetes Mellitus (GDM). GDM affects approximately 10% of pregnant women globally and around 35% within Bangladesh, as reported by the World Health Organization (WHO). Despite its high prevalence, there is a significant lack of awareness and education about GDM in Bangladesh, compounded by language barriers that make existing digital solutions less accessible. The MatrikalinDiabetes mHealth app aims to overcome these barriers by providing comprehensive management and educational resources for GDM in the Bangla language, addressing both pre-pregnancy and post-pregnancy needs. To ensure the app meets the actual needs of potential users, personas were created based on a literature review, and a survey was conducted. This process informed the development of both a low-fidelity, paper-based prototype and a high-fidelity digital prototype. Key features of the MatrikalinDiabetes app include tracking of food and water intake, physical activity monitoring, reminders, GDM education, chat forums for community support, blood glucose level (BGL) monitoring, an SOS button for emergency contacts, and quizzes for user engagement. Preliminary feedback indicated that 53.8% of participants favored the integrated features and expressed willingness to use and recommend the app. The survey of the high-fidelity prototype yielded positive responses, with 57.9% of participants strongly agreeing and 42.1% agreeing that the features were beneficial. The user-friendly design of the high-fidelity prototype ensures intuitive interaction, aiding in health management, enhancing GDM understanding, and promoting a healthier lifestyle among pregnant women in Bangladesh. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Obstetrics

来源：评论

学校读者我要写书评

暂无评论

A Dual-Port MIMO Antenna Decoupling by Common and Differential Mode Cancellation with High Isolation

引用

IEEE Antennas and Wireless Propagation Letters 2025年

作者： Gao, Guo-Ping Bai, Jin-Ming Jin, Li-Jun Guo, Wen-Di Ma, Ge Hu, Bin Lanzhou University Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou730000 China

In this letter, a dual-port Multiple-input multiple-output (MIMO) antenna decoupling by common mode (CM) and differential mode (DM) cancellation with high isolation is proposed. The basic structure of the antenna features a large rectangular slot in the center of the circular patch, along with shorting pins and other decoupling structures to achieve high isolation. The shorting pins arranged on the perfect magnetic conductor (PMC) and the metallic strips passing through the perfect electrical conductor (PEC) can adjust the impedance matching for CM and DM feeding, fulfilling the basic principles for decoupling by CM and DM cancellation. The measured impedance bandwidth reaches 85 MHz (from 3.49 GHz to 3.575 GHz), while the isolation exceeds 25 dB. Analysis of the radiation patterns shows that pattern diversity is achieved between the dual ports of the antenna. The proposed antenna achieved polarized direction matching while maintaining a lower profile and smaller size, these characteristics makes it more suitable for wearable applications. © 2002-2011 IEEE.

关键词： Slot antennas

来源：评论

学校读者我要写书评

暂无评论

Semantic-Aware Dual Contrastive Learning for Multi-Label Image Classification 26

Semantic-Aware Dual Contrastive Learning for Multi-Label Ima...

引用

26th European Conference on Artificial Intelligence, ECAI 2023

作者： Ma, Leilei Sun, Dengdi Wang, Lei Zhao, Haifeng Luo, Bin School of Computer Science and Technology Anhui University China School of Artificial Intelligence Anhui University China School of Computer Science and Engineering Nanjing University of Science and Technology China Anhui Provincial Key Laboratory of Multimodal Cognitive Computing Anhui University China Institute of Artificial Intelligence Hefei Comprehensive National Science Center China

ISBN: (纸本)9781643684369

Extracting image semantics effectively and assigning corresponding labels to multiple objects or attributes for natural images is challenging due to the complex scene contents and confusing label dependencies. Recent works have focused on modeling label relationships with graph and understanding object regions using class activation maps (CAM). However, these methods ignore the complex intra- and inter-category relationships among specific semantic features, and CAM is prone to generate noisy information. To this end, we propose a novel semantic-aware dual contrastive learning framework that incorporates sample-to-sample contrastive learning (SSCL) as well as prototype-to-sample contrastive learning (PSCL). Specifically, we leverage semantic-aware representation learning to extract category-related local discriminative features and construct category prototypes. Then based on SSCL, label-level visual representations of the same category are aggregated together, and features belonging to distinct categories are separated. Meanwhile, we construct a novel PSCL module to narrow the distance between positive samples and category prototypes and push negative samples away from the corresponding category prototypes. Finally, the discriminative label-level features related to the image content are accurately captured by the joint training of the above three parts. Experiments on five challenging large-scale public datasets demonstrate that our proposed method is effective and outperforms the state-of-the-art methods. Code and supplementary materials are released on https://***/yu-gi-oh-leilei/SADCL. © 2023 The Authors.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Body Fat Prediction using Various Regression Techniques 2

Body Fat Prediction using Various Regression Techniques

引用

2nd IEEE International Conference on Advances in computing, Communication and Applied Informatics, ACCAI 2023

作者： Mahesh, Nikhil Pati, Peeta Basa Deepa, K. Yanan, Suresh Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering Bengaluru India University of Technology and Applied Sciences-Al Musannah Sultanate of Oman Department of Engineering Oman

ISBN: (纸本)9798350315905

Predicting body fat percentage is essential for addressing the obesity problem. This paper compares the performance of several machine learning models based on Regression, to predict the body fat percentage. Using a dataset of 252 participants with information on age, weight, height, and fat percentage, the models were assessed based on multiple performance criteria, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Squared Error(MSE). The results demonstrates that Random Forest Regressor surpass other models with a lower RMSE of 0.276. These findings suggest that machine learning models can be a valuable tool for precise BFP, the use of machine learning provides a faster and more precise method for predicting body fat percentage. Overall, the study's results suggest that machine learning models can be valuable tool for accurate body fat percentage prediction. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Chloroplast-mimicking nanoreactor for enhanced CO_(2) electrocatalysis

引用

science Bulletin 2024年第18期69卷 2820-2824页

作者： Weiguang Maa Wenjun Fan Qinye Li Hefeng Zhang Kaixin Zhu Chenghua Sun Lianzhou Wang Xu Zong Clean Energy Center for Ship Marine Engineering CollegeDalian Maritime UniversityDalian 116026China State Key Laboratory of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian National Laboratory for Clean EnergyThe Collaborative Innovation Center of Chemistry for Energy Materials(iChEM)Dalian 116023China School of Science ComputingEngineering&TechnologySwinburne University of TechnologyHawthorn Vic 3122Australia Department Nanomaterials Centre School of Chemical Engineering and Australian Institute for Bioengineering and NanotechnologyThe University of QueenslandSt LuciaQLD 4072Australia

Producing fuels or chemicals via electrochemical carbon dioxide reduction reaction(CO_(2)RR)with renewable electricity has attracted great research interest due to its potential of alleviating the environmental and energy issues in a carbon–neutral manner[1].The CO_(2)RR is a proton-coupled electron transfer process with the simultaneous participation of multiple protons and electrons[2].

关键词： dioxide neutral carbon

来源：评论

学校读者我要写书评

暂无评论

Comparative Study on Impact of Output Modes on User Experience in Object Detection and Distance Estimation Systems

Comparative Study on Impact of Output Modes on User Experien...

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Garima Jain Prasidhi Nandwani Rupayali Swaroop Harshlata Vishakarma Sanat Jain School of Computing Science Engineering and Artificial Intelligence VIT Bhopal University Sehore India School of Computer Science and Engineering JECRC University Jaipur India School of Computer Science and Engineering VIT Bhopal University Sehore India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

This study proposes a thorough investigation of countless object detection models, focusing uniquely on various YOLO versions. The paper begins with a thorough evaluation of object detection models including YOLO, ResNet, SSD, etc. by comparing their performance concerning their accuracy and effectiveness and their relative strengths and weaknesses in real-time object detection. Fabricating on the comparative analysis. This study proposes an innovative approach for object detection that integrates distance estimation and voice commands. The suggested research is aimed at enhancing real-time interaction with the surroundings, enabling users to receive immediate feedback about their surroundings. For identification and categorization, the model depends on live video input. Then estimates the distance of the object from the user, and finally gives an audio output. This study can be applied in various fields like robotics, autonomous vehicles, assistive technologies, and smart environments where object detection is crucial.

关键词： YOLO Technological innovation Estimation Assistive technologies Streaming media User experience Real-time systems Convolutional neural networks Object recognition Robots

来源：评论

学校读者我要写书评

暂无评论

Emotional changes induced by associative memory

引用

The European Physical Journal Special Topics 2025年 1-11页

作者： Ren, Xiyu Xu, Xianying Al-Barakati, Abdullah A. Cao, Yinghong School of Information Science and Engineering Dalian Polytechnic University Dalian China School of Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

Associative memory and Hopfield neural networks are an important area where artificial intelligence and neuroscience are intertwined, and the core idea is to study the mechanisms of information storage and retrieval in the human brain. In this paper, two memristors are introduced into a three-dimensional Hopfield neural network as electronic synapses to simulate the associative memory function of the hippocampus in the human brain. To begin with, the rationality of the two memristors' designs is verified. Next, the effect on emotion produced when the synaptic weights are changed is investigated using numerical analysis. The firing pattern of Hopfield neural networks was also investigated. The changes made by different emotional states in response to the same associative memory stimulus are also analyzed. Finally, the DSP platform verifies the feasibility of the MATLAB simulation results. This paper provides a theoretical basis for the emotional design of intelligent robots.

关键词：

来源：评论

学校读者我要写书评

暂无评论

NEHATE: Large-Scale Annotated Data Shedding Light on Hate Speech in Nepali Local Election Discourse 26

NEHATE: Large-Scale Annotated Data Shedding Light on Hate Sp...

引用

26th European Conference on Artificial Intelligence, ECAI 2023

作者： Thapa, Surendrabikram Rauniyar, Kritesh Shiwakoti, Shuvam Poudel, Sweta Naseem, Usman Nasim, Mehwish Department of Computer Science Virginia Tech United States Department of Computer Science Delhi Technological University India Kathmandu Engineering College Tribhuvan University Nepal College of Science and Engineering James Cook University Australia School of Physics Mathematics and Computing The University of Western Australia Australia College of Science and Engineering Flinders University Australia

ISBN: (纸本)9781643684369

The use of social media during election campaigns has become increasingly popular. However, the unbridled nature of online discourse can lead to the propagation of hate speech, which has far-reaching implications for the democratic process. Natural Language Processing (NLP) techniques are being used to counteract the spread of hate speech and promote healthy online discourse. Despite the increasing need for NLP techniques to combat hate speech, research on low-resource languages such as Nepali is limited, posing a challenge to the realization of the United Nations' Leave No One Behind principle, which calls for inclusive development that benefits all individuals and communities, regardless of their backgrounds or circumstances. To bridge this gap, we introduce NEHATE, a large-scale manually annotated dataset of hate speech and its targets in Nepali local election discourse. The dataset comprises 13,505 tweets, annotated for hate speech with further sub-categorization of hate speech into targets such as community, individual, and organization. Benchmarking of the dataset with various algorithms has shown potential for performance improvement. We have made the dataset publicly available at https://***/shucoll/NEHate to promote further research and development, while also contributing to the UN SDGs aimed at fostering peaceful, inclusive societies, and justice and strong institutions. © 2023 The Authors.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Exploring the Effectiveness of Various Deep Learning Techniques for Text Generation in Natural Language Processing

Exploring the Effectiveness of Various Deep Learning Techniq...

引用

2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023

作者： Singh, Baljap Kumar, Anubhav Kaur, Satjap Shekhar, Shashank Singh, Gurwinder Chandigarh University Apex Institute of Technology Department of Computer Science Mohali India Galgotias University School of Computing Science and Engineering Department of Cse Greater Noida India Sheridan College Missisauga Canada

ISBN: (纸本)9798350344387

Natural Language Processing (NLP) demands the generation of text that exhibits cohesion, fluidity, and semantic coherence. Text generation plays a pivotal role in achieving this objective. Over time, the evolution of Deep Learning (DL) techniques has led to the emergence of several methods for generating text, including Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and Transformers. This study undertakes a comprehensive examination of DL methods for text generation within the realm of *** providing a general overview of text generation and its inherent challenges, an extensive exploration of the various deep learning models and their adaptations is conducted. The strengths and limitations of these models are meticulously assessed, while their performance relative to more traditional approaches is also examined. To conclude, current trends are illuminated, and unanswered questions within this domain are posed. Beyond simply identifying areas ripe for further investigation, this review aims to equip both scholars and practitioners with a comprehensive understanding of the latest developments in DL-based text generation. © 2023 IEEE.

关键词： Algorithm Deep Learning NLP Optimizers Text Generation

来源：评论

学校读者我要写书评

暂无评论

Gyroscope Aided Blur Kernel Estimation for IR Image Deblurring

Gyroscope Aided Blur Kernel Estimation for IR Image Deblurri...

引用

2023 International Conference on Computer, Electronics and Electrical engineering and their Applications, IC2E3 2023

作者： Singh, Kaustubh Saurabh Diwakar, Manoj Singh, Prabhishek Arya, Chandrakala Deemed to Be University Cse Graphic Era Dehradun India Bennett University School of Computer Science Engineering and Technology Greater Noida India Graphic Era Hill University School of Computing Dehradun India

ISBN: (纸本)9798350338003

Stabilized Electro-Optical Systems are used in multiple domains, like target detection, tracking, and area surveillance. Cooled thermal imagers are used for long range surveillance. The requirement of a fast steering speed of the gimbal during surveillance induces blur in the captured IR video frames, which is required to be correct in real-time. Existing blind deblurring methods take a long time to execute. Deep learning methods are fast but cannot be generalised for all practical scenarios. In this work, we propose a noble blur kernel estimation method, using inertial sensor, and integrate it with existing non-blind deblurring methods and a sensor based deep learning method. Our method shows good results and is a suitable candidate for deblurring the image captured by gimbal-based imaging systems. © 2023 IEEE.

关键词： Image enhancement

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：