Iets om over te praten. De problematiek van het voorzetselvoorwerp in het Nederlands en het Tsjechisch

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.

Polynomial approximation to manifold learning

Manifold learning plays an important role in nonlinear dimensionality reduction. But many manifold learning algorithms cannot offer an explicit expression for dealing with the problem of out-of-sample (or new data). In recent, many improved algorithms introduce a fixed function to the object function of manifold learning for learning this expression. In manifold learning, the relationship between the high-dimensional data and its low-dimensional representation is a local homeomorphic mapping. Therefore, these improved algorithms actually change or damage the intrinsic structure of manifold learning, as well as not manifold learning. In this paper, a novel manifold learning based on polynomial approximation (PAML) is proposed, which learns the polynomial approximation of manifold learning by using the dimensionality reduction results of manifold learning and the original high-dimensional data. In particular, we establish a polynomial representation of high-dimensional data with Kronecker product, and learns an optimal transformation matrix with this polynomial representation. This matrix gives an explicit and optimal nonlinear mapping between the high-dimensional data and its low-dimensional representation, and can be directly used for solving the problem of new data. Compare with using the fixed linear or nonlinear relationship instead of the manifold relationship, our proposed method actually learns the polynomial optimal approximation of manifold learning, without changing the object function of manifold learning (i.e., keeping the intrinsic structure of manifold learning). We implement experiments over eight data sets with the advanced algorithms published in recent years to demonstrate the benefits of our algorithm.

Inventory Models for Non-Instantaneous Deteriorating Items with Expiration Dates and Imperfect Quality under Hybrid Payment Policy in the Three-Level Supply Chain

This article considers an inventory model for non-instantaneous deteriorating items with expiration dates, such as seasonal items, first-hand vegetables, and fruits. Interestingly, an inspection will be performed to manage the quality of the items during the state of no deterioration because it is difficult to purchase items with 100% perfection. Additionally, we assume that the upstream member has the power of controlling or influencing downstream members’ decisions. That is, the supplier asks the retailer for a partial advance payment to avoid cancellation of orders and offers them a credit payment to stimulate sales; in turn, the customer must pay some cash when placing an order and pay the remainder in credit for the retailer. The goal of this article is to determine an optimal replenishment cycle and the total annual cost function, so we explore the functional properties of the total annual cost function and show that the total annual cost function is convex. Theoretical analysis of the optimal properties shows the existence and uniqueness of the optimal solution. Then, we obtain simple and easy solution procedures for the inventory system. Moreover, numerical analysis of the inventory model is conducted, and the corresponding examples are considered with a view to illustrating the application of the supply chain model that we have investigated in this article. Finally, in the concluding section, we have not only provided the motivation and the need for our usages of mathematical analytic solution procedures based upon the convexity, monotonicity (increasing and decreasing) and differentiability properties of the object function (that is, the total annual cost function), which involve some symmetry aspects of the object function, but we have also indicated the limitations and shortcomings in our investigation, which will naturally lead to some potential directions for further research on the supply chain model, which we have considered and mathematically analyzed in this article.

A FRAMEWORK FOR DESIGNING AN AUGMENTED REALITY APPLICATION FOCUSING ON OBJECT FUNCTION FOR CHILDREN WITH AUTISM

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.

Different Object Functions for SWIPT Optimization by SADDE and APSO

Multiple objective function with beamforming techniques by algorithms have been studied for the Simultaneous Wireless Information and Power Transfer (SWIPT) technology at millimeter wave. Using the feed length to adjust the phase for different objects of SWIPT with Bit Error Rate (BER) and Harvesting Power (HP) are investigated in the broadband communication. Symmetrical antenna array is useful for omni bearing beamforming adjustment with multiple receivers. Self-Adaptive Dynamic Differential Evolution (SADDE) and Asynchronous Particle Swarm Optimization (APSO) are used to optimize the feed length of the antenna array. Two different object functions are proposed in the paper. The first one is the weighting factor multiplying the constraint BER and HP plus HP. The second one is the constraint BER multiplying HP. Simulations show that the first object function is capable of optimizing the total harvesting power under the BER constraint and APSO can quickly converges quicker than SADDE. However, the weighting for the final object function requires a pretest in advance, whereas the second object function does not need to set the weighting case by case and the searching is more efficient than the first one. From the numerical results, the proposed criterion can achieve the SWIPT requirement. Thus, we can use the novel proposed criterion (the second criterion) to optimize the SWIPT problem without testing the weighting case by case.

Promoting Electric Vehicle Cell Innovation Diffusion Considering Patent Licensing Strategy: A Combination of Evolutionary Game and Optimization Algorithm Approach

Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return; however, the strategy is unclear in certain scenarios. We tried to explain the question of how to maximize the patent holder’s return by appropriate patent license strategy to promote EV cell innovation diffusion, when competition and patent licensing relationship exist in the supply chain. A multistage and multichannel diffusion model of EV cell comprising the patent holder, EV cell producer and EV producers is developed; the evolutionary game is analyzed considering the competition among same stage players and patent licensing relationship among different stage players; and an optimization algorithm is introduced to find the maximum weighted object function of the patent holder. We established the multistage and multichannel diffusion model and found a nonlinear complex relationship between patent holder object function and the key factors including patent royalty pricing and innovation advantage coefficient; in addition, an optimization algorithm is developed based on adopters’ decision-making related with competition and patent licensing.