A Fuzzy Logic Approach To Modelling The Passengers’ Flow And Dwelling Time

The passengers’ flow and station dwell time estimation are important tasks for mass transit planning. However, classical methods are difficult to apply into some practical achievements. This paper presents a new approach that models passengers’ flow and its effect on passenger alighting and boarding time in mass transportation systems in the presence of uncertainties. The applied technique combines origin destination matrices approach with the application of artificial intelligence. This new approach allows the inclusion of some intuitive knowledge provided by a fuzzy logic inference motor to predict the flow demand of passengers’ trips, alighting and boarding time passenger cars in explicit stations.The passengers’ flow and station dwell time estimation are important tasks for mass transit planning. However, classical methods are difficult to apply into some practical achievements. This paper presents a new approach that models passengers’ flow and its effect on passenger alighting and boarding time in mass transportation systems in the presence of uncertainties. The applied technique combines origin destination matrices approach with the application of artificial intelligence. This new approach allows the inclusion of some intuitive knowledge provided by a fuzzy logic inference motor to predict the flow demand of passengers’ trips, alighting and boarding time passenger cars in explicit stations

A Fuzzy Logic Inference Approach for the Estimation of the Passengers Flow Demand

This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origin- destination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers’ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach.This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origin- destination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers’ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach

Morphological and structural evidences concerning the origin of sheet fractures

[Abstract] Sheet fractures are well and widely developed in massive rocks, i.e., rocks lacking other partings, and they have been discussed in the literature for more than a century. Yet there is no agreement as to their origino Two contrasted interpretations hold sway. Almost without exception, geologist adhere to the pressure release or erosional offloading hypothesis. Engineers and engineering geologist, on the other hand, interpret sheet partings as buckling, i.e., crumpling or bending out of plane, related to compressive stresses, particularly lateral stresses. After a review of nomenclature and a description of the characteristics of sheet fractures, a critique ofprevious explanations of their origin is presented. What are perceived to be critical Enes of structural and morphological evidence. bearing on the origin ofsheet fracture are next reviewed, and this is followed by a discusion of the possible origins of the structures

Lyapunov Based Stability Analysis for Metro Lines

In this work a direct method to measure the stability of metro system lines with respect to a previously constructed time schedule is presented. For this purpose we first model saturation effects using a real time discrete space state representation and then apply a Lyapunov-based stability analysis considering time delays of trains as disturbances. As a result we have been able to define a new set of indexes that relate time delays with the validity of the actual time schedule when falling inside a particular ‘stability area’. Results obtained in a simulated environment show that the new stability indexes are able to evaluate quantitatively and qualitatively the effects of saturation in metro lines as well as predict the need for rescheduling Keywords: metro system, stability, planning, genetic algorithm, artificial intelligence. 1 Introduction The dynamics of metro line systems have been deeply studied by several researchers [1–5,7–10]. Most of these dynamical models are based on the Sasama and Ohkawa [9] linear model. It is well known that such kind of linear models, usually yield simple formulation, implementation and simulation. As a result, some dynamic traffic linear controllers [1–3,7] and real time simulators [3,4] have been proposed.In this work a direct method to measure the stability of metro system lines with respect to a previously constructed time schedule is presented. For this purpose we first model saturation effects using a real time discrete space state representation and then apply a Lyapunov-based stability analysis considering time delays of trains as disturbances. As a result we have been able to define a new set of indexes that relate time delays with the validity of the actual time schedule when falling inside a particular ‘stability area’. Results obtained in a simulated environment show that the new stability indexes are able to evaluate quantitatively and qualitatively the effects of saturation in metro lines as well as predict the need for rescheduling Keywords: metro system, stability, planning, genetic algorithm, artificial intelligence. 1 Introduction The dynamics of metro line systems have been deeply studied by several researchers [1–5,7–10]. Most of these dynamical models are based on the Sasama and Ohkawa [9] linear model. It is well known that such kind of linear models, usually yield simple formulation, implementation and simulation. As a result, some dynamic traffic linear controllers [1–3,7] and real time simulators [3,4] have been proposed

New Advances on Modelling Control Processes applied to the Detection of Train Operations

In the main frame of the optimal control process has to be focused this work, where a methodology based on the performance of Genetic Algorithms to be used to search the appropriate knowledge base, defined in the sense of Fuzzy Logic, for the process controller. Two stages have to be considered to obtain the control system - Initial Stage and Conclusions Phase. First point search the control law for the reference functional point and defines design concepts and how to do it works. Second stage search allows adjusting the control action according to the dynamic of the process during its cycle-life

A Fuzzy Logic Inference Approach for the Estimation of the Passengers Flow Demand

This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origin destination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers’ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach

Upstream kinases of plant SnRKs are involved in salt stress tolerance

Sucrose non-fermenting 1-related protein kinases (SnRKs) are important for plant growth and stress responses. This family has three clades: SnRK1, SnRK2 and SnRK3. Although plant SnRKs are thought to be activated by upstream kinases, the overall mechanism remains obscure. Geminivirus Rep-Interacting Kinase (GRIK)1 and GRIK2 phosphorylate SnRK1s, which are involved in sugar/energy sensing, and the grik1-1 grik2-1 double mutant shows growth retardation under regular growth conditions. In this study, we established another Arabidopsis mutant line harbouring a different allele of gene GRIK1 (grik1-2 grik2-1) that grows similarly to the wild-type, enabling us to evaluate the function of GRIKs under stress conditions. In the grik1-2 grik2-1 double mutant, phosphorylation of SnRK1.1 was reduced, but not eliminated, suggesting that the grik1-2 mutation is a weak allele. In addition to high sensitivity to glucose, the grik1-2 grik2-1 mutant was sensitive to high salt, indicating that GRIKs are also involved in salinity signalling pathways. Salt Overly Sensitive (SOS)2, a member of the SnRK3 subfamily, is a critical mediator of the response to salinity. GRIK1 phosphorylated SOS2 in vitro, resulting in elevated kinase activity of SOS2. The salt tolerance of sos2 was restored to normal levels by wild-type SOS2, but not by a mutated form of SOS2 lacking the T168 residue phosphorylated by GRIK1. Activation of SOS2 by GRIK1 was also demonstrated in a reconstituted system in yeast. Our results indicate that GRIKs phosphorylate and activate SnRK1 and other members of the SnRK3 family, and that they play important roles in multiple signalling pathways in vivo.España, MINECO IO2015-70946-

Un algoritmo de replanificación en tiempo real basado en un índice de estabilidad de Lyapunov para líneas de metro

En este trabajo, se propone un nuevo índice basado en el método directo de Lyapunov para el diseño de un algoritmo de reprogramación en tiempo real para líneas de metro. En este estudio se utiliza una versión modificada de un modelo de espacio de estados en tiempo real discreto, que considera los efectos de saturación en la línea de metro. Una vez que el modelo de espacio de estados se ha obtenido, el método directo de Lyapunov se aplica con el fin de analizar la estabilidad del sistema de la línea de metro. Como resultado de este análisis no sólo se propone un nuevo índice de estabilidad, sino también la creación de tres zonas de estabilidad para indicar el estado actual del sistema. Finalmente, se presenta un nuevo algoritmo que permite la reprogramación del calendario de los trenes en tiempo real en presencia de perturbaciones medianas.En este trabajo, se propone un nuevo índice basado en el método directo de Lyapunov para el diseño de un algoritmo de reprogramación en tiempo real para líneas de metro. En este estudio se utiliza una versión modificada de un modelo de espacio de estados en tiempo real discreto, que considera los efectos de saturación en la línea de metro. Una vez que el modelo de espacio de estados se ha obtenido, el método directo de Lyapunov se aplica con el fin de analizar la estabilidad del sistema de la línea de metro. Como resultado de este análisis no sólo se propone un nuevo índice de estabilidad, sino también la creación de tres zonas de estabilidad para indicar el estado actual del sistema. Finalmente, se presenta un nuevo algoritmo que permite la reprogramación del calendario de los trenes en tiempo real en presencia de perturbaciones medianas

Desigualdades en Salud: La Mortalidad Perinatal e Infantil en España

ResumenSe ha considerado al coeficiente de variación interprovincial (CV) como un indicador objetivo de la dispersión de los valores provinciales de las tasas de mortalidad infantil, neonatal, postneonatal y perinatal. Así, se ha estudiado la evolución de los CV anuales, para las cuatro tasas, desde 1940 hasta 1986, con objeto de identificar la evolución temporal de las diferencias interprovinciales con respecto a dichas tasas de mortalidad. Se observa que en ningún caso los CV muestran una tendencia decreciente en el tiempo, lo que parece indicar que las desigualdades interregionales permanecen inalteradas. La tasa de mortalidad postneonatal es la que mayor dispersión presenta en sus valores provinciales durante el período estudiado (CV entre 23 y 40%), y su evolución es independiente de la de la tasa de mortalidad neonatal, lo que parece indicar que los factores que influyen en ambas son diferentes.SummaryThe interregional variation coefficient (VC)) has been considered as an accurate measure of the dispersion of regional infant, neonatal, postneonatal and perinatal mortality rates. Thus, trends of annual VC have been analyzed, for each rate, from 1940 to 1986, to identify the evolution in time of the regional differences with respect to these mortality rates. None of the four mortality rates showed a decreasing trend in their respective VCs. This may indicate that interregional differences do not change along time. The postneonatal mortality rate has been shown to have the highest VCs during the study period (ranging from 23 to 40%), with an independent evolution with respect to neonatal mortality rate, probably because the factors that influence both rates are clearly different

2023 26th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)

Network Slicing (NS) is a key enabler of the 5G network ecosystem due to its potential to provide distinct services over the same physical infrastructure. However, the necessity to optimally orchestrate resources for heterogeneous demands is crucial when dealing with resource constraints and Quality-of-Service (QoS) requirements. We consider a radio access network scenario providing NS over multiple base stations (BS) with limited resources, and we design an efficient resource orchestration technique, based on reinforcement learning, which optimizes resource utilization among different services while satisfying the constraints and complying with Service Level Agreement (SLA) and QoS requirements. The proposed technique makes use of the Trust Region Method to formulate the orchestration objective function and satisfy the constraints and is then optimized via Kronecker Factored Approximate Curvature (K-FAC). Extensive simulations demonstrate that the proposed technique outperforms other Reinforcement Learning (RL) algorithms, reaching 99% of QoS and SLA satisfaction while assuring bandwidth constraints.EU H2020 MSCA ITN-ETN IoTalentum (grant no. 953442)Consejería de Educación de la Junta de Castilla y León y FEDER (VA231P20)Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033