Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding Survival Groups in SEER Lung Cancer Data

This paper investigates application of novel Bidirectional Data Partitioning Technique (BDP) to cancer survival analysis. Author has developed this technique for classification problems with unstable feature relevance and SEER Cancer Data illustrates this machine learning concept. BDP is applied for survival analysis in order to find groups of patients with different key factors that determine survival time. BDP operates by weights assigned to instance-feature tuples. A measure of class separability is used as a criterion in finding weights. Weights are then used within clustering in order to find clusters (subgroups of patients) with associated feature importance profiles (scored survival factors). Component models of an ensemble are built after agglomerative merging of subgroups. Because different clustering techniques typically yield different results, accuracy of an ensemble is used to establish final groups. Factors of survival time that are crucial in different situations define survival groups according to a dissimilarity principle. The results establish a base for additional epidemiological surveys and studies.
Artificial Ants for Natural Language Processing

The global sense of a text results from the interactions between the different meanings of the words that compose it. Classical approaches for applications like Word Sense Disambiguation (WSD) rely on the use of conceptual vectors that represent word meanings by concept activations. The process for determining the global sense of a text consists in propagating the different vectors within the tree that represents the syntactic structure of the text (called morphosyntactic analysis tree). Unfortunately, such strategies do not take into account interpretation trails, and constraints between word senses. We propose a new approach for this problem by considering a text in natural language as a complex system in which interacting entities are together the meanings of the words and the various elements stemmed from the text analysis. In order to express these interactions, artificial ants are used as conveyors of the meanings, besides able to modify the structure of the text by transforming the initial morphosyntactic analysis tree. The modifications are produced by ants according to both kind of stigmergy: sign-based and sematectonic stigmergies. Early experiments gave hints that beside being cognitively motivated on some aspects, this approach can perform in some difficult cases very well and is a generalization of the standard propagation.
A Business Driven Knowledge Management Process Modelling Methodology Based on Product Design Process

Knowledge management process (KMP) is the core issue of Knowledge management (KM) in organizations. It needs continuous improvement and is closely related with corresponding business process (BP). Many KM practices in organizations, however, are less effective since organizations failed to integrate KMP with BP. This study proposes a business driven KM process modelling methodology called BDKPM, providing better support for the collaboration between BP and KMP and in turn continuous optimizing KMP. This methodology is also implemented as a system called BDKPMS. Finally we give a case study of an aircraft design institute HF to illustrate how this methodology can support the collaboration between its production design process and KMP.
Common Trends and Common Cycles in Canadian Sectoral Output

The authors examine evidence of long- and short-run co-movement in Canadian sectoral output data. Their framework builds on a vector-error-correction representation that allows them to test for and compute full-information maximum-likelihood estimates of models with codependent cycle restrictions. They find that the seven sectors under consideration contain five common trends and five codependent cycles and use their estimates to obtain a multivariate Beveridge- Nelson decomposition to isolate and compare the common components. A forecast error variance decomposition indicates that some sectors, such as manufacturing and construction, are subject to persistent transitory shocks, whereas other sectors, such as financial services, are not. The authors also find that imposing common feature restrictions leads to a non-trivial gain in the ability to forecast both aggregate and sectoral output. Among the main conclusions is that manufacturing, construction, and the primary sector are the most important sources of business cycle fluctuations for the Canadian economy.
Modelling TeV γ-ray emission from the kiloparsec-scale jets of Centaurus A and M87

The widespread detection of synchrotron X-ray emission from the jets of low-power, nearby radio galaxies implies the presence of electrons at and above TeV energies. In this paper we explore the possibility that the TeV γ-rays detected from the radio galaxies Cen A and M87, which both have bright, well-studied X-ray jets, are produced at least in part by inverse-Compton scattering of various photon fields by the high-energy electrons responsible for the synchrotron X-rays on kiloparsec scales. We describe a new numerical code that we have developed to carry out inverse-Compton calculations taking account of all the relevant physics and using detailed models of the jets and the photon fields in which they are embedded, and show that existing constraints on the very high energy γ-ray fluxes of these two objects already place significant constraints on the magnetic field strengths in the jet in Cen A. Finally, we discuss the prospects for constraints on radio galaxy jet physics that may be obtained from observations with the Cerenkov Telescope Array.
Multiple objects tracking method based on particle filter

Object tracking is a challenging problem due to the presence of noise, occlusion, clutter and dynamic change in the scene other than the motion of the object of interest. A variety of tracking algorithms has been proposed and implemented to overcome the related difficulties, but there are still some problems need to be covered. In this paper, we present an approach for multiple objects tracking based on particle filter algorithm. We use the particle filter to predict the trajectory of the target. The problem of occlusion is predicted based on the likelihood measurement and estimated samples distance. The particle filter approximates a posterior probability density of the state using samples or particles. Each state is denoted as the hypothetical state of the tracked object and its weight which is predicted based on the system model. In this paper, the state is treated as a position, speed, size, scale and appearance of the object. The samples weight is considered as the likelihood of each particle which is measured based on the similarity between the colour feature of the target model and the objects. And finally, the mean state of the particles is treated as the estimated state of the object. The experiments are performed to confirm the effectiveness of the method to track multiple objects.
Chimeric Avidin – NMR Structure and Dynamics of a 56 kDa Homotetrameric Thermostable Protein

Chimeric avidin (ChiAVD) is a product of rational protein engineering remarkably resistant to heat and harsh conditions. In quest of the fundamentals behind factors affecting stability we have elucidated the solution NMR spectroscopic structure of the biotin–bound form of ChiAVD and characterized the protein dynamics through 15N relaxation and hydrogen/deuterium (H/D) exchange of this and the biotin–free form. To surmount the challenges arising from the very large size of the protein for NMR spectroscopy, we took advantage of its high thermostability. Conventional triple resonance experiments for fully protonated proteins combined with methyl–detection optimized experiments acquired at 58°C were adequate for the structure determination of this 56 kDa protein. The model–free parameters derived from the 15N relaxation data reveal a remarkably rigid protein at 58°C in both the biotin–bound and the free forms. The H/D exchange experiments indicate a notable increase in hydrogen protection upon biotin binding.
Inter-Specific Competition, but Not Different Soil Microbial Communities, Affects N Chemical Forms Uptake by Competing Graminoids of Upland Grasslands

Evidence that plants differ in their ability to take up both organic (ON) and inorganic (IN) forms of nitrogen (N) has increased ecologists’ interest on resource-based plant competition. However, whether plant uptake of IN and ON responds to differences in soil microbial community composition and/or functioning has not yet been explored, despite soil microbes playing a key role in N cycling. Here, we report results from a competition experiment testing the hypothesis that soil microbial communities differing in metabolic activity as a result of long-term differences to grazing exposure could modify N uptake of Eriophorum vaginatum L. and Nardus stricta L. These graminoids co-occur on nutrient-poor, mountain grasslands where E. vaginatum decreases and N. stricta increases in response to long-term grazing. We inoculated sterilised soil with soil microbial communities from continuously grazed and ungrazed grasslands and planted soils with both E. vaginatum and N. stricta, and then tracked uptake of isotopically labelled NH4 + (IN) and glycine (ON) into plant tissues. The metabolically different microbial communities had no effect on N uptake by either of the graminoids, which might suggest functional equivalence of soil microbes in their impacts on plant N uptake. Consistent with its dominance in soils with greater concentrations of ON relative to IN in the soluble N pool, Eriophorum vaginatum took up more glycine than N. stricta. Nardus stricta reduced the glycine proportion taken up by E. vaginatum, thus increasing niche overlap in N usage between these species. Local abundances of these species in mountain grasslands are principally controlled by grazing and soil moisture, although our results suggest that changes in the relative availability of ON to IN can also play a role. Our results also suggest that coexistence of these species in mountain grasslands is likely based on non-equilibrium mechanisms such as disturbance and/or soil heterogeneity.
HEURISTICS FOR LICENSE PLATE DETECTION AND EXTRACTION

License Plate Detection from images requires the segmentation of the license plate (LP) region from the larger image acquired by the camera. While there may be several LP candidate areas, the detection of the LP area (LPA) requires various diverse methods of image processing to be applied. After detection of a candidate LPA we extract the possible alphanumeric information. We further process the LPA information using heuristics to reject those candidates which may contain alphanumeric like region but which may not be LP information. In this paper we present several heuristics that successfully allow the detection and extraction of alphanumeric regions from correctly identified LPA. Subsequently the extracted alphanumeric regions are recognized by Optical Character Recognition (OCR). Experiments on a number of images on Indian as well as international license plates acquired from the internet and some of our own images are shown here. We find that an accuracy of 88% is obtained from the images in the dataset. The open source software OpenCV configured with Code Blocks IDE (http://sourceforge.net/projects/opencvlibrary/) was used for the experimentation.
Depth+Texture Representation for Image Based Rendering

Image Based Rendering holds a lot of promise for navigating through a real world scene without modeling it manually. Different representations have been proposed for IBR in the literature. In this paper, we argue that a representation using depth maps and texture images from a number of viewpoints is a rich and viable representation for IBR. We discuss different aspects of this representation including capture, representation, compression and rendering. We show several results to show how the representation can be used to model and render complex scenes.
Exploring multidimensional landscapes without a map

A discussion of methodologies for nonlinear geophysical inverse problems is presented. Geophysical inverse problems are often posed as optimization problems in a finite-dimensional parameter space. An Earth model is usually described by a set of parameters representing one or more geophysical properties (e.g. the speed with which seismic waves travel through the Earth's interior). Earth models are sought by minimizing the discrepancies between observation and predictions from the model, possibly, together with some regularizing constraint. The resulting optimization problem is usually nonlinear and often highly so, which may lead to multiple minima in the misfit landscape. Global (stochastic) optimization methods have become popular in the past decade. A discussion of simulated annealing, genetic algorithms and evolutionary programming methods is presented in the geophysical context. Less attention has been paid to assessing how well constrained, or resolved, individual parameters are. Often this problem is poorly posed. A new class of method is presented which offers potential in both the optimization and the `error analysis' stage of the inversion. This approach uses concepts from the field of computational geometry. The search algorithm described here does not appear to be practical in problems with dimension much greater than 10.
Morality Metrics On Iterated Prisoner ’ s Dilemma Players

Research regarding Iterated Prisoner’s Dilemma (IPD) tournaments generally focuses on the objective performance of strategies. This paper instead discusses moral judgement of strategies, and analyzes IPD stratagies’ behaviors through clearly defined morality functions. No single moral code is accepted by everyone, so multiple moral views are represented in this paper. Its purpose is not to argue for a specific moral view (or to attempt to cover all possible views), but rather to present a useful method of moral analysis as well as some interesting, mathematically well-defined morality functions corresponding (or at least relevant) to real-world views represented in society.
Improved phone recognition using Bayesian triphone models

A crucial issue in triphone based continuous speech recognition is the large number of models to be estimated against the limited availability of training data. This problem can be relieved by composing a triphone model from less context-dependent models. This paper introduces a new statistical framework, derived from the Bayesian principle, to perform such a composition. The potential power of this new framework is explored, both algorithmically and experimentally, by an implementation with hidden Markov modeling techniques. This implementation is applied to the recognition of the 39-phone set on the TIMIT database. The new model achieves 74.4% and 75.6% accuracy, respectively, on the core and complete test sets.
Fe II Emission in 14 Low-Redshift Quasars. I. Observations

We present the spectra of 14 quasars with a wide coverage of rest wavelengths from 1000 to 7300 Å. The redshift ranges from z = 0.061 to 0.555 and the luminosity from MB = -22.69 to -26.32. These spectra of high quality result from combining Hubble Space Telescope spectra with those taken from ground-based telescopes. We describe the procedure of generating the template spectrum of Fe II line emission from the spectrum of a narrow-line Seyfert 1 galaxy, I Zw 1, that covers two wavelength regions of 2200-3500 and 4200-5600 Å. Our template Fe II spectrum is semiempirical in the sense that the synthetic spectrum calculated with the CLOUDY photoionization code is used to separate the Fe II emission from the Mg II λ2798 line. The procedure of measuring the strengths of Fe II emission lines is twofold: (1) subtracting the continuum components by fitting models of the power-law and Balmer continua in the continuum windows, which are relatively free from line emissions, and (2) fitting models of the Fe II emission based on the Fe II template to the continuum-subtracted spectra. From 14 quasars including I Zw 1, we obtained the Fe II fluxes in five wavelength bands (U1 [2200-2660 Å], U2 [2660-3000 Å], U3 [3000-3500 Å], O1 [4400-4700 Å], and O2 [5100-5600 Å]), the total flux of Balmer continuum, and the fluxes of Mg II λ2798, Hα, and other emission lines, together with the full widths at half-maximum (FWHMs) of these lines. Regression analysis was performed by assuming a linear relation between any two of these quantities. Eight correlations were found with a confidence level higher than 99%: (1) larger Mg II FWHM for larger Hα FWHM, (2) larger Γ for fainter MB, (3) smaller Mg II FWHM for larger Γ, (4) larger Mg II FWHM for smaller Fe II(O1)/Mg II, (5) larger MBH for smaller Γ, (6) larger MBH for smaller Fe II(O1)/Mg II, (7) larger [O III]/Hβ for larger Mg II FWHM, and (8) larger Fe II(O1)/Mg II for larger Fe II(O1)/Fe II(U1). The fact that six of these eight are related to FWHM or MBH (∝FWHM2) may imply that MBH is a fundamental quantity that controls Γ or the spectral energy distribution (SED) of the incident continuum, which in turn controls the Fe II emission. Furthermore, it is worthy of noting that Fe II(O1)/Fe II(U1) is found to tightly correlate with Fe II(O1)/Mg II, but not with Fe II(U1)/Mg II.
The Broad-Spectrum Blast Resistance Gene Pi9 Encodes a Nucleotide-Binding Site–Leucine-Rich Repeat Protein and Is a Member of a Multigene Family in Rice

The broad-spectrum rice blast resistance gene Pi9 was cloned using a map-based cloning strategy. Sequencing of a 76-kb bacterial artificial chromosome (BAC) contig spanning the Pi9 locus led to identification of six tandemly arranged resistance-like genes with a nucleotide-binding site (NBS) and leucine-rich repeats (LRRs) (Nbs1-Pi9–Nbs6-Pi9). Analysis of selected Pi9 deletion mutants and transformation of a 45-kb fragment from the BAC contig into the susceptible rice cultivar TP309 narrowed down Pi9 to the candidate genes Nbs2-Pi9 and Nbs3-Pi9. Disease evaluation of the transgenic lines carrying the individual candidate genes confirmed that Nbs2-Pi9 is the Pi9 gene. Sequence comparison analysis revealed that the six paralogs at the Pi9 locus belong to four classes and gene duplication might be one of the major evolutionary forces contributing to the formation of the NBS–LRR gene cluster. Semiquantitative reverse transcriptase (RT)–PCR analysis showed that Pi9 was constitutively expressed in the Pi9-resistant plants and was not induced by blast infection. The cloned Pi9 gene provides a starting point to elucidate the molecular basis of the broad-spectrum disease resistance and the evolutionary mechanisms of blast resistance gene clusters in rice.
Lack of natural weighted estimates for some singular integral operators

We show that the classical Hormander condition, or analogously the L r -Hormander condition, for singular integral operators T is not sufficient to derive Coifman's inequality ∫ Rn |Tf(x)| p w(x)dx ≤ C ∫ Rn Mf(x) p w(x)dx, where 0 < p < ∞, M is the Hardy-Littlewood maximal operator, w is any A∞ weight and C is a constant depending upon p and the A∞ constant of w. This estimate is well known to hold when T is a Calderon-Zygmlmd operator. As a consequence we deduce that the following estimate does not hold: ∫ Rn |T f (x)| p w(x) dx ≤ C ∫ Rn Mf(x) p Mw(x)dx, where 0 < p ≤ 1 and where w is an arbitrary weight. However, by a recent result due to A. Lerner, this inequality is satisfied whenever T is a Calderon-Zygmund operator. One of the main ingredients of the proof is a very general extrapolation theorem for A∞ weights.
Measuring the Main Parameters of the Human Body in Images by Canny Edge Detector

The main parameters of the human body can identify and estimate images easier. In this research, various images of people (short, long, lean and obese) were examined and their main features were extracted from the images. In this paper, four types of people in 2D dimension image will be tested and proposed. The system will extract the size and the advantage of them (such as: tall fat, short fat, tall thin and short thin) from images. Fat and thin, according to their result from the human body that has been extract from image, will be obtained. Also the system extract every size of human body such as length, width and shown them in the output.
Physical Activity and Gastrointestinal Cancers: Primary and Tertiary Preventive Effects and Possible Biological Mechanisms

Gastrointestinal cancers account for 37% of all cancer deaths worldwide, underlining the need to further investigate modifiable factors for gastrointestinal cancer risk and prognosis. This review summarizes the corresponding evidence for physical activity (PA), including, briefly, possible biological mechanisms. Despite high public health relevance, there is still a scarcity of studies, especially for tertiary prevention. Besides the convincing evidence of beneficial effects of PA on colon cancer risk, clear risk reduction for gastroesophageal cancer was identified, as well as weak indications for pancreatic cancer. Inverse associations were observed for liver cancer, yet based on few studies. Only for rectal cancer, PA appeared to be not associated with cancer risk. With regard to cancer-specific mortality of the general population, published data were rare but indicated suggestive evidence of protective effects for colon and liver cancer, and to a lesser extent for rectal and gastroesophageal cancer. Studies in cancer patients on cancer-specific and total mortality were published for colorectal cancer only, providing good evidence of inverse associations with post-diagnosis PA. Overall, evidence of associations of PA with gastrointestinal cancer risk and progression is promising but still limited. However, the already available knowledge further underlines the importance of PA to combat cancer.
A color based fuzzy algorithm for CBIR

Volume of the information on the World Wide Web has become very huge in which digital images occupy the largest chunk of such information due to availability of good-quality digital photographic tools in affordable prices. Goal of ongoing research in the field of Image Retrieval is not only the expansion of storage capacity but also the development of effective and efficient retrieval techniques. The objective of this research is to find a solution for retrieving image information from digital image databases with better rate of recall and precision using theory of soft computing which is suitable to model a system for digital image retrieval because of the capability of this approach to capture the vague and imprecise information in digital images. In this paper a review of conventional and content-based image retrieval techniques has been given and finally a color based fuzzy algorithm for CBIR has been implemented by using Fuzzy C-Means algorithm.
Potential guided directional-RRT* for accelerated motion planning in cluttered environments

Recently proposed Rapidly Exploring Random Tree Star (RRT*) algorithm which is an extension of Rapidly Exploring Random Tree (RRT) provides collision free asymptotically optimal path regardless of obstacle's geometry in a given environment. However, the drawback of this technique is a slow processing rate. This paper presents our proposed Potential Guided Directional-RRT* which addresses this problem and provides accelerated processing rate by incorporating Artificial Potential Fields Algorithm into RRT*. Artificial Potential Field algorithm directs the random samples toward the goal which leads to an increase in the speed of RRT*. We have presented simulation results of our technique and their comparison with results of RRT* under different environmental conditions to demonstrate apace execution rate of our novel idea.