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2016年密码芯片学术会议

作者： Fan Zhang Liang Geng Congyuan Xu Jizhong Shen Xinjie Zhao Shize Guo College of Information Science & Electronic Engineering Zhejiang UniversityHangzhou 310027 China College of Information Science & Electronic Engineering Zhejiang UniversityHangzhou 310027 China Science and Technology on Communication Security Laboratory Chengdu 610041China The Institute of North Electronic Equipment Beijing 100000 China

Hiding and masking are two mainstream countermeasures against side channel analysis (SCA) at cell *** power analysis, both rely on the fact that variant data transitions consume more distinguishable power than invariant *** this letter, we propose a novel scheme based on fluctuating power logic (FPL), which mitigates the side-channel effect by employing cascade voltage logic to fluctuate physical power *** proposed scheme is illustrated by a standard flip-flop which typically behaves as a major power consumer of the *** based simulation shows that the modified flip-flop is resistant against power analysis at the cost of doubled power *** proposal can be further applied to enhance various SCA-resistant logics, such as sense-amplifier based logic (SABL) and wave dynamic differential logic (WDDL).

关键词： low power flip-flop clock-gating scheme dual-edge

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Markov chain-based attack on the CSMA/CA mechanism

Markov chain-based attack on the CSMA/CA mechanism

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International Conference on Multimedia, communication and Computing Application, MCCA 2014

作者： Wang, W. Zhao, W.H. Science and Technology on Communication Information Security Control Laboratory JiaxingZhejiang China Jiangnan Electronic Communication Institute JiaxingZhejiang314001 China Nanhu College Jiaxing University Jiaxing China

ISBN: (纸本)9781138027756

The CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) mechanism is formally modeled first. Then, based on the Markov Chain theory, the analysis of the attack on CSMA/CA is introduced from two aspects which are the stochastic performance model and bandwidth share model. After discussing the typical attack methods, the performance is analyzed from the aspects of throughput, communication efficiency, and collision numbers, which validates the feasibility and efficiency of attack method based on Markov Chain theory. © 2015 Taylor & Francis Group, London.

关键词： Carrier sense multiple access

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BLIND CFO ESTIMATION FOR MULTIUSER OFDM UPLINK WITH LARGE NUMBER OF RECEIVE ANTENNAS

BLIND CFO ESTIMATION FOR MULTIUSER OFDM UPLINK WITH LARGE NU...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Weile Zhang Feifei Gao Bobin Yao MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University China Tsinghua National Laboratory for Information Science and Technology Tsinghua University China School of Electronic and Control Engineering Chang'an University China

ISBN: (纸本)9781479999897

In this paper, we propose a new blind carrier frequency offset (CFO) estimation method for multiuser orthogonal frequency division multiplexing (OFDM) uplink transmissions. The spatial multiplexing is supported in the considered model that allows the subcarriers to be simultaneously occupied by multiple users. We propose to assign different null subcarriers to different users and design algorithm that can perform blind CFO estimation for each individual user with the aid of large number of receive antennas, which then removes the necessity of multidimensional searching. Numerical results are provided to corroborate the proposed studies.

关键词： Multiuser CFO estimation OFDM large number of antennas

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Trust recommendation algorithm for the virtual community based Internet of Things(IoT)

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Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University 2015年第2期42卷 52-57and179页

作者： Guo, Jingjing Ma, Jianfeng School of Computer Science and Technology Xidian Univ. Xi'an710071 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

In available trust based recommendation schemes, users always tend to transact with the entity with the highest trust value, which will result in the fact that the virtual community's resource cannot be fully utilized. The entity with the highest trust value will also delay the response because of its capacity constraint, so that its trust value will be bound to decline. To resolve this problem, we propose a recommendation algorithm which takes the community benefit and the stability of the entities' trust value into account. The community's control center adopts the Lyapunov optimization method to make a decision which can give it the maximum benefit on the premise of satisfying the desired constraint of the interaction requester, meanwhile guaranteeing the stability of the community nodes' trust value. Theoretical analysis and experiments show that our algorithm can stabilize the community nodes' trust value, and that it also can enable the whole community and resource requester to get more benefits. ©, 2015, science Press. All right reserved.

关键词： Network security

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Profiling and Identifying Users' Activities With Network Traffic Analysis

Profiling and Identifying Users' Activities With Network Tra...

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2015 6th IEEE International Conference on Software Engineering and Service science(ICSESS 2015)

作者： Ma Tao Ye Chun ming Chen Juan Science and Technology on Communication Information Security Control Laboratory Army Officer Academy

Traffic identification technique is used for classification of different network protocols and applications even with detection of users' network activities. In this paper, we conduct our study on some typical users' network activities and present a traffic identification method to describe the feature about users' behaviors. We convert users' network activities information into different sequences with frame size and interarrival time just like HMM model does. Then we use latent dirichlet allocation model to extract potential characterization from these activity sequences. We use some machine learning algorithms to classify different activities in the data, and we suggest a method to evaluate the mixed activities within a sequence. Our research shows that it is possible to distinguish exact users' on-line activities without inspection to packet payloads, and users' privacy may need more protection against traffic analysis.

关键词： User Activity Traffic Identification Privacy

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A New Important-Place Identification Method

A New Important-Place Identification Method

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2015 IEEE International Conference on Computer and communications(ICCC 2015)

作者： Chun-lai Ma Tao Ma Hong Shan Electronic Engineering Institute Science and Technology on Communication Information Security Control Laboratory

For the problem that the location of LBSN users was sparse because of it was updated sporadically. An important place identification method was studied by improving the clustering algorithm. Firstly, a velocity pruning algorithm was applied to remove interference points from source data. Secondly, clustering algorithm based on density peak named CFSFDP was selected. To solve the problem that it is unable to decide the cluster number with CFSFDP, an improved algorithm was presented. With a cluster center automatic choosing strategy, the algorithm searched for the ‘turning points' with the trends of cluster center weights changing. Then we could regard a set of points which weight is bigger than turning points' as cluster center. As a result, the error brought by ruling in the Decision Graph could be avoided with the strategy. Thirdly, reverse geocoding technology was applied to translate coordinate in semantic place. Check-in data of Foursquare user was set as an example in experiment, the result show that the improved algorithm had higher accuracy rate and lower computation compared to CFSFDP and DBSCAN. It also proved that the feasibility and effectiveness of the method proposed in the paper.

关键词： Velocity pruning Density based clustering Density peak Clustering center

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Author Correction: A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic

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Nature human behaviour 2022年第9期6卷 1318-1319页

作者： Ke Wang Amit Goldenberg Charles A Dorison Jeremy K Miller Andero Uusberg Jennifer S Lerner James J Gross Bamikole Bamikole Agesin Márcia Bernardo Olatz Campos Luis Eudave Karolina Grzech Daphna Hausman Ozery Emily A Jackson Elkin Oswaldo Luis Garcia Shira Meir Drexler Anita Penić Jurković Kafeel Rana John Paul Wilson Maria Antoniadi Kermeka Desai Zoi Gialitaki Elizaveta Kushnir Khaoula Nadif Olalla Niño Bravo Rafia Nauman Marlies Oosterlinck Myrto Pantazi Natalia Pilecka Anna Szabelska I M M van Steenkiste Katarzyna Filip Andreea Ioana Bozdoc Gabriela Mariana Marcu Elena Agadullina Matúš Adamkovič Marta Roczniewska Cecilia Reyna Angelos P Kassianos Minja Westerlund Lina Ahlgren Sara Pöntinen Gabriel Agboola Adetula Pinar Dursun Azuka Ikechukwu Arinze Nwadiogo Chisom Arinze Chisom Esther Ogbonnaya Izuchukwu L G Ndukaihe Ilker Dalgar Handan Akkas Paulo Manuel Macapagal Savannah Lewis Irem Metin-Orta Francesco Foroni Megan Willis Anabela Caetano Santos Aviv Mokady Niv Reggev Merve A Kurfali Martin R Vasilev Nora L Nock Michal Parzuchowski Mauricio F Espinoza Barría Marek Vranka Markéta Braun Kohlová Ivan Ropovik Mikayel Harutyunyan Chunhui Wang Elvin Yao Maja Becker Efisio Manunta Gwenael Kaminski Jordane Boudesseul Dafne Marko Kortnee Evans David M G Lewis Andrej Findor Anais Thibault Landry John Jamir Benzon Aruta Manuel S Ortiz Zahir Vally Ekaterina Pronizius Martin Voracek Claus Lamm Maurice Grinberg Ranran Li Jaroslava Varella Valentova Giovanna Mioni Nicola Cellini Sau-Chin Chen Janis Zickfeld Karis Moon Habiba Azab Neil Levy Alper Karababa Jennifer L Beaudry Leanne Boucher W Matthew Collins Anna Louise Todsen Kevin van Schie Jáchym Vintr Jozef Bavolar Lada Kaliska Valerija Križanić Lara Samojlenko Razieh Pourafshari Sandra J Geiger Julia Beitner Lara Warmelink Robert M Ross Ian D Stephen Thomas J Hostler Soufian Azouaghe Randy McCarthy Anna Szala Caterina Grano Claudio Singh Solorzano Gulnaz Anjum William Jimenez-Leal Maria Bradford Laura Calderón Pérez Julio E Cruz Vásquez Oscar J Galindo-Caballero Juan Cami Harvard Kennedy School Harvard University Cambridge MA USA. Harvard Business School Harvard University Cambridge MA USA. Kellogg School of Management Northwestern University Evanston IL USA. Department of Psychology Willamette University Salem OR USA. millerj@willamette.edu. Institute of Psychology University of Tartu Tartu Estonia. Harvard Kennedy School and Department of Psychology Harvard University Cambridge MA USA. Department of Psychology Stanford University Stanford CA USA. Adekunle Ajasin University Akungba Akoko Nigeria. Faculdade de Psicologia e Ciências da Educação Universidade do Porto Porto Portugal. University of Deusto Barakaldo Spain. University of Navarra Pamplona Spain. University of Valencia Valencia Spain. Stockholm University Stockholm Sweden. California State University Northridge Los Angeles CA USA. Indiana University of Pennsylvania Indiana PA USA. Universidad de Navarra Pamplona Spain. Department of Cognitive Psychology Institute of Cognitive Neuroscience Ruhr University Bochum Bochum Germany. Kindergarten Kustošija Zagreb Croatia. GC University Lahore Lahore Pakistan. Montclair State University Jersey City NJ USA. European University of Cyprus Nicosia Cyprus. Indiana University of Pennsylvania Akron PA USA. Leiden University Culemborg The Netherlands. Stockholm Sweden. Poggio Imperiale Italy. Barakaldo Spain. Islamabad Pakistan. Gent Belgium. Oxford Internet Institute University of Oxford Oxford UK. Warsaw Poland. Queen's University Belfast Belfast Ireland. Universiteit Leiden Leiden The Netherlands. Institute of Psychology Jagiellonian University Krakow Poland. Department of Psychology Lucian Blaga University of Sibiu Sibiu Romania. Carol Davila University of Medicine and Pharmacy Bucharest Romania. National Research University Higher School of Economics Moscow Russia. Institute of Psychology Faculty of Arts University of Presov Presov Slovakia. Institute of Social Sciences CSPS Sl

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Mid-infrared ZnGeP2 optical parametric oscillator pumped by Tm:YAlO3 laser

Mid-infrared ZnGeP2 optical parametric oscillator pumped by ...

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作者： Wang, Lixin Zhang, Xiaojuan Xu, Hong School of Electro-Optical Beijing Institute of Technology Beijing100081 China Science and Technology on Electro-Optical Information Security Control Laboratory Sanhe065201 China

We report experimental results on a mid-infrared (mid-IR) ZnGeP2 optical parametric oscillator (OPO) pumped by a thulium laser. A high efficient Q-switched a-cut Tm:YAlO3 (Tm:YAP) laser was used to directly drive a ZnGeP2 OPO to generate 3-5 μm wavelength range. The diode pumped Tm:YAP laser operated on 1.99 μm at 10 kHz repetition rate, and its optical-tooptical conversion efficiency was 22.2%. The laser was run with room temperature components and achieved nearly 2 W average output power at 3-5 μm region with an efficiency of 5.5% starting from the pump diode. The influences of curvature and reflectivity of OPO output mirror on laser output are analysed and validated by experiments, and the results have benefit for the optimisation of such lasers. Copyright © 2015 Inderscience Enterprises Ltd.

关键词： Optical parametric oscillators

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