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79 results on '"Izadi, Masoumeh"'

3. Microencapsulation of Lacticaseibacillus rhamnosusGG ATCC 53103 by freeze-drying: evaluation of storage stability and survival in simulated infant gastrointestinal digestion

Author

Izadi, Masoumeh, Niakousari, Mehrdad, Eskandari, Mohammad Hadi, Shekarforoush, Seyed Shahram, and Majdinasab, Marjan

Abstract

It is important for the probiotic to maintain its viability during food processing, gastrointestinal conditions, and storage. This study was aimed to apply the freeze-drying process to microencapsulate probiotic Lacticaseibacillus rhamnosusGG ATCC 53103. Wall materials consisted of whey protein isolate (WPI), WPI + fructooligosaccharides (WPI + FOS), WPI + galactooligosaccharides (WPI + GOS), and WPI + FOS + GOS. The results showed optimal levels of moisture content (3.85–4.1%) and water activity (0.087–0.115) in the freeze-dried powder (FDP) that contributed to the survival of L. rhamnosusduring storage. The morphology of un-encapsulated FDP indicated cell deformation and pile up whereas, for encapsulated samples, they were well entrapped and randomly distributed. Freeze-dried free cells were larger than encapsulated cells, irrespective of the wall material type. The survival rate results were over 96% after freeze-drying, depending on the type of wall materials. However, in the simulated infant gastrointestinal digestion, WPI + FOS + GOS-encapsulated cells showed a minimum decline in cellular survival. The survival of encapsulated probiotics was about 11.2 and 10.22 log cfu/g before storage and at 24 weeks of storage, respectively. This decline in survivability is within an acceptable range since the encapsulated L. rhamnosusGG 53103 are for incorporation into an infant formula powder. Overall, the data demonstrated that using combination of wall materials shows a better protective effect when encapsulated L. rhamnosusGG 53,103 is freeze dried and can be used in infant formula and baby food industries.

Published
2024
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5. Using Dynamic Bayesian Networks for Incorporating Nontraditional Data Sources in Public Health Surveillance

Author

Izadi, Masoumeh, Charland, Katia, Buckeridge, David L., Alhajj, Reda, Series editor, Glässer, Uwe, Series editor, Aggarwal, Charu C., Advisory board, Brantingham, Patricia L., Advisory board, Gross, Thilo, Advisory board, Han, Jiawei, Advisory board, Liu, Huan, Advisory board, Manasevich, Raul, Advisory board, Masys, Anthony J., Advisory board, Morselli, Carlo, Advisory board, Wittek, Rafael, Advisory board, Zeng, Daniel, Advisory board, Shaban-Nejad, Arash, editor, Brownstein, John S., editor, and Buckeridge, David L., editor

Published
2017
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7. Mining Administrative Data to Predict Falls in the Elderly Population

Author

Hosseinzadeh, Arian, Izadi, Masoumeh, Precup, Doina, Buckeridge, David, 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, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Kosseim, Leila, editor, and Inkpen, Diana, editor

Published
2012
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9. Belief Selection in Point-Based Planning Algorithms for POMDPs

Author

Izadi, Masoumeh T., Precup, Doina, Azar, Danielle, 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, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Lamontagne, Luc, editor, and Marchand, Mario, editor

Published
2006
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10. Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes

Author

Izadi, Masoumeh T., Precup, Doina, 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, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Gama, João, editor, Camacho, Rui, editor, Brazdil, Pavel B., editor, Jorge, Alípio Mário, editor, and Torgo, Luís, editor

Published
2005
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11. Sequential Decision Making Under Uncertainty

Author

Izadi, Masoumeh Tabaeh, 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, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Zucker, Jean-Daniel, editor, and Saitta, Lorenza, editor

Published
2005
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19. Belief selection in point-based planning algorithms for POMDPs

Author

Azar, Danielle, Izadi, Masoumeh T., Precup, Doina, Azar, Danielle, Izadi, Masoumeh T., and Precup, Doina

Abstract

Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. The performance of these algorithms can be improved by eliminating unnecessary backups or concentrating on more important points in the belief simplex. We study three methods designed to improve point-based value iteration algorithms. The first two methods are based on reachability analysis on the POMDP belief space. This approach relies on prioritizing the beliefs based on how they are reached from the given initial belief state. The third approach is motivated by the observation that beliefs which are the most overestimated or underestimated have greater influence on the precision of value function than other beliefs. We present an empirical evaluation illustrating how the performance of point-based value iteration (Pineau et al., 2003) varies with these approaches.

Published
2017

20. Broadening the perspective of AI in public-health surveillance: from local detection to global epidemic monitoring and control

Author

Buckeridge, David L., Izadi, Masoumeh, Verma, Aman, and Okhmatovskaia, Anya

Subjects
Artificial intelligence -- Usage, Epidemics -- Control, Epidemics -- Diagnosis, Epidemics -- Prevention, Medicine, Preventive -- Technology application, Preventive health services -- Technology application, Artificial intelligence, Technology application, Business, Computers, Computers and office automation industries, Electronics
Published
2009

21. A Bayesian Network Model for Analysis of Detection Performance in Surveillance Systems

Author

Izadi, Masoumeh, Buckeridge, David, Okhmatovskaia, Anna, Tu, Samson W., O‘Connor, Martin J., Nyulas, Csongor, and Musen, Mark A.

Subjects
Public Health Informatics, Population Surveillance, Humans, Bayes Theorem, Articles, Communicable Diseases, Algorithms, Disease Outbreaks
Abstract

Worldwide developments concerning infectious diseases and bioterrorism are driving forces for improving aberrancy detection in public health surveillance. The performance of an aberrancy detection algorithm can be measured in terms of sensitivity, specificity and timeliness. However, these metrics are probabilistically dependent variables and there is always a trade-off between them. This situation raises the question of how to quantify this tradeoff. The answer to this question depends on the characteristics of the specific disease under surveillance, the characteristics of data used for surveillance, and the algorithmic properties of detection methods. In practice, the evidence describing the relative performance of different algorithms remains fragmented and mainly qualitative. In this paper, we consider the development and evaluation of a Bayesian network framework for analysis of performance measures of aberrancy detection algorithms. This framework enables principled comparison of algorithms and identification of suitable algorithms for use in specific public health surveillance settings.

Published
2009

22. Decision Theoretic Analysis of Improving Epidemic Detection

Author

Izadi, Masoumeh T. and Buckeridge, David L.

Subjects
Anthrax, Decision Theory, Population Surveillance, Humans, Articles, Bioterrorism, Algorithms, Markov Chains, Decision Support Techniques, Disease Outbreaks
Abstract

The potentially catastrophic impact of an epidemic specially these due to bioterrorist attack, makes developing effective detection methods essential for public health. Current detection methods trade off reliability of alarms for early detection of outbreaks. The performance of these methods can be improved by disease-specific modeling techniques that take into account the potential costs and effects of an attack to provide optimal warnings and the cost and effectiveness of interventions. We study this optimization problem in the framework of sequential decision making under uncertainty. Our approach relies on estimating the future benefit of true alarms and the costs of false alarms. Using these quantities it identifies optimal decisions regarding the credibility of outputs from a traditional detection method at each point in time. The key contribution of this paper is to apply Partially Observable Markov Decision Processes (POMDPs) on outbreak detection methods for improving alarm function in the case of anthrax. We present empirical evidence illustrating that at a fixed specificity, the performance of detection methods with respect to sensitivity and timeliness is improved significantly by utilizing POMDPs in detection of anthrax attacks.

Published
2007

28. AI for Global Disease Surveillance

Author

Chen, Hsinchun, primary, Zeng, Daniel, additional, Buckeridge, David L., additional, Izadi, Masoumeh Izadi, additional, Verma, Aman, additional, Okhmatovskaia, Anya, additional, Hu, Xiaohua, additional, Shen, Xiajiong, additional, Cao, Zhidong, additional, Wang, Fei-Yue, additional, Zheng, Xiaolong, additional, and Wang, Quanyi, additional

Published
2009
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31. Belief Selection in Point-Based Planning Algorithms for POMDPs.

Author

Lamontagne, Luc, Marchand, Marion, Izadi, Masoumeh T., Precup, Doina, and Azar, Danielle

Abstract

Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. The performance of these algorithms can be improved by eliminating unnecessary backups or concentrating on more important points in the belief simplex. We study three methods designed to improve point-based value iteration algorithms. The first two methods are based on reachability analysis on the POMDP belief space. This approach relies on prioritizing the beliefs based on how they are reached from the given initial belief state. The third approach is motivated by the observation that beliefs which are the most overestimated or underestimated have greater influence on the precision of value function than other beliefs. We present an empirical evaluation illustrating how the performance of point-based value iteration (Pineau et al., 2003) varies with these approaches. [ABSTRACT FROM AUTHOR]

Published
2006
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32. Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes.

Author

Gama, João, Camacho, Rui, Brazdil, Pavel B., Jorge, Alípio M., Torgo, Luís, Izadi, Masoumeh T., and Precup, Doina

Abstract

Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actions and receives observations and rewards from the environment. Many POMDP solution methods are based on computing a belief state, which is a probability distribution over possible states in which the agent could be. The action choice of the agent is then based on the belief state. The belief state is computed based on a model of the environment, and the history of actions and observations seen by the agent. However, reward information is not taken into account in updating the belief state. In this paper, we argue that rewards can carry useful information that can help disambiguate the hidden state. We present a method for updating the belief state which takes rewards into account. We present experiments with exact and approximate planning methods on several standard POMDP domains, using this belief update method, and show that it can provide advantages, both in terms of speed and in terms of the quality of the solution obtained. [ABSTRACT FROM AUTHOR]

Published
2005
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33. Tracking Small and Fast Moving Ball in Broadcast Videos Using Transfer Learning and the Enhanced Interactive Multi-motion Model

Author

Jiang, Kan, Liu, Zhaoyu, Wu, Qirui, Ma, Murong, Dong, Jin Song, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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34. Exploring Team Strategy Dynamics in Tennis Doubles Matches

Author

Liu, Zhaoyu, Dong, Chen, Wang, Chen, Dong, Tian Yu, Jiang, Kan, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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35. Soccer Strategy Analytics Using Probabilistic Model Checkers

Author

Hundal, Rajdeep Singh, Liu, Zhaoyu, Wadhwa, Bimlesh, Hou, Zhe, Jiang, Kan, Dong, Jin Song, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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36. Analyzing Soccer Training Sessions to Predict Player Match Performance

Author

Javadpour, Leili, Khazaeli, Mehdi, Molenaar, Ryanne, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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37. Lending a Hand in Bringing Ballcarriers Down

Author

Battiste, Cecil Isaih, IV, Danoff, Charles Jeffrey, Hanes, Christopher, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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39. Effects of KF94 Face Mask on Cardiopulmonary Function and Subjective Sensation During Graded Exercise: A Comparison of KF94 2D and 3D Face Masks

Author

Um, Sungheum, Lee, Robert Seungbok, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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40. Mechanomyography as a Promising Tool for Managing Physical Activity and Preventing Injuries in the Field

Author

Reerink-Boulanger, Juliette, Ferssiwi, Auréanne, Projetti, Maxime, Correa, Matthieu, Somat, Alain, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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44. Age of Peak Performance Among Soccer Players in Sweden

Author

Säfvenberg, Rasmus, Nordgaard, Anders, Lidmark Eriksson, Ola, Carlsson, Niklas, Lambrix, Patrick, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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47. An Evaluation of the Determinants of Performance in NCAA Division I Women’s Basketball: A Dual-Season Investigation

Author

Senbel, Samah, Artan, N. Sertac, Taber, Christopher, Long, S. Alexander, Sharma, Srishti, Kandawala, Mahmud, Raval, Mehul S., Divakaran, Srikrishnan, Kaya, Tolga, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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48. Time-Series Analysis of Ball Carrier Open-Space in Association Football

Author

Bandara, Ishara, Shelyag, Sergiy, Rajasegarar, Sutharshan, Dwyer, Daniel B., Kim, Eun-jin, Angelova, Maia, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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49. Querying Football Matches for Event Data: Towards Using Large Language Models

Author

Schilling, Alexander, Anurathan, James, Mühlberger, Johannes, Gerschner, Felix, Rössle, Manfred, Theissler, Andreas, Klaiber, Marco, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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50. Data-Driven Smart Living Lab: Enhancing Community-Based Rehabilitation and Sports Participation for Individuals with Disabilities

Author

Moon, Kwangtae, Hong, Jin-i, Kim, Jongbae, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dong, Jin Song, editor, Izadi, Masoumeh, editor, and Hou, Zhe, editor

Published
2024
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