Miracle-dz/UniFAR-FTUs huggingface dataset:
Self bounding learning algorithms

Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform convergence. These bounds are a-priori bounds that hold for any distribution of examples and are calculated before any data is observed. In this paper we propose a different approach for bounding the generalization error after the data has been observed. A self-bounding learning algorithm is an algorithm which, in addition to the hypothesis that it outputs, outputs a reliable upper bound on the generalization error of this hypothesis. We first explore the idea in the statistical query learning framework of Keams [lo]. After that we give an explicit self bounding algorithm for learning algorithms that are based on local search. Permission to make digital or h,ard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for prolit or commercial advantage and that copies bear this notice and the full citation on the first page. To COPY otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific pemlission . and/or a fee. COLT 98 Madison WI USA Copyright ACM 1998 l-581 13-057--0/9X/ 7. $5.00
Task-Based Grasp Adaptation on a Humanoid Robot

In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa.
Q Methodology and its Applications: Reflections on Theory

The 2011 Annual Meeting of the International Society for the Scientific Study of Subjectivity in Birmingham offered numerous opportunities for reflecting on the role of theory in Q methodology and on further theoretical implications in applied Q studies. A summary is provided of the opening addresses from Eefje Cuppen and David Ockwell and of a ‘roundtable’ discussion organised by James Good, with comments from Steven Brown, Simon Watts and Amanda Wolf. Reflections on theoretical matters, both those indicated explicitly by presenters or otherwise suggested by matters discussed, concern theory in Q methodology as methodology, the role of substantive theory in applications of Q methodology and the continuum of theory from the concrete to the general.
Multiple ecological pathways to extinction in mammals

As human population and resource demands continue to grow, biodiversity conservation has never been more critical. About one-quarter of all mammals are in danger of extinction, and more than half of all mammal populations are in decline. A major priority for conservation science is to understand the ecological traits that predict extinction risk and the interactions among those predictors that make certain species more vulnerable than others. Here, using a new database of nearly 4,500 mammal species, we use decision-tree models to quantify the multiple interacting factors associated with extinction risk. We show that the correlates of extinction risk vary widely across mammals and that there are unique pathways to extinction for species with different lifestyles and combinations of traits. We find that risk is relative and that all kinds of mammals, across all body sizes, can be at risk depending on their specific ecologies. Our results increase the understanding of extinction processes, generate simple rules of thumb that identify species at greatest risk, and highlight the potential of decision-tree analyses to inform conservation efforts.
Ultrasonography Fusion Imaging System Increases the Chance of Radiofrequency Ablation for Hepatocellular Carcinoma with Poor Conspicuity on Conventional Ultrasonography

Objectives: To investigate the usefulness of the ultrasonography (US) fusion imaging system for radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC). Methods: Since the US fusion imaging system became available in 2010, we have conducted RFA with this system in all cases. The characteristics of 75 patients with 120 HCCs and 89 patients with 123 HCCs who underwent RFA before the introduction of this system (period A) and after it (period B), respectively, were retrospectively compared. Results: Significant difference in the characteristics of the patients and HCCs between the two periods was found only in the proportion of HCCs with poor conspicuity on grayscale US treated with RFA (1.7%, 2/120 for period A vs. 15.4%, 19/123 for period B, p < 0.01). Among the 19 HCCs with poor conspicuity on grayscale US for period B, 5 and 9 HCCs were identified on grayscale US and contrast-enhanced US, respectively, by the use of the US fusion imaging system, whereas the 5 remaining undetectable HCCs were treated by using the system in conjunction with reference images displayed side-by-side with grayscale US. Conclusion: Since the introduction of the US fusion imaging system, it has become possible to perform RFA for HCCs with poor conspicuity on grayscale US.
The nitrate inducible NAC transcription factor TaNAC2-5A controls nitrate response and increases wheat yield

T meet the food security demands of growing human population, yield of majority of the crop plants needs to be doubled by 2050 while dealing with the climate change. With the increasing temperature trends and unusual climatic changes, crops in future climates will experience frequent temperature extremes causing significant yield losses. Heat stress is a serious challenge to wheat production as every 1 °C increase above the optimal temperature results in 4-5% yield loss. Rainfed areas of the US are projected to decrease wheat production by 20-40% due to climate change. Thus, developing climate resilient wheat is crucial in today’s context. As a public-private partnership, Feed the Future Innovation lab-Climate Resilient Wheat is developing heat tolerant varieties by exploiting natural variation. A short period of heat stress during germination had serious and long-term effect on plant development and yield. A ten-day heat stress at germination reduced germination percentage, coleoptile length and yield. Sugars availability maybe a reason for the effect on germination as external application of sucrose showed significant recovery in germination percentage and coleoptile length. Heat stress during vegetative phase significantly affected tiller number, flowering time, pollen fertility, plant height and yield. During the reproductive stage, heat stress adversely affected photosynthesis and increased membrane disintegration due to decreased chlorophyll index and increased ROS and lipid peroxidase activity. The identified heat tolerant lines will be used to transfer the trait into wheat cultivars by simultaneous detection and utilization of QTLs. Various molecular and physiological studies for the trait are underway and update will be presented.
A bi-directional visual stereo interface for accessing stereo matching results from a human brain

An interface, called BVSI, allowing people to input stereo correspondences more efficiently is proposed. The BVSI consists of a stereo display for providing a stereo view of a 3-D scene and a binocular gaze tracker for recording the binocular fixation points of an operator. A calibration method of the BVSI is presented. The horizontal gaze tracking error of the calibrated BVSI is about /spl plusmn/10 pixels. Real experiments have been conducted and the results showed that the proposed system is very promising.
A Splitting-based Iterative Method for Sparse Reconstruction

In this paper, we study a l 1 -norm regularized minimization method for sparse solution recovery in compressed sensing and X-ray CT image reconstruction. In the proposed method, an alternating minimization algorithm is employed to solve the involved l 1 -norm regularized minimization problem. Under some suitable conditions, the proposed algorithm is shown to be globally convergent. Numerical results indicate that the presented method is effective and promising.
Frequency of congenital craniofacial malformations in a Brazilian Reference Center

OBJECTIVE: To evaluate the frequency of craniofacial anomalies in patients treated at a Brazilian Reference Center for craniofacial deformities. METHOD: Retrospective epidemiological study evaluating the clinical records of 1,142 patients: 656 (57.4%) male and 486 (42.6%) female, between 1992 and 2008. RESULTS: Among birth defects, non-syndromic cleft lip and/or palate were the most frequent ones (778 cases; 68.1%), followed by single or multiple congenital anomalies without cleft lip and/or palate (240 cases; 21%), recognized syndromes or sequences (56 cases; 5%), syndromes with orofacial cleft as a component (41 cases; 3.5%), and orofacial clefts in association with systemic malformations (27 cases; 2.4%). CONCLUSIONS: Non-syndromic cleft lip and/or palate was the congenital defect most frequently identified, although, isolated anomalies and syndromes involving craniofacial structures were quite frequent. Furthermore, the need for studies to identify the frequency and risk factors associated with craniofacial anomalies in the Brazilian population is emphasized in order to plan comprehensive strategies and integrated actions for the development of preventive programs and treatment.
Failure mechanism based failure rate model

For electronic products, the typical failure rate curve takes on three-stage bathtub shape, while few failure rate equations can describe the bathtub shaped curve. Based on environment load impact failure mechanism, the present paper develops load-property interference failure rate model for electronic products. The operation load, i.e. the impact is taken as a random process, and product property suffers degradation over service time. The ever changing load-property relationship yields the variation in failure rate curve. During service life, the product is continuously subjected to stochastic load impact, and product property degrades continuously. Since failure occurs when a load higher than the relevant property appears, failure rate model can be developed based on load statistical characteristic and product property. From such a principle, the variation in failure rate is interpreted in both the load uncertainty and product property uncertainty. Moreover, the effects of product property degradation, as well as load dispersion and product property dispersion on failure rate are highlighted.
Power saving model for mobile device and virtual base station in the 5G era

It is a critical requirement of the future 5G communication networks to provide high speed and significantly reduce the network energy consumption. Energy efficient networks along with an energy saving strategy in mobile devices play a vital role in the mobile revolution. The new strategies should not only focus on wireless base stations, which consumes most of the power, but also considers the other power consumption elements for future mobile communication networks, including User Equipment (UE). In this paper, we have proposed a method that calculates the power consumption of a 5G network by considering its main elements based on current vision of 5G network infrastructure. Our proposed model uses the component based methodology that simplifies the process by taking into account the different high power consuming elements. The proposed method is evaluated by considering the three UE's DRX models and Virtual Base Station (VBS) with respect to different DRX timer in terms of Power Saving (PS) and delay as performance parameters.
Predicting unroll factors using supervised classification

Compilers base many critical decisions on abstracted architectural models. While recent research has shown that modeling is effective for some compiler problems, building accurate models requires a great deal of human time and effort. This paper describes how machine learning techniques can be leveraged to help compiler writers model complex systems. Because learning techniques can effectively make sense of high dimensional spaces, they can be a valuable tool for clarifying and discerning complex decision boundaries. In this work we focus on loop unrolling, a well-known optimization for exposing instruction level parallelism. Using the Open Research Compiler as a testbed, we demonstrate how one can use supervised learning techniques to determine the appropriateness of loop unrolling. We use more than 2,500 loops - drawn from 72 benchmarks - to train two different learning algorithms to predict unroll factors (i.e., the amount by which to unroll a loop) for any novel loop. The technique correctly predicts the unroll factor for 65% of the loops in our dataset, which leads to a 5% overall improvement for the SPEC 2000 benchmark suite (9% for the SPEC 2000 floating point benchmarks).
ON THE FORGETTING OF COLLEGE ACADEMICS: AT “EBBINGHAUS SPEED”?

How important are Undergraduate College Academics after graduation? How much do we actually remember after we leave the college classroom, and for how long? Taking a look at major University ranking methodologies one can easily observe they consistently lack any objective measure of what content knowledge and skills students retain from college education in the long term. Is there any rigorous scholarly published evidence on retention of long-term unused academic content knowledge? We have found no such evidence based on a preliminary literature review. Furthermore, findings in all research papers reviewed in this study were consistent with the following assertion: the Ebbinghaus forgetting curve [Ebbinghaus 1880-1885] is a fundamental law of human nature – in fact, of the whole animal kingdom and applies to memory of all types: verbal, visual, abstract, social and autobiographical. This fundamental law of nature, when examined within the context of academic learning retention, manifests itself as an exponential curve halving memory saliency about every two years (what we call "Ebbinghaus Speed"). This paper presents the research group’s initial hypothesis and conjectures for college level education programming and curriculum development, suggestions for instructional design enhancing learning durability, as well as future research directions. “Six verses of a poem require for learning not only three times as much as two but considerably more than that. ” Ebbinghaus (1885) “We find that our working stock of ideas is narrowly limited, but that the mind continually recurs to them in conducting its operations, therefore its tracks necessarily become more defined and its flexibility diminished as age advances. ” Francis Galton, F.R. S. (1879)
Personalized QoS Prediction for Web Services Using Latent Factor Models

Recommending the suitable Web service is an important topic in today's society. The critical step is to accurately predict QoS of Web services. However, the highly sparse QoS data complicate the challenges. In the real world, since QoS delivery can be significantly affected by some dominant factors in the service environment (e.g., network delay and the location of user or service), Web services which are published by the same provider usually have the similar fundamental network environment. These factors can be leveraged for accurate QoS predictions, leading to high-quality service recommendations. In this paper, we expound how Latent Factor Models (LFM) can be utilized to predict the unknown QoS values. Meanwhile, we take the factors of provider and its country into consideration, which imply the latent physical location and network status information, as the latent neighbor for the set of Web services. Hence, the novel neighbor factor model is built to evaluate the personalized connection quality of latent neighbors for each service user. Then, we propose an integrated model based on LFM. Finally, we conduct a group of experiments on a large-scale real-world QoS dataset and the results demonstrate that our approach is effective, especially in the situation of data sparsity.
Morphologic analysis of fetal stress organsin different causes of perinatal death

Complications act as stress-inducers during pregnancy so the fetus can develop functional compensatory mechanisms or morphologic changes. The cases analyzed are with congenital malformations or acute stress; chronic included cases with ascending infection (AI) and perinatal hypoxia/anoxia (PHA). The hematoxylin-eosin (H&E) was done to analyze the vacuolization, and the immunohistochemistry to the phagocytosis. The discreet standard of vacuolization was observed in 52.6% of the cases, 22.1% moderate, and 25.3% severe. The number of macrophages was higher in PHA. Changes in these organs are closely related to the cause of death and to the period during which the harmful agent.
The cultural diversity phenomenon in organisations and different approaches for effective cultural diversity management: a literary review

Purpose – To make a literary review related to effective management of cultural diversity in organisations and to systematically bring up different views put forward regarding this issue.Design/methodology/approach – First, the literature which covers the “diversity management” and “cultural diversity management” is reviewed in detail and then tried to explore the contributors’ different views about the effective cultural diversity management approach. In the paper these different perspectives about this matter are classified.Findings – The answer to the question of how cultural diversity should be managed effectively cannot be given easily. There are various typologies about the organisational and managerial literature. In order to be able to effectively manage cultural diversity in organisations, it is beneficial to develop a “cultural diversity management model” peculiar to the organisation by considering the positive and negative sides of different perspectives located in this study.Research limitatio.
Adaptive multitemporal filtering of polarimetric SAR images

This paper proposes an approach for temporal adaptive filtering of Polarimetric Synthetic Aperture Radar (PolSAR) image time series by integrating a change detection technique. The filtering strategy is based on the detection of changed and unchanged areas derived by applying an appropriate similarity test. A time series including 7 descending fine-quad polarization RADARSAT2 images acquired from January 29, 2009 to Jun 22, 2009 over Chamonix-MontBlanc test-site which includes different kinds of change is used to validate the proposed method.
Enhanced antitumor activity of low-dose continuous administration schedules of topotecan in prostate cancer

Purpose: The objective of this study was to determine the antitumor effects of alternate dosing schedules of topotecan in prostate cancer. Results: A concentration-dependent increase in cytotoxicity was observed in PC-3 and LNCaP cells after topotecan treatment using conventional and metronomic protocols. A significant increase in potency (2.4-18 fold, after 72 hr) was observed following metronomic dosing compared to conventional dosing administration in both cell lines. Metronomic dosing also increased the percentage of PC-3 cells in the G2/M, compared to control, but did not alter LNCaP cell cycle distribution. Metronomic dosing increased p21 protein expression in LNCaP and PC-3 cells compared to conventional dosing. The observed in vitro activity was confirmed using an in vivo model of human prostate cancer. Metronomic dosing and continuous infusion decreased tumor volume significantly (p < 0.05) compared to control and conventional topotecan treatment, but had no effect on tumor vascular staining. Methods: The cytotoxicity of topotecan after conventional or metronomic dosing was determined by examining cellular morphology, mitochondrial enzymatic activity (MTT), total cellular protein (SRB), annexin V and propidium iodine (PI) staining, cell cycle and western blot analysis in human prostate cancer cell lines (PC-3 and LNCaP) and the effects metronomic or continuous infusion on tumor growth in an in vivo tumor xenograft model. Conclusions: These data support the hypothesis that low-dose continuous administration of topotecan increases potency compared to conventional dosing in prostate cancer. These data also suggest the novel finding that the enhanced antitumor activity of topotecan following low-dose exposure correlates to alterations in cell cycle and increased p21 expression.
Cognitive bridge between haptic impressions and texture images for subjective image retrieval

As a step towards subjective image retrieval, This work reports an on-going collaboration project between Waseda University and SUNY, Binghamton, on relating texture images to haptic impressions. To capture the surface height variations, texture images are taken under different illuminations and viewing conditions. Our method applies a new frequency analysis method to the texture images. We evaluate the performances of our feature and other typical conventional features by checking whether texture images are correctly classified into "soft" or "hard" by the SVM (support vector machine) method, where the training data for the SVM are collected by subjective tests. Experimental results show that our texture feature can classify "soft" or "hard" better than the other features.
Asymptotically tight performance bounds for equal-gain combining over a new correlated fading channel

A recently proposed fading model which can be used to describe both line-of-sight and non-line-of-sight components of a fading channel is analyzed. The outage probability and error rate performance of equal-gain combining over arbitrary correlated Beaulieu-Xie fading channels is considered. Asymptoticallytight closed-form lower and upper bounds are derived and these analytical results are verified via Monte Carlo simulations.
SNUMedinfo at CLEF BioASQ 2015

This paper describes our participation at the BioASQ Task 3b of CLEF 2015 Question Answering track. We participated at the document retrieval subtask in Phase A and the ideal answer generation subtask in Phase B. As of previous year, in the document retrieval task, we mostly experimented with semantic concept-enriched dependence model and sequential dependence model. In the ideal answer generation task, relevant passages are selected and combined to automatically produce answer text.