Miracle-dz/UniFAR-FTUs huggingface dataset:
REMOVAL OF SHADOWS AND SHADINGS FROM TEXTURE IMAGES FOR ARCHIVING HISTORICAL RUINS

We are digitizing a whole terrain and ruined buildings of a medieval harbor city on the island called Gemiler Island, as ’Digital Gemiler Island project. ’ To make textured 3D models of the ancient buildings, we have measured shapes of some of the buildings on the site with a laser range scanner and taken high-resolution images for textures with digital cameras. Since we’ve taken the photos in the daytime, the texture images are affected with shadows and shadings by the sunlight. To render the 3D model of the buildings on arbitrary lighting conditions, these effects of shadows and shadings must be removed from the images. Although there are several techniques for removing shadows and shadings from images, most of them need several images with different lighting conditions for each scene. However, taking images several times with the same camera positions and different lighting conditions is very time consuming. In Digital Gemiler Island project, we can use the globally registered 3D model of the buildings, which is measured with 3D laser scanner and GPS, the direction of light (the sun), and camera pose information for each images. In addition, variations of the surface materials of the ruined buildings are very limited. In this paper, effects of shadows and shadings are removed taking advantages of these characteristics. We assume a parametric reflection model and estimate the parameters of the model fitting the model to the images, by which separating effects of shadows/shadings from reflectance. The method needs only single image for each scene.
International Journal of Advanced Robotic Systems Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks Regular Paper

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Energy efficiency is very important for wireless sensor networks (WSNs) since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM) approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual‐grid‐based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM) and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.
Evolution of stratospheric ozone during winter 2002/2003 as observed by a ground-based millimetre wave radiometer at Kiruna, Sweden

Abstract. We present ozone measurements from the millimetre wave radiometer installed at the Swedish Institute of Space Physics (Institutet for rymdfysik, IRF) in Kiruna (67.8° N, 20.4° E, 420 m asl). Nearly continuous operation in the winter of 2002/2003 allows us to give an overview of ozone evolution in the stratosphere between 15 and 55 km. In this study we present a detailed analysis of the Arctic winter 2002/2003. By means of a methodology using equivalent latitudes we investigate the meteorological processes in the stratosphere during the entire winter/spring period. During the course of the winter strong mixing into the vortex took place in the middle and upper stratosphere as a result of three minor and one major warming event, but no evidence was found for significant mixing in the lower stratosphere. Ozone depletion in the lower stratosphere during this winter was estimated by measurements on those days when Kiruna was well inside the Arctic polar vortex. The days were carefully chosen using a definition of the vortex edge based on equivalent latitudes. At the 475 K isentropic level a cumulative ozone loss of about 0.5 ppmv was found starting in January and lasting until mid-March. The early ozone loss is probably a result of the very cold temperatures in the lower stratosphere in December and the geographical extension of the vortex to lower latitudes where solar irradiation started photochemical ozone loss in the pre-processed air. In order to correct for dynamic effects of the ozone variation due to diabatic subsidence of air masses inside the vortex, we used N2O measurements from the Odin satellite for the same time period. The derived ozone loss in the lower stratosphere between mid-December and mid-March varies between 1.1±0.1 ppmv on the 150 ppbv N2O isopleth and 1.7±0.1 ppmv on the 50 ppbv N2O isopleth.
Scalable Address Spaces Using Rcu Balanced Trees Citation

Software developers commonly exploit multicore processors by building multithreaded software in which all threads of an application share a single address space. This shared address space has a cost: kernel virtual memory operations such as handling soft page faults, growing the address space, mapping files, etc. can limit the scalability of these applications. In widely-used operating systems, all of these operations are synchronized by a single per-process lock. This paper contributes a new design for increasing the concurrency of kernel operations on a shared address space by exploiting read-copy-update (RCU) so that soft page faults can both run in parallel with operations that mutate the same address space and avoid contending with other page faults on shared cache lines. To enable such parallelism, this paper also introduces an RCU-based binary balanced tree for storing memory mappings. An experimental evaluation using three multithreaded applications shows performance improvements on 80 cores ranging from 1.7× to 3.4× for an implementation of this design in the Linux 2.6. 37 kernel. The RCU-based binary tree enables soft page faults to run at a constant cost with an increasing number of cores, suggesting that the design will scale well beyond 80 cores.
The Lidcombe Program: a series of case studies with Kuwaiti preschool children who stutter

ABSTRACT Purpose: The aim of this series of case studies was to determine (1) the impact of the Lidcombe Program on early stuttering in Arabic-speaking preschool children, (2) whether adaptations are necessary when implementing the treatment program in Kuwait, and (3) the opinions of Arab parents about the treatment program. Method: This paper reports case studies of six Kuwaiti preschool age children who stuttered, aged 4;9–5;11 years (median 5;3 years), and were treated with the Lidcombe Program. The treatment program was administered in Arabic. The outcome measures included percentage of syllables stuttered (%SS) and severity ratings (SR), treatment times, and parent report. Results: Four children completed both stages of the treatment program. Significant changes in the speech of all four children were noted, reaching below 1.0%SS. The treatment was completed in a median of 10.5, 1-hour clinic sessions, and a median of 136.5 days from commencement of the treatment program. Conclusion: Findings suggest that this Western program is applicable and effective with a Kuwaiti population when presented in Arabic.
Double System Co-Evolutionary Gene Expression Programming and Its Application in Function Finding Problems

Inspired by the evolution process of human, a double system co-evolutionary gene expression programming (DSCEGEP) is proposed in this paper. The DSCE-GEP consists of natural evolution system and artificial intervention system, where the natural evolution system solves problem according to the mode of standard gene expression programming (STGEP) and the artificial intervention system guides the process of natural evolution system to solve problem. The artificial intervention system includes individual intervention operation and population intervention operation and is based on a gene pool, which is first created according to prior knowledge and then is updated according to posterior knowledge, contains eminent genes, morbid genes and their characteristic information as well. The individual intervention operation, which aims to improve the quality of population individuals, consists of a repairing operator that removes the morbid genes in individuals and a strengthening operator that spreads eminent genes to the individuals of population. The population intervention operation uses entropy as the diversity indicators of population and increases the population entropy by introducing a certain number of feasible random individuals and feasible mirror individuals to improve the global searching ability of the algorithm when the population entropy drops to a given threshold. The experimental results show that the performance of DSCE-GEP is better than other GEP algorithms proposed in the related literatures as regards function finding problems, and promises competitive performance.
Cardiac Infarction Injury Score: An Electrocardiographic Coding Scheme for Ischemic Heart Disease

A multivariate decision-theoretic electrocardiogram (ECG) classification scheme called Cardiac Infarction Injury Score (CIIS) was developed using ECGs of 387 patients with myocardial infarction (MI) and 320 subjects without infarction. The most accurate and stable classification was achieved by using a combination of eight binary (single threshold), three ternary (two thresholds), and four ECG features measured on a continuous scale. For practical visual coding of ECGs, the CIIS coding procedure uses a checklist containing 12 items measured from the conventional 12-lead ECG.The CIIS test results indicate that, in comparison with conventional ECG criteria for MI used in clinical trials, the diagnostic accuracy can be considerably improved by optimizing feature and threshold selection and by multivariate analysis. The CIIS detected MI with a sensitivity of 85% and a specificity of 95%. Using a higher severity level, a specificity of 99% was achieved, with a sensitivity of 71%. One of the primary uses of the CIIS is coding of significant worsening of the ECG with new coronary events from annually recorded ECGs in clinical trials and epidemiologic studies.
Image denoising with patch based PCA: local versus global

In recent years, overcomplete dictionaries combined with sparse learning techniques became extremely popular in computer vision. While their usefulness is undeniable, the improvement they provide in specific tasks of computer vision is still poorly understood. The aim of the present work is to demonstrate that for the task of image denoising, nearly state-of-the-art results can be achieved using orthogonal dictionaries only, provided that they are learned directly from the noisy image. To this end, we introduce three patchbased denoising algorithms which perform hard thresholding on the coefficients of the patches in image-specific orthogonal dictionaries. The algorithms differ by the methodology of learning the dictionary: local PCA, hierarchical PCA and global PCA.We carry out a comprehensive empirical evaluation of the performance of these algorithms in terms of accuracy and running times. The results reveal that, despite its simplicity, PCA-based denoising appears to be competitive with the state-of-the-art denoising algorithms, especially for large images and moderate signal-to-noise ratios.
Rearrangement-Based Phylogeny Using the Single-Cut-or-Join Operation

Recently, the Single-Cut-or-Join (SCJ) operation was proposed as a basis for a new rearrangement distance between multichromosomal genomes, leading to very fast algorithms, both in theory and in practice. However, it was not clear how well this new distance fares when it comes to using it to solve relevant problems, such as the reconstruction of evolutionary history. In this paper, we advance current knowledge, by testing SCJ's ability regarding evolutionary reconstruction in two aspects: 1) How well does SCJ reconstruct evolutionary topologies? and 2) How well does SCJ reconstruct ancestral genomes? In the process of answering these questions, we implemented SCJ-based methods, and made them available to the community. We ran experiments using as many as 200 genomes, with as many as 3,000 genes. For the first question, we found out that SCJ can recover typically between 60 percent and more than 95 percent of the topology, as measured through the Robinson-Foulds distance (a.k.a. split distance) between trees. In other words, 60 percent to more than 95 percent of the original splits are also present in the reconstructed tree. For the second question, given a topology, SCJ's ability to reconstruct ancestral genomes depends on how far from the leaves the ancestral is. For nodes close to the leaves, about 85 percent of the gene adjacencies can be recovered. This percentage decreases as we move up the tree, but, even at the root, about 50 percent of the adjacencies are recovered, for as many as 64 leaves. Our findings corroborate the fact that SCJ leads to very conservative genome reconstructions, yielding very few false-positive gene adjacencies in the ancestrals, at the expense of a relatively larger amount of false negatives. In addition, experiments with real data from the Campanulaceae and Protostomes groups show that SCJ reconstructs topologies of quality comparable to the accepted trees of the species involved. As far as time is concerned, the methods we implemented can find a topology for 64 genomes with 2,000 genes each in about 10.7 minutes, and reconstruct the ancestral genomes in a 64-leaf tree in about 3 seconds, both on a typical desktop computer. It should be noted that our code is written in Java and we made no significant effort to optimize it.
The extreme plasticity of killer cell Ig‐like receptor (KIR) haplotypes differentiates rhesus macaques from humans

NK cells are essential in shaping immune responses and play an important role during pregnancy and in controlling infections. Killer cell immunoglobulin‐like receptors (KIRs) educate the NK cell and determine its state of activation. Our goal was to determine how the KIR repertoire of the rhesus macaque (Macaca mulatta) has been shaped during evolution. The presence or absence of 22 KIR gene groups was determined in 378 animals. Some unexpected observations were made in an outbred colony comprising animals of different origins. For instance, the KIR region appears to be highly plastic, and an unprecedented number of genotypes and haplotypes was observed. In contrast to humans, there is no distinction between group A and B haplotypes in the rhesus macaque, suggesting that different selective forces may be operative. Moreover, specific genes appear to be either present or absent in animals of different geographic origins. This extreme plasticity may have been propelled by co‐evolution with the rhesus macaque MHC class I region, which shows signatures of expansion. The mosaic‐like complexity of KIR genotypes as observed at the population level may represent an effective strategy for surviving epidemic infections.
Multi-party human-robot interaction with distant-talking speech recognition

Speech is one of the most natural medium for human communication, which makes it vital to human-robot interaction. In real environments where robots are deployed, distant-talking speech recognition is difficult to realize due to the effects of reverberation. This leads to the degradation of speech recognition and understanding, and hinders a seamless human-robot interaction. To minimize this problem, traditional speech enhancement techniques optimized for human perception are adopted to achieve robustness in humanrobot interaction. However, human and machine perceive speech differently: An improvement in speech recognition performance may not automatically translate to an improvement in human-robot interaction experience (as perceived by the users). In this paper, we propose a method in optimizing speech enhancement techniques specifically to improve automatic speech recognition (ASR) with emphasis on the human-robot interaction experience. Experimental results using real reverberant data in a multi-party conversation, show that the proposed method improved human-robot interaction experience in severe reverberant conditions compared to the traditional techniques.
Diversification for multi-domain result sets

Multi-domain search answers to queries spanning multiple entities, like "Find an affordable house in a city with low criminality index, good schools and medical services", by producing ranked sets of entity combinations that maximize relevance, measured by a function expressing the user's preferences. Due to the combinatorial nature of results, good entity instances (e.g., inexpensive houses) tend to appear repeatedly in top-ranked combinations. To improve the quality of the result set, it is important to balance relevance (i.e., high values of the ranking function) with diversity, which promotes different, yet almost equally relevant, entities in the top-k combinations. This paper explores two different notions of diversity for multi-domain result sets, compares experimentally alternative algorithms for the trade-off between relevance and diversity, and performs a user study for evaluating the utility of diversification in multi-domain queries.
Herschel : the first science highlights Special feature L etter to the E ditor Herschel-SPIRE observations of the disturbed galaxy NGC 4438

We present Herschel-SPIRE observations of the perturbed galaxy NGC 4438 in the Virgo cluster. These images reveal the presence of extra-planar dust up to ∼4–5 kpc away from the galaxy’s disk. The dust closely follows the distribution of the stripped atomic and molecular hydrogen, supporting the idea that gas and dust are perturbed in a similar fashion by the cluster environment. Interestingly, the extra-planar dust lacks a warm temperature component when compared to the material still present in the disk, explaining why it was missed by previous far-infrared investigations. Our study provides evidence for dust stripping in clusters of galaxies and illustrates the potential of Herschel data for our understanding of environmental effects on galaxy evolution.
PigSPARQL: mapping SPARQL to Pig Latin

In this paper we investigate the scalable processing of complex SPARQL queries on very large RDF datasets. As underlying platform we use Apache Hadoop, an open source implementation of Google's MapReduce for massively parallelized computations on a computer cluster. We introduce PigSPARQL, a system which gives us the opportunity to process complex SPARQL queries on a MapReduce cluster. To this end, SPARQL queries are translated into Pig Latin, a data analysis language developed by Yahoo! Research. Pig Latin programs are executed by a series of MapReduce jobs on a Hadoop cluster. We evaluate the processing of SPARQL queries by means of PigSPARQL using the SP2Bench, a SPARQL specific performance benchmark and demonstrate that PigSPARQL enables a scalable execution of SPARQL queries based on Hadoop without any additional programming efforts.
On the Distributed Compression of Quantum Information

The problem of distributed compression for correlated quantum sources is considered. The classical version of this problem was solved by Slepian and Wolf, who showed that distributed compression could take full advantage of redundancy in the local sources created by the presence of correlations. Here it is shown that, in general, this is not the case for quantum sources, by proving a lower bound on the rate sum for irreducible sources of product states which is stronger than the one given by a naive application of Slepian-Wolf. Nonetheless, strategies taking advantage of correlation do exist for some special classes of quantum sources. For example, Devetak and Winter demonstrated the existence of such a strategy when one of the sources is classical. Optimal nontrivial strategies for a different extreme, sources of Bell states, are presented here. In addition, it is explained how distributed compression is connected to other problems in quantum information theory, including information-disturbance questions, entanglement distillation and quantum error correction
Visual Secret Sharing Scheme UsingEncrypting Multiple Images

Visual Cryptography is an encryption technique where a secret image is cryptographically encoded into n meaningless share images. A basic model for visual cryptography for natural images was proposed by Naor and Shamir. Security has gained a lot of importance as information technology is widely used. Cryptography refers to the study of mathematical techniques and related aspects of Information Security like data confidentiality, data Integrity, and of data authentication. Visual cryptography is a process where a secret image is encrypted into shares which refuse to divulge information about the original secret image. Its strength is a fact that the decryption of the secret image is through human visual system without computation. This paper provides a formulation of encryption for multiple secret images, which is a generalization of the existing ones, and also a general method of constructing visual secret sharing schemes encrypting multiple secret images.
Data and Responsibility: Toward a Feminist Methodology for Producing Historical Data on Women in the Contemporary UK Film Industry

This article addresses how feminist interrogations of research methods and knowledge claims have an important role to play in the collection and dispersion of quantitative data. Taking the contemporary film industry as a historical formation, and seeking to identify and understand patterns of continued gendered inequality, it considers the methodological and ethical dilemmas we have experienced as feminist researchers gathering and presenting quantitative data on the numbers of women working in the UK film industry between 2003 and 2015. It argues that data plays a paradoxical role in creating a sense of women9s absence, and ultimately arrives at a set of guiding principles for feminist quantitative research in film histories.
The Legacy of Disadvantage: Multigenerational Neighborhood Effects on Cognitive Ability

This study examines how the neighborhood environments experienced over multiple generations of a family influence children's cognitive ability. Building on recent research showing strong continuity in neighborhood environments across generations of family members, the authors argue for a revised perspective on “neighborhood effects” that considers the ways in which the neighborhood environment in one generation may have a lingering impact on the next generation. To analyze multigenerational effects, the authors use newly developed methods designed to estimate unbiased treatment effects when treatments and confounders vary over time. The results confirm a powerful link between neighborhoods and cognitive ability that extends across generations. A family's exposure to neighborhood poverty across two consecutive generations reduces child cognitive ability by more than half a standard deviation. A formal sensitivity analysis suggests that results are robust to unobserved selection bias.