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An infrared thermal imaging system was assessed for its capability to identify eight western Canadian wheat classes. Twenty-gram wheat samples at 14% moisture content (wet basis) were spread in a 100 × 100 mm monolayer and heated by a plate heater (maintained at 90°C) placed at a distance of 10 mm from the grain layer. The surface temperatures of the top surface of the grain bulk were imaged before heating, after heating for 180 s, and after cooling for 30 s using a thermal camera (n = 100 samples in each class). Temperature rise (after heating) and drop (after cooling) were significantly different for wheat classes (a = 0.05). Wheat samples were classified with twelve derived thermal features using statistical classifiers. Overall classification accuracies of an eight-class model, red class model (four classes), white class model (four classes), and pairwise comparison (two-class model) using a quadratic discriminant method were 76%, 87%, 79%, and 95%, respectively. The thermal imaging approach may have potential to develop class identification methods in wheat handling facilities. However, further investigations are required to determine the performance of this system for wheat samples mixed with defects, with different moisture contents, and grown in different locations and years.

Parental support for educational innovation has been described as essential in school change. This study examines parent and caregiver perceptions of educational opportunities for students with severe disabilities. Parents and caregivers from two high schools were interviewed. One high school uses an inclusive service delivery model, while the other uses a special day class model with limited mainstreaming. The data suggest that interviewees support inclusive schools and believe that their children are acquiring new skills. Questions remain regarding the balance of community-based Instruction and the amount of teacher training provided.

In an effort to improve the overall safety of the current and future air transportation system, researchers have been investigating the causes and series of events that can potentially lead to aircraft loss of control (LoC) as well as methods to prevent the occurrence of such events. Motivated by this challenging problem, this paper presents preliminary work on the development of technologies for in-flight LoC prediction and prevention. The developed scheme is based on a quantitative approach for LoC characterization introduced by the Boeing Company and NASA Langley Research Center, and is designed to arrest the development of an LoC sequence through an integrated LoC prediction and prevention control system. The paper also presents initial piloted simulations that analyze the ability of the developed system to assist the pilot in flying the aircraft through adverse environmental conditions, and to preserve safe aircraft operation by preventing erroneous crew input that could potentially lead to an LoC situation.

Motivated by the problem of loss-of-control prevention, this paper presents a dynamic flight envelope protection system for NASA’s Transport Class Model. The developed protection scheme is based on a command-limiting approach that accounts for aircraft adverse aerodynamics, unusual attitude, and structural integrity, and is implemented around a standard gain-scheduled flight control law. The scheme also includes an energy protection scheme, which relies on an automatic throttle control system that implements a total energy control law. Preliminary batch and pilot-in-the-loop simulations demonstrate the efficacy of the protection system in maintaining the aircraft within desired safe conditions, without limiting the ability of the pilot to perform aggressive, evasive maneuvers.

In this chapter, you are going to learn how to integrate your Spring application, My Documents, with external or existing systems. Let’s imagine for a moment that you have two friends. The first friend wants to send you some document information: the same Document class model that you have in XML format. But this friend only knows JMS (Java Message Service). The second friend wants to only receive document information in XML format as well, but this friend only knows AMQP (Advance Message Queue Protocol).

Much has been made of recent news that the field of heat transfer has fewer teaching professors now than in years past. It remains a challenging field for many college students who then tend to go into other engineering applications. But this trend can be reversed by utilizing modern educational tools in a flipped class model that takes advantage of and optimizes both online delivery in concert with classroom activities. Specifically, the flipped classroom model allows for the use of graphical visualization of heat transfer (a phenomena that for the most part is outside our visual spectrum) in an online format and active learning exercises that engage students in the classroom. This paper will explain how both sides of this educational equation may be the optimal method for heat transfer content delivery.

This paper proposes LTE radio scheduler analytical models. The motivation behind the models is to evaluate the performance of the complex LTE system analytically, rather than using simulations or real life experiments (which are not always possible to perform) that are too exhaustive and consumes large computation power and time. The models are developed to approximate the system behavior mathematically; it enhances the performance evaluation's processing effort and time significantly compared to traditional simulations. The proposed analytical models are based on the Continuous Time Markov Chain (CTMC) and represent different LTE Time Domain Schedulers (TDS) as well as two different model categories: a single class model and a two class model. In the single class model only a single traffic class is considered with no QoS differentiation. Whereas, the two classes model supports QoS differentiation between the two classes. An extensive analysis have been performed using the aforementioned analytical models and is compared with a well developed simulation model.

National audience; Lors de la conception des modèles de classes pour les systèmes d'information, les bases de données et la programmation, les experts du domaine et les concepteurs collaborent pour identifier les concepts du domaine. L'Analyse Formelle de Concepts et l'Analyse Relationnelle de Concepts permettent de mettre en évidence des concepts de domaine et des relations de plus haut niveau d'abstraction, tout en factorisant des descriptions et des comportements. Le risque de ces deux méthodes est de submerger le concepteur avec une quantité de concepts trop importante pour être analysée. Dans cet exposé, nous étudions de manière systématique une application pratique de RCA sur plusieurs versions du modèle de classes d'un système d'information réel dans le domaine de l'environnement, de manière à donner des chiffres précis sur le comportement de RCA et d'identifier quelles configurations sont réalistes.

International audience; During the design of class models for information systems, databases or programming, experts of the domain and designers discuss to identify and agree on the domain concepts. Formal Concept Analysis (FCA) and Relational Concept Analysis (RCA) have been proposed, for fostering the emergence of higher level domain concepts and relations, while factorizing descriptions and behaviors. The risk of these methods is overwhelming the designer with too many concepts to be analyzed. In this paper, we systematically study a practical application of RCA on several versions of a real class model for an information system in order to give precise figures about RCA and to identify which configurations are tractable.

OntoUML is a promising method for ontological modelling. In this paper, we discuss its possible use for software engineering. We propose a method of transformation of an ontological model into a software-engineering object-oriented class model in UML and its instantiation. Our approach is based on the following best practices: pure object-oriented paradigm and approach of dividing state and identity as introduced in the Clojure programming language.

This paper discusses the relevant information for product assembly model, and built aircraft assembly model based on object-oriented modeling method. Via constructing aircraft general structure object model, paper evolves class model to object model. Paper takes a specific model fighter wing-body docking structure for example, illustrating the structure of assembly and modelling method, the object model of docking structure is builted and eventually applied to the development of a particular model fighter digital assembly management system.

Slicing is a reduction technique that has been applied to class models to support model comprehension, analysis, and other modeling activities. In particular, slicing techniques can be used to produce class model fragments that include only those elements needed to analyze semantic properties of interest. In this paper we describe a class model slicing approach that takes into consideration invariants and operation contracts expressed in the Object Constraint Language OCL. The approach is used to produce model fragments, each of which consists of only the model elements needed to analyze specified properties. We use the slicing approach to support a technique for analyzing sequences of operation invocations to uncover invariant violations. The slicing technique is used to produce model fragments that can be analyzed separately. The preliminary evaluation we performed provides evidence that the proposed slicing technique can significantly reduce the time to perform the analysis.

The research literature points to health behaviour being multidimensional but is not consistent regarding the number or nature of dimensions. In this study, health behaviour data was subjected to latent class analysis, which is appropriate when underlying types rather than continua of health behaviour are hypothesized. Questionnaire data on various eating behaviours and on exercising, drinking alcohol, and smoking were obtained from 109 adult subjects. Each behaviour was dichotomized, the split being at the point which best corresponded to contemporary public health advice. Latent class analysis of the eating behaviours was consistent with a two class model of eating: healthy vs more mixed eating. Thereby, a single eating behaviour variable was created. Latent class analysis of this eating behaviour along with the exercising, alcohol, and smoking behaviours was modestly consistent with a two-type model of health behaviour: healthy behaviour vs more mixed behaviour. Latent class analysis may be an appropriate technique to apply to health behaviour data if there is reason to believe that the latent variables are categorical rather than continuous.

This paper reconsiders the two/one-class model of economic growth, attributable to Kaldor, Pasinetta, Meade, Samuelson, Modigliani, and Sato, under the assumptions that part of corporate profits may not be distributed as dividends. Using results of M. Baranzini (1991), the distribution of property between the workers and capitalists is related to the rates of return on capital. Implications of a positive retention ratio are briefly considered. Copyright 1995 by Royal Economic Society.

We propose function for candidate discrimination, i.e., suspect ordering during model-based diagnosis. Function offers advantages over structure and fault probabilities currently being used for candidate discrimination. It is readily available from device design, unlike fault probabilities, which are hard to obtain. Function-based discrimination is not dependent on the topology of the device, unlike structure-based discrimination. We propose classes as a scheme for representation of function. As part of classes, we define a set of function primitives and provide a framework for identifying the functions of components and subsystems of a device. The representation scheme is domain independent. We propose a function-based technique for candidate discrimination called the default order technique, and outline a diagnosis algorithm that applies the technique to the class model of a device. Function-based diagnosis is in addition to and as a supplement for model-based diagnosis based on behavior and structure. ...

Understanding the difference between two models, such as different versions of a design, can be difficult. It is a commonly held belief that the best way of presenting a model difference is by using graph or tree-based visualizations. We disagree and present an alternative approach where sets of low-level model differences are abstracted into high-level model differences that lend themselves to being presented textually. The results of preliminary user studies support our claim.

This paper develops a rapid analysis method for adulteration identification of a popular traditional Chinese food, lotus root powder (LRP), by near-infrared spectroscopy and chemometrics. 85 pure LRP samples were collected from 7 main lotus producing areas of China to include most if not all of the significant variations likely to be encountered in unknown authentic materials. To evaluate the model specificity, 80 adulterated LRP samples prepared by blending pure LRP with different levels of four cheaper and commonly used starches were measured and predicted. For multivariate quality models, two class modeling methods, the traditional soft independent modeling of class analogy (SIMCA) and a recently proposed partial least squares class model (PLSCM) were used. Different data preprocessing techniques, including smoothing, taking derivative and standard normal variate (SNV) transformation were used to improve the classification performance. The results indicate that smoothing, taking second-order derivatives and SNV can improve the class models by enhancing signal-to-noise ratio, reducing baseline and background shifts. The most accurate and stable models were obtained with SNV spectra for both SIMCA (sensitivity 0.909 and specificity 0.938) and PLSCM (sensitivity 0.909 and specificity 0.925). Moreover, both SIMCA and PLSCM could detect LRP samples mixed with 5% (w/w) or more other cheaper starches, including cassava, sweet potato, potato and maize starches. Although it is difficult to perform an exhaustive collection of all pure LRP samples and possible adulterations, NIR spectrometry combined with class modeling techniques provides a reliable and effective method to detect most of the current LRP adulterations in Chinese market.

This study is porposed to : (1) encompass and identify the students od elementary school who are expected to have spesific learning difficulty because of Brain Minimal Disfunction, (2) understand of the teacher action model and its intervention effect toward the increasing of children learning performance. The research was done in Gamping, Sleman in year 2000. Stage 1 : 10 of 40 elementary school in Gamping, Sleman were chosen. Stage 2 : Student of second and third grade were selected as research subject. The methods of data collection are observation, interview, and demostration. The research is done by research team and the class teacher. The result of this study?é?á and the conclusion show that from 523 students of the second and third grade of 10 elementary scoool, 45 students (8,60%) have mathematic spesific learning difficulties, 36 students (6,88%) have writing difficulties. A class teacher gives remedial teaching and special guide will help students to over-come learning difficulties with special class model, source room model and regular class model. Keyword : Treatment of children with specific learning difficulty

One interesting problem in data integration is, when users submit a query in one domain, he may also want to know more information in other domains which haven't come up to his or her mind yet. It's a great idea to recommend correlated domains to users so that they could get more information. However, the existing researches in solving this problem are quite rare and limited. In this paper, we propose a method of selecting query paths, and the query paths consist of correlated domains. We propose an entity class model which is based to construct a domain correlation graph, and query paths are picked based on the graph. At last we evaluate our method by experiments and demonstrate the effectiveness of our method.

This paper discusses several features of parametrized classes, such as categories of its parameters, operations allowed and modes of instanciation. It also discusses the difficulties in describing the semantics of a class when it is used as a parameter for a parametrized class. The paper proposes a model unifying all parametrized class features discussed and presents suggestions for enhancing the use of these classes.

An electronic nose (e-nose), in combination with chemometrics, has been used to classify the cultivar, harvest year, and geographical origin of economically important Turkish extra virgin olive oils. The aroma fingerprints of the eight different olive oil samples [Memecik (M), Erkence (E), Gemlik (G), Ayvalik (A), Domat (D), Nizip (N), Gemlik-Edremit (GE), Ayvalik-Edremit (AE)] were obtained using an e-nose consisting a surface acoustic wave detector. Data were analyzed by principal component analysis (PCA) and discriminant function analysis (DFA). Classification of cultivars using PCA revealed that A class model was correctly discriminated from N in two harvest years. The DFA classified 100 and 97% of the samples correctly according to the cultivar in the 1st and 2nd harvest years, respectively. Successful separation among the harvest years and geographical origins were obtained. Sensory analyses were performed for determining the differences in the geographical origin of the olive oils and the preferences of the panelists. The panelists could not detect the differences among olive oils from two different regions. The cultivar, harvest year, and geographical origin of extra virgin olive oils could be discriminated successfully by the e-nose., Scientific and Technical Research Council of Turkey (104O333)

The ability to identify neuronal damage in the dendritic arbor during HIV-1-associated dementia (HAD) is crucial for designing specific therapies for the treatment of HAD. In this chapter, we utilized a computer based image analysis method to quantitatively assess HIV-1 viral protein gp120 and glutamate mediated individual neuronal damage in cultured cortical neurons. Changes in the number of neurites, arbors, branch nodes, cell body area, and average arbor lengths were determined and a database was formed. We further proposed a two class model of MCLP to classify such HIV-1mediated neuronal dendritic and synaptic damages. Given certain classes, including treatments with brain-derived neurotrophic factor (BDNF), glutamate, gp120 or non-treatment controls from our in vitro experimental systems, we used the two-class MCLP model to determine the data patterns between classes in order to gain insight about neuronal dendritic damages. This knowledge can be applied in principle to the design and study of specific therapies for the prevention or reversal of neuronal damage associated with HAD. Finally, the MCLP method was compared with a well-known artificial neural network algorithm to test for the relative potential of different data mining applications in HAD research.

We introduce NST, an expressive and extensible unit testing framework for Common Lisp. Distinct features of Lisp's object system CLOS allow an elegant implementation for NST, and we describe this class model and implementation. There are over a dozen test frameworks for Lisp which are currently available, almost half of which are under active maintenance, and we compare these packages features. Development of NST is ongoing, and we conclude with a discussion of future directions for the system.

Compared with other large-scale warfare simulation systems, wargame, as a traditional type of warfare simulation, has the advantages of low cost, convenience, practicability, etc. This paper discusses the system structure and class model based on “Future: Korea War” which is a product of U.S. “One Small Step” company's Millennium Wars series strategic-level wargames, and designs wargame umpire rule description method based on CLIPS. The “Future: Korea War” system umpire rules could be revised without recompilation of the application software, which enhances the flexibility and expansibility of the wargame umpire rules.

The paper describes a new approach for disjoint hard modelling of classes. This involves developing independent PC models for each group in the class, and calculating both the Q statistic (square prediction error) for each sample to the class model and a separate statistic about how well samples are classified within the projected PC space. The latter statistic can be applied to different types of classifiers, in this paper we choose to illustrate by Quadratic Discriminant Analysis (D statistic) and one class Support Vector Domain Description (SVDD) (f-value). The two measures (Q and the classifier dependent statistic) are combined into a joint decision function which uniquely classifies each sample. The disjoint hard models are contrasted to conjoint models where PCA is performed on the entire dataset using both QDA and Support Vector Machines (SVMs) classifiers. The optimum number of PCs for each model is determined using the bootstrap, and model performance assessed on 100 test sets obtained using different iterative splits, using %PA (Predictive Ability) and %CR (Classification Rate). The method is illustrated using a dataset consisting of 293 samples from nine groups of polymers obtained using thermal profiling. The approach described, in this paper, has many of the advantages of one class disjoint models (e.g. SIMCA) and of conventional hard models, and is useful if it is known that all samples must belong to one of a series of known groups but each group has a very different structure. Copyright © 2010 John Wiley & Sons, Ltd.

When applying model checking to the design models of the embedded systems, it is necessary to model not only the behavior of the target system but also that of the environment interacting with the system. In this paper, we present a method to model the environment and to automatically generate all possible environments from the model. In our method, we can flexibly model the structural variation of the environment and the sequences of the function calls using a class model and statechart models. We also present a tool to generate Promela scripts of SPIN from the environment model. As a practical experiment, we applied our tool to the verification of an OSEK/VDX RTOS design model.

Programinės įrangos kūrimo procese reikalavimų rinkimo ir jų analizės etapai yra patys svarbiausi, nuo jų priklauso tolesnių programinės įrangos kūrimo etapų įgyvendinimas. Informacinių sistemų specifikavimui dažniausiai naudojamos projektavimo kalbos (UML, Z, DFD, OCL ir t.t.), kurių supratimui reikalingos specifinės žinios. Užsakovo projektavimo kalbos žinios dažnai yra minimalios, tad jis pasitiki projektuotojo žiniomis ir pateiktų reikalavimų interpretavimu. Projektavimo etape tinkamai užsakovo nesuprastų, formalia kalba specifikuotų, sistemos projektinių modelių netikslumai, dažnai išryškėja tik realizavimo etape. Klaidingai IT specialisto interpretuotų žinių padarinių taisymas yra brangus ir pailgina programinio produkto kūrimo trukmę. Šiam nesusišnekimui išvengti buvo pasiūlyta dalykinę sritį aprašinėti veiklos taisyklėmis natūralios kalbos šablonais. Veiklos taisyklės yra struktūrizuotos ir vienareikšmiškai interpretuojamos tiek IT specialistų, tiek verslo atstovų. Šis dalykinės srities aprašymo metodas yra labai neseniai pasirodęs ir dar nėra nusistovėjusių standartų jo taikyme. Šiame darbe bus kuriamas algoritmas, kuris veiklos taisyklių pagrindu patikslins nuo skaičiavimų nepriklausomo (arba nuo platformos nepriklausomo) lygmens duomenų modelius. Tuo savo ruoštu paspartindamas projektinių modelių kūrimą ir patikslinimą automatizuojant veiklos taisyklių ir klasių modelio analizę. Software development process of the collection and analysis phases are the key, since they belong to the software development phases of implementation. Information systems are the most used in the design specification language (UML, Z, DFD, OCL, etc.), understanding the need for specific knowledge. Customer's design language is often minimal, so he is confident in the knowledge the designer and the requirements of the interpretation. The design phase of the customer due misunderstood formally specified language, system design models, inaccuracies, often become apparent only in the realization phase. Erroneous interpretation of the IT professional knowledge effects editing is expensive and prolonged the duration of software product development. This misunderstood was proposed to avoid the subject area specificate operational rules of natural-language ralios pattern. Activities are structured and unambiguous interpretation of the IT professionals and business representatives. The Subject field of the description method is a very recent and has not established standards for its application. This work will be developed in the algorithm, the business rules-based adjustments to the calculations of independent (or platform-independent) level of data models. Meanwhile, prepare their own models for accelerating the development of design automation and to verify rules and model of class analysis.

Natural oils possess a characteristic and more or less unique pattern of fatty acids and triacylglycerols. These patterns can be used in several manners, as a means of identification, for batch-consistency testing (e. g. for the pharmaceutical and cosmetic industry), detection of adulteration and also possibly as a basis for a chemotaxonomy, revealing relationships between species. The fatty acid composition, determined by GC/MS of the methyl esters and the triacylglycerol pattern analysed by reversed phase high performance liquid chromatography, were utilized in multivariate-statistical analysis to ‘map’ and classify different oils. A class model was developed for each of the different sources of oil, constituting an objective and quantitative means of identification, through nearness in the multi-dimensional measurement space. Eine multivariable Identifizierung von naturlichen Triacylglycerin-Olen Naturliche Fette und Ole besitzen ein charakteristisches und ein mehr oder weniger einzigartiges Muster der Zusammensetzung der Fettsauren bzw. der Triacylglycerine. Diese Muster konnen in verschiedener Weise verwendet werden, so z.B. als Mittel zur Identifizierung, zur Prufung der Bestandigkeit von Chargen (zB. in der Arzneimittelindustrie und in der kosmetischen Industrie), zum Aufdecken von Verfalschungen, aber auch moglicherweise als Basis fur eine Chemotaxonomie, d.h. zur Ermittlung eventueller Beziehungen zwischen Spezies. Die Fettsaurezusammensetzung (bestimmt durch GC/MC der Methylester) und das Triacylglycerinmuster (durch Umkehrphasenanalyse der HPLC bestimmt) wurden bei der multivariabel-statistischen Analyse zur Kennzeichnung und Klassifizierung verschiedener Ole wurde entwickelt. Das Modell stellt eine objektive und quantitative Art der Identifizierung durch die No;he im multidimensionalen Mesraum dar.

Static analysis tools, such as OCLE and USE, can be used to analyze structural properties of class models. The USE tool also provides support for analyzing specified operations through interactive simulations in which users provide operation parameters, and manually assign values to state elements to reflect the effect of an operation. In this paper we describe an approach to statically analyzing behavior that does not require a user to manually simulate behavior. The approach involves transforming a class model into a static model of behavior, called a Snapshot Model. A Snapshot Model characterizes sequences of snapshots, where a snapshot describes an application state. A scenario describing a sequence of operation invocations can be verified against a Snapshot Model using tools such as USE and OCLE. We illustrate our approach by verifying a scenario against a Snapshot Model that describes the behavior of some operations in a role-based access control (RBAC) application.

In one-class classification we seek a rule to find a coherent subset of instances similar to a few positive examples in a large pool of instances. The problem can be formulated and analyzed naturally in a rate-distortion framework, leading to an efficient algorithm that compares well with two previous one-class methods. The model can be also be extended to remove background clutter in clustering to improve cluster purity.

New telecom services demand/traffic forecasting and planning tasks are often quite complicated and surrounded by uncertainty because of their structural complexity and lack of (sufficient) historical data. The contention of this paper is that these tasks can and should be performed in a more careful and structured manner using the subjective knowledge of experts/managers, structured scenario analysis, and that different sorts of imprecision/ uncertainty/risk associated with new telecom forecasting and planning can be discriminated, described in a structured way and quantified. Several new concepts in demand/traffic forecasting and planning have been introduced and appropriate computer tools developed. These tools are general enough to accept crisp and soft inputs (e.g. verbally expressed expert opinions) and allow formal problem specification, selection and analysis of alternatives, translation between different ways of expression and analysis of decision consequences.

Alternative models were examined for adjustments of herd, year and season effects for evaluation of dairy sires in Switzerland where average herd-year subclass size for first lactation records is less than 4. Herds are presently grouped into herd classes according to production level, and herd classyear-season is fitted as a fixed effect like herd-year-season in situations with large herds. Several models were compared fitting herd class vs. herd effect, accounting for the interaction with year and season as random or fixed effects. The empirical and predicted error variances of sire effects were estimated from 10 random subsets of the data of proven sires. The empirical and predicted error variances were consistently smaller with herd class models than with herd effect models. However the plots of sire effects showed that the herd class models overestimated poor sires and underestimated good sires. This bias was mainly because the herds with good management and poor sires were grouped in the same herd class as those with poor management and good sires. A herd class model with herd classification based on herd averages adjusted for genetic merit of sires showed no bias. A model with herds as fixed and herd-years as random effects was found to be a good alternative to a herd class model. Models accounting for herd-year × season interactions showed no advantage in the accuracy of evaluation.

Interest often focuses on estimating sensitivity and specificity of a group of raters or a set of new diagnostic tests in situations in which gold standard evaluation is expensive or invasive. Various authors have proposed semilatent class modeling approaches for estimating diagnostic accuracy in this situation. This article presents imputation approaches for this problem. I show how imputation provides a simpler way of performing diagnostic accuracy and prevalence estimation than the use of semilatent modeling. Furthermore, the imputation approach is more robust to modeling assumptions and, in general, there is only a moderate efficiency loss relative to a correctly specified semilatent class model. I apply imputation to a study designed to estimate the diagnostic accuracy of digital radiography for gastric cancer. The feasibility and robustness of imputation is illustrated with analysis, asymptotic results, and simulations.

The article considers the issue of constructing a class model based on positive pedagogy. The author defines the purpose of raising a positive human being and specifies the principles of positive pedagogy in relation to the learning process. The article also analyzes a number of researchers’ experience in the use of modelling in solving various didactics issues. The author suggests her own model of a class that meets the requirements of positive pedagogy. Specific features of the structured plan of the class are presented on the basis on technologies of positive pedagogy: positive motivation, learning, positive reflection and positive conclusion, summarizing the class. The writer suggests activities algorithms, methods and class stage techniques for teachers, argues that any class has to be characterized by its upbringing value, specifies the role of the class based on techniques of positive pedagogy in raising a positive human being in every student.

Purpose: This research aimed at exploring the background of the appearance of teaching games for understanding (TGfU) and change process, and investigating teacher"s experience of applying this class model to physical education. Methods: The researcher collected data through literature analysis and interview. Particularly, the material collected through interview was analyzed based on area analysis and distribution analysis, which were suggested by Spradley(1979). Results: First, TGfU appeared, which emphasized the importance of strategy and tactic, as the alternative of function-oriented teaching games model. Second, this research analyzed the development process of TGfU. In the development process, site compatibility was enhanced by being amended to the tactical approach model for teaching games and the modified frame of TGfU, suggested by Ahn, yang-ok(2002). Third, as the result of applying TGfU to the field, effective learning, active participation in class, increase of teacher"s interest and role, efficiency of class operation, and transformation to a model considering site compatibility, etc. were derived.

The performance of automatic speech summarisation has been improved in previous experiments by using linguistic model adaptation. We extend such adaptation to the use of class models, whose robustness further improves summarisation performance on a wider variety of objective evaluation metrics such as ROUGE-2 and ROUGE-SU4 used in the text summarisation literature. Summaries made from automatic speech recogniser transcriptions benefit from relative improvements ranging from 6.0% to 22.2% on all investigated metrics.

A class model of rational auction negotiation for multi-agent in which time is related. In a creative way, time parameter is introduced into the process of the rational negotiation in multi-agent system. Buyer agents are able to choose several bidding ways like time-dependent tactics, behavior-dependent tactics. As the result, agents can receive different utilities.

CQL++ is a declarative front end to the Ode object-oriented database. It combines a SQL-like syntax with the C++ class model. CQL++ provides facilities for defining classes, and for creating, querying, displaying, and updating objects. Classes and objects created using CQL++ can freely be intermixed with those created using O++, the primary programming language of Ode. CQL++ gives its users a relatively straightforward interface, by hiding from them such O++ details as object-ids, public and private members of objects, and the implementations (bodies) of member functions.

In this research, we present predictions of carbon sequestration by pines growing in reforested sites of Durango, Mexico. Four methodologies to predict carbon stocks in standing aboveground biomass were tested. Two models at the whole stand scale and two hybrid models between whole stand, stand class, and individual trees were fitted. A chronosequence of 23 small-scale reforested sites and stem analysis conducted on 60 trees were used to fit model parameters and estimate goodness of fit statistics. A stand class model produced a better fit to measure carbon stocks in aboveground standing biomass. 3 Reforested sites with native pine species are sequestering carbon at differential rates partially explained by density, species, micro site, climate and age of pines. Society is benefiting from the environmental services provided by carbon sequestration and conservation of native coniferous forests.

Detailed investigations of student reasoning show that students approach the topic of wave physics using both event-like and object-like descriptions of wavepulses, but primarily focus on object properties in their reasoning. Student responses to interview and written questions are analysed using diSessa and Sherin's coordination class model which suggests that student use of specific reasoning resources is guided by possibly unconscious cues. Here, the term reasoning resources is used in a general fashion to describe any of the smaller grain size models of reasoning (p-prims, facets of knowledge, intuitive rules, etc) rather than theoretically ambiguous (mis)conceptions. Student applications of reasoning resources, including one previously undocumented, are described. Though the coordination class model is extremely helpful in organising the research data, problematic aspects of the model are also discussed., 20 pages, 8 figures, 27 references

Single and multiple grain class model formulations for the erosion and deposition of clay and silt sized particles are compared to each other for a series of laboratory experiments and field data from a shallow lake where resuspension occurs from wind-waves. The approach for coupling between grain classes during settling and deposition is presented in Part I (this volume). Threshold shear stresses for mutually-exclusives erosion and deposition are used in the model formulation to be consistent with previous laboratory investigations. Model deposition and erosion laws treat silt and clay fractions differently, yet couple them during certain modes of vertical transport. Models with up to 7 grain classes are compared to laboratory flume tests which formed steady state suspension concentrations during deposition. Models with 1 and 4 grain classes are compared to field data. An automated, objective method is used to adjust coefficients for both model simulations. Comparisons indicate that the multiple grain class formulation improves erosion and deposition process descriptions.

Whilst research has indicated that the practitioner use of entity-relationship modelling is problematic, proponents of object oriented modelling suggest that their paradigm offers both a new approach and also more effective modelling. This paper examines some practitioner perceptions of one object oriented modelling technique in the context of previous work on entity-relationship modelling. The findings show that there are similar practitioner issues arising from common underlying techniques and that object oriented modelling is problematic when used with project clients. However, the suggestion is that object oriented practitioners are not gaining insight from practitioner experience from more than twenty years of entity-relationship modelling practice.

This paper describes recent progress in an 11-years project mainly for research and development on the applications of superconductive technologies to electric power apparatuses in Japan. The major targets of the project are to verify basic performances and reliability of superconducting generator (SCG) and also to establish technologies on design and manufacture of 200MW class pilot SCG, by developing and testing 70MW class model SCGs. Test run for verification tests of the first model SCG has started in May 1997.

A 500A class model of High Tc Superconductor current lead for 1MJ SMES system has been fabricated with the Bi-2223 tapes. In the SMES system, a time varying magnetic field is applied on the current leads through both energy storing and releasing processes, which causes an uneven current flow degrading the Jc of the leads. A spiral shaped winding was used for getting rid of the problem. Ag-Au alloy was used as a sheath material of superconducting tapes for reducing heat leakage through the leads. It is estimated to be less than 0.2W/kA for a lead.

The decay behavior of Li 2 SrSiO 4 :Eu 2+ , Li 2 CaSiO 4 :Eu 2+ , and Li 2 BaSiO 4 :Eu 2+ phosphors, which exhibit similar stoichiometries but different structures, differed significantly, even at the same activator concentration. Such differences in decay behavior cannot be elucidated by the traditional energy-transfer model based on homogeneous distribution of activators in the host. In this regard, we examined the decay curves of Li 2 SrSiO 4 :Eu 2+ , Li 2 CaSiO 4 :Eu 2+ , and Li 2 BaSiO 4 :Eu 2+ phosphors based on the angular class model. It was found that the decay behavior was closely related to the local structure around the activator, indicating that the higher the site symmetry the more active the concentration quenching.

We have structured an upper-level undergraduate course in organometallic chemistry on a selection of "classic" publications in the field. This approach offers students a richly contextual introduction to many of the fundamental tenets of the discipline. After a brief introduction to the field led by the faculty, the students themselves are responsible for researching and presenting selected papers to their classmates for analysis and discussion. Beyond mastery of basic organometallic principles, course goals for the students include improved proficiency in using the primary chemical literature and increased experience and confidence in researching, preparing, and delivering an informative oral presentation in individual and collaborative settings. Student performance is assessed based on performance on open-ended, take-home exams, quality of presentations, and contribution to in-class discussions. Student end-of-term survey responses indicate that this class model is successful as an introduction to organ...

In his nice paper (Mykhopadhyay, 1982) as well as in his significant monograph (Mykhopadhyay & Solanky, 1994) N. Mykhopadhyay considers the following application of STEIN's two-stage procedure: Suppose that (X 1,..., Xn ) T , n = 1, 2,..., is n-dimensional normal with mean vector µ = µ l and dispersion matrix Σ n =σ 2(ρij ) with ρij = 1, ρij = ρ *, i ≠ j = 1,..., n where (µ, Σ, ρ) ∈ ℝ × ℝ+ × (-1, 0); this is called the intra-class model. For given d > 0 and α ∈ (0, 1) one wants to construct a (sequential) confidence interval I for µ having width 2d and confidence coefficient at least (1 - α). It is claimed that where N is determined, according to Stein's two-stage procedure (Stein, 1945), as where m ⩾ 2 is the first stage sample size and denotes the sample variance, fulfills this aim.