With the increase in mobile traffic and the bandwidth demand, Device-to-Device (D2D) communication underlaying Long Term Evolution (LTE) networks has gained tremendous interest by the researchers, cellular operators and equipment manufacturers. Howev...
Despite recent progress in memory augmented neural network (MANN) research, associative memory networks with a single external memory still show limited performance on complex relational reasoning tasks. Especially the content-based addressable memor...
Some social networks, such as LinkedIn and ResearchGate, allow user endorsements for specific skills. In this way, for each skill we get a directed graph where the nodes correspond to users' profiles and the arcs represent endorsement relations. From...
In the present research, the effectiveness of large-scale Augmented Granger Causality (lsAGC) as a tool for gauging brain network connectivity was examined to differentiate between marijuana users and typical controls by utilizing resting-state funct...
Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while proper support from the programming language perspective has been consid...
There is an extensive body of research on Social Network Analysis (SNA) based on the email archive. The network used in the analysis is generally extracted either by capturing the email communication in From, To, Cc and Bcc email header fields or by...
I am looking to start copy trading - accounts on The Futures Network, Purdia Capital, Funded Futures Network and I still have one Topstep account. What is your experience with them? My research show...
Research on peer effects in sociology has been focused for long on social influence power to investigate the social foundations for social interactions. This paper extends Xu(2011)'s large--network--based game model by allowing for social-influence-d...
In recent years, the analysis of economic crime and corruption in procurement has benefited from integrative studies that acknowledge the interconnected nature of the procurement ecosystem. Following this line of research, we present a networks appro...
The rise of platforms like Netflix has expanded the possibility for audiences worldwide to watch the same content simultaneously, motivating research on cross-country media consumption. We investigate the global dynamics of media consumption by analy...
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Researchers use community-detection algorithms to reveal large-scale organization in biological and social networks, but community detection is useful only if the communities are significant and not a result of noisy data. To assess the statistical s...
We present a novel approach to automatically detect and classify great ape calls from continuous raw audio recordings collected during field research. Our method leverages deep pretrained and sequential neural networks, including wav2vec 2.0 and LSTM...
Recently, many researchers have studied efficiently gathering data in wireless sensor networks to minimize the total energy consumption when a fixed number of data are allowed to be aggregated into one packet. However, minimizing the total energy con...
The majority of the research on the quantization of Deep Neural Networks (DNNs) is focused on reducing the precision of tensors visible by high-level frameworks (e.g., weights, activations, and gradients). However, current hardware still relies on hi...
Activation functions play a decisive role in determining the capacity of Deep Neural Networks as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused...
OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and nei...
Current research in Computer Vision has shown that Convolutional Neural Networks (CNN) give state-of-the-art performance in many classification tasks and Computer Vision problems. The embedding of CNN, which is the internal representation produced by...
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Several studies claim that listening to Mozart music affects cognition and can be used to treat neurological conditions like epilepsy. Research into this Mozart effect has not addressed how dynamic interactions between brain networks, i.e. effective...