The dual of convolutional codes over Zpr\mathbb{Z}_{p^r}

An important class of codes widely used in applications is the class of convolutional codes. Most of the literature of convolutional codes is devoted to con- volutional codes over finite fields. The extension of the concept of convolutional codes from finite fields to finite rings have attracted much attention in recent years due to fact that they are the most appropriate codes for phase modulation. However convolutional codes over finite rings are more involved and not fully understood. Many results and features that are well-known for convolutional codes over finite fields have not been fully investigated in the context of finite rings. In this paper we focus in one of these unexplored areas, namely, we investigate the dual codes of convolutional codes over finite rings. In particular we study the p-dimension of the dual code of a convolutional code over a finite ring. This contribution can be considered a generalization and an extension, to the rings case, of the work done by Forney and McEliece on the dimension of the dual code of a convolutional code over a finite field.Comment: submitte

The development of an SPH tree-based algorithm to investigate the evolution of self-gravitating Protoplanetary Disks

I Dischi Circumstellari costituiscono un campo di studio molto moderno, per diverse ragioni. Prima di tutto, lo studio dell'evoluzione di tali sistemi mira a spiegare la configurazione delle migliaia di sistemi planetari che sono stati osservati fin ora, e può fornire risposte importanti anche sulla formazione del Sistema Solare. In secondo luogo, gli sviluppi delle tecnologie interferometriche nella banda Infrarossa e Millimetrica hanno fornito un ampia gamma di possibilità di osservare i dischi con una risoluzione angolare molto piccola. I dischi hanno dunque rappresentato un ampio target osservativo che ha stimolato non in maniera indifferente l'applicazione e il miglioramento delle più avanzate tecniche osservative. Inoltre, l'evoluzione dei dischi è guidata da diversi processi fisici, sia dinamici sia idrodinamici, e dunque essi figurano tragli oggetti di studio più importanti a cui applciare sofisticate tecniche di modellistica numerica. In particolare, i dischi Protoplanetari sono diventati, dagli ultimi due decenni, un obbiettivo chiave nel campo dei sistemi stellari multipli. La loro evoluzione in ambienti eterogenei ricchi di stelle e gas rappresenta una nuova frontiera del calcolo numerico applicato all’astronomia, perché implica numerosi problemi ancora irrisolti. Le recenti scoperte di dischi in ammassi aperti ha aperto a nuove prospettive nello studio teorico di sistemi planetari extrasolari nel loro stato primordiale gassoso. Per queste ragioni, l’attività del mio Dottorato ha come scopo l’implementazione di uno strumento di modellistica numerico, capace di affrontare questi e molti altri problemi legati all’interazione tra gas e stelle. In questo documento, il Sottoscritto presenterà un nuovo algoritmo sviluppato per integrare l’evoluzione temporale di sistemi gassosi (con o senza gravità) e la loro interazione con le stelle. Il codice si basa sul ben noto approccio Smoothed Particles Hydrodynamics (SPH), e contiene un metodo numerico per accoppiare il cas con un limitato numero di punti di massa calcolando, con elevata precisione, la loro mutua interazione gravitazionale. Il calcolo dell’autogravità è fatto approssimando la forza mediante il noto Tree-Scheme. Dopo aver descritto alcuni test basilari sulla stabilità e sulle prestazioni, il Sottoscritto descriverà il problema astrofisico principale studiato durante il lavoro di dottorato: l’evoluzione di dischi protoplanetari perturbati da stelle che effettuano incontri ravvicinati, che cistituisce uno schema approssimato del più complesso caso di interazione di un disco con l’ambiente stellare in cui esso è immerso.Circumstellar Disks represent a very modern object of investigation, for many reasons. First, the investigation on their evolution aims at explaining the configuration of several thousand of planetary systems detected so far and may give important answers even on the formation of Solar System. Secondly, the early development of the interferometric technique to observe in the infrared and mm wave-length, opened a wide range of possibilities to observe disks with very short angular resolution. Thus, Disks constitute a wide target, stimulating the application and the improvement of the most advanced observational techniques. Moreover, disk evolution is driven by several physical processes, both dynamical and hydrodynamical, they are indeed one of the most important objects of application of several sophisticated numerical techniques. Protoplanetary disks have become, since the last 20 years, a key target in the field of star clusters. Their evolution in heterogeneous environments rich in stars and gas represents a new frontier for the Numerical Astronomy because it carries several issues still not overcome. The recent discoveries of circumstellar disks in open clusters opened to new perspectives to the theoretical investigations of non-isolated exoplanetary systems in their primordial gaseous state. For such purposes, my PhD activity aimed at building a suitable numerical investigating instrument, able to face this and many other problems related to the interaction between gaseous systems and stars. In this document, I will present a new Algorithm developed to treat the evolution of gaseous systems (both selfgravitating and non-selfgravitating) and their interaction with Stars. The Code is based on the well-known Lagrangian Smoothed Particle Hydrodynamics approach, and contains a numerical technique to couple a gas distribution with a few amounts of point-mass particles, evaluating, with high precision, their motion. The calculus of self-gravity is accomplished with a tree-scheme approach. After describing some basic stability and performance tests, I will focus on the main problem investigated during my work: the evolution of protoplanetary disks perturbed by passing-by stars, which constitute an approximated scheme of the more complex disk-stellar environment interaction

Mathematical optimization and learning models to address uncertainties and sustainability of supply chain management

As concerns about climate change, biodiversity loss, and pollution have become more widespread, new worldwide challenges deal with the protection of the environment and the conservation of natural resources. Thus, in order to empower sustainability and circular economy ambitions, the world has shifted to embrace sustainable practices and policies. This is carried out, primarily, through the implementation of sustainable business practices and increased investments in green technology. Advanced information systems, digital technologies and mathematical models are required to respond to the demanding targets of the sustainability paradigm. This trend is expanding with the growing interest in production and services sustainability in order to achieve economic growth and development while preventing their negative impact on the environment. A significant step forward in this direction is enabled by Supply Chain Management (SCM) practices that exploit mathematical and statistical modeling to better support decisions affecting both profitability and sustainability targets. Indeed, these targets should not be approached as competing goals, but rather addressed simultaneously within a comprehensive vision that responds adequately to both of them. Accordingly, Green Supply Chain Management (GSCM) can achieve its goals through innovative management approaches that consider sustainable efficiency and profitability to be clearly linked by the savings that result from applying optimization techniques. To confirm the above, there is a growing trend of applying mathematical optimization models for enhancing decision-making in pursuit of both environmental and profit performance. Indeed, GSCM takes into account many decision problems, such as facility location, capacity allocation, production planning and vehicle routing. Besides sustainability, uncertainty is another critical issue in Supply Chain Management (SCM). Considering a deterministic approach would definitely fail to provide concrete decision support when modeling those kinds of scenarios. According to various hypothesis and strategies, uncertainties can be addressed by exploiting several modeling approaches arising from statistics, statistical learning and mathematical programming. While statistical and learning models accounts variability by definition, Robust Optimization (RO) is a particular modeling approach that is commonly applied in solving mathematical programming problems where a certain set of parameters are subject to uncertainty. In this dissertation, mathematical and learning models are exploited according to different approaches and models combinations, providing new formulations and frameworks to address strategic and operational problems of GSCM under uncertainty. All models and frameworks presented in this dissertation are tested and validated on real-case instances

T-WAS and T-XAS algorithms for fiber-loop optical buffers

In optical packet/burst switched networks fiber loops provide a viable and compact means of contention resolution. For fixed size packets it is known that a basic void-avoiding schedule (VAS) can vastly outperform a more classical pre-reservation algorithm as FCFS. For the setting of a uniform distributed packet size and a restricted buffer size we proposed two novel forward-looking algorithms, WAS and XAS, that, in specific settings, outperform VAS up to 20% in terms of packet loss. This contribution extends the usage and improves the performance of the WAS and XAS algorithms by introducing an additional threshold variable. By optimizing this threshold, the process of selectively delaying packet longer than strictly necessary can be made more or less strict and as such be fitted to each setting. By Monte Carlo simulation it is shown that the resulting T-WAS and T-XAS algorithms are most effective for those instances where the algorithms without threshold can offer no or only limited performance improvement

Multiobjective multicast routing with Ant Colony Optimization

This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

Brazilian music for youth choir by FUNARTE: exploring issues of pedagogy and authenticity in Brazilian choral music

The purpose of this study is to stimulate the dissemination of Brazilian choral repertoire, especially the pieces from the series Brazilian Music for Youth Choir by FUNARTE, and provide accurate interpretative information for authentic performance and effective teaching. Musical and pedagogical analyses of three of the pieces from the series by FUNARTE (2009) were done as means to the purpose of the study. In addition, ethnographic interview were held with the composers of each of those pieces, Paulo Malaguti, Leandro Maia, and Caio Senna, and the technical-pedagogical coordinator of the series, Eduardo Lakschevitz. Through the interviews with the composers it was possible to identify musical and pedagogical approaches relevant to accurate performance of Brazilian choral music, as well as to raise the discussion about authenticity in Brazilian music, which seemed to be a taboo among Brazilian musicians. The interview with the technical-pedagogical coordinator helped to understand the purpose of FUNARTE and the Choral Project. This study found that choral music in Brazil is a multifaceted phenomenon that does not fit the categories folk, popular, or classical music alone; so, it can be considered a style apart. The composers’ opinion about authenticity proves that it is flexible and that Brazilian musicians are open to new interpretations of Brazilian music. Complementary materials such as translation and IPA version of the pieces, and suggested reading and recording are provided to support music educators on an accurate and authentic performance of Brazilian choral repertoire

Multicast routing and wavelength assignment in optical networks with particle swarm optimization

Large bandwidth on hand in WDM networks is the best choice for increasing tra c demand; although, routing and wavelength assignment (RWA) problems still remain a challenge. This work proposes a novel method to solve multicast-RWA problems, using multi-objective Particle Swarm Optimization (PSO), implementing four competitive ap- proaches of state-of-the-art. Such algorithms minimize simultaneously the hop count, the number of splitting power light, the number of split- ter node and the balancing of multicast tree for a given set of multicast demands. This way, a set of optimal solutions (known as Pareto set) is obtained in one run of the algorithms, without a priori restrictions. Sim- ulation results prove the viability of the PSO proposal and the advantage compared on classical approaches as Multicast Open Shortest Path First routing algorithm and Least Used wavelength assignment algorithm.IV Workshop Arquitectura, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI