The paper proposes a **general** **model** to obtain the **OWA** operator with **orness** as its control parameter. This **general** **model** includes the maximum entropy **OWA** operator and minimum variance **OWA** operator as spe- cial cases. Some properties of its solution are discussed. The solution equivalence to the minimax problem are proved, which is also a generalization of the solution equivalence for the minimum variance and minimax dis- parity problems. Then, these results are extended to the RIM quantiﬁer case, which corresponds to the **OWA** operator in continuous form. A **general** **model** to obtain the **parameterized** RIM quantiﬁers of **given** **orness** **level** is proposed, with the property discussions and the solution equivalence proof to the corresponding mini- max problem. With the analytical optimal solution expression of these two kinds problems, the relationship between the **OWA** operator vector elements or the shape of the RIM quantiﬁer membership function can be observed intuitively. We can not only use the **OWA** operator or RIM quantiﬁer to get **aggregation** results con- sistent to the preference information (**orness** **level**), but also can make the obtained optimal **OWA** operator or

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Then, the paper proposes the **orness** measures for two compound forms of the quasi-arithmetic mean: the quasi-**OWA** operator and the Bajraktarevic´ mean. With the generating function technique, some properties of these **orness** measures are discussed. Two kinds of **parameterized** quasi-**OWA** operators and Bajraktarevic´ means with exponential functions and power functions are proposed, respectively. The exponential function quasi-**OWA** operator and Bajraktarevic´ mean are sym- metrical for their parameters. They are shift invariant. One can easily get its complementary part with **given** **orness** **level**. The power function quasi-**OWA** operator can be seen as the extension of the generalized **OWA** operator, while the power func- tion Bajraktarevic´ mean can be seen as the extension of the commonly used power root means and the weighted function average method. They are ratio invariant. The relationships and some extensions on the **orness** expressions of these aggre- gation operators are also discussed.

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Getting **OWA** weights under **given** **orness** **level** is an active topic in the **OWA** operator research. The paper proposes a series of weights generating methods in equidiﬀerent forms. Similar to the geometric (maximum entropy) **OWA** operator, we propose a **parameterized** **OWA** operator called equidiﬀerent **OWA** operator, which consist the adjacent weighes with a common diﬀerence. The maximum spread equidiﬀerent **OWA** (MSEOWA) operator is equivalent to the minimum variance **OWA** operator, but is more computational eﬃcient. Some properties associated with the **orness** **level** are discussed. One of them is that the **aggregation** value for any elements set is always increasing with the **orness** **level**, which can used as a **parameterized** **aggregation** method with **orness** as its control parameter. These properties similar to that of the geometric (maximum entropy) **OWA** operator, which can also be seen as the discrete case of equidiﬀerent RIM (regular increasing monotone) quan- tiﬁers. The **general** forms of equidiﬀerent **OWA** operator are proposed, and the weights generating methods are also extended in a similar way.

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Yager’s [1] ordered weighted averaging (**OWA**) operator for aggregating multiple input arguments has been a focus of re- search in a variety of ﬁelds such as decision science and computer science ever since its introduction. From a decision science perspective, the **OWA** method presents not only an unifying and generalizing formula for uncertain decision-making prob- lems, but also a multi-criteria **aggregation** technique capable of reﬂecting a decision-maker’s attitudinal character. In partic- ular, semantic meaning such as **orness** (or andness) provides an innovative method for the logical **aggregation** of multiple arguments in multi-criteria problems. The **OWA** operator is the inner product of an ordered input (or argument) vector and a weighting vector [1] . When the (ordered) argument vector is **given**, the **OWA** operator depends on the weighting vec- tor. In other words, the weighting vector plays a key role in the **aggregation** process. Thus, one of the main concerns when using **OWA** **aggregation** is how to generate **OWA** operator weights. Thus, it is possible to **model** different kinds of relation- ships among the criteria by appropriately selecting the weighting vector. Previous studies have advocated numerous weights generation and **aggregation** methods, including the programming-based approach [2–9] , the experience- or learning-based approach [10–12] , the analytic formula-based approach [13,14] , and the quantiﬁer-guided approach [15–23] (please see pa- pers [24,25] for comprehensive reviews on these methods).

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used method is to obtain the desired **OWA** operator under a **given** **orness** **level** [12–15,29,35,58] , which is usu- ally formulated as a constrained optimization problem. The objective to be optimized can be the (Shannon) entropy [12,14,29,35] , the variance [15,24] , the maximum dispersion [2,43] , the (generalized) Re´nyi entropy [31] , the total square deviation [41] , or even the preemptive goal programming [42] . O’Hagan [35] suggested the problem of constraint nonlinear programming with a maximum entropy procedure, the solution is called a MEOWA (Maximum Entropy **OWA**) operator. Filev and Yager [12] further proposed a method to generate MEOWA weighting vector by an immediate parameter. Fulle´r and Majlender [14] transformed the maximum entropy **model** into a polynomial equation, which can be solved analytically. Liu and Chen [29] proposed gen- eral forms of the MEOWA operator with a parametric geometric approach, and discussed its **aggregation** properties. Apart from maximum entropy **OWA** operator, Fulle´r and Majlender [15] suggested the minimal variability **OWA** operator problem in quadratic programming, and proposed an analytical method of it. Liu [24] gave this **OWA** operator generating method with the equidiﬀerent **OWA** operator, and discussed its properties. A closely related work is that of Wang and Parkan [43] . They proposed a linear programming **model** with minimax disparity approach to get the **OWA** operator under desired **orness** **level**. The solution equivalence of the minimum variance problem and the minimax disparity problem was proved theoretically by Liu recently [28] . Majlender [31] proposed a maximum Re´nyi entropy **OWA** operator problem with expo- nential objective function, which can include the maximum entropy and minimum variance problem as special cases, and an analytical solution was proposed.

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The fuzzy rule-based classification system generates too many rules for high dimension problems. It is often said that the numeral of fuzzy if-then rules exponentially increases as the number of features increases. [2]For this purpose, only a small number of features are selected for constructing a fuzzy classifier, which decreases its accuracy. To solve this problem, we present a multi-**level** fuzzy classifier consists of several small fuzzy classifiers with a small number of features, which not only improve the performance of fuzzy classifier but also solve the problem of high dimension.

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The LMPST approach for estimating SHIN was adapted for CGE modelling by Dixon, Parmenter and Sutton (1978) who disaggregated results from a CGE **model** to the six Australian States. In Australia, LMPST’s distinction between local and national goods is tenable for disaggregation to the state **level**. This is because most of Australia’s economic activity takes place in the capital cities of the states and these cities are far from state borders. Thus, there are many goods that are barely traded across state borders and can therefore be classified as local without too much loss of realism. At the same time, there are many goods for which the state distribution of production seems to be independent of the state distribution of absorption. It is reasonable to classify these goods as national.

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Abstract: In recent years robotic systems have matured enough to perform simple home or office tasks, guide visitors in environments such as museums or stores and aid people in their daily life. To make the interaction with service and even industrial robots as fast and intuitive as possible, researchers strive to create transparent interfaces close to human-human interaction. As facial expressions play a central role in human-human communication, robot faces were implemented with varying degrees of human-likeness and expressiveness. We propose an emotion **model** to parameterize a screen based facial animation via inter-process communication. A software will animate transitions and add additional animations to make a digital face appear “alive” and equip a robotic system with a virtual face. The result will be an inviting appearance to motivate potential users to seek interaction with the robot.

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Abstract In this work, we introduce a new class of functions defined on the interval-valued setting. These functions extend classical **OWA** operators but allow for different weighting vectors to handle the lower bounds and the upper bounds of the considered intervals. As a consequence, the resulting functions need not be an interval-valued **aggregation** function, so we study, in the case of the lexicographical order, when these operators give an interval as output and are monotone. We also discuss an illustrative example on a decision making problem in order to show the usefulness of our developments.

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Abstract. A new method for decision making that uses the ordered weighted averaging (**OWA**) operator in the **aggregation** of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum **level** (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the **OWA** operator in the IMAM, we form a new **aggregation** operator that we call the ordered weighted averaging index of maximum and minimum **level** (OWAIMAM) operator. The main advantage is that it provides a **parameterized** family of **aggregation** operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

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The typical asymmetric form of river dunes is important for the determination of hydraulic roughness of the river bed. Asymmetric dunes generated in a steady, uniform and unidirectional flow induce implications to the flow. Flow resistance, bed shear stress and sediment transport are affected by the shape of these dunes. Turbulence over such dunes is dominated by the flow separation zone and very important for dune formation (Best, 2005). Flow close to the bed follows the bed profile. However, when river dunes have an asymmetric form with steep lee sides, the flow will separate from this profile at the dune crest because the longitudinal flow velocity is larger than the vertical velocity caused by gravitational force. The flow separation results in rotational flow behind the dune crest with variations in the pressure gradient, as presented in figure 1. The rotational flow causes energy loss, a turbulent flow regime and a reverse flow near the bed that result in a zero net discharge through a vertical cross section between the bed and the separation zone (Paarlberg et al., 2007). This leads to a sudden increase in the hydraulic roughness and therefore to an increase of the water **level**.

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curriculum) for students who are the same age and grade **level** as the student for whom the IEP is being designed, as well as with information about unique student learning needs (based on input from multiple stakeholders and assessment sources). This **model** is detailed in Wehmeyer, Lattin, et al. (2001), so will only be summarized in this article. When considering a student’s formal curriculum, it may be that some students can progress on portions of the **general** curriculum without accommodations or curriculum modifications and as such that portion of the **general** curriculum will be the “most appropriate” formal curriculum. It is likely, however, that most students with mental retardation or developmental disabilities will need some accommodations or modifications. To achieve that, the IEP team is first encouraged to consider how assistive technology can accommodate for student limitations and can enable the student to progress without curriculum modifications. Once assistive technology has been considered, teams consider three levels of curriculum modifications. The first is curriculum adaptation, which refers to efforts to adapt the curriculum’s presentation and representation or the student’s engagement with the curriculum (as discussed subsequently). A second **level** of modification is curriculum augmentation, where additional content is added to the curriculum to enable students to progress. Such efforts typically include teaching students additional ‘learning-to-learn’ or self- regulation strategies that, in turn, enable students to progress more effectively in the curriculum. Neither of these levels of curriculum modification changes the **general** curriculum content. The third **level**, curriculum alteration, does change the **general** curriculum to add content specific to students needs, which might include traditional functional skills or other needed skills not in the **general** curriculum. This also, presumably, necessitates the elimination of content in the **general** curriculum. For many students with mental retardation, the third **level** of curriculum modification (e.g., alternative curriculum) is where planning currently begins, but if students are to maximally benefit from and progress in the **general** curriculum, IEP teams need to consider accommodations and curriculum adaptations and augmentations before considering alternative curricula. It is also evident that if the **general** curriculum is broad enough to cover functional areas, that will limit the need to move to an alternative curriculum.

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In all aggregations discussed so far the results are numeric values such as counts, sums, statistical means, etc. Buliung & Kanaroglou (2004) derive a kind of geometric summary of several trajectories. The authors use functions of ArcGIS to build a convex hull containing the trajectories, compute the central tendency and dispersion of the paths, and represent the results on a map as the averaged path. Such geometric summarization can work well only when the trajectories are similar in shape and close in space. It can be applied, for example, to groups of similar trajectories resulting from clustering. Grouping of trajectories by similarity and/or closeness of the routes followed by geometric and/or numeric summarization may be called R-**aggregation** (i.e. route-based). The paper (Andrienko et al. 2007) contains examples of combining route-based grouping of trajectories by means of clustering with S×S- and S×S×T×T-**aggregation**. It should be noted that route-based grouping does not guarantee that each trajectory is put in some group as there may be trajectories whose routes significantly differ from all others. Hence, a result of R-**aggregation** may consist of aggregates and solitary trajectories. For the sake of uniformity, the latter can be represented as aggregates of magnitude one.

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o Shared or Unsecured: Select this option if you are working from a non- secure computer, or one that multiple people have access to (such as at a public library). This will cause your **OWA** session to automatically timeout after only a short period of inactivity to prevent non-authorized people from accessing your account.

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Temporal **aggregation** accounts for this phenomenon, that is, the frequency of data collection is lower than the frequency at which data are generated, thus part of items in the original random process 𝑥 = {𝑥 𝑡 } 𝑡=0 ∞ are missing, only items after **aggregation** 𝑋 = {𝑋 𝜏 } 𝜏=0 ∞ can be observed, where 𝑡 is the original frequency and 𝜏 is the after-**aggregation** frequency, 𝑋 is a specific function of 𝑥 determined by the **aggregation** scheme (Marcellino, 1999). In the above case, trading data are generated at every minute while people only gather them at every day. Temporal **aggregation** **model** is a great method to fix this problem by ‘transferring’ time unit to integrate every single hour data or even every minute data (not realistic though) into the daily **model** for optimization. So once data is available, players could improve their **model** to better its forecasting ability.

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In online data stream processing, data stream classification task confronts several challenges such as, concept drift, concept evolution and partial labeling due to the dynamic nature of data streams. Amid these issues, concept drift is on the top concern that degrades the accuracy of data stream classification task, immediately upon its occurrence. However, concept evolution and partial labeling are also equally notable plights that are not focused by most of the existing approaches. Ensemble learning is a widely accepted prominent method that attempts to reconcile the issues encountering in the data stream classification. Our previous work addresses only the different types of concept drifts. This paper expounds a Novel Incremental **Aggregation** **Model** (IAM) which makes use of Adaptive Probabilistic Neural Network (APNN), Aggregate Weighted Ensemble **Model** (AWEM) and Ensemble Cloning that makes the system impeccable by combating against all the above said issues. The performance of the proposed algorithm has been experimentally tested with few synthetic data sets. Experimental results show that our **model** outperforms the existing ensemble approaches in terms of accuracy.

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In this chapter, a **parameterized** MOR technique is developed for distributed electromagnetic systems that have arbitrary functions of frequency due to material properties, boundary conditions and delay elements. The proposed algorithm directly differentiates the network equations and uses multi-order Arnoldi method to calculate the moments, without having to perform rational curve fitting or introduce separate variables to approximate the arbitrary functions of frequency. The developed algorithm is also extended to implicitly calculate the moments with respect to arbitrary function design parameters as well as the cross-moments. This procedure results in a **parameterized** reduced order **model** that is valid over a user defined range of design parameters while preserving the form of the original system. Numerical examples are provided to illustrate the validity of the proposed technique.

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In this **model**, curtailment can be defined as an instance, when a generation unit produces less than it could. Curtail- ment can be voluntary or involuntary, as for example en- forced by a TSO/DSO, and common reasons for curtail- ment include network constraints, operational security, ex- cess generation with respect to the grid load, and strategic bidding related to the potential price manipulations [2]. The availability of wind does not only influence when power can be generated, but also the ability to adjust the generated output [3]. The same can be applied to solar pho- tovoltaic (PV) generation. PV generation provides possi- bilities to full or partial down-regulation by reducing the volume of injected electricity. Down-regulation is also used for wind power. By controlling the pitch of the wind turbine blades, the power output can be curtailed partially. In addition, there are test projects [4] studying the possi- bility for using wind power for upward-regulation. The market design considered in the SmartNet project is for nearly real-time operation, and therefore it is reasonable to assume that wind power can be used for both up- and down-regulation. The flexibility levels submitted by wind and PV generation should correspond to the available gen- eration potential at a **given** time.

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The Block or Allow section in the options pane allows users to whitelist (allow) or blacklist (deny) all mail from specific email addresses as well as extra options to handle personal[r]

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