An IP capable data link layer protocol for narrow band half-duplex packet data radio networks

The wide adaptation of Internet Protocol (IP) as de facto protocol for most communication networks has established a need for developing IP capable data link layer protocol solutions for Machine to machine (M2M) and Internet of Things (IoT) networks. However, the wireless networks used for M2M and IoT applications usually lack the resources commonly associated with modern wireless communication networks. The existing IP capable data link layer solutions for wireless IoT networks provide the necessary overhead minimising and frame optimising features, but are often built to be compatible only with IPv6 and specific radio platforms. The objective of this thesis is to design IPv4 compatible data link layer for Netcontrol Oy's narrow band half-duplex packet data radio system. Based on extensive literature research, system modelling and solution concept testing, this thesis proposes the usage of tunslip protocol as the basis for the system data link layer protocol development. In addition to the functionality of tunslip, this thesis discusses the additional network, routing, compression, security and collision avoidance changes required to be made to the radio platform in order for it to be IP compatible while still being able to maintain the point-to-multipoint and multi-hop network characteristics. The data link layer design consists of the radio application, dynamic Maximum Transmission Unit (MTU) optimisation daemon and the tunslip interface. The proposed design uses tunslip for creating an IP capable data link protocol interface. The radio application receives data from tunslip and compresses the packets and uses the IP addressing information for radio network addressing and routing before forwarding the message to radio network. The dynamic MTU size optimisation daemon controls the tunslip interface maximum MTU size according to the link quality assessment calculated from the radio network diagnostic data received from the radio application. For determining the usability of tunslip as the basis for data link layer protocol, testing of the tunslip interface is conducted with both IEEE 802.15.4 radios and packet data radios. The test cases measure the radio network usability for User Datagram Protocol (UDP) based applications without applying any header or content compression. The test results for the packet data radios reveal that the typical success rate for packet reception through a single-hop link is above 99% with a round-trip-delay of 0.315s for 63B packets.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

UWB radar sensor networks: Detection algorithms design and experimental analysis

In the last years radar sensor networks for localization and tracking in indoor environment have generated more and more interest, especially for anti-intrusion security systems. These networks often use Ultra Wide Band (UWB) technology, which consists in sending very short (few nanoseconds) impulse signals. This approach guarantees high resolution and accuracy and also other advantages such as low price, low power consumption and narrow-band interference (jamming) robustness. In this thesis the overall data processing (done in MATLAB environment) is discussed, starting from experimental measures from sensor devices, ending with the 2D visualization of targets movements over time and focusing mainly on detection and localization algorithms. Moreover, two different scenarios and both single and multiple target tracking are analyzed.

Social issues in sustainable supply chain networks: state of the art and further research directions

The study of supply networks sustainability is a field with a long path behind. Nonetheless, most studies to date are focused on the environmental sub dimension of sustainability, while the social perspective in supply chain networks research still shows a potential for pioneering contri butions. Moreover, from the development standpoint we have observed a paradigm shift advancing from a narrow concept of development, centered on purely economic dimensions, towards more refined issues such as inclusive business, shared value or poverty footprint, all of which are highly related to supply chain activities. In this paper we present a review of the current state of the art on social sustainability of supply chains and we identify the main existing trends in this field. After conducting this study, we can state that a new sphere of knowledge is emerging at the interface between sustainable supply chain networks and development research. The academic community is called to play an important dovetailing role in this scenario by advancing both conceptual and methodological contributions.

Design and optimization of optical, fiber based PSK demodulators for high-bit-rate optical networks

El objetivo principal de esta tesis ha sido el diseño y la optimización de receptores implementados con fibra óptica, para ser usados en redes ópticas de alta velocidad que empleen formatos de modulación de fase. En los últimos años, los formatos de modulación de fase (Phase Shift keying, PSK) han captado gran atención debido a la mejora de sus prestaciones respecto a los formatos de modulación convencionales. Principalmente, presentan una mejora de la eficiencia espectral y una mayor tolerancia a la degradación de la señal causada por la dispersión cromática, la dispersión por modo de polarización y los efectos no-lineales en la fibra óptica. En este trabajo, se analizan en detalle los formatos PSK, incluyendo sus variantes de modulación de fase diferencial (Differential Phase Shift Keying, DPSK), en cuadratura (Differential Quadrature Phase Shift Keying, DQPSK) y multiplexación en polarización (Polarization Multiplexing Differential Quadrature Phase Shift Keying, PM-DQPSK), con la finalidad de diseñar y optimizar los receptores que permita su demodulación. Para ello, se han analizado y desarrollado nuevas estructuras que ofrecen una mejora en las prestaciones del receptor y una reducción de coste comparadas con las actualmente disponibles. Para la demodulación de señales DPSK, en esta tesis, se proponen dos nuevos receptores basados en un interferómetro en línea Mach-Zehnder (MZI) implementado con tecnología todo-fibra. El principio de funcionamiento de los MZI todo-fibra propuestos se asienta en la interferencia modal que se produce en una fibra multimodo (MMF) cuando se situada entre dos monomodo (SMF). Este tipo de configuración (monomodo-multimodo-monomodo, SMS) presenta un buen ratio de extinción interferente si la potencia acoplada en la fibra multimodo se reparte, principal y equitativamente, entre dos modos dominantes. Con este objetivo, se han estudiado y demostrado tanto teórica como experimentalmente dos nuevas estructuras SMS que mejoran el ratio de extinción. Una de las propuestas se basa en emplear una fibra multimodo de índice gradual cuyo perfil del índice de refracción presenta un hundimiento en su zona central. La otra consiste en una estructura SMS con las fibras desalineadas y donde la fibra multimodo es una fibra de índice gradual convencional. Para las dos estructuras, mediante el análisis teórico desarrollado, se ha demostrado que el 80 – 90% de la potencia de entrada se acopla a los dos modos dominantes de la fibra multimodo y se consigue una diferencia inferior al 10% entre ellos. También se ha demostrado experimentalmente que se puede obtener un ratio de extinción de al menos 12 dB. Con el objeto de demostrar la capacidad de estas estructuras para ser empleadas como demoduladores de señales DPSK, se han realizado numerosas simulaciones de un sistema de transmisión óptico completo y se ha analizado la calidad del receptor bajo diferentes perspectivas, tales como la sensibilidad, la tolerancia a un filtrado óptico severo o la tolerancia a las dispersiones cromática y por modo de polarización. En todos los casos se ha concluido que los receptores propuestos presentan rendimientos comparables a los obtenidos con receptores convencionales. En esta tesis, también se presenta un diseño alternativo para la implementación de un receptor DQPSK, basado en el uso de una fibra mantenedora de la polarización (PMF). A través del análisi teórico y del desarrollo de simulaciones numéricas, se ha demostrado que el receptor DQPSK propuesto presenta prestaciones similares a los convencionales. Para complementar el trabajo realizado sobre el receptor DQPSK basado en PMF, se ha extendido el estudio de su principio de demodulación con el objeto de demodular señales PM-DQPSK, obteniendo como resultado la propuesta de una nueva estructura de demodulación. El receptor PM-DQPSK propuesto se basa en la estructura conjunta de una única línea de retardo junto con un rotador de polarización. Se ha analizado la calidad de los receptores DQPSK y PM-DQPSK bajo diferentes perspectivas, tales como la sensibilidad, la tolerancia a un filtrado óptico severo, la tolerancia a las dispersiones cromática y por modo de polarización o su comportamiento bajo condiciones no-ideales. En comparación con los receptores convencionales, nuestra propuesta exhibe prestaciones similares y además permite un diseño más simple que redunda en un coste potencialmente menor. En las redes de comunicaciones ópticas actuales se utiliza la tecnología de multimplexación en longitud de onda (WDM) que obliga al uso de filtros ópticos con bandas de paso lo más estrechas posibles y a emplear una serie de dispositivos que incorporan filtros en su arquitectura, tales como los multiplexores, demultiplexores, ROADMs, conmutadores y OXCs. Todos estos dispositivos conectados entre sí son equivalentes a una cadena de filtros cuyo ancho de banda se va haciendo cada vez más estrecho, llegando a distorsionar la forma de onda de las señales. Por esto, además de analizar el impacto del filtrado óptico en las señales de 40 Gbps DQPSK y 100 Gbps PM-DQPSK, este trabajo de tesis se completa estudiando qué tipo de filtro óptico minimiza las degradaciones causadas en la señal y analizando el número máximo de filtros concatenados que permiten mantener la calidad requerida al sistema. Se han estudiado y simulado cuatro tipos de filtros ópticos;Butterworth, Bessel, FBG y F-P. ABSTRACT The objective of this thesis is the design and optimization of optical fiber-based phase shift keying (PSK) demodulators for high-bit-rate optical networks. PSK modulation formats have attracted significant attention in recent years, because of the better performance with respect to conventional modulation formats. Principally, PSK signals can improve spectrum efficiency and tolerate more signal degradation caused by chromatic dispersion, polarization mode dispersion and nonlinearities in the fiber. In this work, many PSK formats were analyzed in detail, including the variants of differential phase modulation (Differential Phase Shift Keying, DPSK), in quadrature (Differential Quadrature Phase Shift Keying, DQPSK) and polarization multiplexing (Polarization Multiplexing Differential Quadrature Phase Shift Keying, PM-DQPSK), in order to design and optimize receivers enabling demodulations. Therefore, novel structures, which offer good receiver performances and a reduction in cost compared to the current structures, have been analyzed and developed. Two novel receivers based on an all-fiber in-line Mach-Zehnder interferometer (MZI) were proposed for DPSK signal demodulation in this thesis. The operating principle of the all-fiber MZI is based on the modal interference that occurs in a multimode fiber (MMF) when it is located between two single-mode fibers (SMFs). This type of configuration (Single-mode-multimode-single-mode, SMS) can provide a good extinction ratio if the incoming power from the SMF could be coupled equally into two dominant modes excited in the MMF. In order to improve the interference extinction ratio, two novel SMS structures have been studied and demonstrated, theoretically and experimentally. One of the two proposed MZIs is based on a graded-index multimode fiber (MMF) with a central dip in the index profile, located between two single-mode fibers (SMFs). The other one is based on a conventional graded-index MMF mismatch spliced between two SMFs. Theoretical analysis has shown that, in these two schemes, 80 – 90% of the incoming power can be coupled into the two dominant modes exited in the MMF, and the power difference between them is only ~10%. Experimental results show that interference extinction ratio of 12 dB could be obtained. In order to demonstrate the capacity of these two structures for use as DPSK signal demodulators, numerical simulations in a completed optical transmission system have been carried out, and the receiver quality has been analyzed under different perspectives, such as sensitivity, tolerance to severe optical filtering or tolerance to chromatic and polarization mode dispersion. In all cases, from the simulation results we can conclude that the two proposed receivers can provide performances comparable to conventional ones. In this thesis, an alternative design for the implementation of a DQPSK receiver, which is based on a polarization maintaining fiber (PMF), was also presented. To complement the work made for the PMF-based DQPSK receiver, the study of the demodulation principle has been extended to demodulate PM-DQPSK signals, resulting in the proposal of a novel demodulation structure. The proposed PM-DQPSK receiver is based on only one delay line and a polarization rotator. The quality of the proposed DQPSK and PM-DQPSK receivers under different perspectives, such as sensitivity, tolerance to severe optical filtering, tolerance to chromatic dispersion and polarization mode dispersion, or behavior under non-ideal conditions. Compared with the conventional receivers, our proposals exhibit similar performances but allow a simpler design which can potentially reduce the cost. The wavelength division multiplexing (WDM) technology used in current optical communications networks requires the use of optical filters with a passband as narrow as possible, and the use of a series of devices that incorporate filters in their architecture, such as multiplexers, demultiplexers, switches, reconfigurable add-drop multiplexers (ROADMs) and optical cross-connects (OXCs). All these devices connected together are equivalent to a chain of filters whose bandwidth becomes increasingly narrow, resulting in distortion to the waveform of the signals. Therefore, in addition to analyzing the impact of optical filtering on signal of 40 Gbps DQPSK and 100 Gbps PM-DQPSK, we study which kind of optical filter minimizes the signal degradation and analyze the maximum number of concatenated filters for maintaining the required quality of the system. Four types of optical filters, including Butterworth, Bessel, FBG and FP, have studied and simulated.

Call admission control algorithms in OFDM-based wireless multiservice networks

Orthogonal frequency division multiplexing (OFDM) is becoming a fundamental technology in future generation wireless communications. Call admission control is an effective mechanism to guarantee resilient, efficient, and quality-of-service (QoS) services in wireless mobile networks. In this paper, we present several call admission control algorithms for OFDM-based wireless multiservice networks. Call connection requests are differentiated into narrow-band calls and wide-band calls. For either class of calls, the traffic process is characterized as batch arrival since each call may request multiple subcarriers to satisfy its QoS requirement. The batch size is a random variable following a probability mass function (PMF) with realistically maximum value. In addition, the service times for wide-band and narrow-band calls are different. Following this, we perform a tele-traffic queueing analysis for OFDM-based wireless multiservice networks. The formulae for the significant performance metrics call blocking probability and bandwidth utilization are developed. Numerical investigations are presented to demonstrate the interaction between key parameters and performance metrics. The performance tradeoff among different call admission control algorithms is discussed. Moreover, the analytical model has been validated by simulation. The methodology as well as the result provides an efficient tool for planning next-generation OFDM-based broadband wireless access systems.

Enhanced slotted aloha protocols for underwater sensor networks with large propagation delay

Recently underwater sensor networks (UWSN) attracted large research interests. Medium access control (MAC) is one of the major challenges faced by UWSN due to the large propagation delay and narrow channel bandwidth of acoustic communications used for UWSN. Widely used slotted aloha (S-Aloha) protocol suffers large performance loss in UWSNs, which can only achieve performance close to pure aloha (P-Aloha). In this paper we theoretically model the performances of S-Aloha and P-Aloha protocols and analyze the adverse impact of propagation delay. According to the observation on the performances of S-Aloha protocol we propose two enhanced S-Aloha protocols in order to minimize the adverse impact of propagation delay on S-Aloha protocol. The first enhancement is a synchronized arrival S-Aloha (SA-Aloha) protocol, in which frames are transmitted at carefully calculated time to align the frame arrival time with the start of time slots. Propagation delay is taken into consideration in the calculation of transmit time. As estimation error on propagation delay may exist and can affect network performance, an improved SA-Aloha (denoted by ISA-Aloha) is proposed, which adjusts the slot size according to the range of delay estimation errors. Simulation results show that both SA-Aloha and ISA-Aloha perform remarkably better than S-Aloha and P-Aloha for UWSN, and ISA-Aloha is more robust even when the propagation delay estimation error is large. © 2011 IEEE.

Self-organising zooms for decentralised redundancy management in visual sensor networks

When visual sensor networks are composed of cameras which can adjust the zoom factor of their own lens, one must determine the optimal zoom levels for the cameras, for a given task. This gives rise to an important trade-off between the overlap of the different cameras’ fields of view, providing redundancy, and image quality. In an object tracking task, having multiple cameras observe the same area allows for quicker recovery, when a camera fails. In contrast having narrow zooms allow for a higher pixel count on regions of interest, leading to increased tracking confidence. In this paper we propose an approach for the self-organisation of redundancy in a distributed visual sensor network, based on decentralised multi-objective online learning using only local information to approximate the global state. We explore the impact of different zoom levels on these trade-offs, when tasking omnidirectional cameras, having perfect 360-degree view, with keeping track of a varying number of moving objects. We further show how employing decentralised reinforcement learning enables zoom configurations to be achieved dynamically at runtime according to an operator’s preference for maximising either the proportion of objects tracked, confidence associated with tracking, or redundancy in expectation of camera failure. We show that explicitly taking account of the level of overlap, even based only on local knowledge, improves resilience when cameras fail. Our results illustrate the trade-off between maintaining high confidence and object coverage, and maintaining redundancy, in anticipation of future failure. Our approach provides a fully tunable decentralised method for the self-organisation of redundancy in a changing environment, according to an operator’s preferences.

Novel cost-effective PON-to-mm-wave RoF photonic bridge for multigigabit access networks

A novel low-cost photonic PON-to-RoF bridge is presented, allowing simultaneous wireline and wireless multi-Gbps data transmission with minor impact on deployed PON networks. Simulation results show that the proposed scheme does not require narrow-linewidth lasers when envelope detector mobile terminals are used, since the transmission performance is not limited by the phase noise but by the RIN and the frequency difference between the two beating lasers. © 2013 IEEE.

Circular migration and the Internet: The role of social networks in the sociocultural context of Mexican residents in Barcelona

This work focuses on the study of the circular migration between America and Europe, particularly in the discussion about knowledge transfer and the way that social networks reconfigure the form of information distribution among people, that due to labor and academic issues have left their own country. The main purpose of this work is to study the impact of social media use in migration flows between Mexico and Spain, more specifically the use by Mexican migrants who have moved for  multiple years principally for educational purposes and then have returned to their respective locations in Mexico seeking to integrate themselves into the labor market. Our data collection concentrated exclusively on a group created on Facebook by Mexicans who mostly reside in Barcelona, Spain or wish to travel to the city for economic, educational or tourist reasons.  The results of this research show that while social networks are spaces for exchange and integration, there is a clear tendency by this group to "narrow lines" and to look back to their homeland, slowing the process of opening socially in their new context.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

Contrasting Effects Of Land Use Intensity And Exotic Host Plants On The Specialization Of Interactions In Plant-herbivore Networks.

Human land use tends to decrease the diversity of native plant species and facilitate the invasion and establishment of exotic ones. Such changes in land use and plant community composition usually have negative impacts on the assemblages of native herbivorous insects. Highly specialized herbivores are expected to be especially sensitive to land use intensification and the presence of exotic plant species because they are neither capable of consuming alternative plant species of the native flora nor exotic plant species. Therefore, higher levels of land use intensity might reduce the proportion of highly specialized herbivores, which ultimately would lead to changes in the specialization of interactions in plant-herbivore networks. This study investigates the community-wide effects of land use intensity on the degree of specialization of 72 plant-herbivore networks, including effects mediated by the increase in the proportion of exotic plant species. Contrary to our expectation, the net effect of land use intensity on network specialization was positive. However, this positive effect of land use intensity was partially canceled by an opposite effect of the proportion of exotic plant species on network specialization. When we analyzed networks composed exclusively of endophagous herbivores separately from those composed exclusively of exophagous herbivores, we found that only endophages showed a consistent change in network specialization at higher land use levels. Altogether, these results indicate that land use intensity is an important ecological driver of network specialization, by way of reducing the local host range of herbivore guilds with highly specialized feeding habits. However, because the effect of land use intensity is offset by an opposite effect owing to the proportion of exotic host species, the net effect of land use in a given herbivore assemblage will likely depend on the extent of the replacement of native host species with exotic ones.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.