Miracle-dz/UniFAR-FTUs huggingface dataset:
Larval and juvenile distribution and growth of Patagonian toothfish around South Georgia

Early stages of toothfish are reported from cruises between 1978 and 2001. South Georgia was regularly sampled, Shag Rocks was briefly sampled in three summers, and Burdwood Bank was sampled in 1997. Most samples were using 8 m2 and 1 m2 nets in the upper 250 m and upper 3 m, respectively. Forty-three pelagic larval/early juvenile stages between 18.2 and 63 mm standard length (Ls) were taken between December and March. Four specimens were taken at Burdwood Bank, one at Shag Rocks, and 38 at South Georgia. Forty fish were from the upper 250 m, and 23 from the upper 3 m. They occurred onshelf and offshore over water depths between 10 and 3000 m. Estimated growth rate, at South Georgia from 11 cohorts (including published data), is c. 1% Ls, d−1 (n = 39). From this and a hatch size of 15 mm Ls, the predicted hatching season is November to mid-December. From seven trawl surveys during summer at South Georgia and Shag Rocks between 1986 and 2000, the mean depth of the smaller demersal juveniles 13–25 cm total length (LT) was < 140 m, indicating that early juveniles probably migrate inshore.
Data in Brief

This paper presents a dataset of bird’s eye chilies in a single farm for semantic segmentation. The dataset is generated using two cameras that are aligned left and right forming a stereo-vision video capture. By analyzing the disparity be-tween corresponding points in the left and right images, algorithms can calculate the relative distance of objects in the scene. This depth information is useful in various applications, including 3D reconstruction, object tracking, and autonomous navigation. The dataset consists of 1150 left and right compressed images extracted from ten sets of stereo videos taken at ten different locations within the chili farm from the same ages of the bird’s eye chilies. Since the dataset is used for semantic segmentation, the ground truth images of manually semantic segmented images are also provided in the dataset. The dataset can be
Improving session-to-session transfer performance of motor imagery-based BCI using Adaptive Extreme Learning Machine

to address non-stationarity, adaptation is a promising method. In this study, an adaptive extreme learning machine (AELM) is proposed to update the initial classifier from the calibration session by using chunks of EEG data from the evaluation session whereby the common spatial pattern (CSP) algorithm is used to extract the most discriminative features. The effectiveness of the proposed algorithm is on motor imagery data collected from 12 healthy subjects during a calibration session and an evaluation session on a separate day. The results from the proposed AELM were compared with non-adaptive ELM and SVM classifiers. The results showed that AELM was significantly better (p=0.03). Moreover, the results also showed that accumulating the evaluation session data and useing them for adapting the classifier will significantly improve the performance (p=0.001). Hence, the proposed AELM is effective in addressing the non-stationarity of EEG signal for online BCI systems.
University of

Networks are a natural and effective tool to study relational data, in which observations are collected on pairs of units. The units are represented by nodes and their relations by edges. In biology, for example, proteins and their interactions, and, in social science, people and inter-personal relations may be the nodes and the edges of the network. In this paper we address the question of clustering vertices in networks, as a way to uncover homogeneity patterns in data that enjoy a network representation. We use a mixture model for random graphs and propose a reversible jump Markov chain Monte Carlo algorithm to infer its parameters. Applications of the algorithm to one simulated data set and three real data sets, which describe friendships among members of a University karate club, social interactions of dolphins, and gap junctions in the C. Elegans, are given.
The Aquila Digital Community The Aquila Digital Community

In recent years, pedestrians have been dangerously overrepresented in traffic crashes, and the pedestrian fatality rate has steadily increased during the last decade. Additionally, studies have shown that the majority of pedestrian-involved traffic accidents occur in urban non-intersections, which suggests that a more well-connected pedestrian facility network in cities would lower the rate of pedestrian involvement in traffic accidents. One way to improve the pedestrian facility network coverage is to first have up-to-date, accurate, and thorough data regarding the presence of existing pedestrian facilities. However, state departments of transportation have stated that the current methods of acquiring this data are expensive and time consuming. In this project, we developed a mobile application prototype for crowdsourced acquisition of street-view images containing pedestrian facilities, or more specifically, crosswalks. The resulting application used modern full-stack development techniques and is a native Android application that allows the user to take pictures using their mobile devices and automatically upload those pictures, along with relevant metadata (such as location data), to a server where they are classified using a machine learning model that was trained to recognize the presence of crosswalks in images.
Optimized Data Fusion in an Intelligent Integrated GPS / INS System Using Genetic Algorithm

global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites' outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.
Various versatile variances : An object-oriented implementation of clustered covariances in R Working

Clustered covariances or clustered standard errors are very widely used to account for correlated or clustered data, especially in economics, political sciences, or other social sciences. They are employed to adjust the inference following estimation of a standard least-squares regression or generalized linear model estimated by maximum likelihood. Although many publications just refer to “the” clustered standard errors, there is a surprisingly wide variety of clustered covariances, particularly due to di erent flavors of bias corrections. Furthermore, while the linear regression model is certainly the most important application case, the same strategies can be employed in more general models (e.g. for zero-inflated, censored, or limited responses). In R, functions for covariances in clustered or panel models have been somewhat scattered or available only for certain modeling functions, notably the (generalized) linear regression model. In contrast, an object-oriented approach to “robust” covariance matrix estimation – applicable beyond lm() and glm() – is available in the sandwich package but has been limited to the case of cross-section or time series data. Now, this shortcoming has been corrected in sandwich (starting from version 2.4.0): Based on methods for two generic functions (estfun() and bread()), clustered and panel covariances are now provided in vcovCL(), vcovPL(), and vcovPC(). These are directly applicable to models from many packages, e.g., including MASS, pscl, countreg, betareg, among others. Some empirical illustrations are provided as well as an assessment of the methods’ performance in a simulation study.
A Survey on Query Recommendation Techniques and Evaluation of Snippet based Query Recommendation

Recently web has been widely used for getting different kinds of information. Web mining is considered to store the information in a specific format known as weblog. This valuable mined information can be used in many applications such as query log analysis, query recommendation, query reformulation and many more for improved performance of search engine. Search engine provide the platform for users to describe their information need more clearly by using query recommendation. Previously there has been lot of work done for retrieving more relevant data to users in order to meet their information need thus improving performance of search engines. This paper reviews and compares different available methods in query log processing for information retrieval. Moreover the approach based on clicked snippets is better to understand users interaction process with search engines to find the appropriate information need.
OPRE-2009-06-260 . R 2 Approximation Algorithms for the Stochastic Lot-sizing Problem with Order Lead Times

We develop new algorithmic approaches to compute provably near-optimal policies for multi-period stochastic lot-sizing inventory models with positive lead times, general demand distributions and dynamic forecast updates. The policies that are developed have worst-case performance guarantees of 3 and typically perform very close to optimal in extensive computational experiments. The newly proposed algorithms employ a novel randomized decision rule and depart from the previous work of Levi et al. (2007). We believe that these new algorithmic and performance analysis techniques could be used in designing provably near-optimal randomized algorithms for other stochastic inventory control models, and more generally in other multistage stochastic control problems.
THUNDER: A reference-free deconvolution method to infer cell type proportions from bulk Hi-C data

Hi-C data provide population averaged estimates of three-dimensional chromatin contacts across cell types and states in bulk samples. To effectively leverage Hi-C data for biological insights, we need to control for the confounding factor of differential cell type proportions across heterogeneous bulk samples. We propose a novel unsupervised deconvolution method for inferring cell type composition from bulk Hi-C data, the Two-step Hi-c UNsupervised DEconvolution appRoach (THUNDER). We conducted extensive real data based simulations to test THUNDER constructed from published single-cell Hi-C (scHi-C) data. THUNDER more accurately estimates the underlying cell type proportions when compared to both supervised and unsupervised deconvolution methods including CIBERSORT, TOAST, and NMF. THUNDER will be a useful tool in adjusting for varying cell type composition in population samples, facilitating valid and more powerful downstream analysis such as differential chromatin organization studies. Additionally, THUNDER estimates cell-type-specific chromatin contact profiles for all cell types in bulk Hi-C mixtures. These estimated contact profiles provide a useful exploratory framework to investigate cell-type-specificity of the chromatin interactome while experimental data is still sparse.
Optimized View Frustum Culling Algorithms

This paper presents new techniques for fast view frustum culling. View frustum cullers (VFCs) are typically used in virtual reality software, walkthrough algorithms, scene graph APIs or other 3D graphics applications. First we develop a fast basic VFC algorithm. Then we suggest and evaluate four further optimizations, which are independent of each other and works for all kinds of VFC algorithms that test the bounding volumes (BVs) against the planes of the view frustum. Results when optimizing specifically for axis aligned bounding boxes (AABBs), oriented bounding boxes (OBBs), bounding spheres and different kinds of navigation are delivered. In particular, we provide solutions which give average speed ups of 3-10 times for AABBS and OBBs depending on the circumstances, compared to the conventional AABB algorithm used for instance in DirectModel [DirectModel], and speed ups of 1.2-1.4 for bounding spheres, compared to Silicon Graphics’ implementation in Cosmo3D [Cosmo3D] and Performer [Performer].
Stormwater Detention Systems with Effluent Filtration

The growing concern for water quality enhancement of our surf ace waters has led to changes in detention facility design. Providing a filter media for the effluent water to travel through before discharge into the environment has become an area of interest . Thus, detention facilities may be used for both ater quality and quantity control . Different soil medias were studied for the potential of pollutant removal and infiltration rates usable in design work. Both laboratory and field experimentation were performed. A computer program was also developed to model stormwater movement through a swale detention system. This research was performed to examine filter media and to indicate the advisability of designing a combination of detention ponds and berms.
A nonlinear principal component analysis on image data

Principal component analysis (PCA) has been applied in various areas such as pattern recognition and data compression. In some cases, however, PCA does not extract the characteristic of the data-distribution efficiently. In order to overcome this problem, we have proposed a novel method of nonlinear PCA which preserves the order of principal components. In this paper, we reduce the dimensionality of image data with the proposed method, and examine its effectiveness in compression and recognition of the images
Peri-Personal Space and the Representation of Quantity

Title: Peri-personal space and the representation of quantity: Two types of re-use responsible for motor and spatial compatibility effects Advisor: Michael Kaschak 2009 MS. Cognitive Psychology, Florida State University, Thesis Title: The influence of movement on the directionality of space-time representation mappings Advisor: Michael Kaschak 2006 BS. Psychology, University of Florida, Honors Thesis Title: Using homophones in auditory priming of tip-of-tongue resolution.
Network Time Protocol Version 4: Protocol and Algorithms Specification

The Network Time Protocol (NTP) is widely used to synchronize computer clocks in the Internet. This document describes NTP version 4 (NTPv4), which is backwards compatible with NTP version 3 (NTPv3), described in RFC 1305, as well as previous versions of the protocol. NTPv4 includes a modified protocol header to accommodate the Internet Protocol version 6 address family. NTPv4 includes fundamental improvements in the mitigation and discipline algorithms that extend the potential accuracy to the tens of microseconds with modern workstations and fast LANs. It includes a dynamic server discovery scheme, so that in many cases, specific server configuration is not required. It corrects certain errors in the NTPv3 design and implementation and includes an optional extension mechanism. [STANDARDS-TRACK]
Access to family physician services in Canada: a tale of two provinces

Over much of the industrialized world, the provision of health care has been and remains an issue of intense debate. Health-care systems, such as Canada's, that are based on sorne notion of universal coverage have been affected by recent attention to cost containment (Evans et al. 1991). But universality has not been rejected as a fundamental principle and continues to imply a cornmit­ ment to equity. These continuing concerns over getting the population distribu­ tion of health care 'right' have led policy-makers in many countries to focus attention on policies aimed at changing that distribution. In this paper, we examine these distributional issues in Ontario and Quebec. In Canada, the legislation governing the fiscal arrangements for federal
Journal of Proteomics & Bioinformatics

MicroRNAs are small, non-coding RNA molecules that regulate gene expression. MicroRNA may binds to mRNAs and control the intended function of mRNAs. There are a handful of computational algorithms for target prediction, but the degree of false positives and false negatives are high. In this paper, we propose a Hidden Markov Model for seed prediction and a Support Vector Machine (SVM) classifier for target prediction. Positive data set for training has been collected from experimentally validated targets, while negative data set has been identified systematically from predicted false positives. Each mRNA target candidate sequence is aligned with microRNA sequence and tested for a seed region using the trained HMM model. If the test succeeds, 22 features were extracted from the aligned duplex and fed into an SVM classifier. HMM based seed identification module works with an accuracy of 95.6% and SVM classifier provides 97.49% accuracy. We have compared binding sites of 9 microRNA in 148 m RNAs with the results of validated target sites and our results are more accurate than other approaches.
BAMscale: quanti�cation of next-generation sequencing peaks and generation of scaled coverage tracks

Background: Next-generation sequencing allows genome-wide analysis of changes in chromatin states and gene expression. Data analysis of these increasingly used methods either requires multiple analysis steps, or extensive computational time. We sought to develop a tool for rapid quanti�cation of sequencing peaks, and an e�cient method to produce coverage tracks for accurate visualization that can be intuitively interpreted by experimentalists with minimal bioinformatics background. We demonstrate its strength by integrating data from several types of sequencing approaches. Results: We have developed BAMscale, a one-step tool that processes a wide set of sequencing datasets. To demonstrate the usefulness of BAMscale, we analyzed multiple sequencing datasets from chromatin immunoprecipitation sequencing (ChIP-seq) data, chromatin state change data (Assay for Transposase-Accessible Chromatin using sequencing: ATAC-seq, DNA double strand break mapping sequencing: END-seq), DNA replication data (Okazaki fragments sequencing: OK-seq, Nascent-strand sequencing: NS-seq, single-cell replication timing sequencing: scRepli-seq) and RNA-seq data. The outputs consist of raw and normalized peak scores (multiple normalizations) in text format and scaled bigWig coverage tracks that are directly accessible to data visualization programs. Our tool can effectively analyze large sequencing datasets (~100Gb size) in minutes, outperforming currently available tools. Conclusions: BAMscale is a tool that can be used to accurately quantify and normalize identi�ed peaks directly from BAM �les, as well as create coverage tracks for visualization in genome browsers. BAMScale can be implemented for a wide set
Vid2Curve: Simultaneously Camera Motion Estimation and Thin Structure Reconstruction from an RGB Video

Fig. 1. This figure shows three thin structured objects reconstructed using our method, together with selected frames of the input videos. Using an RGB video as input, our method performs curve-based camera pose estimation and reconstructs complex 3D thin structures in better quality than other existing methods. See the comparisons with the other methods on the bucket model and the hanger model in Section 5.5.
Fast 4‐D Imaging of Fluid Flow in Rock by High‐Speed Neutron Tomography

High‐speed neutron tomographies (1‐min acquisition) have been acquired during water invasion into air‐filled samples of both intact and deformed (ex situ) Vosges sandstone. Three‐dimensional volume images have been processed to detect and track the evolution of the waterfront and to calculate full‐field measurement of its speed of advance. The flow process correlates well with known rock properties and is especially sensitive to the distribution of the altered properties associated with observed localized deformation, which is independently characterized by Digital Volume Correlation of X‐ray tomographies acquired before and after the mechanical test. The successful results presented herein open the possibility of in situ analysis of the local evolution of hydraulic properties of rocks due to mechanical deformation.
The Sciences of Design: Observations on an Emerging Field

The boundaries and contours of design sciences continue to undergo definition and refinement. In many ways, the sciences of design defy disciplinary characterization. They demand multiple epistemologies, theoretical orientations (e.g. construction, analysis or intervention) and value considerations. As our understanding of this emerging field of study grows, we become aware that the sciences of design require a systemic perspective that spans disciplinary boundaries. The Doctoral Consortium at the Design Science Research Conference in Information Sciences and Technology (DESRIST) was an important milepost in their evolution. It provided a forum where students and leading researchers in the design sciences challenged one another to tackle topics and concerns that are similar across different disciplines. This paper reports on the consortium outcomes and insights from mentors who took part in it. We develop a set of observations to guide the evolution of the sciences of design. It is our intent that the observations will be beneficial, not only for IS researchers, but also for colleagues in allied disciplines who are already contributing to shaping the sciences of design.
Wave runup estimates at gentle beaches in the northern Indian Ocean

Faculty of Mathematics and Natural Sciences Geophysical Institute Master of Science by Ahmed Alkarory Ahmed Abdalazeez The aim of this study is to estimate the wave runup on selected beaches around the northern Indian Ocean. The runup has been estimated using ERA-Interim, which is the latest global atmospheric re-analysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). ECMWF uses the global Wave Model (WAM) model to calculate two dimensional wave spectra. The distances between the model grid points and the beaches have been calculated by a great circle calculator. The beach slopes have been calculated by Google Earth for all locations, except Maldives beach, which was assumed as an imaginary beach because the method of calculating the slope could not be used there. The significant wave height as well as the peak wave period at the grid points are assumed to be the same at the beach. The most frequent estimated runup is between 0.5 m and 1.0 m, which is produced by swell coming from the southern Indian Ocean for all locations except Sri Lanka, India and Maldives shores, where the most frequent runup value is less than 0.5 m. However, the extreme wave runup occurs with the largest wave heights during summer monsoon in July. Generally, the high wave height depends on wind speed. The mean elevation of the runup for all locations is 0.56 m. It is comparable to the measured values obtained by (Stochdon et al., 2006) at several beaches in USA and the Netherlands who found the mean value of dissipative sites (84 cm) for all experiments.