Miracle-dz/UniFAR-FTUs huggingface dataset:
3D Object Reconstruction Using Single Image

Recentely, many algorithms were implemeneted; in order to get better and accurate 3D modeling. In this paper, five proposed methods were presented for 3D object reconstruction from a single 2D color image. The basic idea of the five proposed algorithms: depend on changing the process of 3D reconstruction from single image to 3D reconstruction using two images on which feature extraction and matching were applied and after finding correspondences a 3D model can be obtained. KanadeLucas-Tomasi (KLT) and Scale Invariant Feature Transform (SIFT) algorithms used for feature extraction and matching. Experiments were applied in this approach to explore the effectiveness of our methods.
Is patients’ loneliness a matter for general practice? A qualitative study

Background Loneliness is linked to morbidity and mortality and use of social and health services resources. Therefore, general practitioners may have an import ant role to play. Hoverer, not much is known about how general practitioners handle loneliness i n their patients, and not much is known about the GPs’ attitudes and willingness to take on this task . Objective This study focuses on GPs awareness of patients’ lo neliness and their attitudes towards and perceptions of possibilities to actively address lo ne iness during consultations. Methods We performed semi-structured interviews with 13 Dan ish general practitioners from urban and rural areas. The interviews were transcribed for thematic analysis. Results The interviewees had slightly different definitions of loneliness, but these differences did not seem to affect their attitudes and behaviour regarding l one y patients. Some were hesitant to mention the word loneliness in the dialogue with the patient an d to write it in the patient record. The interviewees all regarded social network and loneli ness to be a natural part of an anamnesis when relevant, but they did not consider it obvious to i nvestigate feelings of loneliness in patients as an isolated task of theirs. Reasons for this were that ”jus diagnosing loneliness” was of limited use – or might be contraindicated – because GPs themselve s normally have no tools or options to alleviate this feeling. Knowledge of municipal and other support activities for lonely people that GPs can refer to or recommend was limited. Conclusions Patients’ feelings of loneliness were rarely on the ag nda during general practice consultations though general practitioners regarded patients’ lon eliness and social network as a critical factor in disease and recovery. The dominant feeling of the G Ps was that they themselves cannot help the patient get rid of the feeling of loneliness; and t he GPs called for updated information on relevant activities outside general practice in order to be a le to guide, motivate, and refer lonely patients.
Risks of Untrustworthiness

This paper revisits the risks of untrustworthiness, and considers some incidents involving computer-based systems that have failed to live up to what had been expected of them. The risks relate to security, reliability, survivability, human safety, and other attributes, and span a variety of applications and critical infrastructures - such as electric power, telecommunications, transportation, finance, medical care, and elections. The range of causative factors and the diversity of the resulting risks are both enormous. Unfortunately, many of the problems seem to recur far too often. Various lessons there from and potential remedies are discussed
Kainate receptor gene expression in the developing rat brain

Kainate-preferring receptors are a subclass of ionotropic glutamate receptors that might play a role in brain development. The expression of the five known genes encoding kainate receptor subunits (GluR-5, -6, -7, KA-1, and KA-2) was studied by in situ hybridization during pre- and postnatal development of the rat brain. We compared the combined expression patterns of these genes with autoradiography using 3H- kainate in the developing brain from embryonic day 12 (E12) through to adult. Although mRNAs for the receptor subunits (except KA-1) can be detected at stage E12, 3H-kainic acid binding (as an index of receptor protein) is not found at this stage. However, by E14 high-affinity kainate sites are found throughout the gray matter, but particularly in spinal cord, primordial cerebellum, and ventral forebrain structures. All genes undergo a peak in their expression in the late embryonic/early postnatal period. GluR-5 expression during development shows the most interesting features because the changes are qualitative. The GluR-5 gene shows peaks of expression around the period of birth in the sensory cortex (layers II, III, and IV), in CA1 hippocampal interneurons in the stratum oriens, in the septum, and in the thalamus. GluR-6 shows a prenatal expression peak in the cingulate gyrus of the neocortex. KA-1 transcripts appear with the development of the hippocampus and remain largely confined to discrete areas such as the CA3 region, the dentate gyrus, and subiculum. KA-2 transcripts are found throughout the CNS from as early as E12 and remain constant until adulthood. The GluR-5 and GluR-6 genes are coexpressed in multiple peripheral ganglia (e.g., cranial nerve ganglia, dorsal root ganglia, and mural ganglia) at E14.
Some sex hormone profiles are consistent over time in normal menstruating women: implications for sports injury epidemiology

Purpose It is unclear whether sex hormone profiles obtained in two consecutive months are consistent within women. Month-to-month consistency in daily, nadir, peak and mean hormone concentrations during the early follicular and luteal phases in recreationally active, young eumenorrheic women was prospectively examined. Methods 60 healthy, non-smoking women who reported normal and consistent menstrual cycles lasting 26–32 days for the past 6 months were followed prospectively to obtain serum samples for the first 6 days of menses and for 8 days after a positive ovulation test over two consecutive months. Month-to-month consistency of daily concentrations of oestradiol (pg/ml), progesterone (ng/ml), testosterone (ng/dl), sex hormone-binding globulin (nmol/l) and free androgen index were determined using linear mixed models. Month-to-month consistency in nadir, peak and mean concentrations were then assessed using intraclass correlation coefficients and SEM to more precisely examine intraindividual consistency. Results Linear mixed models revealed stable hormone concentrations across cycles and cycles by day. Reliability estimates for nadir, peak, mean menses and mean postovulatory concentrations range from 0.56 to 0.86 for oestradiol, 0.44 to 0.91 for progesterone, 0.60 to 0.86 for testosterone, 0.88 to 0.97 for sex hormone-binding globulin and 0.78 to 0.91 for free androgen index. Conclusions Hormone profiles were reproducible over two consecutive months. To reduce month-to-month intraindividual variations and improve measurement consistency, it is recommended that multiple samples be taken over consecutive days as opposed to a single sample.
Automatic Detection of Salient Object Based on Multi-Features

Many existing detecting measures of salient object mostly depend on the information between the pixels and lack for the comprehension of salient object features. This paper presents an unsupervised algorithm for automatically extracting the interesting object. We firstly extract the junior feature as basic elements of saliency by a biologically plausible Gabor model, and then combine the understanding knowledge of the salient object to define the local feature, which is used to locate the salient regions further. Finally, a novel extracting scheme based on fuzzy threshold approach is proposed, which acts on the conspicuity map integrated by the junior and local features to locate the salient object. Apply the algorithm on various images for the simulation experiments, the satisfying results are obtained. That shows the algorithm is feasible.
VIEW-CENTRIC REASONING ABOUT SPACE-BASED MIDDLEWARE

Distributed computing systems, including those that utilize space-based middleware, present significant challenges when attempting to reason formally about their behaviors and properties. In particular, two or more computational events may occur in parallel. We introduce View-Centric Reasoning (VCR)—a set of abstractions that comprises a general framework for reasoning about parallel and distributed computation. First we extend the CSP metaphor to support traces of parallel events, rather than the traditional random interleaving of individual events. Next we introduce the concept of views to represent explicitly the multiple possible perspectives of the same parallel computation. Finally, we consider an instance of VCR for reasoning about Gelernter’s Linda language and tuple space computation, the basis for much of today’s space-based middleware.
Advances in moving horizon estimation for nonlinear systems

In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique for tackling the problem of estimating the state of a dynamic system in the presence of nonlinearities and disturbances. MHE is based on the idea of minimizing an estimation cost function defined on a sliding window composed of a finite number of time stages. The cost function is usually made up of two contributions: a prediction error computed on a recent batch of inputs and outputs; an arrival cost that serves the purpose of summarizing the past data. However, the diffusion of such techniques has been hampered by: i) the difficulty in choosing the arrival cost so as to ensure stability of the overall estimation scheme; ii) the request of an adequate computational effort on line. In this paper, both problems are addressed and possible solutions are proposed. First, by means of a novel stability analysis, it is constructively shown that under very general observability conditions a quadratic arrival cost is sufficient to ensure the stability of the estimation error provided that the weight matrix is adequately chosen. Second, a novel approximate MHE algorithm is proposed that is based on nonlinear programming sensitivity calculations. The approximate MHE algorithm has the same stability properties of the optimal one which make the overall approach suitable to be applied in real settings. Preliminary simulation results confirm the effectiveness of proposed method.
Natural Selection and Developmental Constraints in the Evolution of Allometries

In animals, scaling relationships between appendages and body size exhibit high interspecific variation but low intraspecific variation. This pattern could result from natural selection for specific allometries or from developmental constraints on patterns of differential growth. We performed artificial selection on the allometry between forewing area and body size in a butterfly to test for developmental constraints, and then used the resultant increased range of phenotypic variation to quantify natural selection on the scaling relationship. Our results show that the short-term evolution of allometries is not limited by developmental constraints. Instead, scaling relationships are shaped by strong natural selection.
fMRI of Past Tense Processing: The Effects of Phonological Complexity and Task Difficulty

The generation of regular and irregular past tense verbs has been an important issue in cognitive science and has been used to advance different models of the organization of language in the brain. The dual-system view holds that the regular past tense forms are generated by a rule while irregular forms are retrieved from memory. The single-system view, on the other hand, holds that both forms are generated by a single integrated system and differ only in their reliance on factors such as phonology and semantics. We conducted an event-related fMRI study to examine the activation patterns associated with the generation and reading of regular and irregular past tense forms, in addition to the reading of their stems. Regular and irregular past tense generation activated similar brain regions compared to the reading of their respective stems. The areas activated more for irregular generation compared to regular generation included inferior frontal, precentral, and parietal regions bilaterally. This activation can be interpreted as reflecting the greater attentional and response selection demands of irregular generation. Compared to irregular generation, regular generation activated a small region in the left superior temporal gyrus when the regular and irregular past tense forms were mismatched on phonological complexity. No areas were more activated for regulars than irregulars when the past tense forms were matched on this variable. This suggests that the activation specific to regulars was related to the higher phonological complexity of their past tense forms rather than to their generation. A contrast of the reading of regular and irregular past tense forms was consistent with this hypothesis. These results support a single-system account of past tense generation.
Comparison of LDPC decoding algorithms with and without estimation of noise variance

The original sum product algorithms (SPA) of LDPC decoding in AWGN channel require the knowledge of noise variance. Mini-sum algorithm need not the variance estimation but has performance degradation. If the assumed noise variance of SPA algorithm deviates largely from the true value, the performance also degrade seriously. In this paper, an iterative noise variance estimation algorithm using the decoded data is presented. The true noise variance is then substituted by the estimated one. The computational load is analyzed. Performance difference between SPA, Mini-sum algorithm and our algorithm are compared by simulations.
Multi-agent Intrusion Detection System Using Feature Selection Approach

Due to the increased connectivity to Internet and corporate network, industrial control system (ICS) is no longer immune to network attacks. Most of these ICSs are not designed with security protection nowadays, so there is an increasing demand of designing protection mechanism in infrastructure of industrial plants. In this paper, we propose multi-agent intrusion detection architecture and a feature selection approach to protect ICS. Multi-agent intrusion detection system (MIDS) architecture is designed for decentralized intrusion detection and prevention control in large switched networks, so it can make intrusion detection system (IDS) efficient and scalable, while the feature detection approach is proposed to improve detection reliability. We chose NSL-KDD as experimental data and had a test on four kinds of attacks (Probe, Dos, U2R and R2L) to evaluate the performance of IDS. Compared with four other common feature selection algorithms (IG, GR, Relief and Chi-Square), the experimental results show that our method can effectively improve True Positive Rate and reduce False Positive Rate of IDS.
A systematic mapping study on mining software repositories

Background: Software repositories provide large amount of data encompassing software changes throughout its evolution. Those repositories can be effectively used to extract and analyze pertinent information and derive conclusions related to the software history or its current snapshot. Objective: This work aims to investigate recent studies on Mining Software Repositories (MSR) approaches collecting evidences about software analysis goals (purpose, focus, and object of analysis), data sources, evaluation methods, tools, and how the area is evolving. Method: A systematic mapping study was performed to identify and analyze research on mining software repositories by analyzing five editions of Working Conference on Mining Software Repositories -- the main conference on this area. Results: MSR approaches have been used for many different goals, mainly for comprehension of defects, analysis of the contribution and behavior of developers, and software evolution comprehension. Besides, some gaps were identified with respect to their goals, focus, and data source type (e.g. lack of usage of comments to identify smells, refactoring, and issues of software quality). Regarding the evaluation method, our analysis pointed out to an extensive usage of some types of empirical evaluation. Conclusion: Studies of the MSR have focused on different goals, however there are still many research opportunities to be explored and issues associated with MSR that should be considered.
Second-order non-stationary online learning for regression

The goal of a learner in standard online learning, is to have the cumulative loss not much larger compared with the best-performing function from some fixed class. Numerous algorithms were shown to have this gap arbitrarily close to zero, compared with the best function that is chosen off-line. Nevertheless, many real-world applications, such as adaptive filtering, are non-stationary in nature, and the best prediction function may drift over time. We introduce two novel algorithms for online regression, designed to work well in non-stationary environment. Our first algorithm performs adaptive resets to forget the history, while the second is last-step min-max optimal in context of a drift. We analyze both algorithms in the worst-case regret framework and show that they maintain an average loss close to that of the best slowly changing sequence of linear functions, as long as the cumulative drift is sublinear. In addition, in the stationary case, when no drift occurs, our algorithms suffer logarithmic regret, as for previous algorithms. Our bounds improve over existing ones, and simulations demonstrate the usefulness of these algorithms compared with other state-of-the-art approaches.
Effect of a Chitosan-Based Biodegradable Middle Meatal Dressing after Endoscopic Sinus Surgery: A Prospective Randomized Comparative Study

Introduction: The use of biomaterials to improve wound healing after endoscopic sinus surgery (ESS) is not new. Many types of resorbable and non-resorbable materials have been tried as a middle meatal (MM) dressing, spacer, or stent to prevent lateralization of the middle turbinate, formation of synechia, granulation tissue, adhesions and scarring. The FDA has recently approved Chitosan-based nasal dressing/spacers which have optimal wound healing characteristics, including hemostatic and bacteriostatic properties. Herein, we compare a new chitosan-based biomaterial to a popular fully synthetic resorbable dressing in patients undergoing ESS. Materials and Methods: A prospective randomized controlled study was performed comparing a new Chitosan-based bioresorbable nasal dressing (Posi-Sep X) against a previously studied and well known fully synthetic polyurethane-based control (Nasopore). Post-operative outcome metrics included the degree of crusting, amount of retained implant, patient comfort, wound healing, epistaxis, and post-operative infection at two weeks. Results: Thirty-five patients were enrolled and a total seventy implants were placed (n = 70) at the completion of ESS. The results show a statistically significant difference between the Chitosan-based product and the control with respect to wound healing, degree of crusting, and resorption profile. In addition, the Chitosan-based dressing had a markedly lower requirement for post-operative debridement, and a lower incidence of epistaxis and infection, which corresponds to superior patient comfort. Conclusion: Our study is consistent with the biomaterials literature regarding the potential advantages of Chitosan-based MM dressings after ESS regarding improved wound healing, biocompatibility, and patient comfort.
Monocular vision simultaneous localization and mapping using SURF

In visual SLAM features are extracted from images as landmarks. Features should be easily and fast extracted and should be reliably matched in different situations. However, most point features extraction methods used in visual SLAM cannot trade off the reliability of matching and the speed of extraction. In our monocular vision SLAM research, a new feature extractor SURF, which provides both robust matching and high speed extraction, is applied to detect point landmarks from image of indoor environment. We use EKF method to estimate the states of camera and landmarks. In addition, both a new feature detecting strategy which considers landmark distribution in the environment, and an improved landmark management mechanism which allows some landmarks existing permanently to deal with unobservable situation are proposed. The experiments demonstrate that our SLAM approach is effective and has real-time performance.
Exploring expressive speech space in an audio-book

In this paper, an audio-book, in which a professional voice talent performs multiple characters, is exploited to investigate the expressiveness of speech. The expressive speech space of the sole speaker is explored by finding the distances between acoustic models of multiple characters and the perceived proximity between their speech utterances. Using the speech of ten characters as test data, the character confusion is evaluated in both acoustic space and perceptual space. We find that the average precision to differentiate one character from the others is 81.7% in the acoustic space and 72.6% in the perceptual space. It is interesting that the objective measure outperforms the subjective measure. Furthermore, the acoustic distance measured by normalized Kullback-Leibler divergence (NKLD) between two characters is highly correlated with the perceptual distance. The correlation coefficient is 0.814. Therefore, NKLD can measure the perceptual similarity between groups of utterances objectively.
An effective error concealment method used in multi-view video coding

Multi-view video coding (MVC) is one of the newest video compression standards, which has better compression efficiency than single view video coding. As the coding scheme exploits spatial, temporal and inter-view dependability for this scope, it leads the reconstructed multi-view video (MVV) become worse when transmitted in error-prone networks. To solve this problem, an effective error concealment (EC) method for MVC is proposed in this paper. The proposed method conceals a corrupted block by combining a few candidate blocks in intra-view reference frames or inter-view reference frames. The experimental results show that the proposed method has better concealment effect if using the inter-view reference frames effectively in B-view.
Model-driven software development approaches in robotics research

Recently, there is an encouraging trend in adopting model-driven engineering approaches for software development in robotics research. In this paper, currently available model-driven techniques in robotics are analyzed with respect to the domain-specific requirements. A conceptual overview of our software development approach called 'Self Adaptive Framework for Robotic Systems (SafeRobots)' is explained and we also try to position our approach within this model ecosystem.
Stanford's Distantly Supervised Slot Filling Systems for KBP 2014

We describe Stanford’s entry in the TACKBP 2014 Slot Filling challenge. We submitted two broad approaches to Slot Filling, both strongly based on the ideas of distant supervision: one built on the DeepDive framework (Niu et al., 2012), and another based on the multi-instance multilabel relation extractor of Surdeanu et al. (2012). In addition, we evaluate the impact of learned and hard-coded patterns on performance for slot filling, and the impact of the partial annotations described in Angeli et al. (2014).