Self-Evaluation Model Management Inclusive Education in Primary School District Bantul YOGYAKARTA

The research aims to find out the Self-Evaluation Model Management Inclusive Education in Elementary School Bantul Yogyakarta. Variables that will be revealed include: institutional, learning curriculum and evaluation, workforce, student affairs, infrastructure, and financing. Subjects were teachers, principals and committee inclusive education in primary school Bantul district. The total population was all Inclusive Elementary Schools located in Bantul district consisting both public and private elementary Inclusive schools.Type of evaluation research was the survey held in April-October 2013. The technique of collecting data included questionnaires: interview, observation, and documentation. Data analysis technique used integrated or simultaneous quantitative and qualitative descriptive approach.The results of the study revealed clearly and operational condition of the success of inclusive elementary schools, indicated by: (1) institutional, (2) curriculum, (3) staffing, (4) student, (5) infrastructure, and (6) financing, implementation and management success Inclusive Elementary School Principal in Bantul Yogyakarta

Model evaluation of target product profiles of an infant vaccine against respiratory syncytial virus (RSV) in a developed country setting

Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract disease in children worldwide and is a significant cause of hospital admissions in young children in England. No RSV vaccine has been licensed but a number are under development. In this work, we present two structurally distinct mathematical models, parameterized using RSV data from the UK, which have been used to explore the effect of introducing an RSV paediatric vaccine to the National programme. We have explored different vaccine properties, and dosing regimens combined with a range of implementation strategies for RSV control. The results suggest that vaccine properties that confer indirect protection have the greatest effect in reducing the burden of disease in children under 5 years. The findings are reinforced by the concurrence of predictions from the two models with very different epidemiological structure. The approach described has general application in evaluating vaccine target product profiles

Dropout Model Evaluation in MOOCs

The field of learning analytics needs to adopt a more rigorous approach for predictive model evaluation that matches the complex practice of model-building. In this work, we present a procedure to statistically test hypotheses about model performance which goes beyond the state-of-the-practice in the community to analyze both algorithms and feature extraction methods from raw data. We apply this method to a series of algorithms and feature sets derived from a large sample of Massive Open Online Courses (MOOCs). While a complete comparison of all potential modeling approaches is beyond the scope of this paper, we show that this approach reveals a large gap in dropout prediction performance between forum-, assignment-, and clickstream-based feature extraction methods, where the latter is significantly better than the former two, which are in turn indistinguishable from one another. This work has methodological implications for evaluating predictive or AI-based models of student success, and practical implications for the design and targeting of at-risk student models and interventions

Evaluation of the NDICEA model

Within the N-Toolbox project the NDICEA nitrogen model, one of the key tools in the virtual Toolbox, has been improved and tested in England, Denmark and Spain. The model performance was evaluated on datasets from these three countries by means of visual observation, RMSE and RSR from the soil nitrogen dynamics. In England the scenarios with organic fertilizer performed better than those with artificial fertilizer, leading to the suggestion that the calculated nitrogen release out of fertilizer could be improved. Timing of the soil sampling on soil inorganic nitrogen is important to realize a good model evaluation; two samples only, before sowing and after harvest, is not enough. When soil mineral nitrogen samples were taken during crop growth, model calculation and measured values showed sometimes big differences. It is suggested to improve the plant nitrogen uptake sub-model. In the Danish dataset the soil mineral N of the topsoil was well described, but that of the subsoil was not. This might be caused by the depth of the subsoil, which was up to 2.5 meters. The model performance could be improved by introducing a multi-layer soil sub-model instead of the actual two-layer soil sub-model. Spain, with its different climatic and soil conditions, needed an adaptation of the evapotranspiration calculation and a calibration of the scenarios to reach an acceptable model performance. If more Spanish datasets were studied, the NDICEA model could be enriched with standard Spanish soils and evapotranspiration data. For the improvement of the model, equations from the EU-ROTATE_N model are used to describe root growth and nitrogen uptake in more detail

VPPA weld model evaluation

NASA uses the Variable Polarity Plasma Arc Welding (VPPAW) process extensively for fabrication of Space Shuttle External Tanks. This welding process has been in use at NASA since the late 1970's but the physics of the process have never been satisfactorily modeled and understood. In an attempt to advance the level of understanding of VPPAW, Dr. Arthur C. Nunes, Jr., (NASA) has developed a mathematical model of the process. The work described in this report evaluated and used two versions (level-0 and level-1) of Dr. Nunes' model, and a model derived by the University of Alabama at Huntsville (UAH) from Dr. Nunes' level-1 model. Two series of VPPAW experiments were done, using over 400 different combinations of welding parameters. Observations were made of VPPAW process behavior as a function of specific welding parameter changes. Data from these weld experiments was used to evaluate and suggest improvements to Dr. Nunes' model. Experimental data and correlations with the model were used to develop a multi-variable control algorithm for use with a future VPPAW controller. This algorithm is designed to control weld widths (both on the crown and root of the weld) based upon the weld parameters, base metal properties, and real-time observation of the crown width. The algorithm exhibited accuracy comparable to that of the weld width measurements for both aluminum and mild steel welds

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

Evaluation Criteria for Object-oriented Metrics

In this paper an evaluation model for object-oriented (OO) metrics is proposed. We have evaluated the existing evaluation criteria for OO metrics, and based on the observations, a model is proposed which tries to cover most of the features for the evaluation of OO metrics. The model is validated by applying it to existing OO metrics. In contrast to the other existing criteria, the proposed model is simple in implementation and includes the practical and important aspects of evaluation; hence it suitable to evaluate and validate any OO complexity metric