24,575 research outputs found
Organization Development Experiences . A Case for Enriching HRD through OD
No full textThis article reviews a few definitions of OD and identifies eight characters that are necessary to call an activity or experience as an OD activity or experience. The article then goes on to examine ten case studies (of research, consulting and OD) of what appears like an OD activity in which the author was involved as one of the facilitators for whole system or subsystem and examines each on of them for their appropriateness to be called as OD interventions. The author then goes on to derive some lessons from these experiences. The article outlines also some advantages of using traditional OD approach in various HRD interventions and offers some suggestions for making specific HRD interventions like competency mapping, 360Degree Feedback based leadership Development and Assessment and Development Centers as OD activities. The paper concludes that using an OD approach enriches HRD and yields a good ROI on HRD interventions.
A data driven method for OD matrix estimation
No full textThe fundamental challenge of the origin-destination (OD) matrix estimation problem is that it is severely under-determined. In this paper we propose a new data driven OD estimation method for cases where a supply pattern in the form of speeds and flows is available. We show that with these input data, we do not require an iterative dynamic network loading procedure that results in an equilibrium assignment, nor do we need an assumption on the kind of equilibrium that emerges from this process. The minimal number of ingredients which are needed are (a) a method to estimate/predict production and attraction time series; (b) a method to compute the N shortest paths from each OD zone to the next; and (c) two—possibly OD-specific—assumptions on the magnitude of N; and on the proportionality of path flows between these origins and destinations, respectively. The latter constitutes the most important behavioral assumption in our method, which relates to how we assume travelers have chosen their routes between OD pairs. We choose a proportionality factor that is inversely proportional to realized travel time, where we incorporate a penalty for path overlap. For large networks, these ingredients may be insufficient to solve the resulting system of equations. We show how additional constraints can be derived directly from the data by using principal component analysis, with which we exploit the fact that temporal patterns of production and attraction are similar across the network. Experimental results on a toy network and a large city network (Santander, Spain) show that our OD estimation method works satisfactorily, given a reasonable choice of N, and the use of so-called 3D supply patterns, which provide a compact representation of the supply dynamics over the entire network. Inclusion of topological information makes the method scalable both in terms of network size and for different topologies. Although we use a neural network to predict production and attraction in our experiments (which implies ground-truth OD data were needed), there are straight-forward paths to improve the method using additional data, such as demographic data, household survey data, social media and or movement traces, which could support estimating such ground-truth baseline production and attraction patterns. The proposed framework would fit very nicely in an online traffic modeling and control framework, and we see many paths to further refine and improve the method.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
Self-archiving dermatology articles
No full textDiscusses the merits of depositing medical journal articles in open repositories
Dynamic OD demand estimation and prediction for dynamic traffic management
No full textDynamic origin-destination (OD) demand is important input to many simulation models applied within dynamic traffic management systems (DTMS) for predicting traffic states on the network. The inability to provide high-quality dynamic OD demand estimates makes prediction with simulation models simply impossible, irrespective of how well these models have been calibrated. This thesis presents methods regarding the provision of efficient and reliable dynamic OD demand information for DTMS applications.Transport & PlanningCivil Engineering and Geoscience
Development of sign language for young children
No full textPlan AThe Child and Family Study Center (CFSC) serves as a laboratory school and observation site for Early Childhood Education Majors and other related majors on campus. The center experience allows University students to link educational theory with practice and therefore must set the example for developmentally appropriate practices by modeling best practices. CFSC programs benefit teachers, parents, university students and children ages 6 months to 35 months. Our nation depends on child care programs to care for their children. Programs vary in their content, but one of the aspects that is common to all is developing language and a form of communication. The problem is the lack of training for teachers and parents to help children communicate. All early childhood teachers have a tremendous responsibility to understand the wants and needs of the children; which will help the children succeed in the program. Using sign language, you can take advantage of children's natural abilities to communicate sooner. The level of frustration that children feel diminishes significantly when a child can tell you what he or she wants. Tantrums are often caused by a toddler's inability to communicate needs or wants. Using sign language, you can communicate with children as early as 6 months and reduce the number of tantrums you encounter. The objective of this project is to provide quality sign language training experiences for teachers and parents. The goal is to better prepare teachers and parents to communicate with their children at a young age. Objective 1: Provide teacher training that focuses on sign language skills and how to effectively teach young children to use sign language. Objective 2: Provide parent seminars that focus on sign language skills and how to use those skills at home with their children. Objective 3: To update and create classroom materials that provides an ideal learning environment for sign language. The project outcomes are to enhance the skills of teachers and parents of the CFSC. Teachers and parents that have sign language training and the tools to use will be able to promote student learning and development. Identifying and implementing best practices for teaching and learning sign language is the strategy that will be used. During the granting year, Lindsay Barnhart, CFSC Instructional Specialist, will coordinate teacher and parent training seminars with a sign language expert, and update curriculum and classroom materials that will foster sign language development for young children. This project represents a cost effective approach, with a budget request of $5,853.08, to prepare current and future teachers and parents of young children. Updated classroom materials will promote sign language in the classrooms. Curriculum enhancements will be adapted to center policies and goals. A study over five years will be done on what teachers, parents and the children have learned. No additional funding will be necessary to complete this project
Exploring the effects od a rigid body on the evolution of the Rayleigh-Taylor instability
No full textThis talk discusses the effects of a rigid solid boundary impeding the evolution of the Rayleigh-Taylor (RT) instability. The introduction of an obstacle completely alters the evolution of RT growth, instead of mixing the domain rapidly, a quasi-steady flow, rich in dynamics is established for long periods of time. Using a combination of low Atwood number experiments and ILES simulations, this talk will present a non-dimensional analytical model for a multi-stage mixing process, discussing the effects of the opening size and topology on the density change of each layer, buoyancy driven flux through the opening and mixing efficiency
Solving Multi-Agent Pathfinding with Matching using A*+ID+OD
No full textThis paper extends the Multi-Agent Pathfinding (MAPF) algorithm, A*+ID+OD, to be able to solve problems with matching. This extension still keeps the optimal and completeness properties of the original algorithm. Matching is added to the algorithm in both an exhaustive and heuristic manner. Exhaustive matching is further improved by adding a new layer of Independence Detection (ID) to reduce the number of matchings. Besides this, the pruning efficiency is increased by sorting the matchings based on the initial heuristic. The exhaustive matching method has been found to perform better than the heuristic matching method. The exhaustive version of A*+ID+OD is finally compared to other extended MAPF algorithms which shows that on small maps, Conflict Based Min-Cost Flow (CBM) performs best as it is the only algorithm that does not use exhaustive matching. A*+ID+OD and Enhanced Partial Expansion A* (EPEA*) also perform well on open maps with multiple teams when compared to other exhaustive matching algorithms due to the addition of matching ID.CSE3000 Research ProjectComputer Science and Engineerin
A dynamic OD prediction approach for urban networks based on automatic number plate recognition data
No full textOD flows provide important information for traffic management and planning. The prediction of dynamic OD matrices gives the possibility to apply anticipatory traffic management measures. In this paper, we propose an OD prediction approach based on the data obtained by Automated Number Plate Recognition (ANPR) cameras. The principal component analysis (PCA) is applied to reduce the dimension of the original OD matrices and to separate the main structure patterns from the noisier components. A state-space model is established for the main structure patterns and the structure deviations, and is incorporated in the Kalman filter framework to make predictions. We further propose three K-Nearest Neighbour (K-NN) based long-term pattern recognition approaches. The proposed approaches are validated with field ANPR data from Changsha city, P.R. China. The results show that the observed OD flows can be accurately predicted by our proposed approaches. Which prediction method performs best depends on the quality of the available data: for regular, periodic OD matrices the Kalman filter is better, for irregular OD matrices the pattern recognition that looks at different time periods in the historical data, gives better results.Transport and Plannin
Methodology for efficient real time OD demand estimation on large scale networks
No full textIn previous work, we have explored the idea of dimensionality reduction and approximation of OD demand based on principal component analysis (PCA). In particular, we have shown how we can apply PCA to linearly transform the high dimensional OD matrices into the lower dimensional space without significant loss of accuracy. Next, we have defined a new transformed set of variables (demand principal components) that is used to represent the OD demand in lower dimensional space. These new variables are defined as state variable in a novel reduced state space model for real time estimation of OD demand. In this paper, we review previous work and continue this line of research. Based on the previous results, we demonstrate the quality improvement of OD estimates using this new formulation and a so-called, ’colored’ Kalman filter approach for OD estimation, in which correlated observation noise is accounted. Moreover, we provide a thorough analysis of the model performance and computational efficiency using real data from a large network, and method for obtaining a reduced set of state variables.Transport and PlanningCivil Engineering and Geoscience
Histochemical examination on principal collagen fibers in periodontal ligaments of ascorbic acid-deficient ODS-od/od rats
No full textIn this study, we aimed to clarify the role of ascorbic acid in collagen synthesis in periodontal ligaments using osteogenic disorder Shionogi (ODS)/ShiJcl-od/od rats lacking L-gulonolactone oxidase. These rats cannot synthesize ascorbic acid in vivo. Eight-week-old ODS/ShiJcl-od/od male rats were administered ascorbic acid solution at a concentration of 200 mg/dL (control group, n = 6) or ascorbic acid solution at concentration of 0.3 mg/dL (insufficient group, n = 12). Six rats of the insufficient group were then given with ascorbic acid solution at concentration of 200 mg/dL for additional 3 weeks (rescued group, n = 6), and then, their mandibles were histochemically examined. Consequently, the insufficient group specimens were seen to possess fewer collagen fibers, and silver impregnation revealed numerous fine, reticular fiber-like fibrils branching off from collagen in the periodontal ligaments. In control group, faint immunoreactivities for matrix metalloproteinase (MMP)2 and cathepsin H were seen in the periphery of blood vessels and throughout the ligament, respectively. In contrast, in the insufficient group, intense MMP2-immunoreactivity was observed to be associated with collagen fibrils in the periodontal ligaments, and cathepsin H-immunopositivity was seen in ligamentous cells. The rescued group showed abundant collagen fibers filling the periodontal ligament space. Under transmission electron microscopy, ligamentous fibroblasts incorporated collagen fibrils into tubular endosomes/lysosomes while simultaneously synthesizing collagen fibril bundles. Thus, ascorbic acid insufficiency affected the immunolocalization of cathepsin H and MMP2; however, ligamentous fibroblasts appear to possess the potential to synthesize collagen fibers when supplied with ascorbic acid
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