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Conference on Lasers and Electro-Optics (CLEO)

作者： Lue Wu Weiqiang Xie Chao Xiang Lin Chang Yan Yu Hao-Jing Chen Yoshihisa Yamamoto John E. Bowers Kerry J. Vahala Myoung-Gyun Suh T. J. Watson Laboratory of Applied Physics California Institute of Technology Pasadena CA USA Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA USA Physics & Informatics Laboratories NTT Research Inc. Sunnyvale CA USA

Soliton generation in AlGaAs microresonators at room temperation is reported for the first time. The destabilizing thermo-optic effect is shown to instead provide stability for high soliton repetition rates. The optic... 详细信息

ISBN: (纸本)9781957171258

关键词： Dielectric microcavities Frequency combs Microresonators Mode locking Q factor Thermo optic effects

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A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos

arXiv

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arXiv 2022年

作者： Lin, Zhi Lin, Junhao Zhu, Lei Fu, Huazhu Qin, Jing Wang, Liansheng Department of Computer Science School of Informatics Xiamen University Xiamen China Guangzhou China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Institute of High Performance Computing Agency for Science Technology and Research Singapore School of Nursing The Hong Kong Polytechnic University Kowloon Hong Kong

Breast lesion detection in ultrasound is critical for breast cancer diagnosis. Existing methods mainly rely on individual 2D ultrasound images or combine unlabeled video and labeled 2D images to train models for breast lesion detection. In this paper, we first collect and annotate an ultrasound video dataset (188 videos) for breast lesion detection. Moreover, we propose a clip-level and video-level feature aggregated network (CVA-Net) for addressing breast lesion detection in ultrasound videos by aggregating video-level lesion classification features and clip-level temporal features. The clip-level temporal features encode local temporal information of ordered video frames and global temporal information of shuffled video frames. In our CVA-Net, an inter-video fusion module is devised to fuse local features from original video frames and global features from shuffled video frames, and an intra-video fusion module is devised to learn the temporal information among adjacent video frames. Moreover, we learn video-level features to classify the breast lesions of the original video as benign or malignant lesions to further enhance the final breast lesion detection performance in ultrasound videos. Experimental results on our annotated dataset demonstrate that our CVA-Net clearly outperforms state-of-the-art methods. The corresponding code and dataset are publicly available at https://***/jhl-Det/CVA-Net. Copyright © 2022, The Authors. All rights reserved.

关键词： Ultrasonic applications

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Interfacial magnetic characteristics of nearly compensated gadolinium iron garnet

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Physical Review Materials 2024年第4期8卷 044403-044403页

作者： Karthik Srinivasan Alexander J. Grutter Thomas E. Gage P. Quarterman Christy J. Kinane Andrew J. Caruana Guichuan Yu Javier Garcia-Barriocanal Sean Langridge Bethanie J. H. Stadler Department of Electrical and Computer Engineering University of Minnesota 200 Union Street SE Minneapolis Minnesota 55455 USA Department of Electrical and Computer Engineering Boise State University Boise Idaho 83725 USA NIST Center for Neutron Research National Institute of Standards and Technology Gaithersburg Maryland 20878 USA Center for Nanoscale Materials Argonne National Laboratory Lemont Illinois 60439 USA ISIS-Neutron and Muon Source STFC Rutherford Appleton Laboratory Didcot Oxfordshire OX11 0QX United Kingdom Characterization Facility University of Minnesota 100 Union Street SE Minneapolis Minnesota 55455 USA Institute of Informatics University of Minnesota 2231 6th Street SE Minneapolis Minnesota 55455 USA

Reports on spin Hall magnetoresistance, magnonic spin currents from thermal gradients, and spin transfer-torque magnetic random-access memory using compensated ferrimagnets largely discuss bulk magnetization but lack consideration of depth profiles or interfacial characteristics. Here, magnetic and structural characterization of profiles and interfaces was performed for nearly compensated gadolinium iron garnet (GdIG) thin films. X-ray diffraction and reciprocal space maps show that sputter deposited GdIG on Si is polycrystalline with the desired cubic garnet phase, and GdIG on gadolinium gallium garnet (GGG) is epitaxial with <0.06% compressive strain. Temperature-dependent magnetometry confirms the compensation temperatures of GGG/GdIG and Si/GdIG to be 285 and 260 K, respectively, both near room temperature. Interestingly, these measurements suggest the presence of unsaturated rare-earth moments, which result in a characteristic hysteresis between heating and cooling sequences in the magnetization-temperature curves at zero field. Depth-profile measurements from polarized neutron reflectometry (PNR) indicate up to 91% volume fraction in GdIG on Si. At the interface, PNR reveals a region containing magnetized Fe-doped GGG, a low-density GdIG at the GGG/GdIG interface, and a thin magnetically dead layer at the Si/GdIG interface. Cross-sectional transmission electron microscopy and energy dispersive x-ray spectroscopy confirm the assessment of PNR. The magnetic characteristics of interfacial regions are attributed to intermixing of Fe-Ga at the GGG/GdIG interface and the presence of amorphous Fe-Si at the Si/GdIG interface.

关键词： Ferrimagnetism Magnetic insulators Rare-earth magnetic materials Magnetization measurements Neutron reflectometry Scanning transmission electron microscopy Sputtering

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Strategic Planning and Knowledge Management Approaches as input to remote area strategic plans: A Case study in Aru Islands Regency Maluku Province 8

Strategic Planning and Knowledge Management Approaches as in...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Irena Gutandjala, Ilona Harso Supangkat, Suhono Lumban Gaol, Ford Rianti, Benny Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta11480 Indonesia Bandung Institute of Technology Smart City and Community Innovation Center School of Electrical and Informatics Engineering Bandung Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781665416979

Knowledge is an important asset in an organization. Aru Islands District is one of the districts in Maluku Province. The Government of Aru Islands District Maluku has a vision and mission as outlined in the Regional Strategic Plan or commonly referred to as RENSTRA. This vision and mission are an activity that requires a policy direction that is planned and integrated with the strategic environment of all related aspects. The strategic plan is then realized with the implementation of the government with regional autonomy which is the modern governance in realizing quality public services, fast, easy, fair and unlimited for the welfare and progress of the region. In this research will be used a strategic approach as input from the analysis with knowledge management and assessment of the condition of Aru district. © 2021 IEEE.

关键词： Strategic planning

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Traffic Classification in Software-Defined Networking (SDN): Application of Machine Learning Models for Flooding DDoS Attack Detection

Traffic Classification in Software-Defined Networking (SDN):...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Lucas Leal Bosi André Chaves Mendes Raphael Melo Guedes Ronaldo Moreira Salles Defense Engineering Military Institute of Engineering Rio de Janeiro Brasil VALORIZA - Research Centre for Endogenous Resource Valorization Campus Politécnico Portalegre Portugal Informatics and Computer Science Department State University of Rio de Janeiro Campus Maracanã Rio de Janeiro Brazil CIICESI ESTG Polytechnic of Porto Porto Portugal

ISBN: (数字)9798331540319

ISBN: (纸本)9798331540326

Among the advantages offered by the SDN paradigm over traditional networks is the centralized implementation of comprehensive security policies. From this perspective, this study develops, trains, and tests several machine learning algorithms for traffic classification, distinguishing between legitimate traffic and three types of DDoS flooding attacks (HTTP, UDP, and TCP). The dataset used for training was employed both in its raw and preprocessed forms, and was generated in a reference study. The Random Forest and Gradient Boosting algorithms achieved the highest results in terms of accuracy and F1-score. Additionally, a comparison of the results of the studies is conducted.

关键词： Training Machine learning algorithms Accuracy Heuristic algorithms Denial-of-service attack Classification algorithms Security computer crime Software defined networking Tuning

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A machine learning method for predicting disease-associated microRNA connections using network internal topology data

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Healthcare Analytics 2023年 4卷 100215-100215页

作者： Jindal, Latika Sharma, Aditi Prasad, K.D.V. Irshad, Azeem Rivera, Richard Karimovna, Abdurakhimova Dilora Department of Computer Science and Engineering Medi-Caps university Indore India Department of computer science institute of engineering & technology Lucknow India Symbiosis Institute of Business Management Hyderabad India Symbiosis International (Deemed University) Pune India Asghar Mall College Rawalpindi Higher Education Department (HED) Govt. of the Punjab Pakistan Department of Informatics and Computer Science Escuela Politécnica Nacional Quito Ecuador Department of Corporate Finance and Securities Tashkent Institute of Finance Tashkent Uzbekistan

Recent studies have shown that aberrations or mutations of microRNAs (miRNA) can cause various diseases. Therefore, identifying disease-associated microRNAs can aid in diagnosing and treating related disorders. However, getting precise correlations through biological research is expensive and time-consuming. This research suggests a machine learning method (HNDLM) based on network internal topology data to anticipate disease-miRNA connections. HNDLM applies the recently described network embedding technique to biological networks rather than creating similar ones. According to the experimental findings, HNDLM performs better in terms of accuracy and Area Under the ROC Curve (AUC) value when compared to the traditional algorithms MIDPE, MIDP, WBSMDA, RLSMDA, Collective Prediction based on Transductive Learning (CPTL), and Human Disease-related MiRNA Prediction (HDMP). The top 30 potential miRNAs suggested by HNDLM can also be verified by earlier research in the case study. HNDLM can identify probable disease-miRNA correlations, which will aid in the investigation of illness path physiology and advance the field of bioinformatics. © 2023 The Authors

关键词： Bioinformatics Correlations Link prediction Machine learning MicroRNAs

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A Study on Methods for Managing Full-Duplex Self-Interference 5

A Study on Methods for Managing Full-Duplex Self-Interferenc...

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5th International Conference on Contemporary Computing and informatics, IC3I 2022

作者： Saxena, Shubham Sonawane, Sameer Lohani, Bhanu Prakash Garg, Ashish Deepak, A. Arora, Deepika International School of Business and Media Maharashtra Pune India Vidyapeeth's Institute of Management Studies & Research Department of Postgraduate Studies Bharati Maharashtra Navi-Mumbai India Amity University Uttar Pradesh Greater Noida India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha School of Engineering Tamilnadu Chennai India Lloyd Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350398267

This paper provides a comprehensive analysis of the steps necessary to disable self-interference (SI) in wireless networks and allow full duplex (FD) broadcasting. As a way of constructing mobile networks in regions where there is a scarcity of broadcast signals, the adoption of a frequency division method, also known as an in-band FD approach, has seen a rise in popularity. This method is also known as an in-band frequency division approach. Although the study does include reviews of methods for mitigating self-interference, great care has been taken to highlight not only the various strategies for mitigating the self-interference that occurs when FD equipment is activated, but also other methods that have a significant impact on self-interference in satellite propagation. While the study does include reviews of methods for mitigating self-interference, it is important to note that great care has been taken to highlight not only the various strategies for mitigating the self-interference that This review gives a scientific classification of self-interference and illustrates the usefulness of various kinds of self-interference as well as the limits that come with them. A synopsis of the study, a discussion of the difficulties encountered in the research, and a list of recommendations for the future stages are all necessary components of the review. The findings of this study might be used as a starting point and direction for future work on SI to perform FD propagation in mobile contexts with varied surrounds, such as the Internet of Things. © 2022 IEEE.

关键词： Wireless networks

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Integrating educational theories with virtual reality: Enhancing engineering education and VR laboratories

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Social Sciences and Humanities Open 2024年 10卷

作者： Abbas Shah, Syed Faisal Mazhar, Tehseen Shahzad, Tariq khan, Muhammad Amir Ghadi, Yazeed Yasin Hamam, Habib Department of Computer Science & Information Technology Virtual University of Pakistan Lahore 54000 Pakistan Department of Computer Science and information Technology School Education Department Government of Punjab Layyah 31200 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia Department of Computer Science and Software Engineering Al Ain University Abu Dhabi 12555 United Arab Emirates Faculty of Engineering University de Moncton Moncton E1A3E9 NB Canada Department of Electrical and Electronic Engineering Sciences University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles BP Libreville 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Immersive technologies, including virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR), create realistic digital experiences by overlaying digital elements. This study aims to highlight the benefits of utilizing VR technology in education, particularly in universities and higher education institutions, by integrating VR with educational theories to create engaging and interactive learning experiences that enhance understanding and retention. This review includes a comprehensive analysis of 103 works, synthesizing existing literature to evaluate the suitability of various educational approaches and theories for implementation in VR-based educational applications. The findings emphasize VR's potential to transform learning by providing immersive experiences that bridge different domains and encourage engagement. By integrating learning theory into VR development, meaningful learning environments can be created, improving student understanding and retention across diverse learning settings. The study concludes that the combination of technology and educational theories provides a novel approach to motivate students and foster deep learning in VR laboratories. © 2024 The Authors

关键词： Augmented reality Educational theories engineering education Immersive technology Interactive learning VR laboratories

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review

Critical Factors of Immersive Learning in Higher Education: ...

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International Conference on ICT For Smart Society (ICISS)

作者： Sunardi Meyliana Arief Ramadhan Yusep Rosmansyah Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information System Departement School of information system Bina Nusantara University Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of electrical engineering and informatics Bandung Institute of Technology Bandung Indonesia

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education.

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Forest Region Extraction and Evaluation from Satellite Images using CNN Segmentation

Forest Region Extraction and Evaluation from Satellite Image...

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Advances in Computing, Communication and Applied informatics (ACCAI), International Conference on

作者： Swaetha Ramadasan K. Vijayakumar S. Prabha E. Karthickeien Senior Business Intelligence Engineer Perma Technologies Atlanta GA USA Department of Information Technology St. Joseph’s Institute of Technology OMR Chennai TN India Department of CSE Center for Research and Innovation Saveetha School of Engineering SIMATS Chennai TN India Computer and Communication Engineering Amrita Vishwa Vidyapeetham Chennai TN India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

The segmentation and analysis of forests from satellite images play a vital role in the comprehensive monitoring and effective management of ecosystems. This process facilitates precise evaluations of various critical aspects such as forest cover, biodiversity, and overall health. By connecting this information, resource planning becomes more informed and strategic, contributing to sustainable forest management practices. Moreover, the data derived from satellite imagery aids in identifying areas susceptible to deforestation, allowing for timely intervention to mitigate its adverse environmental impacts. The integration of advanced satellite technologies in forest analysis enhances the ability to address contemporary environmental challenges, providing a foundation for policies and practices that promote ecological resilience and the long-term well-being of our planet. In this work, VGG-UNet is implemented to segment the forest and it achieved an accuracy of >94%, which is better compared to other existing methods in the literature.

关键词： Measurement Image segmentation Forests Satellites Information resources Planets Satellite images

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