The characterization of complex networks can be addressed by considering each network either as an isolated and unique entity or as a sample (i.e., an outcome) from a random experiment. The latter perspective is grounded on constructing a probability space (i.e., a probability measure on the space of possible networks); this probability model allows for a compact network characterization and it can be employed for several purposes (e.g., link detection or prediction). In this paper, we formalize this perspective to rigorously define Random Network Models (RNMs) and characterize their properties. The relationship between some network features such as link density, clustering coefficient, degree distribution and connectivity, is analyzed from the point of view of the RNM complexity measured in terms of some defined entropies.
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A large variety of complex systems can be analyzed by constructing a model that relies on some network structure [1–4]. The model may be dynamical, meaning that the values of some (state) variables do change with time and, depending on the nature of such variables, we can have different types of network models. The first type corresponds to dynamic graphs that follow evolution laws defined explicitly on the network [5–8]; the second type gathers dynamical systems where the state variables are defined on a network [9,10]; finally, the third type refers to co-evolution models that combine evolving networks and dynamical systems. In the first and third type, the underlying network structure changes with time, defining a time-varying or evolving network [11,12]. In the present work, we first characterize the basic features of some simple models of evolving networks whose evolution does not depend on network structure; the time evolution of these features serves as a reference baseline signature of the behavior of simple models. Then, a model that makes use of network structure is proposed to reflect some real network characteristics. The analysis of this model shows several regimes that indicate a sophisticated behavior; for some regime, the network reaches a high clustering coefficient/link density ratio  (when compared to the ratio values of baseline signatures), a common feature in many real networks.
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Abstract. This work presents a neural network based model for in- ferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet leg- islative and policy requirements. Measurement equipment tends to be expensive to purchase and maintain. Therefore, a model based approach capable of accurate determination of pollution levels is highly beneficial. The objective of this study was to develop a neural network model to ac- curately infer pollution levels from existing data sources in Leicester, UK. Neural Networks are models made of several highly interconnected pro- cessing elements. These elements process information by their dynamic state response to inputs. Problems which were not solvable by traditional algorithmic approaches frequently can be solved using neural networks. This paper shows that using a simple neural network with traffic and me- teorological data as inputs, the air quality can be estimated with a good level of generalisation and in near real-time. By applying these models to links rather than nodes, this methodology can directly be used to in- form traffic engineers and direct traffic management decisions towards enhancing local air quality and traffic management simultaneously.
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To understand the biological significance of the responses to CN treatments, we analyzed the frequency of functional anno- tations in lists of genes using the BioMaps tool (see Materials and methods). Interestingly, genes regulated by different CN sensing mechanisms (models 1, 2 and 3) showed overlapping functional annotations (Figure 3). That is, the same biological process, for example, protein synthesis, contained genes reg- ulated according to multiple models of CN response. This observation suggests that C and N interact not only at the level of gene expression but also functionally in Arabidopsis. Primary and secondary metabolism and energy were predom- inant biological functions regulated by CN as follows. Genes involved in carbohydrate, nucleotide and amino acid metabo- lism were induced by C independent of N (model 2). In con- trast, N independent of C (model 1) was shown to repress genes involved in secondary metabolism. C and N interacted (model 3) to control the expression of over 200 genes involved in various aspects of primary metabolism, including glycolysis/gluconeogenesis and the pentose-phosphate path- way, among others. In addition to metabolism, other aspects of cellular function, such as protein synthesis, protein degra- Unsupervised hierarchical clustering analysis suggests various modes of regulation by CN
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Such techniques include the modernisation and rehabilitation of the networks to minimise leakage. This is a problem that affects not only the urban centres where 30% of the water that enters the network does not get to its destination at the consumption points but also the watering infrastructures. There are 100,000 kilometres of canals where 30% are 100 years old and most of the remainder more than 40 years old. Installation of low consumption devices nowadays allows savings of 50% without losing quality in the service. There are models of taps, showers and toilets with such improved efficiency. Wastewater can be reused after a good process of depuration. Education campaigns are crucial for saving water and the introduction of new tariffs can stimulate such savings. The contamination of both surface (rivers become increasingly polluted as they pass by cities and industrial areas) and ground water (polluted by nitrates, heavy metals and organic components and affected by salinisation) should be reduced.
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Considering all of this, the artificial neural network models here calibrated were recommended to be the structural engine for Level III (low-traffic rural roads, in which manual stress calculation is viable alongside basic material characterization) analysis of the proposed Costa Rican mechanistic-empirical pavement design guide. For Levels I and II (medium- and high-importance roads and more-specialized material characterization), artificial neural network models are recommended, as the use of design software is necessary. The software ApRIGID 1.0 was developed as a tool for ANN models and their use for design purposes. Its architecture is highly modular, allowing the code to be reused for the future CR- ME design software. All software modules were thoroughly tested in local structures and proved to be an important tool for M-E implementation and training, allowing designers to analyze
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En el Capítol 2 s'introdueixen els models amb efectes aleatoris. Als darrers anys s'ha observat un increment de l'ús dels models lineals gen- eralitzats mixts (GLMM) en articles de medicina clínica. A l'apartat de mètodes d'aquests articles moltes vegades hi ha manca d'informació rellevant (mètode d'estimació, algoritme, software,...) respecte els models GLMM al no haver-hi una pauta o guia del què cal informar sobre aquests models. En aquest capítol s'inclou un article on es recull una revisió del grau d'aplicació dels GLMM i s'avalua també la qualitat de la informació aportada en relació amb l'anàlisi amb GLMM en articles originals en el camp de la medicina clínica. L'objectiu de l'article és comprovar l'ús i la qualitat de la informació proporcionada dels GLMM en la recerca clínica. El Capítol 3 inclou un article on es descriu l'estimació dels paràmetres del model Poisson GLMM en el cas de recomptes a través de tres losoes estadístiques. La losoa, mètode d'estimació, algoritme o software util- itzats en un estudi poden inuir en l'estimació dels paràmetres. A més a més, cal tenir present alhora d'estimar els paràmetres el grau de sobre- dispersió, el tamany mostral i la mitjana marginal. L'objectiu de l'article ha estat comparar el rendiment de tres losoes diferents d'un GLMM mitjançant estudis de simulació i amb dades reals sobre lesions d'un es- port de contacte. En aquest capítol s'inclou també com a exemple de la utilitat dels GLMM un altre article on s'ajusten les lesions d'un esport de contacte. D'aquesta manera es pretén conèixer les associacions amb factors potencials de risc de forma que es pugui ampliar el coneixement sobre les possibles causes de lesions.
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In the publication “ Los últimos arquitectos del Gótico ” , Alonso Ruiz (2010) notes that one of the main problems encountered in the ﬁ eld of historical and architectural research is the absence of a global vision mapping historical phenomena with clear spatiotemporal coordinates. Although there has been signi ﬁ cant progress in this area since then, it consists of individual projects on speciﬁc aspects rather than shedding light on the overall network of buildings which Gestoso y Pérez (1899) addressed in the 19th century and which more recently has drawn the attention of a number of researchers (Alonso Ruiz and Jiménez Martin, 2009; Alonso Ruiz, 2011; Serra Des ﬁ lis, 2016; Alonso Ruiz and Villaseñor Sebastián, 2014; Alonso Ruiz and Rodríguez Estévez, 2016). In earlier projects we were able to model the local transporta- tion network represented by the routes that permitted the provision of materials and the mobility of agents. We also researched the spatio- temporal identi ﬁ cation of the agents involved in certain building activities (professionals, patrons, etc.) using GIS, and we used a graph
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The alternatives of network modeling and simulation have been studied for many years. Some famous simulators/emulators, such as NS2  and ModelNet , have come forth. In our work, according to the theory of automata and discrete event system, we propose a formal description of network and worm models. By defining the virtualization levels, we then find different alternatives of network modeling and simulation have different expression capability. As mentioned above, current worm related research is mainly based on existing network simulators. However, these simulators mostly focus on the details of lower layers of the network so that the functions of application layer are greatly simplified. In addition, it is possible that packet level worm simulation will degrade the performance of these simulators.
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En el Network Marketing o Comercialización en Red, tu te beneficias del apalancamiento en la misma medida que te interesas en que tus consumidores y socios obtengan lo que desean. Esto obviamente genera un GANA-GANA para todas las partes involucradas: la empresa, los socios distribuidores y los consumidores.
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Another important function of the directory is to provide information for Celsius Instances to connect to each other and synchronize their tasks, which implies IP address or URL, ports, user name and password. Celsius Directory manages all the required information for each Celsius to have access to remote functions in other Celsius in the network, specially stressing in the security in order to avoid illegitimate access or remote procedure call and execution without the proper privileges.
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Abstract— Network Mobility (NEMO) Basic Support Protocol (NBSP) provides mobility supports for mobile networks. NBSP is an extension of Mobile IPv6 which employs a centralized mobility management approach. It relies on a static and centralized home agent for signaling management and data forwarding. All data traffic traverses a centralized home agent, which leads to sub-‐optimal routing, high packet overhead and latency, especially in nested NEMO (i.e. when the mobile networks connect to one another to reach the infrastructure). In this paper, we develop a network-‐based distributed mobility management (DMM) scheme for non-‐ nested and nested NEMO scenarios, with the goal of mitigating the aforementioned problems. Additionally, the proposed scheme improves the packet delivery and location update (i.e., binding update) costs. The paper discusses in detail the scheme’s design, operation mechanism and the performance evaluation analysis. The numerical results of the proposed scheme show significant improvement in packet overhead and latency as well as binding update and packet delivery costs.
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Reputation-based schemes define a method for keeping track of nodes’ actions in order to classify reliable and unreli- able nodes –. The main problem of this approach is distinguishing misbehaving nodes from those that can not retransmit packets due to energy constraints, channel fadings or simply natural disconnections. The assumption that a node shall forward always all the packets it receives is too hard for a network formed of -beyond others- small and handheld devices. On the other hand, nodes on some strategic points of the network will have more transmission requests than those on the periphery, and it will be unfair to punish them if they can not hold all the transport.
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In references [123, 124], the authors developed both linear and MIANN models for DPIs using 2D physicochemical properties of drugs, but 3D physicochemical properties (electrostatic potentials) of the protein. The accuracy of the best linear model was 94.4% (3,859/4,086 cases) for training and 94.9% (1,909/2,012 cases) for the external validation series. In addition, the model was implemented into the Web portal Bio-AIMS. In so doing, we called the new web server MIND-BEST , acronym of MARCH-INSIDE Nested Drug-Bank Exploration & Screening Tool. The URL for this server is http://bio-aims.udc.es/MIND-BEST.php. This on-line tool is based on PHP/HTML/Python and MARCH-INSIDE routines. This work also illustrates with two examples the practical uses of this server. The experiment 1 includes MIND-BEST prediction, synthesis, characterization, and MAO-A and MAO-B pharmacological assay of eight rasagiline derivatives, promising for anti-Parkinson drug design. Experiment 2 reports the sampling, parasite culture, sample preparation, 2-DE, MALDI-TOF and -TOF/TOF MS, MASCOT search, 3D structure modeling with LOMETS, and MIND-BEST prediction for different peptides found in the proteome of the bird parasite Trichomonas gallinae, which is promising for the discovery of antiparasite drug targets.
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and sigmoid were used, but researchers found out that ReLU layers work far better because the network is able to train a lot faster (because of the computational efficiency) without making a significant difference to the accuracy. It also helps to alleviate the vanishing gradient problem, which is the issue where the lower layers of the network train very slowly because the gradient decreases exponentially through the layers.
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According to Diudea and Gutman,(10) the physical and chemical properties of organic substances, which can be expected to depend on the area of the molecular surface and/or on the branching of the molecular carbon-atom skeleton, are usually well correlated with W. Among them, there are the heats of formation, vaporization and atomization, density, boiling point, critical pressure, refractive index, surface tension and viscosity of various, acyclic and cyclic, saturated and unsaturated as well as aromatic hydrocarbon species, velocity of ultrasound in alkanes and alcohols, rate of electroreduction of chlorobenzenes, etc. Correlations between W and melting points were also reported, but in this case the results were not completely satisfactory. W was also used to predict the behavior of organic substances in gas chromatography, for instance, chromatographic retention times (CRT) of monoalkyl- and o-dialkylbenzenes. In this sense, W is very useful in chemoinformatics for the search of models that connect the molecular structure with molecular properties.
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The concept of a virtual laboratory is not new. Virtual labs use software simulation of physical devices and systems. Remote labs offer remote access to real physical laboratory systems, e.g., to equipment, instruments and educational models, with the goal of their monitoring and control. The educational aspects are as important as the technological ones.
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Agencies commonly use deterioration indices for network level decision making, which may combine different types of surface distresses, serviceability and structural indicators (Wolters, A. et al. 2011). Examples of these indices are: Pavement Condition Index (PCI) (Reza, F. et al. 2006), Distress Manifestation Index for Network Level (DMI) (Chamorro et al. 2009b), Índice de Condición de Caminos Pavimentados (ICP) (MOP 2006), and Índice de Serviciabilidad (P) (MINVU 1999). Almost all these indices differ in the types of deterioration and criteria considered to quantify severity and density of distresses. However, these indices were developed for interurban road networks (highways, express corridor, etc.); therefore, their direct application to urban networks (streets, avenues, etc.), is not representative and requires calibration and validation. The Serviceability Index (P) (MINVU 1999) was defined for urban pavements but consider as an important characteristic the roughness rather than other distresses; then, .the analysis and calibration considering other distresses present in urban environment is needed for its application.
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(Lian, 2001a) makes a comparison between three popular control networks, including DeviceNet which is based on the standard CAN specification. The study identifies the key components of the time delay in NCS through an analysis of network protocols and network dynamics. In (Lian, 2001b) a timing analysis is presented where time delays are characterized by the networks parameters. Different processing time models were built based on histogram parameterization, a statistical ap- proach. The models can adopt four different con- figurations: zero, mean, normal and uniform. The zero processing model lets the processing time equals zero; the mean model uses the mean value as the processing time; the normal model assumes a normal distribution of the processing time; and the uniform model uniformly assigns the process- ing time for each message.
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Another study that can reflect the importance of including triadic effects is the work of Galaskiewicz and Burt (1991). As previously explained, the authors constructed a network of corporate contribution officers to detect mimetic behavior in corporate donations. The network consisted of each officer’s connections to their counterparts in other firms as well as those to local non-profit organizations. To test their hypothesis, they analyzed a panel data set using OLS and autocorrelation models. Although including structural equivalence proves to be helpful for detecting influence in their data, the exclusive dyadic approach might provide a limited view of how contribution officers influence each other without considering triadic influences. For example, the transitivity effect between two officers indirectly connected via a common third actor, whether a firm or a non-profit, might be relevant in determining whom a firm imitates for their corporate donations. Also, triadic effects are relevant especially for structural equivalence since indirect connections can change to direct over time.
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