scispace - formally typeset
Search or ask a question
Institution

Military Academy

About: Military Academy is a based out in . It is known for research contribution in the topics: Population & Context (language use). The organization has 2478 authors who have published 3003 publications receiving 33188 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the authors investigated the nonlinear buckling and postbuckling of functionally graded porous circular cylindrical shells reinforced by orthogonal stiffeners resting on Pasternak elastic foundations in thermal environment and under torsional load by an analytical approach.
Abstract: This paper investigates the nonlinear buckling and postbuckling of functionally graded porous circular cylindrical shells reinforced by orthogonal stiffeners resting on Pasternak elastic foundations in thermal environment and under torsional load by an analytical approach. Shells are reinforced by closely spaced stringers and rings in which material properties of the shell and the stiffeners are assumed to be continuously graded in the thickness direction. Basing on the classical shell theory with von Karman geometrical nonlinearity and smeared stiffeners technique, the governing equations are derived. Using the Galerkin method with the three-term solution of deflection, the closed form to find critical load and post-buckling response are obtained. The effects of porosity coefficient, material, temperature, dimensional parameters, stiffener and foundation are analyzed.

34 citations

Journal ArticleDOI
TL;DR: In this paper, a hybrid numerical algorithm of the Laplace transform technique and finite-difference method with a sequential-in-time concept and the least-squares scheme is proposed to predict the unknown surface temperature of two-sided boundary conditions for two-dimensional inverse heat conduction problems.

34 citations

Journal ArticleDOI
01 Nov 2006-Pain
TL;DR: Results indicate that anti‐hyperalgesic effects of carbamazepine and oxcarbazepine are, at least partially, mediated by activation of adrenergic &agr;2‐receptors.
Abstract: In this study, the effects of yohimbine (α2-adrenoceptor antagonist) and clonidine (α2-adrenoceptor agonist) on anti-hyperalgesia induced by carbamazepine and oxcarbazepine in a rat model of inflammatory pain were investigated. Carbamazepine (10–40 mg/kg; i.p.) and oxcarbazepine (40–160 mg/kg; i.p.) caused a significant dose-dependent reduction of the paw inflammatory hyperalgesia induced by concanavalin A (Con A, intraplantarly) in a paw pressure test in rats. Yohimbine (1–3 mg/kg; i.p.) significantly depressed the anti-hyperalgesic effects of carbamazepine and oxcarbazepine, in a dose- and time-dependent manner. Both drug mixtures (carbamazepine–clonidine and oxcarbazepine–clonidine) administered in fixed-dose fractions of the ED50 (1/2, 1/4 and 1/8) caused significant and dose-dependent reduction of the hyperalgesia induced by Con A. Isobolographic analysis revealed a significant synergistic (supra-additive) anti-hyperalgesic effect of both combinations tested. These results indicate that anti-hyperalgesic effects of carbamazepine and oxcarbazepine are, at least partially, mediated by activation of adrenergic α2-receptors. In addition, synergistic interaction for anti-hyperalgesia between carbamazepine and clonidine, as well as oxcarbazepine and clonidine in a model of inflammatory hyperalgesia, was demonstrated.

34 citations

Book ChapterDOI
18 Apr 2018
TL;DR: This work focuses on explanations with quantitative expressions of uncertainty and experiment with common design factors of a robot: its embodiment and its communication strategy in case of an error, which help identify valuable properties and dynamics of the human-robot trust relationship.
Abstract: Trust is critical to the success of human-robot interaction. Research has shown that people will more accurately trust a robot if they have an accurate understanding of its decision-making process. The Partially Observable Markov Decision Process (POMDP) is one such decision-making process, but its quantitative reasoning is typically opaque to people. This lack of transparency is exacerbated when a robot can learn, making its decision making better, but also less predictable. Recent research has shown promise in calibrating human-robot trust by automatically generating explanations of POMDP-based decisions. In this work, we explore factors that can potentially interact with such explanations in influencing human decision-making in human-robot teams. We focus on explanations with quantitative expressions of uncertainty and experiment with common design factors of a robot: its embodiment and its communication strategy in case of an error. Results help us identify valuable properties and dynamics of the human-robot trust relationship.

34 citations


Authors

Showing all 2478 results

NameH-indexPapersCitations
Kamil Kuca55102916708
Antoni Rogalski4728611516
Ufuk Gündüz442066560
George P. Patrinos433538785
Ching-Hsue Cheng422098222
Saad M. Alshehri422806179
Roman Dabrowski384696415
Daniel Jun372875505
Susheel Kalia361056984
Dragan Pamučar361944519
Turgay Celik355085417
Janice D. Yoder33813486
Miodrag Čolić322123894
T. C. T. Ting321219662
Manuela Tvaronavičienė311532832
Network Information
Related Institutions (5)
University at Buffalo
63.8K papers, 2.2M citations

80% related

University of Connecticut
81.2K papers, 2.9M citations

80% related

City University of New York
56.5K papers, 1.7M citations

80% related

City University of Hong Kong
60.1K papers, 1.7M citations

79% related

Ben-Gurion University of the Negev
60.8K papers, 1.4M citations

79% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20225
2021228
2020263
2019228
2018186
2017243