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For foreign students, the prepositional object is among the most problematic syntactic features of the Dutch language, as its form presents strong similarities with the adverbial clause, but it has an object function. In some cases it is very difficult to even decide whether the prepositional phrase has an adverbial function or is an object comparable with the direct object. In this paper the Dutch prepositional object is compared with similar constructions in the Czech language. Furthermore, the function of the preposition and its categorisation are briefly discussed. The paper ends with some criteria for Czech-speaking students to recognize a prepositional object as such.

Augmented Reality (AR) is the evolution of the concept of Virtual Reality (VR). Its goal is to enhance a person's perception of the surrounding world. Augmented reality techniques are often applied to facilitate understanding and create attractive educational and health tools. As such, augmented reality is deemed suitable to be implemented as one of the potential intervention methods as the treatment of autism in a fun environment. Hence, this study is aimed to develop a conceptual framework to design augmented reality applications based on object function to help in the communication of children with autism. The study framework will be developed based on vision-based object recognition. Object recognition has been used in many applications, especially in bio-imaging, industrial inspection, and robotic vision. The findings of this study will benefit autistic children in visual communication and indirectly help them to effectively link objects with their functions. This framework will then help designers to develop augmented reality applications suited to be an intervention tool that fits the need of autistic children.

As one of clustering methods K-Means algorithm can be used to group 93 data of STMIK Palangka Raya students into 3 namely pass, active, and inactive. The stages of it produce 9 iterations since the displacement of the group in which there is a movement from one group to another because the change value of the object function. The iteration can be stopped at the 9th because the value of the object function change is below the given threshold value of 0.1 and the absence of group movement in the data used. The 9 iterations that occur indicate the rise and fall the change value of object function and data transfer in the location of the group.

In recent years, photovoltaic has been developing rapidly, which is of great significance to the research of reactive power optimization for distributed photovoltaic large scale connected distribution networks. The mathematical model of reactive power optimization in distributed photovoltaic distribution network is introduced in this paper, including the introduction of reactive power optimization algorithms and the object function and restrictions of reactive power optimization modeling.

Combining historical, archaeological and experimental data, traditional and archaeological ceramics, from the Santarem district, with different chronology and functions have been studied. Our aim is to understand ancient pottery technology and to evaluate whether ceramic production followed similar principles in the Middle Ages (from the Islamic to the Christian domination) and Modern times. Moreover, traditional ceramics, knowing the productive process, have been used as a tool to interpret ancient pottery technology. We considered different utilitarian ceramic groups, namely fire, table and food-liquid container wares. Through the combination of optical microscopy (OM), X-ray powder diffraction (XRPD), X-ray fluorescence spectroscopy (XRF) with physical and mechanical tests, it has been possible to collect valuable information regarding pottery manufacturing, considering the age and the object function. Moreover, it is also considered the effect of raw materials mixing and ceramic paste preparation on ceramics final characteristics. Our results indicate that both during the Middle Ages and in Modern times, technical expertise played, and still play, a fundamental role in the creation of a specific object. In this specific case, behavioural and socio-cultural factor drove ceramists’ decision when selecting between different technological solutions, and every decision or technical choice is/was taken depending on the functional and performance characteristics desired for a specific artefact. This happened during the Middle Ages, and is still happening nowadays for the production of traditional ceramics in the district of Santarem, Portugal.

One improved micro-nano optical fiber coupler sensor and an error object function base on the modal acoustic emission theory are combined to locate the linear acoustic source, and its performance is experimentally validated.

The convolutional neural network (CNN) is a promising algorithm for artificial intelligence. Although it was developed for image classification, much research is currently in progress in various fields, such as object detection and image processing. The basic principle of the CNN, especially for classification, is to adopt a loss function and minimize it in an iterative way. In this paper, a multigradient-based training algorithm is proposed for image classification. The proposed algorithm defines an object function based on multigradients and trains the CNN by maximizing the corresponding objective function. When applied to open access databases, the proposed algorithm performed better than conventional back-propagation based CNN methods.

The designing of the methodology for a differential-diagnostic study involves planning for the formation of the study base and for the documentation of the relevant facts on this, including the elementary facts’ synthesis into the empirical values for the parameters in the designed object function for the study in reference to the designed domain of this function. The design is aimed at the attainment of certain qualities for the study, some of them mere desiderata, others more than that: one is a sine-qua-non requirement for meaningfulness of the study’s result, and another a requirement for the very admissibility of the study. The process of the designing involves a sequence of topics conforming to that in the actual formation of the study base and then in the documentation of the relevant facts about it, the design decisions on each of them governed by logical principles.

Moving on now, we realize that in any case a nominal and an adjectival presentation suffice for the unity of a judgment. Individual simple-independent meanings are not enough for any actual independent meaning (which is a complete thought-meaning). But, two suffice for this purpose, namely, in the form “N is A”–in the subject position, a nominal meaning, in the “predicate position”, an arbitrary nominal or non-nominal meaning. In this way, we acquire the basic form of a propositionally simple judgment. It is, as far as that goes, the traditional understanding, as actually passed down, to treat the “categorical judgment” as basic form. However, the tradition goes further and immediately puts two basic forms here, “S is P”, “S is not P”. These are forms designated by the class-name “categorical judgments”, which, however, also designates other forms related in terms of general ways of composition, especially the plural judgments to be discussed later. What is characteristic of all categorical judgments is that, grounded in a compound nominal positing or a multifold (pieced together) nominal positing as basic positing, is a positing−single or multifold−built upon that, namely, in such a way that the positings are positive or affirmative or negative. The first component is the subject component. It posits the subject-object, which is conscious noematically as the substrate of the subject-positing. And the predicate-positing is built upon that−whence the break. The noun that functions in the subject function–through which the subject-positing therefore goes as positing-under–functions for precisely that reason differently than the same noun in a different function, for instance, an object function, whereby, the positing performed there is precisely not positing-under. The noun is not “subjectum” (ὑποκeίμeνον). Do not confuse subject-presentation and subject-object!

Zero-shot Learning (ZSL) aims to transfer knowledge from seen image categories to unseen ones by leveraging semantic information. It is generally assumed that the seen and unseen classes share a common semantic space. A number of methods propose to design a common space to accomplish the projection between image and class embeddings by learning a compatibility function, which make up sample pairs to train the object function. However, considering the drawbacks of previous compatibility function, we design a new compatibility function in this paper. Different from previous compatibility pattern, our proposed compatibility function is more discriminative by employing label vectors, which can measure the similarity between the projected image features and all seen class prototypes. Extensive experiments on four benchmark datasets show the effectiveness of our proposed approach.

It is projected that the electric vehicle will become a dominant method of transportation within future road infrastructure. Moreover, the electric vehicle is expected to form an additional role in power systems in terms of electrical storage and load balancing. This paper considers the latter role of the electric vehicle and its impact on the steady-state stability of power systems, particularly in the context of large-scale electric vehicle integration. The paper establishes a model framework which examines four major issues: electric vehicle capacity forecasting; optimization of an object function; electric vehicle station siting and sizing; and steady-state stability. A numerical study has been included which uses projected United Kingdom 2020 power system data with results which indicate that the electric vehicle capacity forecasting model proposed in this paper is effective to describe electric vehicle charging and discharging profiles. The proposed model is used to establish criteria for electric vehicle station siting and sizing and to determine steady-state stability using a real model of a small-scale city power system.

Purpose – According to the grey uncertainty and the connotation of different types weights, the purpose of this paper is to establish the pattern of multi-dimensional grey fuzzy decision making with feedback based on weight vector and weight matrix, and applies this pattern to evaluate the regional financial innovation ability. Design/methodology/approach – At first, this paper analyzes the connotation of financial innovation ability and establishes the evaluation system of regional financial innovation ability. Second, the formula of computing the multi-objective weighted comprehensive value based on weight vector and weight matrix is put forward. In view of the object function with supervised factor and stability coefficient, this paper gives the formulas to compute weight vector and weight matrix. Moreover, the algorithm of the multi-dimensional grey fuzzy decision making pattern with feedback based on weight vector and weight matrix is expressed. At last, this paper uses the presented pattern to evaluate the financial innovation ability of thirty-one provinces in China. Findings – The results are convincing: the development of regional financial innovation is not balanced in China, having obvious spatial clustering feature. The comparisons of evaluation results based on different forms of weights show that the calculating convergence speed of the pattern presented in this paper is fast. The pattern enhances the rationality of the demarcation point between categories, and the convergence within categories, making the evaluation more reasonable. Practical implications – The method exposed in the paper can be used at evaluating the regional financial innovation ability and even for other similar evaluation problem. Originality/value – The paper succeeds in realising both the pattern of multi-dimensional grey fuzzy decision making with feedback and evaluating the regional financial innovation ability by using the newest developed theories: weighted grey and fuzzy recognition theory based on weight vector and weight matrix.

A new robust method is designed to estimate mutual coupling and channel gain/phase inconsistency parameters for a uniform circular array (UCA) jointly. It only needs a single signal source and two trials with different impinging directions to complete the calibration. The directions of the trials do not need to be calibrated beforehand. First, the two kinds of parameters are uncoupled into a linear equation in discrete Fourier transform (DFT) beam space by a novel decoupling technique. Then, a new object function is set according to the symmetry of the mutual coupling parameters. Finally, with some prior directional information, all the parameters can be estimated through a limited angular search. Simulations verify the effectiveness and robustness of the proposed method.

Massive usage scenarios prompt the prosperity of terahertz (THz) reflective imaging methods. In this Letter, we apply ptychography to continuous-wave THz reflective imaging. Our scheme has a compact lensless layout and uses a full-field oblique-illumination recording mode. Diffraction patterns are corrected through tilted plane correction. This method can be used to retrieve the complex-valued object function and to suppress the negative effect of non-uniform illumination. The feasibility is investigated using two metal samples.

The production of pantomime is a sensible task to detect praxis deficits. It is usually assessed by presenting objects visually or by verbal command. Verbal instructions are given either by providing the name of the object (e.g., “Show me how to use a pen”) or by requiring the object function (e.g., “Show me how to write”). These modes of testing are used interchangeably. The aim of this study is to investigate whether the different instructions generate different performances. Fifty-one healthy participants (17–89 years old) were assessed on three pantomime production tasks differing for the instruction given: two with verbal instructions (Pantomime by Name and Pantomime by Function) and one with the object visually presented (Pantomime by Object). Results showed that Pantomime by Function produced the poorest performance and the highest frequency of Body Parts as Tool (BPT) errors, suggesting that the way the instructions are given may determine the performance in a task. Nuances in test instructions could result in misleading outcome.

Determining the harmonic responsibilities of utility and customer side at a PCC has been a great concern in harmonic research, and utility harmonic impedance is a key factor for assessing harmonic emission levels. When background harmonic is unstable, traditional methods have a large error. A new method is proposed in this paper to assess harmonic impedance based on minimum energy fluctuation. The method can calculate harmonic impedance by constructing an object function which minimizes the background harmonic energy fluctuation, without assuming background harmonic is stable. Simulation analysis indicates that the proposed method is more reliable to calculate harmonic impedance, which can reduce the error caused by the fluctuation of background harmonic.

The penalized weighted least-squares (PWLS) image reconstruction with the widely used edge-preserving nonlocal means (NLM) penalty has shown the potential to significantly improve the image quality for low dose CT (LDCT). Considering the nonlocal weights have significant effects for the smoothness and resolution of the reconstruction, much effort has been made to improve their accuracy. A high quality image of normal dose with less noise and artifacts is sometimes used for the weight’s calculation to further improvement. However, registration should be employed first when misalignment between the low-dose and normal-dose scans cannot be ignored. It will bring an extra work and the effect of registration error on the proposed method are uncertain. The paper aims to propose a new NLM prior model based on normal-dose CT (NDCT) without registration, by predicting nonlocal weights with selecting most similar patch samples from FDCT database. The patch samples are determined by evaluating the similarity between patches from NDCT and the target patch of LDCT. After building up the normal dose based NLM penalty, the PWLS object function is iteratively minimized for reconstruction. Preliminary reconstruction with LDCT data has shown its potential in the structure detail preservation.

Previous work has shown that the perception of a graspable object may automatically potentiate actions that are tailored to specific action-related features of the object (e.g., its size) and may be related to its immediate grasping as well as to its long-term, functional use. We investigated the neural correlates of function- and size-related object affordances that may be concurrently potentiated by a graspable object. Participants were lying in a MR scanner holding a large switch in one hand and a small switch in the other hand. They passively attended a large or a small object with clearly separated functional and graspable end that was displayed centrally at an average angle of 45 degrees. Participants responded to the direction of an arrow that was overlaid on the object after a mean period of 1,000 ms after object onset and was pointing to the left or to the right with equal probability. Response times were shorter when the arrow pointed to the functional end of the object and when the responses were made with the switch that was congruent to the size of the perceived object. A clear distinction was found in the representation of function- and size-related affordances; the former was represented in the posterior parietal cortex and the latter in prefrontal, premotor, and primary sensorimotor cortices. We conclude that different aspects of object-directed actions may be automatically potentiated by individual object features and are represented in distinct brain areas.

Plate spacing is an important parameter in passive electromagnetic armor systems. Its value directly influences the effect of the passive electromagnetic armor on the metal jet. The parameter optimization is important for structural design for the passive electromagnetic armor system. The action time and the complete action time of current on the metal jet and the armor plate inductance are associated with armor plate spacing. To reduce the armor plate inductance, and prolong the action time and the complete action time, armor plate spacing is taken as the optimization variable for objective function. Through LINGO solution to the objective function and the verification of MATLAB, LINGO solution results are found in line with the trend of the objective function image. Through the analysis of the impact of different weights on the objective function and optimal plate spacing, the weight coefficients of complete action time and action time should be increased, and the weight coefficient of armor plate inductance should be decreased to make the object function to get a smaller value, c 1 ≥ 0.5, 0.3 ≤ c 2

In this paper, we investigate the problem how to clean uncertain data with aggregate constraints in order to reduce the uncertainty and clean the dirty data in uncertain data sets. We find the shortages by analyzing the existing model and methods for cleaning uncertain data with aggregate constraints. We modified the existing Object Function model in literature and designed an appropriate algorithm for our problem by studying the Modified Simulated Annealing algorithm. Our experiments verify the efficiency and effectiveness of our algorithm.

An new optimization method which combines layout optimization of stiffeners with structural parameters optimization of structures is discussed. The first step is to optimize the layout of stiffenerser, then the structural parameters were optimized. In layout optimization of stiffeners, the strain energy density sensitivities of the elements were used to determine which elements of stiffeners should be deleted. In structural parameters optimization, the object function and the constraint functions were approximated by the second-order Taylor expansion. DFP (Davidon, Fletcher and Powell) method was presented to solve optimal problem. In order to reduce computational effort, the combined approximation (CA) method was used to reanalysis and update the displacements and stresses of the structure. The present method was applied to a bunker. The numerical results show that the optimization method was effective for optimization of plate-shell structure with stiffeners, and it could be to implement on a computer.

The accurate volumetric imaging using breathing motion model and single X-ray projection has a significant meaning to the clinical treatment of moving tumors. However, it is of great difficulty to realize the real-time reconstruction of volumetric image with high accuracy. In this work, a volumetric imaging method from one X-ray projection utilizing convolutional neural network (CNN) is proposed. With the aid of principal component analysis (PCA)-based motion model, a CNN regression model with weighted object function is trained to estimate the volumetric image accurately. Due to the high parallelization of CNN, the computing efficiency of the proposed method is able to meet the real-time requirement of practical treatment (less than 0.05 seconds). A synthetic test using 4D Extended Cardiac-Torso (XCAT) Phantom is carried out which testify the effectiveness of our method.

Dissertação de mestrado integrado em Psicologia, Áreas específicas para o conhecimento da função e manipulação de um objeto já foram encontradas em estudos anteriores. Contudo, objetos que possuem a mesma forma de manipulação tendem a ser visualmente semelhantes, enquanto objetos que têm a mesma função normalmente pertencem ao mesmo contexto. Neste estudo, pretende-se investigar o conhecimento de função e manipulação de um objeto, controlando o contexto e semelhanças visuais, respetivamente. O paradigma consiste num design de blocos de fMRI, onde 15 adultos saudáveis tiveram de realizar julgamentos de semelhanças de acordo com a manipulação, função, semelhanças visuais e contexto dos objetos, a partir de desenhos de objetos manipuláveis. A comparação direta entre o conhecimento de manipulação e as semelhanças visuais demonstrou ativação no gyrus supramarginal e no gyrus superior frontal. Quando o conhecimento da função foi comparado com o contexto, nenhuma ativação sobreviveu. Na comparação chave entre conhecimento da manipulação controlando semelhanças visuais e conhecimento da função controlando contexto observou-se ativação no gyrus médio esquerdo, occipital e temporal. Nenhuma ativação foi encontrada na comparação contrária. Os nossos resultados sugerem que o conhecimento da manipulação baseia-se na integração da postura das mãos (gyrus supramarginal) com uma representação abstrata do objeto (gyrus médio temporal). O conhecimento da função parece ser uma soma integrada da representação de características dos objetos., Previous neuroimaging studies have found specific brain areas for function and manipulation knowledge. However, objects sharing the same manner of manipulation tend to be visually similar while objects sharing the same function usually belong to the same context. In the present study, we investigated function and manipulation knowledge when controlling for context and visual similarity respectively. In an fMRI block design paradigm, 15 healthy young adults had to make similarity judgments according to object manipulation, object function, visual similarity and context of a series of pairs of line drawing pictures of manipulable objects. Direct comparison of manipulation knowledge to visual similarity showed activation in the supramarginal gyrus and the superior frontal gyrus. When function knowledge was compared to context no cluster survived. The key comparison between manipulation knowledge controlled for visual similarity and function knowledge for context, showed activation in the left middle occipital and middle temporal gyrus for manipulation knowledge. No activation was found in the reverse comparison. Our results suggest that the manipulation knowledge relies on the integration of hand postures (supramarginal gyrus) with an abstract representation of the object (middle temporal gyrus) and that function knowledge may be the sum of a highly integrated representation of objects features.

Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the perturbation. The value of the objective function for an unperturbed output is called a baseline. Cho et al. proposed node-perturbation learning with a noisy baseline. In this paper, we report on building the statistical mechanics of Cho's model and on deriving coupled differential equations of order parameters that depict learning dynamics. We also show how to derive the generalization error by solving the differential equations of order parameters. On the basis of the results, we show that Cho's results are also apply in general cases and show some general performances of Cho's model., 16 pages, 7 figures, submitted to JPSJ

A method for performing a formation-related operation based on corrected vertical seismic profile (VSP) data of an earth formation includes performing a VSP survey and applying a normal moveout (NMO) correction equation to the survey data that is a function of source offset to wellhead. The method also includes solving the NMO correction equation using a simulated annealing algorithm having an object function that is a coherence coefficient of semblance analysis of an NMO corrected reflection event within a time window to provide NMO corrected data. The method further includes performing the formation-related operation at at least one of a location, a depth and a depth interval based on the VSP NMO corrected data.

A relatively simple yet accurate analytical model for the image formation in the imaging scanning TEM (ISTEM) imaging mode, which implements partial spatial incoherence using a combination of scanning illumination and conventional imaging, is presented. Based on an object function approximation the ISTEM intensity can be divided into a constant, a linear and a nonlinear term. Under certain conditions, which are discussed, the formation of both linear and nonlinear terms can be expressed by convolutions with point spread functions. A closer inspection of these allows an insight into the advantages of ISTEM compared to conventional TEM (CTEM). The findings of the proposed model are confirmed by comparison to multislice simulations. A close investigation of the linear coherent contrast transfer function allows the derivation of optimal imaging conditions to reach a maximum resolution for a given signal-to-noise ratio. The robustness of ISTEM towards temporal incoherence is finally demonstrated and discussed within the model. (C) 2017 Elsevier B.V. All rights reserved.

Based on the Sobol’ theory, Hamma and Saltelli indicator system, the path parameters were divided into the different subsets for the vibration transfer path systems with random paths in this paper. The object function was constructed and decomposed, thus the global sensitivity based on variances was formed. The first-order and total sensitivities of various parameter subsets were calculated using Monte-Carlo simulation method combined with Latin hypercube sampling technique. Through the analysis example, the way is feasible to analyze the interaction of paths or path parameters in the vibration transfer path systems with uncertainty.