Search results for "Networks"
showing 10 items of 3260 documents
Water adsorption on amorphous silica surfaces: A Car-Parrinello simulation study
2005
A combination of classical molecular dynamics (MD) and ab initio Car-Parrinello molecular dynamics (CPMD) simulations is used to investigate the adsorption of water on a free amorphous silica surface. From the classical MD SiO_2 configurations with a free surface are generated which are then used as starting configurations for the CPMD.We study the reaction of a water molecule with a two-membered ring at the temperature T=300K. We show that the result of this reaction is the formation of two silanol groups on the surface. The activation energy of the reaction is estimated and it is shown that the reaction is exothermic.
AIOC2: A deep Q-learning approach to autonomic I/O congestion control in Lustre
2021
Abstract In high performance computing systems, I/O congestion is a common problem in large-scale distributed file systems. However, the current implementation mainly requires administrator to manually design low-level implementation and optimization, we proposes an adaptive I/O congestion control framework, named AIOC 2 , which can not only adaptively tune the I/O congestion control parameters, but also exploit the deep Q-learning method to start the training parameters and optimize the tuning for different types of workloads from the server and the client at the same time. AIOC 2 combines the feedback-based dynamic I/O congestion control and deep Q-learning parameter tuning technology to …
WORDY: a Semi-automatic Methodology aimed at the Creation of Neologisms based on a Semantic Network and Blending Devices
2017
In this paper, we propose a semi-automatic tool, named WORDY, that implements a methodology aimed at speeding-up the pro- cess of creation of neologisms. The approach exploits a semantic network, which is explored through the spreading activation methodology and ex- ploits three blending linguistic techniques together with a proper ranking function in order to support companies in the creation of neologisms ca- pable of evoking semantic meaningful associations to customers.
DEMO: Unconventional WiFi-ZigBee communications without gateways
2014
Nowadays, the overcrowding of ISM bands is becoming an evident limitation for the performance and widespread usage of 802.11 and 802.15.4 technologies. In this demo, we prove that it is possible to opportunistically exploit the inter-technology interference between 802.11 and 802.15.4 to build an unconventional low-rate communication channel and signalling protocol, devised to improve the performance of each contending technology. Differently from previous solutions, inter-technology communications do not require the deployment of a gateway with two network interfaces, but can be activated (when needed) directly between two heterogeneous nodes, e.g. a WiFi node and a ZigBee node. This capab…
Enabling Backoff for SCM Wake-Up Radio: Protocol and Modeling
2017
In sub-carrier modulation (SCM) wake-up radio (WuR) enabled wireless sensor networks, a node can initiate data transmission at any instant of time. In this letter, we propose to activate a backoff procedure before sending wake-up calls (WuCs) in order to avoid potential collisions among WuCs. Consequently, no backoff is needed for the main radio after a WuC is received. A discrete-time Markov chain model is developed to evaluate the performance. Numerical results on network throughput, energy efficiency, average delay, and collision probability reveal the benefits of enabling backoff for SCM-WuRs, especially under heavy traffic loads or saturated traffic conditions.
Empirically-derived subgroups of Facebook users and their association with personality characteristics: a Latent Class Analysis
2018
Abstract In recent years, considerable research effort has been directed at the identification of relationships between psychological variables and Facebook usage indicators. However, the identification of homogeneous subgroups of individuals based on similar Facebook usage characteristics still presents a challenge. This study aims: (1) to empirically determine homogeneous groups of Facebook users based on variables regarding their personal experience on Facebook, by using a Latent Class Analysis; and (2) to examine the association between an individual's personality and interpersonal characteristics and the empirically-derived profiles of Facebook usage. Eight hundred and eleven Facebook …
Mammogram Segmentation by Contour Searching and Mass Lesions Classification with Neural Network
2006
The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting masses in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration (Medical Applications on a Grid Infrastructure Connection). A reduction of the whole image's area under investigation is achieved through a segmentation process, by means of a ROI Hunter algorithm, without loss of meaningful information. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters.…
Automatic image-based identification and biomass estimation of invertebrates
2020
1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based ident…
USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
2019
Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, the capability to differentiate between the blurry boundary of the Central Gland (CG) and Peripheral Zone (PZ) can lead to differential diagnosis, since tumor's frequency and severity differ in these regions. To tackle the prostate zonal segmentation task, we propose a novel Convolutional Neural Network (CNN), called USE-Net, which incorporates Squeeze-and-Excitation (SE) blocks into U-Net. Especially, the SE blocks are added after every Encoder (Enc USE-Net) or Encoder-Decoder block (Enc-Dec USE-Net). This study ev…
Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks
2020
We consider an epidemic process on adaptive activity-driven temporal networks, with adaptive behaviour modelled as a change in activity and attractiveness due to infection. By using a mean-field approach, we derive an analytical estimate of the epidemic threshold for SIS and SIR epidemic models for a general adaptive strategy, which strongly depends on the correlations between activity and attractiveness in the susceptible and infected states. We focus on strong social distancing, implementing two types of quarantine inspired by recent real case studies: an active quarantine, in which the population compensates the loss of links rewiring the ineffective connections towards non-quarantining …