Academic literature on the topic 'Channel adaptation'
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Journal articles on the topic "Channel adaptation"
Ricci, Anthony. "Differences in Mechano-Transducer Channel Kinetics Underlie Tonotopic Distribution of Fast Adaptation in Auditory Hair Cells." Journal of Neurophysiology 87, no. 4 (April 1, 2002): 1738–48. http://dx.doi.org/10.1152/jn.00574.2001.
Full textSmall, D. L., and C. E. Morris. "Delayed activation of single mechanosensitive channels in Lymnaea neurons." American Journal of Physiology-Cell Physiology 267, no. 2 (August 1, 1994): C598—C606. http://dx.doi.org/10.1152/ajpcell.1994.267.2.c598.
Full textGeiser, Florian, Daniel Wessel, Matthias Hummert, Andreas Weber, Dirk Wübben, Armin Dekorsy, and Alberto Viseras. "DRLLA: Deep Reinforcement Learning for Link Adaptation." Telecom 3, no. 4 (November 23, 2022): 692–705. http://dx.doi.org/10.3390/telecom3040037.
Full textYang, Ge, Chao Zhang, Ling Gao, Yufei Guo, and Jinyang Guo. "Domain Adaptive Channel Pruning." Electronics 13, no. 5 (February 26, 2024): 887. http://dx.doi.org/10.3390/electronics13050887.
Full textWichmann, Lukas, and Mike Althaus. "Evolution of epithelial sodium channels: current concepts and hypotheses." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 319, no. 4 (October 1, 2020): R387—R400. http://dx.doi.org/10.1152/ajpregu.00144.2020.
Full textPejoski, Slavche, and Venceslav Kafedziski. "Cross-Layer Framework for Multiuser Real Time H.264/AVC Video Encoding and Transmission over Block Fading MIMO Channels Using Outage Probability." Advances in Multimedia 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/362196.
Full textRice, Joseph, Richard Shockley, Dale Green, John Proakis, and Milica Stojanovic. "Telesonar channel estimation and adaptation." Journal of the Acoustical Society of America 105, no. 2 (February 1999): 1364. http://dx.doi.org/10.1121/1.426462.
Full textIvanov, D. V., V. A. Ivanov, N. V. Ryabova, and A. A. Kislitsyn. "Implementation of the Maximum Bandwidth Ratio of Satellite Radio Communication Systems under the Conditions for Intramodal Dispersion of Transionospheric Radio Channels." Радиотехника и электроника 68, no. 6 (June 1, 2023): 571–78. http://dx.doi.org/10.31857/s0033849423060049.
Full textLi, Shuang, Chi Liu, Qiuxia Lin, Binhui Xie, Zhengming Ding, Gao Huang, and Jian Tang. "Domain Conditioned Adaptation Network." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 11386–93. http://dx.doi.org/10.1609/aaai.v34i07.6801.
Full textBelyy, Vladislav, Kishore Kamaraju, Bradley Akitake, Andriy Anishkin, and Sergei Sukharev. "Adaptive behavior of bacterial mechanosensitive channels is coupled to membrane mechanics." Journal of General Physiology 135, no. 6 (May 31, 2010): 641–52. http://dx.doi.org/10.1085/jgp.200910371.
Full textDissertations / Theses on the topic "Channel adaptation"
Choi, Jihwan Patrick 1975. "Channel prediction and adaptation over satellite channels with weather-induced impairments." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/9070.
Full textIncludes bibliographical references (leaves 85-87).
Title as it appears in MIT commencement exercises program, June 2000: Satellite channels with weather-induced impairments.
Bad weather conditions, especially due to rain, cause satellites operating at high frequencies (above 10 GHz) to have significant link attenuation. Usually extra link margins are used to assure link availability. These margins cause inefficient use of precious satellite and terminal power, and unnecessarily limit data throughputs. Efficiency improvements using channel prediction and adaptation over satellite channels with weather-induced impairments are considered in this thesis. First, we consider scintillation and rain attenuation as two dominant factors for signal fading over satellite-earth paths above 10 GHz, and explore physical and mathematical modeling of the two processes. Statistical and spectral analyses of these processes using one or two pole autoregressive (AR) models yield simple linear estimators for the received signal attenuation. Using these estimators, we present results where we can predict the received signal attenuation within ±0.5 dB 1 second ahead and within ± 1.0 dB 4 seconds ahead. For adaptation, we change the signal transmission power, the modulation symbol size, and the code rate adaptively. In particular, we suggest a continuous power control and discrete rate control strategy, through which we build a set of modulation/code states, and discretely change the modulation symbol size and the code rate from state to state. Within each state, continuous power control is implemented. Several examples that use this technique and quantitative analyses of power increase and capacity are provided. The analyses indicate that there is a substantial gain in performance either in capacity and/or power consumption with the adaptive schemes.
by Jihwan Patrick Choi.
S.M.
Qela, Blerim. "The 8-channel dynamic channel equalizer and its adaptation as a "smart amplifier solution"." Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/27013.
Full textRan, Jianjun. "Signal processing, channel estimation and link adaptation in MIMO-OFDM systems." Göttingen Cuvillier, 2008. http://d-nb.info/989862291/04.
Full textDu, Jinfeng. "Pulse Shape Adaptation and Channel Estimation in Generalised Frequency Division Multiplexing Systems." Licentiate thesis, Stockholm : Informations- och kommunikationsteknik, Kungliga Tekniska högskolan, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9457.
Full textOgino, Tetsuya. "Environmental adaptation mechanism in marine annelids." Kyoto University, 2019. http://hdl.handle.net/2433/242707.
Full text0048
新制・課程博士
博士(農学)
甲第21830号
農博第2343号
新制||農||1068(附属図書館)
学位論文||H31||N5202(農学部図書室)
京都大学大学院農学研究科応用生物科学専攻
(主査)教授 佐藤 健司, 教授 澤山 茂樹, 准教授 豊原 治彦
学位規則第4条第1項該当
El, Yakzan Adnan. "Performance prediction, parameter selection, and channel adaptation in the line-of-sight outdoors optical wireless channels using intelligent systems." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/59682/.
Full textHuusko, J. (Jarkko). "Communication performance prediction and link adaptation based on a statistical radio channel model." Doctoral thesis, Oulun yliopisto, 2016. http://urn.fi/urn:isbn:9789526211473.
Full textTiivistelmä Työn tavoitteena on kehittää luotettava semianalyyttinen suorituskyvyn ennustusmenetelmä tehokkaalle iteratiiviselle vastaanottimelle, joka käsittelee taajuusselektiivisen, vastaanotinpäässä tilakorreloituneen moniantennikanavan kautta kulkeneita tilakanavoituja signaaleja. Toisessa vaiheessa esitettyjä ennustusmenetelmiä hyödynnetään mukauttamalla lähetystehoa tai modulaatioastetta ja koodisuhdetta (adaptive modulation and coding [AMC]), samalla säilyttäen tavoitteeksi asetetun kehysvirhesuhteen (frame error rate [FER]). Suorituskyvyn ennustusmenetelmä hyödyntää kanavan tilastollisia ominaisuuksia – kohinan varianssia, eroteltavien etenemispolkujen lukumäärää sekä vastaanottimen korrelaatiomatriisin ominaisarvoja – ennustaakseen signaali–kohina-plus-interferenssisuhteen (signal-to-interference-plus-noise ratio [SINR]) jakauman taajuustasossa toimivan, häiriötä poistavan pienimmän keskineliösumman kanavakorjaimen lähdössä. SINR-jakaumasta johdetaan pehmän symboleista biteiksi -muunnoksen jälkeisten logaritmisten bittitodennäköisyyksien suhdelukujen (log-likelihood ratio [LLR]) jakauma. Keskinäisinformaation siirroskartat perustuvat LLR:ien varianssin sekä keskinäisinformaation väliseen bijektiivisyyteen. Informaatio on kanavakoodattu 3rd Generation Partnership Project -standardin mukaisella turbokoodilla. Turbodekooderin toiminta on kanavasta riippumatonta, joten dekooderin lisäinformaation siirroskartat (extrinsic information transfer [EXIT] charts) voidaan simuloida itsenäisesti. Hyödyntämällä kanavakorjaimen lähdön pehmeiden bittipäätösten LLR:ien varianssin jakaumaa, on mahdollista arvioida millä todennäköisyydellä korjaimen satunnaisen kanavarealisaation siirroskartta leikkaa dekooderin siirroskartan. Tämä todennäköisyys voidaan tulkita kehysvirhesuhteeksi. Koska suorituskyvyn ennustusmenetelmä ei vaadi hetkellistä tietoa kanavan tilasta, sitä voidaan hyödyntää lähetyksen mukautuksessa. Mukautuvassa tehonsäädössä modulaatio ja koodisuhde eivät muutu. Lähetin pyrkii iteratiivisella tehonsäädöllä löytämään korjaimen lähdölle LLR-jakauman, joka tuottaa halutun kehysvirhesuhteen. Mukautuvassa modulaation ja koodisuhteen valinnassa lähetysteho säilyy vakiona. Modulaatioaste vaikuttaa korjaimen lähdön LLR-jakaumaan ja koodisuhde dekooderin siirroskartan muotoon. Iteratiivisesti koodisuhdetta säätämällä lähetin pyrkii löytämään modulaation ja koodisuhteen yhdistelmän, joka saavuttaa tavoitellun kehysvirhesuhteen. Vertikaalisesti tilakanavoiduissa järjestelmissä mukautuvaa tehonsäätöä täydennetään lähetystehoa mukauttavilla uudellenlähetyksillä, kun taas mukautuvaa modulaation ja koodisuhteen valintaa täydennetään puolestaan koodisuhdetta pienentävillä automattisilla uudelleenlähetyspyynnöillä (hybrid automatic repeat request [HARQ])
Huang, Jinliang. "Adaptation in multiple input multiple output systems with channel state information at transmitter." Licentiate thesis, Stockholm : Institutionen för elektronik, dator- och programvarusystem, Kungliga tekniska högskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4443.
Full textFALCÃO, Marcos Rocha de Moraes. "Channel reservation and spectrum adaptation strategies in a multi-level prioritized cognitive radio network." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/21070.
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CAPES
Wireless technologies have dominated the communication's market by offering reasonable speeds and convenience at low deployment costs. However, due to the significant growth of mobile computing devices and their bandwidth demands, together with the paradigm shift brought by the Internet of things, future wireless networks should become highly dense and heterogeneous, which will hardly cope with the traditional fixed spectrum allocation policy. Some standards such as the Long Term Evolution – Advanced (LTE-A), have already set the precedent for carrier aggregation (CA), aiming at scaling up bitrates, which partially helps solving the problem. However, cognitive radio (CR) has been put forward as the most promising solution to handle this complex ecosystem since it may provide better spectrum utilization and user coordination through non-traditional mechanisms. Among other features, it allows non-licensed users, known as secondary users (SUs) to opportunistically use temporarily idle licensed bands that are used by licensed clients called primary users (PUs). Once PUs and SUs are expected to share the same spectrum bands, a critical issue is to concomitantly avoid primary interference while supporting QoS for the secondary services. This dissertation studies the synergistic integration of cognitive radio networks (CRNs), Dynamic Spectrum Access DSA techniques and resource allocation strategies (e.g., CA) that combined, should improve the overall system’s performance. We have proposed a layered M/M/N/N queue-based model that addresses three user priorities, flexible bandwidth choices, multi-level channel reservation and two channel aggregation strategies. Different network load conditions for each feature were evaluated in terms of four performance metrics: blocking probability, forced termination probability, spectrum utilization and throughput. Such study is particularly useful for understanding the effects of each of these approaches in the secondary network. To the best of our knowledge, our model fulfills almost completely the user bandwidth’s possibilities, improves the existing channel reservation formulation and demonstrates that our proposed dynamic channel aggregation strategy performs similarly to a more complex simultaneous channel aggregation and fragmentation approach, but can be technically more feasible.
Tecnologias sem fio têm dominado o mercado das comunicações, oferecendo velocidades razoáveis e conveniência a um baixo custo de implantação. No entanto, devido ao crescimento significativo do número de plataformas computacionais móveis e de suas demandas por largura de banda, acrescido do advento da Internet das Coisas, as redes sem fio do futuro devem passar a ser muito mais densas e heterogêneas, sendo difíceis de se adequar a política tradicional de alocação espectral fixa. Recentemente, o método de agregação de portadora (AP) fora proposto no padrão Long Term Evolution – Advanced (LTE-A), com o propósito de aumentar as taxas de bit, mitigando assim parte do problema. Todavia, rádio cognitivo (RC) foi apresentada como a solução mais promissora para lidar com este ecossistema complexo, uma vez que pode proporcionar uma melhor utilização do espectro e coordenação de usuários através de mecanismos não-tradicionais. Entre outras características, isso permite que usuários não-licenciados também conhecidos como usuários secundários (USs) utilizem de forma oportunista bandas licenciadas temporariamente ociosas, cujos clientes licenciados são também chamados de usuários primários (UPs). Como os UPs e os USs devem compartilhar as mesmas bandas, uma questão crítica é evitar interferência primária e concomitantemente apoiar a qualidade de serviço prestada aos USs. Esta dissertação estuda a integração sinérgica das redes de rádio cognitivas, técnicas de acesso dinâmico ao espectro e estratégias de alocação de recursos (AP), que combinados, devem melhorar o desempenho do sistema. Neste trabalho, propomos um modelo baseado em filas do tipo M/M/N/N, que inclui três prioridades de usuário, opções de largura de banda, reserva de canal multi-nível e duas estratégias de agregação de canal. Para cada recurso estudado, empregamos diferentes condições de carga de rede e avaliamos os resultados em termos de quatro métricas: probabilidade de bloqueio, a probabilidade de terminação forçada, utilização espectral e vazão. Este estudo é particularmente útil para compreender os efeitos de cada uma destas abordagens em relação à rede secundária. O modelo fornecido cumpre quase completamente as possibilidades do largura de banda de cada nível de usuário, melhora a formulação de reserva de canal existente e demonstra que estratégia de agregação de canais proposta possui performance similar a uma abordagem mais complexa de agregação e fragmentação simultânea, mas que seria tecnicamente mais viável.
Pollitte, Wesley Alan. "The effect of vertical networks on channel governance adaptation a transaction cost economics approach /." Diss., Connect to online resource - MSU authorized users, 2008.
Find full textBooks on the topic "Channel adaptation"
European Society for Comparative Physiology and Biochemistry. Conference. Adaptations to climatic changes. Edited by Pévet P. Basel: Karger, 1987.
Find full textFlint, Erdreich Sarah, ed. Adaptation and climate change. Detroit: Greenhaven Press, 2009.
Find full textPalutikof, Jean. Climate adaptation futures. The Atrium, Southern Gate, Chichester, West Sussex, UK: Wiley-Blackwell, A John Wiley & Sons Inc., 2013.
Find full textJenkins, Adam, and Adam Jenkins. Climate change adaptation: Ecology, mitigation, and management. Hauppauge, N.Y: Nova Science Publishers, 2010.
Find full textAdaptation to climate change. Abingdon, Oxon, England: Routledge, 2010.
Find full textUnited Nations Development Programme (Viangchan, Laos)., ed. National adaptation programme of action to climate change. [Vientiane]: UNDP, 2009.
Find full textClimate change adaptation: Ecology, mitigation, and management. Hauppauge, N.Y: Nova Science Publishers, 2010.
Find full textNeil, Leary, ed. Climate change and adaptation. London: Earthscan, 2008.
Find full textLuke, Parsons. Climate change risk and adaptation in Bangladesh. Dhaka: Green University Press, 2015.
Find full text1930-, Rosenberg Norman J., and Resources for the Future, eds. Greenhouse warming: Abatement and adaptation. Washington, D.C: Resources for the Future, 1989.
Find full textBook chapters on the topic "Channel adaptation"
Ponting, Keith M. "Channel Adaptation." In Computational Models of Speech Pattern Processing, 112–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60087-6_12.
Full textClasson, Brian, Ajit Nimbalker, Stefania Sesia, and Issam Toufik. "Link Adaptation and Channel Coding." In LTE - The UMTS Long Term Evolution, 215–48. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9780470978504.ch10.
Full textMorais, Douglas H. "Channel Coding and Link Adaptation." In Key 5G Physical Layer Technologies, 103–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51441-9_6.
Full textMorais, Douglas H. "Channel Coding and Link Adaptation." In Key 5G Physical Layer Technologies, 113–41. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89209-8_6.
Full textMorais, Douglas H. "Channel Coding and Link Adaptation." In 5G NR, Wi-Fi 6, and Bluetooth LE 5, 55–72. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33812-0_5.
Full textMorais, Douglas H. "Channel Coding and Link Adaptation." In Key 5G/5G-Advanced Physical Layer Technologies, 113–41. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-57426-9_6.
Full textJia, Yan, Xiang Zhang, Long Lan, and Zhigang Luo. "Self-Reinforcing Feedback Domain Adaptation Channel." In Neural Information Processing, 140–52. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30105-6_12.
Full textVallejo, Mónica, Joaquín Recas, and José L. Ayala. "Channel Analysis and Dynamic Adaptation for Energy-Efficient WBSNs." In Ubiquitous Computing and Ambient Intelligence, 42–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35377-2_6.
Full textYu, Chaohui, Jindong Wang, Yiqiang Chen, and Zijing Wu. "Transfer Channel Pruning for Compressing Deep Domain Adaptation Models." In Lecture Notes in Computer Science, 257–73. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26142-9_23.
Full textAkhtar, Saleem, and Djamal Zeghlache. "Rate and Power Adaptation for Downlink Shared Channel in WCDMA." In Multiaccess, Mobility and Teletraffic for Wireless Communications, volume 6, 61–74. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-5918-1_4.
Full textConference papers on the topic "Channel adaptation"
Yang, Chi, Bo Zhou, Xiaohui Hu, Jianying Chen, Qianhua Cai, and Yun Xue. "Dual-Channel Domain Adaptation Model." In WI-IAT '21: IEEE/WIC/ACM International Conference on Web Intelligence. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3498851.3498984.
Full textNguyen, Minh-Quang, Hang Nguyen, Eric Renault, and Phan-Thuan Do. "Joint source-channel coding with adaptation." In 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE). IEEE, 2016. http://dx.doi.org/10.1109/cce.2016.7562616.
Full textGanapathy, Sriram, Mohamed Omar, and Jason Pelecanos. "Noisy channel adaptation in language identification." In 2012 IEEE Spoken Language Technology Workshop (SLT 2012). IEEE, 2012. http://dx.doi.org/10.1109/slt.2012.6424241.
Full textJudd, Glenn, Xiaohui Wang, and Peter Steenkiste. "Low-overhead channel-aware rate adaptation." In the 13th annual ACM international conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1287853.1287903.
Full textHan, Cong, Kevin Wilson, Scott Wisdom, and John R. Hershey. "Unsupervised Multi-Channel Separation And Adaptation." In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024. http://dx.doi.org/10.1109/icassp48485.2024.10447422.
Full textBobarshad, H., M. R. Shikh Bahaei, and A. Kobravi. "BER-based adaptation in composite fading channel." In 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2008. http://dx.doi.org/10.1109/pimrc.2008.4699402.
Full textTridenski, Sergey, and Ram Zamir. "Channel Input Adaptation via Natural Type Selection." In 2018 IEEE International Symposium on Information Theory (ISIT). IEEE, 2018. http://dx.doi.org/10.1109/isit.2018.8437624.
Full textFissore, Lorenzo, Pietro Laface, G. Micca, and G. Sperto. "Channel adaptation for a continuous speech recognizer." In 2nd International Conference on Spoken Language Processing (ICSLP 1992). ISCA: ISCA, 1992. http://dx.doi.org/10.21437/icslp.1992-188.
Full textMohan, Avinash, and K. V. S. Hari. "Low complexity adaptation for channel shortening equalizers." In 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2011. http://dx.doi.org/10.1109/mwscas.2011.6026296.
Full textYao, Mingde, Jie Huang, Xin Jin, Ruikang Xu, Shenglong Zhou, Man Zhou, and Zhiwei Xiong. "Generalized Lightness Adaptation with Channel Selective Normalization." In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.00979.
Full textReports on the topic "Channel adaptation"
Odobetska, Iryna. ADAPTING REGIONAL TELEVISION CONTENT TO THE FORMAT OF SOCIAL NETWORKS (ON THE EXAMPLE OF THE VITA TV CHANNEL). Ivan Franko National University of Lviv, March 2024. http://dx.doi.org/10.30970/vjo.2024.54-55.12163.
Full textHertel, Thomas, and David Lobell. Agricultural Adaptation to Climate Change in Rich and Poor Countries: Current Modeling Practice and Potential for Empirical Contributions. GTAP Working Paper, December 2012. http://dx.doi.org/10.21642/gtap.wp72.
Full textGregow, Hilppa, Antti Mäkelä, Heikki Tuomenvirta, Sirkku Juhola, Janina Käyhkö, Adriaan Perrels, Eeva Kuntsi-Reunanen, et al. Ilmastonmuutokseen sopeutumisen ohjauskeinot, kustannukset ja alueelliset ulottuvuudet. Suomen ilmastopaneeli, 2021. http://dx.doi.org/10.31885/9789527457047.
Full textUS ARMY CORPS OF ENGINEERS. Climate Change Adaptation Plan. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada617444.
Full textCarrión, Gloria. Trade and Climate Change Adaptation. Geneva, Switzerland: International Centre for Trade and Sustainable Development, 2009. http://dx.doi.org/10.7215/co_in_20091023a.
Full textJohnson, T. Fisheries Adaptations to Climate Change. Alaska Sea Grant, University of Alaska Fairbanks, March 2012. http://dx.doi.org/10.4027/facc.2012.
Full textR., Bartlett, Bharati L., Pant D., Hosterman H., and McCornick P. Climate change impacts and adaptation in Nepal. International Water Management Institute (IWMI), 2010. http://dx.doi.org/10.5337/2010.227.
Full textKahn, Matthew. Climate Change Adaptation: Lessons from Urban Economics. Cambridge, MA: National Bureau of Economic Research, November 2014. http://dx.doi.org/10.3386/w20716.
Full textSveinsson, Oli G. B. Energy in Iceland: Adaptation to Climate Change. Edited by Hiroshan Hettiarachchi. United Nations University Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES), 2016. http://dx.doi.org/10.53325/adwy8262.
Full textLudeña, Carlos E., and Maria Netto. Brazil: Mitigation and Adaptation to Climate Change. Inter-American Development Bank, August 2011. http://dx.doi.org/10.18235/0009162.
Full text