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Cognition Open Data (COD) Reproducibility Report: DvcDF

Tom Hardwicke
This is one of 35 analytic reproducibility reports arising from the Cognition Open Data (COD) project. DvcDF 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/.


Wei Dongdong
The fleet assignment problem (FAP) is to study the method which assigns aircraft type to the scheduled flights, considering equipment capabilities and availabilities, operational costs and potential revenues. In this paper, a simple optimization model of FAP is proposed, which considers spill costs, in order to maximize the total profit. The fleet assignment solution must satisfy cover constraints, aircraft usage constraints and availability constraints. In order to solve the model, an improved partheno-genetic algorithm (IPGA)...

​Supplementary code for: Symbol Error Rate Model for Communication Using Femtosecond Pulses for Space Applications

E. Weiss, D. Bykhovsky & S. Arnon
This code provides numerical simulation to evaluate the performance of soft-decoded multiple-inverse- pulse-position modulation (MIPPM). The goal of this simulation is to validate the theoretical symbol error rate (SER) expression in the paper. The simulation also include the comparison to the theoretical upper-bound (UB).

GOtrack analysis: Monitoring changes in the Gene Ontology and their impact on genomic data analysis

Matthew Jacobson, Adriana Estela Sedeño-Cortés & Paul Pavlidis
To facilitate informed use of the Gene Ontology (http://www.geneontology.org/), we developed GOtrack (https://gotrack.msl.ubc.ca/ ), which provides access to historical records and trends in the Gene Ontology and GO annotations (GOA). The code and data provided here reproduces the figures and main analyses reported in the cited publication, including exploratory analyses of the data and documentation of the effects of GO/GOA changes on "enrichment analysis" over time.

Feature Selection Based on High Dimensional Model Representation

Gülşen Taşkın, Hüseyin Kaya & Lorenzo Bruzzone
This project provides the implementation of the algorithm proposed in the article "Feature Selection Based on High Dimensional Model Representation for Hyperspectral Images" (DOI:10.1109/TIP.2017.2687128). The project also contains the implementations of the other feature selection algorithms used in the article. In order to give the users the ability to recreate the results in article, the datasets and a couple of visualisation scripts are also provided. By running the algorithm, you will use eight different feature...

Robust Target Localization Based on Squared Range Iterative Reweighted Least Squares

Alireza Zaeemzadeh, Mohsen Joneidi, Behzad Shahrasbi & Nazanin Rahnavard
In this paper, the problem of target localization in the presence of outlying sensors is tackled. This problem is important in practice because in many real-world applications the sensors might report irrelevant data unintentionally or maliciously. We propose a localization method based on robust statistics, seeking to eliminate the effect of outliers. The main goal is to achieve optimal or near-optimal performance for different outlier types and different contamination ratios. The problem is formulated by...

optfrog - Analytic signal spectrograms with optimized time-frequency resolution (code and data)

O. Melchert, B. Roth, U. Morgner & A. Demircan
This Code Ocean capsule comprises examples demonstrating the optfrog Python-tool for the calculation of spectrograms with optimized time and frequency resolution for the analysis of numerical simulations on ultrashort pulse propagation.


Mahdi S. Hosseini, Yueyang Zhang & Konstantinos N. Plataniotis
A MATLAB package for No-Reference (NR) Image Sharpness Assessment (ISA) of Natural Images

Sampling Clustering

Tarn Yeong Ching
We propose an efficient graph-based divisive cluster analysis approach called sampling clustering. It constructs a lite informative dendrogram by recursively dividing a graph into subgraphs. In each recursive call, a graph is sampled first with a set of vertices being removed to disconnect latent clusters, then condensed by adding edges to the remaining vertices to avoid graph fragmentation caused by vertex removals. We also present some sampling and condensing methods and discuss the effectiveness in...

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.

Fitness Dependent Optimizer FDO - JAVA

Jaza Mahmood Abdullah
This code is a JAVA implementation of novel swarm intelligent algorithm , known as the fitness dependent optimizer (FDO). The bee swarming reproductive process and their collective decision-making have inspired this algorithm; it has no algorithmic connection with the honey bee algorithm or the artificial bee colony algorithm.

Distributed Energy Trading: The Multiple-Microgrid Case

David Gregoratti & Javier Matamoros
Optimization algorithm that minimizes the global cost of a system of interconnected microgrids that can trade energy to one another (see associated article for the details).

EMPOWER Pencil Beam

Thomas McIntyre
This capsule contains the Biomedical Optics Pencil Beam simulation using EMPOWER. I've added the Monte Carlo Results to the program so they may be better compared.

Simple Numerical Analysis of the Multi-looked Interferometric Phase Error for K-distributed signals

Paco Lopez Dekker
A simple numerical simulation to evaluate the multi-looked interferometric phase error for K-distributed speckle and compare it with the typical case of circular-Gaussian homogeneous speckle. Since the amplitude distribution has a longer tail, the (confirmed) expectation is that the phase uncertainty increases (dominant scatterers reduce the effective number of looks)

Intersubject functional correlation (ISFC) as a function of attention

Mor Regev, Erez Simony, Katherine Lee, Kean Ming Tan, Janice Chen & Uri Hasson
This capsule demonstrates the inter-subject functional correlation (ISFC) analysis described in "Propagation of information along the cortical hierarchy as a function of attention while reading and listening to stories " by Regev, Simony, Lee, Tan, Chen and Hasson.

Results Analysis: Modeling Non-Uniform Memory Access on Large Compute Nodes with the Cache-Aware Roofline Model

Brice Goglin, Emmanuel Jeannot, Aleksandar Ilic, Leonel Sousa & Nicolas Denoyelle
The Cache-Aware Roofline Model (CARM) is an insightful, yet simple model designed to address this issue. It provides feedback on potential applications bottlenecks and shows how far is the application performance from the achievable hardware upper-bounds. However, it does not encompass NUMA systems and next generation processors with heterogeneous memories. Yet, some application bottlenecks belong to those memory subsystems, and would benefit from the CARM insights. In this paper, we fill the missing requirements to...

R script and data for: A research note regarding "Variation in cancer risk among tissues can be explained by the number of stem cell divisions"

Maxime Tarabichi & Vincent Detours
Tomasetti and Vogelstein argued that 2/3 of human cancers are due to ‘bad luck’ and that “primary prevention measures [against cancer] are not likely to be very effective”. We demonstrate that their calculations for hepatocellular carcinomas overlooked a major subset of these cancers proven to be preventable through vaccination. The problem, which is not limited to hepatocellular carcinoma, arises from the general reliance of their analysis on average incidences in the United States and the...

MRI-only Proton: bulk assigned pseudo-CT images generation with Air

Matteo Maspero, Cornelis A T Van Den Berg, Guillaume Landry, Claus Belka, Katia Parodi, Peter R Seevinck, Bas W Raaymakers & Christopher Kurz
This work aims at exploring the feasibility of MR-only proton Radiotherapy for prostate cancer patients. The matlab code to produce bulk assigned pseudo-CT (pCT) with internal air cavities. The code is intended to integrate the pCTs originally produced with a commercial solution. The description of the method has been presented in Maspero et al., 2017, Physics in Medicine and Biology, "Feasibility of MR-only proton dose calculations for prostate cancer radiotherapy using a commercial pseudo-CT generation...

Voice Conversion using GMM with Enhanced Global Variance

Hadas Benisty & David Malah
The goal of voice conversion is to transform a sentence said by one speaker, to sound as if another speaker had said it. The classical conversion based on a Gaussian Mixture Model and several other schemes suggested since, produce muffled sounding outputs, due to excessive smoothing of the spectral envelopes. To reduce the muffling effect, enhancement of the Global Variance (GV) of the spectral features was recently suggested. We propose a different approach for GV...

Methods for enhancing the reproducibility of biomedical research findings using electronic health records

Spiros Denaxas, Kenan Direk, Maria Pikoula, Aylin Cakiroglu, Jason Moore, Harry Hemingway & Liam Smeeth
Table 3: Example of an R function for converting lipid measurements between mmol/L and mg/dL units Table 4: Using the RUnit library to perform unit tests for a function converting measurements of lipids from mmol/L to mg/dL Figure 5: Example of using the Knitr R package to produce a dynamic report with embedded R code and results including a plot. Documentation and data processing code chunks are written in plain text in a file that...

Pattern Masking Estimation in Image With Structural Uncertainty

Jinjian Wu, Weisi Lin, Guangming Shi, Xiaotian Wang & Fu Li
This is a Matlab software for calculating the pattern masking. Please refer to the following papers: J. Wu, W. Lin, G. Shi, Xiaotian Wang, and Fu Li, Pattern Masking Estimation in Image With Structural Uncertainty. IEEE Trans. on Image Processing, accepted, 2013. J. Wu, W. Lin, and G. Shi, Visual Masking Estimation Based On Structural Uncertainty, IEEE ISCAS 2013.

Generalising treatment effects to unseen contexts (code to reproduce the analysis in myUG Dissertation)

Lubos Pernis
This capsule generates the tables and figures from my Dissertation on 'Generalising experimental results to unseen contexts'. Abstract: Being able to use existing experimental results to obtain predictions about the treatment effects in new locations can be highly relevant for policymakers wishing to implement a new programme. In this dissertation, I propose the use of an improved matching estimator and causal forests (Wager and Athey, 2018) for this problem. Using synthetic data, I show that...

Robust model-based reliability approach to tackle shilling attacks in collaborative filtering recommender systems

Santiago Alonso, Jesús Bobadilla, Fernando Ortega & Ricardo Moya
As the use of recommender systems becomes generalized in society, the interest in varying the orientation of their recommendations increases. There are shilling attacks strategies that introduce malicious profiles in collaborative filtering recommender systems in order to promote the own products or services, or to discredit those of the competition. Academic research against shilling attacks has been focused in statistical approaches to detect unusual patterns in user ratings. Nowadays there is a growing research area...

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.

DRAMSim2 - A cycle accurate DRAM simulator modified for row-buffer caching

Zhao Zhang, Zhichun Zhu & Xiaodong Zhang
Reproducibility experimentation for "A permutation-based page interleaving scheme to reduce row-buffer conflicts and exploit data locality" that uses a modified DRAMSim2 to simulate SPEC CPU benchmarks with an interleaved row-buffer addressing scheme.

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