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12,908 results

3. The Impact of Waste Paper Recycling on the Carbon Emissions from China's Paper Industry.

Author

Shang, Di, Diao, Gang, Liu, Chang, and Yu, Lucun

Subjects
PAPER recycling, CARBON emissions, WASTE recycling, PAPER industry, WASTE paper
Abstract

As China's demand for paper products increases, China's paper industry faces enormous pressure to reduce greenhouse gas emissions. By using material flow analysis in combination with input–output analysis, this study measured the waste paper recovery rate in a more accurate method and analyzed the impact of waste paper recycling on the carbon emissions from China's paper industry. China's waste paper recovery rate estimated in this study was close to 70% in 2017, much higher than that of 48% obtained with the traditional method. The regression results displayed a negative relationship between waste paper recovery rate and CO2 emissions per unit of paper consumption during 2000–2017 in China. The rolling regression results further indicated that the impact of waste paper recycling was becoming stronger on reducing CO2 emissions per unit of paper consumption in China. Since an inverted "U" shape relationship exists between waste paper recovery rate and its reduction effect on carbon emissions from the paper industry, the regression results suggested that China's waste paper recovery rate has not reached the optimal level with regard to carbon emissions from China's paper industry. Thus, although China's waste paper recovery rate has reached a relatively high level, currently waste paper recycling is still an effective method to reduce carbon emissions from China's paper industry. [ABSTRACT FROM AUTHOR]

Published
2021
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6. Route Planning Under Uncertainty: A Case Study on Objectives Apart from Mean Travel Time

Author

Gertheiss, Jan, Jaehn, Florian, Barbosa-Povoa, Ana Paula, Editorial Board Member, de Almeida, Adiel Teixeira, Editorial Board Member, Gans, Noah, Editorial Board Member, Gupta, Jatinder N. D., Editorial Board Member, Heim, Gregory R., Editorial Board Member, Hua, Guowei, Editorial Board Member, Kimms, Alf, Editorial Board Member, Li, Xiang, Editorial Board Member, Masri, Hatem, Editorial Board Member, Nickel, Stefan, Editorial Board Member, Qiu, Robin, Editorial Board Member, Shankar, Ravi, Editorial Board Member, Slowiński, Roman, Editorial Board Member, Tang, Christopher S., Editorial Board Member, Wu, Yuzhe, Editorial Board Member, Zhu, Joe, Editorial Board Member, Zopounidis, Constantin, Editorial Board Member, Trautmann, Norbert, editor, and Gnägi, Mario, editor

Published
2022
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7. Impact of Wind on the Predictability and Uncertainty Management of 4D-Trajectories

Author

Rodriguez-Sanz, Á., Canadell, M. Terradellas, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, and Electronic Navigation Research Institute, editor

Published
2021
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10. Application of Advanced Simulation Methods for the Tolerance Analysis of Mechanical Assemblies

Author

Bacharoudis, Konstantinos, Popov, Atanas, Ratchev, Svetan, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, and Ratchev, Svetan, editor

Published
2021
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11. The Dimensional Tolerance Analysis in Different Assembly Procedures Based on 3DCS

Author

Xia, Yufeng, Jiang, Lai, Yang, Dong, Zhou, Yuting, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, and (SAE-China), Society of Automotive Engineers, editor

Published
2019
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12. A Probabilistic Approach for Trade-off Analysis of Composite Wing Structures at the Conceptual Phase of Design

Author

Bacharoudis, Konstantinos, Turner, Thomas, Popov, Atanas, Ratchev, Svetan, Rannenberg, Kai, Editor-in-Chief, Sakarovitch, Jacques, Series Editor, Goedicke, Michael, Series Editor, Tatnall, Arthur, Series Editor, Neuhold, Erich J., Series Editor, Pras, Aiko, Series Editor, Tröltzsch, Fredi, Series Editor, Pries-Heje, Jan, Series Editor, Whitehouse, Diane, Series Editor, Reis, Ricardo, Series Editor, Furnell, Steven, Series Editor, Furbach, Ulrich, Series Editor, Winckler, Marco, Series Editor, Rauterberg, Matthias, Series Editor, and Ratchev, Svetan, editor

Published
2019
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13. A Probabilistic Modeling Strategy for Wind Power and System Demand

Author

Abdelaziz, A. Y., Othman, M. M., Ezzat, M., Mahmoud, A. M., Kanwar, Neeraj, Barbosa, Simone Diniz Junqueira, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Zelinka, Ivan, editor, Senkerik, Roman, editor, Panda, Ganapati, editor, and Lekshmi Kanthan, Padma Suresh, editor

Published
2018
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14. Computerized Adaptive English Ability Assessment Based on Deep Learning

Author

Wang, Xiao, Zhang, Yuanyuan, Yu, Shengnan, Liu, Xiwei, Wang, Fei-Yue, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, and Satoh, Shin'ichi, editor

Published
2018
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15. Approximate Probabilistic Power Flow

Author

Zuluaga, Carlos D., Álvarez, Mauricio A., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Woon, Wei Lee, editor, Aung, Zeyar, editor, Kramer, Oliver, editor, and Madnick, Stuart, editor

Published
2017
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16. Predicting the Unpredictable: Using Monte Carlo Simulation to Predict Project Completion Date

Author

Colucci, Lucas, Albino, Raphael, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Silva da Silva, Tiago, editor, Estácio, Bernardo, editor, Kroll, Josiane, editor, and Mantovani Fontana, Rafaela, editor

Published
2017
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21. Probabilistic Time-Dependent Travel Time Computation Using Monte Carlo Simulation

Author

Tomis, Radek, Rapant, Lukáš, Martinovič, Jan, Slaninová, Kateřina, Vondrák, Ivo, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Josef, Kittler, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Kozubek, Tomáš, editor, Blaheta, Radim, editor, Šístek, Jakub, editor, Rozložník, Miroslav, editor, and Čermák, Martin, editor

Published
2016
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22. STRATEGIES OF MAINTENANCE MODEL FOR EXERCISE BOOK MANUFACTURING MACHINE ON PAPER INDUSTRY BY IMPLEMENTING MONTE CARLO SIMULATION APPROACH

Author

Fina Andika Frida Astuti, Sugiono Sugiono, and Moch Agus Choiron

Subjects
Exercise Book Machine, Mean Time to Failure (MTTF), Component Reliability, Monte Carlo Simulation, Industrial engineering. Management engineering, T55.4-60.8
Abstract

PT. XYZ is one of many paper manufacturing companies in East Java which produces Exercise Book. The company implements corrective engine maintenance system where new components replacement is done when the engine is damaged. This treatment system resulted in frequent engine sudden stopping. With so many breakdown frequencies resulting from the fact that the engine stops abruptly, the broken raw materials increases in number and causes losses for the company. To overcome that problem we need appropriate treatment strategies to minimize the frequency of breakdown. Another aim is to minimize downtime and maintenance costs incurred because of engine maintenance activity. There are 3 maintenance scenarios implemented to solve such problem, i.e. scenario based on the existing condition of the company, scenario of component replacement in accordance with Mean Time to Failure (MTTF) value, and scenario of component replacement when the reliability of the component has reached 70%. From those three scenarios we will manually carry out an interval maintenance planning and Monte Carlo simulation. The result of data processing shows that in order to minimize the number of Exercise Book engine breakdown we can apply the 3rd scenario namely the replacement of component when the reliability of component has reached 70%. To minimize the amount of downtime and maintenance costs appropriately we shall use scenario 2, namely the replacement of component based on the Mean Time To Failure (MTTF) value.

Published
2017
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24. Multi-factor approximation : An analysis and comparison ofMichael Pykhtin's paper 'Multifactor adjustment'

Author

Zanetti, Michael and Güzel, Philip

Subjects
Advanced Internal Rantings-Based models, Matematik, Value at Risk, Kreditrisk, Advanced Internal Rantings-Based-modeller, Expected Shortfall, Credit risk, Monte Carlo simulation, Mathematics
Abstract

The need to account for potential losses in rare events is of utmost importance for corporations operating in the financial sector. Common measurements for potential losses are Value at Risk and Expected Shortfall. These are measures of which the computation typically requires immense Monte Carlo simulations. Another measurement is the Advanced Internal Ratings-Based model that estimates the capital requirement but solely accounts for a single risk factor. As an alternative to the commonly used time-consuming credit risk methods and measurements, Michael Pykhtin presents methods to approximate the Value at Risk and Expected Shortfall in his paper Multi-factor adjustment from 2004. The thesis’ main focus is an elucidation and investigation of the approximation methods that Pykhtin presents. Pykhtin’s approximations are thereafter implemented along with the Monte Carlo methods that is used as a benchmark. A recreation of the results Pykhtin presents is completed with satisfactory, strongly matching results, which is a confident verification that the methods have been implemented in correspondence with the article. The methods are also applied on a small and large synthetic Nordea data set to test the methods on alternative data. Due to the size complexity of the large data set, it cannot be computed in its original form. Thus, a clustering algorithm is used to eliminate this limitation while still keeping characteristics of the original data set. Executing the methods on the synthetic Nordea data sets, the Value at Risk and Expected Shortfall results have a larger discrepancy between approximated and Monte Carlo simulated results. The noted differences are probably due to increased borrower exposures, and portfolio structures not being compatible with Pykhtin’s approximation. The purpose of clustering the small data set is to test the effect on the accuracy and understand the clustering algorithm’s impact before implementing it on the large data set. Clustering the small data set caused deviant results compared to the original small data set, which is expected. The clustered large data set’s approximation results had a lower discrepancy to the benchmark Monte Carlo simulated results in comparison to the small data. The increased portfolio size creates a granularity decreasing the outcome’s variance for both the MC methods, and the approximation methods, hence the low discrepancy. Overall, Pykhtin’s approximations’ accuracy and execution time are relatively good for the experiments. It is however very challenging for the approximate methods to handle large portfolios, considering the issues that the portfolio run into at just a couple of thousand borrowers. Lastly, a comparison between the Advanced Internal Ratings-Based model, and modified Value at Risks and Expected Shortfalls are made. Calculating the capital requirement for the Advanced Internal Ratings-Based model, the absence of complex concentration risk consideration is clearly illustrated by the significantly lower results compared to either of the other methods. In addition, an increasing difference can be identified between the capital requirements obtained from Pykhtin’s approximation and the Monte Carlo method. This emphasizes the importance of utilizing complex methods to fully grasp the inherent portfolio risks. Behovet av att ta hänsyn till potentiella förluster av sällsynta händelser är av yttersta vikt för företag verksamma inom den finansiella sektorn. Vanliga mått på potentiella förluster är Value at Risk och Expected Shortfall. Dessa är mått där beräkningen vanligtvis kräver enorma Monte Carlo-simuleringar. Ett annat mått är Advanced Internal Ratings-Based-modellen som uppskattar ett kapitalkrav, men som enbart tar hänsyn till en riskfaktor. Som ett alternativ till dessa ofta förekommande och tidskrävande kreditriskmetoderna och mätningarna, presenterar Michael Pykhtin metoder för att approximera Value at Risk och Expected Shortfall i sin uppsats Multi-factor adjustment från 2004. Avhandlingens huvudfokus är en undersökning av de approximativa metoder som Pykhtin presenterar. Pykhtins approximationer implementeras och jämförs mot Monte Carlo-metoder, vars resultat används som referensvärden. Ett återskapande av resultaten Pykhtin presenterar i sin artikel har gjorts med tillfredsställande starkt matchande resultat, vilket är en säker verifiering av att metoderna har implementerats i samstämmighet med artikeln. Metoderna tillämpas även på ett litet och ett stor syntetiskt dataset erhållet av Nordea för att testa metoderna på alternativa data. På grund av komplexiteten hos det stora datasetet kan det inte beräknas i sin ursprungliga form. Således används en klustringsalgoritm för att eliminera denna begränsning samtidigt som egenskaperna hos den ursprungliga datamängden fortfarande bibehålls. Vid appliceringen av metoderna på de syntetiska Nordea-dataseten, identifierades en större diskrepans hos Value at Risk och Expected Shortfall-resultaten mellan de approximerade och Monte Carlo-simulerade resultaten. De noterade skillnaderna beror sannolikt på ökade exponeringar hos låntagarna och att portföljstrukturerna inte är förenliga med Pykhtins approximation. Syftet med klustringen av den lilla datasetet är att testa effekten av noggrannheten och förstå klustringsalgoritmens inverkan innan den implementeras på det stora datasetet. Att gruppera det lilla datasetet orsakade avvikande resultat jämfört med det ursprungliga lilla datasetet, vilket är förväntat. De modifierade stora datasetets approximativa resultat hade en lägre avvikelse mot de Monte Carlo simulerade benchmark resultaten i jämförelse med det lilla datasetet. Den ökade portföljstorleken skapar en finkornighet som minskar resultatets varians för både MC-metoderna och approximationerna, därav den låga diskrepansen. Sammantaget är Pykhtins approximationers noggrannhet och utförandetid relativt bra för experimenten. Det är dock väldigt utmanande för de approximativa metoderna att hantera stora portföljer, baserat på de problem som portföljen möter redan vid ett par tusen låntagare. Slutligen görs en jämförelse mellan Advanced Internal Ratings-Based-modellen, och modifierade Value at Risks och Expected shortfalls. När man beräknar kapitalkravet för Advanced Internal Ratings-Based-modellen, illustreras saknaden av komplexa koncentrationsrisköverväganden tydligt av de betydligt lägre resultaten jämfört med någon av de andra metoderna. Dessutom kan en ökad skillnad identifieras mellan kapitalkraven som erhålls från Pykhtins approximation och Monte Carlo-metoden. Detta understryker vikten av att använda komplexa metoder för att fullt ut förstå de inneboende portföljriskerna.

Published
2023

29. Towards Integration of Compositional Risk Analysis Using Monte Carlo Simulation and Security Testing

Author

Viehmann, Johannes, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bauer, Thomas, editor, Großmann, Jürgen, editor, Seehusen, Fredrik, editor, Stølen, Ketil, editor, and Wendland, Marc-Florian, editor

Published
2014
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30. Improving paper machine clothing supplier's industrial internet offering with artificial intelligence

Author

Janhunen, Lasse, Tekniikan ja luonnontieteiden tiedekunta - Faculty of Engineering and Natural Sciences, and Tampere University

Subjects
Artificial intelligence, Paper machine clothing, Konetekniikan DI-tutkinto-ohjelma, Reliability, Monte Carlo simulation, Industrial internet
Abstract

Overall amount of data has grown exponentially during the last few years. The increase in the availability of data has driven companies and countries towards digitalization with growing pace. Therefore, the industrial internet applications have become more successful than ever. These applications provide companies more tools to utilize data-driven decisions. In paper industry, paper machine original equipment manufacturers have started to utilize the industrial internet capabilities with increasing pace. The increasing competition has led to the fact that today, utilization of the possibilities offered by industrial internet is part of target organization’s (Valmet) main strategies. Thus, the paper machine clothing (PMC) unit of Valmet has commissioned this thesis work. The goal of this research was to improve Valmet’s PMC unit’s industrial internet offering. Improvement actions taken were to enhance the existing offering through customer feedback and to provide additional value with artificial intelligence. The approach towards the subject was to find out the existing theory behind the operational context of the fabrics, discover possible developmental actions through prototyping and by creating value-adding AI models to support the offering. During this research process it came evidently clear that the initial industrial internet applications would have good applicability in pilot customer’s daily routines. Though good developmental points were discovered from the prototyping phase, the functionality issues of the initial industrial internet applications during the timeframe of this thesis limited the quality of the feedback. More thorough study for customer feedback should be conducted after the applications have been in daily use for solid amount of time. This research provided two value-adding models for industrial internet applications. The idea for the models sprung from the hopes of the target company. Initially, fabric delivery cycles have been defined more or less by hand. Thus, the Monte Carlo simulation to optimize delivery cycles and to manage risk governing possible shortages was illustrated as the first model. The second model aimed to enhance the first model by conducting estimations of remaining fabric lifetime from customer’s mill’s process data. Neural network was chosen as the machine learning method for this model. Both models were tested with actual process data and the results of the case study were polarized. The simulation model provided valid results and first indications showed that it would bring true added value to the target organization. However, the results of the second model indicated that with available data valid results were not acquired. The results of this study indicate that the artificial intelligence models can be utilized to fabrics industrial internet but more emphasis should be pointed on the comparison of different machine learning methods and to enhance the quality and quantity of the available data.

Published
2019

33. Designing Capital-Intensive Systems with Architectural and Operational Flexibility Using a Screening Model

Author

Lin, Jijun, de Weck, Olivier, de Neufville, Richard, Robinson, Bob, MacGowan, David, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin (Sherman), Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert, Series editor, Coulson, Geoffrey, Series editor, and Zhou, Jie, editor

Published
2009
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34. Study of Human Influenza’s Spreading Phenomenon

Author

Trandafir, Romică, Resteanu, Cornel, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lirkov, Ivan, editor, Margenov, Svetozar, editor, and Waśniewski, Jerzy, editor

Published
2012
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37. High-Performance Ocean Color Monte Carlo Simulation in the Geo-info Project

Author

Kajiyama, Tamito, D’Alimonte, Davide, Cunha, José C., Zibordi, Giuseppe, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Karczewski, Konrad, editor, and Wasniewski, Jerzy, editor

Published
2010
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40. Monte Carlo Simulation for Reliability Centered Maintenance Management

Author

Resteanu, Cornel, Vaduva, Ion, Andreica, Marin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Lirkov, Ivan, editor, Margenov, Svetozar, editor, and Waśniewski, Jerzy, editor

Published
2008
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43. First Spiking Dynamics of Stochastic Neuronal Model with Optimal Control

Author

Wu, Yongjun, Peng, Jianhua, Luo, Ming, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Köppen, Mario, editor, Kasabov, Nikola, editor, and Coghill, George, editor

Published
2009
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44. Inverse-Halftoning for Error Diffusion Based on Statistical Mechanics of the Spin System

Author

Saika, Yohei, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ishikawa, Masumi, editor, Doya, Kenji, editor, Miyamoto, Hiroyuki, editor, and Yamakawa, Takeshi, editor

Published
2008
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