884,677 research outputs found
Performance evaluation of data link protocol with adaptive frame length in satellite networks
No full textWe propose a new data link protocol with an adaptive frame length control scheme for satellite networks. The wireless communication channel in satellite networks is subject to errors that occur with time variance. The frame length of the data link layer is another important factor that affects throughput performance in dynamic channel environments. If the frame length could be chosen adaptively in response to changes in the dynamically varying satellite channel, maximum throughput could be achieved under both noisy and non-noisy error conditions. So, we propose a frame length control scheme that acts adaptively to counter errors that occur with time variance. We model the satellite channel as a two-state Markov block interference (BI) model. The estimation of the channel error status is based on the short-term bit error rate and the duty cycle of noise bursts. Numerical and computer simulation results show that the proposed scheme can achieve high throughput for both dense and diffuse burst noise channels.
Kim Kim
No full text"Knowing that most interracial and international adoptions send children of color into Western Caucasian families, the artist and activist kimura byol-nathalie lemoine wanted to present another vision of what interracial adoption could be. To realize this, the artist Kim Waldron and kimura-lemoine decided to stage photographs of everyday life and key moments of the journey of a fictitious adoption. These photographs tell the story of a Caucasian woman adopted into a Canadian family of Korean descent. By this reversal, these images, at first sight banal, become interesting and intriguing here. The Kim Kim project elaborates Kim Waldron’s previous photographic and video work that incorporates self-portraiture into fictitious situations in order to challenge aspects of identity and social conditioning. Her photographic work uses a documentary aesthetic to make fictional propositions credible. This collaboration with kimura-lemoine uses the aesthetics of family photographs, a Korean family whose surname is Kim and Kim Waldron’s birth parents to create an imaginary and improbable tale of international adoption." -- Artexte website
수소화물의 형상이 Zr-2.5 wt% Nb 압력관의 파괴인성에 미치는 영향
No full text학위논문(석사) - 한국과학기술원 : 원자력공학과, 1994.2, [ iii, 46 p. ]The effects of hydride morphology on the axial fracture toughness of cold-worked Zr - 2.5 wt\% Nb pressure tube material have been determined at room temperature and . To obtain various hydride morphology, specimens containing 50, 120 and 200 ppm hydrogen were cooled at three different rates: Water-quenching, air-cooling and furnace-cooling. The hydride morphology was observed with optical microscope. The crack extension during fracture toughness testing was measured using direct current potential drop method. Fracture toughness characterized by maximum load toughness, J-R curve and initial slope of the J-R curve was discussed with the hydride morphology. As cooling rate increased, the hydride distribution was varied from uniform and continuous to irregular and discrete, and the hydride size and interhydride spacing decreased. The influence of hydrogen concentration was to increase the hydride size and interhydride spacing. In the case of air-cooling, the variation of hydride orientation was due to residual stress produced during rapid cooling. Materials with closely spaced and large hydrides exhibited very low toughness at room temperature due to insufficient matrix material to blunt a crack travelling between the hydride platelets and little or no plastic deformation necessary to fracture large hydrides. The increase in fracture toughness of the water-quenched with 50 ppm hydrogen and tested at room temperature was due to dispersion hardening by small intragranular hydride. The upper shelf toughness level and increase in the slope of the J-R curves at were resulted from a loss of triaxial constriaint at the crack tip with increasing temperature, because of increasing plasticity corresponding to a reduction in flow stress, which made it difficult to sustain stress large enough to crack individual hydrides.한국과학기술원 : 원자력공학과
Analysis of the factors affecting decentration in photorefractive keratectomy and laser in situ keratomileusis for myopia
No full textTo evaluate the relationship between ablation zone decentration measured by corneal topography and various factors such as sex, age, order of operation, preoperative sedative prescription, ablation diameter and depth, type of procedure (photorefractive keratectomy = PRK, laser in situ keratomileusis = LASIK), and the use of a passive eye tracker, we examined the data of 80 eyes in 50 patients. The patients received PRK (43 eyes in 30 patients) or LASIK (37 eyes in 20 patients), and were followed for 3 months postoperatively. Statistical analysis of the data was performed using t-test, ANOVA and multiple regression analysis. The overall average ablation decentration from the pupil center was 0.43 +/- 0.27 mm, 0.35 +/- 0.22 mm in PRK and 0.47 +/- 0.30 mm in LASIK. Overall 91.3% of patients were decentered less than 0.75 mm and 95.0% were decentered less than 1.00 mm, while 93.9% of patients were decentered less than 0.75 mm in PRK and 88.7% were decentered less than 0.75 mm in LASIK. The most meridional displacement was toward the superonasal quadrant; 46% in PRK and 51% in LASIK. There was less decentration in males, in the 2nd-operated eye, in older age, PRK, in larger ablation diameter, and in shallower ablation depth, but these differences were not statistically significant.ope
Exploiting symmetries in POMDPs for point-based algorithms
No full textWe extend the model minimization technique for partially observable Markov decision processes (POMDPs) to handle symmetries in the joint space of states, actions, and observations. The POMDP symmetry we de-ne in this paper cannot be handled by the model minimization techniques previously published in the literature.
We formulate the problem of nding the symmetries as a graph automorphism (GA) problem, and although not yet known to be tractable, we experimentally show that the sparseness of the graph representing the POMDP allows us to quickly nd symmetries. We show how the symmetries in POMDPs can be exploited for speeding up point-based algorithms. We experimentally demonstrate the effectiveness of our approach
Estimation methods for efficiency of additive in removing impurity in hydrometallurgical purification process
No full textThe purification process removes impurity in the solution through a chemical reaction with an additive. The amount of additive to be fed into the process depends on the estimate of its efficiency in removing the impurity. We propose the Box-Jenkins method in time series models for the estimation of efficiency. Through simulation, the performance and the robustness of the method are analyzed under various situations including an actual case and compared with those of existing regression and adaptive methods. The case study determines the amount of zinc dust additive that reacts with copper impurity in a hydrometallurgical zinc purification process. In this study, the Box-Jenkins method has been found superior, in both performance and robustness, to the other existing methods.
Dual Correction Strategy for Ranking Distillation in Top-N Recommender System
No full textKnowledge Distillation (KD), which transfers the knowledge of a well-trained large model (teacher) to a small model (student), has become an important area of research for practical deployment of recommender systems. Recently, Relaxed Ranking Distillation (RRD) has shown that distilling the ranking information in the recommendation list significantly improves the performance. However, the method still has limitations in that 1) it does not fully utilize the prediction errors of the student model, which makes the training not fully efficient, and 2) it only distills the user-side ranking information, which provides an insufficient view under the sparse implicit feedback. This paper presents Dual Correction strategy for Distillation (DCD), which transfers the ranking information from the teacher model to the student model in a more efficient manner. Most importantly, DCD uses the discrepancy between the teacher model and the student model predictions to decide which knowledge to be distilled. By doing so, DCD essentially provides the learning guidance tailored to "correcting"what the student model has failed to accurately predict. This process is applied for transferring the ranking information from the user-side as well as the item-side to address sparse implicit user feedback. Our experiments show that the proposed method outperforms the state-of-the-art baselines, and ablation studies validate the effectiveness of each component
Inverse Reinforcement Learning in Partially Observable Environments
No full textInverse reinforcement learning (IRL) is the problem of recovering the underlying reward function from the behavior of an expert. Most of the existing IRL algorithms assume that the environment is modeled as a Markov decision process (MDP), although it is desirable to handle partially observable settings in order to handle more realistic scenarios. In this paper, we present IRL algorithms for partially observable environments that can be modeled as a partially observable Markov decision process (POMDP). We deal with two cases according to the representation of the given expert's behavior, namely the case in which the expert's policy is explicitly given, and the case in which the expert's trajectories are available instead. The IRL in POMDPs poses a greater challenge than in MDPs since it is not only ill-posed due to the nature of IRL, but also computationally intractable due to the hardness in solving POMDPs. To overcome these obstacles, we present algorithms that exploit some of the classical results from the POMDP literature. Experimental results on several benchmark POMDP domains show that our work is useful for partially observable settings.
How to make a machine think in art psychotherapy: An expert systems reasoning process
No full textIn making decisions, a human being considers all of the factors concerning the situation in a comprehensive and intuitive manner by using all of his or her experience and knowledge. Due to the inherent nature of human decision making, the reasoning process from confronting the problem to finding a solution is too complicated to be explicitly represented. In this paper, we implement an expert system for the diagnosis process of art psychotherapists. We model the complicated mechanism of this process as several procedural stages and feedbacks. We devise a suitable method of maintaining consistency among numerous decisions derived from the system. We also provide the system with a learning facility to improve its intelligence. Finally, we demonstrate the usefulness and suitability of the proposed system through a case study. (c) 2006 Elsevier Inc. All rights reserved.
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