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1,271 results on '"Phan H"'

1. Development of shear strength prediction model for RC beams strengthened with FRP strips based on a novel ensemble learning model

Author

Huynh P. Nam, Nguyen D. D. Nam, Nguyen H. Thinh, Phan H. Nam, Ho M. Hung, Do V. Hai, and Phan D. Thao

Subjects
shears strengthening, rc beam, frp strips, ensemble learning, shear strength, Technology
Abstract

The use of fiber-reinforced polymer (FRP) strips as an external strengthening method has gained widespread acceptance for enhancing the capacity of aging reinforced concrete (RC) beams. Despite extensive research and practical applications, there exist unresolved issues necessitating further investigation, including interface bonding, failure mechanisms, and the development of accurate predictive models for shear strength, considering diverse parameters. This paper systematically reviews shear strength formulas applied in the strengthening of RC beams using FRP strips. An extensive experimental dataset is compiled from diverse sources to support the analysis. Utilizing this dataset, a novel ensemble learning model is developed for predicting the shear strength contributed by FRP strips. Following the training of this model, the important score of each input parameter is also assessed. The findings presented herein contribute to a deeper understanding of the strengthening effectiveness of FRP strips on RC beams.

Published
2024
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2. Alterations in iron content, iron-regulatory proteins and behaviour without tau pathology at one year following repetitive mild traumatic brain injury

Author

Sydney M. A. Juan, Maria Daglas, Phan H. Truong, Celeste Mawal, and Paul A. Adlard

Subjects
Repetitive mild traumatic brain injury, Tau phosphorylation, Metal dyshomeostasis, Iron-regulatory proteins, Neurodegeneration, Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Repetitive mild traumatic brain injury (r-mTBI) has increasingly become recognised as a risk factor for the development of neurodegenerative diseases, many of which are characterised by tau pathology, metal dyshomeostasis and behavioural impairments. We aimed to characterise the status of tau and the involvement of iron dyshomeostasis in repetitive controlled cortical impact injury (5 impacts, 48 h apart) in 3-month-old C57Bl6 mice at the chronic (12-month) time point. We performed a battery of behavioural tests, characterised the status of neurodegeneration-associated proteins (tau and tau-regulatory proteins, amyloid precursor protein and iron-regulatory proteins) via western blot; and metal levels using bulk inductively coupled plasma-mass spectrometry (ICP-MS). We report significant changes in various ipsilateral iron-regulatory proteins following five but not a single injury, and significant increases in contralateral iron, zinc and copper levels following five impacts. There was no evidence of tau pathology or changes in tau-regulatory proteins following five impacts, although some changes were observed following a single injury. Five impacts resulted in significant gait deficits, mild anhedonia and mild cognitive deficits at 9–12 months post-injury, effects not seen following a single injury. To the best of our knowledge, we are the first to describe chronic changes in metals and iron-regulatory proteins in a mouse model of r-mTBI, providing a strong indication towards an overall increase in brain iron levels (and other metals) in the chronic phase following r-mTBI. These results bring to question the relevance of tau and highlight the involvement of iron dysregulation in the development and/or progression of neurodegeneration following injury, which may lead to new therapeutic approaches in the future.

Published
2023
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3. Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS

Author

Phan H. Nguyen, Long T. Banh, Viet. D. Bui, and Dung T. Hoang

Subjects
Taguchi, TOPSIS, EDM, PMEDM, S/N ratio, Titanium, Social Sciences, Management. Industrial management, HD28-70
Abstract

In this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (toff), Current (I) and powder concentration have been selected to optimize two responses; namely surface roughness (Ra) and surface hardness (HV). The results show that titanium powder mixed dielectric fluid improves multi-response optimization efficiency in PMEDM. In addition, machining conditions, such as tool electrode material, powder concentration, pulse on time, polarity, current density, A×G and B×G interactions play a very important role on S/N ratio of C* whereby powder concentration has the strongest influence. TOPSIS -Taguchi is a potential method for multi-response optimization in PMEDM. However, the optimal results using ANOVA analysis show that there is a necessity to have more studies in TOPSIS-Taguchi to improve the in-tegration efficiency between two methods for optimizing multiple responses in PMEDM.

Published
2018
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18. Integrating Blockchain and RSA-Encrypted NFTs for Enhanced Digital Knowledge Management

Author

Trung, Phan H. T., Bang, Le K., Kha, Nguyen Hoang, Bao, Tran Quoc, Trong, Nguyen Duong Phu, Nam, Tran Ba, Hieu, Doan Minh, Khiem, Huynh Gia, 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, Cao, Cungeng, editor, Chen, Huajun, editor, Zhao, Liang, editor, Arshad, Junaid, editor, Asyhari, Taufiq, editor, and Wang, Yonghao, editor

Published
2024
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19. miR-155 Controls Lymphoproliferation in LAT Mutant Mice by Restraining T-Cell Apoptosis via SHIP-1/mTOR and PAK1/FOXO3/BIM Pathways.

Author

Alexandre K Rouquette-Jazdanian, Robert L Kortum, Wenmei Li, Robert K Merrill, Phan H Nguyen, Lawrence E Samelson, and Connie L Sommers

Subjects
Medicine, Science
Abstract

Linker for Activation of T cells (LAT) is an adapter protein that is essential for T cell function. Knock-in mice with a LAT mutation impairing calcium flux develop a fatal CD4+ lymphoproliferative disease. miR-155 is a microRNA that is correlated with hyperproliferation in a number of cancers including lymphomas and leukemias and is overexpressed in mutant LAT T cells. To test whether miR-155 was merely indicative of T cell activation or whether it contributes to lymphoproliferative disease in mutant LAT mice, we interbred LAT mutant and miR-155-deficient mice. miR-155 deficiency markedly inhibited lymphoproliferative disease by stimulating BIM-dependent CD4+ T cell apoptosis, even though ERK activation and T cell proliferation were increased in double mutant CD4+ T cells. Bim/Bcl2l11 expression is activated by the forkhead transcription factor FOXO3. Using miR-155-deficient, LAT mutant T cells as a discovery tool, we found two connected pathways that impact the nuclear translocation and activation of FOXO3 in T cells. One pathway is mediated by the inositide phosphatase SHIP-1 and the serine/threonine kinases AKT and PDK1. The other pathway involves PAK1 and JNK kinase activation. We define crosstalk between the two pathways via the kinase mTOR, which stabilizes PAK1. This study establishes a role for PAK1 in T cell apoptosis, which contrasts to its previously identified role in T cell proliferation. Furthermore, miR-155 regulates the delicate balance between PAK1-mediated proliferation and apoptosis in T cells impacting lymphoid organ size and function.

Published
2015
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23. Numerical and Experimental Study of Flow-Induced Vibrations in Micro-Tube Heat Exchangers.

Author

Phan, H. M., Newman, F., O'Pray, C. E., and Parikh, D.

Abstract

Thermal management presents an increasing challenge in future engineering systems, especially in applications like combined cycle precooling, waste heat recovery, and innovative propulsion systems. These systems face a growing demand for managing higher heat loads while coping with limited heat sink. Central to these thermal management systems is the heat exchanger, with microtube heat transfer emerging as a promising solution for future technologies. Microtube heat exchangers are becoming popular owing to their ability to significantly enhance the heat transfer surface area while maintaining a compact core volume. As the demand for high-performance, lightweight heat exchangers escalates, microtube heat exchangers are being designed to be increasingly compact yet highly loaded. This trend poses significant challenges to their structural integrity, particularly under harsh operational conditions. Flow-induced vibrations, a critical concern in the design of tubular heat exchangers, can lead to tube failures, compromising the safe operation of engineering systems. While the flow-induced vibrations of conventional-sized heat exchangers have been extensively studied, there is a noticeable gap in the research on similar phenomena in microtube heat exchangers. This paper details ongoing research at Reaction Engines Ltd (REL) to aid the design of safe and robust heat exchangers, focusing on the flow-induced vibrations in microtube heat exchangers and utilizing a cutting-edge laser vibrometry test facility. A predictive model, employing an unsteady flow simulation approach and eigenvalue analysis, has been formulated. A key observation is the distinctive coupled transverse-streamwise orbital motion in microtube heat exchangers, differing from the predominantly transverse direction of failures in conventional-sized heat exchangers. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Genomic epidemiology and longitudinal sampling of ward wastewater environments and patients reveals complexity of the transmission dynamics of blaKPC-carbapenemase-producing Enterobacterales in a hospital setting.

Author

Stoesser, N, George, R, Aiken, Z, Phan, H T T, Lipworth, S, Quan, T P, Mathers, A J, Maio, N De, Seale, A C, Eyre, D W, Vaughan, A, Swann, J, Peto, T E A, Crook, D W, Cawthorne, J, Dodgson, A, Walker, A S, and Group, TRACE Investigators

Published
2024
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30. Active demultiplexing of single-photons from a solid-state source

Author

Lenzini, F., Haylock, B., Loredo, J. C., Abrahao, R. A., Zakaria, N. A., Kasture, S., Sagnes, I., Lemaitre, A., Phan, H. -P., Dao, D. V., Senellart, P., Almeida, M. P., White, A. G., and Lobino, M.

Subjects
Quantum Physics
Abstract

A scheme for active temporal-to-spatial demultiplexing of single-photons generated by a solid-state source is introduced. The scheme scales quasi-polynomially with photon number, providing a viable technological path for routing n photons in the one temporal stream from a single emitter to n different spatial modes. The active demultiplexing is demonstrated using a state-of-the-art photon source---a quantum-dot deterministically coupled to a micropillar cavity---and a custom-built demultiplexer---a network of electro-optically reconfigurable waveguides monolithically integrated in a lithium niobate chip. The measured demultiplexer performance can enable a six-photon rate three orders of magnitude higher than the equivalent heralded SPDC source, providing a platform for intermediate quantum computation protocols., Comment: 4 pages, 2 figures

Published
2016
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33. Residual Partial Least Squares Learning: Brain Cortical Thickness Simultaneously Predicts Eight Non-pairwise-correlated Behavioural and Disease Outcomes in Alzheimer's Disease.

Author

Chén, O.Y., Vũ, D.T., Diaz, C.S., Bodelet, J.S., Phan, H., Allali, G., Nguyen, V.D., Cao, H., He, X., Müller, Y., Zhi, B., Shou, H., Zhang, H., He, W., Wang, X., Munafò, M., Trung, N.L., Nagels, G., Ryvlin, P., Pantaleo, G., Alzheimer's Disease, Neuroimaging Initiative, Chén, O.Y., Vũ, D.T., Diaz, C.S., Bodelet, J.S., Phan, H., Allali, G., Nguyen, V.D., Cao, H., He, X., Müller, Y., Zhi, B., Shou, H., Zhang, H., He, W., Wang, X., Munafò, M., Trung, N.L., Nagels, G., Ryvlin, P., Pantaleo, G., and Alzheimer's Disease, Neuroimaging Initiative

Abstract

Alzheimer's Disease (AD) is the leading cause of dementia. It results in cortical thickness changes and is associated with a decline in cognition and behaviour. Such decline affects multiple important day-to-day functions, including memory, language, orientation, judgment and problem-solving. Recent research has made important progress in identifying brain regions associated with single outcomes, such as individual AD status and general cognitive decline. The complex projection from multiple brain areas to multiple AD outcomes, however, remains poorly understood. This makes the assessment and especially the prediction of multiple AD outcomes - each of which may unveil an integral yet different aspect of the disease - challenging, particularly when some are not strongly correlated. Here, uniting residual learning, partial least squares (PLS), and predictive modelling, we develop an explainable, generalisable, and reproducible method called the Residual Partial Least Squares Learning (the re-PLS Learning) to (1) chart the pathways between large-scale multivariate brain cortical thickness data (inputs) and multivariate disease and behaviour data (outcomes); (2) simultaneously predict multiple, non-pairwise-correlated outcomes; (3) control for confounding variables (e.g., age and gender) affecting both inputs and outcomes and the pathways in-between; (4) perform longitudinal AD disease status classification and disease severity prediction. We evaluate the performance of the proposed method against a variety of alternatives on data from AD patients, subjects with mild cognitive impairment (MCI), and cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results unveil pockets of brain areas in the temporal, frontal, sensorimotor, and cingulate areas whose cortical thickness may be respectively associated with declines in different cognitive and behavioural subdomains in AD. Finally, we characterise re-PLS' geometric interpretation

Published
2024

34. On behavior of the Lannes-Zarati homomorphism

Author

Chon, Phan H. and Triet, Dong T.

Subjects
Mathematics - Algebraic Topology, 55P47, 55Q45, 55S10, 55T15
Abstract

In this paper, we construct the chain level representation in the lambda algebra of the Lannes-Zarati homomorphism for $\mathbb{F}_2$ as well as for $\tilde{H}^*B\mathbb{Z}/2$. Using this construction, we show that the sixth Lannes-Zarati homomorphism for $\mathbb{F}_2$ is trivial at all stems $t$ for $t\leq 114$. Furthermore, using this method, we also investigate the behavior of the Lannes-Zarati homomorphis for $\tilde{H}^*B\mathbb{Z}/2$ at the homological $s\leq 4$., Comment: This paper has been withdrawn by the authors because the results have already been done by others

Published
2015

35. On the mod $p$ Lannes-Zarati homomorphism

Author

Chon, Phan H. and Triet, Dong T.

Subjects
Mathematics - Algebraic Topology, Primary 55P47, 55Q45, Secondary 55S10, 55T15
Abstract

The mod $2$ Lannes-Zarati homomorphism was constructed in \cite{Lan-Zar87}, which is considered as a graded associated version of the mod $2$ Hurewicz map in the $E_2$-term of Adams spectral sequence. The map is studied by many authors such as Lannes-Zarati \cite{Lan-Zar87}, H\horn{u}ng \cite{Hung97}, \cite{Hung2001}, \cite{Hung2003}, H\horn{u}ng et. al. \cite{Hung.et.al2014}, Ch\horn{o}n-Tri\'\^et \cite{Chon.Triet2014}. In this paper, we construct an analogue $\varphi_s$ for $p$ odd, and we also investigate the behavior of this map for $s\leq 3$., Comment: This paper has been withdrawn by the authors because the results have already been done by others

Published
2015

37. Insights Into Frictional Brush Seal Hysteresis.

Author

Phan, H. M., Pekris, M. J., and Chew, J. W.

Abstract

Brush seals offer a superior sealing effectiveness compared to labyrinth seals. However, widespread use of brush seals is constrained by deleterious behaviors such as pressure-stiffening and hysteresis. For the latter, the bristles bend during the shaft incursion process and do not fully recover during the shaft retraction process. An opening gap is created, which increases seal leakage unless the pressure load drops to a certain level. In this work, analytical and numerical models based on a single bristle are proposed to capture the seal's response to shaft displacement with and without pressure loading. The models are validated using static stiffness tests at an unpressurized condition from literature. The main results show that modeling of the backing ring friction is essential to capture the bristle hang-up behavior. Shaft friction dominates at unpressurized conditions, while backing ring friction dominates at high pressure loading. An expression for shaft hang-up displacement has been derived. A sensitivity study shows that seals with shallow lay angle, short bristle length, and large bristle diameter are less prone to hang-up problems. The models developed in the present framework have been shown to qualitatively capture the pressure stiffening, hysteresis, bristle hang-up, and shaft rotation effects. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Modular coinvariants and the mod p homology of QS^k

Author

Chon, Phan H.

Subjects
Mathematics - Algebraic Topology, Primary 55P47, 55S12, Secondary 55S10, 20C20
Abstract

We use modular invariant theory to establish a complete set of relations of the mod $p$ homology of $\{QS^k\}_{k\geq0}$, for $p$ odd, as a ring object in the category of coalgebras (also known as a coalgebraic ring or a Hopf ring). We also describe the action of the mod $p$ Dyer-Lashof algebra as well as the mod $p$ Steenrod algebra on the coalgebraic ring., Comment: 26 pages; To appear in Proceedings of the London Mathematical Society

Published
2014
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41. Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization–Lancet Neurology Commission

Author

Feigin, V, Owolabi, M, Abd-Allah, F, Akinyemi, R, Bhattacharjee, N, Brainin, M, Cao, J, Caso, V, Dalton, B, Davis, A, Dempsey, R, Duprey, J, Feng, W, Ford, G, Gall, S, Gandhi, D, Good, D, Hachinski, V, Hacke, W, Hankey, G, Ishida, M, Johnson, W, Kim, J, Lavados, P, Lindsay, P, Mahal, A, Martins, S, Murray, C, Nguyen, T, Norrving, B, Olaiya, M, Olalusi, O, Pandian, J, Phan, H, Platz, T, Ranta, A, Rehman, S, Roth, G, Sebastian, I, Smith, A, Suwanwela, N, Sylaja, P, Thapa, R, Thrift, A, Uvere, E, Vollset, S, Yavagal, D, Yaria, J, Abera, S, Ibrahim, N, Liu, L, Ovbiagele, B, Piradov, M, Abanto, C, Addissie, A, Adeleye, A, Adilbekov, Y, Adilbekova, B, Adoukonou, T, Aguiar de Sousa, D, Akhmetzhanova, Z, Akpalu, A, El Alaoui-Faris, M, Ameriso, S, Andonova, S, Arsovska, A, Awoniyi, F, Bakhiet, M, Barboza, M, Basri, H, Bath, P, Bereczki, D, Beretta, S, Berkowitz, A, Bernhardt, J, Berzina, G, Bhavsar, B, Bisharyan, M, Bohara, M, Bovet, P, Budincevic, H, Cadilhac, D, Cerimagic, D, Charway-Felli, A, Chen, C, Chin, J, Christensen, H, Chwojnicki, K, Conforto, A, Correia, M, Mora Cuervo, D, Czlonkowska, A, D'Amelio, M, Danielyan, K, Davis, S, Demarin, V, Demchuk, A, Dichgans, M, Dokova, K, Donnan, G, Duran, J, Ekeng, G, Elkind, M, Endres, M, Fischer, U, Flomin, Y, Gankpe, F, Gavidia, M, Gaye Saavedra, A, Gebreyohanns, M, George, M, Gierlotka, M, Giroud, M, Gnedovskaya, E, Goncalves, I, Gongora-Rivera, F, Gunaratne, P, Hamadeh, R, Hamzat, T, Heldner, M, Ibrahim, E, Ihle-Hansen, H, Jee, S, Jiann-Shing, J, Johnston, S, Jovanovic, D, Jurjans, K, Kalani, R, Kalkonde, Y, Kamenova, S, Karaszewski, B, Kelly, P, Kiechl, S, Kondybayeva, A, Korv, J, Kozera, G, Kravchenko, M, Krespi, Y, Krishnamurthi, R, Kruja, J, Kutluk, K, Langhorne, P, Law, Z, Lebedynets, D, Lee, T, Leung, T, Liebeskind, D, Lopez-Jaramillo, P, Lotufo, P, Machline-Carrion, M, Maia, L, Malojcic, B, Markus, H, Marquez-Romero, J, Medina, M, Medukhanova, S, Mehndiratta, M, Miglane, E, Mihejeva, I, Mikulik, R, Mirrakhimov, E, Mohl, S, Munakomi, S, Murphy, S, Musa, K, Nasreldein, A, Nogueira, R, Nolte, C, Noubiap, J, Novarro-Escudero, N, Ocampo, C, O'Donnell, M, Ogun, Y, Ogunniyi, A, Oraby, M, Orken, D, Ozdemir, A, Ozturk, S, Paccot, M, Pereira, T, Peeters, A, Potpara, T, Proios, H, Rathore, F, Sacco, R, Sahathevan, R, Sandset, E, Renato Santos, I, Saposnik, G, Sarfo, F, Sargento-Freitas, J, Sharma, M, Shaw, L, Sheth, K, Shin, Y, Shobhana, A, Silva, S, Tedim Cruz, V, Thakur, K, Thapa, L, Toni, D, Topcuoglu, M, Torales, J, Towfighi, A, Truelsen, T, Tsiskaridze, A, Tulloch-Reid, M, Useche, J, Vanacker, P, Vassilopoulou, S, Vukorepa, G, Vuletic, V, Wahab, K, Wang, W, Wijeratne, T, Wojtyniak, B, Wolfe, C, Yacouba, M, Yang, J, Yifru, Y, Yock-Corrales, A, Yonemoto, N, Yperzeele, L, Zagozdzon, P, Feigin V. L., Owolabi M. O., Abd-Allah F., Akinyemi R. O., Bhattacharjee N. V., Brainin M., Cao J., Caso V., Dalton B., Davis A., Dempsey R., Duprey J., Feng W., Ford G. A., Gall S., Gandhi D., Good D. C., Hachinski V., Hacke W., Hankey G. J., Ishida M., Johnson W., Kim J., Lavados P., Lindsay P., Mahal A., Martins S., Murray C., Nguyen T. P., Norrving B., Olaiya M. T., Olalusi O. V., Pandian J., Phan H., Platz T., Ranta A., Rehman S., Roth G., Sebastian I. A., Smith A. E., Suwanwela N. C., Sylaja P. N., Thapa R., Thrift A. G., Uvere E., Vollset S. E., Yavagal D., Yaria J., Abera S. F., Akinyemi R., Dempsey R. J., Ibrahim N. M., Liu L., Ovbiagele B., Piradov M., Suwanwela N., Abanto C., Addissie A., Adeleye A. O., Adilbekov Y., Adilbekova B., Adoukonou T. A., Aguiar de Sousa D., Akhmetzhanova Z., Akpalu A., El Alaoui-Faris M., Ameriso S. F., Andonova S., Arsovska A., Awoniyi F. E., Bakhiet M., Barboza M. A., Basri H., Bath P. M., Bereczki D., Beretta S., Berkowitz A. L., Bernhardt J., Berzina G., Bhavsar B., Bisharyan M. S., Bohara M., Bovet P., Budincevic H., Cadilhac D. A., Cerimagic D., Charway-Felli A., Chen C., Chin J. H., Christensen H., Chwojnicki K., Conforto A. B., Correia M., Mora Cuervo D. L., Czlonkowska A., D'Amelio M., Danielyan K. E., Davis S., Demarin V., Demchuk A. M., Dichgans M., Dokova K., Donnan G., Duran J. C., Ekeng G., Elkind M. S., Endres M., Fischer U., Flomin Y., Gankpe F., Gavidia M., Gaye Saavedra A., Gebreyohanns M., George M., Gierlotka M., Giroud M., Gnedovskaya E. V., Goncalves I. P., Gongora-Rivera F., Gunaratne P. S., Hamadeh R. R., Hamzat T. -H. K., Heldner M. R., Ibrahim E., Ihle-Hansen H., Jee S., Jiann-Shing J., Johnston S. C., Jovanovic D., Jurjans K., Kalani R., Kalkonde Y., Kamenova S., Karaszewski B., Kelly P., Kiechl S., Kondybayeva A., Korv J., Kozera G., Kravchenko M., Krespi Y., Krishnamurthi R., Kruja J., Kutluk K., Langhorne P., Law Z. K., Lebedynets D., Lee T. -H., Leung T. W., Liebeskind D. S., Lopez-Jaramillo P., Lotufo P. A., Machline-Carrion M. J., Maia L. F., Malojcic B., Markus H. S., Marquez-Romero J. M., Medina M. T., Medukhanova S., Mehndiratta M. M., Miglane E., Mihejeva I., Mikulik R., Mirrakhimov E., Mohl S., Munakomi S., Murphy S., Musa K. I., Nasreldein A., Nogueira R. G., Nolte C. H., Noubiap J. J., Novarro-Escudero N., Ocampo C., O'Donnell M., Ogun Y., Ogunniyi A., Oraby M. I., Orken D. N., Ozdemir A. O., Ozturk S., Paccot M., Pereira T., Peeters A., Potpara T., Proios H., Rathore F. A., Sacco R. L., Sahathevan R., Sandset E. S., Renato Santos I., Saposnik G., Sarfo F. S., Sargento-Freitas J., Sharma M., Shaw L., Sheth K. N., Shin Y. -I., Shobhana A., Silva S. N., Tedim Cruz V., Thakur K., Thapa L. J., Toni D., Topcuoglu M. A., Torales J., Towfighi A., Truelsen T., Tsiskaridze A., Tulloch-Reid M., Useche J. N., Vanacker P., Vassilopoulou S., Vukorepa G., Vuletic V., Wahab K. W., Wang W., Wijeratne T., Wojtyniak B., Wolfe C., Yacouba M. N., Yang J., Yifru Y. M., Yock-Corrales A., Yonemoto N., Yperzeele L., Zagozdzon P., Feigin, V, Owolabi, M, Abd-Allah, F, Akinyemi, R, Bhattacharjee, N, Brainin, M, Cao, J, Caso, V, Dalton, B, Davis, A, Dempsey, R, Duprey, J, Feng, W, Ford, G, Gall, S, Gandhi, D, Good, D, Hachinski, V, Hacke, W, Hankey, G, Ishida, M, Johnson, W, Kim, J, Lavados, P, Lindsay, P, Mahal, A, Martins, S, Murray, C, Nguyen, T, Norrving, B, Olaiya, M, Olalusi, O, Pandian, J, Phan, H, Platz, T, Ranta, A, Rehman, S, Roth, G, Sebastian, I, Smith, A, Suwanwela, N, Sylaja, P, Thapa, R, Thrift, A, Uvere, E, Vollset, S, Yavagal, D, Yaria, J, Abera, S, Ibrahim, N, Liu, L, Ovbiagele, B, Piradov, M, Abanto, C, Addissie, A, Adeleye, A, Adilbekov, Y, Adilbekova, B, Adoukonou, T, Aguiar de Sousa, D, Akhmetzhanova, Z, Akpalu, A, El Alaoui-Faris, M, Ameriso, S, Andonova, S, Arsovska, A, Awoniyi, F, Bakhiet, M, Barboza, M, Basri, H, Bath, P, Bereczki, D, Beretta, S, Berkowitz, A, Bernhardt, J, Berzina, G, Bhavsar, B, Bisharyan, M, Bohara, M, Bovet, P, Budincevic, H, Cadilhac, D, Cerimagic, D, Charway-Felli, A, Chen, C, Chin, J, Christensen, H, Chwojnicki, K, Conforto, A, Correia, M, Mora Cuervo, D, Czlonkowska, A, D'Amelio, M, Danielyan, K, Davis, S, Demarin, V, Demchuk, A, Dichgans, M, Dokova, K, Donnan, G, Duran, J, Ekeng, G, Elkind, M, Endres, M, Fischer, U, Flomin, Y, Gankpe, F, Gavidia, M, Gaye Saavedra, A, Gebreyohanns, M, George, M, Gierlotka, M, Giroud, M, Gnedovskaya, E, Goncalves, I, Gongora-Rivera, F, Gunaratne, P, Hamadeh, R, Hamzat, T, Heldner, M, Ibrahim, E, Ihle-Hansen, H, Jee, S, Jiann-Shing, J, Johnston, S, Jovanovic, D, Jurjans, K, Kalani, R, Kalkonde, Y, Kamenova, S, Karaszewski, B, Kelly, P, Kiechl, S, Kondybayeva, A, Korv, J, Kozera, G, Kravchenko, M, Krespi, Y, Krishnamurthi, R, Kruja, J, Kutluk, K, Langhorne, P, Law, Z, Lebedynets, D, Lee, T, Leung, T, Liebeskind, D, Lopez-Jaramillo, P, Lotufo, P, Machline-Carrion, M, Maia, L, Malojcic, B, Markus, H, Marquez-Romero, J, Medina, M, Medukhanova, S, Mehndiratta, M, Miglane, E, Mihejeva, I, Mikulik, R, Mirrakhimov, E, Mohl, S, Munakomi, S, Murphy, S, Musa, K, Nasreldein, A, Nogueira, R, Nolte, C, Noubiap, J, Novarro-Escudero, N, Ocampo, C, O'Donnell, M, Ogun, Y, Ogunniyi, A, Oraby, M, Orken, D, Ozdemir, A, Ozturk, S, Paccot, M, Pereira, T, Peeters, A, Potpara, T, Proios, H, Rathore, F, Sacco, R, Sahathevan, R, Sandset, E, Renato Santos, I, Saposnik, G, Sarfo, F, Sargento-Freitas, J, Sharma, M, Shaw, L, Sheth, K, Shin, Y, Shobhana, A, Silva, S, Tedim Cruz, V, Thakur, K, Thapa, L, Toni, D, Topcuoglu, M, Torales, J, Towfighi, A, Truelsen, T, Tsiskaridze, A, Tulloch-Reid, M, Useche, J, Vanacker, P, Vassilopoulou, S, Vukorepa, G, Vuletic, V, Wahab, K, Wang, W, Wijeratne, T, Wojtyniak, B, Wolfe, C, Yacouba, M, Yang, J, Yifru, Y, Yock-Corrales, A, Yonemoto, N, Yperzeele, L, Zagozdzon, P, Feigin V. L., Owolabi M. O., Abd-Allah F., Akinyemi R. O., Bhattacharjee N. V., Brainin M., Cao J., Caso V., Dalton B., Davis A., Dempsey R., Duprey J., Feng W., Ford G. A., Gall S., Gandhi D., Good D. C., Hachinski V., Hacke W., Hankey G. J., Ishida M., Johnson W., Kim J., Lavados P., Lindsay P., Mahal A., Martins S., Murray C., Nguyen T. P., Norrving B., Olaiya M. T., Olalusi O. V., Pandian J., Phan H., Platz T., Ranta A., Rehman S., Roth G., Sebastian I. A., Smith A. E., Suwanwela N. C., Sylaja P. N., Thapa R., Thrift A. G., Uvere E., Vollset S. E., Yavagal D., Yaria J., Abera S. F., Akinyemi R., Dempsey R. J., Ibrahim N. M., Liu L., Ovbiagele B., Piradov M., Suwanwela N., Abanto C., Addissie A., Adeleye A. O., Adilbekov Y., Adilbekova B., Adoukonou T. A., Aguiar de Sousa D., Akhmetzhanova Z., Akpalu A., El Alaoui-Faris M., Ameriso S. F., Andonova S., Arsovska A., Awoniyi F. E., Bakhiet M., Barboza M. A., Basri H., Bath P. M., Bereczki D., Beretta S., Berkowitz A. L., Bernhardt J., Berzina G., Bhavsar B., Bisharyan M. S., Bohara M., Bovet P., Budincevic H., Cadilhac D. A., Cerimagic D., Charway-Felli A., Chen C., Chin J. H., Christensen H., Chwojnicki K., Conforto A. B., Correia M., Mora Cuervo D. L., Czlonkowska A., D'Amelio M., Danielyan K. E., Davis S., Demarin V., Demchuk A. M., Dichgans M., Dokova K., Donnan G., Duran J. C., Ekeng G., Elkind M. S., Endres M., Fischer U., Flomin Y., Gankpe F., Gavidia M., Gaye Saavedra A., Gebreyohanns M., George M., Gierlotka M., Giroud M., Gnedovskaya E. V., Goncalves I. P., Gongora-Rivera F., Gunaratne P. S., Hamadeh R. R., Hamzat T. -H. K., Heldner M. R., Ibrahim E., Ihle-Hansen H., Jee S., Jiann-Shing J., Johnston S. C., Jovanovic D., Jurjans K., Kalani R., Kalkonde Y., Kamenova S., Karaszewski B., Kelly P., Kiechl S., Kondybayeva A., Korv J., Kozera G., Kravchenko M., Krespi Y., Krishnamurthi R., Kruja J., Kutluk K., Langhorne P., Law Z. K., Lebedynets D., Lee T. -H., Leung T. W., Liebeskind D. S., Lopez-Jaramillo P., Lotufo P. A., Machline-Carrion M. J., Maia L. F., Malojcic B., Markus H. S., Marquez-Romero J. M., Medina M. T., Medukhanova S., Mehndiratta M. M., Miglane E., Mihejeva I., Mikulik R., Mirrakhimov E., Mohl S., Munakomi S., Murphy S., Musa K. I., Nasreldein A., Nogueira R. G., Nolte C. H., Noubiap J. J., Novarro-Escudero N., Ocampo C., O'Donnell M., Ogun Y., Ogunniyi A., Oraby M. I., Orken D. N., Ozdemir A. O., Ozturk S., Paccot M., Pereira T., Peeters A., Potpara T., Proios H., Rathore F. A., Sacco R. L., Sahathevan R., Sandset E. S., Renato Santos I., Saposnik G., Sarfo F. S., Sargento-Freitas J., Sharma M., Shaw L., Sheth K. N., Shin Y. -I., Shobhana A., Silva S. N., Tedim Cruz V., Thakur K., Thapa L. J., Toni D., Topcuoglu M. A., Torales J., Towfighi A., Truelsen T., Tsiskaridze A., Tulloch-Reid M., Useche J. N., Vanacker P., Vassilopoulou S., Vukorepa G., Vuletic V., Wahab K. W., Wang W., Wijeratne T., Wojtyniak B., Wolfe C., Yacouba M. N., Yang J., Yifru Y. M., Yock-Corrales A., Yonemoto N., Yperzeele L., and Zagozdzon P.

Published
2023

43. On Transformations between Probability and Spohnian Disbelief Functions

Author

Giang, Phan H. and Shenoy, Prakash P.

Subjects
Computer Science - Artificial Intelligence
Abstract

In this paper, we analyze the relationship between probability and Spohn's theory for representation of uncertain beliefs. Using the intuitive idea that the more probable a proposition is, the more believable it is, we study transformations from probability to Sphonian disbelief and vice-versa. The transformations described in this paper are different from those described in the literature. In particular, the former satisfies the principles of ordinal congruence while the latter does not. Such transformations between probability and Spohn's calculi can contribute to (1) a clarification of the semantics of nonprobabilistic degree of uncertain belief, and (2) to a construction of a decision theory for such calculi. In practice, the transformations will allow a meaningful combination of more than one calculus in different stages of using an expert system such as knowledge acquisition, inference, and interpretation of results., Comment: Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999)

Published
2013

44. A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs

Author

Giang, Phan H. and Shenoy, Prakash P.

Subjects
Computer Science - Artificial Intelligence
Abstract

In this paper, we formulate a qualitative "linear" utility theory for lotteries in which uncertainty is expressed qualitatively using a Spohnian disbelief function. We argue that a rational decision maker facing an uncertain decision problem in which the uncertainty is expressed qualitatively should behave so as to maximize "qualitative expected utility." Our axiomatization of the qualitative utility is similar to the axiomatization developed by von Neumann and Morgenstern for probabilistic lotteries. We compare our results with other recent results in qualitative decision making., Comment: Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)

Published
2013

45. A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory

Author

Giang, Phan H. and Shenoy, Prakash P.

Subjects
Computer Science - Artificial Intelligence
Abstract

In this paper we analyze two recent axiomatic approaches proposed by Dubois et al and by Giang and Shenoy to qualitative decision making where uncertainty is described by possibility theory. Both axiomtizations are inspired by von Neumann and Morgenstern's system of axioms for the case of probability theory. We show that our approach naturally unifies two axiomatic systems that correspond respectively to pessimistic and optimistic decision criteria proposed by Dubois et al. The simplifying unification is achieved by (i) replacing axioms that are supposed to reflect two informational attitudes (uncertainty aversion and uncertainty attraction) by an axiom that imposes order on set of standard lotteries and (ii) using a binary utility scale in which each utility level is represented by a pair of numbers., Comment: Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001)

Published
2013

47. Statistical Decisions Using Likelihood Information Without Prior Probabilities

Author

Giang, Phan H. and Shenoy, Prakash P.

Subjects
Computer Science - Artificial Intelligence
Abstract

This paper presents a decision-theoretic approach to statistical inference that satisfies the likelihood principle (LP) without using prior information. Unlike the Bayesian approach, which also satisfies LP, we do not assume knowledge of the prior distribution of the unknown parameter. With respect to information that can be obtained from an experiment, our solution is more efficient than Wald's minimax solution.However, with respect to information assumed to be known before the experiment, our solution demands less input than the Bayesian solution., Comment: Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002)

Published
2012

48. Decision Making with Partially Consonant Belief Functions

Author

Giang, Phan H. and Shenoy, Prakash P.

Subjects
Computer Science - Artificial Intelligence
Abstract

This paper studies decision making for Walley's partially consonant belief functions (pcb). In a pcb, the set of foci are partitioned. Within each partition, the foci are nested. The pcb class includes probability functions and possibility functions as extreme cases. Unlike earlier proposals for a decision theory with belief functions, we employ an axiomatic approach. We adopt an axiom system similar in spirit to von Neumann - Morgenstern's linear utility theory for a preference relation on pcb lotteries. We prove a representation theorem for this relation. Utility for a pcb lottery is a combination of linear utility for probabilistic lottery and binary utility for possibilistic lottery., Comment: Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)

Published
2012

49. Decision Making for Symbolic Probability

Author

Giang, Phan H. and Sandilya, Sathyakama

Subjects
Computer Science - Artificial Intelligence
Abstract

This paper proposes a decision theory for a symbolic generalization of probability theory (SP). Darwiche and Ginsberg [2,3] proposed SP to relax the requirement of using numbers for uncertainty while preserving desirable patterns of Bayesian reasoning. SP represents uncertainty by symbolic supports that are ordered partially rather than completely as in the case of standard probability. We show that a preference relation on acts that satisfies a number of intuitive postulates is represented by a utility function whose domain is a set of pairs of supports. We argue that a subjective interpretation is as useful and appropriate for SP as it is for numerical probability. It is useful because the subjective interpretation provides a basis for uncertainty elicitation. It is appropriate because we can provide a decision theory that explains how preference on acts is based on support comparison., Comment: Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)

Published
2012

50. A new axiomatization for likelihood gambles

Author

Giang, Phan H.

Subjects
Computer Science - Artificial Intelligence
Abstract

This paper studies a new and more general axiomatization than one presented previously for preference on likelihood gambles. Likelihood gambles describe actions in a situation where a decision maker knows multiple probabilistic models and a random sample generated from one of those models but does not know prior probability of models. This new axiom system is inspired by Jensen's axiomatization of probabilistic gambles. Our approach provides a new perspective to the role of data in decision making under ambiguity. It avoids one of the most controversial issue of Bayesian methodology namely the assumption of prior probability., Comment: Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)

Published
2012

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