Miracle-dz/UniFAR-FTUs huggingface dataset:
A Gradient Vector Flow-Based Method for Video Character Segmentation

In this paper, we propose a method based on gradient vector flow for video character segmentation. By formulating character segmentation as a minimum cost path finding problem, the proposed method allows curved segmentation paths and thus it is able to segment overlapping characters and touching characters due to low contrast and complex background. Gradient vector flow is used in a new way to identify candidate cut pixels. A two-pass path finding algorithm is then applied where the forward direction helps to locate potential cuts and the backward direction serves to remove the false cuts, i.e. those that go through the characters, while retaining the true cuts. Experimental results show that the proposed method outperforms an existing method on multi-oriented English and Chinese video text lines. The proposed method also helps to improve binarization results, which lead to a better character recognition rate.
Real-time infrared pedestrian detection based on multi-block LBP

This paper presents a real-time infrared pedestrian detection algorithm based on multi-block LBP features. Local pattern feature has been successfully used in many computer vision applications. However, to our best knowledge, it has not been utilized for pedestrian detection in infrared imagery. We exploit the discriminative power and computational simplicity of local pattern features for real-time infrared pedestrian detection. The proposed approach has been implemented on an experimental vehicle equipped with a forward-looking infrared (FLIR) camera. Experimental results under different urban street scenarios prove that our method is robust and efficient.
Martian surface mineralogy from Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité on board the Mars Express spacecraft (OMEGA/MEx): Global mineral maps

[1] After 2 years of operation the Observatoire pour la Mineralogie, l'Eau, les Glaces et l'Activite (OMEGA) imaging spectrometer on board Mars Express has acquired data coverage of the Martian surface with spatial resolution varying between 300 m and 4.8 km, depending on the pericenter altitude of the spacecraft's elliptical orbit. We report the global surface distributions of some minerals using the OMEGA observations in the visible and near infrared (VNIR) wavelength domains (0.35–2.5 μm). Global maps of ferric phases, mafic minerals (pyroxenes and olivines), and hydrated minerals have been derived from spectral parameters. The limits of detection in terms of abundance for some minerals of different grain size distributions are given. The distribution of pyroxenes is in general agreement with the mineral maps of previous telescopic and space observations. The Fe3+ absorption feature in the visible wavelength region is present everywhere on the surface. The spectra of the bright regions compare with anhydrous nanophase ferric oxides. Terrains with water-bearing minerals cover a very small fraction of the Martian surface. Olivine (Mg-rich compositions) is detected in more extensive regions of the pyroxene-rich zones than previously reported. Olivine with higher iron content and/or larger grain size (>100 μm) is only detected in isolated areas. The mineralogy of the northern low-albedo regions is discussed in the light of these mineral maps. Chemical alteration or oxidation during extrusion producing a coating or varnish of anhydrous ferric phases over a dark basaltic surface best accounts for the VNIR spectral properties of these regions, although a glassy composition resulting from impact is also considered.
Conditioned pilots for ISI channels

One of the proposals to increase the spectral efficiency of the DVB-S2 standard is based on time-frequency packing. This technique causes intersymbol and interchannel interferences to arise, requiring a significant growth of the number of pilots used to carry out frequency and phase synchronization. Therefore, a new pilot design will be introduced and suited optimal and suboptimal reduced-complexity algorithms derived. We will show that the proposed pilot strategy may outperform the classical one in terms of bit error rate and spectral efficiency.
Sequence analysis Protein solubility : sequence based prediction and experimental verification

Motivation: Obtaining soluble proteins in sufficient concentrations is a recurring limiting factor in various experimental studies. Solubility is an individual trait of proteins which, under a given set of experimental conditions, is determined by their amino acid sequence. Accurate theoretical prediction of solubility from sequence is instrumental for setting priorities on targets in large-scale proteomics projects. Results: We present a machine-learning approach called PROSO to assess the chance of a protein to be soluble upon heterologous expression in Escherichia coli based on its amino acid composition. The classification algorithm is organized as a two-layered structure in which the output of primary support vector machine (SVM) classifiers serves as input for a secondary Naive Bayes classifier. Experimental progress information from the TargetDB database aswell as previously published datasets were used as the source of training data. In comparison with previously published methods our classification algorithmpossesses improved discriminatory capacity characterized by the Matthews Correlation Coefficient (MCC) of 0.434 between predicted and known solubility states and the overall prediction accuracy of 72% (75 and 68% for positive and negative class, respectively). We also provide experimental verification of our predictions using solubility measurements for 31 mutational variants of two different proteins. Availability: A web server for protein solubility prediction is available at http://webclu.bio. wzw.tum. de:8080/proso Contact: d.frishman@wzw.tum. de Supplementary information: Supplementary data are available at Bioinformatics online
Genomic resources for songbird research and their use in characterizing gene expression during brain development

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3′ ends. A web-based database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30–50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis.
ExpLOD : Exploring Interlinking and RDF Usage in the Linked Open Data Cloud

The Linking Open Data community project is promoting the creation of interlinked RDF datasets with links between data items identified using dereferenceable URIs. This promising direction for publishing data on the web brings forward a number of issues. A key challenge is to understand the data, the schema, and the interlinks that are actually used both within and across linked datasets. Understanding actual RDF usage is critical in the increasingly common situations where terms from many different vocabularies are mixed (potentially with no consistent RDFS or OWL schema). In this paper we propose a novel mechanism to describe RDF usage by combining neighborhood defining queries with bisimilar contractions to produce bisimulation contractions of neighbourhoods (or BCNs). We present algorithms for computing BCNs and describe a tool, ExpLOD, that supports constructing and visualizing BCNs. ExpLOD can also generate SPARQL queries based on the BCNs. We use ExpLOD to describe RDF usage within several of the collections from the Linked Open Data cloud.
Identification of the optic disk boundary in retinal images using active contours

This paper describes a technique for identifying the boundary of the optic disk in digital images of the retina, using an approach based on active contours (snakes). The optic disk is the region on the retina at which optic nerve axons enter and leave the eye. Changes in optic disk shape and area may indicate disease processes, particularly glaucoma, and accurate identification of the disk boundary may be used to quantify changes. For accurate boundary identification, some pre-processing of the image is necessary. This pre-processing minimises incorrect boundary detection due to blood vessels crossing the optic disk. Pre-processing techniques based on local minima detection and morphological filtering were developed. After pre-processing, the optic disk boundary was determined using an active contour. The contour was driven by a novel external image-derived field called the Gradient Vector Flow. This reduced the need for accurate initialisation of the contour. Results obtained by applying these techniques to a set of nine retinal images are presented.
Getting the Message: Front of Package Labeling

The nutrition fact label has been on foods in the United States since the 1990 Nutrition Labeling and Education Act. Many countries have started utilizing front of package labels to inform consumers more quickly, and highlight the nutritional risks and benefits of food items. The purpose of this focus group study was to determine what food label designs are most appealing to consumers and label modifications that would be most effective in encouraging better nutritional choices. Results revealed that having labels on the front of packages was not as important as improving the information on the current nutrition facts panel.
Costationarity of Locally Stationary Time Series

Given more than one locally stationary (LS) time series, this article describes a method to discover time-varying linear combinations of the LS series that are stationary. Systems for which this can occur are called costationary, and the associated time-varying linear combinations are called costationary vectors. Costationary systems are interesting for a number of reasons. The costationary vectors shed light on the nature and strength of a potentially interesting relationship between the LS series. The derived stationary series, which is the time-varying combination of the LS series, is often of independent interest and use. The article discusses why a spectral approach is often preferred to the time-domain and why costationary vectors need to be complexity constrained, and it also demonstrates an interesting error-correction formulae which shows how costationary systems must evolve to maintain stationarity in response to system shocks. We illustrate our methodology with two examples: one from asset allocation in financial portfolio construction and the other which mitigates intermittency in wind power management. In the former, a stationary synthetic asset is constructed using market index data and is shown to have superior Sharpe ratios to two established portfolio selectors. In the latter, power outputs from separate wind series are dynamically combined to provide a power output which has smaller intermittency than the individual inputs.
An OFDM-based multipath channel sounding method with fractional delays resolution

In this paper, an OFDM-based high resolution CS method is proposed under T/2-spaced sampling. The proposed CS method consists of three iterative steps. In each iteration, it attempts to catch a new path with accurate fractional delay. Besides, it is equipped with EDC criterion for path order determination. The CFR-MSE performance can be greatly improved over the conventional LS method. Besides, the proposed CS method is robust enough for different settings of EDC penalty factor a. In addition, some algorithmic refinements could be added for decreasing the complexity in the future.
Threshold effects on the mass-scale predictions in SO(10) models and solar-neutrino puzzle.

We compute the threshold uncertainties due to unknown masses of the Higgs bosons on the predictions for the intermediate and unification scales, ${\mathit{M}}_{\mathit{I}}$ and ${\mathit{M}}_{\mathit{U}}$, respectively, in SO(10) models. We focus on models with separate breaking scales for parity and SU(2${)}_{\mathit{R}}$ symmetries since they provide a natural realization of the seesaw mechanism for neutrino masses. For the two-step symmetry-breaking chains, where left-right-symmetric gauge groups appear at the intermediate scale, we find that parity invariance of the theory at the unification scale drastically reduces the grand-unification-theory (GUT) threshold effects in some cases. Including the effects of the intermediate-scale thresholds, we compute the uncertainty in the above mass scales and study their implications for proton lifetime and neutrino masses. An important outcome of our analysis is that if the Mikheyev-Smirnov-Wolfenstein (MSW) solution to the solar-neutrino puzzle is accepted at the 1\ensuremath{\sigma} level, it rules out SU(2${)}_{\mathit{L}}$\ifmmode\times\else\texttimes\fi{}SU(2${)}_{\mathit{R}}$\ifmmode\times\else\texttimes\fi{}U(1${)}_{\mathit{B}\mathrm{\ensuremath{-}}\mathit{L}}$\ifmmode\times\else\texttimes\fi{}SU(3${)}_{\mathit{c}}$ as an intermediate symmetry for SO(10) breaking whereas the intermediate symmetry SU(2${)}_{\mathit{L}}$\ifmmode\times\else\texttimes\fi{}SU(2${)}_{\mathit{R}}$\ifmmode\times\else\texttimes\fi{}SU(4${)}_{\mathit{c}}$ is quite consistent with it.
Do We Know What Homeostasis Model Assessment Measures?

The point-counterpoint articles in the September issue of Diabetes Care (1,2) raise several interesting issues on our understanding of insulin resistance, homeostasis model assessment (HOMA), and the future of measurement shortcuts for insulin resistance and secretion. McAuley et al. (1) provide an overview of methods to assess insulin sensitivity and secretion. The conditional nature of the title of their article implies that there is room for improvement and that something better will come along to assess insulin resistance and secretion with the convenience of HOMA but with better accuracy. For the time being, however, they support its use. Hockaday et al. (2) bring up many points that undermine confidence in HOMA as a measure of insulin resistance. Input into HOMA consists of fasting insulin and glucose concentration and thus will reflect conditions present in the basal state, with the liver as the main target for insulin action as manifested by the suppression of gluconeogenesis. A shortcoming of HOMA is the lack of complete capture of brain glucose uptake, of which 50% is non–insulin mediated. Although HOMA has been compared against the euglycemic hyperinsulinemic clamp, the current gold standard for assessment of insulin sensitivity, the latter method assesses insulin resistance in the stimulated state, which is a function to a large extent of muscle glucose disposal. Thus, an implicit assumption of HOMA is that steady-state and stimulated insulin resistance are highly correlated. Other concerns include test variability over time and the assumption that insulin resistance, if present, is common to major sites of insulin action (liver, muscle, and adipose tissue). Similarly, a number of concerns are raised about the use of HOMA to assess insulin secretion. Of particular concern is whether β-cell glycemic sensitivity can be assumed constant. In addition, other factors bear on insulin secretion that are not …
Genetic Structure of Mongolic-Speaking Kalmyks

Genetic polymorphisms of blood groups ABO and RH D, serum proteins HP, TF, and GC, and red cell enzymes ACP1, PGM1, ESD, GLO1, and SOD-A have been reported for three tribes (Torguts, Derbets, and Buzavs) of the Volga's Kalmyk-Oyrats. The Kalmyks exhibit genetic markers that are characteristic of Central Asian populations, namely, high allelic frequencies for ABO*B, TF*C2, GC*1F, ESD*2, and GLO1*2, and the rare incidence of individuals with the RH-negative phenotype. Genetic distance measures reveal that close genetic affinities exist between the Derbets and Buzavs, but both populations differ significantly from the Torguts. Collectively as an ethnic group, the Kalmyks genetically resemble the contemporary Buryats of the Baikal region of southeastern Siberia and the Mongols of Mongolia. The transplantation of the Kalmyk-Oyrats from their homeland near Lake Baikal to their current residence (4500 km) near the Caspian Sea and their subsequent isolation for more than 300 years have not appreciably altered the gene frequencies from the parental populations for frequencies of standard genetic markers.
A Hybrid Genetic Algorithm Approach for OSPF Weight Setting Problem VVvuEjil

In this paper, a method based on hybrid genetic algorithm (GA), is presented to optimize administrative weights for OSPF routing. This method can be seen as an alternative to the localsearch method in [1] or another GA-based method in [8,10]. However, the GA as well as the objective function we use are different. Instead of minimizing a convex cost function we prefer to minimize the maximum and average utilization directly. This objective function is similar as one proposed in [6,7]. In addition we combine the population-based search feature of the GA with a search heuristic representing an individual-based search method and propose a new objective function to minimize weight changes for an existing operational network. We will demonstrate our method in a case of a small network and compare the results with MIP-based (Mixed Integer Programming) method from [6,7]. Afterwards we will show the results for a bigger network with increasing traffic demands, compared with the results of some conventional weight settings as well as with the lower bound of general optimal routing (linear program / LP solution).
Detecting Deception in On and Off-line Communications

As online services become increasingly prevalent, detection of deception in electronic communication becomes vital to maintaining the many communities built around mutual trust between strangers (e.g. OkCupid, Quora, Yelp). Automating the detection process via machine learning has shown promise in recent years. This paper presents the results of using support vector machines (SVMs) and probabilistic context-free grammars (PCFGs) to classify text as truthful or deceptive. Experiments are conducted on two wellknown datasets of truthful and detective texts. A novel corpus is also developed via an online interrogation game, yielding additional insights regarding detecting deception in online conversations. The results of these experiments suggest that SVMs are superior to PCFGs at classifying deceptive text, and that the classification of deceptive text is highly dependant upon domain.
Entity Identification on Microblogs by CRF Model with Adaptive Dependency

We address the problem of entity identification on a microblog with special attention to indirect reference cases in which entities are not referred to by their names. Most studies on identifying entities referred to by their full/partial name or abbreviation, while there are many indirectly mentioned entities in microblogs, which are difficult to identify in short text such as microblogs. We therefore tackled indirect reference cases by developing features that are particularly important for certain types of indirect references and modeling dependency among referred entities by a Conditional Random Field (CRF) model. In addition, we model non-sequential order dependency while keeping the inference tractable by dynamically building dependency among entities. The experimental results suggest that our features were effective for indirect references, and our CRF model with adaptive dependency was robust even when there were multiple mentions in a microblog and achieved the same high performance as that with the fully connected CRF model.
Optimizing the temporal dynamics of light to human perception

No previous research has tuned the temporal characteristics of light-emitting devices to enhance brightness perception in human vision, despite the potential for significant power savings. The role of stimulus duration on perceived contrast is unclear, due to contradiction between the models proposed by Bloch and by Broca and Sulzer over 100 years ago. We propose that the discrepancy is accounted for by the observer’s “inherent expertise bias,” a type of experimental bias in which the observer’s life-long experience with interpreting the sensory world overcomes perceptual ambiguities and biases experimental outcomes. By controlling for this and all other known biases, we show that perceived contrast peaks at durations of 50–100 ms, and we conclude that the Broca–Sulzer effect best describes human temporal vision. We also show that the plateau in perceived brightness with stimulus duration, described by Bloch’s law, is a previously uncharacterized type of temporal brightness constancy that, like classical constancy effects, serves to enhance object recognition across varied lighting conditions in natural vision—although this is a constancy effect that normalizes perception across temporal modulation conditions. A practical outcome of this study is that tuning light-emitting devices to match the temporal dynamics of the human visual system’s temporal response function will result in significant power savings.
Low-Cost CMOS-Based Receive Modules for 60 GHz Wireless Communication

To enable mass-market applications based on short- range wireless communication around 60 GHz at datarates above 1 Gbps, cheap implementation technologies are needed. The radios for these applications often use antenna arrays with beamforming to improve the link budget. This work discusses the state-of-the-art on CMOS beamforming architectures and describes the different parts of a wireless link that is built around a four-antenna array on a PCB that also contains 45nm digital CMOS receiver ICs with beamforming capabilities. Keywords-CMOS, 60 GHz, mm-wave, phased arrays.
In-cache MapReduce: Leverage Tiling to Boost Temporal Locality-Sensitive MapReduce Computations

The MapReduce framework is being increasingly used in the scientific computing and image/video processing fields. Relevant research has tailored it for the field's specificities but there are still overwhelming limitations when it comes to temporal locality-sensitive computations. The performance of this class of computations is closely tied to an efficient use of the memory hierarchy, concern that is not yet taken into consideration by the existing distributed MapReduce runtimes. Consequently, implementing temporal locality-sensitive computations, such as stencil algorithms, on top of MapReduce is a complex chore not rewarded with proportional dividends. This paper tackles both the complexity and the performance issues by integrating tiling techniques and memory hierarchy information into MapReduce's split stage. We prototyped our proposal atop the Apache Hadoop framework, and applied it to the context of stencil computations. Our experimental results reveal that, for a typical stencil computation, our prototype clearly outperforms Hadoop MapReduce, specially as the computation scales.