810 Works

Overlapping identities: The role of village and occupational group for small-scale fishers’ perceptions on environment and governance

Stefan Gehrig, Achim Schlüter & Narriman Jiddawi
The capsule contains all data, analysis and results of the original research article "Overlapping identities: The role of village and occupational group for small-scale fishers’ perceptions on environment and governance". Abstract: Resource users’ perceptions are crucial for successful marine governance, because they affect community support, participation and legitimacy. Efforts have been made to understand how fishers’ attitudes, understandings and interpretations of the environment and its use emerge in small-scale fisheries. However, many quantitative studies have...

Symmetric Bilinear Regression

Lu Wang
Matlab code for fitting a symmetric bilinear model with L1 regularization (https://arxiv.org/abs/1804.09567). This model is useful in identifying a set of small subgraphs from a large graph that contain useful information about a response. The code implements a coordinate descent algorithm to estimate the model. We attach the simulated data in the simulation study to illustrate how to use this method.

Wandering Spurs in MASH 1-1 Delta-Sigma Modulators

Yann Donnelly & Michael Peter Kennedy
Abstract: Wandering spurs are a little-studied phenomenon seen in MASH and SQ-DDSM modulators. They take the form of frequency-modulated spurs which periodically appear in-band. Since modulators are often employed as divide ratio controllers in fractional-N phase lock loops, these spurs can feed into the output phase noise spectrum. In this paper we explain the mechanism which creates the wandering spurs, and offer a prediction for the behavior of these spurs in the MASH 1-1 modulator....

Semi-Laplacian-deep-network

Haikel Alhichri, Yakoub Bazi, Nassim Ammour & Mansour Alzuair
This paper deals with the problem of the classification of large-scale very high resolution (VHR) remote sensing (RS) images and in a semi-supervised scenario where we have a limited training set. Typical pixel-based classification methods are unfeasible for large-scale VHR images, and so as a practical and efficient solution, we propose to subdivide the large image into a grid of tiles, and then classify the tiles instead. Our proposed method uses the power of a...

MATLAB codes for optimization under unitary matrix constraint

Traian Emanuel Abrudan
*** Matlab codes for optimization under unitary matrix constraint Author of the codes: Traian Emanuel Abrudan (joint work with Jan Eriksson and Visa Koivunen) SMARAD CoE, Department of Signal Processing and Acoustics, Aalto Univestity, Espoo, Finland ** General description This set of codes may be used to optimize a smooth (differentiable) cost function J (W) over the Lie group of n × n unitary matrices. The codes we provide can be used to either minimize...

Cardiac pulsatility mapping and vessel type identification using laser speckle contrast imaging

Dmitry Postnov, Sefik Evren Erdener, Kivilcim Kilic & David A. Boas
Exemplary code and data for figures generation (figures may not fully correspond to the published version). Additional code details: https://github.com/BUNPC/laserSpeckleImaging (runPulsatilityBasedIdentification.m)

(Quasi)periodicity in Videos Using Sliding Windows And Topology

Christopher Tralie & Jose Perea
ARXIV LINK: https://arxiv.org/pdf/1704.08382.pdf ABSTRACT: This work introduces a novel framework for quantifying the presence and strength of recurrent dynamics in video data. Specifically, we provide continuous measures of periodicity (perfect repetition) and quasiperiodicity (superposition of periodic modes with non-commensurate periods), in a way which does not require segmentation, training, object tracking or 1-dimensional surrogate signals. Our methodology operates directly on video data. The approach combines ideas from nonlinear time series analysis (delay embeddings) and computational...

Analytical approach to transforming filter design for sound field recording and reproduction using circular arrays with a spherical baffle

Shoichi Koyama, Ken'ichi Furuya, Keigo Wakayama, Suehiro Shimauchi & Hiroshi Saruwatari
A sound field recording and reproduction method using circular arrays of microphones and loudspeakers with a spherical baffle is proposed. The spherical baffle is an acoustically rigid object on which the microphone array is mounted. The driving signals of the loudspeakers must be obtained from the signals received by the microphones. A transform filter for this signal conversion is analytically derived, which is referred to as the wave field reconstruction filter. The proposed method using...

Competition EEG

Nicole S. Rafidi, Justin C. Hulbert, Paula Pacheco & Kenneth A. Norman
Code for reproducing the main analysis of: Reductions in Retrieval Competition Predict the Benefit of Repeated Testing Nicole S. Rafidi, Justin C. Hulbert, Paula Pacheco, and Kenneth A. Norman Reproduces Figure 7 and with modifications can reproduce Figures S2-4

Hypercube Clustering

Oscar LiJen Hsu & Che-Rung Lee
Conventional sub-trajectory clustering is used to identify similarities among multiple trajectories. This method has been applied to traffic routes in urban areas as well as hurricane behavior. Existing methods tend to overlook many relevant sub-trajectories; others require a road network as input; all are slowed down considerably by large datasets. In this paper, we design a novel approach to sub-trajectory clustering in which trajectories are transformed into a set of hypercubes with four dimensions. The...

Data and figure scripts supporting The Arabidopsis thaliana pan-NLRome

Freddy Monteiro
Publication Summary: Disease is both among the most important selection pressures in nature and among the main causes of yield loss in agriculture. In plants, resistance to disease is often conferred by Nucleotide-binding Leucine-rich Repeat (NLR) proteins. These proteins function as intracellular immune receptors that recognize pathogen proteins and their effects on the plant. Consistent with evolutionarily dynamic interactions between plants and pathogens, NLRs are known to be encoded by one of the most variable...

Machine Learning Techniques for Detecting Identifying Linguistic Patterns in the News Media

A Samuel Pottinger
Code and reference configurations used in research for https://whowrotethis.com and "Machine Learning Techniques for Detecting Identifying Linguistic Patterns in the News Media" by A. Samuel Pottinger. Released under the MIT license. For data, please see https://whowrotethis.com.

Enhanced PUMA for direction-of-arrival estimation and its performance analysis

Cheng Qian
Direction-of-arrival (DOA) estimation is a problem of significance in many applications. In practice, due to the occurrence of coherent signals and/or when the number of available snapshots is small, it is a challenge to find DOAs accurately. This problem is revisited here through a new enhanced principal-singular-vector utilization for modal analysis (EPUMA) DOA estimation approach, which improves the threshold performance by first generating ($P+K$) DOA candidates for $K$ sources where $P\geq K$, and then judiciously...

Data Detection in Single User Massive MIMO Using Re-Transmissions

K. Vasudevan, K. Madhu & Shivani Singh
Single user massive multiple input multiple output (MIMO) can be used to increase the spectral efficiency, since the data is transmitted simultaneously from a large number of antennas located at both the base station and mobile. It is feasible to have a large number of antennas in the mobile, in the millimeter wave frequencies. However, the major drawback of single user massive MIMO is the high complexity of data recovery at the receiver. In this...

Estimation of Input-Output Curve in Transcranial Magnetic Stimulation (TMS) Using Sequential Sampling and Fisher Information

Seyed Mohammad Mahdi Alavi, Stefan M. Goetz & Angel V. Peterchev
This package presents a Fisher information matrix based sequential parameter estimation (FIM-SPE) method for fast and optimal estimation of input--output (IO) curve and its parameters in brain stimulation and specifically transcranial magnetic stimulation (TMS).

A Computational Framework for Cortical Learning

Roland Suri
A Computational Framework for Cortical Learning Roland E. Suri*, Biological Cybernetics, https://doi.org/10.1007/s00422-004-0487-1 Recent physiological findings revealed that long-term adaptation of the synaptic strengths between cortical pyramidal neurons depends on the temporal order of presynaptic and postsynaptic spikes, which is called Temporally Asymmetric Hebbian (TAH) learning. Here I prove by analytical means that a physiologically plausible variant of TAH learning adapts synaptic strengths such that the presynaptic spikes predict the postsynaptic spikes. This hypothesis implies a...

Análisis univariado de series de tiempo. Índice de confianza del consumidor.

Rodrigo Taborda
Código que lleva a cabo análisis univariado de serie de tiempo. 0. Carga datos, manipula para análisis de serie de tiempo. 1. Gráfica de serie de tiempo. 2. Gráfica de auto-correlación (AC) y auto-correlación parcial (PAC). 3. Generación valores correspondientes de la AC y PAC.

OCT_calibration: Simple and robust calibration procedure for k-linearization and dispersion compensation in optical coherence tomography

Xavier Attendu & Roosje M. Ruis
This script performs the calibration procedure to extract k-linearization interpolation indices as well as a dispersion compensation complex window. It requires as input two interferograms from mirror measurements on either side of the zero-delay plane (one on each side). The interference signals should be corrected for background and DC.

City-scale car traffic and parking density maps from Uber Movement travel time data

Arsam Aryandoust
We are given the arithmetic mean of hourly travel time measurements between different zones of a city and want to estimate the traffic flow and spatial parking distribution of cars in that city. In a first stage, we estimate the probabilities of car traffic between zones as a function of mean travel times. These probabilities exploit the changes in mean travel time between the zones of the city throughout a day to approximate information about...

Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features

Kuangen Zhang, Ming Hao, Jing Wang, Clarence W. De Silva & Chenglong Fu
We propose a linked dynamic graph CNN (LDGCNN) to classify and segment point cloud directly. We remove the transformation network, link hierarchical features from dynamic graphs, freeze feature extractor, and retrain the classifier to increase the performance of LDGCNN.

Cognition Open Data (COD) Reproducibility Report: jCSIW

Tom Hardwicke
This is one of 35 analytic reproducibility reports arising from the Cognition Open Data (COD) project. jCSIW is the ID code used to refer to this specific report. The COD project involved attempting to reproduce a subset of key target outcomes reported in 35 articles published in the journal Cognition by repeating the original analyses upon the original data. For more details, please visit the Open Science Framework project: https://osf.io/wn8fd/.

Subgroup Analysis Template

James Andrew Watson & Chris Holmes
This computational notebook (written in R) runs an exploratory subgroup analysis on the SEAQUAMAT trial data. This implements and illustrates the concepts of Holmes & Watson (2018) for exploratory subgroup analysis using Machine Learning protocols with valid control of the type I error. SEAQUAMAT was a multi-centre randomised controlled trial comparing mortality between intravenous quinine and intravenous artesunate in adults with severe malaria in South East Asia. The code is as generic as possible in...

Frangi-Net on High-Resolution Fundus (HRF) image database

Weilin Fu
This capsule holds the code for Frangi-Net experiment on High-Resolution Fundus (HRF) Image Database. We reformulate the conventional multi-scale 2-D Frangi vesselness measure into a pre-weighted neural network ("Frangi-Net"). Without training, Frangi-Net is equivalent to the original Frangi filter. With further training, the segmentation performance of the network is increased.

Populating the Data Ark: An attempt to retrieve, preserve, and liberate data from the most highly-cited psychology and psychiatry articles

Tom Hardwicke & John Ioannidis
The vast majority of scientific articles published to-date have not been accompanied by concomitant publication of the underlying research data upon which they are based. This state of affairs precludes the routine re-use and re-analysis of research data, undermining the efficiency of the scientific enterprise, and compromising the credibility of claims that cannot be independently verified. It may be especially important to make data available for the most influential studies that have provided a foundation...

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