A Pre-Activation Residual Convolutional Network With Attention Modules for High-Resolution Segmented EEG Emotion Recognition by Ioannis Charalampous, Christos Mavrokefalidis, Kostas Berberidis

“…Emotion recognition based on electroencephalography (EEG) signals has attracted considerable research interest over the past few years and several potential applications have been proposed such as enhancing human-computer interaction, improving mental health diagnosis, and fine-tuning the customer experience at the marketing level. …”
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Automated image-based identification and consistent classification of fire patterns with quantitative shape analysis and spatial location identification by Pengkun Liu, Shuna Ni, Stoliarov Stanislav I, Pingbo Tang

“…First, it leverages human-computer interaction to extract fire patterns from surfaces, combining investigator expertise with computational analysis. …”
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Research on multi-user identity recognition based on Wi-Fi sensing by Zhongcheng WEI, Wei CHEN, Yanhu DONG, Bin LIAN, Wei WANG, Jijun ZHAO

“…With the advancement of wireless sensing technology, research on Wi-Fi-based identity recognition has garnered significant attention in fields such as human-computer interaction and home security.While identity recognition based on Wi-Fi signals has achieved initial success, it is currently primarily suitable for scenarios involving individual user behavior.Identity recognition for multiple users in concurrent behavior scenarios still faces a series of challenges, including issues related to mutual interference between users and poor model robustness.Therefore, a Wiblack system for recognizing multiple user identities in a concurrent distribution behavior scenario was proposed.The core idea was to train a multi-branch deep neural network (Wiblack-Net) to extract unique features for each individual user.Firstly, the common features among multiple users were extracted using the backbone network.Then, a binary classifier was assigned to each user to determine the presence of the target user within a given group, thereby achieving identity recognition for multiple users based on concurrent behavior.In addition, experiments comparing Wiblack with several independent binary classification models and a single multiclassification model were conducted to analyze operational efficiency.System performance experimental results demonstrate that when simultaneously identifying the identities of three users, Wibalck achieves an average accuracy of 92.97%, an average precision of 93.71%, an average recall of 93.24%, and an average F1 score of 92.43%.…”
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A conceptual framework for designing human-centered building-occupant interactions to enhance user experience in specific-purpose buildings by N. Roofigari-Esfahan, E. Morshedzadeh

“…This research proposes a novel conceptual framework that combines the concepts of Human-Computer Interaction (HCI) and Ambient Intelligence (AmI). …”
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Extending NGOMSL Model for Human-Humanoid Robot Interaction in the Soccer Robotics Domain by Rajesh Elara Mohan, Carlos Antonio Acosta Calderon, Changjiu Zhou, Pik Kong Yue

“…In the field of human-computer interaction, the Natural Goals, Operators, Methods, and Selection rules Language (NGOMSL) model is one of the most popular methods for modelling knowledge and cognitive processes for rapid usability evaluation. …”
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Cross-modality fusion with EEG and text for enhanced emotion detection in English writing by Jing Wang, Ci Zhang

“…IntroductionEmotion detection in written text is critical for applications in human-computer interaction, affective computing, and personalized content recommendation. …”
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Arabic Sign Language Recognition System for Alphabets Using Machine Learning Techniques by Gamal Tharwat, Abdelmoty M. Ahmed, Belgacem Bouallegue

“…In recent years, the role of pattern recognition in systems based on human computer interaction (HCI) has spread in terms of computer vision applications and machine learning, and one of the most important of these applications is to recognize the hand gestures used in dealing with deaf people, in particular to recognize the dashed letters in surahs of the Quran. …”
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A review on speech recognition approaches and challenges for Portuguese: exploring the feasibility of fine-tuning large-scale end-to-end models by Yan Li, Yapeng Wang, Lap Man Hoi, Dingcheng Yang, Sio-Kei Im

“…Abstract At present, automatic speech recognition has become an important bridge for human-computer interaction and is widely applied in multiple fields. …”
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Current status and application of visual-tactile sensing technology by Bin WEI, Zihao WANG, Ping WANG, Jie LI, Guang LIU

“…Finally, the following prospects were proposed for visual touch fusion technology: 1) development of multimodal perception technology; 2) innovation in human-computer interaction methods; 3) improvement of control accuracy for intelligent robots; 4) drive the consumption of electronic products.…”
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An Updated Systematic Mapping Study on Usability and User Experience Evaluation of Touchable Holographic Solutions by Thiago Campos, Maria Castello, Eduardo Damasceno, Natasha Valentim

“…This work contributes to the Human-Computer Interaction (HCI) area by mapping current evaluation technologies, identifying research gaps, and providing a foundation for developing innovative and effective evaluation methods for THS, thus advancing the understanding and improvement of user interaction in immersive environments. …”
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Multiperson Interactive Activity Recognition Based on Interaction Relation Model by Hongbin Tu, Renyu Xu, Rui Chi, Yuanyuan Peng

“…On this ground, it automatically learns from the human-computer interaction dataset in an end-to-end manner and performs reasoning with standard matrix operations. …”
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Tuning into urban birdsong: enhancing nature connectedness with an AI-powered wearable by Zhuying Li, Si Cheng, Xiaoqing Sun, Xipei Ren, Yan Wang, Min-Ling Zhang

“…There is a a growing interest in leveraging technology to address this gap in Human-Computer Interaction. This article introduces GoChirp, an AI-powered wearable device for enhancing nature relatedness within urban landscapes. …”
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Residual Vision Transformer and Adaptive Fusion Autoencoders for Monocular Depth Estimation by Wei-Jong Yang, Chih-Chen Wu, Jar-Ferr Yang

“…Precision depth estimation plays a key role in many applications, including 3D scene reconstruction, virtual reality, autonomous driving and human–computer interaction. Through recent advancements in deep learning technologies, monocular depth estimation, with its simplicity, has surpassed the traditional stereo camera systems, bringing new possibilities in 3D sensing. …”
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STA-HAR: A Spatiotemporal Attention-Based Framework for Human Activity Recognition by Md. Khaliluzzaman, Md. Furquan, Mohammod Sazid Zaman Khan, Md. Jiabul Hoque

“…Human activity recognition (HAR) has gained significant attention in computer vision and human-computer interaction. This paper investigates the difficulties encountered in human activity recognition (HAR), precisely differentiating between various activities by extracting spatial and temporal features from sequential data. …”
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Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition by Heon-Sung Park, Min-Kyung Sung, Dae-Won Kim, Jaesung Lee

“…Sensor-based gesture recognition on mobile devices is critical to human–computer interaction, enabling intuitive user input for various applications. …”
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Researchers and practitioners talk about users and each other: making user and audience studies matter by Brenda Dervin, CarrieLynn Reinhard

“…</b> We report here on the research phase of a multi-stage dialogue examining convergences and divergences in how three fields (library and information science, human computer interaction and communication and media studies) looked at users and each other. …”
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Research on Gait Recognition Based on GaitSet and Multimodal Fusion by Xiling Shi, Wenqiang Zhao, Huandou Pei, Hongru Zhai, Yongxia Gao

“…., assisted identity verification), and human-computer interaction. However, individual differences, such as changes in physical condition, and environmental variability, such as differences in lighting, can impact its accuracy. …”
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Dual-Mode Textile Sensor Based on PEDOT:PSS/SWCNTs Composites for Pressure–Temperature Detection by Ying Wang, Qingchao Zhang, Zhidong Zhang

“…As an innovative branch of electronics, intelligent electronic textiles (e-textiles) have broad prospects in applications such as e-skin, human–computer interaction, and smart homes. However, it is still a challenge to distinguish multiple stimuli in the same e-textile. …”
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ETHICS BY DESIGN AND RECONSIDERATION OF THE SUBJECT-OBJECT IN THE DIGITAL ERA by Тетяна ПАВЛОВА, Роман ПАВЛОВ

“…Design / Method / Approach: The research is based on an interdisciplinary approach combining methods of philosophical analysis, ethics, sociology of technology and research in the field of human-computer interaction. The methods of conceptual modeling, ethical analysis of technologies and scenario forecasting are used. …”
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Integrating Multi-Model Simulations to Address Partial Observability in Population Dynamics: A Python-Based Ecological Tool by Yide Yu, Huijie Li, Yue Liu, Yan Ma

“…Our contributions include the following: (I) integrating multiple ecological models for a comprehensive understanding of ecological processes, (II) developing a no-code mode of human–computer interaction for biodiversity stakeholders and researchers, and (III) implementing a Python-based framework for easy extension and customization. …”
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