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6th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2024

作者： Kaoshik, Jay Vyas, Pranav Tripathy, B.K. Swarnalatha, P. Nagaraja, G. School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India

ISBN: (纸本)9783031813351

Named Entity Recognition (NER), sometimes also referred to as Entity Extraction has been an integral part of Natural Language Understanding systems. To date, there have been continuous myriad efforts in linguistics and sequential modelling which have led to the development of reliable and highly efficient NER architectures. One frequent occurrence, however, is that most work done constitutes an inclination towards resource rich corpora. To bridge the grey space for real time code-mixed expressions, we present CASCAIN (Cascaded Attention Infused Network), which leverages attention for capturing sentence level context. We also experiment with multiple architectures involving varying number of recurrent units, attention types and stacking arrangements. To provide a comprehensive performance benchmark, we train and test our models on an extended set generated from two popular Hinglish datasets. Our best performing architecture incorporates Stacked Bi-Directional LSTM Units, each of which are paired with Attention Mechanisms for generating representations from Context Vector. CASCAIN achieves an accuracy of 94.31% on the Validation Set. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Long short-term memory

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Proactive Transport with High Link Utilization Using Opportunistic Packets in Cloud Data Centers

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IEEE Transactions on Mobile Computing 2025年

作者： Hu, Jinbin Huang, Jiawei Li, Zhaoyi Li, Yijun Rao, Shuying Jiang, Wenchao Chen, Kai Wang, Jianxin He, Tian Changsha University of Science and Technology School of Computer Science and Technology Changsha410114 China Central South University School of Computer Science and Engineering Changsha410083 China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong Hong Kong University of Minnesota Department of Computer Science and Engineering MinneapolisMN55455 United States

To meet the stringent demanding low latency and high throughput of cloud datacenter applications, recent receiver-driven transport protocols transmit only one packet once receiving each credit packet from the receiver to achieve ultra-low queueing delay. However, the round-trip time variation and the highly dynamic background traffic significantly deteriorate the performance of receiver-driven transport protocols, resulting in under-utilized bandwidth. This paper designs a simple yet effective solution called RPO, which retains the advantages of receiver-driven transmission while efficiently utilizing the available bandwidth. Specifically, RPO rationally uses low-priority opportunistic packets to ensure high network utilization without increasing the queueing delay of high-priority normal packets. Furthermore, to tackle the queueing buildup due to line-rate transmission in the first RTT, we design a selective dropping mechanism called SDM to help the majority of small flows complete within only one RTT by prioritizing the first-RTT bursty packets over the packets triggered by grants. We implement RPO in Linux hosts with DPDK. The experimental results show that RPO significantly improves the network utilization by up to 35% over the state-of-the-art schemes, without introducing additional queueing delay. Moreover, RPO integrated with SDM reduces the AFCT of small flows by up to 45% compared with RPO integrated with Aeolus. © 2002-2012 IEEE.

关键词： Bandwidth

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Integrating Function and Connection: Two Perspectives to Telepresence Robot Design for Classroom 25

Integrating Function and Connection: Two Perspectives to Tel...

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2025 ACM International Conference on Supporting Group Work, GROUP Companion 2025

作者： Berhane, Roda Akiode, Deo Adejoke Joshi, Swapna Elmimouni, Houda School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Field Robotics Lab Northeastern University BostonMA United States Department of Computer Science University of Manitoba WinnipegMB Canada Information Systems and New Media University of Siegen Siegen Germany

ISBN: (纸本)9798400711879

This study explores robotic telepresence in classrooms, from the perspectives of both the remote students (operators) and their in-person classmates. Analyzing a subset of field study data from 35 participants (22 operators, 13 classmates), we identified differing priorities: operators of the robot emphasize the need for improved functional aspects like camera control, while co-present classmates value social presence, interaction and identification, advocating for features like personalization and effective communication channels. These insights underline the need for telepresence robots that balance functional efficacy with social integration to provide a holistic educational experience. This work, though incomplete, enriches Group and CSCW literature on telepresence robots to facilitate collaborative interactions by highlighting the distinct needs of remote and in-person students, proposing design recommendations for telepresence robots that are technically proficient and socially responsive. © 2025 Copyright held by the owner/author(s).

关键词： Students

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A Review Analysis on Smart Blind Stick Using IoT 4

A Review Analysis on Smart Blind Stick Using IoT

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Asha, P.K. Shanmugha Priya, R.K. Nagaraj, D. Aswini, S. Wilson, G Preethi Vinoth Kumar, K. New Horizon College of Engineering Department of Chemistry Bengaluru India Jai Shriram Engineering College Avinashipalayam Department of Information Technology Tirupur India Dhanalakshmi College of Engineering Department of Cse Chennai India Bangalore Technological Institute Department of Cse Bengaluru India Jerusalem College of Engineering Department of Computer Science & Business Systems Chennai India New Horizon College of Engineering Department of Eee Bengaluru India

ISBN: (纸本)9798331523923

Millions of individuals worldwide struggle with blindness and other forms of visual impairment. 940 million individuals will suffer some degree of vision loss by 2015, according to the WHO (World Health Organization). 246 million people experience fleeting apparitions, while 39 million people are blind. Most people with bad vision are older than 50 and live in industrialized cultures. The main challenge that blind individuals encounter is mobility. They are cut off from their environment. Since they are oblivious to what is going on around them, they require assistance. Technological advancements have been crucial in increasing the mobility and freedom of those who are blind. One such innovation is the Smart Blind Stick, a high-tech assistance gadget made to improve the safety and navigation of the blind. The goal of this review article is to examine the many facets of Smart Blind Stick technology, including its functionality, benefits, drawbacks, and overall influence on users' life. This review aims to shed light on the current status of Smart Blind Stick technology and its potential future advances by reviewing existing literature and advancements. © 2025 IEEE.

关键词： Obstacle detectors

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Comparison and assessment of machine learning approaches in manufacturing applications

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Industrial Artificial Intelligence 2025年第1期3卷 1-16页

作者： Ramesh, K. Indrajith, M. N. Prasanna, Y. S. Deshmukh, Sandip S. Parimi, Chandu Ray, Tathagata Department of Mechanical Engineering BITS Pilani Hyderabad India Birla Institute of Technology and Science-Pilani Hyderabad India Department of Civil Engineering BITS Pilani Hyderabad India Department of Computer Science and Information Systems BITS Pilani Hyderabad India

Machine learning (ML) is increasingly used in industry processes to advance digital technologies for Industry 4.0. This paper comprehensively reviews ML applications in manufacturing, covering supervised, unsupervised, and deep learning (DL) approaches across various industrial processes. The use of ML approaches in manufacturing process planning and control, fault identification/manufacturing/assembly, monitoring in the agricultural industry, quality control, and optimisation of logistics and robots are being investigated. Key highlights include an analysis of 70 primary studies, comparing recent trends in ML for manufacturing, and examining ML training concepts in learning factories. We also use ML techniques to assess the automotive manufacturing industry's architectures, models, and deployment challenges. Furthermore, these notions will be examined and applied to all possible approaches. The improvements in the scope of identification of the proper algorithm for the adequate set of applications will be examined further to ensure the smooth going of the process from training to the testing set.

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Direct Photolithography of WO_(x) Nanoparticles for High‑Resolution Non‑Emissive Displays

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Nano-Micro Letters 2025年第3期17卷 297-309页

作者： Chang Gu Guojian Yang Wenxuan Wang Aiyan Shi Wenjuan Fang Lei Qian Xiaofei Hu Ting Zhang Chaoyu Xiang Yu‑Mo Zhang Laboratory of Optoelectronic Information Technology and Devices Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201People’s Republic of China Hangzhou Bay Laboratory of Advanced Nano‑Optoelectronic Materials and Devices Qianwan Institute of CNITECHNingbo 315336People’s Republic of China Smart Materials for Architecture Research Lab Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314100People’s Republic of China University of Science and Technology of China Hefei 230026People’s Republic of China State Key Lab of Supramolecular Structure and Materials College of ChemistryJilin UniversityChangchun 130012People’s Republic of China

High-resolution non-emissive displays based on electrochromic tungsten oxides(WOx)are crucial for future near-eye virtual/augmented reality interactions,given their impressive attributes such as high environmental stability,ideal outdoor readability,and low energy ***,the limited intrinsic structure of inorganic materials has presented a significant challenge in achieving precise patterning/pixelation at the micron ***,we successfully developed the direct photolithography for WOx nanoparticles based on in situ photo-induced ligand *** strategy enabled us to achieve ultra-high resolution efficiently(line width<4μm,the best resolution for reported inorganic electrochromic materials).Additionally,the resulting device exhibited impressive electrochromic performance,such as fast response(<1 s at 0 V),high coloration efficiency(119.5 cm^(2) C^(−1)),good optical modulation(55.9%),and durability(>3600 cycles),as well as promising applications in electronic logos,pixelated displays,flexible electronics,*** success and advancements presented here are expected to inspire and accelerate research and development(R&D)in high-resolution non-emissive displays and other ultra-fine micro-electronics.

关键词： Electrochromic Direct photolithography WOx nanoparticles In situ photo-induced ligand exchange High-resolution displays

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Low-coherence interferometric dimensional measurement technique based on synchrosqueezed wavelet transform

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Optics Express 2025年第10期33卷 20192-20201页

作者： Tian, Yuqi Dang, Hong Zhang, Pengyu Yu, Liang Feng, Kunpeng Cui, Jiwen Deng, Hu Shang, Liping School of Information Engineering Southwest University of Science and Technology Mianyang 621010 China State Key Laboratory of Optical Fiber and Cable Manufacture Technology Department of EEE Southern University of Science and Technology Shenzhen 518055 China Joint Laboratory for Extreme Conditions Matter Properties Southwest University of Science and Technology 59 Qinglong Road Sichuan Mianyang 621010 China Sichuan Vocational and Technical College of Communications Chengdu 611130 China School of Civil Aviation Northwestern Polytechnical University Xi’an 710072 China Key Laboratory of Non-Destructive Testing and Monitoring Technology for High-Speed Transport Facilities Nanjing University of Aeronautics and Astronautics Nanjing 211106 China Key Lab of Ultra-Precision Intelligent Instrumentation (Harbin Institute of Technology) Ministry of Industry and Information Technology Harbin 150080 China

This paper addresses the issue of reduced measurement stability in low-coherence measurement techniques when applied to glass-based dispersive media. A high-precision, low-coherence interferometric measurement method is proposed based on synchrosqueezed Wavelet Transform (SSWT). First, the Schott dispersion formula is used to analyze the impact of glass-based dispersive media on the phase of the interference spectrum. Wavelet transform is then employed to extract the chirp information of the interference spectrum, enabling the separation of optical path lengths for different wavenumbers. Building upon this, SSWT is introduced to enhance time-frequency resolution further, improving the measurement performance of the system. An experimental setup is constructed to validate the effectiveness of the proposed method. Compared to traditional methods, SSWT optimizes the distribution of wavelet coefficients, concentrating signal energy and significantly improving instantaneous frequency capture accuracy. Experimental results show that, in addition to effectively capturing chirp characteristics and reducing phase noise, SSWT achieves a 3-fold and 7-fold improvement in peak full-width at half-maximum compared to conventional Fourier Transform (FT) and Continuous Wavelet Transform (CWT), respectively, and a 9.1-fold and 17.1-fold improvement in standard deviation over 20 measurements, demonstrating superior noise resistance and measurement precision. In conclusion, the SSWT-based white-light interferometric measurement method provides a high-precision, reliable solution for dimensional measurements in industrial applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Fiber optic couplers Fourier transforms Optical frequency domain reflectometry Phase noise Precision metrology Wavelet transforms

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Mask-guided Multi-scale Spatial-Spectral Transformer for Snapshot Compressive Imaging

Mask-guided Multi-scale Spatial-Spectral Transformer for Sna...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Heyuan Yin Jingxiang Yang Jia Liu Liang Xiao School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Key Laboratory of Analysis of Mathematical Theory and Modeling of Complex Systems The Ministry of Industry and Information Technology China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Effectively reconstructing 3D hyperspectral images (HSIs) from 2D measurements presents a significant challenge in Coded Aperture Snapshot Spectral Imaging (CASSI) systems. While recent transformers exhibit potential in HSI reconstruction, they often suffer from inadequate exploration of multi-scale spatial-spectral self-similarity, leading to mean effects and information loss. Additionally, these methods struggle with insufficient modeling of the degradation inherent in the compressive imaging process. To address these issues, we propose a novel Mask-guided Multi-scale Spatial-Spectral Transformer (MMSST). Specifically, we introduce a Degradation Aware Mask Attention (DAMA) module to incorporate degradation information of the compressive imaging process. Furthermore, MMSST leverages Local-Regional SpAtial attention (LRSA) and Global-Regional SpEctral attention (GRSE) to effectively exploit multi-scale self-similarity across spatial and spectral dimensions. Extensive experimental results demonstrate the effectiveness of our MMSST.

关键词： Degradation Three-dimensional displays Computational modeling Imaging Transformer cores Signal processing Transformers Speech processing Image reconstruction Hyperspectral imaging

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Brain Function Assessment of EEG in Mild Cognitive Impairment using Timelag Analysis

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2025年第4期145卷 467-473页

作者： Tanabe, Akifumi Harachi, Kento Yamamoto, Yusuke Muramatsu, Ayumi Nagahara, Hajime Takemura, Noriko Shimojo, Shinji Furihata, Daisuke Mizuno-Matsumoto, Yuko Graduate School of Information Science University of Hyogo 7-1-28 Minatojima Minami Chuo-ku Hyogo Kobe650-0047 Japan Department of Medical Engineering Aino University 4-5-4 Higashi-Ohda Ibaraki Osaka567-0012 Japan D3 Center The University of Osaka 2-8 Yamadaoka Osaka Suita565-0871 Japan D3 Center The University of Osaka 5-1 Mihogaoka Ibaraki Osaka567-0047 Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Faculty of Software and Information Technology Aomori University 2-3-1 Shachihata Aomori-shi Aomori030-0943 Japan

This research aimed to reveal the information process in the brain of the patients who suffered from mild cognitive impairment (MCI) using the power spectra and timelag analysis in electroencephalogram (EEG). The patients with MCI have memory or thinking problems, and are at a great risk of developing Alzheimer's disease or a related dementia. Ten patients with MCI and 13 healthy adults (non-MCI) were examined. The EEGs (122.88 seconds/subject) during a state of relaxation with the eyes closed, were analyzed using the Fourier analysis (power spectrum) and the timelag analysis. The results showed that the mean value of the power spectra in MCI was significantly higher than the mean value in non-MCI in the theta band. The mean value of the absolute timelag values (ATL) in MCI was significantly lower than the mean value in non-MCI in the frontal and left temporal areas. Our findings suggest that the features from EEG of MCI were abstracted in the theta band, and the propagation of information related to memory in brain would becoming fast in MCI. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Electroencephalography

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Combining Instance Segmentation and Background Subtraction Models for Small Object Detection

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International Journal of Automation technology 2025年第3期19卷 237-247页

作者： Dhammatorn, Wisan Ito, Seiya Kaneko, Naoshi Sumi, Kazuhiko Graduate School of Science and Engineering Aoyama Gakuin University 5-10-1 Fuchinobe Chuo-ku Kanagawa Sagamihara252-5258 Japan Tokyo Japan Department of Information Systems and Multimedia Design School of Science and Technology for Future Life Tokyo Denki University Tokyo Japan Department of Integrated Information Technology College of Science and Engineering Aoyama Gakuin University Sagamihara Japan

Object detection is a fundamental problem in computer vision that has been extensively investigated over the past decades. Although deep neural networks (DNNs) improve object detection, they cannot effectively rec-ognize small objects. Detecting small objects remains challenging owing to several factors, such as low res-olution and scale variance. These challenges are par-ticularly evident in object detection using surveillance cameras, where small objects typically appear in clut-tered environments and at varying distances. In object detection using surveillance cameras, the static nature of the background has not been fully exploited in DNN-based object detection methods, although it can be an important cue for detection. In this study, we propose a simple yet effective method to enhance object detection in areas of small objects not detectable by state-of-the-art DNN-based instance segmentation methods. The proposed method extracts foreground regions using a background subtraction model and classifies them, thereby enabling the identification of small objects. In our experiments, we evaluate two real-world scenarios: detecting a person walking on campus and identifying vehicles in road-surveillance footage. The results show that our method improves the detection of small objects and performs better than baseline methods. © Fuji technology Press Ltd.

关键词： Vehicle detection

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