ELECTRE I Method Using Hesitant Linguistic Term Sets: An Application to Supplier Selection

Decision making is a common process in human activities. Every person or organization needs to make decisions besides dealing with uncertainty and vagueness associated with human cognition. The theory of fuzzy logic provides a mathematical base to model the uncertainities. Hesitant fuzzy linguistic term set (HFLTS) creates an appropriate method to deal with uncertainty in decision making. Managerial decision making generally implies that decision making process conducts multiple and conflicting criteria. Multi criteria decision analysis (MCDA) is a widely applied decision making method. Outranking methods are one type of MCDA methods which facilitate the decision making process through comparing binary relations in order to rank the alternatives. Elimination et Choix Traduisant la Réalité (ELECTRE), means elimination and choice that translates reality, is an outranking method. In this paper, an extended version of ELECTRE I method using HFLTS is proposed. Finally, a real case problem is provided to illustrate the HFLTS-ELECTRE I method

Application of Artificial Neural Networks (ANNs) for Weight Predictions of Blue Crabs (Callinectes sapidus RATHBUN, 1896) Using Predictor Variables

An evaluation of the performance of artificial networks (ANNs) to estimate the weights of blue crab (Callinectes sapidus) catches in Yumurtalık Cove (Iskenderun Bay) that uses measured predictor variables is presented, including carapace width (CW), sex (male, female and female with eggs), and sampling month. Blue crabs (n=410) were collected each month between 15 September 1996 and 15 May 1998. Sex, CW, and sampling month were used and specified in the input layer of the network. The weights of the blue crabs were utilized in the output layer of the network. A multi-layer perception architecture model was used and was calibrated with the Levenberg Marguardt (LM) algorithm. Finally, the values were determined by the ANN model using the actual data. The mean square error (MSE) was measured as 3.3, and the best results had a correlation coefficient (R) of 0.93. We compared the predictive capacity of the general linear model (GLM) versus the Artificial Neural Network model (ANN) for the estimation of the weights of blue crabs from independent field data. The results indicated the higher performance capacity of the ANN to predict weights compared to the GLM (R=0.97 vs. R=0.95, raw variable) when evaluated against independent field data

Investigating Miniature Electrodynamic Tethers and Interaction with the Low Earth Orbit Plasma

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106509/1/AIAA2013-5391.pd

Power density of a bare electrodynamic tether generator

The maximum performance of bare electrodynamic tethers as power generating systems under OML-theory is analyzed. Results show that best performance in terms of power density is achieved by designing the tether in such a way to increase ohmic impedance with respect to plasma contact impedance, hence favoring longer and thinner tethers. In such condition the corresponding optimal value of the load impedance is seen to approach the ohmic impedance of the conducting tether. At the other extreme, when plasma contact impedance dominates (which is not optimal but can be relevant for some applications) optimum power generation is found by matching the load impedance with an effective tether-plasma contact impedance whose expression is derived

Implementation of a Space Communications Cognitive Engine

Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC)

LSP1 is an endothelial gatekeeper of leukocyte transendothelial migration

Leukocyte-specific protein 1 (LSP1), an F-actin binding protein and a major downstream substrate of p38 mitogen-activated protein kinase as well as protein kinase C, has been reported to be important in leukocyte chemotaxis. Although its distribution has been thought to be restricted to leukocytes, herein we report that LSP1 is expressed in endothelium and is essential to permit neutrophil emigration. Using intravital microscopy to directly visualize leukocyte rolling, adhesion, and emigration in postcapillary venules in LSP1-deficient (Lsp1−/−) mice, we found that LSP1 deficiency inhibits neutrophil extravasation in response to various cytokines (tumor necrosis factor-α and interleukin-1β) and to neutrophil chemokine keratinocyte-derived chemokine in vivo. LSP1 deficiency did not affect leukocyte rolling or adhesion. Generation of Lsp1−/− chimeric mice using bone marrow transplantation revealed that in mice with Lsp1−/− endothelial cells and wild-type leukocytes, neutrophil transendothelial migration out of postcapillary venules is markedly restricted. In contrast, Lsp1−/− neutrophils in wild-type mice were able to extravasate normally. Consistent with altered endothelial function was a reduction in vascular permeability to histamine in Lsp1−/− animals. Western blot analysis and immunofluorescence microscopy examination confirmed the presence of LSP1 in wild-type but not in Lsp1−/− mouse microvascular endothelial cells. Cultured human endothelial cells also stained positive for LSP1. Our results suggest that LSP1 expressed in endothelium regulates neutrophil transendothelial migration

Enhancing Mass Transport in Redox Flow Batteries by Tailoring Flow Field and Electrode Design

In this study, we investigate the mass transport effects of various flow field designs paired with raw and laser perforated carbon paper electrodes in redox flow batteries (RFBs). Previously, we observed significant increases in peak power density and limiting current density when perforated electrodes were used in conjunction with the serpentine flow field. In this work, we expand on our earlier findings by investigating various flow field designs (e.g., serpentine, parallel, interdigitated, and spiral), and continuously measuring pressure drop in each configuration. In all cases, these perforated electrodes are found to be associated with a reduction in pressure drop from 4% to 18%. Flow field designs with a continuous path from inlet to outlet (i.e., serpentine, parallel, spiral) are observed to exhibit improved performance (up to 31%) when paired with perforated electrodes, as a result of more facile reactant delivery and resulting greater utilization of the available surface area. Conversely, flow fields with discontinuous paths which force electrolyte to travel through the electrode (e.g. interdigitated), are adversely affected by the creation of perforations due to the high permeability 'channels' in the electrode. These results demonstrate that mass transport can significantly limit the performance of RFBs with carbon paper electrodes. (C) 2015 The Electrochemical Society. All rights reserved

Spatio-Temporal Fusion Networks for Action Recognition

The video based CNN works have focused on effective ways to fuse appearance and motion networks, but they typically lack utilizing temporal information over video frames. In this work, we present a novel spatio-temporal fusion network (STFN) that integrates temporal dynamics of appearance and motion information from entire videos. The captured temporal dynamic information is then aggregated for a better video level representation and learned via end-to-end training. The spatio-temporal fusion network consists of two set of Residual Inception blocks that extract temporal dynamics and a fusion connection for appearance and motion features. The benefits of STFN are: (a) it captures local and global temporal dynamics of complementary data to learn video-wide information; and (b) it is applicable to any network for video classification to boost performance. We explore a variety of design choices for STFN and verify how the network performance is varied with the ablation studies. We perform experiments on two challenging human activity datasets, UCF101 and HMDB51, and achieve the state-of-the-art results with the best network

Rate-distortion optimized layered stereoscopic video streaming with raptor codes

A near optimal streaming system for stereoscopic video is proposed. Initially, the stereoscopic video is separated into three layers and the approximate analytical model of the Rate-Distortion (RD) curve of each layer is calculated from sufficient number of rate and distortion samples. The analytical modeling includes the interdependency of the defined layers. Then, the analytical models are used to derive the optimal source encoding rates for a given channel bandwidth. The distortion in the quality of the stereoscopic video that is caused by losing a NAL unit from the defined layers is estimated to minimize the average distortion of a single NAL unit loss. The minimization is performed over protection rates allocated to each layer. Raptor codes are utilized as the error protection scheme due to their novelty and suitability in video transmission. The layers are protected unequally using Raptor codes according to the parity ratios allocated to the layers. Comparison of the defined scheme with two other protection allocation schemes is provided via simulations to observe the quality of stereoscopic video. ©2007 IEEE