Search results for "network [detector]"
showing 10 items of 496 documents
Interpretability of Recurrent Neural Networks in Remote Sensing
2020
In this work we propose the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for multivariate time series of satellite data for crop yield estimation. Recurrent nets allow exploiting the temporal dimension efficiently, but interpretability is hampered by the typically overparameterized models. The focus of the study is to understand LSTM models by looking at the hidden units distribution, the impact of increasing network complexity, and the relative importance of the input covariates. We extracted time series of three variables describing the soil-vegetation status in agroe-cosystems -soil moisture, VOD and EVI- from optical and microwave satellites, as well as available in si…
Intermediate units and competence creation in the multinational firm: a network approach
2019
Multinational Corporations (MNCs) as economic and social actors have an enormous impact on the global economy. They have been acknowledged as the forefront of the technological and organizational developments (Lundan, 2018) while also presented as resource spoilers in other contexts (Narula, 2018). Currently, the economic environment MNCs face is determined by the fragmentation of the global production. Mainly, this is due to technological advances, the rise of emerging economies and liberalization policies (Narula, 2014) which have facilitated cross-border coordination of transactions (Kano, 2017). As a consequence, the MNC is assisting to the subsequent dispersion of its activities which …
Active Learning for Monitoring Network Optimization
2012
Kernel-based active learning strategies were studied for the optimization of environmental monitoring networks. This chapter introduces the basic machine learning algorithms originated in the statistical learning theory of Vapnik (1998). Active learning is closer to an optimization done using sequential Gaussian simulations. The chapter presents the general ideas of statistical learning from data. It derives the basics of kernel-based support vector algorithms. The active learning framework is presented and machine learning extensions for active learning are described in the chapter. Kernel-based active learning strategies are tested on real case studies. The chapter explores the use of a c…
The journalOsteuropaas a forum for Russian–German academic dialogue
2014
This article focuses on the interdisciplinary, monthly academic journal Osteuropa as a mediator between Russian and German academic discourses, and as a tool for bringing Russian perspectives closer to German intellectual audiences. The historical overview provided in this paper shall show the actors involved in the development of the journal since its founding at the beginning of the twentieth century. The actor–network theory and the Bourdieusian concepts of field and habitus will be deployed to reveal the academic networks Osteuropa is involved in and the role of the actors in them. Osteuropa's Russian collaborative partners and joint publication projects are presented in the paper. The …
An efficient adaptive strategy for searching in peer-to-peer networks
2005
One of the main technical challenges in Peer-to-Peer (P2P) networks is how to efficiently locate desired resources. Although structured systems, based on distributed hash tables, can achieve fair effectiveness, they are not suitable for widely deployed Internet applications. In fact, this kind of systems shows many severe limitations, such as ignoring the autonomous nature of peers, and supporting only weakly semantic functions. Unstructured P2P networks are more attractive for real applications, since they can avoid both the limitations of centralized systems, and the drawbacks of structured approaches. However, their search algorithms are usually based on inefficient flooding schemes, tha…
Increased structural white and grey matter network connectivity compensates for functional decline in early multiple sclerosis
2016
Background: The pathology of multiple sclerosis (MS) consists of demyelination and neuronal injury, which occur early in the disease; yet, remission phases indicate repair. Whether and how the central nervous system (CNS) maintains homeostasis to counteract clinical impairment is not known. Objective: We analyse the structural connectivity of white matter (WM) and grey matter (GM) networks to understand the absence of clinical decline as the disease progresses. Methods: A total of 138 relapsing–remitting MS patients (classified into six groups by disease duration) and 32 healthy controls were investigated using 3-Tesla magnetic resonance imaging (MRI). Networks were analysed using graph the…
Plasticity of brain wave network interactions and evolution across physiologic states
2015
Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions repre…
Alexithymia and personality traits of patients with inflammatory bowel disease
2017
AbstractPsychological factors, specific lifestyles and environmental stressors may influence etiopathogenesis and evolution of chronic diseases. We investigate the association between Chronic Inflammatory Bowel Diseases (IBD) and psychological dimensions such as personality traits, defence mechanisms, and Alexithymia, i.e. deficits of emotional awareness with inability to give a name to emotional states. We analyzed a survey of 100 patients with IBD and a control group of 66 healthy individuals. The survey involved filling out clinical and anamnestic forms and administering five psychological tests. These were then analyzed by using a network representation of the system by considering it a…
Impaired conflict resolution and vigilance in euthymic bipolar disorder.
2015
Abstract Difficulty attending is a common deficit of euthymic bipolar patients. However, it is not known whether this is a global attentional deficit or relates to a specific attentional network. According to the attention network approach, attention is best understood in terms of three functionally and neuroanatomically distinct networks-alerting, orienting, and executive control. In this study, we explored whether and which of the three attentional networks are altered in euthymic Bipolar Disorder (BD). A sample of euthymic BD patients and age-matched healthy controls completed the Attention Network Test for Interactions and Vigilance (ANTI-V) that provided not only a measure of orienting…
Threshold rule and scaling behavior in a multi-agent supply chain
2010
In this paper an agent-based model of self organized criticality is developed in a network economy characterized by lead time and a threshold behavior of firms. Instead of considering the aggregate production of the economy as a whole, we focus on both the propagation and amplification effects of a demand shock in the sectorial productions of a multi-agent supply chain. We study a static network structure representing a relation of firms in a lower-upper stream in an industrial organization. In our model, the individual (R, nQ) policies play an important role in generating a propagation effect across the different layers of the economy, and the propagation turns into the large fluctuations …