AbstractInteractions between units in political systems often occur across multiple relational contexts. These relational systems feature interdependencies that result in inferential shortcomings and poorly-fitting models when ignored. General advancements in inferential network analysis have improved our ability to understand relational systems featuring interdependence, but developments specific to working with interdependence that cross relational contexts remain sparse. In this paper, I introduce a multilayer network approach to modeling systems comprising multiple relations using the exponential random graph model. In two substantive applications, the first a policy communication network and the second a global conflict network, I demonstrate that the multilayer approach affords inferential leverage and produces models that better fit observed data.
Personal safety is a critical aspect of daily life, but also in the military. Active soldiers often have to carry heavy gear during missions, which puts pressure on their backs. Therefore, the military must come up with new technologies that allow both protection and movement. In this paper, it is explaining the development of an armored upper limb exoskeleton with three degrees of freedom. To ensure portability, it is used battery-fed DC actuators. The system was encased in a metal matrix that doubles up as a protective plate. The exoskeleton, the control system, the actuators, and the plate are integrated so that they offer protection while supporting the flexion and extension of the upper limb.
Purpose – In this paper we propose an iterative approach for the deployment of rural telecommunication networks. Methodology/approach/design – This approach relies heavily on the concept of locality, prioritizing small 'cells' with a considerable population density, and exploits the natural nesting of the distribution of rural communities, focusing in communities which are populous enough to justify the investment required to provide them with connectivity, and whose sheer size promotes the formation of 'satellite' communities that could be benefited from the initial investment at a marginal expense. For this approach, the concept of 'cells' is paramount, which are constructed iteratively based on the contour of a Voronoi tessellation centered on the community of interest. Once the focal community has been 'connected' with network of the previous layer, the process is repeated with less populous communities at each stage until a coverage threshold has been reached. One of the main contributions of this methodology is that it makes every calculation based on 'street distance' instead of Euclidean, giving a more realistic approximate of the length of the network and hence the amount of the investment. To test our results, we ran our experiments on two segregated communities in one of the most complicated terrains, due to the mountain chains, in the state of Chiapas, Mexico. Findings – The results suggest that the use of 'street distance' and a local approach leads to the deployment of a remarkably different network than the standard methodology would imply. Practical implications – The results of this paper might lead to a significant reduction in the costs associated with these kinds of projects and therefore make the democratization of connectivity a reality. In order to make our results reproducible, we make all our code open and publicly available on GitHub. ; Purpose – In this paper we propose an iterative approach for the deployment of rural telecommunication networks. Methodology/approach/design – This approach relies heavily on the concept of locality, prioritizing small 'cells' with a considerable population density, and exploits the natural nesting of the distribution of rural communities, focusing in communities which are populous enough to justify the investment required to provide them with connectivity, and whose sheer size promotes the formation of 'satellite' communities that could be benefited from the initial investment at a marginal expense. For this approach, the concept of 'cells' is paramount, which are constructed iteratively based on the contour of a Voronoi tessellation centered on the community of interest. Once the focal community has been 'connected' with network of the previous layer, the process is repeated with less populous communities at each stage until a coverage threshold has been reached. One of the main contributions of this methodology is that it makes every calculation based on 'street distance' instead of Euclidean, giving a more realistic approximate of the length of the network and hence the amount of the investment. To test our results, we ran our experiments on two segregated communities in one of the most complicated terrains, due to the mountain chains, in the state of Chiapas, Mexico. Findings – The results suggest that the use of 'street distance' and a local approach leads to the deployment of a remarkably different network than the standard methodology would imply. Practical implications – The results of this paper might lead to a significant reduction in the costs associated with these kinds of projects and therefore make the democratization of connectivity a reality. In order to make our results reproducible, we make all our code open and publicly available on GitHub. ; Purpose – In this paper we propose an iterative approach for the deployment of rural telecommunication networks. Methodology/approach/design – This approach relies heavily on the concept of locality, prioritizing small 'cells' with a considerable population density, and exploits the natural nesting of the distribution of rural communities, focusing in communities which are populous enough to justify the investment required to provide them with connectivity, and whose sheer size promotes the formation of 'satellite' communities that could be benefited from the initial investment at a marginal expense. For this approach, the concept of 'cells' is paramount, which are constructed iteratively based on the contour of a Voronoi tessellation centered on the community of interest. Once the focal community has been 'connected' with network of the previous layer, the process is repeated with less populous communities at each stage until a coverage threshold has been reached. One of the main contributions of this methodology is that it makes every calculation based on 'street distance' instead of Euclidean, giving a more realistic approximate of the length of the network and hence the amount of the investment. To test our results, we ran our experiments on two segregated communities in one of the most complicated terrains, due to the mountain chains, in the state of Chiapas, Mexico. Findings – The results suggest that the use of 'street distance' and a local approach leads to the deployment of a remarkably different network than the standard methodology would imply. Practical implications – The results of this paper might lead to a significant reduction in the costs associated with these kinds of projects and therefore make the democratization of connectivity a reality. In order to make our results reproducible, we make all our code open and publicly available on GitHub.
Mobile communications are growing and the number of users is constantly increasing at an accelerated rate, as well as the demand for the services they request. In the last few years, many efforts have focused on the design and deployment of the new fifth generation (5G) cellular networks. However, novel highly demanding applications, which are already emerging, need to go beyond 5G in order to meet the requirements in terms of network performance. But, at the same time, as the Earth does not allow us to increase the carbon footprint anymore, the energy consumption of the communication networks has to be critically taken into consideration. A multi-objective approach for addressing all these issues is therefore required. This work develops a cellular network framework that allows the evaluation of different system parameters over dynamic traffic patterns, as well as optimizing the different conflicting objectives simultaneously. The novelty relies on that the optimization process integrates key performance indicators from different layers of the network, namely the radio and the network layers, aiming at reaching solutions that account for the power consumption of the base stations, the total capacity provided to mobile users and also the signaling cost generated by handovers. Moreover, new metrics are needed to evaluate different solutions. Starting from the well-known energy efficiency merit factor (bits/Joule), three new merit factors are proposed to classify the network performance since they take into account several network parameters at the same time. These indicators show us the ideal working point that can be used to plan the point of operation of the network. These operation points are a medium-high power and capacity load and a low signaling load. ; Spanish National Program of Research, Development, Innovation TIN2016-75097-P RTI2018-102002-A-I00 EQC2018-004988-P ; Junta de Andalucía B-TIC-402-UGR18 ; European Union (EU) IB18003 ; Junta de Extremadura IB18003 ; FPU19/01251 ; FPU18/01965
Transportation networks, from bicycle paths to buses and railways, are the backbone of urban mobility. In large metropolitan areas, the integration of different transport modes has become crucial to guarantee the fast and sustainable flow of people. Using a network science approach, multimodal transport systems can be described as multilayer networks, where the networks associated to different transport modes are not considered in isolation, but as a set of interconnected layers. Despite the importance of multimodality in modern cities, a unified view of the topic is currently missing. Here, we provide a comprehensive overview of the emerging research areas of multilayer transport networks and multimodal urban mobility, focusing on contributions from the interdisciplinary fields of complex systems, urban data science, and science of cities. First, we present an introduction to the mathematical framework of multilayer networks. We apply it to survey models of multimodal infrastructures, as well as measures used for quantifying multimodality, and related empirical findings. We review modeling approaches and observational evidence in multimodal mobility and public transport system dynamics, focusing on integrated real-world mobility patterns, where individuals navigate urban systems using different transport modes. We then provide a survey of freely available datasets on multimodal infrastructure and mobility, and a list of open-source tools for their analyses. Finally, we conclude with an outlook on open research questions and promising directions for future research.