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2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Sato, Toshiki Toyoura, Fuwa Terasawa, Shinichiro School of Knowledge Science Japan Advanced Institute of Science and Technology Ishikawa Japan School of Informatics and Engineering The University of Electro-Communications Chofu Tokyo Japan Japan Advanced Institute of Science and Technology Ishikawa Japan

ISBN: (纸本)9798400713958

We propose a novel projection screen material that utilizes the freezing phenomenon of soap film. Soap film is naturally transparent, but when frozen at low temperatures, it becomes more opaque and can serve as a projection screen. In this research, we focus on the frozen soap film and the freezing process and propose the possibility of using it as a new screen material. We also describe a method for implementing an omni-directional ProCam system that reproduces the freezing phenomenon at room temperature and enables interactive projection onto the frozen soap film. We present a prototype-based application and discuss its technological potential and future research directions. © 2025 Copyright held by the owner/author(s).

关键词： Projection screens

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Enhanced Indoor Mapping via Integration of Lidar and HoloLens 2 Data Using Iterative Closest Point Algorithm

Enhanced Indoor Mapping via Integration of Lidar and HoloLen...

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International Symposium on Intelligent Systems and informatics (SISY)

作者： Panka Szalka Attila Hideg Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350385601

ISBN: (纸本)9798350385618

This study presents an innovative method to improve the accuracy of indoor mapping by deploying and integrating a sensor that transmits two-dimensional data with a three-dimensional mesh created by another device. The Iterative Closest Point algorithm was used to coordinate the different data sets and transform their different coordinate systems into a common indoor map. Prior to this, rigorous image cleaning and matching processes are conducted to ensure the quality of the data used. The effectiveness of this methodology has been validated through multiple tests using a Lidar scanner and a HoloLens 2 Augmented Reality device. This method not only offers potential for enhancing indoor navigation and safety protocols like emergency evacuation but also presents opportunities for advancing asset tracking and other applications.

关键词： Laser radar Accuracy Iterative closest point algorithm Tracking Heuristic algorithms Transforms Robot sensing systems Real-time systems Cleaning Augmented reality

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Learning Explainable Malware Characterization Using Knowledge Base Embedding 5

Learning Explainable Malware Characterization Using Knowledg...

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5th IEEE International Conference on Electro-Computing Technologies for Humanity, NIGERCON 2024

作者： Trizna, Daniel Anthony, Peter Homola, Martin Adams, Zekeri Balogh, Štefan Comenius University Department of Applied Informatics Bratislava Slovakia Slovak University of Technology Faculty of Electrical Engineering and Information Technology Bratislava Slovakia

ISBN: (纸本)9798331542559

Malware detection is critical in cybersecurity, yet traditional signature-based methods often fail against emerging threats. Recent advancements suggest machine learning models can enhance malware classification accuracy;however, these models frequently lack explainability, limiting the insights they provide to cybersecurity experts. In this work, we introduce a novel approach using knowledge base embedding to classify malware while also delivering interpretable explanations. By learning vector representations for entities and relationships within a knowledge base, our method preserves semantic meaning, effectively distinguishing between malicious and benign software. Leveraging the RotatE model, our approach achieves 80% classification accuracy and generates meaningful, human-understandable explanations of model decisions, offering insights into malware behavior and improving transparency in detection and characterization. © 2024 IEEE.

关键词： Explainable AI Explainable Malware Detection Knowledge Base Embedding Knowledge Graph Embedding

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SGFormer: Semantic-Geometry Fusion Transformer for Multi-modal 3D Panoptic Segmentation 39

SGFormer: Semantic-Geometry Fusion Transformer for Multi-mod...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Yu, Hongqi Chan, Sixian Zhou, Xiaolong Zhang, Xiaoqin Key Laboratory of Intelligent Informatics for Safety and Emergency of Zhejiang Province Wenzhou University China College of Computer Science and Technology Zhejiang University of Technology China College of Electrical and Information Engineering Quzhou University China

ISBN: (纸本)157735897X

Modern methods for autonomous driving perception widely adopt multi-modal fusion to enhance 3D scene understanding. However, existing methods suffer from inferior semantic extraction in image encoders that treat all pixels equally, ignoring contextual differences. The generated multi-modal representations also typically lack comprehensive semantic and spatial geometry information, which is crucial for the 3D panoptic segmentation task. In this paper, we propose a novel Semantic-Geometry Fusion Transformer (SGFormer) that extracts adaptive semantic contexts, aggregates geometric information and captures the semantic-geometry fusion. First, in the Image Branch, we tailor semantic contexts for each pixel with context-guided attention and spatial context alignment to refine semantic details. Second, we transform image and voxel features into point-pixel geometry representations, simultaneously learning semantic category priors as embeddings to better represent scene geometry and semantics. Finally, to aggregate semantic information with related geometry, we design a semantic-geometry fusion that combines the transformer, effectively capturing semantic-geometry relationships into multi-modal panoptic representations. Notably, SGFormer achieves the state-of-the-art (SOTA) results on the nuScenes and SemanticPOSS, as well as yielding competitive performance on the SemanticKITTI. Moreover, SGFormer exhibits superior robustness compared to leading methods, marking an improvement of 2% to 10%. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Geometry

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Deep Learning Approaches for Stress Detection: A Survey

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IEEE Transactions on Affective Computing 2025年第2期16卷 499-517页

作者： Kyrou, Maria Kompatsiaris, Ioannis Petrantonakis, Panagiotis C. Aristotle University of Thessaloniki Artificial Intelligence and Information Analysis Laboratory Deptartment of Informatics Thessaloniki54124 Greece Centre for Research and Technology - Hellas Information Technologies Institute Thessaloniki57001 Greece Aristotle University of Thessaloniki Deptartment of Electrical and Computer Engineering Thessaloniki54124 Greece

Stress has a severe impact on individuals irrespective of age, sex, work, or background. The reliable development of stress detection techniques enhances the social, educational, physical, economic, and professional quality of life, preventing chronic stress and proposing alleviation strategies. Research studies examine psychological, cognitive, behavioral, and physiological reactions to identify stress adequately. Deep Learning (DL) has received significant attention in recent years as it deals with high-dimensional, heterogeneous data and automatically learns representative features. This paper presents a survey on stress detection with recent DL approaches, leveraging data from all possible sources (physiological, speech, facial expressions, gestures, and social media content). The methodological outlines, the best results, and the main contributions of each study are discussed. We also describe publicly available datasets used by several of the presented works. Finally, we emphasize various open issues within the field of research and highlight key directions for future work. © 2010-2012 IEEE.

关键词： Social psychology

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Development of Slotted Array Antenna Using SIW Structure for WLAN Communications 2

Development of Slotted Array Antenna Using SIW Structure for...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Munir, Achmad Muhammad, Rivaldi Aulia Nurmantris, Dwi Andi Maulana, Muhammad Farhan Institut Teknologi Bandung Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Bandung Indonesia Uin Sunan Gunung Djati Bandung Faculty of Science and Technology Department of Electrical Engineering Bandung Indonesia Itb Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Bandung Indonesia Telkom University School of Applied Sciences Bandung Indonesia

ISBN: (纸本)9798350317558

The development of a slot array antenna based on Substrate Integrated waveguide (SIW) has been carried out. The antenna, consisting of 4 rectangular slots, is designed to operate at a frequency of 2.4 GHz. The design process includes SIW and slot array structure design, microstrip to SIW transition structure design, and microstripline structure design. The final design results were then fabricated on an FR4 Epoxy substrate with a substrate thickness of 1.6 mm for measurements. From the measurement results, it was found that the antenna resonates at a frequency of 2.385 GHz with a bandwidth of 1.67%. The measurement results, in general, also agree with the simulation results. The manufactured antenna is suitable for use in WLAN applications. © 2024 IEEE.

关键词： slotted array antenna substrate integrated waveguide (SIW) wavegudie Wireless Local Area Networks (WLAN) communications

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A Novel Approach to Remote Detection in Medical Radar Applications Using Flexible Transmit Array Lenses

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IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology 2024年第1期8卷 36-50页

作者： Asyari, Rifa Atul Izza Lee, Kuan-Yuan Arif, Rezki El Horng, Tzyy-Sheng Jason Teichmann, Daniel University of Southern Denmark Sdu Health Informatics and Technology The Maersk Mc-Kinney Moller Institute Odense5230 Denmark National Sun Yat-Sen University Department of Electrical Engineering Kaohsiung804 Taiwan Institut Teknologi Sepuluh Nopember Department of Biomedical Engineering Surabaya60111 Indonesia

This study introduces a novel method employing adaptable transmitarray lenses for medical radar systems, enhancing the direction of electromagnetic beams in the far-field. The newly developed antenna array exhibited marked improvements in gain, bandwidth, return loss, and isolation within specific frequency ranges during testing. Comprehensive evaluations, including various focal lengths and bending scenarios, underscored the superior performance of this adaptable lens over prior techniques. Its exceptional precision and sensitivity render it an ideal tool for real-time remote health monitoring systems, particularly in pulse detection. The research findings consistently aligned the heart rates detected by this innovative method with standard reference rates, reaffirming its reliability and accuracy. This consistency highlights the potential of the transmitarray lenses as a valuable advancement in medical radar systems. The study not only validates the effectiveness and reliability of the lenses but also lays a solid foundation for further research and development in this field. The insights garnered are expected to significantly bolster the progression of radar technologies in healthcare, leading to more accurate, efficient, and non-invasive health monitoring solutions, thereby enhancing patient care and outcomes. © 2016 IEEE.

关键词： Bandwidth

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Web-based Rice Pest and Diseases Detection Using Hybrid Fuzzy and K-Nearest Neighbor Methods

Web-based Rice Pest and Diseases Detection Using Hybrid Fuzz...

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6th International Conference on informatics and Computational Sciences, ICICoS 2022

作者： Anamisa, Devie Rosa Satoto, Budi Dwi Yusuf, Muhammad Sophan, Moch. Kautsar Alamsyah, Nurwahyu Muntasa, Arif University of Trunojoyo Madura Informatics Engineering Department Bangkalan Indonesia National Taiwan University of Science and Technology Informatics Engineering Department Taipei Taiwan

ISBN: (数字)9781665460996

ISBN: (纸本)9781665460996

Rice is a food crop that produces rice which is very useful for human life. And this is one of the main food commodities in Indonesia. Therefore, the Government must pay attention to the agricultural sector as a forum for providing food needs for the Indonesian population, which is increasing every year. East Java Province is one of the regions that produces the highest rice harvest in Indonesia. However, in recent years, rice production in East Java has not been able to meet the population's food demand properly. This is due to disease and pest attacks on rice plants and a lack of knowledge so that rice farmers experience crop failure. Therefore, rice production at the farm level can be increased through web-based technological innovations in early detection of diseases and pests. This research used the hybrid Fuzzy and K-Nearest Neighbor (K-NN) method to detect diseases and problems in rice plants. The fuzzy logic is used to find the membership value of the disease detection class and the K-NN method is used to find the closest distance between the evaluated data and its k closest neighbors in the training data. The results of trials conducted on 200 case data with 13 diseases and pests and 32 symptoms resulted in an accuracy of 98.74% with 160 training data and 40 test data, and the value of k=4. © 2022 IEEE.

关键词： Crops

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A Decoupled Segmentation-Classification Strategy based on Semantic-SAM for Precise Semantic Segmentation in Coal Mine Areas

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 14820-14842页

作者： Wang, Libing Dong, Jihong Wang, Lei Liu, Feng Wen, Qingke Genc, Bekir China University of Mining and Technology School of Environment and Spatial Informatics Engineering Research Center of Mine Ecological Restoration Ministry of Education Xuzhou 221116 China China University of Mining and Technology School of Environment and Spatial Informatics Xuzhou 221116 China China Coal Society Beijing 100013 China Chinese Academy of Sciences National Engineering Research Center for Geomatics (NCG) Aerospace Information Research Institute Beijing 100101 China University of the Witwatersrand School of Mining Engineering Johannesburg 2050 South Africa

Addressing the critical challenges of complex semantic segmentation in coal mine areas, this study proposes a precise recognition method based on Semantic-SAM. We developed the SAM-SEF (SAM-based Semantic Enhancement Framework) framework, which innovatively integrates the zero-shot segmentation capability of Semantic-SAM with specialized deep learning models. Through a “segmentation-classification-update” strategy, accurate segmentation is achieved. The framework initially employs Semantic-SAM to obtain category-agnostic multi-granularity segmentation results, followed by semantic understanding of the segmented regions using specialized deep learning models, and finally generates precise segmentation results through a category mapping mechanism. Experiments evaluated 18 deep learning models, including ResNet series, Vision Transformer series, classical convolutional neural networks, and lightweight networks. Results indicate that the SAM-SEF-ENet-B0 model, based on the SAM-SEF framework, performs most prominently in segmenting Open-pit Coal Mining Sites (OCMS) and Composite Coal-related Sites (CCS), achieving IoUs of 93.68% and 81.52%, respectively, and an mIoU of 87.60%, significantly outperforming traditional segmentation models. Additionally, a semi-automatic annotation tool based on Semantic-SAM was developed, reducing traditional manual annotation time by approximately 60% through pre-segmentation and interactive editing functions. A multi-scale evaluation system based on the 33% and 66% percentiles of target area was established, revealing a clear positive correlation between target scale and segmentation performance, with small-scale target segmentation being the primary challenge (IoU of 0.79 for OCMS and 0.67 for CCS in small scales). Systematic experiments validated the necessity of selecting Semantic-SAM, showing that Semantic-SAM has significant advantages over SAM (mIoU of 54.03%) and SAM2 (mIoU of 45.33%) in semantic understanding capability, architect

关键词： Coal Mine Site Segmentation Deep Learning Multi-scale Evaluation Remote Sensing Image Segmentation Semantic-SAM Semi-automatic Annotation

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Assessing Security and Performance: Varying Ring Oscillator Counts in Configurable Inversion Unit-based PUF

Assessing Security and Performance: Varying Ring Oscillator ...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Husam Kareem Dmitriy Dunaev Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

The concept of Physical Unclonable Function (PUF) has recently garnered attention in both industrial and academic fields as a promising hardware primitive for enhancing the security of electronic systems and devices. PUFs leverage inherent manufacturing inconsistencies to generate a distinct key for every device. PUFs utilize the inherent manufacturing variations to generate a distinct key for each device despite using identical input values across all devices. A range of PUF types have been developed, such as optical, electronic, and magnetic variations. However, the Ring Oscillator (RO) PUF stands out particularly due to its simple implementation and impressive performance. Due to the limited combinations of the RO-PUF input-output bits, or as it is called in the field of PUFs, challenge-response pairs (CRPs), researchers have developed the configurable ring oscillator (CRO) PUF, which produces a larger set of CRPs by utilizing a configurable inversion unit (CIU) instead of the standard inverter in the traditional design. Most of the recent research primarily focuses on increasing the size of the CRPs and enhancing security features. Yet, there is a lack of emphasis on investigating how the count of ROs affects the performance of the CRO-PUF. This paper uses several performance metrics to investigate the impact of altering the ring oscillator count on the CRO-PUF.

关键词： Ring oscillators Performance evaluation Embedded computing Physical unclonable function Reliability engineering Hardware Inverters

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