Dynamic Allocation of Smart City Applications

Cities around the world are evaluating the potential of Internet of Things (IoT) to automate and optimize public services. Cities that implement this approach are commonly referred to as smart cities. A smart city IoT architecture needs to be layered and scalable in order to fulfill not only today's but also future needs of smart cities. Network Function Virtualization (NFV) provides the scale and flexibility necessary for smart city services by enabling the automated control, management and orchestration of network resources. In this paper we consider a scalable, layered, NFV based smart city architecture and discuss the optimal location of applications regarding cloud computing and mobile edge computing (MEC). Introducing a novel concept of dynamic application allocation we show how to fully benefit from MEC and present relevant decision criteria

A Highly Scalable IoT Architecture through Network Function Virtualization

As the number of devices for Internet of Things (IoT) is rapidly growing, existing communication infrastructures are forced to continually evolve. The next generation network infrastructure is expected to be virtualized and able to integrate different kinds of information technology resources. Network Functions Virtualization (NFV) is one of the leading concepts facilitating the operation of network services in a scalable manner. In this paper, we present an architecture involving NFV to meet the requirements of highly scalable IoT scenarios. We highlight the benefits and challenges of our approach for IoT stakeholders. Finally, the paper illustrates our vision of how the proposed architecture can be applied in the context of a state-of-the-art high-tech operating room, which we are going to realize in future work

Application of the partitioning method to specific Toeplitz matrices

We propose an adaptation of the partitioning method for determination of theMoore–Penrose inverse of a matrix augmented by a block-column matrix. A simplified implementation of the partitioning method on specific Toeplitz matrices is obtained. The idea for observing this type of Toeplitz matrices lies in the fact that they appear in the linear motion blur models in which blurring matrices (representing the convolution kernels) are known in advance. The advantage of the introduced method is a significant reduction in the computational time required to calculate the Moore–Penrose inverse of specific Toeplitz matrices of an arbitrary size. The method is implemented in MATLAB, and illustrative examples are presented

Participatory Research as a Path to Community-Informed, Gender-Fair Machine Translation

Recent years have seen a strongly increased visibility of non-binary people in public discourse. Accordingly, considerations of gender-fair language go beyond a binary conception of male/female. However, language technology, especially machine translation (MT), still suffers from binary gender bias. Proposing a solution for gender-fair MT beyond the binary from a purely technological perspective might fall short to accommodate different target user groups and in the worst case might lead to misgendering. To address this challenge, we propose a method and case study building on participatory action research to include experiential experts, i.e., queer and non-binary people, translators, and MT experts, in the MT design process. The case study focuses on German, where central findings are the importance of context dependency to avoid identity invalidation and a desire for customizable MT solutions.Comment: 11 pages, 4 figure

Temporada coreográfica primavera 1974

Programa de la Temporada coreogràfica de la primavera de 1974. El Ballet del Teatre Nacional de Belgrad era dirigit per M. Jovanovic, el director d'orquestra va ser D. Miladinovic i el pianista acompanyant fou M. Zamurovic. Van estrenar "Ana Karenina", amb música de R. Schredin, "Golem", amb música de F. Burt i "Bacchus et Arianne" amb música d'A. Roussel. D. Parlic va ser el coreògraf de totes elles. També es van representar "Simfonia en do" amb música de G. Bizet i coreografia de D. Parlic, "Danses Polovtsianes d'El príncep Ígor" amb música d'A. Borodin i coreografia de M. Fokine adaptada per Anica Prelie, i passos a dos de "Don Quixote" amb música de L. Minkus, "El llac dels cignes" i "El trencanous" amb música de P. I. TxaikovskiEl Ballet del Teatre de l'òpera alemanya del Rhin estava dirigit per E. Walter, que també n'era coreògraf. L'orquestra va ser dirigida per R. Schaub, R. Kubik i A. Quennet i els pianistes W. Riddlespurger i A. Roth-Schutzbach. Van estrenar una nova versió de "Romeo i Julieta" amb música de S. Prokofiev i coreografia d'E. Walter, "Apollon Musagette" amb música d'I. Stravinsky i coreografia de G. Balanchine, "La mort i la donzella" amb música de F. Schubert i coreografia d'E. Walter, i "Jeux", amb música de C. Debussy i coreografia d'E. Walter. També van dansar les reposicions de "Giselle" amb música d'Adolphe Adam amb coreografia de R. Mazalova i E. Walter, "El mandarí meravellós" amb música de Bela Bartók i coreografia d'E. Walter, i "Daphnis et Chloe" amb música de M. Ravel i coreografia d'E. Walte

Using of the Moore-Penrose Inverse Matrix in Image Restoration

A method for digital image restoration, based on the Moore- Penrose inverse matrix, has many practical applications. We apply the method to remove blur in an image caused by uniform linear motion. This method assumes that linear motion corresponds to an integral number of pixels. Compared to other classical methods, this method attains higher values of the Improvement in Signal to Noise Ratio (ISNR) parameter and of the Peak Signal-to-Noise Ratio (PSNR), but a lower value of the Mean Square Error (MSE). We give an implementation in the MATLAB programming package

Applying the Algorithm of Lagrange Multipliers in Digital Image Restoration

A method for digital image restoration, based on the algorithm of Lagrange multipliers, has many practical applications. We apply the method to remove blur in an image caused by uniform linear motion. This method assumes that linear motion corresponds to an integral number of pixels. The main contributions of the method were found on the Improvement in Signal to Noise Ration (ISNR) that have been increase significantly compared to the classic techniques, also the parameter Mean Square Error (MSE) has lower values and computational time that has been decreased considerably with respect to the other methods. We give an implementation in the MATLAB programming package

Application of the Moore-Penrose Inverse Matrix in Image Deblurring

This paper presents an image deblurring method that finds application in a broad scientific field such as image deblurring. A method for image deblurring, based on the pseudoinverse matrix is applied for removal of blur in an image caused by linear motion. This method assumes that linear motion corresponds to an integer number of pixels. Compared to other classical methods, this method attains higher values of the Improvement in Signal to Noise Ratio (ISNR) and the Peak Signal to Noise Ratio (PSNR) parameter. The values for the Mean Square Error (MSE) is lower and computational time has been decreased considerably with respect to the other methods. The presented experimental results are implemented in MATLAB

Application of Non-Iterative Method in Image Deblurring

This paper presents a non-iterative method that finds application in a broad scientific field such as image deblurring. A method for image deblurring, based on the pseudo-inverse matrix is apply for removal of blurr in an image caused by linear motion. This method assumes that linear motion corresponds to an integral number of pixels. Compared to other classical methods, this method attains higher values of the Improvement in Signal to Noise Ratio (ISNR) parameter and of the Peak Signal-to-Noise Ratio (PSNR). We give an implementation in the MATLAB programming package

Application of the pseudoinverse computation in reconstruction of blurred images

We present a direct method for removing uniform linear motion blur from images. The method is based on a straightforward construction of the Moore-Penrose inverse of the blurring matrix for a given mathematical model. The computational load of the method is decreased significantly with respect to other competitive methods, while the resolution of the restored images remains at a very high level. The method is implemented in the programming package MATLAB and respective numerical examples are presented