Miracle-dz/UniFAR-FTUs huggingface dataset:
Adapting RANSAC SVM to Detect Outliers for Robust Classification

Most visual classification tasks assume the authenticity of the label information. However, due to several reasons such as difficulty of annotation or inadvertently due to human error, the annotation can often be noisy. This results in wrongly annotated examples. In this paper, we consider the examples that are wrongly annotated to be outliers. The task of learning a robust inlier model in the presence of outliers is typically done through the RANSAC algorithm[6]. We show that instead of adopting RANSAC to obtain the ‘right’ model, we could use many instances of randomly sampled subsets to build a lot of models. The collective decision of all these models can be used to identify examples that are likely to be outliers. This results in a modification to RANSAC SVM[11] to explicitly obtain probable outliers from the set of given examples. Once the outliers are detected, these examples are excluded from the training set. We also show that the method can be used to identify very hard examples present in the training data. In this case, where we believe that the examples are correctly annotated, we can achieve good generalization when such examples are excluded from the training set. The method is evaluated using the standard PASCAL VOC 2007 dataset[4]. We show that the method is particularly suited for identifying wrongly annotated examples resulting in improvement of more than 12% over the RANSAC-SVM approach. Hard examples in PASCAL VOC dataset are also identified by this method and this even results in a marginal improvement of the mean average precision over the base classifier provided with all clean examples.
Manganese‐enhanced magnetic resonance imaging (MEMRI) of mouse brain development

Given the importance of genetically modified mice in studies of mammalian brain development and human congenital brain diseases, MRI has the potential to provide an efficient in vivo approach for analyzing mutant phenotypes in the early postnatal mouse brain. The combination of reduced tissue contrast at the high magnetic fields required for mice, and the changing cellular composition of the developing mouse brain make it difficult to optimize MRI contrast in neonatal mouse imaging. We have explored an easily implemented approach for contrast‐enhanced imaging, using systemically administered manganese (Mn) to reveal fine anatomical detail in T1‐weighted MR images of neonatal mouse brains. In particular, we demonstrate the utility of this Mn‐enhanced MRI (MEMRI) method for analyzing early postnatal patterning of the mouse cerebellum. Through comparisons with matched histological sections, we further show that MEMRI enhancement correlates qualitatively with granule cell density in the developing cerebellum, suggesting that the cerebellar enhancement is due to uptake of Mn in the granule neurons. Finally, variable cerebellar defects in mice with a conditional mutation in the Gbx2 gene were analyzed with MEMRI to demonstrate the utility of this method for mutant mouse phenotyping. Taken together, our results indicate that MEMRI provides an efficient and powerful in vivo method for analyzing neonatal brain development in normal and genetically engineered mice. Copyright © 2004 John Wiley & Sons, Ltd.
A Concealed Data Aggregation Using PrivacyHomomorphism in Wireless Sensor Networks

Data aggregation is a process in which data is collected from the sensor nodes and sent to the base station via cluster heads. Data aggregation schemes are vulnerable to various security attacks. Such Attacks take place compromising at the sensor node and cluster head levels. An adversary node eavesdrops the sensed data, modifies and injects forged data. Security plays a key role in the data aggregation process and the base station needs to confirm data integrity and authenticity. Data aggregation schemes based on privacy homomorphism (PH) provide better security compared with traditional aggregation. In PH based encryption the cluster heads can directly aggregate the cipher texts without decryption. The proposed System is based on privacy homomorphism encryption and uses elliptic curve Cryptography (algorithm) to encrypt the sensed data. And this system deals with transmitting difference data rather than the raw sensed data from sensor node. Compared to the existing aggregation schemes, the differential data transfer achieves more energy efficiency and increase in the packet delivery ratio.
Carotenoid-based epaulettes reveal male competitive ability: experiments with resident and floater red-shouldered widowbirds

Many birds display carotenoid-based ornaments, which are typically considered to be honest indicators of individual health and condition. Experimental work on male red-shouldered widowbirds, Euplectes axillaris, has demonstrated a function of the carotenoid-based epaulettes in male contests and territory acquisition. Using two experiments, we investigated whether the natural variation in this colour signal reveals male competitive ability. Males with larger and redder (more longwave) epaulettes established territories to the exclusion of males with smaller and less red signals, which formed a large population of ‘floaters’. In an experiment in which we removed 42 resident males, these floaters rapidly filled up vacant territories. Among removed birds held in captivity, residents strongly dominated floaters in dyadic contests over access to an easily monopolized feeder (i.e. outside the context of territory defence). Only epaulette size predicted the outcome of these male contests. In addition, when competitors were experimentally given similar epaulette signals (removed or painted red to the average population size), the males were involved in more aggressive interactions than during unmanipulated contests, but residents continued to outcompete floaters. On release (after 8 days) to the breeding grounds, most residents (88%) rapidly reclaimed their territories from replacements. Combined, these results suggest that some intrinsic ‘resource-holding potential’, associated with the variation in epaulette signal, is primarily responsible for residents dominating nonresidents.  2003 Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour.
An upper bound on the characteristic polynomial of a nonnegative matrix leading to a proof of the Boyle-Handelman conjecture

In their celebrated 1991 paper on the inverse eigenvalue problem for nonnegative matrices, Boyle and Handelman conjectured that if A is an (n+1) × (n+1) nonnegative matrix whose nonzero eigenvalues are: λ 0 > |λ i |, i = 1,. ,r, r λ 0 , (*) Π r (x-λ i ) 0, for all k > 1. i=0 A strong form of the Boyle-Handelman conjecture, conjectured in 2002 by the present authors, says that (*) continues to hold if the trace inequalities in (**) hold only for k = 1,. , r. We further improve here on earlier results of the authors concerning this stronger form of the Boyle-Handelman conjecture.
The Mediate Effect of Employee Engagement on the Relationship between Perceived Employer Branding and Discretionary Effort

The purpose of this study is to test the relationships among employer branding, employee engagement, and discretionary effort via the effect of employee expectation. A survey was conducted with 1,349 current employees working in Thai petroleum industry. The results indicated that there were strong positive relationships between employer branding and employee engagement, employee engagement and discretionary effort, employer branding and discretionary effort, employer branding and employee expectation, and employee expectation and employee engagement. The results further indicated that there was a partial effect of employer branding on employee engagement through employee expectation, while there was also a partial effect of employer branding on discretionary effort through employee engagement.
Streak detection in mottled and noisy images

We describe a method for automatically detecting streaks in printed images using adaptive window-based image pro- jections and mutual information. The proposed approach accepts a scanned image enclosing the defect and computes the projections across the entire image at different window sizes. The resulting traces collected from the projections are analyzed with a peak de- tection algorithm and subsequently correlated using normalized mu- tual information to pinpoint the location and width of streak(s). Fi- nally, for a given peak, the window size is changed adaptively to identify and locate the intensity and length of the corresponding streak(s) while maximizing the signal-to-noise ratio. Results on syn- thetic and real-life images are provided to demonstrate the effective- ness of our proposed technique. © 2007 SPIE and IS&T.
A Link Prediction Method That Can Learn from Network Dynamics

Link prediction is an important issue in Social Network Analysis area. Most of the existing link prediction methods aim to find the missing links or to predict the future links mainly based on a static network, ignoring the evolution of the network over time. This paper proposes a link prediction method that can learn from network dynamics. Using machine learning techniques, the method models the changes over time of several structural features in the network. One classifier is trained for each structural feature and the final prediction result is obtained by weighting all the classifiers. The experimental results of three real collaboration networks show that the proposed method outperforms both a traditional static method and a state-of-art dynamic method. Moreover, the experiments also show that the ability to describe network dynamics for different structural features is also different.
Prototyping an inconsistency checking tool for software process models

Software process modeling has attracted much research effort in software engineering. However, there is little work reported for the verification of process models. In fact, the verification is often either performed by hand or it is left to the enacting mechanism to detect inconsistencies during execution. Since process models are becoming more and more powerful and complex, their verification is also becoming increasingly difficult and critical. The authors proposition is that one needs special tools to help verify the consistency of software process models. They present part of their experience in designing and prototyping such a tool for the verification of software process models in the ALF project. The tool helps verify the partial consistency of process models by statically detecting various inconsistencies. This prototype uses techniques developed in different fields such as compilation, constraint solving and logic. As far as they know, this is the first tool of its kind designed for the static checking for process models. <<ETX>>
Variable mesh optimization for the 2013 CEC Special Session Niching Methods for Multimodal Optimization

Many real-world problems have several optima, and the aim of niching optimisation algorithms is to obtain the different global optima, and not only the best solution. One common technique to create niches is the clearing method that removes solutions too close to better ones. Unfortunately, clearing is very sensitive to the niche radius, and its right value depends on the problem (in real-world problems the minimum distance between optima is unknown). In this work we propose a niching algorithm that uses clearing with an adaptive niche radius, that decreases during the run. The proposal uses an external memory that stores current global optima to avoid losing found optima during the clearing process, allowing a non-elitist search. This algorithm applies this clearing method to a mesh of solutions, expanded by the generation of nodes using combination methods between the nodes, their best neighbour, and their nearest current global optima in the population (current global optima are nodes with fitness very similar to current best fitness). The proposal is tested on the competition benchmark proposed in the Special Session Niching Methods for Multimodal Optimization, and compared with other algorithms. The proposal obtains very good results detecting global optima. In comparisons with other algorithm, this proposal obtains the best results, proving to be a very competitive niching algorithm.
Lattice Boltzmann method simulation gas slip flow in long microtubes

Purpose – This paper aims to examine how using lattice Boltzmann method (LBM) aids the study of the isothermal‐gas flow with slight rarefaction in long microtubes.Design/methodology/approach – A revised axisymmetric lattice Boltzmann model is proposed to simulate the flow in microtubes. The wall boundary condition combining the bounce‐back and specular‐reflection schemes is used to capture the slip velocity on the wall. Appropriate relation between the Knudsen number and relax‐time constant is defined.Findings – The computed‐slip velocity, average velocity and non‐linear pressure distribution along the microtube are in excellent agreement with analytical solution of the weakly compressible Navier‐Stokes equations. The calculated‐friction factors are also consistent with available experimental data. For simulations of slip flow in microtube, LBM is more accurate and efficient than DSMC method.Research limitations/implications – The laminar flow in circular microtube is assumed to be axisymmetric. The prese.
Global FDTD Maxwell's Equations Modeling of Electromagnetic Propagation From Currents in the Lithosphere

Electromagnetic wave propagation from electric currents within the Earth's crust is investigated using a three-dimensional finite-difference time-domain (FDTD) full-vector Maxwell's equations model of the global Earth-ionosphere cavity. The FDTD model employed extends from km below sea level to an altitude of km, and can account for arbitrary horizontal as well as vertical geometrical and electrical inhomogeneities and anisotropies of the ionosphere, lithosphere, and oceans. Using this model, the surface horizontal magnetic field is calculated for different depths and orientations of an electric current occurring below the epicenter of the 1989 Loma Prieta earthquake. Results show that the alignment and depth of the electric current within the Earth's crust yields significant differences for the calculated surface magnetic field time-waveforms and spectra. Further, it is found that EM wave phenomena measured at the Earth's surface due to electric currents buried in the Earth's crust will only have significant spectra below 1 Hz.
Variance-constrained filtering for uncertain stochastic systems with missing measurements

In this note, we consider a new filtering problem for linear uncertain discrete-time stochastic systems with missing measurements. The parameter uncertainties are allowed to be norm-bounded and enter into the state matrix. The system measurements may be unavailable (i.e., missing data) at any sample time, and the probability of the occurrence of missing data is assumed to be known. The purpose of this problem is to design a linear filter such that, for all admissible parameter uncertainties and all possible incomplete observations, the error state of the filtering process is mean square bounded, and the steady-state variance of the estimation error of each state is not more than the individual prescribed upper bound. It is shown that, the addressed filtering problem can effectively be solved in terms of the solutions of a couple of algebraic Riccati-like inequalities or linear matrix inequalities. The explicit expression of the desired robust filters is parameterized, and an illustrative numerical example is provided to demonstrate the usefulness and flexibility of the proposed design approach.
Complete Genome Sequence of Noninvasive Streptococcus pyogenes M/emm28 Strain STAB10015, Isolated from a Child with Perianal Dermatitis in French Brittany

ABSTRACT We report here the complete genome sequence of a noninvasive strain of Streptococcus pyogenes M/emm28, isolated from perianal dermatitis in a child. The genome is composed of 1,950,454 bp, with a G+C content of 38.2%, and it has 1,925 identified coding sequences and harbors two intact prophages and a new integrating conjugative element (ICE).
Haplo-Insufficiency of MPK3 in MPK6 Mutant Background Uncovers a Novel Function of These Two MAPKs in Arabidopsis Ovule Development[W]

The plant life cycle includes diploid sporophytic and haploid gametophytic generations. Female gametophytes (embryo sacs) in higher plants are embedded in specialized sporophytic structures (ovules). Here, we report that two closely related mitogen-activated protein kinases in Arabidopsis thaliana, MPK3 and MPK6, share a novel function in ovule development: in the MPK6 mutant background, MPK3 is haplo-insufficient, giving female sterility when heterozygous. By contrast, in the MPK3 mutant background, MPK6 does not show haplo-insufficiency. Using wounding treatment, we discovered gene dosage–dependent activation of MPK3 and MPK6. In addition, MPK6 activation is enhanced when MPK3 is null, which may help explain why mpk3−/− mpk6+/− plants are fertile. Genetic analysis revealed that the female sterility of mpk3+/− mpk6−/− plants is a sporophytic effect. In mpk3+/− mpk6−/− mutant plants, megasporogenesis and megagametogenesis are normal and the female gametophyte identity is correctly established. Further analysis demonstrates that the mpk3+/− mpk6−/− ovules have abnormal integument development with arrested cell divisions at later stages. The mutant integuments fail to accommodate the developing embryo sac, resulting in the embryo sacs being physically restricted and female reproductive failure. Our results highlight an essential function of MPK3 and MPK6 in promoting cell division in the integument specifically during ovule development.
Performance analysis of unconventional dictionary on retinal images

Signals are sparsely represented by a set of over-complete basis vectors called dictionary. Atoms of a dictionary are either chosen from a predefined set of functions such as Discrete Cosine Transform (DCT), Wavelets, Gabor, Contourlets, and Curvelets or learned from an image itself. Recently, a nonlinear (NL) dictionary has been proposed by adding NL functions to the conventional DCT atoms. This paper presents performance of a novel NL dictionary for retinal image reconstruction and denoising. The NL dictionary demonstrates good performance and can be adapted if shorter execution time is required.
NLOS Error Mitigation for UWB Ranging in Dense Multipath Environments

To mitigate the non-line-of-sight (NLOS) error of ultra-wideband (UWB) ranging caused by obstructions in dense multipath environments, this paper proposed a novel NLOS error mitigation method. The principles and characteristics of NLOS error are analyzed. Based on the signal propagation path loss model, the NLOS error estimation expression is deduced and further used to calibrate the ranging results. Low complexity path detection algorithms are proposed for implementation of the method. Test on measured data shows that the method can improve the ranging precision greatly.
A case study of English-medium education in Bhutan

This thesis examines the implementation of the policy for English-medium education in government-run schools in Bhutan, a small multilingual developing country in the eastern Himalayas. It identifies factors influencing its effective implementation, plus policy and practice measures to improve learning outcomes for students. It takes as a theoretic framework an approach known as ‘content and language integrated learning’ (CLIL). This involves integration of language and subject teaching. The study addresses the following research question: How can implementation of Bhutan’s policy of English-medium education be enhanced? Data to address these questions were gathered through a literature review, key informant interviews, focus group discussions and classroom observations. The study also draws on personal experience. The findings reveal that implementation of Bhutan’s policy of English-medium government-run education could be significantly enhanced. Students are not attaining control over English at desired levels of schooling; classroom practices favour didactic teaching-learning approaches; teachers’ tend to teach toward terminal examinations and adhere to traditional teacher and student roles; and subject teachers do not consistently support students’ English language development. The study also found that many stakeholders, including policy-makers, teachers, curriculum developers and teacher trainers lack awareness of the concept of language-related disadvantage in education and approaches for more effective second language-medium teaching and learning. This includes a lack of language-sensitive classroom practices in both language and subject classes. These findings highlight the need for teachers to make different methodological choices inside classrooms. To do this, teachers should become skilled and confident in the use of classroom practices which support students’ English language learning. Key stakeholders, particularly policy-makers, teachers and teacher educators, must understand and accept the need for further policy and practice measures to support language-sensitive teaching-learning approaches for English-medium education in Bhutan. The implications of these findings for policy, practice and future research are further elucidated.
Asian English Writers of Chinese Origin: Singapore, Malaysia, Hong Kong

This is the first book to bring together nine Asian English writers of Chinese descent from Singapore, Malaysia and Hong Kong: Catherine Lim, Christine Lim, Ee Tiang Hong, Kee Thuan Chye, Lee Kok Liang, Shirley Lim, Timothy Mo, Xu Xi and Agnes Lam. It discusses how the withdrawal of colonial power and the implementation of nation-building policies impact race/ethnicity, class and language in these former British colonies. The last chapters take a special look at postcolonialism and gender politics, and explore how Chinese women, at home or abroad, defy the Orientalist gaze and the native patriarchy.