Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D.

PubMed

Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

2014-05-01

A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent.

Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D

PubMed Central

Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

2014-01-01

A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent. PMID:25834481

Retrenchment in Education: Hierarchical Decision Models for Instructional Program Termination, District Consolidations and School Closures.

ERIC Educational Resources Information Center

Wholeben, Brent Edward

A number of key issues facing elementary, secondary, and postsecondary educational administrators during retrenchment require a hierarchical decision-modeling approach. This paper identifies and discusses the use of a hierarchical multiple-alternatives modeling formulation (computer-based) that compares and evaluates a group of solution…

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model

PubMed Central

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

Enhancing cycling durability of Li-ion batteries with hierarchical structured silicon-graphene hybrid anodes.

PubMed

Loveridge, Melanie J; Lain, Michael J; Huang, Qianye; Wan, Chaoying; Roberts, Alexander J; Pappas, George S; Bhagat, Rohit

2016-11-09

Hybrid anode materials consisting of micro-sized silicon (Si) particles interconnected with few-layer graphene (FLG) nanoplatelets and sodium-neutralized poly(acrylic acid) as a binder were evaluated for Li-ion batteries. The hybrid film has demonstrated a reversible discharge capacity of ∼1800 mA h g -1 with a capacity retention of 97% after 200 cycles. The superior electrochemical properties of the hybrid anodes are attributed to a durable, hierarchical conductive network formed between Si particles and the multi-scale carbon additives, with enhanced cohesion by the functional polymer binder. Furthermore, improved solid electrolyte interphase (SEI) stability is achieved from the electrolyte additives, due to the formation of a kinetically stable film on the surface of the Si.

3D hierarchical architecture based on 1D TiO2 nanorod and 2D MnO2 nanoflake for high performance supercapacitor electrode

NASA Astrophysics Data System (ADS)

Thakur, S.; Maiti, S.; Acharya, A.; Paul, T.; Besra, N.; Sarkar, S.; Chattopadhyay, K. K.

2018-04-01

Possibility of integration of manifold functionalities coupled with novel interface phenomenon generation in geometrically intricate hierarchical nanoform has made them greatly pertinent from both research and technological point of view. Here, oxide based hybrid has been realized by integrating 1D TiO2 nanorod with 2D MnO2 nanoflake via low temperature chemical route. Meticulous tunability over the hierarchical morphology was achieved by subtle variation of reaction parameter which in turn created difference in MnO2 growth over TiO2. Morphological features of the samples were examined by FESEM and TEM. Hybrid samples exhibited high electrochemical performance than pristine TiO2 nanorods. Registered electrochemical performance from TiO2-MnO2 hybrid was found to be ˜1024F/g at a current density of 0.66A/g which is ˜100 fold than TiO2 at same current density. Such enhanced performance is accounted from higher surface area and electrical conductivity of the hybrid.

Models for Rational Decision Making. Analysis of Literature and Selected Bibliography. Analysis and Bibliography Series, No. 6.

ERIC Educational Resources Information Center

Hall, John S.

This review analyzes the trend in educational decision making to replace hierarchical authority structures with more rational models for decision making drawn from management science. Emphasis is also placed on alternatives to a hierarchical decision-making model, including governing models, union models, and influence models. A 54-item…

Hierarchically porous silicon–carbon–nitrogen hybrid materials towards highly efficient and selective adsorption of organic dyes

PubMed Central

Meng, Lala; Zhang, Xiaofei; Tang, Yusheng; Su, Kehe; Kong, Jie

2015-01-01

The hierarchically macro/micro-porous silicon–carbon–nitrogen (Si–C–N) hybrid material was presented with novel functionalities of totally selective and highly efficient adsorption for organic dyes. The hybrid material was conveniently generated by the pyrolysis of commercial polysilazane precursors using polydivinylbenzene microspheres as sacrificial templates. Owing to the Van der Waals force between sp2-hybridized carbon domains and triphenyl structure of dyes, and electrostatic interaction between dyes and Si-C-N matrix, it exhibites high adsorption capacity and good regeneration and recycling ability for the dyes with triphenyl structure, such as methyl blue (MB), acid fuchsin (AF), basic fuchsin and malachite green. The adsorption process is determined by both surface adsorption and intraparticle diffusion. According to the Langmuir model, the adsorption capacity is 1327.7 mg·g−1 and 1084.5 mg·g−1 for MB and AF, respectively, which is much higher than that of many other adsorbents. On the contrary, the hybrid materials do not adsorb the dyes with azo benzene structures, such as methyl orange, methyl red and congro red. Thus, the hierarchically porous Si–C–N hybrid material from a facile and low cost polymer-derived strategy provides a new perspective and possesses a significant potential in the treatment of wastewater with complex organic pollutants. PMID:25604334

Model-based hierarchical reinforcement learning and human action control

PubMed Central

Botvinick, Matthew; Weinstein, Ari

2014-01-01

Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour. PMID:25267822

Hierarchical hybrid film of MnO2 nanoparticles/multi-walled fullerene nanotubes-graphene for highly selective sensing of hydrogen peroxide.

PubMed

Pan, Yang; Hou, Zhaohui; Yi, Wei; Zhu, Wei; Zeng, Fanyan; Liu, You-Nian

2015-08-15

Hierarchical hybrid films of MnO2 nanoparticles/multi-walled fullerene nanotubes-graphene (MNPs/MWFNTs-GS) have been prepared via a simple wet-chemical method. For this purpose, MWFNTs (~300nm in length) are fabricated from tailoring multi-walled carbon nanotubes (MWCNTs), and then inserted into GS to pile up into a hierarchical hybrid film with the in situ formative MNPs. Scanning electron microscope, transmission electron microscope and X-ray diffraction are used to confirm the morphology and structure of the as-obtained film. The electrochemical studies reveal that MNPs/MWFNTs-GS exhibit significantly enhanced electrocatalytic activity compared with MNPs/GS, and show a rapid response to H2O2 over a wide linear range of 2.0μM-8.44mM with a high sensitivity of 206.3μA mM(-1)cm(-2) and an excellent selectivity. These favorable electrochemical detection properties may be mainly attributed to the introduction of MWFNTs, which helps to promote the electron/ion transport between MNPs and GS and form the hierarchical film structure. Copyright © 2015 Elsevier B.V. All rights reserved.

Hierarchical assembly of viral nanotemplates with encoded microparticles via nucleic acid hybridization.

PubMed

Tan, Wui Siew; Lewis, Christina L; Horelik, Nicholas E; Pregibon, Daniel C; Doyle, Patrick S; Yi, Hyunmin

2008-11-04

We demonstrate hierarchical assembly of tobacco mosaic virus (TMV)-based nanotemplates with hydrogel-based encoded microparticles via nucleic acid hybridization. TMV nanotemplates possess a highly defined structure and a genetically engineered high density thiol functionality. The encoded microparticles are produced in a high throughput microfluidic device via stop-flow lithography (SFL) and consist of spatially discrete regions containing encoded identity information, an internal control, and capture DNAs. For the hybridization-based assembly, partially disassembled TMVs were programmed with linker DNAs that contain sequences complementary to both the virus 5' end and a selected capture DNA. Fluorescence microscopy, atomic force microscopy (AFM), and confocal microscopy results clearly indicate facile assembly of TMV nanotemplates onto microparticles with high spatial and sequence selectivity. We anticipate that our hybridization-based assembly strategy could be employed to create multifunctional viral-synthetic hybrid materials in a rapid and high-throughput manner. Additionally, we believe that these viral-synthetic hybrid microparticles may find broad applications in high capacity, multiplexed target sensing.

Serial, parallel and hierarchical decision making in primates

PubMed Central

Zylberberg, Ariel; Lorteije, Jeannette AM; Ouellette, Brian G; De Zeeuw, Chris I; Sigman, Mariano; Roelfsema, Pieter

2017-01-01

The study of decision-making has mainly focused on isolated decisions where choices are associated with motor actions. However, problem-solving often involves considering a hierarchy of sub-decisions. In a recent study (Lorteije et al. 2015), we reported behavioral and neuronal evidence for hierarchical decision making in a task with a small decision tree. We observed a first phase of parallel evidence integration for multiple sub-decisions, followed by a phase in which the overall strategy formed. It has been suggested that a 'flat' competition between the ultimate motor actions might also explain these results. A reanalysis of the data does not support the critical predictions of flat models. We also examined the time-course of decision making in other, related tasks and report conditions where evidence integration for successive decisions is decoupled, which excludes flat models. We conclude that the flexibility of decision-making implies that the strategies are genuinely hierarchical. DOI: http://dx.doi.org/10.7554/eLife.17331.001 PMID:28648172

Hierarchical heterostructure of MoS2 flake anchored on TiO2 sphere for supercapacitor application

NASA Astrophysics Data System (ADS)

Chanda, K.; Thakur, S.; Maiti, S.; Acharya, A.; Paul, T.; Besra, N.; Sarkar, S.; Das, A.; Sardar, K.; Chattopadhyay, K. K.

2018-05-01

Hierarchical architectures realized via rational coupling of several components not only boast synergy driven raised functionality compared to their structural constituents also exhibit noble interface phenomena, thus made them significantly pertinent from research and technological point of view. Here in, geometrically intricate hierarchical nanoform constituting MoS2 nanoflakes anchored on TiO2 sphere was realized via two steps hydrothermal protocol. Initially TiO2 sphere was synthesized using titanium isopropoxide assisted hydrothermal route followed by which the sphere was used as scaffold for secondary growth of MoS2. As synthesized hybrid sample displayed much improved electrochemical behavior than pristine TiO2 sphere. Assessed value of specific capacitance for the hybrid is found to 152.22 F/g at current density of 0.1A/g which is 30 fold than TiO2 sphere. This electrochemical performance enhancement can be accredited to high surface area of the hybrid sample.

A hierarchical-multiobjective framework for risk management

NASA Technical Reports Server (NTRS)

Haimes, Yacov Y.; Li, Duan

1991-01-01

A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.

A Hybrid P2P Overlay Network for Non-strictly Hierarchically Categorized Content

NASA Astrophysics Data System (ADS)

Wan, Yi; Asaka, Takuya; Takahashi, Tatsuro

In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

Supramolecular Engineering of Hierarchically Self-Assembled, Bioinspired, Cholesteric Nanocomposites Formed by Cellulose Nanocrystals and Polymers.

PubMed

Zhu, Baolei; Merindol, Remi; Benitez, Alejandro J; Wang, Baochun; Walther, Andreas

2016-05-04

Natural composites are hierarchically structured by combination of ordered colloidal and molecular length scales. They inspire future, biomimetic, and lightweight nanocomposites, in which extraordinary mechanical properties are in reach by understanding and mastering hierarchical structure formation as tools to engineer multiscale deformation mechanisms. Here we describe a hierarchically self-assembled, cholesteric nanocomposite with well-defined colloid-based helical structure and supramolecular hydrogen bonds engineered on the molecular level in the polymer matrix. We use reversible addition-fragmentation transfer polymerization to synthesize well-defined hydrophilic, nonionic polymers with a varying functionalization density of 4-fold hydrogen-bonding ureidopyrimidinone (UPy) motifs. We show that these copolymers can be coassembled with cellulose nanocrystals (CNC), a sustainable, stiff, rod-like reinforcement, to give ordered cholesteric phases with characteristic photonic stop bands. The dimensions of the helical pitch are controlled by the ratio of polymer/CNC, confirming a smooth integration into the colloidal structure. With respect to the effect of the supramolecular motifs, we demonstrate that those regulate the swelling when exposing the biomimetic hybrids to water, and they allow engineering the photonic response. Moreover, the amount of hydrogen bonds and the polymer fraction are decisive in defining the mechanical properties. An Ashby plot comparing previous ordered CNC-based nanocomposites with our new hierarchical ones reveals that molecular engineering allows us to span an unprecedented mechanical property range from highest inelastic deformation (strain up to ∼13%) to highest stiffness (E ∼ 15 GPa) and combinations of both. We envisage that further rational design of the molecular interactions will provide efficient tools for enhancing the multifunctional property profiles of such bioinspired nanocomposites.

Novel hierarchical tantalum oxide-PDMS hybrid coating for medical implants: One pot synthesis, characterization and modulation of fibroblast proliferation.

PubMed

Tran, Phong A; Fox, Kate; Tran, Nhiem

2017-01-01

Surface properties such as morphology, roughness and charge density have a strong influence on the interaction of biomaterials and cells. Hierarchical materials with a combination of micron/submicron and nanoscale features for coating of medical implants could therefore have significant potential to modulate cellular responses and eventually improve the performance of the implants. In this study, we report a simple, one pot wet chemistry preparation of a hybrid coating system with hierarchical surface structures consisting of polydimethylsiloxane (PDMS) and tantalum oxide. Medical grade, amine functional PDMS was mixed with tantalum ethoxide which subsequently formed Ta 2 O 5 in situ through hydrolysis and condensation during coating process. The coatings were characterized by SEM, EDS, XPS, confocal scanning microscopy, contact angle measurement and in vitro cell culture. Varying PDMS and tantalum ethoxide ratios resulted in coatings of different surface textures ranging from smooth to submicro- and nano-structured. Strikingly, hierarchical surfaces containing both microscale (1-1.5μm) and nanoscale (86-163nm) particles were found on coatings synthesized with 20% and 40% (v/v) tantalum ethoxide. The coatings were similar in term of hydrophobicity but showed different surface roughness and chemical composition. Importantly, higher cell proliferation was observed on hybrid surface with hierarchical structures compared to pure PDMS or pure tantalum oxide. The coating process is simple, versatile, carried out under ambient condition and requires no special equipment. Copyright © 2016 Elsevier Inc. All rights reserved.

Hierarchical semi-numeric method for pairwise fuzzy group decision making.

PubMed

Marimin, M; Umano, M; Hatono, I; Tamura, H

2002-01-01

Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.

Synergistic Enhancement of Microwave Absorption Using Hybridized Polyaniline@helical CNTs with Dual Chirality.

PubMed

Tian, Xin; Meng, Fanbin; Meng, Fanchen; Chen, Xiangnan; Guo, Yifan; Wang, Ying; Zhu, Wenjun; Zhou, Zuowan

2017-05-10

In this study, we designed a dual-chirality hierarchical structure to achieve a synergistically enhanced effect in microwave absorption via the hybridization of nanomaterials. Herein, polyaniline (PANi) nanorods with tunable chirality are grown on helical carbon nanotubes (HCNTs), a typical nanoscale chiral structure, through in situ polymerization. The experimental results show that the hierarchical hybrids (PANi@HCNTs) exhibit distinctly dual chirality and a significant enhancement in electromagnetic (EM) losses compared to those of either pure PANi or HCNTs. The maximum reflection loss of the as-prepared hybrids can reach -32.5 dB at 8.9 GHz. Further analysis demonstrates that combinations of chiral acid-doped PANi and coiled HCNTs with molecular and nanoscale chirality lead to synergistic effects resulting from the dual chirality. The so-called cross-polarization may result in additional interactions with induced EM waves in addition to multiscaled relaxations from functional groups and interfacial polarizations, which can benefit EM absorption.

Multi-Objective and Multidisciplinary Design Optimisation (MDO) of UAV Systems using Hierarchical Asynchronous Parallel Evolutionary Algorithms

DTIC Science & Technology

2007-09-17

been proposed; these include a combination of variable fidelity models, parallelisation strategies and hybridisation techniques (Coello, Veldhuizen et...Coello et al (Coello, Veldhuizen et al. 2002). 4.4.2 HIERARCHICAL POPULATION TOPOLOGY A hierarchical population topology, when integrated into...to hybrid parallel Multi-Objective Evolutionary Algorithms (pMOEA) (Cantu-Paz 2000; Veldhuizen , Zydallis et al. 2003); it uses a master slave

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization.

PubMed

Brand, John; Johnson, Aaron P

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization

PubMed Central

Brand, John; Johnson, Aaron P.

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675

Elaboration and properties of hierarchically structured optical thin films of MIL-101(Cr).

PubMed

Demessence, Aude; Horcajada, Patricia; Serre, Christian; Boissière, Cédric; Grosso, David; Sanchez, Clément; Férey, Gérard

2009-12-14

Stable nanoparticles dispersions of the porous hybrid MIL-101(Cr) allow dip-coating of high quality optical thin films with dual hierarchical porous structure. Moreover, for the first time, mechanical and sorption properties of mesoporous MOFs based thin films are evaluated.

Hierarchical Task Analysis and Training Decisions.

ERIC Educational Resources Information Center

Shepherd, A.

1985-01-01

Hierarchical task analysis (HTA), which requires description of a task in terms of a hierarchy of operations and plans, is reviewed and examined as a basis for making training decisions. Benefits of HTA in terms of economy of analysis and as a means of accounting for complex performance are outlined. (Author/MBR)

A Hierarchical Analysis of Bridge Decision Makers; the Role of New Technology Adoption in the Timber Bridge Market: Special Project Fiscal Year 1992

DOT National Transportation Integrated Search

1995-08-01

Bridge design engineers and local highway officials make bridge replacement decsions across the U.S. The Analytical Hierarchical Process was used to characterize the bridge material selection decisions of these individuals. State Departments of Trans...

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina

2018-05-23

Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.

A robust H∞ control-based hierarchical mode transition control system for plug-in hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Yang, Chao; Jiao, Xiaohong; Li, Liang; Zhang, Yuanbo; Chen, Zheng

2018-01-01

To realize a fast and smooth operating mode transition process from electric driving mode to engine-on driving mode, this paper presents a novel robust hierarchical mode transition control method for a plug-in hybrid electric bus (PHEB) with pre-transmission parallel hybrid powertrain. Firstly, the mode transition process is divided into five stages to clearly describe the powertrain dynamics. Based on the dynamics models of powertrain and clutch actuating mechanism, a hierarchical control structure including two robust H∞ controllers in both upper layer and lower layer is proposed. In upper layer, the demand clutch torque can be calculated by a robust H∞controller considering the clutch engaging time and the vehicle jerk. While in lower layer a robust tracking controller with L2-gain is designed to perform the accurate position tracking control, especially when the parameters uncertainties and external disturbance occur in the clutch actuating mechanism. Simulation and hardware-in-the-loop (HIL) test are carried out in a traditional driving condition of PHEB. Results show that the proposed hierarchical control approach can obtain the good control performance: mode transition time is greatly reduced with the acceptable jerk. Meanwhile, the designed control system shows the obvious robustness with the uncertain parameters and disturbance. Therefore, the proposed approach may offer a theoretical reference for the actual vehicle controller.

MOF-5 decorated hierarchical ZnO nanorod arrays and its photoluminescence

NASA Astrophysics Data System (ADS)

Zhang, Yinmin; Lan, Ding; Wang, Yuren; Cao, He; Jiang, Heng

2011-04-01

The strategy to manipulate nanoscale materials into well-organized hierarchical architectures is very important to both material synthesis and nanodevice applications. Here, nanoscale MOF-5 crystallites were successfully fabricated onto ordered hierarchical ZnO arrays based on aqueous chemical synthesis and molecule self-assembly technology guided room temperature diffusion method, which has the advantages of energy saving and simple operation. The structures and morphologies of the samples were performed by X-ray powder diffraction and field emission scanning electronic microscopy. The MOF-5 crystallites have good quality and bind well to the hexagonal-patterned ZnO arrays. The photoluminescence spectrum shows that the emission of hybrid MOF-5-ZnO films displays a blue shift in green emission and intensity reduction in UV emission. This ordered hybrid semiconductor material is expected to exploit the great potentiality in sensors, micro/nanodevices, and screen displays.

A Hierarchical Phosphorus Nanobarbed Nanowire Hybrid: Its Structure and Electrochemical Properties.

PubMed

Zhao, Dan; Li, Beibei; Zhang, Jinying; Li, Xin; Xiao, Dingbin; Fu, Chengcheng; Zhang, Lihui; Li, Zhihui; Li, Jun; Cao, Daxian; Niu, Chunming

2017-06-14

Nanostructured phosphorus-carbon composites are promising materials for Li-ion and Na-ion battery anodes. A hierarchical phosphorus hybrid, SiC@graphene@P, has been synthesized by the chemical vapor deposition of phosphorus on the surfaces of barbed nanowires, where the barbs are vertically grown graphene nanosheets and the cores are SiC nanowires. A temperature-gradient vaporization-condensation method has been used to remove the unhybridized phosphorus particles formed by homogeneous nucleation. The vertically grown barb shaped graphene nanosheets and a high concentration of edge carbon atoms induced a fibrous red phosphorus (f-RP) growth with its {001} planes in parallel to {002} planes of nanographene sheets and led to a strong interpenetrated interface interaction between phosphorus and the surfaces of graphene nanosheets. This hybridization has been demonstrated to significantly enhance the electrochemical performances of phosphorus.

Synergistic effects from graphene and carbon nanotubes endow ordered hierarchical structure foams with a combination of compressibility, super-elasticity and stability and potential application as pressure sensors

NASA Astrophysics Data System (ADS)

Kuang, Jun; Dai, Zhaohe; Liu, Luqi; Yang, Zhou; Jin, Ming; Zhang, Zhong

2015-05-01

Nanostructured carbon material based three-dimensional porous architectures have been increasingly developed for various applications, e.g. sensors, elastomer conductors, and energy storage devices. Maintaining architectures with good mechanical performance, including elasticity, load-bearing capacity, fatigue resistance and mechanical stability, is prerequisite for realizing these functions. Though graphene and CNT offer opportunities as nanoscale building blocks, it still remains a great challenge to achieve good mechanical performance in their microarchitectures because of the need to precisely control the structure at different scales. Herein, we fabricate a hierarchical honeycomb-like structured hybrid foam based on both graphene and CNT. The resulting materials possess excellent properties of combined high specific strength, elasticity and mechanical stability, which cannot be achieved in neat CNT and graphene foams. The improved mechanical properties are attributed to the synergistic-effect-induced highly organized, multi-scaled hierarchical architectures. Moreover, with their excellent electrical conductivity, we demonstrated that the hybrid foams could be used as pressure sensors in the fields related to artificial skin.Nanostructured carbon material based three-dimensional porous architectures have been increasingly developed for various applications, e.g. sensors, elastomer conductors, and energy storage devices. Maintaining architectures with good mechanical performance, including elasticity, load-bearing capacity, fatigue resistance and mechanical stability, is prerequisite for realizing these functions. Though graphene and CNT offer opportunities as nanoscale building blocks, it still remains a great challenge to achieve good mechanical performance in their microarchitectures because of the need to precisely control the structure at different scales. Herein, we fabricate a hierarchical honeycomb-like structured hybrid foam based on both graphene and CNT. The resulting materials possess excellent properties of combined high specific strength, elasticity and mechanical stability, which cannot be achieved in neat CNT and graphene foams. The improved mechanical properties are attributed to the synergistic-effect-induced highly organized, multi-scaled hierarchical architectures. Moreover, with their excellent electrical conductivity, we demonstrated that the hybrid foams could be used as pressure sensors in the fields related to artificial skin. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr00841g

Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

PubMed

Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

2018-05-01

Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

Controlled Growth of NiCo2O4 Nanorods and Ultrathin Nanosheets on Carbon Nanofibers for High-performance Supercapacitors

PubMed Central

Zhang, Genqiang; (David) Lou, Xiong Wen

2013-01-01

Two one-dimensional hierarchical hybrid nanostructures composed of NiCo2O4 nanorods and ultrathin nanosheets on carbon nanofibers (CNFs) are controllably synthesized through facile solution methods combined with a simple thermal treatment. The structure of NiCo2O4 can be easily controlled to be nanorods or nanosheets by using different additives in the synthesis. These two different nanostructures are evaluated as electrodes for high performance supercapacitors, in view of their apparent advantages, such as high electroactive surface area, ultrathin and porous features, robust mechanical strength, shorter ion and electron transport path. Their electrochemical performance is systematically studied, and both of these two hierarchical hybrid nanostructures exhibit high capacitance and excellent cycling stability. The remarkable electrochemical performance will undoubtedly make these hybrid structures attractive for high-performance supercapacitors with high power and energy densities. PMID:23503561

Hierarchical mesostructured titanium phosphonates with unusual uniform lines of macropores.

PubMed

Ma, Tian-Yi; Lin, Xiu-Zhen; Zhang, Xue-Jun; Yuan, Zhong-Yong

2011-04-01

Organic-inorganic hybrid materials of mesostructured titanium phosphonates with unusual uniform lines of macropores were synthesized by using bis(hexamethylenetriamine) penta(methylenephosphonic acid) (BHMTPMP) as the coupling molecule, through a one-pot hydrothermal process without any surfactant assistance. A wormhole-like mesostructure and many uniform parallel lines of macropores divided by solid ridges in the same direction were confirmed by N(2) sorption, SEM and TEM observations. This novel macropore architecture has never been observed in other metal phosphonate materials, which may be directly related to the structure nature of BHMTPMP with extra long alkyl chains. The structural characterization of FT-IR and MAS NMR revealed the integrity of organic groups inside the hybrid framework. The hybrid materials were also used as adsorbents for heavy metal ions and CO(2), in order to clarify the impacts of the organic contents and organic types on the physicochemical properties of the synthesized hierarchical macro-/mesoporous phosphonate materials.

Hybrid Energy Cell with Hierarchical Nano/Micro-Architectured Polymer Film to Harvest Mechanical, Solar, and Wind Energies Individually/Simultaneously.

PubMed

Dudem, Bhaskar; Ko, Yeong Hwan; Leem, Jung Woo; Lim, Joo Ho; Yu, Jae Su

2016-11-09

We report the creation of hybrid energy cells based on hierarchical nano/micro-architectured polydimethylsiloxane (HNMA-PDMS) films with multifunctionality to simultaneously harvest mechanical, solar, and wind energies. These films consist of nano/micro dual-scale architectures (i.e., nanonipples on inverted micropyramidal arrays) on the PDMS surface. The HNMA-PDMS is replicable by facile and cost-effective soft imprint lithography using a nanoporous anodic alumina oxide film formed on the micropyramidal-structured silicon substrate. The HNMA-PDMS film plays multifunctional roles as a triboelectric layer in nanogenerators and an antireflection layer for dye-sensitized solar cells (DSSCs), as well as a self-cleaning surface. This film is employed in triboelectric nanogenerator (TENG) devices, fabricated by laminating it on indium-tin oxide-coated polyethylene terephthalate (ITO/PET) as a bottom electrode. The large effective contact area that emerged from the densely packed hierarchical nano/micro-architectures of the PDMS film leads to the enhancement of TENG device performance. Moreover, the HNMA-PDMS/ITO/PET, with a high transmittance of >90%, also results in highly transparent TENG devices. By placing the HNMA-PDMS/ITO/PET, where the ITO/PET is coated with zinc oxide nanowires, as the top glass substrate of DSSCs, the device is able to add the functionality of TENG devices, thus creating a hybrid energy cell. The hybrid energy cell can successfully convert mechanical, solar, and wind energies into electricity, simultaneously or independently. To specify the device performance, the effects of external pushing frequency and load resistance on the output of TENG devices are also analyzed, including the photovoltaic performance of the hybrid energy cells.

Hierarchical time series bottom-up approach for forecast the export value in Central Java

NASA Astrophysics Data System (ADS)

Mahkya, D. A.; Ulama, B. S.; Suhartono

2017-10-01

The purpose of this study is Getting the best modeling and predicting the export value of Central Java using a Hierarchical Time Series. The export value is one variable injection in the economy of a country, meaning that if the export value of the country increases, the country’s economy will increase even more. Therefore, it is necessary appropriate modeling to predict the export value especially in Central Java. Export Value in Central Java are grouped into 21 commodities with each commodity has a different pattern. One approach that can be used time series is a hierarchical approach. Hierarchical Time Series is used Buttom-up. To Forecast the individual series at all levels using Autoregressive Integrated Moving Average (ARIMA), Radial Basis Function Neural Network (RBFNN), and Hybrid ARIMA-RBFNN. For the selection of the best models used Symmetric Mean Absolute Percentage Error (sMAPE). Results of the analysis showed that for the Export Value of Central Java, Bottom-up approach with Hybrid ARIMA-RBFNN modeling can be used for long-term predictions. As for the short and medium-term predictions, it can be used a bottom-up approach RBFNN modeling. Overall bottom-up approach with RBFNN modeling give the best result.

Hierarchically structured materials for lithium batteries

NASA Astrophysics Data System (ADS)

Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang

2013-10-01

The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg-1), new energy storage systems, such as lithium-oxygen (Li-O2) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li-O2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime.

Hierarchical composites of polyaniline-graphene nanoribbons-carbon nanotubes as electrode materials in all-solid-state supercapacitors.

PubMed

Liu, Mingkai; Miao, Yue-E; Zhang, Chao; Tjiu, Weng Weei; Yang, Zhibin; Peng, Huisheng; Liu, Tianxi

2013-08-21

A three dimensional (3D) polyaniline (PANI)-graphene nanoribbon (GNR)-carbon nanotube (CNT) composite, PANI-GNR-CNT, has been prepared via in situ polymerization of an aniline monomer on the surface of a GNR-CNT hybrid. Here, the 3D GNR-CNT hybrid has been conveniently prepared by partially unzipping the pristine multi-walled CNTs, while the residual CNTs act as "bridges" connecting different GNRs. The morphology and structure of the resulting hybrid materials have been characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), Raman spectroscopy and X-ray diffraction (XRD). Electrochemical tests reveal that the hierarchical PANI-GNR-CNT composite based on the two-electrode cell possesses much higher specific capacitance (890 F g(-1)) than the GNR-CNT hybrid (195 F g(-1)) and neat PANI (283 F g(-1)) at a discharge current density of 0.5 A g(-1). At the same time, the PANI-GNR-CNT composite displays good cycling stability with a retention ratio of 89% after 1000 cycles, suggesting that this novel PANI-GNR-CNT composite is a promising candidate for energy storage applications.

Hierarchical composites of polyaniline-graphene nanoribbons-carbon nanotubes as electrode materials in all-solid-state supercapacitors

NASA Astrophysics Data System (ADS)

Liu, Mingkai; Miao, Yue-E.; Zhang, Chao; Tjiu, Weng Weei; Yang, Zhibin; Peng, Huisheng; Liu, Tianxi

2013-07-01

A three dimensional (3D) polyaniline (PANI)-graphene nanoribbon (GNR)-carbon nanotube (CNT) composite, PANI-GNR-CNT, has been prepared via in situ polymerization of an aniline monomer on the surface of a GNR-CNT hybrid. Here, the 3D GNR-CNT hybrid has been conveniently prepared by partially unzipping the pristine multi-walled CNTs, while the residual CNTs act as ``bridges'' connecting different GNRs. The morphology and structure of the resulting hybrid materials have been characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), Raman spectroscopy and X-ray diffraction (XRD). Electrochemical tests reveal that the hierarchical PANI-GNR-CNT composite based on the two-electrode cell possesses much higher specific capacitance (890 F g-1) than the GNR-CNT hybrid (195 F g-1) and neat PANI (283 F g-1) at a discharge current density of 0.5 A g-1. At the same time, the PANI-GNR-CNT composite displays good cycling stability with a retention ratio of 89% after 1000 cycles, suggesting that this novel PANI-GNR-CNT composite is a promising candidate for energy storage applications.

Evaluating biomass-derived hierarchically porous carbon as the positive electrode material for hybrid Na-ion capacitors

NASA Astrophysics Data System (ADS)

Chen, Jizhang; Zhou, Xiaoyan; Mei, Changtong; Xu, Junling; Zhou, Shuang; Wong, Ching-Ping

2017-02-01

As a promising renewable resource, biomass has several advantages such as wide availability, low cost, and versatility. In this study, we use peanut shell, wheat straw, rice straw, corn stalk, cotton stalk, and soybean stalk as the precursors to synthesize hierarchically porous carbon as the positive electrode material for hybrid Na-ion capacitors, aiming to establish a criterion of choosing suitable biomass precursors. The carbon derived from wood-like cotton stalk has abundant interconnected macropores, high surface area of 1994 m2 g-1, and large pore volume of 1.107 cm3 g-1, thanks to which it exhibits high reversible capacitance of 160.5 F g-1 at 0.2 A g-1 and great rate capability, along with excellent cyclability. The carbonaceous positive electrode material is combined with a Na2Ti2.97Nb0.03O7 negative electrode material to assemble a hybrid Na-ion capacitor, which delivers a high specific energy of 169.4 Wh kg-1 at 120.5 W kg-1, ranking among the best-performed hybrid ion capacitors.

A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

NASA Astrophysics Data System (ADS)

Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

2017-09-01

Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

Self-assembled three-dimensional hierarchical graphene/polypyrrole nanotube hybrid aerogel and its application for supercapacitors.

PubMed

Ye, Shibing; Feng, Jiachun

2014-06-25

A three-dimensional hierarchical graphene/polypyrrole aerogel (GPA) has been fabricated using graphene oxide (GO) and already synthesized one-dimensional hollow polypyrrole nanotubes (PNTs) as the feedstock. The amphiphilic GO is helpful in effectively promoting the dispersion of well-defined PNTs to result in a stable, homogeneous GO/PNT complex solution, while the PNTs not only provide a large accessible surface area for fast transport of hydrate ions but also act as spacers to prevent the restacking of graphene sheets. By a simple one-step reduction self-assembly process, hierarchically structured, low-density, highly compressible GPAs are easily obtained, which favorably combine the advantages of graphene and PNTs. The supercapacitor electrodes based on such materials exhibit excellent electrochemical performance, including a high specific capacitance up to 253 F g(-1), good rate performance, and outstanding cycle stability. Moreover, this method may be feasible to prepare other graphene-based hybrid aerogels with structure-controllable nanostructures in large scale, thereby holding enormous potential in many application fields.

Mineral-Templated 3D Graphene Architectures for Energy-Efficient Electrodes.

PubMed

Zhang, Mingchao; Chen, Ke; Wang, Chunya; Jian, Muqiang; Yin, Zhe; Liu, Zhenglian; Hong, Guo; Liu, Zhongfan; Zhang, Yingying

2018-05-01

3D graphene networks have shown extraordinary promise for high-performance electrochemical devices. Herein, the chemical vapor deposition synthesis of a highly porous 3D graphene foam (3D-GF) using naturally abundant calcined Iceland crystal as the template is reported. Intriguingly, the Iceland crystal transforms to CaO monolith with evenly distributed micro/meso/macropores through the releasing of CO 2 at high temperature. Meanwhile, the hierarchical structure of the calcined template could be easily tuned under different calcination conditions. By precisely inheriting fine structure from the templates, the as-prepared 3D-GF possesses a tunable hierarchical porosity and low density. Thus, the hierarchical pores offer space for guest hybridization and provide an efficient pathway for ion/charge transport in typical energy conversion/storage systems. The 3D-GF skeleton electrode hybridized with Ni(OH) 2 /Co(OH) 2 through an optimal electrodeposition condition exhibits a high specific capacitance of 2922.2 F g -1 at a scan rate of 10 mV s -1 , and 2138.4 F g -1 at a discharge current density of 3.1 A g -1 . The hybrid 3D-GF symmetry supercapacitor shows a high energy density of 83.0 Wh kg -1 at a power density of 1011.3 W kg -1 and 31.4 Wh kg -1 at a high power density of 18 845.2 W kg -1 . The facile fabrication process enables the mass production of hierarchical porous 3D-GF for high-performance supercapacitors. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cohesion in Military and Aviation Psychology: An Annotated Bibliography and Suggestions for US Army Aviation

DTIC Science & Technology

2005-06-01

serve a significant influence upon perceptions. Strategies for mitigating the detrimental effects of racism and sexism are suggested. Leaders need to...Hedlund, J. (1998). Extending the multilevel theory of team decision making: Effects of feedback and experience in hierarchical teams. Academy of...Colquitt, J.A., & Hedlund, J. (1998). Extending the multilevel theory of team decision making: Effects of feedback and experience in hierarchical

Habits as action sequences: hierarchical action control and changes in outcome value

PubMed Central

Dezfouli, Amir; Lingawi, Nura W.; Balleine, Bernard W.

2014-01-01

Goal-directed action involves making high-level choices that are implemented using previously acquired action sequences to attain desired goals. Such a hierarchical schema is necessary for goal-directed actions to be scalable to real-life situations, but results in decision-making that is less flexible than when action sequences are unfolded and the decision-maker deliberates step-by-step over the outcome of each individual action. In particular, from this perspective, the offline revaluation of any outcomes that fall within action sequence boundaries will be invisible to the high-level planner resulting in decisions that are insensitive to such changes. Here, within the context of a two-stage decision-making task, we demonstrate that this property can explain the emergence of habits. Next, we show how this hierarchical account explains the insensitivity of over-trained actions to changes in outcome value. Finally, we provide new data that show that, under extended extinction conditions, habitual behaviour can revert to goal-directed control, presumably as a consequence of decomposing action sequences into single actions. This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure. PMID:25267824

Perceived Learning and Timely Graduation for Business Undergraduates Taking an Online or Hybrid Course

ERIC Educational Resources Information Center

Blau, Gary; Drennan, Rob B.; Hochner, Arthur; Kapanjie, Darin

2016-01-01

An online survey tested the impact of background, technological, and course-related variables on perceived learning and timely graduation for a complete data sample of 263 business undergraduates taking at least one online or hybrid course in the fall of 2015. Hierarchical regression results showed that course-related variables (instructor…

ZnO nanorods/ZnS·(1,6-hexanediamine)(0.5) hybrid nanoplates hierarchical heteroarchitecture with improved electrochemical catalytic properties for hydrazine.

PubMed

Wu, Zhengcui; Wu, Yaqin; Pei, Tonghui; Wang, Huan; Geng, Baoyou

2014-03-07

Novel hierarchical heteronanostructures of ZnO nanorods/ZnS·(HDA)0.5 (HDA = 1,6-hexanediamine) hybrid nanoplates on a zinc substrate are successfully synthesized on a large scale by combining hydrothermal growth (for ZnO nanorods) and liquid chemical conversion (for ZnS·(HDA)0.5 nanoplates) techniques. The formation of ZnS·(HDA)0.5 hybrid nanoplates branches takes advantage of the preferential binding of 1,6-hexanediamine on specific facets of ZnS, which makes the thickening rate much lower than the lateral growth rate. The ZnS·(HDA)0.5 hybrid nanoplates have a layered structure with 1,6-hexanediamine inserted into interlayers of wurtzite ZnS through the bonding of nitrogen. The number density and thickness of the secondary ZnS·(HDA)0.5 nanoplates can be conveniently engineered by variation of the sulfur source and straightforward adjustment of reactant concentrations such as 1,6-hexanediamine and the sulfur source. The fabricated ZnO/ZnS·(HDA)0.5 heteronanostructures show improved electrochemical catalytic properties for hydrazine compared with the primary ZnO nanorods. Due to its simplicity and efficiency, this approach could be similarly used to fabricate varieties of hybrid heterostructures made of materials with an intrinsic large lattice mismatch.

A hierarchical instrumental decision theory of nicotine dependence.

PubMed

Hogarth, Lee; Troisi, Joseph R

2015-01-01

It is important to characterize the learning processes governing tobacco-seeking in order to understand how best to treat this behavior. Most drug learning theories have adopted a Pavlovian framework wherein the conditioned response is the main motivational process. We favor instead a hierarchical instrumental decision account, wherein expectations about the instrumental contingency between voluntary tobacco-seeking and the receipt of nicotine reward determines the probability of executing this behavior. To support this view, we review titration and nicotine discrimination research showing that internal signals for deprivation/satiation modulate expectations about the current incentive value of smoking, thereby modulating the propensity of this behavior. We also review research on cue-reactivity which has shown that external smoking cues modulate expectations about the probability of the tobacco-seeking response being effective, thereby modulating the propensity of this behavior. Economic decision theory is then considered to elucidate how expectations about the value and probability of response-nicotine contingency are integrated to form an overall utility estimate for that option for comparison with qualitatively different, nonsubstitute reinforcers, to determine response selection. As an applied test for this hierarchical instrumental decision framework, we consider how well it accounts for individual liability to smoking uptake and perseveration, pharmacotherapy, cue-extinction therapies, and plain packaging. We conclude that the hierarchical instrumental account is successful in reconciling this broad range of phenomenon precisely because it accepts that multiple diverse sources of internal and external information must be integrated to shape the decision to smoke.

Breaking down hierarchies of decision-making in primates

PubMed Central

Hyafil, Alexandre; Moreno-Bote, Rubén

2017-01-01

Possible options in a decision often organize as a hierarchy of subdecisions. A recent study concluded that perceptual processes in primates mimic this hierarchical structure and perform subdecisions in parallel. We argue that a flat model that directly selects between final choices accounts more parsimoniously for the reported behavioral and neural data. Critically, a flat model is characterized by decision signals integrating evidence at different hierarchical levels, in agreement with neural recordings showing this integration in localized neural populations. Our results point to the role of experience for building integrated perceptual categories where sensory evidence is merged prior to decision. DOI: http://dx.doi.org/10.7554/eLife.16650.001 PMID:28648171

Hierarchical Bayes approach for subgroup analysis.

PubMed

Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C

2017-01-01

In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.

Hierarchically Superstructured Prussian Blue Analogues: Spontaneous Assembly Synthesis and Applications as Pseudocapacitive Materials

DOE PAGES

Yue, Yanfeng; Zhang, Zhiyong; Binder, Andrew J.; ...

2014-11-10

Hierarchically superstructured Prussian blue analogues (hexa- conventional hybrid graphene/MnO 2 nanostructured textiles. cyanoferrate, M = Ni II, Co II and Cu II) are synthesized through Because sodium or potassium ions are involved in energy stor- a spontaneous assembly technique. In sharp contrast to mac- age processes, more environmentally neutral electrolytes can roporous-only Prussian blue analogues, the hierarchically su- be utilized, making the superstructured porous Prussian blue perstructured porous Prussian blue materials are demonstrated analogues a great contender for applications as high-per- to possess a high capacitance, which is similar to those of the formance pseudocapacitors.

Patterned Diblock Co-Polymer Thin Films as Templates for Advanced Anisotropic Metal Nanostructures.

PubMed

Roth, Stephan V; Santoro, Gonzalo; Risch, Johannes F H; Yu, Shun; Schwartzkopf, Matthias; Boese, Torsten; Döhrmann, Ralph; Zhang, Peng; Besner, Bastian; Bremer, Philipp; Rukser, Dieter; Rübhausen, Michael A; Terrill, Nick J; Staniec, Paul A; Yao, Yuan; Metwalli, Ezzeldin; Müller-Buschbaum, Peter

2015-06-17

We demonstrate glancing-angle deposition of gold on a nanostructured diblock copolymer, namely polystyrene-block-poly(methyl methacrylate) thin film. Exploiting the selective wetting of gold on the polystyrene block, we are able to fabricate directional hierarchical structures. We prove the asymmetric growth of the gold nanoparticles and are able to extract the different growth laws by in situ scattering methods. The optical anisotropy of these hierarchical hybrid materials is further probed by angular resolved spectroscopic methods. This approach enables us to tailor functional hierarchical layers in nanodevices, such as nanoantennae arrays, organic photovoltaics, and sensor electronics.

Free-standing hierarchically sandwich-type tungsten disulfide nanotubes/graphene anode for lithium-ion batteries.

PubMed

Chen, Renjie; Zhao, Teng; Wu, Weiping; Wu, Feng; Li, Li; Qian, Ji; Xu, Rui; Wu, Huiming; Albishri, Hassan M; Al-Bogami, A S; El-Hady, Deia Abd; Lu, Jun; Amine, Khalil

2014-10-08

Transition metal dichalcogenides (TMD), analogue of graphene, could form various dimensionalities. Similar to carbon, one-dimensional (1D) nanotube of TMD materials has wide application in hydrogen storage, Li-ion batteries, and supercapacitors due to their unique structure and properties. Here we demonstrate the feasibility of tungsten disulfide nanotubes (WS2-NTs)/graphene (GS) sandwich-type architecture as anode for lithium-ion batteries for the first time. The graphene-based hierarchical architecture plays vital roles in achieving fast electron/ion transfer, thus leading to good electrochemical performance. When evaluated as anode, WS2-NTs/GS hybrid could maintain a capacity of 318.6 mA/g over 500 cycles at a current density of 1A/g. Besides, the hybrid anode does not require any additional polymetric binder, conductive additives, or a separate metal current-collector. The relatively high density of this hybrid is beneficial for high capacity per unit volume. Those characteristics make it a potential anode material for light and high-performance lithium-ion batteries.

Hierarchically structured graphene-carbon nanotube-cobalt hybrid electrocatalyst for seawater battery

NASA Astrophysics Data System (ADS)

Suh, Dong Hoon; Park, Sul Ki; Nakhanivej, Puritut; Kim, Youngsik; Hwang, Soo Min; Park, Ho Seok

2017-12-01

The design of cost-effective and highly active catalysts is a critical challenge. Inspired by the strong points of stability and conductivity of carbon nanotubes (CNTs), high catalytic activity of Co nanoparticles, and rapid ion diffusion and large accessible area of three-dimensional (3D) graphene, we demonstrate a novel strategy to construct a hierarchical hybrid structure consisting of Co/CoOx nanoparticles-incorporated CNT branches onto the 3D reduced graphene oxide (rGO) architecture. The surface-modified 3D rGO by steam activation process has a large surface area and abundant defect sites, which serve as active sites to uniformly grow Co/CoOx nanoparticles. Furthermore, the CNTs preserve their performance stably by encapsulating Co nanoparticles, while the uniformly decorated Co/CoOx nanoparticles exhibit superior electrocatalytic activity toward oxygen evolution/reduction reaction due to highly exposed active sites. Employing the hybrid particle electrocatalyst, the seawater battery operates stably at 0.01 mA cm-2 during 50 cycles, owing to the good electrocatalytic ability.

Mutual and asynchronous anticipation and action in sports as globally competitive and locally coordinative dynamics

PubMed Central

Fujii, Keisuke; Isaka, Tadao; Kouzaki, Motoki; Yamamoto, Yuji

2015-01-01

Humans interact by changing their actions, perceiving other’s actions and executing solutions in conflicting situations. Using oscillator models, nonlinear dynamics have been considered for describing these complex human movements as an emergence of self-organisation. However, these frameworks cannot explain the hierarchical structures of complex behaviours between conflicting inter-agent and adapting intra-agent systems, especially in sport competitions wherein mutually quick decision making and execution are required. Here we adopt a hybrid multiscale approach to model an attack-and-defend game during which both players predict the opponent’s movement and move with a delay. From both simulated and measured data, one synchronous outcome between two-agent (i.e. successful defence) can be described as one attractor. In contrast, the other coordination-breaking outcome (i.e. successful attack) cannot be explained using gradient dynamics because the asymmetric interaction cannot always assume a conserved physical quantity. Instead, we provide the asymmetric and asynchronous hierarchical dynamical models to discuss two-agent competition. Our framework suggests that possessing information about an opponent and oneself in local-coordinative and global-competitive scale enables us to gain a deeper understanding of sports competitions. We anticipate developments in the scientific fields of complex movement adapting to such uncontrolled environments. PMID:26538452

Mutual and asynchronous anticipation and action in sports as globally competitive and locally coordinative dynamics

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Isaka, Tadao; Kouzaki, Motoki; Yamamoto, Yuji

2015-11-01

Humans interact by changing their actions, perceiving other’s actions and executing solutions in conflicting situations. Using oscillator models, nonlinear dynamics have been considered for describing these complex human movements as an emergence of self-organisation. However, these frameworks cannot explain the hierarchical structures of complex behaviours between conflicting inter-agent and adapting intra-agent systems, especially in sport competitions wherein mutually quick decision making and execution are required. Here we adopt a hybrid multiscale approach to model an attack-and-defend game during which both players predict the opponent’s movement and move with a delay. From both simulated and measured data, one synchronous outcome between two-agent (i.e. successful defence) can be described as one attractor. In contrast, the other coordination-breaking outcome (i.e. successful attack) cannot be explained using gradient dynamics because the asymmetric interaction cannot always assume a conserved physical quantity. Instead, we provide the asymmetric and asynchronous hierarchical dynamical models to discuss two-agent competition. Our framework suggests that possessing information about an opponent and oneself in local-coordinative and global-competitive scale enables us to gain a deeper understanding of sports competitions. We anticipate developments in the scientific fields of complex movement adapting to such uncontrolled environments.

Three-level global resource allocation model for hiv control: A hierarchical decision system approach.

PubMed

Kassa, Semu Mitiku

2018-02-01

Funds from various global organizations, such as, The Global Fund, The World Bank, etc. are not directly distributed to the targeted risk groups. Especially in the so-called third-world-countries, the major part of the fund in HIV prevention programs comes from these global funding organizations. The allocations of these funds usually pass through several levels of decision making bodies that have their own specific parameters to control and specific objectives to achieve. However, these decisions are made mostly in a heuristic manner and this may lead to a non-optimal allocation of the scarce resources. In this paper, a hierarchical mathematical optimization model is proposed to solve such a problem. Combining existing epidemiological models with the kind of interventions being on practice, a 3-level hierarchical decision making model in optimally allocating such resources has been developed and analyzed. When the impact of antiretroviral therapy (ART) is included in the model, it has been shown that the objective function of the lower level decision making structure is a non-convex minimization problem in the allocation variables even if all the production functions for the intervention programs are assumed to be linear.

Fabrication of a 3D Hierarchical Sandwich Co9 S8 /α-MnS@N-C@MoS2 Nanowire Architectures as Advanced Electrode Material for High Performance Hybrid Supercapacitors.

PubMed

Kandula, Syam; Shrestha, Khem Raj; Kim, Nam Hoon; Lee, Joong Hee

2018-06-01

Supercapacitors suffer from lack of energy density and impulse the energy density limit, so a new class of hybrid electrode materials with promising architectures is strongly desirable. Here, the rational design of a 3D hierarchical sandwich Co 9 S 8 /α-MnS@N-C@MoS 2 nanowire architecture is achieved during the hydrothermal sulphurization reaction by the conversion of binary mesoporous metal oxide core to corresponding individual metal sulphides core along with the formation of outer metal sulphide shell at the same time. Benefiting from the 3D hierarchical sandwich architecture, Co 9 S 8 /α-MnS@N-C@MoS 2 electrode exhibits enhanced electrochemical performance with high specific capacity/capacitance of 306 mA h g -1 /1938 F g -1 at 1 A g -1 , and excellent cycling stability with a specific capacity retention of 86.9% after 10 000 cycles at 10 A g -1 . Moreover, the fabricated asymmetric supercapacitor device using Co 9 S 8 /α-MnS@N-C@MoS 2 as the positive electrode and nitrogen doped graphene as the negative electrode demonstrates high energy density of 64.2 Wh kg -1 at 729.2 W kg -1 , and a promising energy density of 23.5 Wh kg -1 is still attained at a high power density of 11 300 W kg -1 . The hybrid electrode with 3D hierarchical sandwich architecture promotes enhanced energy density with excellent cyclic stability for energy storage. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Emerging Hierarchical Aerogels: Self-Assembly of Metal and Semiconductor Nanocrystals.

PubMed

Cai, Bin; Sayevich, Vladimir; Gaponik, Nikolai; Eychmüller, Alexander

2018-06-19

Aerogels assembled from colloidal metal or semiconductor nanocrystals (NCs) feature large surface area, ultralow density, and high porosity, thus rendering them attractive in various applications, such as catalysis, sensors, energy storage, and electronic devices. Morphological and structural modification of the aerogel backbones while maintaining the aerogel properties enables a second stage of the aerogel research, which is defined as hierarchical aerogels. Different from the conventional aerogels with nanowire-like backbones, those hierarchical aerogels are generally comprised of at least two levels of architectures, i.e., an interconnected porous structure on the macroscale and a specially designed configuration at local backbones at the nanoscale. This combination "locks in" the inherent properties of the NCs, so that the beneficial genes obtained by nanoengineering are retained in the resulting monolithic hierarchical aerogels. Herein, groundbreaking advances in the design, synthesis, and physicochemical properties of the hierarchical aerogels are reviewed and organized in three sections: i) pure metallic hierarchical aerogels, ii) semiconductor hierarchical aerogels, and iii) metal/semiconductor hybrid hierarchical aerogels. This report aims to define and demonstrate the concept, potential, and challenges of the hierarchical aerogels, thereby providing a perspective on the further development of these materials. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hierarchical Management Information Systems: A Decentralized Approach for University Administration

ERIC Educational Resources Information Center

Wager, J. James

1977-01-01

A Hierarchical Management Information System (HMIS) provides decision-making as well as operational information to all groups of the institution in a timely and predictable manner. Its operational aspects and benefits are discussed. (Author/LBH)

Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems

PubMed Central

Choo, Benjamin Y.; Adams, Stephen C.; Weiss, Brian A.; Marvel, Jeremy A.; Beling, Peter A.

2017-01-01

The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM leverages and integrates lower-level PHM information such as from a machine or component with hierarchical relationships across the component, machine, work cell, and assembly line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are then made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. To overcome the issue of exponential explosion of complexity associated with describing a large manufacturing system, the AM-PHM methodology takes a hierarchical Markov Decision Process (MDP) approach into describing the system and solving for an optimized policy. A description of the AM-PHM methodology is followed by a simulated industry-inspired example to demonstrate the effectiveness of AM-PHM. PMID:28736651

DECISION-COMPONENTS OF NICE'S TECHNOLOGY APPRAISALS ASSESSMENT FRAMEWORK.

PubMed

de Folter, Joost; Trusheim, Mark; Jonsson, Pall; Garner, Sarah

2018-01-01

Value assessment frameworks have gained prominence recently in the context of U.S. healthcare. Such frameworks set out a series of factors that are considered in funding decisions. The UK's National Institute of Health and Care Excellence (NICE) is an established health technology assessment (HTA) agency. We present a novel application of text analysis that characterizes NICE's Technology Appraisals in the context of the newer assessment frameworks and present the results in a visual way. A total of 243 documents of NICE's medicines guidance from 2007 to 2016 were analyzed. Text analysis was used to identify a hierarchical set of decision factors considered in the assessments. The frequency of decision factors stated in the documents was determined and their association with terms related to uncertainty. The results were incorporated into visual representations of hierarchical factors. We identified 125 decision factors, and hierarchically grouped these into eight domains: Clinical Effectiveness, Cost Effectiveness, Condition, Current Practice, Clinical Need, New Treatment, Studies, and Other Factors. Textual analysis showed all domains appeared consistently in the guidance documents. Many factors were commonly associated with terms relating to uncertainty. A series of visual representations was created. This study reveals the complexity and consistency of NICE's decision-making processes and demonstrates that cost effectiveness is not the only decision-criteria. The study highlights the importance of processes and methodology that can take both quantitative and qualitative information into account. Visualizations can help effectively communicate this complex information during the decision-making process and subsequently to stakeholders.

Genetic population structure of Shoal Bass within their native range

USGS Publications Warehouse

Taylor, Andrew T.; Tringali, Michael D.; Sammons, Steven M.; Ingram, Travis R.; O'Rouke, Patrick M.; Peterson, Douglas L.; Long, James M.

2018-01-01

Endemic to the Apalachicola River basin of the southeastern USA, the Shoal Bass Micropterus cataractae is a fluvial‐specialist sport fish that is imperiled because of anthropogenic habitat alteration. To counter population declines, restorative stocking efforts are becoming an increasingly relevant management strategy. However, population genetic structure within the species is currently unknown, but it could influence management decisions, such as brood source location. Leveraging a collaborative effort to collect and genotype specimens with 16 microsatellite loci, our objective was to characterize hierarchical population structure and genetic differentiation of the Shoal Bass across its native range, including an examination of structuring mechanisms, such as relatedness and inbreeding levels. Specimens identified as Shoal Bass were collected from 13 distinct sites (N ranged from 17 to 209 per location) and were then taxonomically screened to remove nonnative congeners and hybrids (pure Shoal Bass N ranged from 13 to 183 per location). Our results revealed appreciable population structure, with five distinct Shoal Bass populations identifiable at the uppermost hierarchical level that generally corresponded with natural geographic features and anthropogenic barriers. Substructure was recovered within several of these populations, wherein differences appeared related to spatial isolation and local population dynamics. An analysis of molecular variance revealed that 3.6% of the variation in our data set was accounted for among three larger river drainages, but substructure within each river drainage also explained an additional 8.9% of genetic variation, demonstrating that management at a scale lower than the river drainage level would likely best conserve genetic diversity. Results provide a population genetic framework that can inform future management decisions, such as brood source location, so that genetic diversity within and among populations is conserved and overall adaptability of the species is maintained.

Implementation of Hybrid V-Cycle Multilevel Methods for Mixed Finite Element Systems with Penalty

NASA Technical Reports Server (NTRS)

Lai, Chen-Yao G.

1996-01-01

The goal of this paper is the implementation of hybrid V-cycle hierarchical multilevel methods for the indefinite discrete systems which arise when a mixed finite element approximation is used to solve elliptic boundary value problems. By introducing a penalty parameter, the perturbed indefinite system can be reduced to a symmetric positive definite system containing the small penalty parameter for the velocity unknown alone. We stabilize the hierarchical spatial decomposition approach proposed by Cai, Goldstein, and Pasciak for the reduced system. We demonstrate that the relative condition number of the preconditioner is bounded uniformly with respect to the penalty parameter, the number of levels and possible jumps of the coefficients as long as they occur only across the edges of the coarsest elements.

Synergistic effects from graphene and carbon nanotubes endow ordered hierarchical structure foams with a combination of compressibility, super-elasticity and stability and potential application as pressure sensors.

PubMed

Kuang, Jun; Dai, Zhaohe; Liu, Luqi; Yang, Zhou; Jin, Ming; Zhang, Zhong

2015-01-01

Nanostructured carbon material based three-dimensional porous architectures have been increasingly developed for various applications, e.g. sensors, elastomer conductors, and energy storage devices. Maintaining architectures with good mechanical performance, including elasticity, load-bearing capacity, fatigue resistance and mechanical stability, is prerequisite for realizing these functions. Though graphene and CNT offer opportunities as nanoscale building blocks, it still remains a great challenge to achieve good mechanical performance in their microarchitectures because of the need to precisely control the structure at different scales. Herein, we fabricate a hierarchical honeycomb-like structured hybrid foam based on both graphene and CNT. The resulting materials possess excellent properties of combined high specific strength, elasticity and mechanical stability, which cannot be achieved in neat CNT and graphene foams. The improved mechanical properties are attributed to the synergistic-effect-induced highly organized, multi-scaled hierarchical architectures. Moreover, with their excellent electrical conductivity, we demonstrated that the hybrid foams could be used as pressure sensors in the fields related to artificial skin.

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

NASA Technical Reports Server (NTRS)

Caines, P. E.

1999-01-01

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

CuO-Decorated ZnO Hierarchical Nanostructures as Efficient and Established Sensing Materials for H2S Gas Sensors

PubMed Central

Vuong, Nguyen Minh; Chinh, Nguyen Duc; Huy, Bui The; Lee, Yong-Ill

2016-01-01

Highly sensitive hydrogen sulfide (H2S) gas sensors were developed from CuO-decorated ZnO semiconducting hierarchical nanostructures. The ZnO hierarchical nanostructure was fabricated by an electrospinning method following hydrothermal and heat treatment. CuO decoration of ZnO hierarchical structures was carried out by a wet method. The H2S gas-sensing properties were examined at different working temperatures using various quantities of CuO as the variable. CuO decoration of the ZnO hierarchical structure was observed to promote sensitivity for H2S gas higher than 30 times at low working temperature (200 °C) compared with that in the nondecorated hierarchical structure. The sensing mechanism of the hybrid sensor structure is also discussed. The morphology and characteristics of the samples were examined by scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), UV-vis absorption, photoluminescence (PL), and electrical measurements. PMID:27231026

Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

PubMed

Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

2014-12-01

This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

Chitin: Formation of Helically Structured Chitin/CaCO3 Hybrids through an Approach Inspired by the Biomineralization Processes of Crustacean Cuticles (Small 38/2015).

PubMed

Matsumura, Shunichi; Kajiyama, Satoshi; Nishimura, Tatsuya; Kato, Takashi

2015-10-01

Biomineral-inspired hybrids forming helically ordered structures are developed by T. Kato and co-workers on page 5127. These helical hybrids consist of liquid-crystalline chitin and CaCO3 . They resemble the structures of crustacean cuticles such as the exoskeleton of a lobster or crayfish. These hybrids are formed through CaCO3 crystallization on the liquidcrystalline chitin templates. Polymer-stabilized amorphous CaCO3 is incorporated into the liquid-crystalline chitin templates. This approach is useful for the development of new hierarchical hybrid materials from abundant natural resources. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of hybrid clustering using parallel k-means algorithm and DIANA algorithm

NASA Astrophysics Data System (ADS)

Umam, Khoirul; Bustamam, Alhadi; Lestari, Dian

2017-03-01

DNA is one of the carrier of genetic information of living organisms. Encoding, sequencing, and clustering DNA sequences has become the key jobs and routine in the world of molecular biology, in particular on bioinformatics application. There are two type of clustering, hierarchical clustering and partitioning clustering. In this paper, we combined two type clustering i.e. K-Means (partitioning clustering) and DIANA (hierarchical clustering), therefore it called Hybrid clustering. Application of hybrid clustering using Parallel K-Means algorithm and DIANA algorithm used to clustering DNA sequences of Human Papillomavirus (HPV). The clustering process is started with Collecting DNA sequences of HPV are obtained from NCBI (National Centre for Biotechnology Information), then performing characteristics extraction of DNA sequences. The characteristics extraction result is store in a matrix form, then normalize this matrix using Min-Max normalization and calculate genetic distance using Euclidian Distance. Furthermore, the hybrid clustering is applied by using implementation of Parallel K-Means algorithm and DIANA algorithm. The aim of using Hybrid Clustering is to obtain better clusters result. For validating the resulted clusters, to get optimum number of clusters, we use Davies-Bouldin Index (DBI). In this study, the result of implementation of Parallel K-Means clustering is data clustered become 5 clusters with minimal IDB value is 0.8741, and Hybrid Clustering clustered data become 13 sub-clusters with minimal IDB values = 0.8216, 0.6845, 0.3331, 0.1994 and 0.3952. The IDB value of hybrid clustering less than IBD value of Parallel K-Means clustering only that perform at 1ts stage. Its means clustering using Hybrid Clustering have the better result to clustered DNA sequence of HPV than perform parallel K-Means Clustering only.

Decision net, directed graph, and neural net processing of imaging spectrometer data

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki; Barnard, Etienne

1989-01-01

A decision-net solution involving a novel hierarchical classifier and a set of multiple directed graphs, as well as a neural-net solution, are respectively presented for large-class problem and mixture problem treatments of imaging spectrometer data. The clustering method for hierarchical classifier design, when used with multiple directed graphs, yields an efficient decision net. New directed-graph rules for reducing local maxima as well as the number of perturbations required, and the new starting-node rules for extending the reachability and reducing the search time of the graphs, are noted to yield superior results, as indicated by an illustrative 500-class imaging spectrometer problem.

Implementation of hybrid clustering based on partitioning around medoids algorithm and divisive analysis on human Papillomavirus DNA

NASA Astrophysics Data System (ADS)

Arimbi, Mentari Dian; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Data clustering can be executed through partition or hierarchical method for many types of data including DNA sequences. Both clustering methods can be combined by processing partition algorithm in the first level and hierarchical in the second level, called hybrid clustering. In the partition phase some popular methods such as PAM, K-means, or Fuzzy c-means methods could be applied. In this study we selected partitioning around medoids (PAM) in our partition stage. Furthermore, following the partition algorithm, in hierarchical stage we applied divisive analysis algorithm (DIANA) in order to have more specific clusters and sub clusters structures. The number of main clusters is determined using Davies Bouldin Index (DBI) value. We choose the optimal number of clusters if the results minimize the DBI value. In this work, we conduct the clustering on 1252 HPV DNA sequences data from GenBank. The characteristic extraction is initially performed, followed by normalizing and genetic distance calculation using Euclidean distance. In our implementation, we used the hybrid PAM and DIANA using the R open source programming tool. In our results, we obtained 3 main clusters with average DBI value is 0.979, using PAM in the first stage. After executing DIANA in the second stage, we obtained 4 sub clusters for Cluster-1, 9 sub clusters for Cluster-2 and 2 sub clusters in Cluster-3, with the BDI value 0.972, 0.771, and 0.768 for each main cluster respectively. Since the second stage produce lower DBI value compare to the DBI value in the first stage, we conclude that this hybrid approach can improve the accuracy of our clustering results.

Market Competitiveness Evaluation of Mechanical Equipment with a Pairwise Comparisons Hierarchical Model.

PubMed

Hou, Fujun

2016-01-01

This paper provides a description of how market competitiveness evaluations concerning mechanical equipment can be made in the context of multi-criteria decision environments. It is assumed that, when we are evaluating the market competitiveness, there are limited number of candidates with some required qualifications, and the alternatives will be pairwise compared on a ratio scale. The qualifications are depicted as criteria in hierarchical structure. A hierarchical decision model called PCbHDM was used in this study based on an analysis of its desirable traits. Illustration and comparison shows that the PCbHDM provides a convenient and effective tool for evaluating the market competitiveness of mechanical equipment. The researchers and practitioners might use findings of this paper in application of PCbHDM.

Electrospun carbon nanofibers surface-grafted with vapor-grown carbon nanotubes as hierarchical electrodes for supercapacitors

NASA Astrophysics Data System (ADS)

Zhou, Zhengping; Wu, Xiang-Fa; Fong, Hao

2012-01-01

This letter reports the fabrication and electrochemical properties of electrospun carbon nanofibers surface-grafted with vapor-grown carbon nanotubes (CNTs) as hierarchical electrodes for supercapacitors. The specific capacitance of the fabricated electrodes was measured up to 185 F/g at the low discharge current density of 625 mA/g; a decrease of 38% was detected at the high discharge current density of 2.5 A/g. The morphology and microstructure of the electrodes were examined by electron microscopy, and the unique connectivity of the hybrid nanomaterials was responsible for the high specific capacitance and low intrinsic contact electric resistance of the hierarchical electrodes.

Glycol-modified silanes: novel possibilities for the synthesis of hierarchically organized (hybrid) porous materials.

PubMed

Hartmann, Sarah; Brandhuber, Doris; Hüsing, Nicola

2007-09-01

The preparation of porous hierarchical architectures that have structural features spanning from the nanometer to micrometer and even larger dimensions and that exhibit certain functionalities is one of the new challenging frontiers in materials chemistry. The sol-gel process is one of the most promising synthesis routes toward such materials because it not only offers the possibility to incorporate organic functions into the porous host but also offers the possibility to deliberately tailor the pore structure. In this Account, the opportunities given by the application of novel diol-modified silanes are discussed for the synthesis of hierarchically organized inorganic and also inorganic-organic porous monoliths.

Integrated Optoelectronic Networks for Application-Driven Multicore Computing

DTIC Science & Technology

2017-05-08

hybrid photonic torus, the all-optical Corona crossbar, and the hybrid hierarchical Firefly crossbar. • The key challenges for waveguide photonics...improves SXR but with relatively higher EDP overhead. Our evaluation results indicate that the encoding schemes improve worst-case-SXR in Corona and...photonic crossbar architectures ( Corona and Firefly) indicate that our approach improves worst-case signal-to-noise ratio (SNR) by up to 51.7

Hierarchical screening for multiple mental disorders.

PubMed

Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

2013-10-01

There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

Continuous track paths reveal additive evidence integration in multistep decision making.

PubMed

Buc Calderon, Cristian; Dewulf, Myrtille; Gevers, Wim; Verguts, Tom

2017-10-03

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.

Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

PubMed Central

2014-01-01

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

A Hierarchical Z-Scheme α-Fe2 O3 /g-C3 N4 Hybrid for Enhanced Photocatalytic CO2 Reduction.

PubMed

Jiang, Zhifeng; Wan, Weiming; Li, Huaming; Yuan, Shouqi; Zhao, Huijun; Wong, Po Keung

2018-03-01

The challenge in the artificial photosynthesis of fossil resources from CO 2 by utilizing solar energy is to achieve stable photocatalysts with effective CO 2 adsorption capacity and high charge-separation efficiency. A hierarchical direct Z-scheme system consisting of urchin-like hematite and carbon nitride provides an enhanced photocatalytic activity of reduction of CO 2 to CO, yielding a CO evolution rate of 27.2 µmol g -1 h -1 without cocatalyst and sacrifice reagent, which is >2.2 times higher than that produced by g-C 3 N 4 alone (10.3 µmol g -1 h -1 ). The enhanced photocatalytic activity of the Z-scheme hybrid material can be ascribed to its unique characteristics to accelerate the reduction process, including: (i) 3D hierarchical structure of urchin-like hematite and preferable basic sites which promotes the CO 2 adsorption, and (ii) the unique Z-scheme feature efficiently promotes the separation of the electron-hole pairs and enhances the reducibility of electrons in the conduction band of the g-C 3 N 4 . The origin of such an obvious advantage of the hierarchical Z-scheme is not only explained based on the experimental data but also investigated by modeling CO 2 adsorption and CO adsorption on the three different atomic-scale surfaces via density functional theory calculation. The study creates new opportunities for hierarchical hematite and other metal-oxide-based Z-scheme system for solar fuel generation. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

PubMed Central

Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

2015-01-01

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

Aircraft optimization by a system approach: Achievements and trends

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1992-01-01

Recently emerging methodology for optimal design of aircraft treated as a system of interacting physical phenomena and parts is examined. The methodology is found to coalesce into methods for hierarchic, non-hierarchic, and hybrid systems all dependent on sensitivity analysis. A separate category of methods has also evolved independent of sensitivity analysis, hence suitable for discrete problems. References and numerical applications are cited. Massively parallel computer processing is seen as enabling technology for practical implementation of the methodology.

Water decontamination by polyoxometalate-functionalized 3D-printed hierarchical porous devices.

PubMed

Ji, Yuanchun; Ma, Yuan; Ma, Yanjiao; Asenbauer, Jakob; Passerini, Stefano; Streb, Carsten

2018-03-25

The design of organic-inorganic hybrid composites has revolutionized application-driven materials design. Here, we show how hierarchically structured, 3D-printed ABS polymers can be surface-functionalized with lacunary polyoxometalate anions ([α-PW 9 O 34 ] 9- ) featuring heavy-metal binding sites. The resulting composite is highly porous and can be used for the removal of transition-metal pollutants from water. Thus, a facile blueprint for decentralized production of water filtration devices is reported.

A Pilot Study of Pedestrians with Visual Impairments Detecting Traffic Gaps and Surges Containing Hybrid Vehicles

PubMed Central

Emerson, Robert Wall; Naghshineh, Koorosh; Hapeman, Julie; Wiener, William

2010-01-01

The increasing number of hybrid and quiet internal combustion engine vehicles may impact the travel abilities of pedestrians who are blind. Pedestrians who rely on auditory cues for structuring their travel may face challenges in making crossing decisions in the presence of quiet vehicles. This article describes results of initial studies looking at the crossing decisions of pedestrians who are blind at an uncontrolled crossing (no traffic control) and a light controlled intersection. The presence of hybrid vehicles was a factor in each situation. At the uncontrolled crossing, Toyota hybrids were most difficult to detect but crossing decisions were made more often in small gaps ended by a Honda hybrid. These effects were seen only at speed under 20 mph. At the light controlled intersection, parallel surges of traffic were most difficult to detect when made up only of a Ford Escape hybrid. Results suggest that more controlled studies of vehicle characteristics impacting crossing decisions of pedestrians who are blind are warranted. PMID:21379367

A Pilot Study of Pedestrians with Visual Impairments Detecting Traffic Gaps and Surges Containing Hybrid Vehicles.

PubMed

Emerson, Robert Wall; Naghshineh, Koorosh; Hapeman, Julie; Wiener, William

2011-03-01

The increasing number of hybrid and quiet internal combustion engine vehicles may impact the travel abilities of pedestrians who are blind. Pedestrians who rely on auditory cues for structuring their travel may face challenges in making crossing decisions in the presence of quiet vehicles. This article describes results of initial studies looking at the crossing decisions of pedestrians who are blind at an uncontrolled crossing (no traffic control) and a light controlled intersection. The presence of hybrid vehicles was a factor in each situation. At the uncontrolled crossing, Toyota hybrids were most difficult to detect but crossing decisions were made more often in small gaps ended by a Honda hybrid. These effects were seen only at speed under 20 mph. At the light controlled intersection, parallel surges of traffic were most difficult to detect when made up only of a Ford Escape hybrid. Results suggest that more controlled studies of vehicle characteristics impacting crossing decisions of pedestrians who are blind are warranted.

Participatory Decision Making.

ERIC Educational Resources Information Center

King, M. Bruce; And Others

Shifting from traditional, hierarchical bureaucracies to participatory governance and decision making is a major theme in school restructuring. This paper focuses on the involvement of teachers in key aspects of school decision making. Specifically, the paper describes how changes in power relations supported teachers' focus on improving the…

Hierarchical Coupling of First-Principles Molecular Dynamics with Advanced Sampling Methods.

PubMed

Sevgen, Emre; Giberti, Federico; Sidky, Hythem; Whitmer, Jonathan K; Galli, Giulia; Gygi, Francois; de Pablo, Juan J

2018-05-14

We present a seamless coupling of a suite of codes designed to perform advanced sampling simulations, with a first-principles molecular dynamics (MD) engine. As an illustrative example, we discuss results for the free energy and potential surfaces of the alanine dipeptide obtained using both local and hybrid density functionals (DFT), and we compare them with those of a widely used classical force field, Amber99sb. In our calculations, the efficiency of first-principles MD using hybrid functionals is augmented by hierarchical sampling, where hybrid free energy calculations are initiated using estimates obtained with local functionals. We find that the free energy surfaces obtained from classical and first-principles calculations differ. Compared to DFT results, the classical force field overestimates the internal energy contribution of high free energy states, and it underestimates the entropic contribution along the entire free energy profile. Using the string method, we illustrate how these differences lead to different transition pathways connecting the metastable minima of the alanine dipeptide. In larger peptides, those differences would lead to qualitatively different results for the equilibrium structure and conformation of these molecules.

Genetically encoded lipid-polypeptide hybrid biomaterials that exhibit temperature-triggered hierarchical self-assembly

NASA Astrophysics Data System (ADS)

Mozhdehi, Davoud; Luginbuhl, Kelli M.; Simon, Joseph R.; Dzuricky, Michael; Berger, Rüdiger; Varol, H. Samet; Huang, Fred C.; Buehne, Kristen L.; Mayne, Nicholas R.; Weitzhandler, Isaac; Bonn, Mischa; Parekh, Sapun H.; Chilkoti, Ashutosh

2018-05-01

Post-translational modification of proteins is a strategy widely used in biological systems. It expands the diversity of the proteome and allows for tailoring of both the function and localization of proteins within cells as well as the material properties of structural proteins and matrices. Despite their ubiquity in biology, with a few exceptions, the potential of post-translational modifications in biomaterials synthesis has remained largely untapped. As a proof of concept to demonstrate the feasibility of creating a genetically encoded biohybrid material through post-translational modification, we report here the generation of a family of three stimulus-responsive hybrid materials—fatty-acid-modified elastin-like polypeptides—using a one-pot recombinant expression and post-translational lipidation methodology. These hybrid biomaterials contain an amphiphilic domain, composed of a β-sheet-forming peptide that is post-translationally functionalized with a C14 alkyl chain, fused to a thermally responsive elastin-like polypeptide. They exhibit temperature-triggered hierarchical self-assembly across multiple length scales with varied structure and material properties that can be controlled at the sequence level.

Facile solid-state synthesis of Ni@C nanosheet-assembled hierarchical network for high-performance lithium storage

NASA Astrophysics Data System (ADS)

Gu, Jinghe; Li, Qiyun; Zeng, Pan; Meng, Yulin; Zhang, Xiukui; Wu, Ping; Zhou, Yiming

2017-08-01

Micro/nano-architectured transition-metal@C hybrids possess unique structural and compositional features toward lithium storage, and are thus expected to manifest ideal anodic performances in advanced lithium-ion batteries (LIBs). Herein, we propose a facile and scalable solid-state coordination and subsequent pyrolysis route for the formation of a novel type of micro/nano-architectured transition-metal@C hybrid (i.e., Ni@C nanosheet-assembled hierarchical network, Ni@C network). Moreover, this coordination-pyrolysis route has also been applied for the construction of bare carbon network using zinc salts instead of nickel salts as precursors. When applied as potential anodic materials in LIBs, the Ni@C network exhibits Ni-content-dependent electrochemical performances, and the partially-etched Ni@C network manifests markedly enhanced Li-storage performances in terms of specific capacities, cycle life, and rate capability than the pristine Ni@C network and carbon network. The proposed solid-state coordination and pyrolysis strategy would open up new opportunities for constructing micro/nano-architectured transition-metal@C hybrids as advanced anode materials for LIBs.

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations

PubMed Central

Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W.

2016-01-01

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty’s 1–9 scale, this paper proposes a cross-ratio-based bipolar 0.1–0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

PubMed

Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

2016-09-09

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness.

Reinforcement Learning for Weakly-Coupled MDPs and an Application to Planetary Rover Control

NASA Technical Reports Server (NTRS)

Bernstein, Daniel S.; Zilberstein, Shlomo

2003-01-01

Weakly-coupled Markov decision processes can be decomposed into subprocesses that interact only through a small set of bottleneck states. We study a hierarchical reinforcement learning algorithm designed to take advantage of this particular type of decomposability. To test our algorithm, we use a decision-making problem faced by autonomous planetary rovers. In this problem, a Mars rover must decide which activities to perform and when to traverse between science sites in order to make the best use of its limited resources. In our experiments, the hierarchical algorithm performs better than Q-learning in the early stages of learning, but unlike Q-learning it converges to a suboptimal policy. This suggests that it may be advantageous to use the hierarchical algorithm when training time is limited.

Biomimetic mineralized hierarchical hybrid scaffolds based on in situ synthesis of nano-hydroxyapatite/chitosan/chondroitin sulfate/hyaluronic acid for bone tissue engineering.

PubMed

Hu, Yimin; Chen, Jingdi; Fan, Tiantang; Zhang, Yujue; Zhao, Yao; Shi, Xuetao; Zhang, Qiqing

2017-09-01

Biomimetic mineralized hybrid scaffolds are widely used as natural bone substitute materials in tissue engineering by mimicking vital characters of extracellular matrix (ECM). However, the fabrication of hybrid scaffolds with suitable mechanical properties and good biocompatibility remains a challenge. To solve the problems mentioned above, biomimetic calcium phosphate mineralized organic-inorganic hybrid scaffold composed of nano hydroxyapatite (nHAP), Chitosan (CS), Chondroitin sulfate (CSA) and hyaluronic acid (HA) with hierarchical micro/nano structures was successfully developed. In this process, an efficient and easy-to-accomplish method combining in situ biomimetic synthesis with freeze-drying technology was applied. The chemical structure of the scaffolds was confirmed by Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). Surface morphology of scaffolds was characterized by Scanning electron microscopy (SEM). The nHAP/CS/CSA/HA hybrid scaffolds with a well-distributed pore size showed suitable mechanical strength which is not only due to the addition of the nHAP but also the interaction between the positively charged CS and the negatively charged CSA and HA. Simultaneously, the biocompatibility was evaluated by the MTT cytotoxicity assay, alkaline phosphatase (ALP) activity, Hoechst 33258 fluorescence staining. All those results proved that the scaffolds possess good biocompatibility and the components added have enhanced the proliferation and differentiation of osteoblast. Thus, it can be anticipated that the in situ biomimetic mineralized nHAP/CS/CAS/HA hybrid scaffolds will be promising candidates for bone tissue engineering. Copyright © 2017 Elsevier B.V. All rights reserved.

A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context

NASA Astrophysics Data System (ADS)

Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul

Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.

The rational choice model in family decision making at the end of life.

PubMed

Karasz, Alison; Sacajiu, Galit; Kogan, Misha; Watkins, Liza

2010-01-01

Most end-of-life decisions are made by family members. Current ethical guidelines for family decision making are based on a hierarchical model that emphasizes the patient's wishes over his or her best interests. Evidence suggests that the model poorly reflects the strategies and priorities of many families. Researchers observed and recorded 26 decision-making meetings between hospital staff and family members. Semi-structured follow-up interviews were conducted. Transcriptions were analyzed using qualitative techniques. For both staff and families, consideration of a patient's best interests generally took priority over the patient's wishes. Staff generally introduced discussion of the patient's wishes for rhetorical purposes, such as persuasion. Competing moral frameworks, which de-emphasized the salience of patients' autonomy and "right to choose," played a role in family decision making. The priority given to the patients' wishes in the hierarchical model does not reflect the priorities of staff and families in making decisions about end-of-life care.

Fuzzy compromise: An effective way to solve hierarchical design problems

NASA Technical Reports Server (NTRS)

Allen, J. K.; Krishnamachari, R. S.; Masetta, J.; Pearce, D.; Rigby, D.; Mistree, F.

1990-01-01

In this paper, we present a method for modeling design problems using a compromise decision support problem (DSP) incorporating the principles embodied in fuzzy set theory. Specifically, the fuzzy compromise decision support problem is used to study hierarchical design problems. This approach has the advantage that although the system modeled has an element of uncertainty associated with it, the solution obtained is crisp and precise. The efficacy of incorporating fuzzy sets into the solution process is discussed in the context of results obtained for a portal frame.

Distributed Decision Making Environment.

DTIC Science & Technology

1982-12-01

Findeisen , F. N. Bailey, M. Brdys, K. Malinowski, P. Tatjewoki and A. Wozniak, Control and Coordination in Hierarchical Systems, New York, NY: Wiley...1977. [99] W. Findeisen et al., "On-line hierarchical control for steady-state systems," IEEE Trans. Automat. Conts., vol. AC-23, no. 2, pp. 189-209

3D hierarchical assembly of ultrathin MnO2 nanoflakes on silicon nanowires for high performance micro-supercapacitors in Li- doped ionic liquid

PubMed Central

Dubal, Deepak P.; Aradilla, David; Bidan, Gérard; Gentile, Pascal; Schubert, Thomas J.S.; Wimberg, Jan; Sadki, Saïd; Gomez-Romero, Pedro

2015-01-01

Building of hierarchical core-shell hetero-structures is currently the subject of intensive research in the electrochemical field owing to its potential for making improved electrodes for high-performance micro-supercapacitors. Here we report a novel architecture design of hierarchical MnO2@silicon nanowires (MnO2@SiNWs) hetero-structures directly supported onto silicon wafer coupled with Li-ion doped 1-Methyl-1-propylpyrrolidinium bis(trifluromethylsulfonyl)imide (PMPyrrBTA) ionic liquids as electrolyte for micro-supercapacitors. A unique 3D mesoporous MnO2@SiNWs in Li-ion doped IL electrolyte can be cycled reversibly across a voltage of 2.2 V and exhibits a high areal capacitance of 13 mFcm−2. The high conductivity of the SiNWs arrays combined with the large surface area of ultrathin MnO2 nanoflakes are responsible for the remarkable performance of these MnO2@SiNWs hetero-structures which exhibit high energy density and excellent cycling stability. This combination of hybrid electrode and hybrid electrolyte opens up a novel avenue to design electrode materials for high-performance micro-supercapacitors. PMID:25985388

Hierarchically-structured hollow NiO nanospheres/nitrogen-doped graphene hybrid with superior capacity retention and enhanced rate capability for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Chen, Jiayuan; Wu, Xiaofeng; Liu, Ya; Gong, Yan; Wang, Pengfei; Li, Wenhui; Mo, Shengpeng; Tan, Qiangqiang; Chen, Yunfa

2017-12-01

A facile template-free synthesis strategy is demonstrated to fabricate nanostructured NiO/N-doped graphene hybrid, in which NiO hollow nanospheres with hierarchically mesoporous structure are tightly anchored on N-doped graphene matrix. The mesoporous shell of NiO can not only provide sufficient electrode/electrolyte contact areas to accelerate ion diffusion and electron exchange, but also efficiently mitigate the volume change that occurs during long-time reactions. Simultaneously, the reduced graphene oxide with doping nitrogen atoms are employed as effectively conductive backbone, further enhancing the electrochemical performances. When used as anodic material for lithium ion batteries, the synergistic system delivers a reversible capacity up to 1104.6 mAh g-1 after 150 cycles at a current density of 0.08 A g-1 and 422.3 mAh g-1 at a high charging rate of 4 A g-1, which is better than those of the bare counterparts and most other NiO-based materials reported in the previous literatures. The hierarchically hollow NiO nanostructure combined with N-doped graphene matrix provides a promising candidate applied in advanced anode materials for lithium ion batteries.

Morphology-controlled construction of hierarchical hollow hybrid SnO2@TiO2 nanocapsules with outstanding lithium storage

PubMed Central

Zhou, Linzong; Guo, Hong; Li, Tingting; Chen, Weiwei; Liu, Lixiang; Qiao, Jinli; Zhang, Jiujun

2015-01-01

A novel synthesis containing microwave-assisted HCl etching reaction and precipitating reaction is employed to prepare hierarchical hollow SnO2@TiO2 nanocapsules for anode materials of Li-ion batteries. The intrinsic hollow nanostructure can shorten the lengths for both ionic and electronic transport, enlarge the electrode surface areas, and improving accommodation of the anode volume change during Li insertion/extraction cycling. The hybrid multi-elements in this material allow the volume change to take place in a stepwise manner during electrochemical cycling. In particular, the coating of TiO2 onto SnO2 can enhance the electronic conductivity of hollow SnO2 electrode. As a result, the as-prepared SnO2@TiO2 nanocapsule electrode exhibits a stably reversible capacity of 770 mA hg−1 at 1 C, and the capacity retention can keep over 96.1% after 200 cycles even at high current rates. This approach may shed light on a new avenue for the fast synthesis of hierarchical hollow nanocapsule functional materials for energy storage, catalyst and other new applications. PMID:26482415

Hierarchical analysis of bridge decision makers : the role of new technology adoption in the timber bridge market : special project fiscal year 1992

DOT National Transportation Integrated Search

1995-08-01

Bridge design engineers and local highway officials make bridge replacement decisions across the : United States. The Analytical Hierarchy Process was used to characterize the bridge material selection : decision of these individuals. State Departmen...

ZnO nanorods/ZnS.(1,6-hexanediamine)0.5 hybrid nanoplates hierarchical heteroarchitecture with improved electrochemical catalytic properties for hydrazine

NASA Astrophysics Data System (ADS)

Wu, Zhengcui; Wu, Yaqin; Pei, Tonghui; Wang, Huan; Geng, Baoyou

2014-02-01

Novel hierarchical heteronanostructures of ZnO nanorods/ZnS.(HDA)0.5 (HDA = 1,6-hexanediamine) hybrid nanoplates on a zinc substrate are successfully synthesized on a large scale by combining hydrothermal growth (for ZnO nanorods) and liquid chemical conversion (for ZnS.(HDA)0.5 nanoplates) techniques. The formation of ZnS.(HDA)0.5 hybrid nanoplates branches takes advantage of the preferential binding of 1,6-hexanediamine on specific facets of ZnS, which makes the thickening rate much lower than the lateral growth rate. The ZnS.(HDA)0.5 hybrid nanoplates have a layered structure with 1,6-hexanediamine inserted into interlayers of wurtzite ZnS through the bonding of nitrogen. The number density and thickness of the secondary ZnS.(HDA)0.5 nanoplates can be conveniently engineered by variation of the sulfur source and straightforward adjustment of reactant concentrations such as 1,6-hexanediamine and the sulfur source. The fabricated ZnO/ZnS.(HDA)0.5 heteronanostructures show improved electrochemical catalytic properties for hydrazine compared with the primary ZnO nanorods. Due to its simplicity and efficiency, this approach could be similarly used to fabricate varieties of hybrid heterostructures made of materials with an intrinsic large lattice mismatch.Novel hierarchical heteronanostructures of ZnO nanorods/ZnS.(HDA)0.5 (HDA = 1,6-hexanediamine) hybrid nanoplates on a zinc substrate are successfully synthesized on a large scale by combining hydrothermal growth (for ZnO nanorods) and liquid chemical conversion (for ZnS.(HDA)0.5 nanoplates) techniques. The formation of ZnS.(HDA)0.5 hybrid nanoplates branches takes advantage of the preferential binding of 1,6-hexanediamine on specific facets of ZnS, which makes the thickening rate much lower than the lateral growth rate. The ZnS.(HDA)0.5 hybrid nanoplates have a layered structure with 1,6-hexanediamine inserted into interlayers of wurtzite ZnS through the bonding of nitrogen. The number density and thickness of the secondary ZnS.(HDA)0.5 nanoplates can be conveniently engineered by variation of the sulfur source and straightforward adjustment of reactant concentrations such as 1,6-hexanediamine and the sulfur source. The fabricated ZnO/ZnS.(HDA)0.5 heteronanostructures show improved electrochemical catalytic properties for hydrazine compared with the primary ZnO nanorods. Due to its simplicity and efficiency, this approach could be similarly used to fabricate varieties of hybrid heterostructures made of materials with an intrinsic large lattice mismatch. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05231a

Use of facile mechanochemical method to functionalize carbon nanofibers with nanostructured polyaniline and their electrochemical capacitance

PubMed Central

2012-01-01

A facile approach to functionalize carbon nanofibers [CNFs] with nanostructured polyaniline was developed via in situ mechanochemical polymerization of polyaniline in the presence of chemically treated CNFs. The nanostructured polyaniline grafting on the CNF was mainly in a form of branched nanofibers as well as rough nanolayers. The good dispersibility and processability of the hybrid nanocomposite could be attributed to its overall nanostructure which enhanced its accessibility to the electrolyte. The mechanochemical oxidation polymerization was believed to be related to the strong Lewis acid characteristic of FeCl3 and the Lewis base characteristic of aniline. The growth mechanism of the hierarchical structured nanofibers was also discussed. After functionalization with the nanostructured polyaniline, the hybrid polyaniline/CNF composite showed an enhanced specific capacitance, which might be related to its hierarchical nanostructure and the interaction between the aromatic polyaniline molecules and the CNFs. PMID:22315992

Adaptive Multi-scale PHM for Robotic Assembly Processes

PubMed Central

Choo, Benjamin Y.; Beling, Peter A.; LaViers, Amy E.; Marvel, Jeremy A.; Weiss, Brian A.

2017-01-01

Adaptive multiscale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. As a rule, PHM information is not used in high-level decision-making in manufacturing systems. AM-PHM leverages and integrates component-level PHM information with hierarchical relationships across the component, machine, work cell, and production line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. A description of the AM-PHM methodology with a simulated canonical robotic assembly process is presented. PMID:28664161

Effects of different hierarchical hybrid micro/nanostructure surfaces on implant osseointegration.

PubMed

Cheng, Bingkun; Niu, Qiang; Cui, Yajun; Jiang, Wei; Zhao, Yunzhuan; Kong, Liang

2017-06-01

Hierarchical hybrid micro/nanostructure implant surfaces are considered to better mimic the hierarchical structure of bone and the nanostructures substantively influence osseointegration through managing cell behaviors. To enhance implant osseointegration for further clinical application, we evaluated the material properties and osseointegration effects of hierarchical surfaces with different nano-morphologies, using a rat model. Two representative surface fabrication methods, hydrofluoric (HF) acid etching combined with anodization (HF + AN) or magnetron sputtering (HF + MS), were selected. Sample material properties were evaluated by scanning electron microscopy, atomic force microscopy, X-ray diffraction, X-ray photoemission spectroscopy, and epoxy resin docking tensile test. Implants with different surfaces were inserted into the distal femurs of rats. After 12 weeks, osseointegration was examined by microcomputed tomography (micro-CT), histological, and biomechanical tests. Tensile testing demonstrated high bonding strength at coating/implant in the HF + MS group. Micro-CT revealed increased bone volume/total volume and significantly reduced trabecular separation in HF + MS versus other groups. Histological analysis showed significantly higher HF + MS bone-to-implant contact (74.78 ± 4.40%) versus HF + AN (65.11 ± 5.10%) and machined samples (56.03 ± 3.23%). The maximal HF + MS pull-out force increased by 33.7% versus HF + AN. These results indicated that HF + MS surfaces exhibited superior material property in terms of bonding strength and favorable implant osseointegration compared to other groups. © 2017 Wiley Periodicals, Inc.

Merging K-means with hierarchical clustering for identifying general-shaped groups.

PubMed

Peterson, Anna D; Ghosh, Arka P; Maitra, Ranjan

2018-01-01

Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while K -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters. We present a hybrid non-parametric clustering approach that amalgamates the two methods to identify general-shaped clusters and that can be applied to larger datasets. Specifically, we first partition the dataset into spherical groups using K -means. We next merge these groups using hierarchical methods with a data-driven distance measure as a stopping criterion. Our proposal has the potential to reveal groups with general shapes and structure in a dataset. We demonstrate good performance on several simulated and real datasets.

Structural Interplay - Tuning Mechanics in Peptide-Polyurea Hybrids

NASA Astrophysics Data System (ADS)

Korley, Lashanda

Utilizing cues from natural materials, we have been inspired to explore the hierarchical arrangement critical to energy absorption and mechanical enhancement in synthetic systems. Of particular interest is the soft domain ordering proposed as a contributing element to the observed toughness in spider silk. Multiblock copolymers, are ideal and dynamic systems in which to explore this approach via variations in secondary structure of nature's building blocks - peptides. We have designed a new class of polyurea hybrids that incorporate peptidic copolymers as the soft segment. The impact of hierarchical ordering on the thermal, mechanical, and morphological behavior of these bio-inspired polyurethanes with a siloxane-based, peptide soft segment was investigated. These peptide-polyurethane/urea hybrids were microphase segregated, and the beta-sheet secondary structure of the soft segment was preserved during polymerization and film casting. Toughness enhancement at low strains was achieved, but the overall extensibility of the peptide-incorporated systems was reduced due to the unique hard domain organization. To decouple the secondary structure influence in the siloxane-peptide soft segment from mechanics dominated by the hard domain, we also developed non-chain extended peptide-polyurea hybrids in which the secondary structure (beta sheet vs. alpha helix) was tuned via choice of peptide and peptide length. It was shown that this structural approach allowed tailoring of extensibility, toughness, and modulus. The sheet-dominant hybrid materials were typically tougher and more elastic due to intermolecular H-bonding facilitating load distribution, while the helical-prevalent systems generally exhibited higher stiffness. Recently, we have explored the impact of a molecular design strategy that overlays a covalent and physically crosslinked architecture in these peptide-polyurea hybrids, demonstrating that physical constraints in the network hybrids influences peptide hydrogen bonding and morphology. These structural features correlated well with systematic changes in modulus, extensibility, and hysteresis. Complementary to this effort is the design of PEG-based peptide-polyurea hybrids with tunable and responsive as structural and injectable hydrogels. The authors acknowledge funding support from the National Science Foundation (CAREER DMR-0953236).

Hybrid time-frequency domain equalization based on sign-sign joint decision multimodulus algorithm for 6 × 6 mode division multiplexing system

NASA Astrophysics Data System (ADS)

Li, Jiao; Hu, Guijun; Gong, Caili; Li, Li

2018-02-01

In this paper, we propose a hybrid time-frequency domain sign-sign joint decision multimodulus algorithm (Hybrid-SJDMMA) for mode-demultiplexing in a 6 × 6 mode division multiplexing (MDM) system with high-order QAM modulation. The equalization performance of Hybrid-SJDMMA was evaluated and compared with the frequency domain multimodulus algorithm (FD-MMA) and the hybrid time-frequency domain sign-sign multimodulus algorithm (Hybrid-SMMA). Simulation results revealed that Hybrid-SJDMMA exhibits a significantly lower computational complexity than FD-MMA, and its convergence speed is similar to that of FD-MMA. Additionally, the bit-error-rate performance of Hybrid-SJDMMA was obviously better than FD-MMA and Hybrid-SMMA for 16 QAM and 64 QAM.

Perspectives on Multiunit Colleges

ERIC Educational Resources Information Center

Rossmeier, Joseph G.

1976-01-01

Research shows that neither centralization nor decentralization of decision-making authority in multiunit community colleges is a primary determinant of organizational effectiveness; rather it is the degree of participation in decision-making by staff members at all hierarchical levels. (BB)

Hirarchical emotion calculation model for virtual human modellin - biomed 2010.

PubMed

Zhao, Yue; Wright, David

2010-01-01

This paper introduces a new emotion generation method for virtual human modelling. The method includes a novel hierarchical emotion structure, a group of emotion calculation equations and a simple heuristics decision making mechanism, which enables virtual humans to perform emotionally in real-time according to their internal and external factors. Emotion calculation equations used in this research were derived from psychologic emotion measurements. Virtual humans can utilise the information in virtual memory and emotion calculation equations to generate their own numerical emotion states within the hierarchical emotion structure. Those emotion states are important internal references for virtual humans to adopt appropriate behaviours and also key cues for their decision making. A simple heuristics theory is introduced and integrated into decision making process in order to make the virtual humans decision making more like a real human. A data interface which connects the emotion calculation and the decision making structure together has also been designed and simulated to test the method in Virtools environment.

Modeling Choice Under Uncertainty in Military Systems Analysis

DTIC Science & Technology

1991-11-01

operators rather than fuzzy operators. This is suggested for further research. 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) In AHP , objectives, functions and...14 4.1 IMPRECISELY SPECIFIED MULTIPLE A’ITRIBUTE UTILITY THEORY... 14 4.2 FUZZY DECISION ANALYSIS...14 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) ................................... 14 4.4 SUBJECTIVE TRANSFER FUNCTION APPROACH

Coordination of Distributed Fuzzy Behaviors in Mobile Robot Control

NASA Technical Reports Server (NTRS)

Tunstel, E.

1995-01-01

This presentation describes an approach to behavior coordination and conflict resolution within the context of a hierarchical architecture of fuzzy behaviors. Coordination is achieved using weighted decision-making based on behavioral degrees of applicability. This strategy is appropriate for fuzzy control of systems that can be represented by hierarchical or decentralized structures.

People, Policy and Process in College-Level Academic Management

ERIC Educational Resources Information Center

Nguyen, Thang N.

2016-01-01

Academic institution structure is both hierarchical and committee-based. It is hierarchical in the Administration including staff, similar to business corporations. It is committee-based for the Faculty body in a fashion similar to US Congress. It can exploit the best of both models for better governance and rightfully democratic decisions. The…

Orders of C2 Agility and Implications for Information and Decision-Making

DTIC Science & Technology

2013-06-01

of agility and, in particular, in discussions of resilience. Orders of agility also invite the re-examination of conceptions of value in informing...incompatible interpretations of decision-making and information. It also gives greater confidence that different conceptions of value and assessment...examination of conceptions of value in informing decision- making, leading to the exposition of a hierarchical model of nested decision-making and decision

Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

PubMed

Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

2017-07-01

Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

2011-01-01

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

The Role of Personal Ethical Checking in Courageous School Leadership

ERIC Educational Resources Information Center

Buskey, Frederick C.; Pitts, Eric M.

2013-01-01

When school leaders make calculated decisions to deviate from hierarchical or cultural directives and norms, they may be viewed as mavericks or brigands. This paper details a process of ethical checking to help differentiate ethical decisions from more arbitrary or self-serving decisions. The paper examines conflicts inherent in many professional…

A genome-wide perspective on the evolutionary history of enigmatic wolf-like canids

PubMed Central

vonHoldt, Bridgett M.; Pollinger, John P.; Earl, Dent A.; Knowles, James C.; Boyko, Adam R.; Parker, Heidi; Geffen, Eli; Pilot, Malgorzata; Jedrzejewski, Wlodzimierz; Jedrzejewska, Bogumila; Sidorovich, Vadim; Greco, Claudia; Randi, Ettore; Musiani, Marco; Kays, Roland; Bustamante, Carlos D.; Ostrander, Elaine A.; Novembre, John; Wayne, Robert K.

2011-01-01

High-throughput genotyping technologies developed for model species can potentially increase the resolution of demographic history and ancestry in wild relatives. We use a SNP genotyping microarray developed for the domestic dog to assay variation in over 48K loci in wolf-like species worldwide. Despite the high mobility of these large carnivores, we find distinct hierarchical population units within gray wolves and coyotes that correspond with geographic and ecologic differences among populations. Further, we test controversial theories about the ancestry of the Great Lakes wolf and red wolf using an analysis of haplotype blocks across all 38 canid autosomes. We find that these enigmatic canids are highly admixed varieties derived from gray wolves and coyotes, respectively. This divergent genomic history suggests that they do not have a shared recent ancestry as proposed by previous researchers. Interspecific hybridization, as well as the process of evolutionary divergence, may be responsible for the observed phenotypic distinction of both forms. Such admixture complicates decisions regarding endangered species restoration and protection. PMID:21566151

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision.

PubMed

Sgaier, Sema K; Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-09-13

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15-29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision

PubMed Central

Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-01-01

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15–29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior. PMID:28901285

Compromise decision support problems for hierarchical design involving uncertainty

NASA Astrophysics Data System (ADS)

Vadde, S.; Allen, J. K.; Mistree, F.

1994-08-01

In this paper an extension to the traditional compromise Decision Support Problem (DSP) formulation is presented. Bayesian statistics is used in the formulation to model uncertainties associated with the information being used. In an earlier paper a compromise DSP that accounts for uncertainty using fuzzy set theory was introduced. The Bayesian Decision Support Problem is described in this paper. The method for hierarchical design is demonstrated by using this formulation to design a portal frame. The results are discussed and comparisons are made with those obtained using the fuzzy DSP. Finally, the efficacy of incorporating Bayesian statistics into the traditional compromise DSP formulation is discussed and some pending research issues are described. Our emphasis in this paper is on the method rather than the results per se.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review

NASA Astrophysics Data System (ADS)

Uhde, Britta; Andreas Hahn, W.; Griess, Verena C.; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review.

PubMed

Uhde, Britta; Hahn, W Andreas; Griess, Verena C; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

A Hierarchical Analysis of Bridge Decision Makers ... The Role of New Technology Adoption in the Timber Bridge Market: Special Project

Treesearch

Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt

1995-01-01

Bridge design engineers and local highway officials make bridge replacement decisions across the United States. The Analytical Hierarchy Process was used to characterize the bridge material selection decision of these individuals. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in...

Evolving rule-based systems in two medical domains using genetic programming.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

2004-11-01

To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

Hybridization and endangered species protection in the molecular era.

PubMed

Wayne, Robert K; Shaffer, H Bradley

2016-06-01

After decades of discussion, there is little consensus on the extent to which hybrids between endangered and nonendangered species should be protected by US law. As increasingly larger, genome-scale data sets are developed, we can identify individuals and populations with even trace levels of genetic admixture, making the 'hybrid problem' all the more difficult. We developed a decision-tree framework for evaluating hybrid protection, including both the processes that produced hybrids (human-mediated or natural) and the ecological impact of hybrids on natural ecosystems. We then evaluated our decision tree for four case studies drawn from our own work and briefly discuss several other cases from the literature. Throughout, we highlight the management outcomes that our approach provides and the nuances of hybridization as a conservation problem. © 2016 John Wiley & Sons Ltd.

Decision Accuracy in Computer-Mediated versus Face-to-Face Decision-Making Teams.

PubMed

Hedlund; Ilgen; Hollenbeck

1998-10-01

Changes in the way organizations are structured and advances in communication technologies are two factors that have altered the conditions under which group decisions are made. Decisions are increasingly made by teams that have a hierarchical structure and whose members have different areas of expertise. In addition, many decisions are no longer made via strictly face-to-face interaction. The present study examines the effects of two modes of communication (face-to-face or computer-mediated) on the accuracy of teams' decisions. The teams are characterized by a hierarchical structure and their members differ in expertise consistent with the framework outlined in the Multilevel Theory of team decision making presented by Hollenbeck, Ilgen, Sego, Hedlund, Major, and Phillips (1995). Sixty-four four-person teams worked for 3 h on a computer simulation interacting either face-to-face (FtF) or over a computer network. The communication mode had mixed effects on team processes in that members of FtF teams were better informed and made recommendations that were more predictive of the correct team decision, but leaders of CM teams were better able to differentiate staff members on the quality of their decisions. Controlling for the negative impact of FtF communication on staff member differentiation increased the beneficial effect of the FtF mode on overall decision making accuracy. Copyright 1998 Academic Press.

3D hybrid-porous carbon derived from carbonization of metal organic frameworks for high performance supercapacitors

NASA Astrophysics Data System (ADS)

Bao, Weizhai; Mondal, Anjon Kumar; Xu, Jing; Wang, Chengyin; Su, Dawei; Wang, Guoxiu

2016-09-01

We report a rational design and synthesis of 3D hybrid-porous carbon with a hierarchical pore architecture for high performance supercapacitors. It contains micropores (<2 nm diameter) and mesopores (2-4 nm), derived from carbonization of unique porous metal organic frameworks (MOFs). Owning to the synergistic effect of micropores and mesopores, the hybrid-porous carbon has exceptionally high ion-accessible surface area and low ion diffusion resistance, which is desired for supercapacitor applications. When applied as electrode materials in supercapacitors, 3D hybrid-porous carbon demonstrates a specific capacitance of 332 F g-1 at a constant charge/discharge current of 500 mA g-1. The supercapacitors can endure more than 10,000 cycles without degradation of capacitance.

Argument structure hierarchy system and method for facilitating analysis and decision-making processes

DOEpatents

Janssen, Terry

2000-01-01

A system and method for facilitating decision-making comprising a computer program causing linkage of data representing a plurality of argument structure units into a hierarchical argument structure. Each argument structure unit comprises data corresponding to a hypothesis and its corresponding counter-hypothesis, data corresponding to grounds that provide a basis for inference of the hypothesis or its corresponding counter-hypothesis, data corresponding to a warrant linking the grounds to the hypothesis or its corresponding counter-hypothesis, and data corresponding to backing that certifies the warrant. The hierarchical argument structure comprises a top level argument structure unit and a plurality of subordinate level argument structure units. Each of the plurality of subordinate argument structure units comprises at least a portion of the grounds of the argument structure unit to which it is subordinate. Program code located on each of a plurality of remote computers accepts input from one of a plurality of contributors. Each input comprises data corresponding to an argument structure unit in the hierarchical argument structure and supports the hypothesis or its corresponding counter-hypothesis. A second programming code is adapted to combine the inputs into a single hierarchical argument structure. A third computer program code is responsive to the second computer program code and is adapted to represent a degree of support for the hypothesis and its corresponding counter-hypothesis in the single hierarchical argument structure.

Guided particle swarm optimization method to solve general nonlinear optimization problems

NASA Astrophysics Data System (ADS)

Abdelhalim, Alyaa; Nakata, Kazuhide; El-Alem, Mahmoud; Eltawil, Amr

2018-04-01

The development of hybrid algorithms is becoming an important topic in the global optimization research area. This article proposes a new technique in hybridizing the particle swarm optimization (PSO) algorithm and the Nelder-Mead (NM) simplex search algorithm to solve general nonlinear unconstrained optimization problems. Unlike traditional hybrid methods, the proposed method hybridizes the NM algorithm inside the PSO to improve the velocities and positions of the particles iteratively. The new hybridization considers the PSO algorithm and NM algorithm as one heuristic, not in a sequential or hierarchical manner. The NM algorithm is applied to improve the initial random solution of the PSO algorithm and iteratively in every step to improve the overall performance of the method. The performance of the proposed method was tested over 20 optimization test functions with varying dimensions. Comprehensive comparisons with other methods in the literature indicate that the proposed solution method is promising and competitive.

Liposome-Cross-Linked Hybrid Hydrogels for Glutathione-Triggered Delivery of Multiple Cargo Molecules.

PubMed

Liang, Yingkai; Kiick, Kristi L

2016-02-08

Novel, liposome-cross-linked hybrid hydrogels cross-linked by the Michael-type addition of thiols with maleimides were prepared via the use of maleimide-functionalized liposome cross-linkers and thiolated polyethylene glycol (PEG) polymers. Gelation of the materials was confirmed by oscillatory rheology experiments. These hybrid hydrogels are rendered degradable upon exposure to thiol-containing molecules such as glutathione (GSH), via the incorporation of selected thioether succinimide cross-links between the PEG polymers and liposome nanoparticles. Dynamic light scattering (DLS) characterization confirmed that intact liposomes were released upon network degradation. Owing to the hierarchical structure of the network, multiple cargo molecules relevant for chemotherapies, namely doxorubicin (DOX) and cytochrome c, were encapsulated and simultaneously released from the hybrid hydrogels, with differential release profiles that were driven by degradation-mediated release and Fickian diffusion, respectively. This work introduces a facile approach for the development of advanced, hybrid drug delivery vehicles that exhibit novel chemical degradation.

Engineering hierarchical Diatom@CuO@MnO2 hybrid for high performance supercapacitor

NASA Astrophysics Data System (ADS)

Zhang, Yan; Guo, Wan Wan; Zheng, Tian Xu; Zhang, Yu Xin; Fan, Xing

2018-01-01

A rational and hierarchical Diatom@CuO@MnO2 hybrid was fabricated via a facile electroless copper plating technology, following by a one-pot hydrothermal reaction with KMnO4. Such unique architecture acts as a supercapacitor electrode, which exhibits a high specific capacitance (240 F g-1 at a current density of 0.5 A g-1), good rate capability (58.3% retention when the current density increases from 0.5 to 5 A g-1), and excellent electrochemical cycling stability (91.2% retention of the initial specific capacitance after 4000 cycles at a current density of 2 A g-1). The impressive electrochemical performance of this Diatom@CuO@MnO2 electrode ascribed to the synergistic effect between the CuO particles and MnO2 nanosheets. Therefore, it can be expected that this unique Diatom@CuO@MnO2 electrode may have great promise for the application in supercapacitors.

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.; Plaza, Antonio J.

2006-01-01

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product.

Hierarchical Tubular Structures Composed of Co3 O4 Hollow Nanoparticles and Carbon Nanotubes for Lithium Storage.

PubMed

Chen, Yu Ming; Yu, Le; Lou, Xiong Wen David

2016-05-10

Hierarchical tubular structures composed of Co3 O4 hollow nanoparticles and carbon nanotubes (CNTs) have been synthesized by an efficient multi-step route. Starting from polymer-cobalt acetate (Co(Ac)2 ) composite nanofibers, uniform polymer-Co(Ac)2 @zeolitic imidazolate framework-67 (ZIF-67) core-shell nanofibers are first synthesized via partial phase transformation with 2-methylimidazole in ethanol. After the selective dissolution of polymer-Co(Ac)2 cores, the resulting ZIF-67 tubular structures can be converted into hierarchical CNTs/Co-carbon hybrids by annealing in Ar/H2 atmosphere. Finally, the hierarchical CNT/Co3 O4 microtubes are obtained by a subsequent thermal treatment in air. Impressively, the as-prepared nanocomposite delivers a high reversible capacity of 1281 mAh g(-1) at 0.1 A g(-1) with exceptional rate capability and long cycle life over 200 cycles as an anode material for lithium-ion batteries. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Building a Lego wall: Sequential action selection.

PubMed

Arnold, Amy; Wing, Alan M; Rotshtein, Pia

2017-05-01

The present study draws together two distinct lines of enquiry into the selection and control of sequential action: motor sequence production and action selection in everyday tasks. Participants were asked to build 2 different Lego walls. The walls were designed to have hierarchical structures with shared and dissociated colors and spatial components. Participants built 1 wall at a time, under low and high load cognitive states. Selection times for correctly completed trials were measured using 3-dimensional motion tracking. The paradigm enabled precise measurement of the timing of actions, while using real objects to create an end product. The experiment demonstrated that action selection was slowed at decision boundary points, relative to boundaries where no between-wall decision was required. Decision points also affected selection time prior to the actual selection window. Dual-task conditions increased selection errors. Errors mostly occurred at boundaries between chunks and especially when these required decisions. The data support hierarchical control of sequenced behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Molecular level in silico studies for oncology. Direct models review

NASA Astrophysics Data System (ADS)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

A hybrid stochastic hierarchy equations of motion approach to treat the low temperature dynamics of non-Markovian open quantum systems

NASA Astrophysics Data System (ADS)

Moix, Jeremy M.; Cao, Jianshu

2013-10-01

The hierarchical equations of motion technique has found widespread success as a tool to generate the numerically exact dynamics of non-Markovian open quantum systems. However, its application to low temperature environments remains a serious challenge due to the need for a deep hierarchy that arises from the Matsubara expansion of the bath correlation function. Here we present a hybrid stochastic hierarchical equation of motion (sHEOM) approach that alleviates this bottleneck and leads to a numerical cost that is nearly independent of temperature. Additionally, the sHEOM method generally converges with fewer hierarchy tiers allowing for the treatment of larger systems. Benchmark calculations are presented on the dynamics of two level systems at both high and low temperatures to demonstrate the efficacy of the approach. Then the hybrid method is used to generate the exact dynamics of systems that are nearly impossible to treat by the standard hierarchy. First, exact energy transfer rates are calculated across a broad range of temperatures revealing the deviations from the Förster rates. This is followed by computations of the entanglement dynamics in a system of two qubits at low temperature spanning the weak to strong system-bath coupling regimes.

1D Ni-Co oxide and sulfide nanoarray/carbon aerogel hybrid nanostructures for asymmetric supercapacitors with high energy density and excellent cycling stability.

PubMed

Hao, Pin; Tian, Jian; Sang, Yuanhua; Tuan, Chia-Chi; Cui, Guanwei; Shi, Xifeng; Wong, C P; Tang, Bo; Liu, Hong

2016-09-15

The fabrication of supercapacitor electrodes with high energy density and excellent cycling stability is still a great challenge. A carbon aerogel, possessing a hierarchical porous structure, high specific surface area and electrical conductivity, is an ideal backbone to support transition metal oxides and bring hope to prepare electrodes with high energy density and excellent cycling stability. Therefore, NiCo 2 S 4 nanotube array/carbon aerogel and NiCo 2 O 4 nanoneedle array/carbon aerogel hybrid supercapacitor electrode materials were synthesized by assembling Ni-Co precursor needle arrays on the surface of the channel walls of hierarchical porous carbon aerogels derived from chitosan in this study. The 1D nanostructures grow on the channel surface of the carbon aerogel vertically and tightly, contributing to the enhanced electrochemical performance with ultrahigh energy density. The energy density of NiCo 2 S 4 nanotube array/carbon aerogel and NiCo 2 O 4 nanoneedle array/carbon aerogel hybrid asymmetric supercapacitors can reach up to 55.3 Wh kg -1 and 47.5 Wh kg -1 at a power density of 400 W kg -1 , respectively. These asymmetric devices also displayed excellent cycling stability with a capacitance retention of about 96.6% and 92% over 5000 cycles.

A hybrid stochastic hierarchy equations of motion approach to treat the low temperature dynamics of non-Markovian open quantum systems.

PubMed

Moix, Jeremy M; Cao, Jianshu

2013-10-07

The hierarchical equations of motion technique has found widespread success as a tool to generate the numerically exact dynamics of non-Markovian open quantum systems. However, its application to low temperature environments remains a serious challenge due to the need for a deep hierarchy that arises from the Matsubara expansion of the bath correlation function. Here we present a hybrid stochastic hierarchical equation of motion (sHEOM) approach that alleviates this bottleneck and leads to a numerical cost that is nearly independent of temperature. Additionally, the sHEOM method generally converges with fewer hierarchy tiers allowing for the treatment of larger systems. Benchmark calculations are presented on the dynamics of two level systems at both high and low temperatures to demonstrate the efficacy of the approach. Then the hybrid method is used to generate the exact dynamics of systems that are nearly impossible to treat by the standard hierarchy. First, exact energy transfer rates are calculated across a broad range of temperatures revealing the deviations from the Förster rates. This is followed by computations of the entanglement dynamics in a system of two qubits at low temperature spanning the weak to strong system-bath coupling regimes.

Facile fabrication of MnO x and N co-doped hierarchically porous carbon microspheres for high-performance supercapacitors

DOE PAGES

Yang, Ying; Yang, Feng; Lee, Sungsik; ...

2016-01-16

Facile fabrication of manganese oxide (MnO x, 0 < x < 2) and nitrogen (N) co-doped carbon microspheres (MnO x-N-CS) has been firstly developed by one-pot construction of Mn-functionalized melamine-formaldehyde (Mn-MF) resin spheres before pyrolysis. The resulting hybrids bear evenly dispersed MnO x and N moieties in situ anchored on hierarchically porous carbon microspheres formed simultaneously. The capacitive performance is greatly tailored by varying the Mn/melamine molar ratio in the synthetic mixture and pyrolysis temperature. It is found that the MnO x-N-CS hybrid (0.008 wt% Mn, pyrolyzed at 800 °C) exhibits the highest specific capacitance up to 258 F gmore » –1 at a scan rate of 1 mV s –1 (in 6 M KOH), and keeps a high capacitance retention ratio of 98% after 5000 cycles. The synergism between MnO x, N moieties and carbon spheres proves to be responsible for the remarkably improved performance, as compared to the pure carbon sphere and MnO x (N)-doped carbon sphere. Lastly, the well-developed MnO x-N-CS hybrids highlight the great potentials for widespread supercapacitor applications.« less

Graphene oxide reinforced core-shell structured Ag@Cu2O with tunable hierarchical morphologies and their morphology-dependent electrocatalytic properties for bio-sensing applications.

PubMed

Gan, Tian; Wang, Zhikai; Shi, Zhaoxia; Zheng, Dongyun; Sun, Junyong; Liu, Yanming

2018-07-30

In this study, a facile solution approach was developed for the synthesis of a series of core-shell structured Ag@Cu 2 O nanocrystals of various shapes including triangles, spheres, and cubes with well-defined stable heterojunctions. The electrooxidation of dopamine (DA), uric acid (UA), guanine (G), and adenine (A) using these hybrids revealed morphology-dependent sensing properties, with activities and accumulation ability following the order, triangular Ag@Cu 2 O > spherical Ag@Cu 2 O > cubic Ag@Cu 2 O. Further, we constructed a novel graphene oxide (GO) nanosheet-reinforced triangular Ag@Cu 2 O ternary hetero-nanostructure. Such a hybrid with a three-dimensional interconnected hierarchical architecture is suitable for catalysis, since it not only leads to improved interfacial electron transfer, but also readily exposes the highly catalytic Ag@Cu 2 O to the reactants. Therefore, more enhanced electrochemical activities were observed for the oxidation of DA, UA, G, and A. This study provides an efficient way to synthesize morphology-controlled Ag@Cu 2 O heterogeneous catalysts for the fabrication of potential biosensors, and also opens up attractive avenues in the design of multifunctional ternary noble metal-semiconductor-carbon hybrids. Copyright © 2018 Elsevier B.V. All rights reserved.

Multi-objective decoupling algorithm for active distance control of intelligent hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Luo, Yugong; Chen, Tao; Li, Keqiang

2015-12-01

The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.

A hybrid phenomenological model for ferroelectroelastic ceramics. Part II: Morphotropic PZT ceramics

NASA Astrophysics Data System (ADS)

Stark, S.; Neumeister, P.; Balke, H.

2016-10-01

In this part II of a two part series, the rate-independent hybrid phenomenological constitutive model introduced in part I is modified to account for the material behavior of morphotropic lead zirconate titanate ceramics (PZT ceramics). The modifications are based on a discussion of the available literature results regarding the micro-structure of these materials. In particular, a monoclinic phase and a highly simplified representation of the hierarchical structure of micro-domains and nano-domains observed experimentally are incorporated into the model. It is shown that experimental data for the commercially available morphotropic PZT material PIC151 (PI Ceramic GmbH, Lederhose, Germany) can be reproduced and predicted based on the modified hybrid model.

Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

ERIC Educational Resources Information Center

Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung

2016-01-01

The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…

Bayesian techniques for analyzing group differences in the Iowa Gambling Task: A case study of intuitive and deliberate decision-makers.

PubMed

Steingroever, Helen; Pachur, Thorsten; Šmíra, Martin; Lee, Michael D

2018-06-01

The Iowa Gambling Task (IGT) is one of the most popular experimental paradigms for comparing complex decision-making across groups. Most commonly, IGT behavior is analyzed using frequentist tests to compare performance across groups, and to compare inferred parameters of cognitive models developed for the IGT. Here, we present a Bayesian alternative based on Bayesian repeated-measures ANOVA for comparing performance, and a suite of three complementary model-based methods for assessing the cognitive processes underlying IGT performance. The three model-based methods involve Bayesian hierarchical parameter estimation, Bayes factor model comparison, and Bayesian latent-mixture modeling. We illustrate these Bayesian methods by applying them to test the extent to which differences in intuitive versus deliberate decision style are associated with differences in IGT performance. The results show that intuitive and deliberate decision-makers behave similarly on the IGT, and the modeling analyses consistently suggest that both groups of decision-makers rely on similar cognitive processes. Our results challenge the notion that individual differences in intuitive and deliberate decision styles have a broad impact on decision-making. They also highlight the advantages of Bayesian methods, especially their ability to quantify evidence in favor of the null hypothesis, and that they allow model-based analyses to incorporate hierarchical and latent-mixture structures.

A hybrid fuzzy logic/constraint satisfaction problem approach to automatic decision making in simulation game models.

PubMed

Braathen, Sverre; Sendstad, Ole Jakob

2004-08-01

Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.

Design and synthesis of organic-inorganic hybrid capsules for biotechnological applications.

PubMed

Shi, Jiafu; Jiang, Yanjun; Wang, Xiaoli; Wu, Hong; Yang, Dong; Pan, Fusheng; Su, Yanlei; Jiang, Zhongyi

2014-08-07

Organic-inorganic hybrid capsules, which typically possess a hollow lumen and a hybrid wall, have emerged as a novel and promising class of hybrid materials and have attracted enormous attention. In comparison to polymeric capsules or inorganic capsules, the hybrid capsules combine the intrinsic physical/chemical properties of the organic and inorganic moieties, acquire more degrees of freedom to manipulate multiple interactions, create hierarchical structures and integrate multiple functionalities. Thus, the hybrid capsules exhibit superior mechanical strength (vs. polymeric capsules) and diverse functionalities (vs. inorganic capsules), which may give new opportunities to produce high-performance materials. Much effort has been devoted to exploring innovative and effective methods for the synthesis of hybrid capsules that exhibit desirable performance in target applications. This tutorial review firstly presents a brief description of the capsular structure and hybrid materials in nature, then classifies the hybrid capsules into molecule-hybrid capsules and nano-hybrid capsules based upon the size of the organic and inorganic moieties in the capsule wall, followed by a detailed discussion of the design and synthesis of the hybrid capsules. For each kind of hybrid capsule, the state-of-the-art synthesis methods are described in detail and a critical comment is embedded. The applications of these hybrid capsules in biotechnological areas (biocatalysis, drug delivery, etc.) have also been summarized. Hopefully, this review will offer a perspective and guidelines for the future research and development of hybrid capsules.

Corticosterone manipulation reveals differences in hierarchical organization of multidimensional reproductive trade-offs in r-strategist and K-strategist females.

PubMed

Lancaster, L T; Hazard, L C; Clobert, J; Sinervo, B R

2008-03-01

Life history trade-offs are often hierarchical with decisions at one level affecting lower level trade-offs. We investigated trade-off structure in female side-blotched lizards (Uta stansburiana), which exhibit two evolved strategies: yellow-throated females are K-strategists and orange-throated are r-strategists. Corticosterone treatment was predicted to differentially organize these females' reproductive decisions. Corticosterone-treated yellow females suppressed reproduction but survived well, and augmented egg mass without decreasing clutch size. Conversely, corticosterone enhanced mortality and reproductive rates in orange females, and increased egg mass only after lengthy exposure. Corticosterone did not affect post-laying condition, suggesting that corticosterone increased egg mass through enhanced energy acquisition (income breeding). Corticosterone enhanced survival of lightweight females, but decreased survival of heavy females, introducing a foraging vs. predation trade-off. We conclude that rather than being a direct, functional relationship, observed trade-offs between offspring size and number represent evolved differences in hierarchical organization of multidimensional trade-offs, particularly in response to stress.

Hierarchically porous materials from layer-by-layer photopolymerization of high internal phase emulsions.

PubMed

Sušec, Maja; Ligon, Samuel Clark; Stampfl, Jürgen; Liska, Robert; Krajnc, Peter

2013-06-13

A combination of high internal phase emulsion (HIPE) templating and additive manufacturing technology (AMT) is applied for creating hierarchical porosity within an acrylate and acrylate/thiol-based polymer network. The photopolymerizable formulation is optimized to produce emulsions with a volume fraction of droplet phase greater than 80 vol%. Kinetic stability of the emulsions is sufficient enough to withstand in-mold curing or computer-controlled layer-by-layer stereolithography without phase separation. By including macroscale cellular cavities within the build file, a level of controlled porosity is created simultaneous to the formation of the porous microstructure of the polyHIPE. The hybrid HIPE-AMT technique thus provides hierarchically porous materials with mechanical properties tailored by the addition of thiol chain transfer agent. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Efficient, Recyclable, and Stable Immobilized Biocatalyst Based on Bioinspired Microcapsules-in-Hydrogel Scaffolds.

PubMed

Zhang, Shaohua; Jiang, Zhongyi; Shi, Jiafu; Wang, Xueyan; Han, Pingping; Qian, Weilun

2016-09-28

Design and preparation of high-performance immobilized biocatalysts with exquisite structures and elucidation of their profound structure-performance relationship are highly desired for green and sustainable biotransformation processes. Learning from nature has been recognized as a shortcut to achieve such an impressive goal. Loose connective tissue, which is composed of hierarchically organized cells by extracellular matrix (ECM) and is recognized as an efficient catalytic system to ensure the ordered proceeding of metabolism, may offer an ideal prototype for preparing immobilized biocatalysts with high catalytic activity, recyclability, and stability. Inspired by the hierarchical structure of loose connective tissue, we prepared an immobilized biocatalyst enabled by microcapsules-in-hydrogel (MCH) scaffolds via biomimetic mineralization in agarose hydrogel. In brief, the in situ synthesized hybrid microcapsules encapsulated with glucose oxidase (GOD) are hierarchically organized by the fibrous framework of agarose hydrogel, where the fibers are intercalated into the capsule wall. The as-prepared immobilized biocatalyst shows structure-dependent catalytic performance. The porous hydrogel permits free diffusion of glucose molecules (diffusion coefficient: ∼6 × 10(-6) cm(2) s(-1), close to that in water) and retains the enzyme activity as much as possible after immobilization (initial reaction rate: 1.5 × 10(-2) mM min(-1)). The monolithic macroscale of agarose hydrogel facilitates the easy recycling of the immobilized biocatalyst (only by using tweezers), which contributes to the nonactivity decline during the recycling test. The fiber-intercalating structure elevates the mechanical stability of the in situ synthesized hybrid microcapsules, which inhibits the leaching and enhances the stability of the encapsulated GOD, achieving immobilization efficiency of ∼95%. This study will, therefore, provide a generic method for the hierarchical organization of (bio)active materials and the rational design of novel (bio)catalysts.

Decision making in prioritization of required operational capabilities

NASA Astrophysics Data System (ADS)

Andreeva, P.; Karev, M.; Kovacheva, Ts.

2015-10-01

The paper describes an expert heuristic approach to prioritization of required operational capabilities in the field of defense. Based on expert assessment and by application of the method of Analytical Hierarchical Process, a methodology for their prioritization has been developed. It has been applied to practical simulation decision making games.

Administrative Leadership and the Democratic Community as a Social Ideal.

ERIC Educational Resources Information Center

Rizvi, Fazal

Democratic participation in education suggests that communities will be served best when decision-making is decentralized and when people--teachers, parents, and students alike--are encouraged to participate directly in making decisions that affect them. In contrast, the notion of administrative leadership implies hierarchical elevation of chief…

Hierarchical effects on target detection and conflict monitoring

PubMed Central

Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong

2016-01-01

Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989

A Class of Clowns: Spontaneous Joking in Computer-Assisted Discussions.

ERIC Educational Resources Information Center

Holcomb, Christopher

1997-01-01

Finds that joking in computer-mediated communication constitutes a hybrid form of discourse, mingling the conventions of print and speech. Notes that students use typography and space to better capture the rhythms and inflections of oral joking, but such joking instantly organizes participants into hierarchically differentiated groups, creating…

Learning from professionals: Exploring cognitive rehabilitation strategies for the definition of the functional requirements of a telerehabilitation platform.

PubMed

Rosso, Giovanni; Frisiello, Antonella; Trizio, Marco; Mosso, Cristina O; Bazzani, Marco

2018-04-01

In the past few years, the advances in Information and Communication Technology (ICT) led to the development of platforms and applications that aim to support cognitive rehabilitation therapy that contributes to extend patients' treatment at home. In our research we adopted the Human Centered Approach to design a cognitive rehabilitation platform that is able to provide tools and features tailored to the professional needs and strategies and also able to engage patients in their treatment process. In order to explore the clinicians' point of view on the neuropsychological intervention strategies, we applied two different techniques often used in human factors research: the Critical Decision Method to study professionals' strategies with a descriptive perspective, and the Hierarchical Task Analysis to analyze the processes with a normative view. The results of our research showed that the hybrid approach adopted allowed us to have a better focus on the cognitive rehabilitation process and on the professionals' decision making mechanism. This led to a better understanding of functional requirements for supporting clinician's strategic decision making, in terms of personalization of treatments, cognitive exercises settings and feedback customization. In conclusion, our research highlights the value of the CDM to focus deeply on which functionalities professionals require from a cognitive telerehabilitation system and allowed us to design more precisely clinician-patients interactions inside the system compared to prescriptive methods currently used. Our study offers contribution to the comprehension of the rehabilitation processes, suggesting the positive impacts of an "extended" clinic treatment by adopting a flexible and adaptable tool. Copyright © 2017. Published by Elsevier Ltd.

A Theoretical Analysis of Why Hybrid Ensembles Work.

PubMed

Hsu, Kuo-Wei

2017-01-01

Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

Using statistical anomaly detection models to find clinical decision support malfunctions.

PubMed

Ray, Soumi; McEvoy, Dustin S; Aaron, Skye; Hickman, Thu-Trang; Wright, Adam

2018-05-11

Malfunctions in Clinical Decision Support (CDS) systems occur due to a multitude of reasons, and often go unnoticed, leading to potentially poor outcomes. Our goal was to identify malfunctions within CDS systems. We evaluated 6 anomaly detection models: (1) Poisson Changepoint Model, (2) Autoregressive Integrated Moving Average (ARIMA) Model, (3) Hierarchical Divisive Changepoint (HDC) Model, (4) Bayesian Changepoint Model, (5) Seasonal Hybrid Extreme Studentized Deviate (SHESD) Model, and (6) E-Divisive with Median (EDM) Model and characterized their ability to find known anomalies. We analyzed 4 CDS alerts with known malfunctions from the Longitudinal Medical Record (LMR) and Epic® (Epic Systems Corporation, Madison, WI, USA) at Brigham and Women's Hospital, Boston, MA. The 4 rules recommend lead testing in children, aspirin therapy in patients with coronary artery disease, pneumococcal vaccination in immunocompromised adults and thyroid testing in patients taking amiodarone. Poisson changepoint, ARIMA, HDC, Bayesian changepoint and the SHESD model were able to detect anomalies in an alert for lead screening in children and in an alert for pneumococcal conjugate vaccine in immunocompromised adults. EDM was able to detect anomalies in an alert for monitoring thyroid function in patients on amiodarone. Malfunctions/anomalies occur frequently in CDS alert systems. It is important to be able to detect such anomalies promptly. Anomaly detection models are useful tools to aid such detections.

Fault-tolerant continuous flow systems modelling

NASA Astrophysics Data System (ADS)

Tolbi, B.; Tebbikh, H.; Alla, H.

2017-01-01

This paper presents a structural modelling of faults with hybrid Petri nets (HPNs) for the analysis of a particular class of hybrid dynamic systems, continuous flow systems. HPNs are first used for the behavioural description of continuous flow systems without faults. Then, faults' modelling is considered using a structural method without having to rebuild the model to new. A translation method is given in hierarchical way, it gives a hybrid automata (HA) from an elementary HPN. This translation preserves the behavioural semantics (timed bisimilarity), and reflects the temporal behaviour by giving semantics for each model in terms of timed transition systems. Thus, advantages of the power modelling of HPNs and the analysis ability of HA are taken. A simple example is used to illustrate the ideas.

Group Decision Support System to Aid the Process of Design and Maintenance of Large Scale Systems

DTIC Science & Technology

1992-03-23

from a fuzzy set of user requirements. The overall objective of the project is to develop a system combining the characteristics of a compact computer... AHP ) for hierarchical prioritization. 4) Individual Evaluation and Selection of Alternatives - Allows the decision maker to individually evaluate...its concept of outranking relations. The AHP method supports complex decision problems by successively decomposing and synthesizing various elements

Coordinating Information and Decisions of Hierarchical Distributed Decision Units in Crises

DTIC Science & Technology

1997-08-01

learning. Carley, K. (1988) Social stability and constructionism . Pittsburgh: Social and Decision Sciences Working Paper Series, Carnegie Mellon...Behavioral and Social Sciences Approved for public release; distribution is unlimited. U.S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES...it is no longer needed. Please do not return it to the U.S. Army Research Institute for the Behavioral and Social Sciences. NOTE: The views, opinions

The drift diffusion model as the choice rule in reinforcement learning.

PubMed

Pedersen, Mads Lund; Frank, Michael J; Biele, Guido

2017-08-01

Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.

The drift diffusion model as the choice rule in reinforcement learning

PubMed Central

Frank, Michael J.

2017-01-01

Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyper-activity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups. PMID:27966103

A Decision-Oriented Investigation of Air Force Civil Engineering’s Operations Branch and the Implications for a Decision Support System.

DTIC Science & Technology

1984-09-01

information when making a decision [ Szilagyi and Wallace , 1983:3201." Driver and Mock used cognitive complexity ideas to develop this two dimensional...flexible AMOUNT OF INFORMATION USED High hierarchic integrative Figure 6. Cognitive Complexity Model ( Szilagyi and Wallace , 1983:321) Decisive Style. The...large amount of inform- ation. However, he processes this information with a multiple focus approach ( Szilagyi and Wallace , 1983:320-321). 26 McKenney

The hierarchical expert tuning of PID controllers using tools of soft computing.

PubMed

Karray, F; Gueaieb, W; Al-Sharhan, S

2002-01-01

We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.

RSCREEN and OPGEN: Two Problem Structuring Decision Aids Which Employ Decision Templates

DTIC Science & Technology

1980-10-01

example, a hierarchical taxonomy could be provided to the user (something like a Dewey Decimal System for models), either as a complete directory or as...Attention: DDC -TC Cameron Station Alexandria, Virginia 22314 DCASMA Baltimore Office 1 copy Attention: Mrs. Betty L. Drisk-11 300 East Joppa Road Towson

Parental Influences, Career Decision-Making Attributions, and Self-Efficacy: Differences for Men and Women?

ERIC Educational Resources Information Center

Lease, Suzanne H.; Dahlbeck, David T.

2009-01-01

This study investigated the relations of maternal and paternal attachment, parenting styles, and career locus of control to college students' career decision self-efficacy and explored whether these relations differed by student gender. Data analysis using hierarchical multiple regression revealed that attachment was relevant for females' career…

Hierarchically porous Li3VO4/C nanocomposite as an advanced anode material for high-performance lithium-ion capacitors

NASA Astrophysics Data System (ADS)

Xu, Xuena; Niu, Feier; Zhang, Dapeng; Chu, Chenxiao; Wang, Chunsheng; Yang, Jian; Qian, Yitai

2018-04-01

Lithium-ion capacitors, as a hybrid electrochemical energy storage device, realize high specific energy and power density within one device, thus attracting extensive attention. Here, hierarchically porous Li3VO4/C nanocomposite is prepared by a solvo-thermal reaction, followed with a post-annealing process. This composite has macropores at the center and mesopores in the wall, thus effectively promoting electrolyte penetration and structure stability upon cycling simultaneously. Compared to mesoporous Li3VO4, the enhanced rate capability and specific capacity of hierarchically porous Li3VO4/C indicate the synergistic effect of mesopores and macropores. Inspired by these results, this composite is coupled with mesoporous carbon (CMK-3) for lithium-ion capacitors, generating a specific energy density of 105 Wh kg-1 at a power density of 188 W kg-1. Even if the power density increases to 9.3 kW kg-1, the energy density still remains 62 Wh kg-1. All these results demonstrate the promising potential of hierarchically porous Li3VO4 in lithium ion capacitors.

Biomineralization-inspired synthesis of functional organic/inorganic hybrid materials: organic molecular control of self-organization of hybrids.

PubMed

Arakaki, Atsushi; Shimizu, Katsuhiko; Oda, Mayumi; Sakamoto, Takeshi; Nishimura, Tatsuya; Kato, Takashi

2015-01-28

Organisms produce various organic/inorganic hybrid materials, which are called biominerals. They form through the self-organization of organic molecules and inorganic elements under ambient conditions. Biominerals often have highly organized and hierarchical structures from nanometer to macroscopic length scales, resulting in their remarkable physical and chemical properties that cannot be obtained by simple accumulation of their organic and inorganic constituents. These observations motivate us to create novel functional materials exhibiting properties superior to conventional materials--both synthetic and natural. Herein, we introduce recent progress in understanding biomineralization processes at the molecular level and the development of organic/inorganic hybrid materials by these processes. We specifically outline fundamental molecular studies on silica, iron oxide, and calcium carbonate biomineralization and describe material synthesis based on these mechanisms. These approaches allow us to design a variety of advanced hybrid materials with desired morphologies, sizes, compositions, and structures through environmentally friendly synthetic routes using functions of organic molecules.

Hierarchical bioceramic scaffolds with 3D-plotted macropores and mussel-inspired surface nanolayers for stimulating osteogenesis

NASA Astrophysics Data System (ADS)

Xu, Mengchi; Zhai, Dong; Xia, Lunguo; Li, Hong; Chen, Shiyi; Fang, Bing; Chang, Jiang; Wu, Chengtie

2016-07-01

The hierarchical structure of biomaterials plays an important role in the process of tissue reconstruction and regeneration. 3D-plotted scaffolds have been widely used for bone tissue engineering due to their controlled macropore structure and mechanical properties. However, the lack of micro- or nano-structures on the strut surface of 3D-plotted scaffolds, especially for bioceramic scaffolds, limits their biological activity. Inspired by the adhesive versatility of mussels and the active ion-chelating capacity of polydopamine, we set out to prepare a hierarchical bioceramic scaffold with controlled macropores and mussel-inspired surface nanolayers by combining the 3D-plotting technique with the polydopamine/apatite hybrid strategy in order to synergistically accelerate the osteogenesis and angiogenesis. β-Tricalcium phosphate (TCP) scaffolds were firstly 3D-plotted and then treated in dopamine-Tris/HCl and dopamine-SBF solutions to obtain TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds, respectively. It was found that polydopamine/apatite hybrid nanolayers were formed on the surface of both TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds and TCP-DOPA-SBF scaffolds induced apatite mineralization for the second time during the cell culture. As compared to TCP scaffolds, both TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds significantly promoted the osteogenesis of bone marrow stromal cells (BMSCs) as well as the angiogenesis of human umbilical vein endothelial cells (HUVECs), and the TCP-DOPA-SBF group presented the highest in vitro osteogenic/angiogenic activity among the three groups. Furthermore, both TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds significantly improved the formation of new bone in vivo as compared to TCP scaffolds without a nanostructured surface. Our results suggest that the utilization of a mussel-inspired Ca, P-chelated polydopamine nanolayer on 3D-plotted bioceramic scaffolds is a viable and effective strategy to construct a hierarchical structure for synergistically accelerating osteogenesis.The hierarchical structure of biomaterials plays an important role in the process of tissue reconstruction and regeneration. 3D-plotted scaffolds have been widely used for bone tissue engineering due to their controlled macropore structure and mechanical properties. However, the lack of micro- or nano-structures on the strut surface of 3D-plotted scaffolds, especially for bioceramic scaffolds, limits their biological activity. Inspired by the adhesive versatility of mussels and the active ion-chelating capacity of polydopamine, we set out to prepare a hierarchical bioceramic scaffold with controlled macropores and mussel-inspired surface nanolayers by combining the 3D-plotting technique with the polydopamine/apatite hybrid strategy in order to synergistically accelerate the osteogenesis and angiogenesis. β-Tricalcium phosphate (TCP) scaffolds were firstly 3D-plotted and then treated in dopamine-Tris/HCl and dopamine-SBF solutions to obtain TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds, respectively. It was found that polydopamine/apatite hybrid nanolayers were formed on the surface of both TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds and TCP-DOPA-SBF scaffolds induced apatite mineralization for the second time during the cell culture. As compared to TCP scaffolds, both TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds significantly promoted the osteogenesis of bone marrow stromal cells (BMSCs) as well as the angiogenesis of human umbilical vein endothelial cells (HUVECs), and the TCP-DOPA-SBF group presented the highest in vitro osteogenic/angiogenic activity among the three groups. Furthermore, both TCP-DOPA-Tris and TCP-DOPA-SBF scaffolds significantly improved the formation of new bone in vivo as compared to TCP scaffolds without a nanostructured surface. Our results suggest that the utilization of a mussel-inspired Ca, P-chelated polydopamine nanolayer on 3D-plotted bioceramic scaffolds is a viable and effective strategy to construct a hierarchical structure for synergistically accelerating osteogenesis. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01952h

Decision-making in schizophrenia: A predictive-coding perspective.

PubMed

Sterzer, Philipp; Voss, Martin; Schlagenhauf, Florian; Heinz, Andreas

2018-05-31

Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences. Copyright © 2018 Elsevier Inc. All rights reserved.

Spontaneous interfacial reaction between metallic copper and PBS to form cupric phosphate nanoflower and its enzyme hybrid with enhanced activity.

PubMed

He, Guangli; Hu, Weihua; Li, Chang Ming

2015-11-01

We herein report the spontaneous interfacial reaction between copper foil with 0.01 M phosphate buffered saline (PBS) to form free-standing cupric phosphate (Cu3(PO4)2) nanoflowers at ambient temperature. The underlying chemistry was thoroughly investigated and it is found that the formation of nanoflower is synergistically caused by dissolved oxygen, chlorine ions and phosphate ions. Enzyme-Cu3(PO4)2 hybrid nanoflower was further prepared successfully by using an enzyme-dissolving PBS solution and the enzymes in the hybrid exhibit enhanced biological activity. This work provides a facile route for large-scale synthesis of hierarchical inorganic and functional protein-inorganic hybrid architectures via a simple one-step solution-immersion reaction without using either template or surfactant, thus offering great potential for biosensing application among others. Copyright © 2015 Elsevier B.V. All rights reserved.

One-step synthesis of free-standing α-Ni(OH)2 nanosheets on reduced graphene oxide for high-performance supercapacitors

NASA Astrophysics Data System (ADS)

Dong, Bitao; Zhou, Han; Liang, Jin; Zhang, Lusi; Gao, Guoxin; Ding, Shujiang

2014-10-01

In this work, a hierarchical hybrid structure of reduced graphene oxide (rGO) supported ultrathin α-Ni(OH)2 nanosheets (denoted as α-Ni(OH)2@rGO NSs) has been developed successfully via an environmentally friendly one-step solution method. The resulting product of α-Ni(OH)2@rGO NSs was further characterized by scanning electron microscope, transmission electron microscope, x-ray diffraction, Raman spectroscopy, x-ray photoelectron spectroscopy, and Brunauer-Emmett-Teller. The ultrathin α-Ni(OH)2 nanosheets of around 6 nm in thickness are uprightly coated on the double sides of rGO substrate. When evaluated as electrodes for supercapacitors, the hybrid α-Ni(OH)2@rGO NSs demonstrate excellent supercapacitor performance and cycling stability, compared with the self-aggregated α-Ni(OH)2 powder. Even after 2000 cycles, the hybrid electrodes still can deliver a specific capacitance of 1300 F g-1 at the current density of 5 A g-1, corresponding to no capacity loss of the initial cycle. Such excellent electrochemical performance should be attributed to the ultrathin, free-standing, and hierarchical nanosheets of α-Ni(OH)2, which not only promote efficient charge transport and facilitate the electrolyte diffusion, but also prevent aggregation of electro-active materials effectively during the charge-discharge process.

One-step synthesis of free-standing α-Ni(OH)₂ nanosheets on reduced graphene oxide for high-performance supercapacitors.

PubMed

Dong, Bitao; Zhou, Han; Liang, Jin; Zhang, Lusi; Gao, Guoxin; Ding, Shujiang

2014-10-31

In this work, a hierarchical hybrid structure of reduced graphene oxide (rGO) supported ultrathin α-Ni(OH)2 nanosheets (denoted as α-Ni(OH)2@rGO NSs) has been developed successfully via an environmentally friendly one-step solution method. The resulting product of α-Ni(OH)2@rGO NSs was further characterized by scanning electron microscope, transmission electron microscope, x-ray diffraction, Raman spectroscopy, x-ray photoelectron spectroscopy, and Brunauer-Emmett-Teller. The ultrathin α-Ni(OH)2 nanosheets of around 6 nm in thickness are uprightly coated on the double sides of rGO substrate. When evaluated as electrodes for supercapacitors, the hybrid α-Ni(OH)2@rGO NSs demonstrate excellent supercapacitor performance and cycling stability, compared with the self-aggregated α-Ni(OH)2 powder. Even after 2000 cycles, the hybrid electrodes still can deliver a specific capacitance of 1300 F g(-1) at the current density of 5 A g(-1), corresponding to no capacity loss of the initial cycle. Such excellent electrochemical performance should be attributed to the ultrathin, free-standing, and hierarchical nanosheets of α-Ni(OH)2, which not only promote efficient charge transport and facilitate the electrolyte diffusion, but also prevent aggregation of electro-active materials effectively during the charge-discharge process.

Design and construction of three-dimensional CuO/polyaniline/rGO ternary hierarchical architectures for high performance supercapacitors

NASA Astrophysics Data System (ADS)

Zhu, Sheng; Wu, Mi; Ge, Mei-Hong; Zhang, Hui; Li, Shi-Kuo; Li, Chuan-Hao

2016-02-01

Rational design in terms of component and microstructure and fabrication of electrochemical electrodes are crucially important towards superior energy storage device. Herein, we report a novel CuO-PANI-rGO ternary hybrid electrode self-assembled by an in situ polymerization method combined with hydrothermal route for electrochemical capacitor. Well-defined CuO hierarchical architecture is synthesized by the spontaneous oxidization of Cu nanowire. PANI acts as not only binder for anchoring CuO architecture on rGO surface, but also charge transport channels, and high specific capacitance donor to the whole electrode matrix. The typical CuO-PANI-rGO ternary hybrid electrode can be reversibly cycled in a high voltage region up to 1.2 V. And it displays a maximum specific capacitance of 634.4 F g-1 and a high energy density of 126.8 Wh kg-1 with a power density of 114.2 kW kg-1 at a current density of 1.0 A g-1. Furthermore, the ternary hybrid electrode exhibits great cycle life with 97.4% specific capacitance retention after 10000 cycles. Those excellent performances are proposed to derive from the well-defined nanostructure, conductive porous microstructure and homogenously contact. This study might be important for designing the unique structure and component electrode for achieving high performance energy storage device.

Hierarchical MnO2 nanowire/graphene hybrid fibers with excellent electrochemical performance for flexible solid-state supercapacitors

NASA Astrophysics Data System (ADS)

Ma, Wujun; Chen, Shaohua; Yang, Shengyuan; Chen, Wenping; Cheng, Yanhua; Guo, Yiwei; Peng, Shengjie; Ramakrishna, Seeram; Zhu, Meifang

2016-02-01

Towards rapid development of lightweight, flexible, and even wearable electronics, a highly efficient energy-storage device is required for their energy supply management. Graphene fiber-based supercapacitor is considered as one of the promising candidates because of the remarkable mechanical and electrical properties of graphene fibers. However, supercapacitors based on bare graphene fibers generally suffer a low capacitance, which certainly restricts their potentially wide applications. In this work, hierarchically structured MnO2 nanowire/graphene hybrid fibers are fabricated through a simple, scalable wet-spinning method. The hybrid fibers form mesoporous structure with large specific surface area of 139.9 m2 g-1. The mass loading of MnO2 can be as high as 40 wt%. Due to the synergistic effect between MnO2 nanowires and graphene, the main pseudocapacitance of MnO2 and the electric double-layer capacitance of graphene are improved simultaneously. In view of the practical demonstration, a highly flexible solid-state supercapacitor is fabricated by twisting of two MnO2/graphene fibers coated by polyvinyl alcohol/H3PO4 electrolyte. The supercapacitor exhibits a high volumetric capacitance (66.1 F cm-3, normalized by the total volume of two fiber electrodes), excellent cycling stability (96% capacitance retention over 10,000 cycles), high energy and power density (5.8 mWh cm-3 and 0.51 W cm-3, respectively).

Synthesis and thermal responsiveness of self-assembled gold nanoclusters.

PubMed

Ren, Shenqiang; Lim, Sung-Keun; Gradecak, Silvija

2010-09-14

A simple and versatile approach was developed to generate hierarchical assemblies of ultra-small gold nanocluster thin films using the combination of galvanic reaction and a block copolymer coordinated with gold complex. Variation of the temperature allows effective control over the optical response of these stimuli-responsive organic-nanocluster hybrid structures.

Three-Dimensional Hierarchical MoS2 Nanosheets/Ultralong N-Doped Carbon Nanotubes as High-Performance Electromagnetic Wave Absorbing Material.

PubMed

Liu, Lianlian; Zhang, Shen; Yan, Feng; Li, Chunyan; Zhu, Chunling; Zhang, Xitian; Chen, Yujin

2018-04-25

Here, we report a simple method to grow thin MoS 2 nanosheets (NSs) on the ultralong nitrogen-doped carbon nanotubes through anion-exchange reaction. The MoS 2 NSs are grown on ultralong nitrogen-doped carbon nanotube surfaces, leading to an interesting three-dimensional hierarchical structure. The fabricated hybrid nanotubes have a length of approximately 100 μm, where the MoS 2 nanosheets have a thickness of less than 7.5 nm. The hybrid nanotubes show excellent electromagnetic wave attenuation performance, with the effective absorption bandwidth of 5.4 GHz at the thicknesses of 2.5 mm, superior to the pure MoS 2 nanosheets and the MoS 2 nanosheets grown on the short N-doped carbon nanotube surfaces. The experimental results indicate that the direct growth of MoS 2 on the ultralong nitrogen-doped carbon nanotube surfaces is a key factor for the enhanced electromagnetic wave attenuation property. The results open the avenue for the development of ultralong transition metal dichalcogenides for electromagnetic wave absorbers.

A Theoretical Analysis of Why Hybrid Ensembles Work

PubMed Central

2017-01-01

Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles. PMID:28255296

Synthesis of NiMn-LDH Nanosheet@Ni3S2 Nanorod Hybrid Structures for Supercapacitor Electrode Materials with Ultrahigh Specific Capacitance.

PubMed

Yu, Shuai; Zhang, Yingxi; Lou, Gaobo; Wu, Yatao; Zhu, Xinqiang; Chen, Hao; Shen, Zhehong; Fu, Shenyuan; Bao, Binfu; Wu, Limin

2018-03-27

One of the key challenges for pseudocapacitive electrode materials with highly effective capacitance output and future practical applications is how to rationally construct hierarchical and ordered hybrid nanoarchitecture through the simple process. Herein, we design and synthesize a novel NiMn-layered double hydroxide nanosheet@Ni 3 S 2 nanorod hybrid array supported on porous nickel foam via a one-pot hydrothermal method. Benefited from the ultrathin and rough nature, the well-defined porous structure of the hybrid array, as well as the synergetic effect between NiMn-layered double hydroxide nanosheets and Ni 3 S 2 nanorods, the as-fabricated hybrid array-based electrode exhibits an ultrahigh specific capacitance of 2703 F g -1 at 3 A g -1 . Moreover, the asymmetric supercapacitor with this hybrid array as a positive electrode and wood-derived activated carbon as a negative electrode demonstrates high energy density (57 Wh Kg -1 at 738 W Kg -1 ) and very good electrochemical cycling stability.

Automated Hierarchical to CODASYL (Conference on Data Systems Languages) Database Interface Schema Translator.

DTIC Science & Technology

1983-12-16

management system (DBMS) is to record and maintain information used by an organization in the organization’s decision-making process. Some advantages of a...independence. Database Management Systems are classified into three major models; relational, network, and hierarchical. Each model uses a software...feeling impedes the overall effectiveness of the 4-" Acquisition Management Information System (AMIS), which currently uses S2k. The size of the AMIS

Theory of the decision/problem state

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A theory of the decision-problem state was introduced and elaborated. Starting with the basic model of a decision-problem condition, an attempt was made to explain how a major decision-problem may consist of subsets of decision-problem conditions composing different condition sequences. In addition, the basic classical decision-tree model was modified to allow for the introduction of a series of characteristics that may be encountered in an analysis of a decision-problem state. The resulting hierarchical model reflects the unique attributes of the decision-problem state. The basic model of a decision-problem condition was used as a base to evolve a more complex model that is more representative of the decision-problem state and may be used to initiate research on decision-problem states.

Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

Current Scientific Approaches to Decision Making in Complex Systems. 3. Volume 2. Conference Position Papers

DTIC Science & Technology

1980-01-01

Search: Traffic on a Multi- dimensional Structure R. i. Atkin, University of Essex, England b. Annex. Volume 3: Decision: Foundation and Practice Brian R...Gaines, University of Essex, England Volume 4: Competing Modes of Cognition and Communication in Simulated and Self-Reflective Systems Stein Braten... University of Oslo, Norway Volume 5: On the Spontaneous Emergence of Decision Making Constraints in Communicating Hierarchical Structure John S

Towards scar-free surgery: An analysis of the increasing complexity from laparoscopic surgery to NOTES

PubMed Central

Chellali, Amine; Schwaitzberg, Steven D.; Jones, Daniel B.; Romanelli, John; Miller, Amie; Rattner, David; Roberts, Kurt E.; Cao, Caroline G.L.

2014-01-01

Background NOTES is an emerging technique for performing surgical procedures, such as cholecystectomy. Debate about its real benefit over the traditional laparoscopic technique is on-going. There have been several clinical studies comparing NOTES to conventional laparoscopic surgery. However, no work has been done to compare these techniques from a Human Factors perspective. This study presents a systematic analysis describing and comparing different existing NOTES methods to laparoscopic cholecystectomy. Methods Videos of endoscopic/laparoscopic views from fifteen live cholecystectomies were analyzed to conduct a detailed task analysis of the NOTES technique. A hierarchical task analysis of laparoscopic cholecystectomy and several hybrid transvaginal NOTES cholecystectomies was performed and validated by expert surgeons. To identify similarities and differences between these techniques, their hierarchical decomposition trees were compared. Finally, a timeline analysis was conducted to compare the steps and substeps. Results At least three variations of the NOTES technique were used for cholecystectomy. Differences between the observed techniques at the substep level of hierarchy and on the instruments being used were found. The timeline analysis showed an increase in time to perform some surgical steps and substeps in NOTES compared to laparoscopic cholecystectomy. Conclusion As pure NOTES is extremely difficult given the current state of development in instrumentation design, most surgeons utilize different hybrid methods – combination of endoscopic and laparoscopic instruments/optics. Results of our hierarchical task analysis yielded an identification of three different hybrid methods to perform cholecystectomy with significant variability amongst them. The varying degrees to which laparoscopic instruments are utilized to assist in NOTES methods appear to introduce different technical issues and additional tasks leading to an increase in the surgical time. The NOTES continuum of invasiveness is proposed here as a classification scheme for these methods, which was used to construct a clear roadmap for training and technology development. PMID:24902811

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

PubMed Central

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

PubMed

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis

PubMed Central

Badre, David

2012-01-01

Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if–then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper. PMID:21693490

Fabrication of hierarchical hybrid structures using bio-enabled layer-by-layer self-assembly.

PubMed

Hnilova, Marketa; Karaca, Banu Taktak; Park, James; Jia, Carol; Wilson, Brandon R; Sarikaya, Mehmet; Tamerler, Candan

2012-05-01

Development of versatile and flexible assembly systems for fabrication of functional hybrid nanomaterials with well-defined hierarchical and spatial organization is of a significant importance in practical nanobiotechnology applications. Here we demonstrate a bio-enabled self-assembly technique for fabrication of multi-layered protein and nanometallic assemblies utilizing a modular gold-binding (AuBP1) fusion tag. To accomplish the bottom-up assembly we first genetically fused the AuBP1 peptide sequence to the C'-terminus of maltose-binding protein (MBP) using two different linkers to produce MBP-AuBP1 hetero-functional constructs. Using various spectroscopic techniques, surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR), we verified the exceptional binding and self-assembly characteristics of AuBP1 peptide. The AuBP1 peptide tag can direct the organization of recombinant MBP protein on various gold surfaces through an efficient control of the organic-inorganic interface at the molecular level. Furthermore using a combination of soft-lithography, self-assembly techniques and advanced AuBP1 peptide tag technology, we produced spatially and hierarchically controlled protein multi-layered assemblies on gold nanoparticle arrays with high molecular packing density and pattering efficiency in simple, reproducible steps. This model system offers layer-by-layer assembly capability based on specific AuBP1 peptide tag and constitutes novel biological routes for biofabrication of various protein arrays, plasmon-active nanometallic assemblies and devices with controlled organization, packing density and architecture. Copyright © 2011 Wiley Periodicals, Inc.

A multivariate decision tree analysis of biophysical factors in tropical forest fire occurrence

Treesearch

Rey S. Ofren; Edward Harvey

2000-01-01

A multivariate decision tree model was used to quantify the relative importance of complex hierarchical relationships between biophysical variables and the occurrence of tropical forest fires. The study site is the Huai Kha Kbaeng wildlife sanctuary, a World Heritage Site in northwestern Thailand where annual fires are common and particularly destructive. Thematic...

A Hybrid Template-Based Composite Classification System

DTIC Science & Technology

2009-02-01

Hybrid Classifier: Forced Decision . . . . 116 5.3.2 Forced Decision Experimental Results . . . . . 119 5.3.3 Test for Statistical Significance ...Results . . . . . . . . . . 127 5.4.2 Test for Statistical Significance : NDEC Option 129 5.5 Implementing the Hyrid Classifier with OOL Targets . 130...comple- mentary in nature . Complementary classifiers are observed by finding an optimal method for partitioning the problem space. For example, the

An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

PubMed

Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

PubMed Central

Gundogar, Emin; Yılmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

THE ROLE OF CONSUMER VALUES AND SOCIO-DEMOGRAPHICS IN GREEN PRODUCT SATISFACTION: THE CASE OF HYBRID CARS.

PubMed

Hur, Won-Moo; Woo, Jeong; Kim, Yeonshin

2015-10-01

This study investigated the relationship between consumer value and customer satisfaction, seeking a better understanding of the motivations underlying "green product" purchases. Based on the influence of demographic factors, it further explores the moderation effects of buyers' socio-demographics on the link between value and satisfaction. Data were collected through a mail survey of American hybrid car buyers. Consumer value, satisfaction, and socio-demographic information were measured, and the proposed relationships among them were tested using hierarchical multiple regression analysis. This study's findings reveal that values (i.e., functional and social) significantly impact hybrid satisfaction and that the effects vary by sex and age. This research provides insight into the motivations of green product purchases by incorporating important consumer characteristics.

Controllable Modular Growth of Hierarchical MOF-on-MOF Architectures.

PubMed

Gu, Yifan; Wu, Yi-Nan; Li, Liangchun; Chen, Wei; Li, Fengting; Kitagawa, Susumu

2017-12-04

Fabrication of hybrid MOF-on-MOF heteroarchitectures can create novel and multifunctional platforms to achieve desired properties. However, only MOFs with similar crystallographic parameters can be hybridized by the classical epitaxial growth method (EGM), which largely suppressed its applications. A general strategy, called internal extended growth method (IEGM), is demonstrated for the feasible assembly of MOFs with distinct crystallographic parameters in an MOF matrix. Various MOFs with diverse functions could be introduced in a modular MOF matrix to form 3D core-satellite pluralistic hybrid system. The number of different MOF crystals interspersed could be varied on demand. More importantly, the different MOF crystals distributed in individual domains could be used to further incorporate functional units or enhance target functions. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Some induced intuitionistic fuzzy aggregation operators applied to multi-attribute group decision making

NASA Astrophysics Data System (ADS)

Su, Zhi-xin; Xia, Guo-ping; Chen, Ming-yuan

2011-11-01

In this paper, we define various induced intuitionistic fuzzy aggregation operators, including induced intuitionistic fuzzy ordered weighted averaging (OWA) operator, induced intuitionistic fuzzy hybrid averaging (I-IFHA) operator, induced interval-valued intuitionistic fuzzy OWA operator, and induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator. We also establish various properties of these operators. And then, an approach based on I-IFHA operator and intuitionistic fuzzy weighted averaging (WA) operator is developed to solve multi-attribute group decision-making (MAGDM) problems. In such problems, attribute weights and the decision makers' (DMs') weights are real numbers and attribute values provided by the DMs are intuitionistic fuzzy numbers (IFNs), and an approach based on I-IIFHA operator and interval-valued intuitionistic fuzzy WA operator is developed to solve MAGDM problems where the attribute values provided by the DMs are interval-valued IFNs. Furthermore, induced intuitionistic fuzzy hybrid geometric operator and induced interval-valued intuitionistic fuzzy hybrid geometric operator are proposed. Finally, a numerical example is presented to illustrate the developed approaches.

Accelerated decomposition techniques for large discounted Markov decision processes

NASA Astrophysics Data System (ADS)

Larach, Abdelhadi; Chafik, S.; Daoui, C.

2017-12-01

Many hierarchical techniques to solve large Markov decision processes (MDPs) are based on the partition of the state space into strongly connected components (SCCs) that can be classified into some levels. In each level, smaller problems named restricted MDPs are solved, and then these partial solutions are combined to obtain the global solution. In this paper, we first propose a novel algorithm, which is a variant of Tarjan's algorithm that simultaneously finds the SCCs and their belonging levels. Second, a new definition of the restricted MDPs is presented to ameliorate some hierarchical solutions in discounted MDPs using value iteration (VI) algorithm based on a list of state-action successors. Finally, a robotic motion-planning example and the experiment results are presented to illustrate the benefit of the proposed decomposition algorithms.

The hierarchy of task decision and response selection: a task-switching event related potentials study.

PubMed

Braverman, Ami; Berger, Andrea; Meiran, Nachshon

2014-07-01

According to "hierarchical" multi-step theories, response selection is preceded by a decision regarding which task rule should be executed. Other theories assume a "flat" single-step architecture in which task information and stimulus information are simultaneously considered. Using task switching, the authors independently manipulated two kinds of conflict: task conflict (with information that potentially triggers the relevant or the competing task rule/identity) and response conflict (with information that potentially triggers the relevant or the competing response code/motor response). Event related potentials indicated that the task conflict effect began before the response conflict effect and carried on in parallel with it. These results are more in line with the hierarchical view. Copyright © 2014 Elsevier Inc. All rights reserved.

Bayesian Decision Support

NASA Astrophysics Data System (ADS)

Berliner, M.

2017-12-01

Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.

Quasi-hexagonal Cu1.5Mn1.5O4 nanoplates decorated on hollow CuO by Kirkendall effect for enhancing lithium storage performance

NASA Astrophysics Data System (ADS)

Liu, Peng; Xia, Xifeng; Lei, Wu; Jiao, Xinyan; Lu, Lei; Ouyang, Yu; Hao, Qingli

2018-07-01

Constructing a hierarchical heterogeneous composite is deemed as an effective way to solve the current problems of metal oxides as lithium ion batteries' anodes. In this work, we simultaneously designed the heterogeneous component and structure of the novel hybrid based on Kirkendall effect. The composite was composed of quasi-hexagonal Cu1.5Mn1.5O4 nanoplates as a shell and CuO with voids as a core. The hybrids were characterized by using XRD, FTIR, TEM and SEM. It was found that the heating rate greatly influences the combination form of Cu1.5Mn1.5O4 and CuO. The quasi-hexagonal Cu1.5Mn1.5O4 nanoplates were assembled into branch-like shell decorated on the CuO surface under the low heating rate. However, the high heating rate led to a compact Cu1.5Mn1.5O4 shell, although the shell was also assembled by quasi-hexagonal nanoplates. The reasonable formation mechanism of the unique component and structure was proposed. Such a hybrid with the branch-like shell exhibited the best lithium storage performance. The improved electrochemical performance can be attributed to the unique component and structure. Typically, the inside voids can alleviate the volume change and the hierarchical shell can provide much contact and reaction sites. This work not only opens a new view in constructing heterogeneous hybrid with unique structure by Kirkendall effect, but also can be expanded for many other structure-based applications, such as energy storage, sensors, and heterogeneous catalysts.

Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Yasar, Murat; Tolani, Devendra; Ray, Asok; Shah, Neerav; Litt, Jonathan S.

2004-01-01

This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.

Energy Systems Integration News | Energy Systems Integration Facility |

Science.gov Websites

hierarchical control architecture that enables a hybrid control approach, where centralized control systems will be complemented by distributed control algorithms for solar inverters and autonomous control of ), involves developing a novel control scheme that provides system-wide monitoring and control using a small

Golden Rays - March 2017 | Solar Research | NREL

Science.gov Websites

, test and deploy a data enhanced hierarchical control architecture that adopts a hybrid approach to grid control. A centralized control layer will be complemented by distributed control algorithms for solar inverters and autonomous control of grid edge devices. The other NREL project will develop a novel control

Fuzzy bilevel programming with multiple non-cooperative followers: model, algorithm and application

NASA Astrophysics Data System (ADS)

Ke, Hua; Huang, Hu; Ralescu, Dan A.; Wang, Lei

2016-04-01

In centralized decision problems, it is not complicated for decision-makers to make modelling technique selections under uncertainty. When a decentralized decision problem is considered, however, choosing appropriate models is no longer easy due to the difficulty in estimating the other decision-makers' inconclusive decision criteria. These decision criteria may vary with different decision-makers because of their special risk tolerances and management requirements. Considering the general differences among the decision-makers in decentralized systems, we propose a general framework of fuzzy bilevel programming including hybrid models (integrated with different modelling methods in different levels). Specially, we discuss two of these models which may have wide applications in many fields. Furthermore, we apply the proposed two models to formulate a pricing decision problem in a decentralized supply chain with fuzzy coefficients. In order to solve these models, a hybrid intelligent algorithm integrating fuzzy simulation, neural network and particle swarm optimization based on penalty function approach is designed. Some suggestions on the applications of these models are also presented.

Hierarchical structure for audio-video based semantic classification of sports video sequences

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

Automated control of hierarchical systems using value-driven methods

NASA Technical Reports Server (NTRS)

Pugh, George E.; Burke, Thomas E.

1990-01-01

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

A three-dimensional hierarchical collagen scaffold fabricated by a combined solid freeform fabrication (SFF) and electrospinning process to enhance mesenchymal stem cell (MSC) proliferation

NASA Astrophysics Data System (ADS)

Ahn, SeungHyun; Koh, Young Ho; Kim, GeunHyung

2010-06-01

Collagen has the advantage of being very similar to macromolecular substances that can be recognized and metabolized in the biological environment. Although the natural material has superior property for this purpose, its use to fabricate reproducible and pore-structure-controlled 3D structures, which are designed to allow the entry of sufficient cells and the easy diffusion of nutrients, has been limited due to its low processability. Here, we propose a hybrid technology that combines a cryogenic plotting system with an electrospinning process. Using this technique, an easily pore-size-controllable hierarchical 3D scaffold consisting of micro-sized highly porous collagen strands and micro/nano-sized collagen fibers was fabricated. The pore structure of the collagen scaffold was controlled by the collagen micro/nanofibers, which were layered in the scaffold. The hierarchical scaffolds were characterized with respect to initial cell attachment and proliferation of bone marrow-derived mesenchymal stem cells within the scaffolds. The hierarchical scaffold exhibited incredibly enhanced initial cell attachment and cell compactness between pores of the plotted scaffold relative to the normally designed 3D collagen scaffold.

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Cellular behavior on TiO2 nanonodular structures in a micro-to-nanoscale hierarchy model.

PubMed

Kubo, Katsutoshi; Tsukimura, Naoki; Iwasa, Fuminori; Ueno, Takeshi; Saruwatari, Lei; Aita, Hideki; Chiou, Wen-An; Ogawa, Takahiro

2009-10-01

Biological tissues involve hierarchical organizations of structures and components. We created a micropit-and-nanonodule hybrid topography of TiO(2) by applying a recently reported nanonodular self-assembly technique on acid-etch-created micropit titanium surfaces. The size of the nanonodules was controllable by changing the assembly time. The created micro-nano-hybrid surface rendered a greater surface area and roughness, and extensive geographical undercut on the existing micropit surface and resembled the surface morphology of biomineralized matrices. Rat bone marrow-derived osteoblasts were cultured on titanium disks with either micropits alone, micropits with 100-nm nodules, micropits with 300-nm nodules, or micropits with 500-nm nodules. The addition of nanonodules to micropits selectively promoted osteoblast but not fibroblast function. Unlike the reported advantages of microfeatures that promote osteoblast differentiation but inhibit its proliferation, micro-nano-hybrid topography substantially enhanced both. We also demonstrated that these biological effects were most pronounced when the nanonodules were tailored to a diameter of 300nm within the micropits. An implant biomechanical test in a rat femur model revealed that the strength of bone-titanium integration was more than three times greater for the implants with micropits and 300-nm nanonodules than the implants with micropits alone. These results suggest the establishment of functionalized nano-in-microtitanium surfaces for improved osteoconductivity, and may provide a biomimetic micro-to-nanoscale hierarchical model to study the nanofeatures of biomaterials.

Hybrid employment recommendation algorithm based on Spark

NASA Astrophysics Data System (ADS)

Li, Zuoquan; Lin, Yubei; Zhang, Xingming

2017-08-01

Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.

Organic-Inorganic Hybrid Polymers as Adsorbents for Removal of Heavy Metal Ions from Solutions: A Review

PubMed Central

Samiey, Babak; Cheng, Chil-Hung; Wu, Jiangning

2014-01-01

Over the past decades, organic-inorganic hybrid polymers have been applied in different fields, including the adsorption of pollutants from wastewater and solid-state separations. In this review, firstly, these compounds are classified. These compounds are prepared by sol-gel method, self-assembly process (mesopores), assembling of nanobuilding blocks (e.g., layered or core-shell compounds) and as interpenetrating networks and hierarchically structures. Lastly, the adsorption characteristics of heavy metals of these materials, including different kinds of functional groups, selectivity of them for heavy metals, effect of pH and synthesis conditions on adsorption capacity, are studied. PMID:28788483

A simple approach to hybrid inorganic–organic step-growth hydrogels with scalable control of physicochemical properties and biodegradability† †Electronic supplementary information (ESI) available: Experimental details and characterization data as mentioned in the text. See DOI: 10.1039/c4py01789g Click here for additional data file.

PubMed Central

Alves, F.

2015-01-01

We prepared new and scalable, hybrid inorganic–organic step-growth hydrogels with polyhedral oligomeric silsesquioxane (POSS) network knot construction elements and hydrolytically degradable poly(ethylene glycol) (PEG) di-ester macromonomers by in situ radical-mediated thiol–ene photopolymerization. The physicochemical properties of the gels are fine-tailored over orders of magnitude including functionalization of their interior, a hierarchical gel structure, and biodegradability. PMID:25821524

A Hierarchical Approach to Target Recognition and Tracking. Summary of Results for the Period April 1, 1989-November 30, 1989

DTIC Science & Technology

1990-02-07

performance assessment, human intervention, or operator training. Algorithms on different levels are allowed to deal with the world with different degrees...have on the decisions made by the driver are a complex combination of human factors, driving experience, mission objectives, tactics, etc., and...motion. The distinction here is that the decision making program may I 12 1 I not necessarily make its decisions based on the same factors as the human

Drifting through Basic Subprocesses of Reading: A Hierarchical Diffusion Model Analysis of Age Effects on Visual Word Recognition

PubMed Central

Froehlich, Eva; Liebig, Johanna; Ziegler, Johannes C.; Braun, Mario; Lindenberger, Ulman; Heekeren, Hauke R.; Jacobs, Arthur M.

2016-01-01

Reading is one of the most popular leisure activities and it is routinely performed by most individuals even in old age. Successful reading enables older people to master and actively participate in everyday life and maintain functional independence. Yet, reading comprises a multitude of subprocesses and it is undoubtedly one of the most complex accomplishments of the human brain. Not surprisingly, findings of age-related effects on word recognition and reading have been partly contradictory and are often confined to only one of four central reading subprocesses, i.e., sublexical, orthographic, phonological and lexico-semantic processing. The aim of the present study was therefore to systematically investigate the impact of age on each of these subprocesses. A total of 1,807 participants (young, N = 384; old, N = 1,423) performed four decision tasks specifically designed to tap one of the subprocesses. To account for the behavioral heterogeneity in older adults, this subsample was split into high and low performing readers. Data were analyzed using a hierarchical diffusion modeling approach, which provides more information than standard response time/accuracy analyses. Taking into account incorrect and correct response times, their distributions and accuracy data, hierarchical diffusion modeling allowed us to differentiate between age-related changes in decision threshold, non-decision time and the speed of information uptake. We observed longer non-decision times for older adults and a more conservative decision threshold. More importantly, high-performing older readers outperformed younger adults at the speed of information uptake in orthographic and lexico-semantic processing, whereas a general age-disadvantage was observed at the sublexical and phonological levels. Low-performing older readers were slowest in information uptake in all four subprocesses. Discussing these results in terms of computational models of word recognition, we propose age-related disadvantages for older readers to be caused by inefficiencies in temporal sampling and activation and/or inhibition processes. PMID:27933029

Drifting through Basic Subprocesses of Reading: A Hierarchical Diffusion Model Analysis of Age Effects on Visual Word Recognition.

PubMed

Froehlich, Eva; Liebig, Johanna; Ziegler, Johannes C; Braun, Mario; Lindenberger, Ulman; Heekeren, Hauke R; Jacobs, Arthur M

2016-01-01

Reading is one of the most popular leisure activities and it is routinely performed by most individuals even in old age. Successful reading enables older people to master and actively participate in everyday life and maintain functional independence. Yet, reading comprises a multitude of subprocesses and it is undoubtedly one of the most complex accomplishments of the human brain. Not surprisingly, findings of age-related effects on word recognition and reading have been partly contradictory and are often confined to only one of four central reading subprocesses, i.e., sublexical, orthographic, phonological and lexico-semantic processing. The aim of the present study was therefore to systematically investigate the impact of age on each of these subprocesses. A total of 1,807 participants (young, N = 384; old, N = 1,423) performed four decision tasks specifically designed to tap one of the subprocesses. To account for the behavioral heterogeneity in older adults, this subsample was split into high and low performing readers. Data were analyzed using a hierarchical diffusion modeling approach, which provides more information than standard response time/accuracy analyses. Taking into account incorrect and correct response times, their distributions and accuracy data, hierarchical diffusion modeling allowed us to differentiate between age-related changes in decision threshold, non-decision time and the speed of information uptake. We observed longer non-decision times for older adults and a more conservative decision threshold. More importantly, high-performing older readers outperformed younger adults at the speed of information uptake in orthographic and lexico-semantic processing, whereas a general age-disadvantage was observed at the sublexical and phonological levels. Low-performing older readers were slowest in information uptake in all four subprocesses. Discussing these results in terms of computational models of word recognition, we propose age-related disadvantages for older readers to be caused by inefficiencies in temporal sampling and activation and/or inhibition processes.

The Impact of a Hybrid Sport Education-Invasion Games Competence Model Soccer Unit on Students' Decision Making, Skill Execution and Overall Game Performance

ERIC Educational Resources Information Center

Mesquita, Isabel; Farias, Claudio; Hastie, Peter

2012-01-01

The purpose of this study was to examine the impact of a hybrid Sport Education-Invasion Games Competence Model (SE-IGCM) unit application on students' improvements in decision making, skill execution and overall game performance, during a soccer season. Twenty-six fifth-grade students from a Portuguese public elementary school participated in a…

Unbounded and revocable hierarchical identity-based encryption with adaptive security, decryption key exposure resistant, and short public parameters

PubMed Central

Wang, Baosheng; Tao, Jing

2018-01-01

Revocation functionality and hierarchy key delegation are two necessary and crucial requirements to identity-based cryptosystems. Revocable hierarchical identity-based encryption (RHIBE) has attracted a lot of attention in recent years, many RHIBE schemes have been proposed but shown to be either insecure or bounded where they have to fix the maximum hierarchical depth of RHIBE at setup. In this paper, we propose a new unbounded RHIBE scheme with decryption key exposure resilience and with short public system parameters, and prove our RHIBE scheme to be adaptively secure. Our system model is scalable inherently to accommodate more levels of user adaptively with no adding workload or restarting the system. By carefully designing the hybrid games, we overcome the subtle obstacle in applying the dual system encryption methodology for the unbounded and revocable HIBE. To the best of our knowledge, this is the first construction of adaptively secure unbounded RHIBE scheme. PMID:29649326

Fabrication of hierarchical porous hollow carbon spheres with few-layer graphene framework and high electrochemical activity for supercapacitor

NASA Astrophysics Data System (ADS)

Chen, Jing; Hong, Min; Chen, Jiafu; Hu, Tianzhao; Xu, Qun

2018-06-01

Porous amorphous carbons with large number of defects and dangling bonds indicate great potential application in energy storage due to high specific surface area and strong adsorption properties, but poor conductivity and pore connection limit their practical application. Here few-layer graphene framework with high electrical conductivity is embedded and meanwhile hierarchical porous structure is constructed in amorphous hollow carbon spheres (HCSs) by catalysis of Fe clusters of angstrom scale, which are loaded in the interior of crosslinked polystyrene via a novel method. These unique HCSs effectively integrate the inherent properties from two-dimensional sp2-hybridized carbon, porous amorphous carbon, hierarchical pore structure and thin shell, leading to high specific capacitance up to 561 F g-1 at a current density of 0.5 A g-1 as an electrode of supercapacitor with excellent recyclability, which is much higher than those of other reported porous carbon materials up to present.

Rationality Validation of a Layered Decision Model for Network Defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Huaqiang; Alves-Foss, James; Zhang, Du

2007-08-31

We propose a cost-effective network defense strategy built on three key: three decision layers: security policies, defense strategies, and real-time defense tactics for countering immediate threats. A layered decision model (LDM) can be used to capture this decision process. The LDM helps decision-makers gain insight into the hierarchical relationships among inter-connected entities and decision types, and supports the selection of cost-effective defense mechanisms to safeguard computer networks. To be effective as a business tool, it is first necessary to validate the rationality of model before applying it to real-world business cases. This paper describes our efforts in validating the LDMmore » rationality through simulation.« less

Hexagonally Ordered Arrays of α-Helical Bundles Formed from Peptide-Dendron Hybrids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barkley, Deborah A.; Rokhlenko, Yekaterina; Marine, Jeannette E.

Combining monodisperse building blocks that have distinct folding properties serves as a modular strategy for controlling structural complexity in hierarchically organized materials. We combine an α-helical bundle-forming peptide with self-assembling dendrons to better control the arrangement of functional groups within cylindrical nanostructures. Site-specific grafting of dendrons to amino acid residues on the exterior of the α-helical bundle yields monodisperse macromolecules with programmable folding and self-assembly properties. The resulting hybrid biomaterials form thermotropic columnar hexagonal mesophases in which the peptides adopt an α-helical conformation. Bundling of the α-helical peptides accompanies self-assembly of the peptide-dendron hybrids into cylindrical nanostructures. The bundle stoichiometrymore » in the mesophase agrees well with the size found in solution for α-helical bundles of peptides with a similar amino acid sequence.« less

Binary Synergy Strengthening and Toughening of Bio-Inspired Nacre-like Graphene Oxide/Sodium Alginate Composite Paper.

PubMed

Chen, Ke; Shi, Bin; Yue, Yonghai; Qi, Juanjuan; Guo, Lin

2015-08-25

A crucial requirement for most engineering materials is the excellent balance of strength and toughness. By mimicking the hybrid hierarchical structure in nacre, a kind of nacre-like paper based on binary hybrid graphene oxide (GO)/sodium alginate (SA) building blocks has been successfully fabricated. Systematic evaluation for the mechanical property in different (dry/wet) environment/after thermal annealing shows a perfect combination of high strength and toughness. Both of the parameters are nearly many-times higher than those of similar materials because of the synergistic strengthening/toughening enhancement from the binary GO/SA hybrids. The successful fabrication route offers an excellent approach to design advanced strong integrated nacre-like composite materials, which can be applied in tissue engineering, protection, aerospace, and permeable membranes for separation and delivery.

Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.

PubMed

Malekmohammadi, Bahram; Tayebzadeh Moghadam, Negar

2018-04-13

Environmental risk assessment (ERA) is a commonly used, effective tool applied to reduce adverse effects of environmental risk factors. In this study, ERA was investigated using the Bayesian network (BN) model based on a hierarchical structure of variables in an influence diagram (ID). ID facilitated ranking of the different alternatives under uncertainty that were then used to evaluate comparisons of the different risk factors. BN was used to present a new model for ERA applicable to complicated development projects such as dam construction. The methodology was applied to the Gabric Dam, in southern Iran. The main environmental risk factors in the region, presented by the Gabric Dam, were identified based on the Delphi technique and specific features of the study area. These included the following: flood, water pollution, earthquake, changes in land use, erosion and sedimentation, effects on the population, and ecosensitivity. These risk factors were then categorized based on results from the output decision node of the BN, including expected utility values for risk factors in the decision node. ERA was performed for the Gabric Dam using the analytical hierarchy process (AHP) method to compare results of BN modeling with those of conventional methods. Results determined that a BN-based hierarchical structure to ERA present acceptable and reasonable risk assessment prioritization in proposing suitable solutions to reduce environmental risks and can be used as a powerful decision support system for evaluating environmental risks.

Amylose-Derived Macrohollow Core and Microporous Shell Carbon Spheres as Sulfur Host for Superior Lithium-Sulfur Battery Cathodes.

PubMed

Li, Xiang; Cheng, Xuanbing; Gao, Mingxia; Ren, Dawei; Liu, Yongfeng; Guo, Zhengxiao; Shang, Congxiao; Sun, Lixian; Pan, Hongge

2017-03-29

Porous carbon can be tailored to great effect for electrochemical energy storage. In this study, we propose a novel structured spherical carbon with a macrohollow core and a microporous shell derived from a sustainable biomass, amylose, by a multistep pyrolysis route without chemical etching. This hierarchically porous carbon shows a particle distribution of 2-10 μm and a surface area of 672 m 2 g -1 . The structure is an effective host of sulfur for lithium-sulfur battery cathodes, which reduces the dissolution of polysulfides in the electrolyte and offers high electrical conductivity during discharge/charge cycling. The hierarchically porous carbon can hold 48 wt % sulfur in its porous structure. The S@C hybrid shows an initial capacity of 1490 mAh g -1 and retains a capacity of 798 mAh g -1 after 200 cycles at a discharge/charge rate of 0.1 C. A capacity of 487 mAh g -1 is obtained at a rate of 3 C. Both a one-step pyrolysis and a chemical-reagent-assisted pyrolysis are also assessed to obtain porous carbon from amylose, but the obtained carbon shows structures inferior for sulfur cathodes. The multistep pyrolysis and the resulting hierarchically porous carbon offer an effective approach to the engineering of biomass for energy storage. The micrometer-sized spherical S@C hybrid with different sizes is also favorable for high-tap density and hence the volumetric density of the batteries, opening up a wide scope for practical applications.

Hierarchical self-assembly of nanoparticles in polymer matrix and the nature of the interparticle interaction

NASA Astrophysics Data System (ADS)

Lin, Yu-Chiao; Chen, Chun-Yu; Chen, Hsin-Lung; Hashimoto, Takeji; Chen, Show-An; Li, Yen-Cheng

2015-06-01

Using small angle X-ray scattering (SAXS), we elucidated the spatial organization of palladium (Pd) nanoparticles (NPs) in the polymer matrix of poly(2-vinylpyridine) (P2VP) and the nature of inter-nanoparticle interactions, where the NPs were synthesized in the presence of P2VP by the reduction of palladium acetylacetonate (Pd(acac)2). The experimental SAXS profiles were analysed on the basis of a hierarchical structure model considering the following two types of interparticle potential: (i) hard-core repulsion only (i.e., the hard-sphere interaction) and (ii) hard-core repulsion together with an attractive potential well (i.e., the sticky hard-sphere interaction). The corresponding theoretical scattering functions, which were used for analysing the experimental SAXS profiles, were obtained within the context of the Percus-Yevick closure and the Ornstein-Zernike equation in the fundamental liquid theory. The analyses revealed that existence of the attractive potential well is indispensable to account for the experimental SAXS profiles. Moreover, the morphology of the hybrids was found to be characterized by a hierarchical structure with three levels, where about six primary NPs with the diameter of ca. 1.8 nm (level one) formed local clusters (level two), and these clusters aggregated to build up a large-scale mass-fractal structure (level three) with the fractal dimension of ca. 2.3. The scattering function developed here is of general use for quantitatively characterizing the morphological structures of polymer/NP hybrids and, in particular, for exploring the interaction potential of the NPs on the basis of the fundamental liquid theory.

Soft plasma processing of organic nanowires: a route for the fabrication of 1D organic heterostructures and the template synthesis of inorganic 1D nanostructures.

PubMed

Alcaire, Maria; Sanchez-Valencia, Juan R; Aparicio, Francisco J; Saghi, Zineb; Gonzalez-Gonzalez, Juan C; Barranco, Angel; Zian, Youssef Oulad; Gonzalez-Elipe, Agustin R; Midgley, Paul; Espinos, Juan P; Groening, Pierangelo; Borras, Ana

2011-11-01

Hierarchical (branched) and hybrid metal-NPs/organic supported NWs are fabricated through controlled plasma processing of metalloporphyrin, metallophthalocyanine and perylene nanowires. The procedure is also applied for the development of a general template route for the synthesis of supported metal and metal oxide nanowires.

Complex Hollow Nanostructures: Synthesis and Energy-Related Applications.

PubMed

Yu, Le; Hu, Han; Wu, Hao Bin; Lou, Xiong Wen David

2017-04-01

Hollow nanostructures offer promising potential for advanced energy storage and conversion applications. In the past decade, considerable research efforts have been devoted to the design and synthesis of hollow nanostructures with high complexity by manipulating their geometric morphology, chemical composition, and building block and interior architecture to boost their electrochemical performance, fulfilling the increasing global demand for renewable and sustainable energy sources. In this Review, we present a comprehensive overview of the synthesis and energy-related applications of complex hollow nanostructures. After a brief classification, the design and synthesis of complex hollow nanostructures are described in detail, which include hierarchical hollow spheres, hierarchical tubular structures, hollow polyhedra, and multi-shelled hollow structures, as well as their hybrids with nanocarbon materials. Thereafter, we discuss their niche applications as electrode materials for lithium-ion batteries and hybrid supercapacitors, sulfur hosts for lithium-sulfur batteries, and electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions. The potential superiorities of complex hollow nanostructures for these applications are particularly highlighted. Finally, we conclude this Review with urgent challenges and further research directions of complex hollow nanostructures for energy-related applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Continuous flow chemical vapour deposition of carbon nanotube sea urchins.

PubMed

de La Verpilliere, Jean; Jessl, Sarah; Saeed, Khuzaimah; Ducati, Caterina; De Volder, Michael; Boies, Adam

2018-04-26

Hybrid structures consisting of functional materials enhanced by carbon nanotubes (CNTs) have potential for a variety of high impact applications, as shown by the impressive progress in sensing and mechanical applications enabled by CNT-enhanced materials. The hierarchical organisation of CNTs with other materials is key to the design of macroscale devices benefiting from the unique properties of individual CNTs, provided CNT density, morphology and binding with other materials are optimized. In this paper, we provide an analysis of a continuous aerosol process to create a hybrid hierarchical sea urchin structure with CNTs organized around a functional metal oxide core. We propose a new mechanism for the growth of these carbon nanotube sea urchins (CNTSU) and give new insight into their chemical composition. To corroborate the new mechanism, we examine the influence of CNT growth conditions on CNTSU morphology and demonstrate a new in-line characterisation technique to continuously monitor aerosol CNT growth during synthesis, which enables industrial-scale production optimization. Based upon the new formation mechanism we describe the first substrate-based chemical vapour deposition growth of CNTSUs which increases CNT length and improves G to D ratio, which also allows for the formation of CNTSU carpets with unique structures.

Self-assembly of nucleic acids, silk and hybrid materials thereof.

PubMed

Humenik, Martin; Scheibel, Thomas

2014-12-17

Top-down approaches based on etching techniques have almost reached their limits in terms of dimension. Therefore, novel assembly strategies and types of nanomaterials are required to allow technological advances. Self-assembly processes independent of external energy sources and unlimited in dimensional scaling have become a very promising approach. Here,we highlight recent developments in self-assembled DNA-polymer, silk-polymer and silk-DNA hybrids as promising materials with biotic and abiotic moieties for constructing complex hierarchical materials in ‘bottom-up’ approaches. DNA block copolymers assemble into nanostructures typically exposing a DNA corona which allows functionalization, labeling and higher levels of organization due to its specific addressable recognition properties. In contrast, self-assembly of natural silk proteins as well as their recombinant variants yields mechanically stable β-sheet rich nanostructures. The combination of silk with abiotic polymers gains hybrid materials with new functionalities. Together, the precision of DNA hybridization and robustness of silk fibrillar structures combine in novel conjugates enable processing of higher-order structures with nanoscale architecture and programmable functions.

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite while the effect on the axial properties is shown to be insignificant.

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Hybrid NiS/CoO mesoporous nanosheet arrays on Ni foam for high-rate supercapacitors

NASA Astrophysics Data System (ADS)

Wu, Jianghong; Ouyang, Canbin; Dou, Shuo; Wang, Shuangyin

2015-08-01

A new hybrid of NiS/CoO porous nanosheets was synthesized on Ni foam by one-step electrodeposition method and used as an electrode for high-performance pseudocapacitance. The as-synthesized NiS/CoO porous nanosheets hybrid shows a high specific capacitance of 1054 F g-1 at a high current density of 6 A g-1, a good rate capability even at high current density (760 F g-1 at 20 A g-1) and a good long-term cycling stability (91.7% of the maximum specific capacitance after 3000 cycles). These excellent properties can be mainly attributed to the unique hierarchical porous structure with large surface area and interspaces which facilitate charge transfer and redox reaction. The enhancement in the interface contact between active material and substrate results in excellent conductivity of the electrode and a strong synergistic effect of NiS and CoO as individual constituents contributed to high capacitance of the hybrid electrode.

Hybrid NiS/CoO mesoporous nanosheet arrays on Ni foam for high-rate supercapacitors.

PubMed

Wu, Jianghong; Ouyang, Canbin; Dou, Shuo; Wang, Shuangyin

2015-08-14

A new hybrid of NiS/CoO porous nanosheets was synthesized on Ni foam by one-step electrodeposition method and used as an electrode for high-performance pseudocapacitance. The as-synthesized NiS/CoO porous nanosheets hybrid shows a high specific capacitance of 1054 F g(-1) at a high current density of 6 A g(-1), a good rate capability even at high current density (760 F g(-1) at 20 A g(-1)) and a good long-term cycling stability (91.7% of the maximum specific capacitance after 3000 cycles). These excellent properties can be mainly attributed to the unique hierarchical porous structure with large surface area and interspaces which facilitate charge transfer and redox reaction. The enhancement in the interface contact between active material and substrate results in excellent conductivity of the electrode and a strong synergistic effect of NiS and CoO as individual constituents contributed to high capacitance of the hybrid electrode.

Self-assembly of nucleic acids, silk and hybrid materials thereof

NASA Astrophysics Data System (ADS)

Humenik, Martin; Scheibel, Thomas

2014-12-01

Top-down approaches based on etching techniques have almost reached their limits in terms of dimension. Therefore, novel assembly strategies and types of nanomaterials are required to allow technological advances. Self-assembly processes independent of external energy sources and unlimited in dimensional scaling have become a very promising approach. Here, we highlight recent developments in self-assembled DNA-polymer, silk-polymer and silk-DNA hybrids as promising materials with biotic and abiotic moieties for constructing complex hierarchical materials in ‘bottom-up’ approaches. DNA block copolymers assemble into nanostructures typically exposing a DNA corona which allows functionalization, labeling and higher levels of organization due to its specific addressable recognition properties. In contrast, self-assembly of natural silk proteins as well as their recombinant variants yields mechanically stable β-sheet rich nanostructures. The combination of silk with abiotic polymers gains hybrid materials with new functionalities. Together, the precision of DNA hybridization and robustness of silk fibrillar structures combine in novel conjugates enable processing of higher-order structures with nanoscale architecture and programmable functions.

Bio-Based Artificial Nacre with Excellent Mechanical and Barrier Properties Realized by a Facile In Situ Reduction and Cross-Linking Reaction.

PubMed

Shahzadi, Kiran; Mohsin, Imran; Wu, Lin; Ge, Xuesong; Jiang, Yijun; Li, Hui; Mu, Xindong

2017-01-24

Demands for high strength integrated materials have substantially increased across various kinds of industries. Inspired by the relationship of excellent integration of mechanical properties and hierarchical nano/microscale structure of the natural nacre, a simple and facile method to fabricate high strength integrated artificial nacre based on sodium carboxymethylcellulose (CMC) and borate cross-linked graphene oxide (GO) sheets has been developed. The tensile strength and toughness of cellulose-based hybrid material reached 480.5 ± 13.1 MPa and 11.8 ± 0.4 MJm -3 by a facile in situ reduction and cross-linking reaction between CMC and GO (0.7%), which are 3.55 and 6.55 times that of natural nacre. This hybrid film exhibits better thermal stability and flame retardancy. More interestingly, the hybrid material showed good water stability compared to that in the original water-soluble CMC. This type of hybrid has great potential applications in aerospace, artificial muscle, and tissue engineering.

US Army Organizational Culture’s Effect on Innovation and Creativity

DTIC Science & Technology

2017-05-25

of high levels of hierarchical control, clearly defined roles, and centralized decision-making impede flexibility and creativity. When innovation is...of thinking people experience when they are deeply involved in a cohesive team. Members of cohesive decision...represent C.J. Jung’s basic theory on psychological types. In general, these preferences affect what people attend to and how they draw conclusions about

The Relationship between Teachers' and Principals' Decision-Making Power: Is It a Win-Win Situation or a Zero-Sum Game?

ERIC Educational Resources Information Center

Shen, Jianping; Xia, Jiangang

2012-01-01

Is the power relationship between public school teachers and principals a win-win situation or a zero-sum game? By applying hierarchical linear modeling to the 1999-2000 nationally representative Schools and Staffing Survey data, we found that both the win-win and zero-sum-game theories had empirical evidence. The decision-making areas…

IT vendor selection model by using structural equation model & analytical hierarchy process

NASA Astrophysics Data System (ADS)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Self-Reconstructed Formation of a One-Dimensional Hierarchical Porous Nanostructure Assembled by Ultrathin TiO2 Nanobelts for Fast and Stable Lithium Storage.

PubMed

Liu, Yuan; Yan, Xiaodong; Xu, Bingqing; Lan, Jinle; Yu, Yunhua; Yang, Xiaoping; Lin, Yuanhua; Nan, Cewen

2018-06-06

Owing to their unique structural advantages, TiO 2 hierarchical nanostructures assembled by low-dimensional (LD) building blocks have been extensively used in the energy-storage/-conversion field. However, it is still a big challenge to produce such advanced structures by current synthetic techniques because of the harsh conditions needed to generate primary LD subunits. Herein, a novel one-dimensional (1D) TiO 2 hierarchical porous fibrous nanostructure constructed by TiO 2 nanobelts is synthesized by combining a room-temperature aqueous solution growth mechanism with the electrospinning technology. The nanobelt-constructed 1D hierarchical nanoarchitecture is evolves directly from the amorphous TiO 2 /SiO 2 composite fibers in alkaline solutions at ambient conditions without any catalyst and other reactant. Benefiting from the unique structural features such as 1D nanoscale building blocks, large surface area, and numerous interconnected pores, as well as mixed phase anatase-TiO 2 (B), the optimum 1D TiO 2 hierarchical porous nanostructure shows a remarkable high-rate performance when tested as an anode material for lithium-ion batteries (107 mA h g -1 at ∼10 A g -1 ) and can be used in a hybrid lithium-ion supercapacitor with very stable lithium-storage performance (a capacity retention of ∼80% after 3000 cycles at 2 A g -1 ). The current work presents a scalable and cost-effective method for the synthesis of advanced TiO 2 hierarchical materials for high-power and stable energy-storage/-conversion devices.

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

PubMed

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Knowledge engineering for PACES, the particle accelerator control expert system

NASA Astrophysics Data System (ADS)

Lind, P. C.; Poehlman, W. F. S.; Stark, J. W.; Cousins, T.

1992-04-01

The KN-3000 used at Defense Research Establishment Ottawa is a Van de Graaff particle accelerator employed primarily to produce monoenergetic neutrons for calibrating radiation detectors. To provide training and assistance for new operators, it was decided to develop an expert system for accelerator operation. Knowledge engineering aspects of the expert system are reviewed. Two important issues are involved: the need to encapsulate expert knowledge into the system in a form that facilitates automatic accelerator operation and to partition the system so that time-consuming inferencing is minimized in favor of faster, more algorithmic control. It is seen that accelerator control will require fast, narrowminded decision making for rapid fine tuning, but slower and broader reasoning for machine startup, shutdown, fault diagnosis, and correction. It is also important to render the knowledge base in a form conducive to operator training. A promising form of the expert system involves a hybrid system in which high level reasoning is performed on the host machine that interacts with the user, while an embedded controller employs neural networks for fast but limited adjustment of accelerator performance. This partitioning of duty facilitates a hierarchical chain of command yielding an effective mixture of speed and reasoning ability.

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

Stochastic Adaptive Estimation and Control.

DTIC Science & Technology

1994-10-26

Marcus, "Language Stability and Stabilizability of Discrete Event Dynamical Systems ," SIAM Journal on Control and Optimization, 31, September 1993...in the hierarchical control of flexible manufacturing systems ; in this problem, the model involves a hybrid process in continuous time whose state is...of the average cost control problem for discrete- time Markov processes. Our exposition covers from finite to Borel state and action spaces and

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

DTIC Science & Technology

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views , opinions and/or findings contained in this...high dimensionality and multi -modality of their hybrid configuration spaces. Planners that perform a purely geometric search are prohibitively slow...Hamburg, January Paper Title: Hierarchical planning for multi -contact non-prehensile manipulation Publication Type: Conference Paper or Presentation

Synthesis and characterization of transition metal oxide/sulfide nanostructures for electrochemical applications

NASA Astrophysics Data System (ADS)

Yilmaz, Gamze

This thesis is essentially oriented to develop low-cost nanostructured transition metal (nickel and vanadium) oxides and sulfides with high energy density, power density and electrochemical stability via strategies of structural design, hybridization, functionalization and surface engineering. Metal oxide and metal oxide/sulfide hybrid nanostructures in several designs, including hierarchical porous nanostructures, hollow polyhedrons, nanocubes, nanoframes, octopod nanoframes, and nanocages, were synthesized to study the contribution of structural design, compositional engineering, functionalization and surface engineering to the electrochemical properties of the materials. Modulated compositional and structural features disclosed the opportunities of large accessible active sites, facile ion transport, robustness and enhanced electrical conductivity. The best electrochemical performance with merits of highest energy density (38.9 Wh kg-1), power density (7.4 kW kg-1) and electrochemical stability (90.9% after 10000 cycles) was obtained for nickel cobalt layered double hydroxide/cobalt sulfide (NiCo-LDH/Co9S8) hybrid hollow polyhedron structure.

Reticulate evolution and incomplete lineage sorting among the ponderosa pines.

PubMed

Willyard, Ann; Cronn, Richard; Liston, Aaron

2009-08-01

Interspecific gene flow via hybridization may play a major role in evolution by creating reticulate rather than hierarchical lineages in plant species. Occasional diploid pine hybrids indicate the potential for introgression, but reticulation is hard to detect because ancestral polymorphism is still shared across many groups of pine species. Nucleotide sequences for 53 accessions from 17 species in subsection Ponderosae (Pinus) provide evidence for reticulate evolution. Two discordant patterns among independent low-copy nuclear gene trees and a chloroplast haplotype are better explained by introgression than incomplete lineage sorting or other causes of incongruence. Conflicting resolution of three monophyletic Pinus coulteri accessions is best explained by ancient introgression followed by a genetic bottleneck. More recent hybridization transferred a chloroplast from P. jeffreyi to a sympatric P. washoensis individual. We conclude that incomplete lineage sorting could account for other examples of non-monophyly, and caution against any analysis based on single-accession or single-locus sampling in Pinus.

Oligonucleotide primers, probes and molecular methods for the environmental monitoring of methanogenic archaea

PubMed Central

Narihiro, Takashi; Sekiguchi, Yuji

2011-01-01

Summary For the identification and quantification of methanogenic archaea (methanogens) in environmental samples, various oligonucleotide probes/primers targeting phylogenetic markers of methanogens, such as 16S rRNA, 16S rRNA gene and the gene for the α‐subunit of methyl coenzyme M reductase (mcrA), have been extensively developed and characterized experimentally. These oligonucleotides were designed to resolve different groups of methanogens at different taxonomic levels, and have been widely used as hybridization probes or polymerase chain reaction primers for membrane hybridization, fluorescence in situ hybridization, rRNA cleavage method, gene cloning, DNA microarray and quantitative polymerase chain reaction for studies in environmental and determinative microbiology. In this review, we present a comprehensive list of such oligonucleotide probes/primers, which enable us to determine methanogen populations in an environment quantitatively and hierarchically, with examples of the practical applications of the probes and primers. PMID:21375721

Design of water-repellant coating using dual scale size of hybrid silica nanoparticles on polymer surface

NASA Astrophysics Data System (ADS)

Conti, J.; De Coninck, J.; Ghazzal, M. N.

2018-04-01

The dual-scale size of the silica nanoparticles is commonly aimed at producing dual-scale roughness, also called hierarchical roughness (Lotus effect). In this study, we describe a method to build a stable water-repellant coating with controlled roughness. Hybrid silica nanoparticles are self-assembled over a polymeric surface by alternating consecutive layers. Each one uses homogenously distributed silica nanoparticles of a particular size. The effect of the nanoparticle size of the first layer on the final roughness of the coating is studied. The first layer enables to adjust the distance between the silica nanoparticles of the upper layer, leading to a tuneable and controlled final roughness. An optimal size nanoparticle has been found for higher water-repellency. Furthermore, the stability of the coating on polymeric surface (Polycarbonate substrate) is ensured by photopolymerization of hybridized silica nanoparticles using Vinyl functional groups.

A Hybrid Approach on Tourism Demand Forecasting

NASA Astrophysics Data System (ADS)

Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

2018-04-01

Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

NASA Technical Reports Server (NTRS)

Tilton, James C.

2002-01-01

This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

78 FR 38444 - Hyundai Motor Company, Grant of Petition for Decision of Inconsequential Noncompliance

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-26

.... Vehicles Involved: Affected are approximately 14,728 MY 2011 and 2012 Hyundai Sonata Hybrid vehicles... key-like object. If the rear seat back of the Sonata Hybrid vehicle was simply capable of being folded...'') \\1\\ has determined that certain model year (MY) 2011 and 2012 Hyundai Sonata Hybrid passenger cars...

77 FR 22386 - Hyundai Motor Company, Receipt of Petition for Decision of Inconsequential Noncompliance

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-13

... approximately 14,728 model year 2011 and 2012 Hyundai Sonata Hybrid vehicles produced beginning on December 2... Hybrid vehicle was simply capable of being folded, which would have no effect upon seat belt performance... the vehicle owner's manual that the seat belt should not be detached. Further, in the Sonata Hybrid...

A universal hybrid decision tree classifier design for human activity classification.

PubMed

Chien, Chieh; Pottie, Gregory J

2012-01-01

A system that reliably classifies daily life activities can contribute to more effective and economical treatments for patients with chronic conditions or undergoing rehabilitative therapy. We propose a universal hybrid decision tree classifier for this purpose. The tree classifier can flexibly implement different decision rules at its internal nodes, and can be adapted from a population-based model when supplemented by training data for individuals. The system was tested using seven subjects each monitored by 14 triaxial accelerometers. Each subject performed fourteen different activities typical of daily life. Using leave-one-out cross validation, our decision tree produced average classification accuracies of 89.9%. In contrast, the MATLAB personalized tree classifiers using Gini's diversity index as the split criterion followed by optimally tuning the thresholds for each subject yielded 69.2%.

The information architecture of behavior change websites.

PubMed

Danaher, Brian G; McKay, H Garth; Seeley, John R

2005-05-18

The extraordinary growth in Internet use offers researchers important new opportunities to identify and test new ways to deliver effective behavior change programs. The information architecture (IA)-the structure of website information--is an important but often overlooked factor to consider when adapting behavioral strategies developed in office-based settings for Web delivery. Using examples and relevant perspectives from multiple disciplines, we describe a continuum of website IA designs ranging from a matrix design to the tunnel design. The free-form matrix IA design allows users free rein to use multiple hyperlinks to explore available content according to their idiosyncratic interests. The more directive tunnel IA design (commonly used in e-learning courses) guides users step-by-step through a series of Web pages that are arranged in a particular order to improve the chances of achieving a goal that is measurable and consistent. Other IA designs are also discussed, including hierarchical IA and hybrid IA designs. In the hierarchical IA design, program content is arranged in a top-down manner, which helps the user find content of interest. The more complex hybrid IA design incorporates some combination of components that use matrix, tunnel, and/or hierarchical IA designs. Each of these IA designs is discussed in terms of usability, participant engagement, and program tailoring, as well as how they might best be matched with different behavior change goals (using Web-based smoking cessation interventions as examples). Our presentation underscores the role of considering and clearly reporting the use of IA designs when creating effective Web-based interventions. We also encourage the adoption of a multidisciplinary perspective as we move towards a more mature view of Internet intervention research.

Fabrication of bristlegrass-like VO2 (B)-ZnO heteroarchitectures as anode materials for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Ma, Yining; Li, Wenjing; Ji, Shidong; Zhou, Huaijuan; Li, Rong; Li, Ning; Yao, Heliang; Cao, Xun; Jin, Ping

2017-08-01

Three-dimensional bristlegrass-like hierarchical VO2 (B)-ZnO heteroarchitectures with ZnO nanorods grown radially on VO2 (B) nanorods were successfully fabricated via a simple two-step synthesized method. When applied as an anode material for lithium-ion batteries, the VO2 (B)-ZnO hybrid electrode exhibited high reversible capacity and excellent recyclability, which could be originated from the unique hierarchical structure of the bristlegrass. After 80 cycles, the nanocomposite still maintained a higher reversible capacity of 329.4 mA h g-1 at a current density of 50 mA g-1. Therefore, the particular architecture of VO2 (B)-ZnO nanocomposite can be a promising candidate as the anode material in lithium-ion batteries.

Distributed Trust Management for Validating SLA Choreographies

NASA Astrophysics Data System (ADS)

Haq, Irfan Ul; Alnemr, Rehab; Paschke, Adrian; Schikuta, Erich; Boley, Harold; Meinel, Christoph

For business workflow automation in a service-enriched environment such as a grid or a cloud, services scattered across heterogeneous Virtual Organizations (VOs) can be aggregated in a producer-consumer manner, building hierarchical structures of added value. In order to preserve the supply chain, the Service Level Agreements (SLAs) corresponding to the underlying choreography of services should also be incrementally aggregated. This cross-VO hierarchical SLA aggregation requires validation, for which a distributed trust system becomes a prerequisite. Elaborating our previous work on rule-based SLA validation, we propose a hybrid distributed trust model. This new model is based on Public Key Infrastructure (PKI) and reputation-based trust systems. It helps preventing SLA violations by identifying violation-prone services at service selection stage and actively contributes in breach management at the time of penalty enforcement.

Operating room scheduling using hybrid clustering priority rule and genetic algorithm

NASA Astrophysics Data System (ADS)

Santoso, Linda Wahyuni; Sinawan, Aisyah Ashrinawati; Wijaya, Andi Rahadiyan; Sudiarso, Andi; Masruroh, Nur Aini; Herliansyah, Muhammad Kusumawan

2017-11-01

Operating room is a bottleneck resource in most hospitals so that operating room scheduling system will influence the whole performance of the hospitals. This research develops a mathematical model of operating room scheduling for elective patients which considers patient priority with limit number of surgeons, operating rooms, and nurse team. Clustering analysis was conducted to the data of surgery durations using hierarchical and non-hierarchical methods. The priority rule of each resulting cluster was determined using Shortest Processing Time method. Genetic Algorithm was used to generate daily operating room schedule which resulted in the lowest values of patient waiting time and nurse overtime. The computational results show that this proposed model reduced patient waiting time by approximately 32.22% and nurse overtime by approximately 32.74% when compared to actual schedule.

HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

PubMed

Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

2013-01-01

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

Hierarchical decision processes that operate over distinct timescales underlie choice and changes in strategy

PubMed Central

Purcell, Braden A.; Kiani, Roozbeh

2016-01-01

Decision-making in a natural environment depends on a hierarchy of interacting decision processes. A high-level strategy guides ongoing choices, and the outcomes of those choices determine whether or not the strategy should change. When the right decision strategy is uncertain, as in most natural settings, feedback becomes ambiguous because negative outcomes may be due to limited information or bad strategy. Disambiguating the cause of feedback requires active inference and is key to updating the strategy. We hypothesize that the expected accuracy of a choice plays a crucial rule in this inference, and setting the strategy depends on integration of outcome and expectations across choices. We test this hypothesis with a task in which subjects report the net direction of random dot kinematograms with varying difficulty while the correct stimulus−response association undergoes invisible and unpredictable switches every few trials. We show that subjects treat negative feedback as evidence for a switch but weigh it with their expected accuracy. Subjects accumulate switch evidence (in units of log-likelihood ratio) across trials and update their response strategy when accumulated evidence reaches a bound. A computational framework based on these principles quantitatively explains all aspects of the behavior, providing a plausible neural mechanism for the implementation of hierarchical multiscale decision processes. We suggest that a similar neural computation—bounded accumulation of evidence—underlies both the choice and switches in the strategy that govern the choice, and that expected accuracy of a choice represents a key link between the levels of the decision-making hierarchy. PMID:27432960

Hierarchical decision processes that operate over distinct timescales underlie choice and changes in strategy.

PubMed

Purcell, Braden A; Kiani, Roozbeh

2016-08-02

Decision-making in a natural environment depends on a hierarchy of interacting decision processes. A high-level strategy guides ongoing choices, and the outcomes of those choices determine whether or not the strategy should change. When the right decision strategy is uncertain, as in most natural settings, feedback becomes ambiguous because negative outcomes may be due to limited information or bad strategy. Disambiguating the cause of feedback requires active inference and is key to updating the strategy. We hypothesize that the expected accuracy of a choice plays a crucial rule in this inference, and setting the strategy depends on integration of outcome and expectations across choices. We test this hypothesis with a task in which subjects report the net direction of random dot kinematograms with varying difficulty while the correct stimulus-response association undergoes invisible and unpredictable switches every few trials. We show that subjects treat negative feedback as evidence for a switch but weigh it with their expected accuracy. Subjects accumulate switch evidence (in units of log-likelihood ratio) across trials and update their response strategy when accumulated evidence reaches a bound. A computational framework based on these principles quantitatively explains all aspects of the behavior, providing a plausible neural mechanism for the implementation of hierarchical multiscale decision processes. We suggest that a similar neural computation-bounded accumulation of evidence-underlies both the choice and switches in the strategy that govern the choice, and that expected accuracy of a choice represents a key link between the levels of the decision-making hierarchy.

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

NASA Technical Reports Server (NTRS)

Tilton, James C.

2003-01-01

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Two-Sided Matching in Hierarchical Organizations-An Application for the Assignment of Military Personnel

DTIC Science & Technology

2011-06-01

information overload has been examined in fields such as consumer behavior , it has not previously been examined in relation to assignment decision making...such as accounting, organization science and consumer behavior , and show that there is considerable evidence that humans make poor quality decisions...accuracy in the consumer behavior domain, however his approach was different for two primary reasons. Firstly, he examined the effect of an individual’s

The Study of Crew Coordination and Performance in Hierarchical Team Decision Making

DTIC Science & Technology

1992-11-01

Technical Report 92-01 3 decision making (Carley, 1991; Levis, 1984; Miao , Luh, Kleinman, & Castanon, 1991). This type of approach uses mathematical 5...Boston: Allyn and Bacon. Bieth, B. H . (1987). Subjective workload under individual and team performance conditions. Proceedings of the Human Factors...B. B., Jr. (1992, June). H •ri•oiLal_ and vertical structures in small teams: Team performance and communication Datteins. Paper presented at the 1991

Proteomic analysis of muscle between hybrid abalone and parental lines Haliotis gigantea Reeve and Haliotis discus hannai Ino

PubMed Central

Di, G; Luo, X; You, W; Zhao, J; Kong, X; Ke, C

2015-01-01

To understand the potential molecular mechanism of heterosis, protein expression patterns were compared from hybrids of Haliotis gigantea (G) and Haliotis discus hannai (D) using two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of-flight/time-of-flight analyses. Expression differences were observed in muscle samples from the four groups with 673±21.0 stained spots for H. discus hannai ♀ × H. discus hannai ♂ (DD), 692±25.6 for H. gigantea ♀ × H. gigantea ♂ (GG), 679±16.2 for H. discus hannai ♀ × H. gigantea ♂ (DG) (F1 hybrid) and 700±19 for H. gigantea ♀ × H. discus hannai ♂ (GD) (F1 hybrid). Different 2-DE image muscle protein spots had a mirrored relationship between purebreds and the F1 hybrid, suggesting that all stained spots in F1 hybrid muscle were on 2-DEs from parents. DD and DG clustered together first, and then clustered with GD, whereas the distance of DD and GG was maximal according to hierarchical cluster analysis. We identified 136 differentially expressed protein spots involved in major biological processes, including energy metabolism and stress response. Most energy metabolism proteins were additive, and stress-induced proteins displayed additivity or over-dominance. In these 136 identified protein spots, hybrid offspring with additivity or over-dominance accounted for 68.38%. Data show that a proteomic approach can provide functional prediction of abalone interspecific hybridization. PMID:25669609

Direct Z-scheme TiO2/CdS hierarchical photocatalyst for enhanced photocatalytic H2-production activity

NASA Astrophysics Data System (ADS)

Meng, Aiyun; Zhu, Bicheng; Zhong, Bo; Zhang, Liuyang; Cheng, Bei

2017-11-01

Photocatalytic H2 evolution, which utilizes solar energy via water splitting, is a promising route to deal with concerns about energy and environment. Herein, a direct Z-scheme TiO2/CdS binary hierarchical photocatalyst was fabricated via a successive ionic layer adsorption and reaction (SILAR) technique, and photocatalytic H2 production was measured afterwards. The as-prepared TiO2/CdS hybrid photocatalyst exhibited noticeably promoted photocatalytic H2-production activity of 51.4 μmol h-1. The enhancement of photocatalytic activity was ascribed to the hierarchical structure, as well as the efficient charge separation and migration from TiO2 nanosheets to CdS nanoparticles (NPs) at their tight contact interfaces. Moreover, the direct Z-scheme photocatalytic reaction mechanism was demonstrated to elucidate the improved photocatalytic performance of TiO2/CdS composite photocatalyst. The photoluminescence (PL) analysis of hydroxyl radicals were conducted to provide clues for the direct Z-scheme mechanism. This work provides a facile route for the construction of redox mediator-free Z-scheme photocatalytic system for photocatalytic water splitting.

Hierarchical sinuous-antenna phased array for millimeter wavelengths

NASA Astrophysics Data System (ADS)

Cukierman, Ari; Lee, Adrian T.; Raum, Christopher; Suzuki, Aritoki; Westbrook, Benjamin

2018-03-01

We present the design, fabrication, and measured performance of a hierarchical sinuous-antenna phased array coupled to superconducting transition-edge-sensor (TES) bolometers for millimeter wavelengths. The architecture allows for dual-polarization wideband sensitivity with a beam width that is approximately frequency-independent. We report on measurements of a prototype device, which uses three levels of triangular phased arrays to synthesize beams that are approximately constant in width across three frequency bands covering a 3:1 bandwidth. The array element is a lens-coupled sinuous antenna. The device consists of an array of hemispherical lenses coupled to a lithographed wafer, which integrates TESs, planar sinuous antennas, and microwave circuitry including band-defining filters. The approximately frequency-independent beam widths improve coupling to telescope optics and keep the sensitivity of an experiment close to optimal across a broad frequency range. The design can be straightforwardly modified for use with non-TES lithographed cryogenic detectors such as kinetic inductance detectors. Additionally, we report on the design and measurements of a broadband 180° hybrid that can simplify the design of future multichroic focal planes including but not limited to hierarchical phased arrays.

Complexity, Robustness, and Multistability in Network Systems with Switching Topologies: A Hierarchical Hybrid Control Approach

DTIC Science & Technology

2015-05-22

sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei

PubMed Central

Uliano-Silva, Marcela; Dondero, Francesco; Dan Otto, Thomas; Costa, Igor; Lima, Nicholas Costa Barroso; Americo, Juliana Alves; Mazzoni, Camila Junqueira; Prosdocimi, Francisco; Rebelo, Mauro de Freitas

2018-01-01

Abstract Background For more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it. Findings We assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei. Conclusions We built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei’s genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control. PMID:29267857

A nitrogen-doped 3D hierarchical carbon/sulfur composite for advanced lithium sulfur batteries

NASA Astrophysics Data System (ADS)

Liu, Xiaoyan; Huang, Wenlong; Wang, Dongdong; Tian, Jianhua; Shan, Zhongqiang

2017-07-01

Hybrid nanostructures containing one-dimensional (1D) carbon nanotubes (CNTs) and three-dimensional (3D) mesoporous carbon sphere have many promising applications due to their unique physical chemical properties. In this study, a novel 3D hierarchical carbon material (MCCNT) composed of mesoporous carbon sphere core and nitrogen rich CNTs shell is successfully prepared via an aerosol spray and subsequent chemical vapor deposition (CVD) processes. Owning to its well defined porous structure and favorable conductive framework, MCCNT is used as a potential sulfur host in lithium sulfur batteries through a classic melt-diffusion method. When cycled at a current density of 0.2 C (1 C = 1675 mA h g-1), it delivers an initial capacity as high as 1438.7 mAh g-1. Even if the current density increase to 1 C, the specific capacity still remain up to 534.6 mAh g-1 after 300 cycles. The enhanced electrochemical performance can be attributed to the hybrid structure of MCCNT, in which, the porous core works as a host to confine sulfur and accommodate volume expansion and the external CNTs provide excellent electron and ion conductive frame work. Furthermore, the in-situ doped nitrogen on the surface of CNTs enables effective trapping of lithium polysulfides, leading to a much-improved cycling performance.

Bioinspired synthesis and self-assembly of hybrid organic–inorganic nanomaterials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Honghu

Nature is replete with complex organic–inorganic hierarchical materials of diverse yet specific functions. These materials are intricately designed under physiological conditions through biomineralization and biological self-assembly processes. Tremendous efforts have been devoted to investigating mechanisms of such biomineralization and biological self-assembly processes as well as gaining inspiration to develop biomimetic methods for synthesis and self-assembly of functional nanomaterials. In this work, we focus on the bioinspired synthesis and self-assembly of functional inorganic nanomaterials templated by specialized macromolecules including proteins, DNA and polymers. The in vitro biomineralization process of the magnetite biomineralizing protein Mms6 has been investigated using small-angle X-ray scattering.more » Templated by Mms6, complex magnetic nanomaterials can be synthesized on surfaces and in the bulk. DNA and synthetic polymers have been exploited to construct macroscopic two- and three-dimensional (2D and 3D) superlattices of gold nanocrystals. Employing X-ray scattering and spectroscopy techniques, the self-assembled structures and the self-assembly mechanisms have been studied, and theoretical models have been developed. Our results show that specialized macromolecules including proteins, DNA and polymers act as effective templates for synthesis and self-assembly of nanomaterials. These bottom-up approaches provide promising routes to fabricate hybrid organic–inorganic nanomaterials with rationally designed hierarchical structures, targeting specific functions.« less

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei.

PubMed

Uliano-Silva, Marcela; Dondero, Francesco; Dan Otto, Thomas; Costa, Igor; Lima, Nicholas Costa Barroso; Americo, Juliana Alves; Mazzoni, Camila Junqueira; Prosdocimi, Francisco; Rebelo, Mauro de Freitas

2018-02-01

For more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it. We assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei. We built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei's genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control.

Passive and active sol-gel materials and devices

NASA Astrophysics Data System (ADS)

Andrews, Mark P.; Najafi, S. Iraj

1997-07-01

This paper examines sol-gel materials for photonics in terms of partnerships with other material contenders for processing optical devices. The discussion in four sections identifies semiconductors, amorphous and crystalline inorganic dielectrics, and amorphous and crystalline organic dielectrics as strategic agents in the rapidly evolving area of materials and devices for data communications and telecommunications. With Zyss, we trace the hierarchical lineage that connects molecular hybridization (chemical functionality), through supramolecular hybridization (collective properties and responses), to functional hybridization (device and system level constructs). These three concepts thread their way through discussions of the roles sol-gel glasses might be anticipated to assume in a photonics marketplace. We assign a special place to glass integrated optics and show how high temperature consolidated sol-gel derived glasses fit into competitive glass fabrication technologies. Low temperature hybrid sol-gel glasses that combine attractive features of organic polymers and inorganic glasses are considered by drawing on examples of our own new processes for fabricating couplers, power splitters, waveguides and gratings by combining chemical synthesis and sol-gel processing with simple photomask techniques.

Effectiveness-implementation Hybrid Designs

PubMed Central

Curran, Geoffrey M.; Bauer, Mark; Mittman, Brian; Pyne, Jeffrey M.; Stetler, Cheryl

2013-01-01

Objectives This study proposes methods for blending design components of clinical effectiveness and implementation research. Such blending can provide benefits over pursuing these lines of research independently; for example, more rapid translational gains, more effective implementation strategies, and more useful information for decision makers. This study proposes a “hybrid effectiveness-implementation” typology, describes a rationale for their use, outlines the design decisions that must be faced, and provides several real-world examples. Results An effectiveness-implementation hybrid design is one that takes a dual focus a priori in assessing clinical effectiveness and implementation. We propose 3 hybrid types: (1) testing effects of a clinical intervention on relevant outcomes while observing and gathering information on implementation; (2) dual testing of clinical and implementation interventions/strategies; and (3) testing of an implementation strategy while observing and gathering information on the clinical intervention’s impact on relevant outcomes. Conclusions The hybrid typology proposed herein must be considered a construct still in evolution. Although traditional clinical effectiveness and implementation trials are likely to remain the most common approach to moving a clinical intervention through from efficacy research to public health impact, judicious use of the proposed hybrid designs could speed the translation of research findings into routine practice. PMID:22310560

The role of justice in team member satisfaction with the leader and attachment to the team.

PubMed

Phillips, J M; Douthitt, E A; Hyland, M M

2001-04-01

This study examined the effects of team decision accuracy, team member decision influence, leader consideration behaviors, and justice perceptions on staff members' satisfaction with the leader and attachment to the team in hierarchical decision-making teams. The authors proposed that staff members' justice perceptions would mediate the relationship between (a) team decision accuracy, (b) the amount of influence a staff member has in the team leader's decision, and (c) the leader's consideration behaviors and staff attachment to the team and satisfaction with the leader. The results of an experiment involving 128 participants in a total of 64 teams, who made recommendations to a confederate acting as the team leader, generally support the proposed model.

Hybrid algorithms for fuzzy reverse supply chain network design.

PubMed

Che, Z H; Chiang, Tzu-An; Kuo, Y C; Cui, Zhihua

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods.

Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design

PubMed Central

Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

Single- versus dual-process models of lexical decision performance: insights from response time distributional analysis.

PubMed

Yap, Melvin J; Balota, David A; Cortese, Michael J; Watson, Jason M

2006-12-01

This article evaluates 2 competing models that address the decision-making processes mediating word recognition and lexical decision performance: a hybrid 2-stage model of lexical decision performance and a random-walk model. In 2 experiments, nonword type and word frequency were manipulated across 2 contrasts (pseudohomophone-legal nonword and legal-illegal nonword). When nonwords became more wordlike (i.e., BRNTA vs. BRANT vs. BRANE), response latencies to nonwords were slowed and the word frequency effect increased. More important, distributional analyses revealed that the Nonword Type = Word Frequency interaction was modulated by different components of the response time distribution, depending on the specific nonword contrast. A single-process random-walk model was able to account for this particular set of findings more successfully than the hybrid 2-stage model. (c) 2006 APA, all rights reserved.

Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

PubMed

Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

2015-08-01

In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

Hierarchical analytical and simulation modelling of human-machine systems with interference

NASA Astrophysics Data System (ADS)

Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.

2017-01-01

The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.

Fabrication and photoluminescence properties of graphite fiber/ZnO nanorod core-shell structures.

PubMed

Liu, Xianbin; Du, Hejun; Liu, Bo; Wang, Jianxiong; Sun, Xiao Wei; Sun, Handong

2011-08-01

Graphite fiber/ZnO nanorod core-shell structures were synthesized by thermal evaporation process. The core-shell hybrid architectures were comprised of ZnO nanorods grown on the surface of graphite fiber. In addition, Hollow ZnO hierarchical structure can be obtained by oxidizing the graphite fiber. Room temperature photoluminescence (PL) of the as-made graphite fiber/ZnO nanorod structures shows two UV peaks at around 3.274 eV and 3.181 eV. The temperature-dependent photoluminescence spectra demonstrate the two UV emissions are attributed to the intrinsic optical transitions and extrinsic defect-related emissions in ZnO. These hybrid structures may be used as the building block for fabrication of nanodevices.

Fuzzy Hybrid Deliberative/Reactive Paradigm (FHDRP)

NASA Technical Reports Server (NTRS)

Sarmadi, Hengameth

2004-01-01

This work aims to introduce a new concept for incorporating fuzzy sets in hybrid deliberative/reactive paradigm. After a brief review on basic issues of hybrid paradigm the definition of agent-based fuzzy hybrid paradigm, which enables the agents to proceed and extract their behavior through quantitative numerical and qualitative knowledge and to impose their decision making procedure via fuzzy rule bank, is discussed. Next an example performs a more applied platform for the developed approach and finally an overview of the corresponding agents architecture enhances agents logical framework.

Challenges for Curriculum Leadership in Contemporary Teacher Education

ERIC Educational Resources Information Center

Parkes, Robert J.

2013-01-01

This paper outlines the complex contemporary milieu of Australian teacher education within which curriculum leaders responsible for designing teacher education programs must make their program design decisions. Particular attention is paid to the collision of vertical ("hierarchical" or "academic rationalist") and horizontal…

Hierarchical Bayesian analysis of outcome- and process-based social preferences and beliefs in Dictator Games and sequential Prisoner's Dilemmas.

PubMed

Aksoy, Ozan; Weesie, Jeroen

2014-05-01

In this paper, using a within-subjects design, we estimate the utility weights that subjects attach to the outcome of their interaction partners in four decision situations: (1) binary Dictator Games (DG), second player's role in the sequential Prisoner's Dilemma (PD) after the first player (2) cooperated and (3) defected, and (4) first player's role in the sequential Prisoner's Dilemma game. We find that the average weights in these four decision situations have the following order: (1)>(2)>(4)>(3). Moreover, the average weight is positive in (1) but negative in (2), (3), and (4). Our findings indicate the existence of strong negative and small positive reciprocity for the average subject, but there is also high interpersonal variation in the weights in these four nodes. We conclude that the PD frame makes subjects more competitive than the DG frame. Using hierarchical Bayesian modeling, we simultaneously analyze beliefs of subjects about others' utility weights in the same four decision situations. We compare several alternative theoretical models on beliefs, e.g., rational beliefs (Bayesian-Nash equilibrium) and a consensus model. Our results on beliefs strongly support the consensus effect and refute rational beliefs: there is a strong relationship between own preferences and beliefs and this relationship is relatively stable across the four decision situations. Copyright © 2014 Elsevier Inc. All rights reserved.

A model-based analysis of impulsivity using a slot-machine gambling paradigm

PubMed Central

Paliwal, Saee; Petzschner, Frederike H.; Schmitz, Anna Katharina; Tittgemeyer, Marc; Stephan, Klaas E.

2014-01-01

Impulsivity plays a key role in decision-making under uncertainty. It is a significant contributor to problem and pathological gambling (PG). Standard assessments of impulsivity by questionnaires, however, have various limitations, partly because impulsivity is a broad, multi-faceted concept. What remains unclear is which of these facets contribute to shaping gambling behavior. In the present study, we investigated impulsivity as expressed in a gambling setting by applying computational modeling to data from 47 healthy male volunteers who played a realistic, virtual slot-machine gambling task. Behaviorally, we found that impulsivity, as measured independently by the 11th revision of the Barratt Impulsiveness Scale (BIS-11), correlated significantly with an aggregate read-out of the following gambling responses: bet increases (BIs), machines switches (MS), casino switches (CS), and double-ups (DUs). Using model comparison, we compared a set of hierarchical Bayesian belief-updating models, i.e., the Hierarchical Gaussian Filter (HGF) and Rescorla–Wagner reinforcement learning (RL) models, with regard to how well they explained different aspects of the behavioral data. We then examined the construct validity of our winning models with multiple regression, relating subject-specific model parameter estimates to the individual BIS-11 total scores. In the most predictive model (a three-level HGF), the two free parameters encoded uncertainty-dependent mechanisms of belief updates and significantly explained BIS-11 variance across subjects. Furthermore, in this model, decision noise was a function of trial-wise uncertainty about winning probability. Collectively, our results provide a proof of concept that hierarchical Bayesian models can characterize the decision-making mechanisms linked to the impulsive traits of an individual. These novel indices of gambling mechanisms unmasked during actual play may be useful for online prevention measures for at-risk players and future assessments of PG. PMID:25071497

Hierarchical NiCo2 O4 nanosheets grown on Ni nanofoam as high-performance electrodes for supercapacitors.

PubMed

Gao, Guoxin; Wu, Hao Bin; Ding, Shujiang; Liu, Li-Min; Lou, Xiong Wen David

2015-02-18

A high-performance electrode for supercapacitors is designed and synthesized by growing electroactive NiCo2 O4 nanosheets on conductive Ni nanofoam. Because of the structural advantages, the as-prepared Ni@NiCo2 O4 hybrid nanostructure exhibits significantly improved electrochemical performance with high capacitance, excellent rate capability, and good cycling stability. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DEPSCOR: Research on ARL’s Intelligent Control Architecture: Hierarchical Hybrid-Model Based Design, Verification, Simulation, and Synthesis of Mission Control for Autonomous Underwater Vehicles

DTIC Science & Technology

2007-02-01

shown in Figure 13 and the abstracted commanded environment is shown in Figure 14. Abort? Start Intl End itmi! Aborti Figure 13: Driver for loiter module...module in UPPAAL Aborti ? start Idle *- SteerToPoirt lot er<=2 Stee Doý2 I Abort? 65 66 Figure 14: Stub for loiter module module in UPPAAL Queries

Bioinspired decision architectures containing host and microbiome processing units.

PubMed

Heyde, K C; Gallagher, P W; Ruder, W C

2016-09-27

Biomimetic robots have been used to explore and explain natural phenomena ranging from the coordination of ants to the locomotion of lizards. Here, we developed a series of decision architectures inspired by the information exchange between a host organism and its microbiome. We first modeled the biochemical exchanges of a population of synthetically engineered E. coli. We then built a physical, differential drive robot that contained an integrated, onboard computer vision system. A relay was established between the simulated population of cells and the robot's microcontroller. By placing the robot within a target-containing a two-dimensional arena, we explored how different aspects of the simulated cells and the robot's microcontroller could be integrated to form hybrid decision architectures. We found that distinct decision architectures allow for us to develop models of computation with specific strengths such as runtime efficiency or minimal memory allocation. Taken together, our hybrid decision architectures provide a new strategy for developing bioinspired control systems that integrate both living and nonliving components.

A taxonomy of possible reasons for and against sperm donation.

PubMed

Bossema, Ercolie R; Janssens, Pim M W; Landwehr, Frieda; Treucker, Roswitha G L; van Duinen, Kor; Nap, Annemiek W; Geenen, Rinie

2013-06-01

Various reasons may guide the decision of men to become a sperm donor. Our aim was to identify a comprehensive set of possible reasons for and against sperm donation. Concept mapping. Assisted reproduction clinics. Nine sperm donors and seven non-sperm donors. Interviews to obtain statements for and against sperm donation, card-sorting tasks to categorize these statements according to similarity, and hierarchical cluster analysis to structure these categorizations. Hierarchical structure with reasons for and against sperm donation. The hierarchical structure with 91 reasons comprised selfishness (including narcissism and procreation), psychosocial drives (including altruism, detached procreation, and sexual/financial satisfaction), and psychosocial barriers (including normative and moral barriers related to oneself, one's spouse, the donor child, and society). The identified hierarchical overview of reasons for and against sperm donation may help potential sperm donors when considering becoming a sperm donor, enable more systematic counseling of potential sperm donors, and guide further research on reasons for and against sperm donation. © 2013 The Authors Acta Obstetricia et Gynecologica Scandinavica © 2013 Nordic Federation of Societies of Obstetrics and Gynecology.

Self-assembly synthesis of 3D graphene-encapsulated hierarchical Fe3O4 nano-flower architecture with high lithium storage capacity and excellent rate capability

NASA Astrophysics Data System (ADS)

Ma, Yating; Huang, Jian; Lin, Liang; Xie, Qingshui; Yan, Mengyu; Qu, Baihua; Wang, Laisen; Mai, Liqiang; Peng, Dong-Liang

2017-10-01

Graphene-encapsulated hierarchical metal oxides architectures can efficiently combine the merits of graphene and hierarchical metal oxides, which are deemed as the potential anode material candidates for the next-generation lithium-ion batteries due to the synergistic effect between them. Herein, a cationic surfactant induced self-assembly method is developed to construct 3D Fe3O4@reduction graphene oxide (H-Fe3O4@RGO) hybrid architecture in which hierarchical Fe3O4 nano-flowers (H-Fe3O4) are intimately encapsulated by 3D graphene network. Each H-Fe3O4 particle is constituted of rod-shaped skeletons surrounded by petal-like nano-flakes that are made up of enormous nanoparticles. When tested as the anode material in lithium-ion batteries, a high reversible capacity of 2270 mA h g-1 after 460 cycles is achieved under a current density of 0.5 A g-1. More impressively, even tested at a large current density of 10 A g-1, a decent reversible capacity of 490 mA h g-1 can be retained, which is still higher than the theoretical capacity of traditional graphite anode, demonstrating the remarkable lithium storage properties. The reasons for the excellent electrochemical performance of H-Fe3O4@RGO electrode have been discussed in detail.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Hierarchical Object-based Image Analysis approach for classification of sub-meter multispectral imagery in Tanzania

NASA Astrophysics Data System (ADS)

Chung, C.; Nagol, J. R.; Tao, X.; Anand, A.; Dempewolf, J.

2015-12-01

Increasing agricultural production while at the same time preserving the environment has become a challenging task. There is a need for new approaches for use of multi-scale and multi-source remote sensing data as well as ground based measurements for mapping and monitoring crop and ecosystem state to support decision making by governmental and non-governmental organizations for sustainable agricultural development. High resolution sub-meter imagery plays an important role in such an integrative framework of landscape monitoring. It helps link the ground based data to more easily available coarser resolution data, facilitating calibration and validation of derived remote sensing products. Here we present a hierarchical Object Based Image Analysis (OBIA) approach to classify sub-meter imagery. The primary reason for choosing OBIA is to accommodate pixel sizes smaller than the object or class of interest. Especially in non-homogeneous savannah regions of Tanzania, this is an important concern and the traditional pixel based spectral signature approach often fails. Ortho-rectified, calibrated, pan sharpened 0.5 meter resolution data acquired from DigitalGlobe's WorldView-2 satellite sensor was used for this purpose. Multi-scale hierarchical segmentation was performed using multi-resolution segmentation approach to facilitate the use of texture, neighborhood context, and the relationship between super and sub objects for training and classification. eCognition, a commonly used OBIA software program, was used for this purpose. Both decision tree and random forest approaches for classification were tested. The Kappa index agreement for both algorithms surpassed the 85%. The results demonstrate that using hierarchical OBIA can effectively and accurately discriminate classes at even LCCS-3 legend.

Teachers' Perceived Influences on Technology Integration Decisions: A Grounded Theory on Instructional Decisions after Professional Development

ERIC Educational Resources Information Center

Greenhaus, Karen Larsen

2014-01-01

This qualitative grounded theory study explored teachers' instructional decisions around planning and practice for technology integration after participation in professional development. The purpose of this study was to determine how a long-term hybrid professional development experience influenced, if at all, math teachers' instructional…

Group Augmentation in Realistic Visual-Search Decisions via a Hybrid Brain-Computer Interface.

PubMed

Valeriani, Davide; Cinel, Caterina; Poli, Riccardo

2017-08-10

Groups have increased sensing and cognition capabilities that typically allow them to make better decisions. However, factors such as communication biases and time constraints can lead to less-than-optimal group decisions. In this study, we use a hybrid Brain-Computer Interface (hBCI) to improve the performance of groups undertaking a realistic visual-search task. Our hBCI extracts neural information from EEG signals and combines it with response times to build an estimate of the decision confidence. This is used to weigh individual responses, resulting in improved group decisions. We compare the performance of hBCI-assisted groups with the performance of non-BCI groups using standard majority voting, and non-BCI groups using weighted voting based on reported decision confidence. We also investigate the impact on group performance of a computer-mediated form of communication between members. Results across three experiments suggest that the hBCI provides significant advantages over non-BCI decision methods in all cases. We also found that our form of communication increases individual error rates by almost 50% compared to non-communicating observers, which also results in worse group performance. Communication also makes reported confidence uncorrelated with the decision correctness, thereby nullifying its value in weighing votes. In summary, best decisions are achieved by hBCI-assisted, non-communicating groups.

The hybrid nanostructure of MnCo2O4.5 nanoneedle/carbon aerogel for symmetric supercapacitors with high energy density

NASA Astrophysics Data System (ADS)

Hao, Pin; Zhao, Zhenhuan; Li, Liyi; Tuan, Chia-Chi; Li, Haidong; Sang, Yuanhua; Jiang, Huaidong; Wong, C. P.; Liu, Hong

2015-08-01

Current applications of carbon-based supercapacitors are limited by their low energy density. One promising strategy to enhance the energy density is to couple metal oxides with carbon materials. In this study, a porous MnCo2O4.5 nanoneedle/carbon aerogel hybrid nanostructure was synthesized by assembling MnCo2O4.5 nanoneedle arrays on the surface of channel walls of hierarchical porous carbon aerogels derived from chitosan for the supercapacitor application. The synthetic process of the hybrid nanostructure involves two steps, i.e. the growth of Mn-Co precursors on carbon aerogel by a hydrothermal process and the conversion of the precursor into MnCo2O4.5 nanoneedles by calcination. The carbon aerogel exhibits a high electrical conductivity, high specific surface area and porous structure, ensuring high electrochemical performance of the hybrid nanostructure when coupled with the porous MnCo2O4.5 nanoneedles. The symmetric supercapacitor using the MnCo2O4.5 nanoneedle/carbon aerogel hybrid nanostructure as the active electrode material exhibits a high energy density of about 84.3 Wh kg-1 at a power density of 600 W kg-1. The voltage window is as high as 1.5 V in neutral aqueous electrolytes. Due to the unique nanostructure of the electrodes, the capacitance retention reaches 86% over 5000 cycles.Current applications of carbon-based supercapacitors are limited by their low energy density. One promising strategy to enhance the energy density is to couple metal oxides with carbon materials. In this study, a porous MnCo2O4.5 nanoneedle/carbon aerogel hybrid nanostructure was synthesized by assembling MnCo2O4.5 nanoneedle arrays on the surface of channel walls of hierarchical porous carbon aerogels derived from chitosan for the supercapacitor application. The synthetic process of the hybrid nanostructure involves two steps, i.e. the growth of Mn-Co precursors on carbon aerogel by a hydrothermal process and the conversion of the precursor into MnCo2O4.5 nanoneedles by calcination. The carbon aerogel exhibits a high electrical conductivity, high specific surface area and porous structure, ensuring high electrochemical performance of the hybrid nanostructure when coupled with the porous MnCo2O4.5 nanoneedles. The symmetric supercapacitor using the MnCo2O4.5 nanoneedle/carbon aerogel hybrid nanostructure as the active electrode material exhibits a high energy density of about 84.3 Wh kg-1 at a power density of 600 W kg-1. The voltage window is as high as 1.5 V in neutral aqueous electrolytes. Due to the unique nanostructure of the electrodes, the capacitance retention reaches 86% over 5000 cycles. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04421a

Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task.

PubMed

Moënne-Loccoz, Cristóbal; Vergara, Rodrigo C; López, Vladimir; Mery, Domingo; Cosmelli, Diego

2017-01-01

Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT) task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task.

A Cognitive Complexity Metric Applied to Cognitive Development

ERIC Educational Resources Information Center

Andrews, Glenda; Halford, Graeme S.

2002-01-01

Two experiments tested predictions from a theory in which processing load depends on relational complexity (RC), the number of variables related in a single decision. Tasks from six domains (transitivity, hierarchical classification, class inclusion, cardinality, relative-clause sentence comprehension, and hypothesis testing) were administered to…

The Data Base and Decision Making in Public Schools.

ERIC Educational Resources Information Center

Hedges, William D.

1984-01-01

Describes generic types of databases--file management systems, relational database management systems, and network/hierarchical database management systems--with their respective strengths and weaknesses; discusses factors to be considered in determining whether a database is desirable; and provides evaluative criteria for use in choosing…

Predicting the decision to pursue mediation in civil disputes: a hierarchical classes analysis.

PubMed

Reich, Warren A; Kressel, Kenneth; Scanlon, Kathleen M; Weiner, Gary A

2007-11-01

Clients (N = 185) involved in civil court cases completed the CPR Institute's Mediation Screen, which is designed to assist in making a decision about pursuing mediation. The authors modeled data using hierarchical classes analysis (HICLAS), a clustering algorithm that places clients into 1 set of classes and CPRMS items into another set of classes. HICLAS then links the sets of classes so that any class of clients can be identified in terms of the classes of items they endorsed. HICLAS-derived item classes reflected 2 underlying themes: (a) suitability of the dispute for a problem-solving process and (b) potential benefits of mediation. All clients who perceived that mediation would be beneficial also believed that the context of their conflict was favorable to mediation; however, not all clients who saw a favorable context believed they would benefit from mediation. The majority of clients who agreed to pursue mediation endorsed items reflecting both contextual suitability and perceived benefits of mediation.

Nacre-like hybrid films: Structure, properties, and the effect of relative humidity.

PubMed

Abba, Mohammed T; Hunger, Philipp M; Kalidindi, Surya R; Wegst, Ulrike G K

2015-03-01

Functional materials often are hybrids composed of biopolymers and mineral constituents. The arrangement and interactions of the constituents frequently lead to hierarchical structures with exceptional mechanical properties and multifunctionality. In this study, hybrid thin films with a nacre-like brick-and-mortar microstructure were fabricated in a straightforward and reproducible manner through manual shear casting using the biopolymer chitosan as the matrix material (mortar) and alumina platelets as the reinforcing particles (bricks). The ratio of inorganic to organic content was varied from 0% to 15% and the relative humidities from 36% to 75% to determine their effects on the mechanical properties. It was found that increasing the volume fraction of alumina from 0% to 15% results in a twofold increase in the modulus of the film, but decreases the tensile strength by up to 30%, when the volume fraction of alumina is higher than 5%. Additionally, this study quantifies and illustrates the critical role of the relative humidity on the mechanical properties of the hybrid film. Increasing the relative humidity from 36% to 75% decreases the modulus and strength by about 45% and triples the strain at failure. These results suggest that complex hybrid materials can be manufactured and tailor made for specific applications or environmental conditions. Copyright © 2015. Published by Elsevier Ltd.

Conditional Random Field (CRF)-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

PubMed Central

Yang, Ehwa; Gwak, Jeonghwan; Jeon, Moongu

2017-01-01

Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT). In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF) for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable. PMID:28304366

In situ fabrication of depth-type hierarchical CNT/quartz fiber filters for high efficiency filtration of sub-micron aerosols and high water repellency

NASA Astrophysics Data System (ADS)

Li, Peng; Zong, Yichen; Zhang, Yingying; Yang, Mengmeng; Zhang, Rufan; Li, Shuiqing; Wei, Fei

2013-03-01

We fabricated depth-type hierarchical CNT/quartz fiber (QF) filters through in situ growth of CNTs upon quartz fiber (QF) filters using a floating catalyst chemical vapor deposition (CVD) method. The filter specific area of the CNT/QF filters is more than 12 times higher than that of the pristine QF filters. As a result, the penetration of sub-micron aerosols for CNT/QF filters is reduced by two orders of magnitude, which reaches the standard of high-efficiency particulate air (HEPA) filters. Simultaneously, due to the fluffy brush-like hierarchical structure of CNTs on QFs, the pore size of the hybrid filters only has a small increment. The pressure drop across the CNT/QF filters only increases about 50% with respect to that of the pristine QF filters, leading to an obvious increased quality factor of the CNT/QF filters. Scanning electron microscope images reveal that CNTs are very efficient in capturing sub-micron aerosols. Moreover, the CNT/QF filters show high water repellency, implying their superiority for applications in humid conditions.We fabricated depth-type hierarchical CNT/quartz fiber (QF) filters through in situ growth of CNTs upon quartz fiber (QF) filters using a floating catalyst chemical vapor deposition (CVD) method. The filter specific area of the CNT/QF filters is more than 12 times higher than that of the pristine QF filters. As a result, the penetration of sub-micron aerosols for CNT/QF filters is reduced by two orders of magnitude, which reaches the standard of high-efficiency particulate air (HEPA) filters. Simultaneously, due to the fluffy brush-like hierarchical structure of CNTs on QFs, the pore size of the hybrid filters only has a small increment. The pressure drop across the CNT/QF filters only increases about 50% with respect to that of the pristine QF filters, leading to an obvious increased quality factor of the CNT/QF filters. Scanning electron microscope images reveal that CNTs are very efficient in capturing sub-micron aerosols. Moreover, the CNT/QF filters show high water repellency, implying their superiority for applications in humid conditions. Electronic supplementary information (ESI) available: Schematic of the synthesis process of the CNT/QF filter; typical size distribution of atomized polydisperse NaCl aerosols used for air filtration testing; images of a QF filter and a CNT/QF filter; SEM image of a CNT/QF filter after 5 minutes of sonication in ethanol; calculation of porosity and filter specific area. See DOI: 10.1039/c3nr34325a

Hierarchical species distribution models

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Hierarchical Structure of the Eysenck Personality Inventory in a Large Population Sample: Goldberg's Trait-Tier Mapping Procedure

PubMed Central

Chapman, Benjamin P.; Weiss, Alexander; Barrett, Paul; Duberstein, Paul

2014-01-01

The structure of the Eysenck Personality Inventory (EPI) is poorly understood, and applications have mostly been confined to the broad Neuroticism, Extraversion, and Lie scales. Using a hierarchical factoring procedure, we mapped the sequential differentiation of EPI scales from broad, molar factors to more specific, molecular factors, in a UK population sample of over 6500 persons. Replicable facets at the lowest tier of Neuroticism included emotional fragility, mood lability, nervous tension, and rumination. The lowest order set of replicable Extraversion facets consisted of social dynamism, sociotropy, decisiveness, jocularity, social information seeking, and impulsivity. The Lie scale consisted of an interpersonal virtue and a behavioral diligence facet. Users of the EPI may be well served in some circumstances by considering its broad Neuroticism, Extraversion, and Lie scales as multifactorial, a feature that was explicitly incorporated into subsequent Eysenck inventories and is consistent with other hierarchical trait structures. PMID:25983361

A hierarchical, ontology-driven Bayesian concept for ubiquitous medical environments--a case study for pulmonary diseases.

PubMed

Maragoudakis, Manolis; Lymberopoulos, Dimitrios; Fakotakis, Nikos; Spiropoulos, Kostas

2008-01-01

The present paper extends work on an existing computer-based Decision Support System (DSS) that aims to provide assistance to physicians as regards to pulmonary diseases. The extension deals with allowing for a hierarchical decomposition of the task, at different levels of domain granularity, using a novel approach, i.e. Hierarchical Bayesian Networks. The proposed framework uses data from various networking appliances such as mobile phones and wireless medical sensors to establish a ubiquitous environment for medical treatment of pulmonary diseases. Domain knowledge is encoded at the upper levels of the hierarchy, thus making the process of generalization easier to accomplish. The experimental results were carried out under the Pulmonary Department, University Regional Hospital Patras, Patras, Greece. They have supported our initial beliefs about the ability of Bayesian networks to provide an effective, yet semantically-oriented, means of prognosis and reasoning under conditions of uncertainty.

Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact.

PubMed

Curran, Geoffrey M; Bauer, Mark; Mittman, Brian; Pyne, Jeffrey M; Stetler, Cheryl

2012-03-01

This study proposes methods for blending design components of clinical effectiveness and implementation research. Such blending can provide benefits over pursuing these lines of research independently; for example, more rapid translational gains, more effective implementation strategies, and more useful information for decision makers. This study proposes a "hybrid effectiveness-implementation" typology, describes a rationale for their use, outlines the design decisions that must be faced, and provides several real-world examples. An effectiveness-implementation hybrid design is one that takes a dual focus a priori in assessing clinical effectiveness and implementation. We propose 3 hybrid types: (1) testing effects of a clinical intervention on relevant outcomes while observing and gathering information on implementation; (2) dual testing of clinical and implementation interventions/strategies; and (3) testing of an implementation strategy while observing and gathering information on the clinical intervention's impact on relevant outcomes. The hybrid typology proposed herein must be considered a construct still in evolution. Although traditional clinical effectiveness and implementation trials are likely to remain the most common approach to moving a clinical intervention through from efficacy research to public health impact, judicious use of the proposed hybrid designs could speed the translation of research findings into routine practice.

Fabrication of highly ordered polyaniline nanocone on pristine graphene for high-performance supercapacitor electrodes

NASA Astrophysics Data System (ADS)

Song, Ningning; Wang, Wucong; Wu, Yue; Xiao, Ding; Zhao, Yaping

2018-04-01

The hybrids of pristine graphene with polyaniline were synthesized by in situ polymerizations for making a high-performance supercapacitor. The formed high-ordered PANI nanocones were vertically aligned on the graphene sheets. The length of the PANI nanocones increased with the concentration of aniline monomer. The specific capacitance of the hybrids electrode in the three-electrode system was measured as high as 481 F/g at a current density of 0.1 A/g, and its stability remained 87% after constant charge-discharge 10000 cycles at a current density of 1 A/g. This outstanding performance is attributed to the coupling effects of the pristine graphene and the hierarchical structure of the PANI possessing high specific surface area. The unique structure of the PANI provided more charge transmission pathways and fast charge-transfer speed of electrons to the pristine graphene because of its large specific area exposed to the electrolyte. The hybrid is expected to have potential applications in supercapacitor electrodes.

Optimal bit allocation for hybrid scalable/multiple-description video transmission over wireless channels

NASA Astrophysics Data System (ADS)

Jubran, Mohammad K.; Bansal, Manu; Kondi, Lisimachos P.

2006-01-01

In this paper, we consider the problem of optimal bit allocation for wireless video transmission over fading channels. We use a newly developed hybrid scalable/multiple-description codec that combines the functionality of both scalable and multiple-description codecs. It produces a base layer and multiple-description enhancement layers. Any of the enhancement layers can be decoded (in a non-hierarchical manner) with the base layer to improve the reconstructed video quality. Two different channel coding schemes (Rate-Compatible Punctured Convolutional (RCPC)/Cyclic Redundancy Check (CRC) coding and, product code Reed Solomon (RS)+RCPC/CRC coding) are used for unequal error protection of the layered bitstream. Optimal allocation of the bitrate between source and channel coding is performed for discrete sets of source coding rates and channel coding rates. Experimental results are presented for a wide range of channel conditions. Also, comparisons with classical scalable coding show the effectiveness of using hybrid scalable/multiple-description coding for wireless transmission.

Facile in situ synthesis of hierarchical porous Ni/Ni(OH)₂ hybrid sponges with excellent electrochemical energy-storage performances for supercapacitors.

PubMed

Wang, Wanren; Wang, Wenhua; Wang, Mengjiao; Guo, Xiaohui

2014-09-01

Herein, we report the in situ growth of single-crystalline Ni(OH)2 nanoflakes on a Ni support by using facile hydrothermal processes. The as-prepared Ni/Ni(OH)2 sponges were well-characterized by using X-ray diffraction (XRD), SEM, TEM, and X-ray photoelectron spectroscopy (XPS) techniques. The results revealed that the nickel-skeleton-supported Ni(OH)2 rope-like aggregates were composed of numerous intercrossed single-crystal Ni(OH)2 flake-like units. The Ni/Ni(OH)2 hybrid sponges served as electrodes and displayed ultrahigh specific capacitance (SC=3247 F g(-1)) and excellent rate-capability performance, likely owing to fast electron and ion transport, sufficient Faradic redox reaction, and robust structural integrity of the Ni/Ni(OH)2 hybrid electrode. These results support the promising application of Ni(OH)2 nanoflakes as advanced pseudocapacitor materials. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Resource-Efficient, Hierarchical Auto-Tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Computational Research Division, Lawrence Berkeley National Laboratory; NERSC, Lawrence Berkeley National Laboratory; Computer Science Department, University of California, Berkeley

2009-05-04

We apply auto-tuning to a hybrid MPI-pthreads lattice Boltzmann computation running on the Cray XT4 at National Energy Research Scientific Computing Center (NERSC). Previous work showed that multicore-specific auto-tuning can improve the performance of lattice Boltzmann magnetohydrodynamics (LBMHD) by a factor of 4x when running on dual- and quad-core Opteron dual-socket SMPs. We extend these studies to the distributed memory arena via a hybrid MPI/pthreads implementation. In addition to conventional auto-tuning at the local SMP node, we tune at the message-passing level to determine the optimal aspect ratio as well as the correct balance between MPI tasks and threads permore » MPI task. Our study presents a detailed performance analysis when moving along an isocurve of constant hardware usage: fixed total memory, total cores, and total nodes. Overall, our work points to approaches for improving intra- and inter-node efficiency on large-scale multicore systems for demanding scientific applications.« less

Cellulose acetate-based SiO2/TiO2 hybrid microsphere composite aerogel films for water-in-oil emulsion separation

NASA Astrophysics Data System (ADS)

Yang, Xue; Ma, Jianjun; Ling, Jing; Li, Na; Wang, Di; Yue, Fan; Xu, Shimei

2018-03-01

The cellulose acetate (CA)/SiO2-TiO2 hybrid microsphere composite aerogel films were successfully fabricated via water vapor-induced phase inversion of CA solution and simultaneous hydrolysis/condensation of 3-aminopropyltrimethoxysilane (APTMS) and tetrabutyl titanate (TBT) at room temperature. Micro-nano hierarchical structure was constructed on the surface of the film. The film could separate nano-sized surfactant-stabilized water-in-oil emulsions only under gravity. The flux of the film for the emulsion separation was up to 667 L m-2 h-1, while the separation efficiency was up to 99.99 wt%. Meanwhile, the film exhibited excellent stability during multiple cycles. Moreover, the film performed excellent photo-degradation performance under UV light due to the photocatalytic ability of TiO2. Facile preparation, good separation and potential biodegradation maked the CA/SiO2-TiO2 hybrid microsphere composite aerogel films a candidate in oil/water separation application.

Hybridization, agency discretion, and implementation of the U.S. Endangered Species Act.

PubMed

Lind-Riehl, Jennifer F; Mayer, Audrey L; Wellstead, Adam M; Gailing, Oliver

2016-12-01

The U.S. Endangered Species Act (ESA) requires that the "best available scientific and commercial data" be used to protect imperiled species from extinction and preserve biodiversity. However, it does not provide specific guidance on how to apply this mandate. Scientific data can be uncertain and controversial, particularly regarding species delineation and hybridization issues. The U.S. Fish and Wildlife Service (FWS) had an evolving hybrid policy to guide protection decisions for individuals of hybrid origin. Currently, this policy is in limbo because it resulted in several controversial conservation decisions in the past. Biologists from FWS must interpret and apply the best available science to their recommendations and likely use considerable discretion in making recommendations for what species to list, how to define those species, and how to recover them. We used semistructured interviews to collect data on FWS biologists' use of discretion to make recommendations for listed species with hybridization issues. These biologists had a large amount of discretion to determine the best available science and how to interpret it but generally deferred to the scientific consensus on the taxonomic status of an organism. Respondents viewed hybridization primarily as a problem in the context of the ESA, although biologists who had experience with hybridization issues were more likely to describe it in more nuanced terms. Many interviewees expressed a desire to continue the current case-by-case approach for handling hybridization issues, but some wanted more guidance on procedures (i.e., a "flexible" hybrid policy). Field-level information can provide critical insight into which policies are working (or not working) and why. The FWS biologists' we interviewed had a high level of discretion, which greatly influenced ESA implementation, particularly in the context of hybridization. © 2016 Society for Conservation Biology.

Modeling the distribution of colonial species to improve estimation of plankton concentration in ballast water

NASA Astrophysics Data System (ADS)

Rajakaruna, Harshana; VandenByllaardt, Julie; Kydd, Jocelyn; Bailey, Sarah

2018-03-01

The International Maritime Organization (IMO) has set limits on allowable plankton concentrations in ballast water discharge to minimize aquatic invasions globally. Previous guidance on ballast water sampling and compliance decision thresholds was based on the assumption that probability distributions of plankton are Poisson when spatially homogenous, or negative binomial when heterogeneous. We propose a hierarchical probability model, which incorporates distributions at the level of particles (i.e., discrete individuals plus colonies per unit volume) and also within particles (i.e., individuals per particle) to estimate the average plankton concentration in ballast water. We examined the performance of the models using data for plankton in the size class ≥ 10 μm and < 50 μm, collected from five different depths of a ballast tank of a commercial ship in three independent surveys. We show that the data fit to the negative binomial and the hierarchical probability models equally well, with both models performing better than the Poisson model at the scale of our sampling. The hierarchical probability model, which accounts for both the individuals and the colonies in a sample, reduces the uncertainty associated with the concentration estimation, and improves the power of rejecting the decision on ship's compliance when a ship does not truly comply with the standard. We show examples of how to test ballast water compliance using the above models.

A dynamic model of reasoning and memory.

PubMed

Hawkins, Guy E; Hayes, Brett K; Heit, Evan

2016-02-01

Previous models of category-based induction have neglected how the process of induction unfolds over time. We conceive of induction as a dynamic process and provide the first fine-grained examination of the distribution of response times observed in inductive reasoning. We used these data to develop and empirically test the first major quantitative modeling scheme that simultaneously accounts for inductive decisions and their time course. The model assumes that knowledge of similarity relations among novel test probes and items stored in memory drive an accumulation-to-bound sequential sampling process: Test probes with high similarity to studied exemplars are more likely to trigger a generalization response, and more rapidly, than items with low exemplar similarity. We contrast data and model predictions for inductive decisions with a recognition memory task using a common stimulus set. Hierarchical Bayesian analyses across 2 experiments demonstrated that inductive reasoning and recognition memory primarily differ in the threshold to trigger a decision: Observers required less evidence to make a property generalization judgment (induction) than an identity statement about a previously studied item (recognition). Experiment 1 and a condition emphasizing decision speed in Experiment 2 also found evidence that inductive decisions use lower quality similarity-based information than recognition. The findings suggest that induction might represent a less cautious form of recognition. We conclude that sequential sampling models grounded in exemplar-based similarity, combined with hierarchical Bayesian analysis, provide a more fine-grained and informative analysis of the processes involved in inductive reasoning than is possible solely through examination of choice data. PsycINFO Database Record (c) 2016 APA, all rights reserved.

Individual differences in attention influence perceptual decision making.

PubMed

Nunez, Michael D; Srinivasan, Ramesh; Vandekerckhove, Joachim

2015-01-01

Sequential sampling decision-making models have been successful in accounting for reaction time (RT) and accuracy data in two-alternative forced choice tasks. These models have been used to describe the behavior of populations of participants, and explanatory structures have been proposed to account for between individual variability in model parameters. In this study we show that individual differences in behavior from a novel perceptual decision making task can be attributed to (1) differences in evidence accumulation rates, (2) differences in variability of evidence accumulation within trials, and (3) differences in non-decision times across individuals. Using electroencephalography (EEG), we demonstrate that these differences in cognitive variables, in turn, can be explained by attentional differences as measured by phase-locking of steady-state visual evoked potential (SSVEP) responses to the signal and noise components of the visual stimulus. Parameters of a cognitive model (a diffusion model) were obtained from accuracy and RT distributions and related to phase-locking indices (PLIs) of SSVEPs with a single step in a hierarchical Bayesian framework. Participants who were able to suppress the SSVEP response to visual noise in high frequency bands were able to accumulate correct evidence faster and had shorter non-decision times (preprocessing or motor response times), leading to more accurate responses and faster response times. We show that the combination of cognitive modeling and neural data in a hierarchical Bayesian framework relates physiological processes to the cognitive processes of participants, and that a model with a new (out-of-sample) participant's neural data can predict that participant's behavior more accurately than models without physiological data.

Problems in Decentralized Decision making and Computation.

DTIC Science & Technology

1984-12-01

systesis being referred to. Findeisen [1982] clarifies this distinction by talking about the "programing" and "execution" phases.) 5. The lower and higher...n ... *iii... -258- Findeisen , W., (1982), "Decentralized and Hierarchical Control Under Consistency or Disagreement of Interest," Automatica, Vol. 18

A run-time control architecture for the JPL telerobot

NASA Technical Reports Server (NTRS)

Balaram, J.; Lokshin, A.; Kreutz, K.; Beahan, J.

1987-01-01

An architecture for implementing the process-level decision making for a hierarchically structured telerobot currently being implemented at the Jet Propolusion Laboratory (JPL) is described. Constraints on the architecture design, architecture partitioning concepts, and a detailed description of the existing and proposed implementations are provided.

Issues to be Considered in the Evaluation of Technical Proposals from the Ada (Trademark) Language Perspective.

DTIC Science & Technology

1985-06-10

flowcharts - hierarchical charts - data flow diagrams - finite state diagrams - control flow diagrams - decision tables/trees - entity-relationship...and beginners ; for example, is prompting via menus provided for beginners and single keystroke capability provided for experienced users? 2-13 - input

Beyond Recall in Reading Comprehension: Five Key Planning Decisions.

ERIC Educational Resources Information Center

Sinatra, Richard; Annacone, Dominic

Over the years, teacher questions have consistently aimed at literal comprehension, indicating that teachers lack understanding of the reading-thinking-questioning hierarchy. Benjamin Bloom's "Cognitive Taxonomy" can serve as a hierarchical framework for the design of questions. Within this framework, a teacher can confront decision…

A hierarchical classification method for finger knuckle print recognition

NASA Astrophysics Data System (ADS)

Kong, Tao; Yang, Gongping; Yang, Lu

2014-12-01

Finger knuckle print has recently been seen as an effective biometric technique. In this paper, we propose a hierarchical classification method for finger knuckle print recognition, which is rooted in traditional score-level fusion methods. In the proposed method, we firstly take Gabor feature as the basic feature for finger knuckle print recognition and then a new decision rule is defined based on the predefined threshold. Finally, the minor feature speeded-up robust feature is conducted for these users, who cannot be recognized by the basic feature. Extensive experiments are performed to evaluate the proposed method, and experimental results show that it can achieve a promising performance.

Decision Making Processes and Outcomes

PubMed Central

Hicks Patrick, Julie; Steele, Jenessa C.; Spencer, S. Melinda

2013-01-01

The primary aim of this study was to examine the contributions of individual characteristics and strategic processing to the prediction of decision quality. Data were provided by 176 adults, ages 18 to 93 years, who completed computerized decision-making vignettes and a battery of demographic and cognitive measures. We examined the relations among age, domain-specific experience, working memory, and three measures of strategic information search to the prediction of solution quality using a 4-step hierarchical linear regression analysis. Working memory and two measures of strategic processing uniquely contributed to the variance explained. Results are discussed in terms of potential advances to both theory and intervention efforts. PMID:24282638

Factors predicting desired autonomy in medical decisions: Risk-taking and gambling behaviors

PubMed Central

Fortune, Erica E; Shotwell, Jessica J; Buccellato, Kiara; Moran, Erin

2016-01-01

This study investigated factors that influence patients’ desired level of autonomy in medical decisions. Analyses included previously supported demographic variables in addition to risk-taking and gambling behaviors, which exhibit a strong relationship with overall health and decision-making, but have not been investigated in conjunction with medical autonomy. Participants (N = 203) completed measures on Amazon’s Mechanical Turk, including two measures of autonomy. Two hierarchical regressions revealed that the predictors explained a significant amount of variance for both measures, but the contribution of predictor variables was incongruent between models. Possible causes for this incongruence and implications for patient–physician interactions are discussed. PMID:28070406

Hydrothermal synthesis for new multifunctional materials: A few examples of phosphates and phosphonate-based hybrid materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rueff, Jean-Michel, E-mail: jean-michel.rueff@ensicaen.fr; Poienar, Maria; Guesdon, Anne

Novel physical or chemical properties are expected in a great variety of materials, in connection with the dimensionality of their structures and/or with their nanostructures, hierarchical superstructures etc. In the search of new advanced materials, the hydrothermal technique plays a crucial role, mimicking the nature able to produce fractal, hyperbranched, urchin-like or snow flake structures. In this short review including new results, this will be illustrated by examples selected in two types of materials, phosphates and phosphonates, prepared by this method. The importance of the synthesis parameters will be highlighted for a magnetic iron based phosphates and for hybrids containingmore » phosphonates organic building units crystallizing in different structural types. - Graphical abstract: Phosphate dendrite like and phosphonate platelet crystals.« less

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Hierarchical Polyphosphazene@Molybdenum Disulfide Hybrid Structure for Enhancing the Flame Retardancy and Mechanical Property of Epoxy Resins.

PubMed

Zhou, Xia; Qiu, Shuilai; Xing, Weiyi; Gangireddy, Chandra Sekhar Reddy; Gui, Zhou; Hu, Yuan

2017-08-30

A novel polyphosphazene (PZS) microsphere@molybdenum disulfide nanoflower (MoS 2 ) hierarchical hybrid architecture was first synthesized and applied for enhancing the mechanical performance and flame retardancy of epoxy (EP) resin via a cooperative effect. Herein, using PZS microsphere as the template, a layer of MoS 2 nanoflowers were anchored to PZS spheres via a hydrothermal strategy. The well-designed PZS@MoS 2 exhibits excellent fire retardancy and a reinforcing effect. The obtained PZS@MoS 2 significantly enhanced the flame-retardant performance of EP composites, which can be proved by thermogravimetric and cone calorimeter results. For instance, the incorporation of 3 wt % PZS@MoS 2 brought about a 41.3% maximum reduction in the peak heat-release rate and decreased by 30.3% maximum in the total heat release, accompanying the higher graphitized char layer. With regard to mechanical property, the storage modulus of EP/PZS@MoS 2 3.0 in the glassy state was dramatically increased to 22.4 GPa in comparison with that of pure EP (11.15 GPa). It is sensible to know that the improved flame-retardant performance for EP composites is primarily assigned to a physical barrier effect of the MoS 2 nanoflowers and the polyphosphazene structure has an positive impact on promoting char formation in the condensed phase.

A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias.

PubMed

Ma, Xiaoye; Chen, Yong; Cole, Stephen R; Chu, Haitao

2016-12-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities, and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. © The Author(s) 2014.

A Hybrid Bayesian Hierarchical Model Combining Cohort and Case-control Studies for Meta-analysis of Diagnostic Tests: Accounting for Partial Verification Bias

PubMed Central

Ma, Xiaoye; Chen, Yong; Cole, Stephen R.; Chu, Haitao

2014-01-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. PMID:24862512

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Enhanced Mechanical Performance of Bio-Inspired Hybrid Structures Utilising Topological Interlocking Geometry.

PubMed

Djumas, Lee; Molotnikov, Andrey; Simon, George P; Estrin, Yuri

2016-05-24

Structural composites inspired by nacre have emerged as prime exemplars for guiding materials design of fracture-resistant, rigid hybrid materials. The intricate microstructure of nacre, which combines a hard majority phase with a small fraction of a soft phase, achieves superior mechanical properties compared to its constituents and has generated much interest. However, replicating the hierarchical microstructure of nacre is very challenging, not to mention improving it. In this article, we propose to alter the geometry of the hard building blocks by introducing the concept of topological interlocking. This design principle has previously been shown to provide an inherently brittle material with a remarkable flexural compliance. We now demonstrate that by combining the basic architecture of nacre with topological interlocking of discrete hard building blocks, hybrid materials of a new type can be produced. By adding a soft phase at the interfaces between topologically interlocked blocks in a single-build additive manufacturing process, further improvement of mechanical properties is achieved. The design of these fabricated hybrid structures has been guided by computational work elucidating the effect of various geometries. To our knowledge, this is the first reported study that combines the advantages of nacre-inspired structures with the benefits of topological interlocking.

Complex Dynamical Behavior in Hybrid Systems

DTIC Science & Technology

2012-09-29

stability for a class of hybrid dynamical systems via averaging”, Mathematics of Control , Signals, and Systems , vol. 23, no. 4, pp...no. 7, pp. 1636-1649, 2011. J9. A.R. Teel and L. Marconi, `` Stabilization for a class of minimum phase hybrid systems under an average dwell- time ...functions for L2 and input-to-state stability in a class of quantized control systems ”, 50th IEEE Conference on Decision and Control , Dec.

Predictors of the decision to adopt motivational interviewing in community health settings.

PubMed

Williams, Jessica Roberts; Blais, Marissa Puckett; Banks, Duren; Dusablon, Tracy; Williams, Weston O; Hennessy, Kevin D

2014-07-01

The purpose of this study is to concurrently examine the impact of individual and organizational characteristics on the decision to adopt the evidence-based practice (EBP) motivational interviewing (MI) among directors and staff (n = 311) in community health organizations (n = 92). Results from hierarchical linear modeling indicated that, at the individual level, attitudes toward EBPs and race each predicted directors' decisions to adopt, while gender predicted staff's decisionmaking. At the organizational level, organizational climate was inversely associated with both staff's and directors' decisions to adopt MI. Organizational barriers to implementing EBPs and use of reading materials and treatment manuals were related to directors' decision to adopt. Type of organization and staff attributes were associated with staff's decision to adopt. These findings underscore the need to tailor dissemination and implementation strategies to address differences between directors and staff in the adoption of EBPs.

Eye Tracking and Pupillometry are Indicators of Dissociable Latent Decision Processes

PubMed Central

Cavanagh, James F.; Wiecki, Thomas V.; Kochar, Angad; Frank, Michael J.

2014-01-01

Can you predict what someone is going to do just by watching them? This is certainly difficult: it would require a clear mapping between observable indicators and unobservable cognitive states. In this report we demonstrate how this is possible by monitoring eye gaze and pupil dilation, which predict dissociable biases during decision making. We quantified decision making using the Drift Diffusion Model (DDM), which provides an algorithmic account of how evidence accumulation and response caution contribute to decisions through separate latent parameters of drift rate and decision threshold, respectively. We used a hierarchical Bayesian estimation approach to assess the single trial influence of observable physiological signals on these latent DDM parameters. Increased eye gaze dwell time specifically predicted an increased drift rate toward the fixated option, irrespective of the value of the option. In contrast, greater pupil dilation specifically predicted an increase in decision threshold during difficult decisions. These findings suggest that eye tracking and pupillometry reflect the operations of dissociated latent decision processes. PMID:24548281

Self-Healing Nanocomposite Hydrogel with Well-Controlled Dynamic Mechanics

NASA Astrophysics Data System (ADS)

Li, Qiaochu; Mishra, Sumeet; Chen, Pangkuan; Tracy, Joseph; Holten-Andersen, Niels

Network dynamics is a crucial factor that determines the macroscopic self-healing rate and efficiency in polymeric hydrogel materials, yet its controllability is seldom studied in most reported self-healing hydrogel systems. Inspired by mussel's adhesion chemistry, we developed a novel approach to assemble inorganic nanoparticles and catechol-decorated PEG polymer into a hydrogel network. When utilized as reversible polymer-particle crosslinks, catechol-metal coordination bonds yield a unique gel network with dynamic mechanics controlled directly by interfacial crosslink structure. Taking advantage of this structure-property relationship at polymer-particle interfaces, we next designed a hierarchically structured hybrid gel with two distinct relaxation timescales. By tuning the relative contribution of the two hierarchical relaxation modes, we are able to finely control the gel's dynamic mechanical behavior from a viscoelastic fluid to a stiff solid, yet preserving its fast self-healing property without the need for external stimuli.

Hierarchical ZIF-8 toward Immobilizing Burkholderia cepacia Lipase for Application in Biodiesel Preparation.

PubMed

Adnan, Miaad; Li, Kai; Wang, Jianhua; Xu, Li; Yan, Yunjun

2018-05-10

A hierarchical mesoporous zeolitic imidazolate framework (ZIF-8) was processed based on cetyltrimethylammonium bromide (CTAB) as a morphological regulating agent and amino acid (l-histidine) as assisting template agent. Burkholderia cepacia lipase (BCL) was successfully immobilized by ZIF-8 as the carrier via an adsorption method (BCL-ZIF-8). The immobilized lipase (BCL) showed utmost activity recovery up to 1279%, a 12-fold boost in its free counterpart. BCL-ZIF-8 was used as a biocatalyst in the transesterification reaction for the production of biodiesel with 93.4% yield. There was no significant lowering of conversion yield relative to original activity for BCL-ZIF-8 when continuously reused for eight cycles. This work provides a new outlook for biotechnological importance by immobilizing lipase on the hybrid catalyst (ZIF-8) and opens the door for its uses in the industrial field.

3D flower-like hierarchical Ag@nickel-cobalt hydroxide microsphere with enhanced electrochemical properties

NASA Astrophysics Data System (ADS)

Lv, Zijian; Zhong, Qin; Bu, Yunfei; Wu, Junpeng

2016-10-01

The morphology and electrical conductivity are essential to electrochemical performance of electrode materials in renewable energy conversion and storage technologies such as fuel cells and supercapacitors. Here, we explored a facile method to grow Ag@nickel-cobalt layered double hydroxide (Ag@Ni/Co-LDHs) with 3D flower-like microsphere structure. The results show the morphology of Ni/Co-LDHs varies with the introduction of Ag species. The prepared Ag@Ni/Co-LDHs not only exhibits an open hierarchical structure with high specific capacitance but also shows good electrical conductivity to support fast electron transport. Benefiting from the unique structural features, these flower-like Ag@Ni/Co-LDHs microspheres have impressive specific capacitance as high as 1768 F g-1 at 1 A g-1. It can be concluded that engineering the structure of the electrode can increase the efficiency of the specific capacitance as a battery-type electrode for hybrid supercapacitors.

Characterization of a Hierarchical Network of Hyaluronic Acid/Gelatin Composite for use as a Smart Injectable Biomaterial

PubMed Central

Heris, Hossein K.; Rahmat, Meysam

2015-01-01

Hybrid HA/Ge hydrogel particles are embedded in a secondary HA network to improve their structural integrity. The internal microstructure of the particles is imaged through TEM. CSLM is used to identify the location of the Ge molecules in the microgels. Through indentation tests, the Young’s modulus of the individual particles is found to be 22 ± 2.5 kPa. The overall shear modulus of the composite is 75 ± 15 Pa at 1 Hz. The mechanical properties of the substrate are found to be viable for cell adhesion. The particles’ diameter at pH = 8 is twice that at pH = 5. The pH sensitivity is found to be appropriate for smart drug delivery. Based on their mechanical and structural properties, HA–Ge hierarchical materials may be well suited for use as injectable biomaterials for tissue reconstruction. PMID:22147507

Morphological Influences on the Recognition of Monosyllabic Monomorphemic Words

ERIC Educational Resources Information Center

Baayen, R. H.; Feldman, L. B.; Schreuder, R.

2006-01-01

Balota et al. [Balota, D., Cortese, M., Sergent-Marshall, S., Spieler, D., & Yap, M. (2004). Visual word recognition for single-syllable words. "Journal of Experimental Psychology: General, 133," 283-316] studied lexical processing in word naming and lexical decision using hierarchical multiple regression techniques for a large data set of…

Bio-Inspired Distributed Decision Algorithms for Anomaly Detection

DTIC Science & Technology

2017-03-01

TERMS DIAMoND, Local Anomaly Detector, Total Impact Estimation, Threat Level Estimator 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU...21 4.2 Performance of the DIAMoND Algorithm as a DNS-Server Level Attack Detection and Mitigation...with 6 Nodes ........................................................................................ 13 8 Hierarchical 2- Level Topology

Improved Space-Time Forecasting of next Day Ozone Concentrations in the Eastern U.S.

EPA Science Inventory

There is an urgent need to provide accurate air quality information and forecasts to the general public and environmental health decision-makers. This paper develops a hierarchical space-time model for daily 8-hour maximum ozone concentration (O3) data covering much of the easter...

In Search of Rationality: The Purposes behind the Use of Formal Analysis in Organizations.

ERIC Educational Resources Information Center

Langley, Ann

1989-01-01

Examines how formal analysis is actually practiced in 3 different organizations. Identifies 4 main groups of purposes for formal analysis and relates them to various hierarchical relationships. Formal analysis and social interaction seem inextricably linked in organizational decision-making. Different structural configurations may generate…

Active Commuting Patterns at a Large, Midwestern College Campus

ERIC Educational Resources Information Center

Bopp, Melissa; Kaczynski, Andrew; Wittman, Pamela

2011-01-01

Objective: To understand patterns and influences on active commuting (AC) behavior. Participants: Students and faculty/staff at a university campus. Methods: In April-May 2008, respondents answered an online survey about mode of travel to campus and influences on commuting decisions. Hierarchical regression analyses predicted variance in walking…

The Homeland Security Ecosystem: An Analysis of Hierarchical and Ecosystem Models and Their Influence on Decision Makers

DTIC Science & Technology

2012-12-01

flows, diversity, emergence, networks, fusion, strategic planning, information sharing, ecosystem, hierarchy, NJ Regional Operations Intelligence ...Related Information...........................................................................79 viii 3. Production of Disaster Intelligence for... Intelligence for Field Personnel .................80 5. Focused Collection Efforts to Support FEMA and NJ OEM Operations

Staff Nurses’ Perceptions and Experiences about Structural Empowerment: A Qualitative Phenomenological Study

PubMed Central

Van Bogaert, Peter; Peremans, Lieve; Diltour, Nadine; Van heusden, Danny; Dilles, Tinne; Van Rompaey, Bart; Havens, Donna Sullivan

2016-01-01

The aim of the study reported in this article was to investigate staff nurses’ perceptions and experiences about structural empowerment and perceptions regarding the extent to which structural empowerment supports safe quality patient care. To address the complex needs of patients, staff nurse involvement in clinical and organizational decision-making processes within interdisciplinary care settings is crucial. A qualitative study was conducted using individual semi-structured interviews of 11 staff nurses assigned to medical or surgical units in a 600-bed university hospital in Belgium. During the study period, the hospital was going through an organizational transformation process to move from a classic hierarchical and departmental organizational structure to one that was flat and interdisciplinary. Staff nurses reported experiencing structural empowerment and they were willing to be involved in decision-making processes primarily about patient care within the context of their practice unit. However, participants were not always fully aware of the challenges and the effect of empowerment on their daily practice, the quality of care and patient safety. Ongoing hospital change initiatives supported staff nurses’ involvement in decision-making processes for certain matters but for some decisions, a classic hierarchical and departmental process still remained. Nurses perceived relatively high work demands and at times viewed empowerment as presenting additional. Staff nurses recognized the opportunities structural empowerment provided within their daily practice. Nurse managers and unit climate were seen as crucial for success while lack of time and perceived work demands were viewed as barriers to empowerment. PMID:27035457

Staff Nurses' Perceptions and Experiences about Structural Empowerment: A Qualitative Phenomenological Study.

PubMed

Van Bogaert, Peter; Peremans, Lieve; Diltour, Nadine; Van heusden, Danny; Dilles, Tinne; Van Rompaey, Bart; Havens, Donna Sullivan

2016-01-01

The aim of the study reported in this article was to investigate staff nurses' perceptions and experiences about structural empowerment and perceptions regarding the extent to which structural empowerment supports safe quality patient care. To address the complex needs of patients, staff nurse involvement in clinical and organizational decision-making processes within interdisciplinary care settings is crucial. A qualitative study was conducted using individual semi-structured interviews of 11 staff nurses assigned to medical or surgical units in a 600-bed university hospital in Belgium. During the study period, the hospital was going through an organizational transformation process to move from a classic hierarchical and departmental organizational structure to one that was flat and interdisciplinary. Staff nurses reported experiencing structural empowerment and they were willing to be involved in decision-making processes primarily about patient care within the context of their practice unit. However, participants were not always fully aware of the challenges and the effect of empowerment on their daily practice, the quality of care and patient safety. Ongoing hospital change initiatives supported staff nurses' involvement in decision-making processes for certain matters but for some decisions, a classic hierarchical and departmental process still remained. Nurses perceived relatively high work demands and at times viewed empowerment as presenting additional. Staff nurses recognized the opportunities structural empowerment provided within their daily practice. Nurse managers and unit climate were seen as crucial for success while lack of time and perceived work demands were viewed as barriers to empowerment.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility.

PubMed

Breitfeld, P P; Weisburd, M; Overhage, J M; Sledge, G; Tierney, W M

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites.

Pilot Study of a Point-of-use Decision Support Tool for Cancer Clinical Trials Eligibility

PubMed Central

Breitfeld, Philip P.; Weisburd, Marina; Overhage, J. Marc; Sledge, George; Tierney, William M.

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites. PMID:10579605

Wavelet Algorithms for Illumination Computations

NASA Astrophysics Data System (ADS)

Schroder, Peter

One of the core problems of computer graphics is the computation of the equilibrium distribution of light in a scene. This distribution is given as the solution to a Fredholm integral equation of the second kind involving an integral over all surfaces in the scene. In the general case such solutions can only be numerically approximated, and are generally costly to compute, due to the geometric complexity of typical computer graphics scenes. For this computation both Monte Carlo and finite element techniques (or hybrid approaches) are typically used. A simplified version of the illumination problem is known as radiosity, which assumes that all surfaces are diffuse reflectors. For this case hierarchical techniques, first introduced by Hanrahan et al. (32), have recently gained prominence. The hierarchical approaches lead to an asymptotic improvement when only finite precision is required. The resulting algorithms have cost proportional to O(k^2 + n) versus the usual O(n^2) (k is the number of input surfaces, n the number of finite elements into which the input surfaces are meshed). Similarly a hierarchical technique has been introduced for the more general radiance problem (which allows glossy reflectors) by Aupperle et al. (6). In this dissertation we show the equivalence of these hierarchical techniques to the use of a Haar wavelet basis in a general Galerkin framework. By so doing, we come to a deeper understanding of the properties of the numerical approximations used and are able to extend the hierarchical techniques to higher orders. In particular, we show the correspondence of the geometric arguments underlying hierarchical methods to the theory of Calderon-Zygmund operators and their sparse realization in wavelet bases. The resulting wavelet algorithms for radiosity and radiance are analyzed and numerical results achieved with our implementation are reported. We find that the resulting algorithms achieve smaller and smoother errors at equivalent work.

Efficient processing of multiple nested event pattern queries over multi-dimensional event streams based on a triaxial hierarchical model.

PubMed

Xiao, Fuyuan; Aritsugi, Masayoshi; Wang, Qing; Zhang, Rong

2016-09-01

For efficient and sophisticated analysis of complex event patterns that appear in streams of big data from health care information systems and support for decision-making, a triaxial hierarchical model is proposed in this paper. Our triaxial hierarchical model is developed by focusing on hierarchies among nested event pattern queries with an event concept hierarchy, thereby allowing us to identify the relationships among the expressions and sub-expressions of the queries extensively. We devise a cost-based heuristic by means of the triaxial hierarchical model to find an optimised query execution plan in terms of the costs of both the operators and the communications between them. According to the triaxial hierarchical model, we can also calculate how to reuse the results of the common sub-expressions in multiple queries. By integrating the optimised query execution plan with the reuse schemes, a multi-query optimisation strategy is developed to accomplish efficient processing of multiple nested event pattern queries. We present empirical studies in which the performance of multi-query optimisation strategy was examined under various stream input rates and workloads. Specifically, the workloads of pattern queries can be used for supporting monitoring patients' conditions. On the other hand, experiments with varying input rates of streams can correspond to changes of the numbers of patients that a system should manage, whereas burst input rates can correspond to changes of rushes of patients to be taken care of. The experimental results have shown that, in Workload 1, our proposal can improve about 4 and 2 times throughput comparing with the relative works, respectively; in Workload 2, our proposal can improve about 3 and 2 times throughput comparing with the relative works, respectively; in Workload 3, our proposal can improve about 6 times throughput comparing with the relative work. The experimental results demonstrated that our proposal was able to process complex queries efficiently which can support health information systems and further decision-making. Copyright © 2016 Elsevier B.V. All rights reserved.

Sure I'm Sure: Prefrontal Oscillations Support Metacognitive Monitoring of Decision Making.

PubMed

Wokke, Martijn E; Cleeremans, Axel; Ridderinkhof, K Richard

2017-01-25

Successful decision making critically involves metacognitive processes such as monitoring and control of our decision process. Metacognition enables agents to modify ongoing behavior adaptively and determine what to do next in situations in which external feedback is not (immediately) available. Despite the importance of metacognition for many aspects of life, little is known about how our metacognitive system operates or about what kind of information is used for metacognitive (second-order) judgments. In particular, it remains an open question whether metacognitive judgments are based on the same information as first-order decisions. Here, we investigated the relationship between metacognitive performance and first-order task performance by recording EEG signals while participants were asked to make a "diagnosis" after seeing a sample of fictitious patient data (a complex pattern of colored moving dots of different sizes). To assess metacognitive performance, participants provided an estimate about the quality of their diagnosis on each trial. Results demonstrate that the information that contributes to first-order decisions differs from the information that supports metacognitive judgments. Further, time-frequency analyses of EEG signals reveal that metacognitive performance is associated specifically with prefrontal theta-band activity. Together, our findings are consistent with a hierarchical model of metacognition and suggest a crucial role for prefrontal oscillations in metacognitive performance. Monitoring and control of our decision process (metacognition) is a crucial aspect of adaptive decision making. Crucially, metacognitive skills enable us to adjust ongoing behavior and determine future decision making when immediate feedback is not available. In the present study, we constructed a "diagnosis task" that allowed us to assess in what way first-order task performance and metacognition are related to each other. Results demonstrate that the contribution of sensory evidence (size, color, and motion direction) differs between first- and second-order decision making. Further, our results indicate that metacognitive performance specifically is orchestrated by means of prefrontal theta oscillations. Together, our findings suggest a hierarchical model of metacognition. Copyright © 2017 the authors 0270-6474/17/370781-09$15.00/0.

Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior

PubMed Central

Bai, Yu; Katahira, Kentaro; Ohira, Hideki

2014-01-01

Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model. PMID:25161635

High-energy lithium-ion hybrid supercapacitors composed of hierarchical urchin-like WO3/C anodes and MOF-derived polyhedral hollow carbon cathodes.

PubMed

Xu, Juan; Li, Yuanyuan; Wang, Lei; Cai, Qifa; Li, Qingwei; Gao, Biao; Zhang, Xuming; Huo, Kaifu; Chu, Paul K

2016-09-22

A lithium-ion hybrid supercapacitor (Li-HSC) comprising a Li-ion battery type anode and an electrochemical double layer capacitance (EDLC) type cathode has attracted much interest because it accomplishes a large energy density without compromising the power density. In this work, hierarchical carbon coated WO 3 (WO 3 /C) with a unique mesoporous structure and metal-organic framework derived nitrogen-doped carbon hollow polyhedra (MOF-NC) are prepared and adopted as the anode and the cathode for Li-HSCs. The hierarchical mesoporous WO 3 /C microspheres assembled by radially oriented WO 3 /C nanorods along the (001) plane enable effective Li + insertion, thus exhibit high capacity, excellent rate performance and a long cycling life due to their high Li + conductivity, electronic conductivity and structural robustness. The WO 3 /C structure shows a reversible specific capacity of 508 mA h g -1 at a 0.1 C rate (1 C = 696 mA h g -1 ) after 160 discharging-charging cycles with excellent rate capability. The MOF-NC achieved the specific capacity of 269.9 F g -1 at a current density of 0.2 A g -1 . At a high current density of 6 A g -1 , 92.4% of the initial capacity could be retained after 2000 discharging-charging cycles, suggesting excellent cycle stability. The Li-HSC comprising a WO 3 /C anode and a MOF-NC cathode boasts a large energy density of 159.97 W h kg -1 at a power density of 173.6 W kg -1 and 88.3% of the capacity is retained at a current density of 5 A g -1 after 3000 charging-discharging cycles, which are better than those previously reported for Li-HSCs. The high energy and power densities of the Li-HSCs of WO 3 /C//MOF-NC render large potential in energy storage.

Self-assembly of hierarchically ordered structures in DNA nanotube systems

NASA Astrophysics Data System (ADS)

Glaser, Martin; Schnauß, Jörg; Tschirner, Teresa; Schmidt, B. U. Sebastian; Moebius-Winkler, Maximilian; Käs, Josef A.; Smith, David M.

2016-05-01

The self-assembly of molecular and macromolecular building blocks into organized patterns is a complex process found in diverse systems over a wide range of size and time scales. The formation of star- or aster-like configurations, for example, is a common characteristic in solutions of polymers or other molecules containing multi-scaled, hierarchical assembly processes. This is a recurring phenomenon in numerous pattern-forming systems ranging from cellular constructs to solutions of ferromagnetic colloids or synthetic plastics. To date, however, it has not been possible to systematically parameterize structural properties of the constituent components in order to study their influence on assembled states. Here, we circumvent this limitation by using DNA nanotubes with programmable mechanical properties as our basic building blocks. A small set of DNA oligonucleotides can be chosen to hybridize into micron-length DNA nanotubes with a well-defined circumference and stiffness. The self-assembly of these nanotubes to hierarchically ordered structures is driven by depletion forces caused by the presence of polyethylene glycol. This trait allowed us to investigate self-assembly effects while maintaining a complete decoupling of density, self-association or bundling strength, and stiffness of the nanotubes. Our findings show diverse ranges of emerging structures including heterogeneous networks, aster-like structures, and densely bundled needle-like structures, which compare to configurations found in many other systems. These show a strong dependence not only on concentration and bundling strength, but also on the underlying mechanical properties of the nanotubes. Similar network architectures to those caused by depletion forces in the low-density regime are obtained when an alternative hybridization-based bundling mechanism is employed to induce self-assembly in an isotropic network of pre-formed DNA nanotubes. This emphasizes the universal effect inevitable attractive forces in crowded environments have on systems of self-assembling soft matter, which should be considered for macromolecular structures applied in crowded systems such as cells.

Multiplex acute leukemia cytosensing using multifunctional hybrid electrochemical nanoprobes at a hierarchically nanoarchitectured electrode interface

NASA Astrophysics Data System (ADS)

Zheng, Tingting; Tan, Tingting; Zhang, Qingfeng; Fu, Jia-Ju; Wu, Jia-Jun; Zhang, Kui; Zhu, Jun-Jie; Wang, Hui

2013-10-01

We have developed a robust, nanobiotechnology-based electrochemical cytosensing approach with high sensitivity, selectivity, and reproducibility toward the simultaneous multiplex detection and classification of both acute myeloid leukemia and acute lymphocytic leukemia cells. The construction of the electrochemical cytosensor involves the hierarchical assembly of dual aptamer-functionalized, multilayered graphene-Au nanoparticle electrode interface and the utilization of hybrid electrochemical nanoprobes co-functionalized with redox tags, horseradish peroxidase, and cell-targeting nucleic acid aptamers. The hybrid nanoprobes are multifunctional, capable of specifically targeting the cells of interest, amplifying the electrochemical signals, and generating distinguishable signals for multiplex cytosensing. The as-assembled electrode interface not only greatly facilitates the interfacial electron transfer process due to its high conductivity and surface area but also exhibits excellent biocompatibility and specificity for cell recognition and adhesion. A superstructured sandwich-type sensor geometry is adopted for electrochemical cytosensing, with the cells of interest sandwiched between the nanoprobes and the electrode interface. Such an electrochemical sensing strategy allows for ultrasensitive, multiplex acute leukemia cytosensing with a detection limit as low as ~350 cells per mL and a wide linear response range from 5 × 102 to 1 × 107 cells per mL for HL-60 and CEM cells, with minimal cross-reactivity and interference from non-targeting cells. This electrochemical cytosensing approach holds great promise as a new point-of-care diagnostic tool for early detection and classification of human acute leukemia and may be readily expanded to multiplex cytosensing of other cancer cells.We have developed a robust, nanobiotechnology-based electrochemical cytosensing approach with high sensitivity, selectivity, and reproducibility toward the simultaneous multiplex detection and classification of both acute myeloid leukemia and acute lymphocytic leukemia cells. The construction of the electrochemical cytosensor involves the hierarchical assembly of dual aptamer-functionalized, multilayered graphene-Au nanoparticle electrode interface and the utilization of hybrid electrochemical nanoprobes co-functionalized with redox tags, horseradish peroxidase, and cell-targeting nucleic acid aptamers. The hybrid nanoprobes are multifunctional, capable of specifically targeting the cells of interest, amplifying the electrochemical signals, and generating distinguishable signals for multiplex cytosensing. The as-assembled electrode interface not only greatly facilitates the interfacial electron transfer process due to its high conductivity and surface area but also exhibits excellent biocompatibility and specificity for cell recognition and adhesion. A superstructured sandwich-type sensor geometry is adopted for electrochemical cytosensing, with the cells of interest sandwiched between the nanoprobes and the electrode interface. Such an electrochemical sensing strategy allows for ultrasensitive, multiplex acute leukemia cytosensing with a detection limit as low as ~350 cells per mL and a wide linear response range from 5 × 102 to 1 × 107 cells per mL for HL-60 and CEM cells, with minimal cross-reactivity and interference from non-targeting cells. This electrochemical cytosensing approach holds great promise as a new point-of-care diagnostic tool for early detection and classification of human acute leukemia and may be readily expanded to multiplex cytosensing of other cancer cells. Electronic supplementary information (ESI) available: Additional figures as noted in the text. See DOI: 10.1039/c3nr02903d

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Hierarchical MnO2 nanosheets synthesized via electrodeposition-hydrothermal method for supercapacitor electrodes

NASA Astrophysics Data System (ADS)

Zheng, Dongdong; Qiang, Yujie; Xu, Shenying; Li, Wenpo; Yu, Shanshan; Zhang, Shengtao

2017-02-01

Metal oxides have emerged as one kind of important supercapacitor electrode materials. Herein, we report hierarchical MnO2 nanosheets prepared of indium tin oxide (ITO) coated glass substrates via a hybrid two-step protocol, including a cathodic electrodeposition technique and a hydrothermal process. The samples are characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM) with energy dispersive X-ray spectroscopy (EDX), and transmission electron microscope (TEM). SEM and TEM images show that the as-synthesized MnO2 nanosheets are hierarchical and porous, which could increase the active surface and short paths for fast ion diffusion. The results of nitrogen adsorption-desorption analysis indicate that the BET surface area of the MnO2 nanosheets is 53.031 m2 g-1. Furthermore, the electrochemical properties of the MnO2 are elucidated by cyclic voltammograms (CV), galvanostatic charge-discharge (GCD) tests, and electrochemical impedance spectroscopy (EIS) in 0.1 M Na2SO4 electrolyte. The electrochemical results demonstrate that the as-grown MnO2 nanosheet exhibits an excellent specific capacitance of 335 F g-1 at 0.5 A g-1 when it is applied as a potential electrode material for an electrochemical supercapacitor. Additionally, the MnO2 nanosheet electrode also presents high rate capability and good cycling stability with 91.8% retention after 1000 cycles. These excellent properties indicate that the hierarchical MnO2 nanosheets are a potential electrode material for electrochemical supercapacitors.

A spatial analysis of hierarchical waste transport structures under growing demand.

PubMed

Tanguy, Audrey; Glaus, Mathias; Laforest, Valérie; Villot, Jonathan; Hausler, Robert

2016-10-01

The design of waste management systems rarely accounts for the spatio-temporal evolution of the demand. However, recent studies suggest that this evolution affects the planning of waste management activities like the choice and location of treatment facilities. As a result, the transport structure could also be affected by these changes. The objective of this paper is to study the influence of the spatio-temporal evolution of the demand on the strategic planning of a waste transport structure. More particularly this study aims at evaluating the effect of varying spatial parameters on the economic performance of hierarchical structures (with one transfer station). To this end, three consecutive generations of three different spatial distributions were tested for hierarchical and non-hierarchical transport structures based on costs minimization. Results showed that a hierarchical structure is economically viable for large and clustered spatial distributions. The distance parameter was decisive but the loading ratio of trucks and the formation of clusters of sources also impacted the attractiveness of the transfer station. Thus the territories' morphology should influence strategies as regards to the installation of transfer stations. The use of spatial-explicit tools such as the transport model presented in this work that take into account the territory's evolution are needed to help waste managers in the strategic planning of waste transport structures. © The Author(s) 2016.

Hybrid Operations in Patients with Peripheral Arterial Disease

PubMed Central

Murakami, Atsubumi

2018-01-01

In this seminar, I would like to discuss the recent hybrid operations in patients with peripheral arterial diseases. Hybrid is generally defined as combinations of different types of things. In the surgical community, it is loosely defined as therapy combining open surgery (OS) and endovascular therapy (EVT). In practice, combination surgery of diseased inflow vessels by EVT and outflow vessels by OS is a typical example, namely, the combination therapy of thromboendarterectomy (TEA) for common femoral artery and EVT (PTA and stenting) for iliac artery in patients with PAD (ilio-femoral lesions). Also, there is the potential of various combinations of OS and EVT for complex lesions. Unfortunately, we do not have specific guidelines for hybrid therapy of PAD, but in clinical practices, justified decision-making for surgical indication is strictly required. I emphasize that the cardiovascular surgeon (or vascular specialist) must have the ability of decision-making for suitable combination therapy of OS and EVT which adheres to existing specific guidelines. (This is a translation of Jpn J Vasc Surg 2017; 26: 275–283.) PMID:29682108

Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions.

PubMed

Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S

2014-06-01

Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.

Patient decision-making preference and physician decision-making style for contraceptive method choice in an Asian culture: does concordance matter?

PubMed

Alden, Dana Latham; Merz, Miwa Yamazaki; Thi, Le Minh

2010-12-01

This study investigates preferences for patient-physician decision-making in an emerging economy with an Asian culture. A survey of 445 randomly sampled women, aged 20-40 in Hanoi, Vietnam, revealed that pre-consultation attitudes were most positive toward a "shared" decision-making approach with the physician for contraceptive method choice. However, following random assignment to one of three vignettes (passive, shared or autonomous) featuring a young Vietnamese woman reaching a contraceptive method decision with her physician, preference was highest for the "autonomous" approach. Furthermore, discordance between pre-consultation preference for decision-making style and the physician's decision-making style negatively impacted evaluations under some but not all circumstances. This study demonstrates that, despite living in a hierarchic Asian culture, active participation in contraceptive method choice is desired by many urban Vietnamese women. However, there is variation on this dimension and adjusting the physician's style to be concordant with patient preference appears important to maximizing patient satisfaction.

One-step synthesis of graphene nanoribbon-MnO2 hybrids and their all-solid-state asymmetric supercapacitors

NASA Astrophysics Data System (ADS)

Liu, Mingkai; Tjiu, Weng Weei; Pan, Jisheng; Zhang, Chao; Gao, Wei; Liu, Tianxi

2014-03-01

Three-dimensional (3D) hierarchical hybrid nanomaterials (GNR-MnO2) of graphene nanoribbons (GNR) and MnO2 nanoparticles have been prepared via a one-step method. GNR, with unique features such as high aspect ratio and plane integrity, has been obtained by longitudinal unzipping of multi-walled carbon nanotubes (CNTs). By tuning the amount of oxidant used, different mass loadings of MnO2 nanoparticles have been uniformly deposited on the surface of GNRs. Asymmetric supercapacitors have been fabricated with the GNR-MnO2 hybrid as the positive electrode and GNR sheets as the negative electrode. Due to the desirable porous structure, excellent electrical conductivity, as well as high rate capability and specific capacitances of both the GNR and GNR-MnO2 hybrid, the optimized GNR//GNR-MnO2 asymmetric supercapacitor can be cycled reversibly in an enlarged potential window of 0-2.0 V. In addition, the fabricated GNR//GNR-MnO2 asymmetric supercapacitor exhibits a significantly enhanced maximum energy density of 29.4 W h kg-1 (at a power density of 12.1 kW kg-1), compared with that of the symmetric cells based on GNR-MnO2 hybrids or GNR sheets. This greatly enhanced energy storage ability and high rate capability can be attributed to the homogeneous dispersion and excellent pseudocapacitive performance of MnO2 nanoparticles and the high electrical conductivity of the GNRs.Three-dimensional (3D) hierarchical hybrid nanomaterials (GNR-MnO2) of graphene nanoribbons (GNR) and MnO2 nanoparticles have been prepared via a one-step method. GNR, with unique features such as high aspect ratio and plane integrity, has been obtained by longitudinal unzipping of multi-walled carbon nanotubes (CNTs). By tuning the amount of oxidant used, different mass loadings of MnO2 nanoparticles have been uniformly deposited on the surface of GNRs. Asymmetric supercapacitors have been fabricated with the GNR-MnO2 hybrid as the positive electrode and GNR sheets as the negative electrode. Due to the desirable porous structure, excellent electrical conductivity, as well as high rate capability and specific capacitances of both the GNR and GNR-MnO2 hybrid, the optimized GNR//GNR-MnO2 asymmetric supercapacitor can be cycled reversibly in an enlarged potential window of 0-2.0 V. In addition, the fabricated GNR//GNR-MnO2 asymmetric supercapacitor exhibits a significantly enhanced maximum energy density of 29.4 W h kg-1 (at a power density of 12.1 kW kg-1), compared with that of the symmetric cells based on GNR-MnO2 hybrids or GNR sheets. This greatly enhanced energy storage ability and high rate capability can be attributed to the homogeneous dispersion and excellent pseudocapacitive performance of MnO2 nanoparticles and the high electrical conductivity of the GNRs. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr06650a

Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

NASA Astrophysics Data System (ADS)

Zaiwani, B. E.; Zarlis, M.; Efendi, S.

2018-03-01

In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

A quantitative method for evaluating alternatives. [aid to decision making

NASA Technical Reports Server (NTRS)

Forthofer, M. J.

1981-01-01

When faced with choosing between alternatives, people tend to use a number of criteria (often subjective, rather than objective) to decide which is the best alternative for them given their unique situation. The subjectivity inherent in the decision-making process can be reduced by the definition and use of a quantitative method for evaluating alternatives. This type of method can help decision makers achieve degree of uniformity and completeness in the evaluation process, as well as an increased sensitivity to the factors involved. Additional side-effects are better documentation and visibility of the rationale behind the resulting decisions. General guidelines for defining a quantitative method are presented and a particular method (called 'hierarchical weighted average') is defined and applied to the evaluation of design alternatives for a hypothetical computer system capability.

Does empowering resident families or nursing home employees in decision making improve service quality?

PubMed

Hamann, Darla J

2014-08-01

This research examines how the empowerment of residents' family members and nursing home employees in managerial decision making is related to service quality. The study was conducted using data from 33 nursing homes in the United States. Surveys were administered to more than 1,000 employees on-site and mailed to the primary-contact family member of each resident. The resulting multilevel data were analyzed using hierarchical linear modeling. The empowerment of families in decision making was positively associated with their perceptions of service quality. The empowerment of nursing staff in decision making was more strongly related to service quality than the empowerment of nonnursing staff. Among nursing staff, the empowerment of nursing assistants improved service quality more than the empowerment of nurses. © The Author(s) 2013.

Methods Used to Support a Life Cycle of Complex Engineering Products

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Kolegova, Olga A.; Nekrasova, Maria E.; Eremenko, Andrey O.

2016-08-01

Management of companies involved in the design, development and operation of complex engineering products recognize the relevance of creating systems for product lifecycle management. A system of methods is proposed to support life cycles of complex engineering products, based on fuzzy set theory and hierarchical analysis. The system of methods serves to demonstrate the grounds for making strategic decisions in an environment of uncertainty, allows the use of expert knowledge, and provides interconnection of decisions at all phases of strategic management and all stages of a complex engineering product lifecycle.

One-step synthesis of graphene nanoribbon-MnO₂ hybrids and their all-solid-state asymmetric supercapacitors.

PubMed

Liu, Mingkai; Tjiu, Weng Weei; Pan, Jisheng; Zhang, Chao; Gao, Wei; Liu, Tianxi

2014-04-21

Three-dimensional (3D) hierarchical hybrid nanomaterials (GNR-MnO₂) of graphene nanoribbons (GNR) and MnO₂ nanoparticles have been prepared via a one-step method. GNR, with unique features such as high aspect ratio and plane integrity, has been obtained by longitudinal unzipping of multi-walled carbon nanotubes (CNTs). By tuning the amount of oxidant used, different mass loadings of MnO₂ nanoparticles have been uniformly deposited on the surface of GNRs. Asymmetric supercapacitors have been fabricated with the GNR-MnO₂ hybrid as the positive electrode and GNR sheets as the negative electrode. Due to the desirable porous structure, excellent electrical conductivity, as well as high rate capability and specific capacitances of both the GNR and GNR-MnO₂ hybrid, the optimized GNR//GNR-MnO₂ asymmetric supercapacitor can be cycled reversibly in an enlarged potential window of 0-2.0 V. In addition, the fabricated GNR//GNR-MnO₂ asymmetric supercapacitor exhibits a significantly enhanced maximum energy density of 29.4 W h kg(-1) (at a power density of 12.1 kW kg(-1)), compared with that of the symmetric cells based on GNR-MnO₂ hybrids or GNR sheets. This greatly enhanced energy storage ability and high rate capability can be attributed to the homogeneous dispersion and excellent pseudocapacitive performance of MnO₂ nanoparticles and the high electrical conductivity of the GNRs.

The hybrid nanostructure of MnCo2O4.5 nanoneedle/carbon aerogel for symmetric supercapacitors with high energy density.

PubMed

Hao, Pin; Zhao, Zhenhuan; Li, Liyi; Tuan, Chia-Chi; Li, Haidong; Sang, Yuanhua; Jiang, Huaidong; Wong, C P; Liu, Hong

2015-09-14

Current applications of carbon-based supercapacitors are limited by their low energy density. One promising strategy to enhance the energy density is to couple metal oxides with carbon materials. In this study, a porous MnCo2O4.5 nanoneedle/carbon aerogel hybrid nanostructure was synthesized by assembling MnCo2O4.5 nanoneedle arrays on the surface of channel walls of hierarchical porous carbon aerogels derived from chitosan for the supercapacitor application. The synthetic process of the hybrid nanostructure involves two steps, i.e. the growth of Mn-Co precursors on carbon aerogel by a hydrothermal process and the conversion of the precursor into MnCo2O4.5 nanoneedles by calcination. The carbon aerogel exhibits a high electrical conductivity, high specific surface area and porous structure, ensuring high electrochemical performance of the hybrid nanostructure when coupled with the porous MnCo2O4.5 nanoneedles. The symmetric supercapacitor using the MnCo2O4.5 nanoneedle/carbon aerogel hybrid nanostructure as the active electrode material exhibits a high energy density of about 84.3 Wh kg(-1) at a power density of 600 W kg(-1). The voltage window is as high as 1.5 V in neutral aqueous electrolytes. Due to the unique nanostructure of the electrodes, the capacitance retention reaches 86% over 5000 cycles.

Self-assembly of cobalt-centered metal organic framework and multiwalled carbon nanotubes hybrids as a highly active and corrosion-resistant bifunctional oxygen catalyst

NASA Astrophysics Data System (ADS)

Fang, Yiyun; Li, Xinzhe; Li, Feng; Lin, Xiaoqing; Tian, Min; Long, Xuefeng; An, Xingcai; Fu, Yan; Jin, Jun; Ma, Jiantai

2016-09-01

Metal organic frameworks (MOF) derived carbonaceous materials have emerged as promising bifunctional oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) catalysts for electrochemical energy conversion and storage. But previous attempts to overcome the poor electrical conductivity of MOFs hybrids involve a harsh high-template pyrolytic process to in situ form carbon, which suffer from extremely complex operation and inevitable carbon corrosion at high positive potentials when OER is operated. Herein, a self-assembly approach is presented to synthesize a non-precious metal-based, high active and strong durable Co-MOF@CNTs bifunctional catalyst for OER and ORR. CNTs not only improve the transportation of the electrons but also can sustain the harsh oxidative environment of OER without carbon corrosion. Meanwhile, the unique 3D hierarchical structure offers a large surface area and stable anchoring sites for active centers and CNTs, which enables the superior durability of hybrid. Moreover, a synergistic catalysis of Co(II), organic ligands and CNTs will enhance the bifunctional electrocatalytic performance. Impressively, the hybrid exhibits comparable OER and ORR catalytic activity to RuO2 and 20 wt% Pt/C catalysts and superior stability. This facile and versatile strategy to fabricating MOF-based hybrids may be extended to other electrode materials for fuel cell and water splitting applications.

Genetic changes in muscle protein following hybridization between Haliotis diversicolor reeve Japan and Taiwan populations revealed using a proteomic approach.

PubMed

Di, Guilan; You, Weiwei; Yu, Jinjin; Wang, Dexiang; Ke, Caihuan

2013-03-01

Protein expression patterns were compared in a Japan and Taiwan population of Haliotis diversicolor and in a hybrid between them using 2DE and MALDI-TOF-TOF analyses. Using the software PDQuest, 924 ± 7 protein spots were detected in the Japan population (RR), 861 ± 11 in the Taiwan population (TT), and 882 ± 9 in the F1 hybrid (TR). RR and TR were clustered together, but the distance between RR and TT was the maximum using hierarchical cluster analysis. A total of 46 gel spots were identified and a total of 15 spots matched with abalone proteins (a 33.6% identification rate). Hybrid exhibiting additivity or overdominance accounted for 73.9% of these 46 identified proteins. The 46 differentially expressed proteins were shown to be involved in major biological processes, including muscle contraction and regulation, energy metabolism, and stress response. The proteins involved in energy metabolism included adenosine triphosphate (ATP) synthase β subunit, fructose 1, 6-bisphosphate aldolase, triosephosphate isomerase, enolase, arginine kinase, and tauropine dehydrogenase. These proteins exhibited additivity in their offspring. The proteins involved in stress responses included HSP Hsp70 (exhibiting overdominance in the offspring) and Cu/Zn-superoxide dismutase (exhibiting additivity). These results suggested that proteomic approach is suitable for analysis of heterosis and functional prediction of abalone hybridization. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Generic hierarchical engine for mask data preparation

NASA Astrophysics Data System (ADS)

Kalus, Christian K.; Roessl, Wolfgang; Schnitker, Uwe; Simecek, Michal

2002-07-01

Electronic layouts are usually flattened on their path from the hierarchical source downstream to the wafer. Mask data preparation has certainly been identified as a severe bottleneck since long. Data volumes are not only doubling every year along the ITRS roadmap. With the advent of optical proximity correction and phase-shifting masks data volumes are escalating up to non-manageable heights. Hierarchical treatment is one of the most powerful means to keep memory and CPU consumption in reasonable ranges. Only recently, however, has this technique acquired more public attention. Mask data preparation is the most critical area calling for a sound infrastructure to reduce the handling problem. Gaining more and more attention though, are other applications such as large area simulation and manufacturing rule checking (MRC). They all would profit from a generic engine capable to efficiently treat hierarchical data. In this paper we will present a generic engine for hierarchical treatment which solves the major problem, steady transitions along cell borders. Several alternatives exist how to walk through the hierarchy tree. They have, to date, not been thoroughly investigated. One is a bottom-up attempt to treat cells starting with the most elementary cells. The other one is a top-down approach which lends itself to creating a new hierarchy tree. In addition, since the variety, degree of hierarchy and quality of layouts extends over a wide range a generic engine has to take intelligent decisions when exploding the hierarchy tree. Several applications will be shown, in particular how far the limits can be pushed with the current hierarchical engine.

Auditing of SNOMED CT's Hierarchical Structure using the National Drug File - Reference Terminology.

PubMed

Zakharchenko, Aleksandr; Geller, James

2015-01-01

With the ongoing development in the field of Medical Informatics, the availability of cross-references and the consistency of coverage between terminologies become critical requirements for clinical decision support. In this paper, we examine the possibility of developing a framework that highlights and exposes hierarchical incompatibilities between different medical terminologies in order to facilitate the process of achieving a sufficient level of consistency between terminologies. For the purpose of this research, we are working with the Systematized Nomenclature of Medicine--Clinical Terms (SNOMED CT) and the National Drug File--Reference Terminology (NDF-RT)--a clinical terminology focused on drugs. For discovery of inconsistencies we built an automated tool.

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

PubMed Central

Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

PubMed

Falat, Lukas; Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

The Role of Evaluative Metadata in an Online Teacher Resource Exchange

ERIC Educational Resources Information Center

Abramovich, Samuel; Schunn, Christian D.; Correnti, Richard J.

2013-01-01

A large-scale online teacher resource exchange is studied to examine the ways in which metadata influence teachers' selection of resources. A hierarchical linear modeling approach was used to tease apart the simultaneous effects of resource features and author features. From a decision heuristics theoretical perspective, teachers appear to…

Understanding the Effects of Personal and School Religiosity on the Decision to Abort a Premarital Pregnancy

ERIC Educational Resources Information Center

Adamczyk, Amy

2009-01-01

Although much research has examined the relationship between religion and abortion attitudes, few studies have examined whether religion influences abortion behavior. This study looks at whether individual and school religiosity influence reported abortion behavior among women who become pregnant while unmarried. Hierarchical Logistic Models are…

A Hierarchical Model and Analysis of Factors Affecting the Adoption of Timber as a Bridge

Treesearch

Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt

1995-01-01

The Analytical Hierarchy Process was used to characterize the bridge material selection decisions of highway engineers and local highway officials across the United States. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in Mississippi, Virginia, Washington, and Wisconsin to identify...

From Quick Start Teams to Home Teams: The Duke TQM Experience.

ERIC Educational Resources Information Center

Lubans, John; Gordon, Heather

This paper describes the Duke University Libraries' transition in early 1994 from its traditional hierarchical model to an organization emphasizing Total Quality Management (TQM) concepts such as self-managing teams and continuous improvement. Existing conditions at the libraries that played a role in the decision to switch included: (1) rising…

Combining analytical hierarchy process and agglomerative hierarchical clustering in search of expert consensus in green corridors development management.

PubMed

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts-landscape architects, regional planners, and geographers-revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Combining Analytical Hierarchy Process and Agglomerative Hierarchical Clustering in Search of Expert Consensus in Green Corridors Development Management

NASA Astrophysics Data System (ADS)

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts—landscape architects, regional planners, and geographers—revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Bioinspired Design: Magnetic Freeze Casting

NASA Astrophysics Data System (ADS)

Porter, Michael Martin

Nature is the ultimate experimental scientist, having billions of years of evolution to design, test, and adapt a variety of multifunctional systems for a plethora of diverse applications. Next-generation materials that draw inspiration from the structure-property-function relationships of natural biological materials have led to many high-performance structural materials with hybrid, hierarchical architectures that fit form to function. In this dissertation, a novel materials processing method, magnetic freeze casting, is introduced to develop porous scaffolds and hybrid composites with micro-architectures that emulate bone, abalone nacre, and other hard biological materials. This method uses ice as a template to form ceramic-based materials with continuously, interconnected microstructures and magnetic fields to control the alignment of these structures in multiple directions. The resulting materials have anisotropic properties with enhanced mechanical performance that have potential applications as bone implants or lightweight structural composites, among others.

Bioinspired Nanocellulose Based Hybrid Materials With Novel Interfacial Properties

NASA Astrophysics Data System (ADS)

Keten, Sinan

This talk will overview a simulation-based approach to enhancing the mechanical properties of nanocomposites by utilizing cellulose - the most abundant and renewable structural biopolymer found on our planet. Cellulose nanocrystals (CNCs) exhibit outstanding mechanical properties exceeding that of Kevlar, serving as reinforcing domains in nature's toughest hierarchical nanocomposites such as wood. Yet, weak interfaces at the surfaces of CNCs have so far made it impossible to scale these inherent properties to macroscopic systems. In this work, I will discuss how surface functionalization of CNCs influences their properties in their self-assembled films and nanocomposites with engineered polymer matrices . Specifically, the role of ion exchange based surface modifications and polymer conjugation will be discussed, where atomistic and coarse-grained simulations will reveal new insights into how superior mechanical properties can potentially be attained by hybrid constructs.

Hierarchical Metal–Organic Framework Hybrids: Perturbation-Assisted Nanofusion Synthesis

DOE PAGES

Yue, Yanfeng; Fulvio, Pasquale F.; Dai, Sheng

2015-12-04

Metal–organic frameworks (MOFs) represent a new family of microporous materials; however, microporous–mesoporous hierarchical MOF materials have been less investigated because of the lack of simple, reliable methods to introduce mesopores to the crystalline microporous particles. State-of-the-art MOF hierarchical materials have been prepared by ligand extension methods or by using a template, resulting in intrinsic mesopores of longer ligands or replicated pores from template agents, respectively. However, mesoporous MOF materials obtained through ligand extension often collapse in the absence of guest molecules, which dramatically reduces the size of the pore aperture. Although the template-directed strategy allows for the preparation of hierarchicalmore » materials with larger mesopores, the latter requires a template removal step, which may result in the collapse of the implemented mesopores. Recently, a general template-free synthesis of hierarchical microporous crystalline frameworks, such as MOFs and Prussian blue analogues (PBAs), has been reported. Our new method is based on the kinetically controlled precipitation (perturbation), with simultaneous condensation and redissolution of polymorphic nanocrystallites in the mother liquor. This method further eliminates the use of extended organic ligands and the micropores do not collapse upon removal of trapped guest solvent molecules, thus yielding hierarchical MOF materials with intriguing porosity in the gram scale. The hierarchical MOF materials prepared in this way exhibited exceptional properties when tested for the adsorption of large organic dyes over their corresponding microporous frameworks, due to the enhanced pore accessibility and electrolyte diffusion within the mesopores. As for PBAs, the pore size distribution of these materials can be tailored by changing the metals substituting Fe cations in the PB lattice. For these, the textural mesopores increased from approximately 10 nm for Cu analogue (mesoCuHCF), to 16 nm in Co substituted compound (mesoCoHCF), and to as large as 30 nm for the Ni derivative (mesoNiHCF). And while bulk PB and analogues have a higher capacitance than hierarchical analogues for Na-batteries, the increased accessibility to the microporous channels of PBAs allow for faster intercalated ion exchange and diffusion than in bulk PBA crystals. Therefore, hierarchical PBAs are promising candidates for electrodes in future electrochemical energy storage devices with faster charge–discharge rates than batteries, namely pseudocapacitors. Finally, this new synthetic method opens the possibility to prepare hierarchical materials having bimodal distribution of mesopores, and to tailor the structural properties of MOFs for different applications, including contrasting agents for MRI, and drug delivery.« less

Mathematical solution of multilevel fractional programming problem with fuzzy goal programming approach

NASA Astrophysics Data System (ADS)

Lachhwani, Kailash; Poonia, Mahaveer Prasad

2012-08-01

In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.

Who Chokes Under Pressure? The Big Five Personality Traits and Decision-Making under Pressure.

PubMed

Byrne, Kaileigh A; Silasi-Mansat, Crina D; Worthy, Darrell A

2015-02-01

The purpose of the present study was to examine whether the Big Five personality factors could predict who thrives or chokes under pressure during decision-making. The effects of the Big Five personality factors on decision-making ability and performance under social (Experiment 1) and combined social and time pressure (Experiment 2) were examined using the Big Five Personality Inventory and a dynamic decision-making task that required participants to learn an optimal strategy. In Experiment 1, a hierarchical multiple regression analysis showed an interaction between neuroticism and pressure condition. Neuroticism negatively predicted performance under social pressure, but did not affect decision-making under low pressure. Additionally, the negative effect of neuroticism under pressure was replicated using a combined social and time pressure manipulation in Experiment 2. These results support distraction theory whereby pressure taxes highly neurotic individuals' cognitive resources, leading to sub-optimal performance. Agreeableness also negatively predicted performance in both experiments.

Standardization of a Hierarchical Transactive Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammerstrom, Donald J.; Oliver, Terry V.; Melton, Ronald B.

2010-12-03

The authors describe work they have conducted toward the generalization and standardization of the transactive control approach that was first demonstrated in the Olympic Peninsula Project for the management of a transmission constraint. The newly generalized approach addresses several potential shortfalls of the prior approach: First, the authors have formalized a hierarchical node structure which defines the nodes and the functional signal pathways between these nodes. Second, by fully generalizing the inputs, outputs, and functional responsibilities of each node, the authors make the approach available to a much wider set of responsive assets and operational objectives. Third, the new, generalizedmore » approach defines transactive signals that include the predicted day-ahead future. This predictive feature allows the market-like bids and offers to become resolved iteratively over time, thus allowing the behaviors of responsive assets to be called upon both for the present and as future dispatch decisions are being made. The hierarchical transactive control approach is a key feature of a proposed Pacific Northwest smart grid demonstration.« less

The Impact of Hybrid Vehicles on Street Crossings

ERIC Educational Resources Information Center

Wiener, William; Naghshineh, Koorosh; Salisbury, Brad; Rozema, Randall

2006-01-01

The authors had three purposes: (a) to compare the sound output of a Toyota Corolla, a vehicle powered by an internal combustion engine (ICE) with that of a hybrid vehicle (Prius) under conditions of acceleration and approach in relation to the potential decision of a pedestrian who is visually impaired to begin to cross the street, (b) to…

Hybrid Hard and Soft Decision Decoding of Reed-Solomon Codes for M-ary Frequency-Shift Keying

DTIC Science & Technology

2010-06-01

Reed-Solomon (RS) coding, Orthogonal signaling, Additive White Gaussian Noise (AWGN), Pulse-Noise Interference (PNI), coherent detection, noncoherent ...Coherent Demodulation of MFSK ....................................................10 2. Noncoherent Demodulation of MFSK...62 V. PERFORMANCE SIMULATION AND ANALYSIS OF MFSK WITH RS ENCODING, HYBRID HD SD DECODING, AND NONCOHERENT DEMODULATION IN AWGN

Three S's of Undergraduate Course Architecture: Compatibilities of Setting, Style and Structure

ERIC Educational Resources Information Center

Robertson, Patricia R.; Wakeling, Victor

2018-01-01

Three separate baseline decisions are recommended when designing an undergraduate course prior to considering any course content. The "Three S" course design decisions include determining (1) the "setting" (on-campus, online or hybrid), (2) the learning "style" (passive or active), and (3) the learning…

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

PubMed Central

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes “winner-take-all” processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans’ value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light. PMID:29077746

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

PubMed

Colas, Jaron T

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

Designing Real-time Decision Support for Trauma Resuscitations

PubMed Central

Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.

2016-01-01

Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed. Results Among 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert–video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low. Conclusions An eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians. PMID:26300010

A hybrid video codec based on extended block sizes, recursive integer transforms, improved interpolation, and flexible motion representation

NASA Astrophysics Data System (ADS)

Karczewicz, Marta; Chen, Peisong; Joshi, Rajan; Wang, Xianglin; Chien, Wei-Jung; Panchal, Rahul; Coban, Muhammed; Chong, In Suk; Reznik, Yuriy A.

2011-01-01

This paper describes video coding technology proposal submitted by Qualcomm Inc. in response to a joint call for proposal (CfP) issued by ITU-T SG16 Q.6 (VCEG) and ISO/IEC JTC1/SC29/WG11 (MPEG) in January 2010. Proposed video codec follows a hybrid coding approach based on temporal prediction, followed by transform, quantization, and entropy coding of the residual. Some of its key features are extended block sizes (up to 64x64), recursive integer transforms, single pass switched interpolation filters with offsets (single pass SIFO), mode dependent directional transform (MDDT) for intra-coding, luma and chroma high precision filtering, geometry motion partitioning, adaptive motion vector resolution. It also incorporates internal bit-depth increase (IBDI), and modified quadtree based adaptive loop filtering (QALF). Simulation results are presented for a variety of bit rates, resolutions and coding configurations to demonstrate the high compression efficiency achieved by the proposed video codec at moderate level of encoding and decoding complexity. For random access hierarchical B configuration (HierB), the proposed video codec achieves an average BD-rate reduction of 30.88c/o compared to the H.264/AVC alpha anchor. For low delay hierarchical P (HierP) configuration, the proposed video codec achieves an average BD-rate reduction of 32.96c/o and 48.57c/o, compared to the H.264/AVC beta and gamma anchors, respectively.

Ultradispersed Cobalt Ferrite Nanoparticles Assembled in Graphene Aerogel for Continuous Photo-Fenton Reaction and Enhanced Lithium Storage Performance

NASA Astrophysics Data System (ADS)

Qiu, Bocheng; Deng, Yuanxin; Du, Mengmeng; Xing, Mingyang; Zhang, Jinlong

2016-07-01

The Photo-Fenton reaction is an advanced technology to eliminate organic pollutants in environmental chemistry. Moreover, the conversion rate of Fe3+/Fe2+ and utilization rate of H2O2 are significant factors in Photo-Fenton reaction. In this work, we reported three dimensional (3D) hierarchical cobalt ferrite/graphene aerogels (CoFe2O4/GAs) composites by the in situ growing CoFe2O4 crystal seeds on the graphene oxide (GO) followed by the hydrothermal process. The resulting CoFe2O4/GAs composites demonstrated 3D hierarchical pore structure with mesopores (14~18 nm), macropores (50~125 nm), and a remarkable surface area (177.8 m2 g-1). These properties endowed this hybrid with the high and recyclable Photo-Fenton activity for methyl orange pollutant degradation. More importantly, the CoFe2O4/GAs composites can keep high Photo-Fenton activity in a wide pH. Besides, the CoFe2O4/GAs composites also exhibited excellent cyclic performance and good rate capability. The 3D framework can not only effectively prevent the volume expansion and aggregation of CoFe2O4 nanoparticles during the charge/discharge processes for Lithium-ion batteries (LIBs), but also shorten lithium ions and electron diffusion length in 3D pathways. These results indicated a broaden application prospect of 3D-graphene based hybrids in wastewater treatment and energy storage.

Magnesium ion implantation on a micro/nanostructured titanium surface promotes its bioactivity and osteogenic differentiation function

PubMed Central

Wang, Guifang; Li, Jinhua; Zhang, Wenjie; Xu, Lianyi; Pan, Hongya; Wen, Jin; Wu, Qianju; She, Wenjun; Jiao, Ting; Liu, Xuanyong; Jiang, Xinquan

2014-01-01

As one of the important ions associated with bone osseointegration, magnesium was incorporated into a micro/nanostructured titanium surface using a magnesium plasma immersion ion-implantation method. Hierarchical hybrid micro/nanostructured titanium surfaces followed by magnesium ion implantation for 30 minutes (Mg30) and hierarchical hybrid micro/nanostructured titanium surfaces followed by magnesium ion implantation for 60 minutes (Mg60) were used as test groups. The surface morphology, chemical properties, and amount of magnesium ions released were evaluated by field-emission scanning electron microscopy, energy dispersive X-ray spectroscopy, field-emission transmission electron microscopy, and inductively coupled plasma-optical emission spectrometry. Rat bone marrow mesenchymal stem cells (rBMMSCs) were used to evaluate cell responses, including proliferation, spreading, and osteogenic differentiation on the surface of the material or in their medium extraction. Greater increases in the spreading and proliferation ability of rBMMSCs were observed on the surfaces of magnesium-implanted micro/nanostructures compared with the control plates. Furthermore, the osteocalcin (OCN), osteopontin (OPN), and alkaline phosphatase (ALP) genes were upregulated on both surfaces and in their medium extractions. The enhanced cell responses were correlated with increasing concentrations of magnesium ions, indicating that the osteoblastic differentiation of rBMMSCs was stimulated through the magnesium ion function. The magnesium ion-implanted micro/nanostructured titanium surfaces could enhance the proliferation, spreading, and osteogenic differentiation activity of rBMMSCs, suggesting they have potential application in improving bone-titanium integration. PMID:24940056

Surface design and engineering of hierarchical hybrid nanostructures for asymmetric supercapacitors with improved electrochemical performance.

PubMed

Achilleos, Demetra S; Hatton, T Alan

2015-06-01

With the current rising world demand for energy sufficiency, there is an increased necessity for the development of efficient energy storage devices. To address these needs, the scientific community has focused on the improvement of the electrochemical properties of the most well known energy storage devices; the Li-ion batteries and electrochemical capacitors, also called supercapacitors. Despite the fact that supercapacitors exhibit high power densities, good reversibility and long cycle life, they still exhibit lower energy densities than batteries, which limit their practical application. Various strategies have been employed to circumvent this problem, specifically targetting an increase in the specific capacitance and the broadening of the potential window of operation of these systems. In recent years, sophisticated surface design and engineering of hierarchical hybrid nanostructures has facilitated significant improvements in the specific and volumetric storage capabilities of supercapacitors. These nanostructured electrodes exhibit higher surface areas for ion adsorption and reduced ion diffusion lengths for the electrolyte ions. Significant advances have also been achieved in broadening the electrochemical window of operation of these systems, as realized via the development of asymmetric two-electrode cells consisting of nanocomposite positive and negative electrodes with complementary electrochemical windows, which operate in environmentally benign aqueous media. We provide an overview of the diverse approaches, in terms of chemistry and nanoscale architecture, employed recently for the development of asymmetric supercapacitors of improved electrochemical performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Ultradispersed Cobalt Ferrite Nanoparticles Assembled in Graphene Aerogel for Continuous Photo-Fenton Reaction and Enhanced Lithium Storage Performance.

PubMed

Qiu, Bocheng; Deng, Yuanxin; Du, Mengmeng; Xing, Mingyang; Zhang, Jinlong

2016-07-04

The Photo-Fenton reaction is an advanced technology to eliminate organic pollutants in environmental chemistry. Moreover, the conversion rate of Fe(3+)/Fe(2+) and utilization rate of H2O2 are significant factors in Photo-Fenton reaction. In this work, we reported three dimensional (3D) hierarchical cobalt ferrite/graphene aerogels (CoFe2O4/GAs) composites by the in situ growing CoFe2O4 crystal seeds on the graphene oxide (GO) followed by the hydrothermal process. The resulting CoFe2O4/GAs composites demonstrated 3D hierarchical pore structure with mesopores (14~18 nm), macropores (50~125 nm), and a remarkable surface area (177.8 m(2 )g(-1)). These properties endowed this hybrid with the high and recyclable Photo-Fenton activity for methyl orange pollutant degradation. More importantly, the CoFe2O4/GAs composites can keep high Photo-Fenton activity in a wide pH. Besides, the CoFe2O4/GAs composites also exhibited excellent cyclic performance and good rate capability. The 3D framework can not only effectively prevent the volume expansion and aggregation of CoFe2O4 nanoparticles during the charge/discharge processes for Lithium-ion batteries (LIBs), but also shorten lithium ions and electron diffusion length in 3D pathways. These results indicated a broaden application prospect of 3D-graphene based hybrids in wastewater treatment and energy storage.

Ultradispersed Cobalt Ferrite Nanoparticles Assembled in Graphene Aerogel for Continuous Photo-Fenton Reaction and Enhanced Lithium Storage Performance

PubMed Central

Qiu, Bocheng; Deng, Yuanxin; Du, Mengmeng; Xing, Mingyang; Zhang, Jinlong

2016-01-01

The Photo-Fenton reaction is an advanced technology to eliminate organic pollutants in environmental chemistry. Moreover, the conversion rate of Fe3+/Fe2+ and utilization rate of H2O2 are significant factors in Photo-Fenton reaction. In this work, we reported three dimensional (3D) hierarchical cobalt ferrite/graphene aerogels (CoFe2O4/GAs) composites by the in situ growing CoFe2O4 crystal seeds on the graphene oxide (GO) followed by the hydrothermal process. The resulting CoFe2O4/GAs composites demonstrated 3D hierarchical pore structure with mesopores (14~18 nm), macropores (50~125 nm), and a remarkable surface area (177.8 m2 g−1). These properties endowed this hybrid with the high and recyclable Photo-Fenton activity for methyl orange pollutant degradation. More importantly, the CoFe2O4/GAs composites can keep high Photo-Fenton activity in a wide pH. Besides, the CoFe2O4/GAs composites also exhibited excellent cyclic performance and good rate capability. The 3D framework can not only effectively prevent the volume expansion and aggregation of CoFe2O4 nanoparticles during the charge/discharge processes for Lithium-ion batteries (LIBs), but also shorten lithium ions and electron diffusion length in 3D pathways. These results indicated a broaden application prospect of 3D-graphene based hybrids in wastewater treatment and energy storage. PMID:27373343

Structural evolution of photocrosslinked silk fibroin and silk fibroin-based hybrid hydrogels: A small angle and ultra-small angle scattering investigation.

PubMed

Whittaker, Jasmin L; Balu, Rajkamal; Knott, Robert; de Campo, Liliana; Mata, Jitendra P; Rehm, Christine; Hill, Anita J; Dutta, Naba K; Roy Choudhury, Namita

2018-07-15

Regenerated Bombyx mori silk fibroin (RSF) is a widely recognized protein for biomedical applications; however, its hierarchical gel structure is poorly understood. In this paper, the hierarchical structure of photocrosslinked RSF and RSF-based hybrid hydrogel systems: (i) RSF/Rec1-resilin and (ii) RSF/poly(N-vinylcaprolactam (PVCL) is reported for the first time using small-angle scattering (SAS) techniques. The structure of RSF in dilute to concentrated solution to fabricated hydrogels were characterized using small angle X-ray scattering (SAXS), small angle neutron scattering (SANS) and ultra-small angle neutron scattering (USANS) techniques. The RSF hydrogel exhibited three distinctive structural characteristics: (i) a Porod region in the length scale of 2 to 3nm due to hydrophobic domains (containing β-sheets) which exhibits sharp interfaces with the amorphous matrix of the hydrogel and the solvent, (ii) a Guinier region in the length scale of 4 to 20nm due to hydrophilic domains (containing turns and random coil), and (iii) a Porod-like region in the length scale of few micrometers due to water pores/channels exhibiting fractal-like characteristics. Addition of Rec1-resilin or PVCL to RSF and subsequent crosslinking systematically increased the nanoscale size of hydrophobic and hydrophilic domains, whereas decreased the homogeneity of pore size distribution in the microscale. The presented results have implications on the fundamental understanding of the structure-property relationship of RSF-based hydrogels. Copyright © 2018. Published by Elsevier B.V.

Eye tracking and pupillometry are indicators of dissociable latent decision processes.

PubMed

Cavanagh, James F; Wiecki, Thomas V; Kochar, Angad; Frank, Michael J

2014-08-01

Can you predict what people are going to do just by watching them? This is certainly difficult: it would require a clear mapping between observable indicators and unobservable cognitive states. In this report, we demonstrate how this is possible by monitoring eye gaze and pupil dilation, which predict dissociable biases during decision making. We quantified decision making using the drift diffusion model (DDM), which provides an algorithmic account of how evidence accumulation and response caution contribute to decisions through separate latent parameters of drift rate and decision threshold, respectively. We used a hierarchical Bayesian estimation approach to assess the single trial influence of observable physiological signals on these latent DDM parameters. Increased eye gaze dwell time specifically predicted an increased drift rate toward the fixated option, irrespective of the value of the option. In contrast, greater pupil dilation specifically predicted an increase in decision threshold during difficult decisions. These findings suggest that eye tracking and pupillometry reflect the operations of dissociated latent decision processes. PsycINFO Database Record (c) 2014 APA, all rights reserved.

The information extraction of Gannan citrus orchard based on the GF-1 remote sensing image

NASA Astrophysics Data System (ADS)

Wang, S.; Chen, Y. L.

2017-02-01

The production of Gannan oranges is the largest in China, which occupied an important part in the world. The extraction of citrus orchard quickly and effectively has important significance for fruit pathogen defense, fruit production and industrial planning. The traditional spectra extraction method of citrus orchard based on pixel has a lower classification accuracy, difficult to avoid the “pepper phenomenon”. In the influence of noise, the phenomenon that different spectrums of objects have the same spectrum is graveness. Taking Xunwu County citrus fruit planting area of Ganzhou as the research object, aiming at the disadvantage of the lower accuracy of the traditional method based on image element classification method, a decision tree classification method based on object-oriented rule set is proposed. Firstly, multi-scale segmentation is performed on the GF-1 remote sensing image data of the study area. Subsequently the sample objects are selected for statistical analysis of spectral features and geometric features. Finally, combined with the concept of decision tree classification, a variety of empirical values of single band threshold, NDVI, band combination and object geometry characteristics are used hierarchically to execute the information extraction of the research area, and multi-scale segmentation and hierarchical decision tree classification is implemented. The classification results are verified with the confusion matrix, and the overall Kappa index is 87.91%.

Preference for oddity: uniqueness heuristic or hierarchical choice process?

PubMed

Waite, Thomas A

2008-10-01

Traditional economic theories assume decision makers in multialternative choice tasks "assign" a value to each option and then express rational preferences. Here, I report an apparent violation of such rationality in gray jays (Perisoreus canadensis). I tested the jays' preference in a quaternary choice task where three options were the same color and the fourth option was a different color. All options offered an identical food reward and so the strictly rational expectation was that subjects would choose the odd-colored option in 25% of choices. In clear disagreement, every subject chose the odd option more frequently than expected. I speculate as to how this surprising preference for oddity might have been ecologically rational: by using a unique-choice heuristic, the jays might have been able to bypass a deliberative phase of the decision process and devote more attention to scanning for predators. Alternatively, it is conceivable that the jays did not prefer oddity per se. Instead, they might have used a hierarchical process, assigning options to color categories and then choosing between categories. If so, their behavior matches expectation after all (on average, subjects chose the odd option 50% of the time). It should be straightforward to test these competing hypotheses. The current results can be viewed as a new example of how simple mechanisms sometimes produce economically puzzling yet ecologically rational decision making.

Enhanced Mechanical Performance of Bio-Inspired Hybrid Structures Utilising Topological Interlocking Geometry

PubMed Central

Djumas, Lee; Molotnikov, Andrey; Simon, George P.; Estrin, Yuri

2016-01-01

Structural composites inspired by nacre have emerged as prime exemplars for guiding materials design of fracture-resistant, rigid hybrid materials. The intricate microstructure of nacre, which combines a hard majority phase with a small fraction of a soft phase, achieves superior mechanical properties compared to its constituents and has generated much interest. However, replicating the hierarchical microstructure of nacre is very challenging, not to mention improving it. In this article, we propose to alter the geometry of the hard building blocks by introducing the concept of topological interlocking. This design principle has previously been shown to provide an inherently brittle material with a remarkable flexural compliance. We now demonstrate that by combining the basic architecture of nacre with topological interlocking of discrete hard building blocks, hybrid materials of a new type can be produced. By adding a soft phase at the interfaces between topologically interlocked blocks in a single-build additive manufacturing process, further improvement of mechanical properties is achieved. The design of these fabricated hybrid structures has been guided by computational work elucidating the effect of various geometries. To our knowledge, this is the first reported study that combines the advantages of nacre-inspired structures with the benefits of topological interlocking. PMID:27216277

Chemically Designed Metallic/Insulating Hybrid Nanostructures with Silver Nanocrystals for Highly Sensitive Wearable Pressure Sensors.

PubMed

Kim, Haneun; Lee, Seung-Wook; Joh, Hyungmok; Seong, Mingi; Lee, Woo Seok; Kang, Min Su; Pyo, Jun Beom; Oh, Soong Ju

2018-01-10

With the increase in interest in wearable tactile pressure sensors for e-skin, researches to make nanostructures to achieve high sensitivity have been actively conducted. However, limitations such as complex fabrication processes using expensive equipment still exist. Herein, simple lithography-free techniques to develop pyramid-like metal/insulator hybrid nanostructures utilizing nanocrystals (NCs) are demonstrated. Ligand-exchanged and unexchanged silver NC thin films are used as metallic and insulating components, respectively. The interfaces of each NC layer are chemically engineered to create discontinuous insulating layers, i.e., spacers for improved sensitivity, and eventually to realize fully solution-processed pressure sensors. Device performance analysis with structural, chemical, and electronic characterization and conductive atomic force microscopy study reveals that hybrid nanostructure based pressure sensor shows an enhanced sensitivity of higher than 500 kPa -1 , reliability, and low power consumption with a wide range of pressure sensing. Nano-/micro-hierarchical structures are also designed by combining hybrid nanostructures with conventional microstructures, exhibiting further enhanced sensing range and achieving a record sensitivity of 2.72 × 10 4 kPa -1 . Finally, all-solution-processed pressure sensor arrays with high pixel density, capable of detecting delicate signals with high spatial selectivity much better than the human tactile threshold, are introduced.

Synthesis of NiO-TiO2 hybrids/mSiO2 yolk-shell architectures embedded with ultrasmall gold nanoparticles for enhanced reactivity

NASA Astrophysics Data System (ADS)

Fang, Jiasheng; Zhang, Yiwei; Zhou, Yuming; Zhao, Shuo; Zhang, Chao; Huang, Mengqiu; Gao, Yan

2017-08-01

Novel NiO-TiO2 hybrids/mSiO2 yolk-shell architectures loaded with ultrasmall Au nanoparticles (STNVS-Au) were developed via the rational synthetic strategy. The hierarchical yolk-shell nanostructures (STNVS) with high surface areas were constructed by a facile "bottom-up" assembly process using SiO2 materials and polymer resins as cores/shells and sacrificial templates, accompanied by a simple hydrothermal incorporation of NiO into uniform amorphous TiO2 layers that were converted to NiO-anatase TiO2 p-n heterojunction hybrids. Then, numerous sub-3 nm Au nanoparticles were post encapsulated within STNVS nanostructures through the low-temperature hydrogen reduction based on the unique deposition-precipitation method with Au(en)2Cl3 compounds as gold precursors. The NiO-TiO2 hybrids alloying with Au nanoparticles were effectively protected and entrapped within STNVS architectures, and interacted with outer mSiO2-Au shells, which comprised the powerful STNVS-Au yolk-shell nanoreactors and produced stronger configural synergies in enhancing the heterogeneous catalysis. Into catalyzing the reduction of 4-nitrophenol to 4-aminophenol, the STNVS-Au was shown with outstanding activity and reusability, and its pristine morphology was well retained during the recycling process.

Realization of 13.6% Efficiency on 20 μm Thick Si/Organic Hybrid Heterojunction Solar Cells via Advanced Nanotexturing and Surface Recombination Suppression.

PubMed

He, Jian; Gao, Pingqi; Liao, Mingdun; Yang, Xi; Ying, Zhiqin; Zhou, Suqiong; Ye, Jichun; Cui, Yi

2015-06-23

Hybrid silicon/polymer solar cells promise to be an economically feasible alternative energy solution for various applications if ultrathin flexible crystalline silicon (c-Si) substrates are used. However, utilization of ultrathin c-Si encounters problems in light harvesting and electronic losses at surfaces, which severely degrade the performance of solar cells. Here, we developed a metal-assisted chemical etching method to deliver front-side surface texturing of hierarchically bowl-like nanopores on 20 μm c-Si, enabling an omnidirectional light harvesting over the entire solar spectrum as well as an enlarged contact area with the polymer. In addition, a back surface field was introduced on the back side of the thin c-Si to minimize the series resistance losses as well as to suppress the surface recombination by the built high-low junction. Through these improvements, a power conversion efficiency (PCE) up to 13.6% was achieved under an air mass 1.5 G irradiation for silicon/organic hybrid solar cells with the c-Si thickness of only about 20 μm. This PCE is as high as the record currently reported in hybrid solar cells constructed from bulk c-Si, suggesting a design rule for efficient silicon/organic solar cells with thinner absorbers.

Utility and impact of early t(15;17) identification by Fluorescence In Situ Hybridization (FISH) in clinical decision making for patients in Acute Promyelocytic Leukemia (APL).

PubMed

Kolhe, R; Mangaonkar, A; Mansour, J; Clemmons, A; Shaw, J; Dupont, B; Walczak, L; Mondal, A; Rojiani, A; Jillella, A; Kota, V

2015-08-01

Acute Promyelocytic Leukemia (APL) is a curable malignancy with studies showing above 90% survival. However, population-based studies looking at survival suggest that approximately 30% of patients with APL die during induction. Early demonstration of t(15;17) will lead to accurate decision making regarding treatment. The aim of this project was to validate earlier time frames for the Abbott Molecular Vysis LSI promyelocytic leukemia (PML)/ retinoic acid receptor alpha (RARA) fluorescence in situ hybridization (FISH) probe (ASR 6-16 h). Twenty patients (15 APL cases and five non-APL cases) were selected for validating various hybridization times for the FISH probe. Expected normal signal pattern was two red and two green signals (2R2G), and the most common expected abnormal signal pattern was two fusion (yellow) signals, one red and one green (2F1R1G) and/or one fusion, one red and one green (1F1R1G). The specificity of the probe ranged from 84% at 2 h, 86% at 4 h, 84% at 6 h, and 87% for overnight hybridization. The sensitivity increased from 79% at 2 h, 80% at 4 h, 81% at 6 h to 87% for overnight hybridization. Based on the validation studies, we recommend reading of FISH results at the 4-h incubation mark for a preliminary diagnosis and confirmation with overnight hybridization. © 2015 John Wiley & Sons Ltd.

Hierarchical Structure and Multifunctional Surface Properties of Carnivorous Pitcher Plants Nepenthes

NASA Astrophysics Data System (ADS)

Hsu, Chiao-Peng; Lin, Yu-Min; Chen, Po-Yu

2015-04-01

Carnivorous pitcher plants of the genus Nepenthes have evolved specialized leaves fulfilling the multi-functions of attracting, capturing, retaining and digesting the prey, mostly arthropods. Different capturing mechanisms have been proposed and discussed in previous works. The most important capture mechanism is the unique super-hydrophilic surface properties of the peristome. The combination of a hierarchical surface structure and nectar secretions results in an exceptional water-lubricated trapping system. Anisotropic and unidirectional wettability is attributed to the ridge-like surface and epidermal folding. The three-dimensional plate-like wax crystals in the hydrophobic waxy zone can further prevent the prey from escaping. The captured prey are then digested in the hydrophilic digestive zone. The hybrid species Nepenthes × Miranda was investigated in this study. The surface morphology and hierarchical microstructure were characterized by scanning electron microscope. Contact angle measurement and wetting efficiency tests were performed to determine the wettability of the peristome under fresh, nectar-free and sucrose-coated conditions with controlled temperature and humidity. The results showed that sucrose-coated peristome surfaces possess the best wetting efficiency. The structure-property-function relationship and the capturing mechanism of Nepenthes were elucidated, which could further lead to the design and synthesis of novel bio-inspired surfaces and potential applications.

Highly Stretchable Superhydrophobic Composite Coating Based on Self-Adaptive Deformation of Hierarchical Structures.

PubMed

Hu, Xin; Tang, Changyu; He, Zhoukun; Shao, Hong; Xu, Keqin; Mei, Jun; Lau, Woon-Ming

2017-05-01

With the rapid development of stretchable electronics, functional textiles, and flexible sensors, water-proof protection materials are required to be built on various highly flexible substrates. However, maintaining the antiwetting of superhydrophobic surface under stretching is still a big challenge since the hierarchical structures at hybridized micro-nanoscales are easily damaged following large deformation of the substrates. This study reports a highly stretchable and mechanically stable superhydrophobic surface prepared by a facile spray coating of carbon black/polybutadiene elastomeric composite on a rubber substrate followed by thermal curing. The resulting composite coating can maintain its superhydrophobic property (water contact angle ≈170° and sliding angle <4°) at an extremely large stretching strain of up to 1000% and can withstand 1000 stretching-releasing cycles without losing its superhydrophobic property. Furthermore, the experimental observation and modeling analysis reveal that the stable superhydrophobic properties of the composite coating are attributed to the unique self-adaptive deformation ability of 3D hierarchical roughness of the composite coating, which delays the Cassie-Wenzel transition of surface wetting. In addition, it is first observed that the damaged coating can automatically recover its superhydrophobicity via a simple stretching treatment without incorporating additional hydrophobic materials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Peripheral infrastructure vectors and an extended set of plant parts for the Modular Cloning system

PubMed Central

Kretschmer, Carola; Gruetzner, Ramona; Löfke, Christian; Dagdas, Yasin; Bürstenbinder, Katharina; Marillonnet, Sylvestre

2018-01-01

Standardized DNA assembly strategies facilitate the generation of multigene constructs from collections of building blocks in plant synthetic biology. A common syntax for hierarchical DNA assembly following the Golden Gate principle employing Type IIs restriction endonucleases was recently developed, and underlies the Modular Cloning and GoldenBraid systems. In these systems, transcriptional units and/or multigene constructs are assembled from libraries of standardized building blocks, also referred to as phytobricks, in several hierarchical levels and by iterative Golden Gate reactions. Here, a toolkit containing further modules for the novel DNA assembly standards was developed. Intended for use with Modular Cloning, most modules are also compatible with GoldenBraid. Firstly, a collection of approximately 80 additional phytobricks is provided, comprising e.g. modules for inducible expression systems, promoters or epitope tags. Furthermore, DNA modules were developed for connecting Modular Cloning and Gateway cloning, either for toggling between systems or for standardized Gateway destination vector assembly. Finally, first instances of a “peripheral infrastructure” around Modular Cloning are presented: While available toolkits are designed for the assembly of plant transformation constructs, vectors were created to also use coding sequence-containing phytobricks directly in yeast two hybrid interaction or bacterial infection assays. The presented material will further enhance versatility of hierarchical DNA assembly strategies. PMID:29847550

Forms of work organization and associations with shoulder disorders: Results from a French working population.

PubMed

Bodin, Julie; Garlantézec, Ronan; Costet, Nathalie; Descatha, Alexis; Fouquet, Natacha; Caroly, Sandrine; Roquelaure, Yves

2017-03-01

The aim of this study was to identify forms of work organization in a French region and to study associations with the occurrence of symptomatic and clinically diagnosed shoulder disorders in workers. Workers were randomly included in this cross-sectional study from 2002 to 2005. Sixteen organizational variables were assessed by a self-administered questionnaire: i.e. shift work, job rotation, repetitiveness of tasks, paced work/automatic rate, work pace dependent on quantified targets, permanent controls or surveillance, colleagues' work and customer demand, and eight variables measuring decision latitude. Five forms of work organization were identified using hierarchical cluster analysis (HCA) of variables and HCA of workers: low decision latitude with pace constraints, medium decision latitude with pace constraints, low decision latitude with low pace constraints, high decision latitude with pace constraints and high decision latitude with low pace constraints. There were significant associations between forms of work organization and symptomatic and clinically-diagnosed shoulder disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

Universal size effects for populations in group-outcome decision-making problems

NASA Astrophysics Data System (ADS)

Borghesi, Christian; Hernández, Laura; Louf, Rémi; Caparros, Fabrice

2013-12-01

Elections constitute a paradigm of decision-making problems that have puzzled experts of different disciplines for decades. We study two decision-making problems, where groups make decisions that impact only themselves as a group. In both studied cases, participation in local elections and the number of democratic representatives at different scales (from local to national), we observe a universal scaling with the constituency size. These results may be interpreted as constituencies having a hierarchical structure, where each group of N agents, at each level of the hierarchy, is divided in about Nδ subgroups with δ≈1/3. Following this interpretation, we propose a phenomenological model of vote participation where abstention is related to the perceived link of an agent to the rest of the constituency and which reproduces quantitatively the observed data.

An explanatory analysis of driver injury severity in rear-end crashes using a decision table/Naïve Bayes (DTNB) hybrid classifier.

PubMed

Chen, Cong; Zhang, Guohui; Yang, Jinfu; Milton, John C; Alcántara, Adélamar Dely

2016-05-01

Rear-end crashes are a major type of traffic crashes in the U.S. Of practical necessity is a comprehensive examination of its mechanism that results in injuries and fatalities. Decision table (DT) and Naïve Bayes (NB) methods have both been used widely but separately for solving classification problems in multiple areas except for traffic safety research. Based on a two-year rear-end crash dataset, this paper applies a decision table/Naïve Bayes (DTNB) hybrid classifier to select the deterministic attributes and predict driver injury outcomes in rear-end crashes. The test results show that the hybrid classifier performs reasonably well, which was indicated by several performance evaluation measurements, such as accuracy, F-measure, ROC, and AUC. Fifteen significant attributes were found to be significant in predicting driver injury severities, including weather, lighting conditions, road geometry characteristics, driver behavior information, etc. The extracted decision rules demonstrate that heavy vehicle involvement, a comfortable traffic environment, inferior lighting conditions, two-lane rural roadways, vehicle disabled damage, and two-vehicle crashes would increase the likelihood of drivers sustaining fatal injuries. The research limitations on data size, data structure, and result presentation are also summarized. The applied methodology and estimation results provide insights for developing effective countermeasures to alleviate rear-end crash injury severities and improve traffic system safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improving Decision Making in Schools through Teacher Participation

ERIC Educational Resources Information Center

Mualuko, Ndiku J.; Mukasa, Simiyu A.; Achoka, Judy S. K.

2009-01-01

The hierarchical structure that places head teachers at the apex of a pyramid of staff is a common feature in secondary schools in Kenya. In this arrangement, school heads are poised to use their superior knowledge and experience to direct and control the working of the entire school. This negatively affects efficiency and productivity of the…

Efficiency vs. Effectiveness: Can W. Edwards Deming's Principles of Quality Management Be Applied Successfully to American Education.

ERIC Educational Resources Information Center

Petry, John R.

The field of education has been slow to recognize the Total Quality Management (TQM) concept. This resistance may result from entrenched management styles characterized by hierarchical decision-making structures. TQM emphasizes management based on leadership instead of management by objective, command, and coercion. The TQM concept consists of…

The Role of the Dean: Fostering Teaching as Scholarship in the School of Education Learning Community.

ERIC Educational Resources Information Center

Huffman-Joley, Gail

Expectations for leaders in colleges of education are changing as are expectations for leaders in public schools and business. The traditional hierarchical model is being transformed into an organizational climate of teamwork and shared decision making, which have become the watchwords for organizational climate and change. In accord with these…

Hierarchical Thinking: A Cognitive Tool for Guiding Coherent Decision Making in Design Problem Solving

ERIC Educational Resources Information Center

Haupt, Grietjie

2018-01-01

This paper builds on two concepts, the first of which is the extended information processing model of expert design cognition. This proposes twelve internal psychological characteristics interacting with the external world of expert designers during the early phases of the design process. Here, I explore one of the characteristics, hierarchical…

A cross-cultural study of noblesse oblige in economic decision-making.

PubMed

Fiddick, Laurence; Cummins, Denise Dellarosa; Janicki, Maria; Lee, Sean; Erlich, Nicole

2013-09-01

A cornerstone of economic theory is that rational agents are self-interested, yet a decade of research in experimental economics has shown that economic decisions are frequently driven by concerns for fairness, equity, and reciprocity. One aspect of other-regarding behavior that has garnered attention is noblesse oblige, a social norm that obligates those of higher status to be generous in their dealings with those of lower status. The results of a cross-cultural study are reported in which marked noblesse oblige was observed on a reciprocal-contract decision-making task. Participants from seven countries that vary along hierarchical and individualist/collectivist social dimensions were more tolerant of non-reciprocation when they adopted a high-ranking perspective compared with a low-ranking perspective.

Decision-Theoretic Control of Planetary Rovers

NASA Technical Reports Server (NTRS)

Zilberstein, Shlomo; Washington, Richard; Bernstein, Daniel S.; Mouaddib, Abdel-Illah; Morris, Robert (Technical Monitor)

2003-01-01

Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We describe two decision-theoretic approaches to maximize the productivity of planetary rovers: one based on adaptive planning and the other on hierarchical reinforcement learning. Both approaches map the problem into a Markov decision problem and attempt to solve a large part of the problem off-line, exploiting the structure of the plan and independence between plan components. We examine the advantages and limitations of these techniques and their scalability.

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

PubMed Central

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.

Resilient control of cyber-physical systems against intelligent attacker: a hierarchal stackelberg game approach

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Sun, Fuchun; Liu, Huaping

2016-07-01

This paper is concerned with the resilient control under denial-of-service attack launched by the intelligent attacker. The resilient control system is modelled as a multi-stage hierarchical game with a corresponding hierarchy of decisions made at cyber and physical layer, respectively. Specifically, the interaction in the cyber layer between different security agents is modelled as a static infinite Stackelberg game, while in the underlying physical layer the full-information H∞ minimax control with package drops is modelled as a different Stackelberg game. Both games are solved sequentially, which is consistent with the actual situations. Finally, the proposed method is applied to the load frequency control of the power system, which demonstrates its effectiveness.

Hierarchical Neural Network (HNN) for Closed Loop Decision Making: Designing the Architecture of a Hierarchical Neural Network to Model Attention, Learning and Goal Oriented Behavior

DTIC Science & Technology

1990-12-01

030(M aau fr e~ re u’. ~oil(eIOE, form a::o n lit Send c f"ent lt ar nq this Ourde" "tii tor ay otther a .e n Of p, amid". to W4Vsntinlln...etadnuaeters ief’ice. 0 i 0reor Iformat.a;tio n ax; d 1 21 ;eQo Q offait of IA4naqe-m.t and Sudget. P01osoer t m edltoru Prole (07044 ,l81.’Nairil m O C NMI. I...I Application of Neural Networks to Robotics I Ziaudin Ahmnad John Selizuky Allm Gun Dmeel University, Depwunent of Electrical miCapue Engineeing

Reciprocal relationships in collective flights of homing pigeons

NASA Astrophysics Data System (ADS)

Xu, Xiao-Ke; Kattas, Graciano Dieck; Small, Michael

2012-02-01

Collective motion of bird flocks can be explained via the hypothesis of many wrongs and/or a structured leadership mechanism. In pigeons, previous studies have shown that there is a well-defined hierarchical structure and certain specific individuals occupy more dominant positions, suggesting that leadership by the few individuals drives the behavior of the collective. Conversely, by analyzing the same datasets, we uncover a more egalitarian mechanism. We show that both reciprocal relationships and a stratified hierarchical leadership are important and necessary in the collective movements of pigeon flocks. Rather than birds adopting either exclusive averaging or leadership strategies, our experimental results show that it is an integrated combination of both compromise and leadership which drives the group's movement decisions.

Activity recognition using dynamic multiple sensor fusion in body sensor networks.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2012-01-01

Multiple sensor fusion is a main research direction for activity recognition. However, there are two challenges in those systems: the energy consumption due to the wireless transmission and the classifier design because of the dynamic feature vector. This paper proposes a multi-sensor fusion framework, which consists of the sensor selection module and the hierarchical classifier. The sensor selection module adopts the convex optimization to select the sensor subset in real time. The hierarchical classifier combines the Decision Tree classifier with the Naïve Bayes classifier. The dataset collected from 8 subjects, who performed 8 scenario activities, was used to evaluate the proposed system. The results show that the proposed system can obviously reduce the energy consumption while guaranteeing the recognition accuracy.

Inferring a District-Based Hierarchical Structure of Social Contacts from Census Data

PubMed Central

Yu, Zhiwen; Liu, Jiming; Zhu, Xianjun

2015-01-01

Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual’s social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model. PMID:25679787

Rough Set Approach to Incomplete Multiscale Information System

PubMed Central

Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

2014-01-01

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

Fuzzy Behavior-Based Navigation for Planetary

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Danny, Harrison; Lippincott, Tanya; Jamshidi, Mo

1997-01-01

Adaptive behavioral capabilities are necessary for robust rover navigation in unstructured and partially-mapped environments. A control approach is described which exploits the approximate reasoning capability of fuzzy logic to produce adaptive motion behavior. In particular, a behavior-based architecture for hierarchical fuzzy control of microrovers is presented. Its structure is described, as well as mechanisms of control decision-making which give rise to adaptive behavior. Control decisions for local navigation result from a consensus of recommendations offered only by behaviors that are applicable to current situations. Simulation predicts the navigation performance on a microrover in simplified Mars-analog terrain.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Decision Aids for Airborne Intercept Operations in Advanced Aircrafts

NASA Technical Reports Server (NTRS)

Madni, A.; Freedy, A.

1981-01-01

A tactical decision aid (TDA) for the F-14 aircrew, i.e., the naval flight officer and pilot, in conducting a multitarget attack during the performance of a Combat Air Patrol (CAP) role is presented. The TDA employs hierarchical multiattribute utility models for characterizing mission objectives in operationally measurable terms, rule based AI-models for tactical posture selection, and fast time simulation for maneuver consequence prediction. The TDA makes aspect maneuver recommendations, selects and displays the optimum mission posture, evaluates attackable and potentially attackable subsets, and recommends the 'best' attackable subset along with the required course perturbation.

Narratives of Assimilation, Divergence, and Hybridity: The Reproduction Decisions of College-Educated Mexican American Women

ERIC Educational Resources Information Center

Alvarado, Emmanuel; Nehring, Daniel

2012-01-01

Our study explored cultural understandings surrounding the reproductive decisions of US-born, college-educated Mexican American women through a series of semi-structured in-depth interviews. In considering the results, this article advances debates on Latina women's reproductive choices beyond the theoretical paradigms of "assimilation" and…

An Investigation of Data Overload in Team-Based Distributed Cognition Systems

ERIC Educational Resources Information Center

Hellar, David Benjamin

2009-01-01

The modern military command center is a hybrid system of computer automated surveillance and human oriented decision making. In these distributed cognition systems, data overload refers simultaneously to the glut of raw data processed by information technology systems and the dearth of actionable knowledge useful to human decision makers.…

Microbial-enzymatic-hybrid biological fuel cell with optimized growth conditions for Shewanella oneidensis DSP-10.

PubMed

Roy, Jared N; Luckarift, Heather R; Sizemore, Susan R; Farrington, Karen E; Lau, Carolin; Johnson, Glenn R; Atanassov, Plamen

2013-07-10

In this work we present a biological fuel cell fabricated by combining a Shewanella oneidensis microbial anode and a laccase-modified air-breathing cathode. This concept is devised as an extension to traditional biochemical methods by incorporating diverse biological catalysts with the aim of powering small devices. In preparing the biological fuel cell anode, novel hierarchical-structured architectures and biofilm configurations were investigated. A method for creating an artificial biofilm based on encapsulating microorganisms in a porous, thin film of silica was compared with S. oneidensis biofilms that were allowed to colonize naturally. Results indicate comparable current and power densities for artificial and natural biofilm formations, based on growth characteristics. As a result, this work describes methods for creating controllable and reproducible bio-anodes and demonstrates the versatility of hybrid biological fuel cells. Copyright © 2013 Elsevier Inc. All rights reserved.

Self-Biased Hybrid Piezoelectric-Photoelectrochemical Cell with Photocatalytic Functionalities.

PubMed

Tan, Chuan Fu; Ong, Wei Li; Ho, Ghim Wei

2015-07-28

Utilizing solar energy for environmental and energy remediations based on photocatalytic hydrogen (H2) generation and water cleaning poses great challenges due to inadequate visible-light power conversion, high recombination rate, and intermittent availability of solar energy. Here, we report an energy-harvesting technology that utilizes multiple energy sources for development of sustainable operation of dual photocatalytic reactions. The fabricated hybrid cell combines energy harvesting from light and vibration to run a power-free photocatalytic process that exploits novel metal-semiconductor branched heterostructure (BHS) of its visible light absorption, high charge-separation efficiency, and piezoelectric properties to overcome the aforementioned challenges. The desirable characteristics of conductive flexible piezoelectrode in conjunction with pronounced light scattering of hierarchical structure originate intrinsically from the elaborate design yet facile synthesis of BHS. This self-powered photocatalysis system could potentially be used as H2 generator and water treatment system to produce clean energy and water resources.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-10-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-01-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature. PMID:27054199

Use of video to facilitate sideline concussion diagnosis and management decision-making.

PubMed

Davis, Gavin; Makdissi, Michael

2016-11-01

Video analysis can provide critical information to improve diagnostic accuracy and speed of clinical decision-making in potential cases of concussion. The objective of this study was to validate a hierarchical flowchart for the assessment of video signs of concussion, and to determine whether its implementation could improve the process of game day video assessment. Prospective cohort study. All impacts and collisions potentially resulting in a concussion were identified during 2012 and 2013 Australian Football League (AFL) seasons. Consensus definitions were developed for clinical signs associated with concussion. A hierarchical flowchart was developed based on the reliability and validity of the video signs of concussion. Ninety videos were assessed, with 45 incidents of clinically confirmed concussion, and 45 cases where no concussion was sustained. Each video was examined using the hierarchical flowchart, and a single response was given for each video based on the highest-ranking element in the flowchart. No protective action, impact seizure, motor incoordination or blank/vacant look were the highest ranked video signs in almost half of the clinically confirmed concussions, but in only 8.8% of non-concussed individuals. The presence of facial injury, clutching at the head and slow to get up were the highest ranked sign in 77.7% of non-concussed individuals. This study suggests that the implementation of a flowchart model could improve timely assessment of concussion, and it identifies the video signs that should trigger automatic removal from play. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Interneuronal Mechanism for Tinbergen’s Hierarchical Model of Behavioral Choice

PubMed Central

Pirger, Zsolt; Crossley, Michael; László, Zita; Naskar, Souvik; Kemenes, György; O’Shea, Michael; Benjamin, Paul R.; Kemenes, Ildikó

2014-01-01

Summary Recent studies of behavioral choice support the notion that the decision to carry out one behavior rather than another depends on the reconfiguration of shared interneuronal networks [1]. We investigated another decision-making strategy, derived from the classical ethological literature [2, 3], which proposes that behavioral choice depends on competition between autonomous networks. According to this model, behavioral choice depends on inhibitory interactions between incompatible hierarchically organized behaviors. We provide evidence for this by investigating the interneuronal mechanisms mediating behavioral choice between two autonomous circuits that underlie whole-body withdrawal [4, 5] and feeding [6] in the pond snail Lymnaea. Whole-body withdrawal is a defensive reflex that is initiated by tactile contact with predators. As predicted by the hierarchical model, tactile stimuli that evoke whole-body withdrawal responses also inhibit ongoing feeding in the presence of feeding stimuli. By recording neurons from the feeding and withdrawal networks, we found no direct synaptic connections between the interneuronal and motoneuronal elements that generate the two behaviors. Instead, we discovered that behavioral choice depends on the interaction between two unique types of interneurons with asymmetrical synaptic connectivity that allows withdrawal to override feeding. One type of interneuron, the Pleuro-Buccal (PlB), is an extrinsic modulatory neuron of the feeding network that completely inhibits feeding when excited by touch-induced monosynaptic input from the second type of interneuron, Pedal-Dorsal12 (PeD12). PeD12 plays a critical role in behavioral choice by providing a synaptic pathway joining the two behavioral networks that underlies the competitive dominance of whole-body withdrawal over feeding. PMID:25155505

Rapid single nucleotide polymorphism detection for personalized medicine applications using planar waveguide fluorescence sensors

NASA Astrophysics Data System (ADS)

Herron, James N.; Tolley, Samuel E.; Smith, Richard; Christensen, Douglas A.

2006-02-01

Personalized medicine is an emerging field in which clinical diagnostics information about a patient's genotype or phenotype is used to optimize his/her pharmacotherapy. This article evaluates whether planar waveguide fluorescent sensors are suitable for determining such information from patient testing in point-of-care (POC) settings. The model system was Long QT Syndrome, a congenital disease associated with single nucleotide polymorphisms (SNPs) in genes encoding for cardiac ion channels. Three different SNP assay formats were examined: DNA/DNA hybridization, DNA/PNA hybridization (PNA: "peptide nucleic acid"), and single base extension (SBEX). Although DNA/DNA hybridization produced a strong intensity-time response for both wildtype and SNP analytes in a 5-min assay at 32°C, their hybridization rates differed by only 32.7%, which was insufficient for clinical decision-making. Much better differentiation of the two rates was observed at 53°C, where the wildtype's hybridization rate was two-thirds of its maximum value, while that of the SNP was essentially zero. Such all-or-nothing resolution would be adequate for clinical decision-making; however, the elevated temperature and precise temperature control would be hard to achieve in a POC setting. Results from DNA/PNA hybridization studies were more promising. Nearly 20-fold discrimination between wildtype and SNP hybridization rates was observed in a 5-min assay at 30°C, although the low ionic strength conditions required necessitated a de-salting step between sample preparation and SNP detection. SBEX was the most promising of the three, determining the absolute identity of the suspected polymorphism in a 5-min assay at 40°C.

Flexible Hybrid Membranes with Ni(OH)2 Nanoplatelets Vertically Grown on Electrospun Carbon Nanofibers for High-Performance Supercapacitors.

PubMed

Zhang, Longsheng; Ding, Qianwei; Huang, Yunpeng; Gu, Huahao; Miao, Yue-E; Liu, Tianxi

2015-10-14

The practical applications of transition metal oxides and hydroxides for supercapacitors are restricted by their intrinsic poor conductivity, large volumetric expansion, and rapid capacitance fading upon cycling, which can be solved by optimizing these materials to nanostructures and confining them within conductive carbonaceous frameworks. In this work, flexible hybrid membranes with ultrathin Ni(OH)2 nanoplatelets vertically and uniformly anchored on the electrospun carbon nanofibers (CNF) have been facilely prepared as electrode materials for supercapacitors. The Ni(OH)2/CNF hybrid membranes with three-dimensional macroporous architectures as well as hierarchical nanostructures can provide open and continuous channels for rapid diffusion of electrolyte to access the electrochemically active Ni(OH)2 nanoplatelets. Moreover, the carbon nanofiber can act both as a conductive core to provide efficient transport of electrons for fast Faradaic redox reactions of the Ni(OH)2 sheath, and as a buffering matrix to mitigate the local volumetric expansion/contraction upon long-term cycling. As a consequence, the optimized Ni(OH)2/CNF hybrid membrane exhibits a high specific capacitance of 2523 F g(-1) (based on the mass of Ni(OH)2, that is 701 F g(-1) based on the total mass) at a scan rate of 5 mV s(-1). The Ni(OH)2/CNF hybrid membranes with high mechanical flexibility, superior electrical conductivity, and remarkably improved electrochemical capacitance are condsidered as promising flexible electrode materials for high-performance supercapacitors.

Nanomorphology Effects in Semiconductors with Native Ferromagnetism: Hierarchical Europium (II) Oxide Tubes Prepared via a Topotactic Nanostructure Transition.

PubMed

Trepka, Bastian; Erler, Philipp; Selzer, Severin; Kollek, Tom; Boldt, Klaus; Fonin, Mikhail; Nowak, Ulrich; Wolf, Daniel; Lubk, Axel; Polarz, Sebastian

2018-01-01

Semiconductors with native ferromagnetism barely exist and defined nanostructures are almost unknown. This lack impedes the exploration of a new class of materials characterized by a direct combination of effects on the electronic system caused by quantum confinement effects with magnetism. A good example is EuO for which currently no reliable routes for nanoparticle synthesis can be established. Bottom-up approaches applicable to other oxides fail because of the labile oxidation state +II. Instead of targeting a direct synthesis, the two steps-"structure control" and "chemical transformation"-are separated. The generation of a transitional, hybrid nanophase is followed by its conversion into EuO under full conservation of all morphological features. Hierarchical EuO materials are now accessible in the shape of oriented nanodisks stacked to tubular particles. Magnetically, the coupling of either vortex or onion states has been found. An unexpected temperature dependence is governed by thermally activated transitions between these states. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Carbon coated SnO2 nanoparticles anchored on CNT as a superior anode material for lithium-ion batteries.

PubMed

Ma, Chunrong; Zhang, Weimin; He, Yu-Shi; Gong, Qiang; Che, Haiying; Ma, Zi-Feng

2016-02-21

Hierarchically structured carbon coated SnO2 nanoparticles well-anchored on the surface of a CNT (C-SnO2/CNT) material were synthesized by a facile hydrothermal process and subsequent carbonization. The as-obtained C-SnO2/CNT hybrid, when applied as an anode material for lithium ion batteries (LIBs), showed a high reversible capacity up to 1572 mA h g(-1) at 200 mA g(-1) with a superior rate capability (685 mA h g(-1) at 4000 mA g(-1)). Even after 100 charge/discharge cycles at 1000 mA g(-1), a specific capacity of 1100 mA h g(-1) can still be maintained. Such impressive electrochemical performance can be mainly attributed to the hierarchical sandwiched structure and strong synergistic effects of the ultrafine SnO2 nanoparticles and the carbon coating, and thus presents this material a promising anode material for LIBs.

Graphene-Encapsulated Nanosheet-Assembled Zinc-Nickel-Cobalt Oxide Microspheres for Enhanced Lithium Storage.

PubMed

Zhang, Qiaobao; Chen, Huixin; Han, Xiang; Cai, Junjie; Yang, Yong; Liu, Meilin; Zhang, Kaili

2016-01-01

The appropriate combination of hierarchical transition-metal oxide (TMO) micro-/nanostructures constructed from porous nanobuilding blocks with graphene sheets (GNS) in a core/shell geometry is highly desirable for high-performance lithium-ion batteries (LIBs). A facile and scalable process for the fabrication of 3D hierarchical porous zinc-nickel-cobalt oxide (ZNCO) microspheres constructed from porous ultrathin nanosheets encapsulated by GNS to form a core/shell geometry is reported for improved electrochemical performance of the TMOs as an anode in LIBs. By virtue of their intriguing structural features, the produced ZNCO/GNS core/shell hybrids exhibit an outstanding reversible capacity of 1015 mA h g(-1) at 0.1 C after 50 cycles. Even at a high rate of 1 C, a stable capacity as high as 420 mA h g(-1) could be maintained after 900 cycles, which suggested their great potential as efficient electrodes for high-performance LIBs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards Stability Analysis of Jump Linear Systems with State-Dependent and Stochastic Switching

NASA Technical Reports Server (NTRS)

Tejada, Arturo; Gonzalez, Oscar R.; Gray, W. Steven

2004-01-01

This paper analyzes the stability of hierarchical jump linear systems where the supervisor is driven by a Markovian stochastic process and by the values of the supervised jump linear system s states. The stability framework for this class of systems is developed over infinite and finite time horizons. The framework is then used to derive sufficient stability conditions for a specific class of hybrid jump linear systems with performance supervision. New sufficient stochastic stability conditions for discrete-time jump linear systems are also presented.

Adaptive Meshing Techniques for Viscous Flow Calculations on Mixed Element Unstructured Meshes

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.

1997-01-01

An adaptive refinement strategy based on hierarchical element subdivision is formulated and implemented for meshes containing arbitrary mixtures of tetrahendra, hexahendra, prisms and pyramids. Special attention is given to keeping memory overheads as low as possible. This procedure is coupled with an algebraic multigrid flow solver which operates on mixed-element meshes. Inviscid flows as well as viscous flows are computed an adaptively refined tetrahedral, hexahedral, and hybrid meshes. The efficiency of the method is demonstrated by generating an adapted hexahedral mesh containing 3 million vertices on a relatively inexpensive workstation.

Effects of in-vehicle warning information displays with or without spatial compatibility on driving behaviors and response performance.

PubMed

Liu, Yung-Ching; Jhuang, Jing-Wun

2012-07-01

A driving simulator study was conducted to evaluate the effects of five in-vehicle warning information displays upon drivers' emergent response and decision performance. These displays include visual display, auditory displays with and without spatial compatibility, hybrid displays in both visual and auditory format with and without spatial compatibility. Thirty volunteer drivers were recruited to perform various tasks that involved driving, stimulus-response, divided attention and stress rating. Results show that for displays of single-modality, drivers benefited more when coping with visual display of warning information than auditory display with or without spatial compatibility. However, auditory display with spatial compatibility significantly improved drivers' performance in reacting to the divided attention task and making accurate S-R task decision. Drivers' best performance results were obtained for hybrid display with spatial compatibility. Hybrid displays enabled drivers to respond the fastest and achieve the best accuracy in both S-R and divided attention tasks. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Hybrid General Pattern Search and Simulated Annealing for Industrail Production Planning Problems

NASA Astrophysics Data System (ADS)

Vasant, P.; Barsoum, N.

2010-06-01

In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.

Preliminary design data package, appendix C. [hybrid electric vehicles

NASA Technical Reports Server (NTRS)

1979-01-01

The data and documentation required to define the preliminary design of a near term hybrid vehicle and to quantify its operational characteristics are presented together with the assumptions and rationale behind the design decisions. Aspects discussed include development requirements for the propulsion system, the chassis system, the body, and the vehicle systems. Particular emphasis is given to the controls, the heat engine, and the batteries.

Complexity science and participation in decision making among Taiwanese nurses.

PubMed

Liu, Yi

2008-04-01

The perspective of interconnection in complexity science is used to examine the concept of participation in decision making among Taiwanese nurses in the context of Chinese communication culture. Participation in decision making among nurses has been widely discussed and tested in the Western healthcare systems. Many studies have shown that participation in decision making relates to nurses' autonomy, job satisfaction and quality of care. However, participation in decision making has not been fully discussed in Taiwan's nursing community. In a different cultural environment, participation in decision making may have different effects. The concept of participation in decision making is analysed in three facets of Chinese communication culture: (1) hierarchical social relationship; (2) harmony maintenance; and (3) insider effects. Key issues Taiwanese nurses might establish different levels of participation and need to use different strategies to enhance participation in decision making for desired outcomes. While applying participation in decision making in a different context, it is very important to consider the social and cultural differences. Two implications are made. First, nursing leaders/managers who are working with a multicultural team should be aware of the cultural difference in the pattern of interaction in the process of participation in decision making. Second, leaders/managers should be creative and try to apply different strategies to encourage staff's participation in decision making.

HIV-related stigma acting as predictors of unemployment of people living with HIV/AIDS.

PubMed

Liu, Ying; Canada, Kelli; Shi, Kan; Corrigan, Patrick

2012-01-01

Obtaining employment is an important part of recovery for many people living with HIV/AIDS (PLHA). However, this population often faces barriers in their attempt to reenter the workplace. One potential barrier lies in the decision-making of employers. Little is known about what influences employers' decision to hire PLHA. The current paper addresses this gap with findings from 156 quantitative interviews with employers across Chicago, Beijing, and Hong Kong regarding the hiring of people with HIV/AIDS. Hierarchical regression analysis showed that both fear of contagion and perceived incompetence are important factors in employers' decision to interview even after controlling for variables related to the employers' business size, their education level, and the provision of health benefits. These two variables accounted for 42% of the variance in employers' decision to interview. Implications of these findings are considered for better understanding of HIV-related employment stigma and further intervention for employing PLHA.

Psychophysiological arousal and inter‐ and intraindividual differences in risk‐sensitive decision making

PubMed Central

Scheibehenne, Benjamin; Clark, Luke

2016-01-01

Abstract The current study assessed peripheral responses during decision making under explicit risk, and tested whether intraindividual variability in choice behavior can be explained by fluctuations in peripheral arousal. Electrodermal activity (EDA) and heart rate (HR) were monitored in healthy volunteers (N = 68) during the Roulette Betting Task. In this task, participants were presented with risky gambles to bet on, with the chances of winning varying across trials. Hierarchical Bayesian analyses demonstrated that EDA and HR acceleration responses during the decision phase were sensitive to the chances of winning. Interindividual differences in this peripheral reactivity during risky decision making were related to trait sensitivity to punishment and trait sensitivity to reward. Moreover, trial‐by‐trial variation in EDA and HR acceleration responses predicted a small portion of intraindividual variability in betting choices. Our results show that psychophysiological responses are sensitive to explicit risk and can help explain intraindividual heterogeneity in choice behavior. PMID:26927730

An Intelligent Hierarchical Decision Architecture for Operational Test and Evaluation

DTIC Science & Technology

1996-05-01

Results .......................................... 60 3.4 CONTRIBUTION...FCM Fuzzy Cognitive Map FMEA Failure Modes and Effects Analysis HWIL Hardware-in-the-Loop IBL Increase in Break Locks xiv IDA Institute for Defense... 60 .5 .40 3 .25 0.21 0.26 Figure 8 PROD-ALL COMMFFY Compositional Method .65 . 7 5 . 60 M 0.67 Figure 9 PROD-MAX COMMFFY Compositional Method 49

Resource analysis and land use planning with space and high altitude photography

NASA Technical Reports Server (NTRS)

Schrumpf, B. J.

1972-01-01

Photographic scales providing resource data for decision making processes of land use and a legend system for barren lands, water resources, natural vegetation, agricultural, urban, and industrial lands in hierarchical framework are applied to various remote sensing techniques. Two natural vegetation resource and land use maps for a major portion of Maricopa County, Arizona are also produced.

A Hierarchical Framework for Demand-Side Frequency Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moya, Christian; Zhang, Wei; Lian, Jianming

2014-06-02

With large-scale plans to integrate renewable generation, more resources will be needed to compensate for the uncertainty associated with intermittent generation resources. Under such conditions, performing frequency control using only supply-side resources become not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in frequency control to maintain the stability of the system at an acceptable cost. In this paper, a novel hierarchical decentralized framework for frequency based load control is proposed. The framework involves two decision layers. The top decision layer determines themore » optimal droop gain required from the aggregated load response on each bus using a robust decentralized control approach. The second layer consists of a large number of devices, which switch probabilistically during contingencies so that the aggregated power change matches the desired droop amount according to the updated gains. The proposed framework is based on the classical nonlinear multi-machine power system model, and can deal with timevarying system operating conditions while respecting the physical constraints of individual devices. Realistic simulation results based on a 68-bus system are provided to demonstrate the effectiveness of the proposed strategy.« less

Assessing the Effects of Financial Literacy on Patient Engagement.

PubMed

Meyer, Melanie A; Hudak, Ronald P

2016-07-01

We investigated the relationship between financial literacy and patient engagement while considering the possible interaction effects due to patient financial responsibility and patient-physician shared decision making, and the impact of personal attributes. Participants consisted of an Internet-based sample of American adults (N = 160). Hierarchical multiple linear regression analysis was conducted to examine the relationship of the study variables on patient engagement. We found that patient financial responsibility (β = -.19, p < .05) and patient-physician shared decision-making (β = .17, p < .05) predicted patient engagement. However, there was no statistically significant relationship between patient financial literacy and patient engagement; moreover, the moderation effects of patient financial responsibility and shared decision making with financial literacy also were not statistically significant. Increasing patient financial responsibility and patient-physician shared decision making can impact patient engagement. Understanding the predictors of patient engagement and the factors that influence financial behaviors may allow for the development of interventions to enable patients to make better healthcare decisions, and ultimately, improve health outcomes.

Improving the food waste composting facilities site selection for sustainable development using a hybrid modified MADM model.

PubMed

Liu, Kung-Ming; Lin, Sheng-Hau; Hsieh, Jing-Chzi; Tzeng, Gwo-Hshiung

2018-05-01

With the growth of population and the development of urbanization, waste management has always been a critical global issue. Recently, more and more countries have found that food waste constitutes the majority of municipal waste, if they are disposed of properly, will bring more benefits in sustainable development. Regarding the issue of selecting and improving the location to make the disposal facility towards achieving the aspiration level for sustainable development, since it involves multiple and complicated interaction factors about environment, society, and economy which have to be considered properly in the decision-making process of mutual influence relationship. It is basically a multiple attribute decision making (MADM) issue, a difficult problem which has been obsessing the governments of many countries is widely studied and discussed. This study uses the new hybrid modified MADM model, as follows, first to build an influential network relation map (INRM) via DEMATEL technique, next to confirm the influential weightings via DANP (DEMATEL-based ANP), and then to construct a decision-making model via a hybrid modified VIKOR method to improve and select the location for remaining the best disposal facilities. Finally, an empirical case study is illustrated to demonstrate that the proposed model can be effective and useful. In finding the process of decision making, environmental pollution is the main concern of many people in the area, but actually it is the resistance by the general public that has to be considered with first priority. Copyright © 2018. Published by Elsevier Ltd.

Hierarchical classification of land use types using multiple vegetation indices to measure the effects of urbanization.

PubMed

Shishir, Sharmin; Tsuyuzaki, Shiro

2018-05-11

Detecting fine-scale spatiotemporal land use changes is a prerequisite for understanding and predicting the effects of urbanization and its related human impacts on the ecosystem. Land use changes are frequently examined using vegetation indices (VIs), although the validation of these indices has not been conducted at a high resolution. Therefore, a hierarchical classification was constructed to obtain accurate land use types at a fine scale. The characteristics of four popular VIs were investigated prior to examining the hierarchical classification by using Purbachal New Town, Bangladesh, which exhibits ongoing urbanization. These four VIs are the normalized difference VI (NDVI), green-red VI (GRVI), enhanced VI (EVI), and two-band EVI (EVI2). The reflectance data were obtained by the IKONOS (0.8-m resolution) and WorldView-2 sensor (0.5-m resolution) in 2001 and 2015, respectively. The hierarchical classification of land use types was constructed using a decision tree (DT) utilizing all four of the examined VIs. The accuracy of the classification was evaluated using ground truth data with multiple comparisons and kappa (κ) coefficients. The DT showed overall accuracies of 96.1 and 97.8% in 2001 and 2015, respectively, while the accuracies of the VIs were less than 91.2%. These results indicate that each VI exhibits unique advantages. In addition, the DT was the best classifier of land use types, particularly for native ecosystems represented by Shorea forests and homestead vegetation, at the fine scale. Since the conservation of these native ecosystems is of prime importance, DTs based on hierarchical classifications should be used more widely.

Developing a Hierarchical Decision Model to Evaluate Nuclear Power Plant Alternative Siting Technologies

NASA Astrophysics Data System (ADS)

Lingga, Marwan Mossa

A strong trend of returning to nuclear power is evident in different places in the world. Forty-five countries are planning to add nuclear power to their grids and more than 66 nuclear power plants are under construction. Nuclear power plants that generate electricity and steam need to improve safety to become more acceptable to governments and the public. One novel practical solution to increase nuclear power plants' safety factor is to build them away from urban areas, such as offshore or underground. To date, Land-Based siting is the dominant option for siting all commercial operational nuclear power plants. However, the literature reveals several options for building nuclear power plants in safer sitings than Land-Based sitings. The alternatives are several and each has advantages and disadvantages, and it is difficult to distinguish among them and choose the best for a specific project. In this research, we recall the old idea of using the alternatives of offshore and underground sitings for new nuclear power plants and propose a tool to help in choosing the best siting technology. This research involved the development of a decision model for evaluating several potential nuclear power plant siting technologies, both those that are currently available and future ones. The decision model was developed based on the Hierarchical Decision Modeling (HDM) methodology. The model considers five major dimensions, social, technical, economic, environmental, and political (STEEP), and their related criteria and sub-criteria. The model was designed and developed by the author, and its elements' validation and evaluation were done by a large number of experts in the field of nuclear energy. The decision model was applied in evaluating five potential siting technologies and ranked the Natural Island as the best in comparison to Land-Based, Floating Plant, Artificial Island, and Semi-Embedded plant.

[Nurses' subjectivity production and the decision-making in the process of care].

PubMed

Busanello, Josefine; Lunardi Filho, Wilson Danilo; Kerber, Nalú Pereira da Costa

2013-06-01

This study aimed to understand the relationship between Nurse's production of subjectivity and the decision-making in the process of Nursing care. A qualitative design of research was conducted. The investigation was carried out with twelve nurses who work at the Associação de Caridade Santa Casa do Rio Grande, a hospital located in Rio Grande, RS, Brazil. For data collection, focus group technique was used three meetings were conducted in december 2011. The results were presented in semantic categories: Capitalist System: maintenance of employment bond; Submission System: institutionalized culture and vision of society; Nursing Hierarchical System; and Values System: feeling of guilt and lack of professional recognition. The capitalist system mediates, mainly, the behavior that prevails in the decision-making process in Nursing care.

Metacognitive Awareness of Facial Affect in Higher-Functioning Children and Adolescents with Autism Spectrum Disorder

PubMed Central

Henderson, Heather A.; Newell, Lisa; Jaime, Mark; Mundy, Peter

2015-01-01

Higher-functioning participants with and without autism spectrum disorder (ASD) viewed a series of face stimuli, made decisions regarding the affect of each face, and indicated their confidence in each decision. Confidence significantly predicted accuracy across all participants, but this relation was stronger for participants with typical development than participants with ASD. In the hierarchical linear modeling analysis, there were no differences in face processing accuracy between participants with and without ASD, but participants with ASD were more confident in their decisions. These results suggest that individuals with ASD have metacognitive impairments and are overconfident in face processing. Additionally, greater metacognitive awareness was predictive of better face processing accuracy, suggesting that metacognition may be a pivotal skill to teach in interventions. PMID:26496991

A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation

NASA Astrophysics Data System (ADS)

Dursun, Mehtap

2017-06-01

Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.

Decision Support System for Determining Scholarship Selection using an Analytical Hierarchy Process

NASA Astrophysics Data System (ADS)

Puspitasari, T. D.; Sari, E. O.; Destarianto, P.; Riskiawan, H. Y.

2018-01-01

Decision Support System is a computer program application that analyzes data and presents it so that users can make decision more easily. Determining Scholarship Selection study case in Senior High School in east Java wasn’t easy. It needed application to solve the problem, to improve the accuracy of targets for prospective beneficiaries of poor students and to speed up the screening process. This research will build system uses the method of Analytical Hierarchy Process (AHP) is a method that solves a complex and unstructured problem into its group, organizes the groups into a hierarchical order, inputs numerical values instead of human perception in comparing relative and ultimately with a synthesis determined elements that have the highest priority. The accuracy system for this research is 90%.

Ni nanoparticles@Ni-Mo nitride nanorod arrays: a novel 3D-network hierarchical structure for high areal capacitance hybrid supercapacitors.

PubMed

Ruan, Yunjun; Lv, Lin; Li, Zhishan; Wang, Chundong; Jiang, Jianjun

2017-11-23

Because of the advanced nature of their high power density, fast charge/discharge time, excellent cycling stability, and safety, supercapacitors have attracted intensive attention for large-scale applications. Nevertheless, one of the obstacles for their further development is their low energy density caused by sluggish redox reaction kinetics, low electroactive electrode materials, and/or high internal resistance. Here, we develop a facile and simple nitridation process to successfully synthesize hierarchical Ni nanoparticle decorated Ni 0.2 Mo 0.8 N nanorod arrays on a nickel foam (Ni-Mo-N NRA/NF) from its NiMoO 4 precursor, which delivers a high areal capacity of 2446 mC cm -2 at a current density of 2 mA cm -2 and shows outstanding cycling stability. The superior performance of the Ni-Mo-N NRA/NF can be ascribed to the metallic conductive nature of the Ni-Mo nitride, the fast surface redox reactions for the electrolyte ions and electrode materials, and the low contacted resistance between the active materials and the current collectors. Furthermore, a hybrid supercapacitor (HSC) is assembled using the Ni-Mo-N NRA/NF as the positive electrode and reduced graphene oxide (RGO) as the negative electrode. The optimized HSC exhibits excellent electrochemical performance with a high energy density of 40.9 W h kg -1 at a power density of 773 W kg -1 and a retention of 80.1% specific capacitance after 6000 cycles. These results indicate that the Ni-Mo-N NRA/NF have a promising potential for use in high-performance supercapacitors.

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

PubMed Central

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

Carbon nanotube-templated assembly of regioregular poly(3-alkylthiophene) in solution

NASA Astrophysics Data System (ADS)

Zhu, Jiahua; Stevens, Eric; He, Youjun; Hong, Kunlun; Ivanov, Ilia

2016-09-01

Control of structural heterogeneity by rationally encoding of the molecular assemblies is a key enabling design of hierarchical, multifunctional materials of the future. Here we report the strategies to gain such control using solution- based assembly to construct a hybrid nano-assembly and a network hybrid structure of regioregular poly(3- alkylthiophene) - carbon nanotube (P3AT-CNT). The opto-electronic performance of conjugated polymer (P3AT) is defined by the structure of the aggregate in solution and in the solid film. Control of P3AT aggregation would allow formation of broad range of morphologies with very distinct electro-optical. We utilize interactive templating to confine the assembly behavior of conjugated polymers, replacing poorly controlled solution processing approach. Perfect crystalline surface of the single-walled and multi-walled carbon nanotube (SWCNT/MWCNT) acts as a template, seeding P3AT aggregation of the surface of the nanotube. The seed continues directional growth through pi-pi stacking leading to the formation of to well-defined P3AT-CNT morphologies, including comb-like nano-assemblies, super- structures and gel networks. Interconnected, highly-branched network structure of P3AT-CNT hybrids is of particular interest to enable efficient, long-range, balanced charge carrier transport. The structure and opto-electionic function of the intermediate assemblies and networks of P3AT/CNT hybrids are characterized by transmission election microscopy and UV-vis absorption.

Effects of a hybrid micro/nanorod topography-modified titanium implant on adhesion and osteogenic differentiation in rat bone marrow mesenchymal stem cells.

PubMed

Zhang, Wenjie; Li, Zihui; Huang, Qingfeng; Xu, Ling; Li, Jinhua; Jin, Yuqin; Wang, Guifang; Liu, Xuanyong; Jiang, Xinquan

2013-01-01

Various methods have been used to modify titanium implant surfaces with the aim of achieving better osseointegration. In this study, we fabricated a clustered nanorod structure on an acid-etched, microstructured titanium plate surface using hydrogen peroxide. We also evaluated biofunctionalization of the hybrid micro/nanorod topography on rat bone marrow mesenchymal stem cells. Scanning electron microscopy and x-ray diffraction were used to investigate the surface topography and phase composition of the modified titanium plate. Rat bone marrow mesenchymal stem cells were cultured and seeded on the plate. The adhesion ability of the cells was then assayed by cell counting at one, 4, and 24 hours after cell seeding, and expression of adhesion-related protein integrin β1 was detected by immunofluorescence. In addition, a polymerase chain reaction assay, alkaline phosphatase and Alizarin Red S staining assays, and osteopontin and osteocalcin immunofluorescence analyses were used to evaluate the osteogenic differentiation behavior of the cells. The hybrid micro/nanoscale texture formed on the titanium surface enhanced the initial adhesion activity of the rat bone marrow mesenchymal stem cells. Importantly, the hierarchical structure promoted osteogenic differentiation of these cells. This study suggests that a hybrid micro/nanorod topography on a titanium surface fabricated by treatment with hydrogen peroxide followed by acid etching might facilitate osseointegration of a titanium implant in vivo.

A Network Selection Algorithm Considering Power Consumption in Hybrid Wireless Networks

NASA Astrophysics Data System (ADS)

Joe, Inwhee; Kim, Won-Tae; Hong, Seokjoon

In this paper, we propose a novel network selection algorithm considering power consumption in hybrid wireless networks for vertical handover. CDMA, WiBro, WLAN networks are candidate networks for this selection algorithm. This algorithm is composed of the power consumption prediction algorithm and the final network selection algorithm. The power consumption prediction algorithm estimates the expected lifetime of the mobile station based on the current battery level, traffic class and power consumption for each network interface card of the mobile station. If the expected lifetime of the mobile station in a certain network is not long enough compared the handover delay, this particular network will be removed from the candidate network list, thereby preventing unnecessary handovers in the preprocessing procedure. On the other hand, the final network selection algorithm consists of AHP (Analytic Hierarchical Process) and GRA (Grey Relational Analysis). The global factors of the network selection structure are QoS, cost and lifetime. If user preference is lifetime, our selection algorithm selects the network that offers longest service duration due to low power consumption. Also, we conduct some simulations using the OPNET simulation tool. The simulation results show that the proposed algorithm provides longer lifetime in the hybrid wireless network environment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ying; Yang, Feng; Lee, Sungsik

Facile fabrication of manganese oxide (MnO x, 0 < x < 2) and nitrogen (N) co-doped carbon microspheres (MnO x-N-CS) has been firstly developed by one-pot construction of Mn-functionalized melamine-formaldehyde (Mn-MF) resin spheres before pyrolysis. The resulting hybrids bear evenly dispersed MnO x and N moieties in situ anchored on hierarchically porous carbon microspheres formed simultaneously. The capacitive performance is greatly tailored by varying the Mn/melamine molar ratio in the synthetic mixture and pyrolysis temperature. It is found that the MnO x-N-CS hybrid (0.008 wt% Mn, pyrolyzed at 800 °C) exhibits the highest specific capacitance up to 258 F gmore » –1 at a scan rate of 1 mV s –1 (in 6 M KOH), and keeps a high capacitance retention ratio of 98% after 5000 cycles. The synergism between MnO x, N moieties and carbon spheres proves to be responsible for the remarkably improved performance, as compared to the pure carbon sphere and MnO x (N)-doped carbon sphere. Lastly, the well-developed MnO x-N-CS hybrids highlight the great potentials for widespread supercapacitor applications.« less

Predicting influent biochemical oxygen demand: Balancing energy demand and risk management.

PubMed

Zhu, Jun-Jie; Kang, Lulu; Anderson, Paul R

2018-01-01

Ready access to comprehensive influent information can help water reclamation plant (WRP) operators implement better real-time process controls, provide operational reliability and reduce energy consumption. The five-day biochemical oxygen demand (BOD 5 ), a critical parameter for WRP process control, is expensive and difficult to measure using hard-sensors. An alternative approach based on a soft-sensor methodology shows promise, but can be problematic when used to predict high BOD 5 values. Underestimating high BOD 5 concentrations for process control could result in an insufficient amount of aeration, increasing the risk of an effluent violation. To address this issue, we tested a hierarchical hybrid soft-sensor approach involving multiple linear regression, artificial neural networks (ANN), and compromise programming. While this hybrid approach results in a slight decrease in overall prediction accuracy relative to the approach based on ANN only, the underestimation percentage is substantially lower (37% vs. 61%) for predictions of carbonaceous BOD 5 (CBOD 5 ) concentrations higher than the long-term average value. The hybrid approach is also flexible and can be adjusted depending on the relative importance between energy savings and managing the risk of an effluent violation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Green material selection for sustainability: A hybrid MCDM approach.

PubMed

Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng

2017-01-01

Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection.

Green material selection for sustainability: A hybrid MCDM approach

PubMed Central

Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng

2017-01-01

Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection. PMID:28498864

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.

Neuromodulation of Nestmate Recognition Decisions by Pavement Ants.

PubMed

Bubak, Andrew N; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

2016-01-01

Ant colonies are distributed systems that are regulated in a non-hierarchical manner. Without a central authority, individuals inform their decisions by comparing information in local cues to a set of inherent behavioral rules. Individual behavioral decisions collectively change colony behavior and lead to self-organization capable of solving complex problems such as the decision to engage in aggressive societal conflicts with neighbors. Despite the relevance to colony fitness, the mechanisms that drive individual decisions leading to cooperative behavior are not well understood. Here we show how sensory information, both tactile and chemical, and social context-isolation, nestmate interaction, or fighting non-nestmates-affects brain monoamine levels in pavement ants (Tetramorium caespitum). Our results provide evidence that changes in octopamine and serotonin in the brains of individuals are sufficient to alter the decision by pavement ants to be aggressive towards non-nestmate ants whereas increased brain levels of dopamine correlate to physical fighting. We propose a model in which the changes in brain states of many workers collectively lead to the self-organization of societal aggression between neighboring colonies of pavement ants.

Neuromodulation of Nestmate Recognition Decisions by Pavement Ants

PubMed Central

Bubak, Andrew N.; Yaeger, Jazmine D. W.; Renner, Kenneth J.; Swallow, John G.; Greene, Michael J.

2016-01-01

Ant colonies are distributed systems that are regulated in a non-hierarchical manner. Without a central authority, individuals inform their decisions by comparing information in local cues to a set of inherent behavioral rules. Individual behavioral decisions collectively change colony behavior and lead to self-organization capable of solving complex problems such as the decision to engage in aggressive societal conflicts with neighbors. Despite the relevance to colony fitness, the mechanisms that drive individual decisions leading to cooperative behavior are not well understood. Here we show how sensory information, both tactile and chemical, and social context—isolation, nestmate interaction, or fighting non-nestmates—affects brain monoamine levels in pavement ants (Tetramorium caespitum). Our results provide evidence that changes in octopamine and serotonin in the brains of individuals are sufficient to alter the decision by pavement ants to be aggressive towards non-nestmate ants whereas increased brain levels of dopamine correlate to physical fighting. We propose a model in which the changes in brain states of many workers collectively lead to the self-organization of societal aggression between neighboring colonies of pavement ants. PMID:27846261

Identification of delaminations in composite: structural health monitoring software based on spectral estimation and hierarchical genetic algorithm

NASA Astrophysics Data System (ADS)

Nag, A.; Mahapatra, D. Roy; Gopalakrishnan, S.

2003-10-01

A hierarchical Genetic Algorithm (GA) is implemented in a high peformance spectral finite element software for identification of delaminations in laminated composite beams. In smart structural health monitoring, the number of delaminations (or any other modes of damage) as well as their locations and sizes are no way completely known. Only known are the healthy structural configuration (mass, stiffness and damping matrices updated from previous phases of monitoring), sensor measurements and some information about the load environment. To handle such enormous complexity, a hierarchical GA is used to represent heterogeneous population consisting of damaged structures with different number of delaminations and their evolution process to identify the correct damage configuration in the structures under monitoring. We consider this similarity with the evolution process in heterogeneous population of species in nature to develop an automated procedure to decide on what possible damaged configuration might have produced the deviation in the measured signals. Computational efficiency of the identification task is demonstrated by considering a single delamination. The behavior of fitness function in GA, which is an important factor for fast convergence, is studied for single and multiple delaminations. Several advantages of the approach in terms of computational cost is discussed. Beside tackling different other types of damage configurations, further scope of research for development of hybrid soft-computing modules are highlighted.

Chinese Medicine: A Cognitive and Epistemological Review*

PubMed Central

2007-01-01

In spite of the common belief that Chinese natural philosophy and medicine have a unique frame of reference completely foreign to the West, this article argues that they in fact have significant cognitive and epistemic similarities with certain esoteric health beliefs of pre-Christian Europe. From the standpoint of Cognitive Science, Chinese Medicine appears as a proto-scientific system of health observances and practices based on a symptomological classification of disease using two elementary dynamical-processes pattern categorization schemas: a hierarchical and combinatorial inhibiting–activating model (Yin-Yang), and a non-hierarchical and associative five-parameter semantic network (5-Elements/Agents). The concept-map of the five-parameter model amounts to a pentagram, a commonly found geomantic and spell casting sigil in a number of pre-Christian health and safety beliefs in Europe, to include the Pythagorean cult of Hygieia, and the Old Religion of Northern Europe. This non-hierarchical pattern-recognition archetype/prototype was hypothetically added to the pre-existing hierarchical one to form a hybrid nosology that can accommodate for a change in disease perceptions. The selection of five parameters rather than another number might be due to a numerological association between the integer five, the golden ratio, the geometry of the pentagram and the belief in health and wholeness arising from cosmic or divine harmony. In any case, this body of purely empirical knowledge is nowadays widely flourishing in the US and in Europe as an alternative to Western Medicine and with the claim of being a unique, independent and comprehensive medical system, when in reality it is structurally—and perhaps historically—related to the health and safety beliefs of pre-Christian Europe; and without the prospect for an epistemological rupture, it will remain built upon rudimentary cognitive modalities, ancient metaphysics, and a symptomological view of disease. PMID:17965759

Incorporating Edge Information into Best Merge Region-Growing Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Pasolli, Edoardo

2014-01-01

We have previously developed a best merge region-growing approach that integrates nonadjacent region object aggregation with the neighboring region merge process usually employed in region growing segmentation approaches. This approach has been named HSeg, because it provides a hierarchical set of image segmentation results. Up to this point, HSeg considered only global region feature information in the region growing decision process. We present here three new versions of HSeg that include local edge information into the region growing decision process at different levels of rigor. We then compare the effectiveness and processing times of these new versions HSeg with each other and with the original version of HSeg.

Hybridization rapidly reduces fitness of a native trout in the wild

USGS Publications Warehouse

Muhlfeld, C.C.; Kalinowski, S.T.; McMahon, T.E.; Taper, M.L.; Painter, S.; Leary, R.F.; Allendorf, F.W.

2009-01-01

Human-mediated hybridization is a leading cause of biodiversity loss worldwide. How hybridization affects fitness and what level of hybridization is permissible pose difficult conservation questions with little empirical information to guide policy and management decisions. This is particularly true for salmonids, where widespread introgression among non-native and native taxa has often created hybrid swarms over extensive geographical areas resulting in genomic extinction. Here, we used parentage analysis with multilocus microsatellite markers to measure how varying levels of genetic introgression with non-native rainbow trout (Oncorhynchus mykiss) affect reproductive success (number of offspring per adult) of native westslope cutthroat trout (Oncorhynchus clarkii lewisi) in the wild. Small amounts of hybridization markedly reduced fitness of male and female trout, with reproductive success sharply declining by approximately 50 per cent, with only 20 per cent admixture. Despite apparent fitness costs, our data suggest that hybridization may spread due to relatively high reproductive success of first-generation hybrids and high reproductive success of a few males with high levels of admixture. This outbreeding depression suggests that even low levels of admixture may have negative effects on fitness in the wild and that policies protecting hybridized populations may need reconsideration. ?? 2009 The Royal Society.

Three Levels of Push-Pull Dynamics among Chinese International Students' Decision to Study Abroad in the Canadian Context

ERIC Educational Resources Information Center

Chen, Jun Mian

2017-01-01

The extant literature on student migration flows generally focus on the traditional push-pull factors of migration at the individual level. Such a tendency excludes the broader levels affecting international student mobility. This paper proposes a hybrid of three levels of push-pull dynamics (micro-individual decision-making, meso-academic…