nils-herrmann/clean_scirepeval huggingface dataset:
Semi-automatic rule-based domain terminology and software feature-relevant information extraction from natural language user manuals

Mature software systems comprise a vast number of heterogeneous system capabilities which are usually requested by different groups of stakeholders and which evolve over time. Software features describe and bundle low level capabilities logically on an abstract level and thus provide a structured and comprehensive overview of the entire capabilities of a software system. Software features are often not explicitly managed. Quite the contrary, feature-relevant information is often spread across several software engineering artifacts (e.g., user manual, issue tracking systems). It requires huge manual effort to identify and extract feature-relevant information from these artifacts in order to make feature knowledge explicit. In this paper we present a two-step-approach to extract feature-relevant information from a user manual: First we semi-automatically extract a domain terminology from a natural language user manual based on linguistic patterns. Then, we apply natural language processing techniques based on the extracted domain terminology and structural sentence information. Our approach is able to extract atomic feature-relevant information with an F1-score of at least 92.00%. We describe the implementation of the approach as well as evaluations based on example sections of a user manual taken from industry.
Image Autoregressive Interpolation Model Using GPU-Parallel Optimization

With the growth in the consumer electronics industry, it is vital to develop an algorithm for ultrahigh definition products that is more effective and has lower time complexity. Image interpolation, which is based on an autoregressive model, has achieved significant improvements compared with the traditional algorithm with respect to image reconstruction, including a better peak signal-to-noise ratio (PSNR) and improved subjective visual quality of the reconstructed image. However, the time-consuming computation involved has become a bottleneck in those autoregressive algorithms. Because of the high time cost, image autoregressive-based interpolation algorithms are rarely used in industry for actual production. In this study, in order to meet the requirements of real-time reconstruction, we use diverse compute unified device architecture (CUDA) optimization strategies to make full use of the graphics processing unit (GPU) (NVIDIA Tesla K80), including a shared memory and register and multi-GPU optimization. To be more suitable for the GPU-parallel optimization, we modify the training window to obtain a more concise matrix operation. Experimental results show that, while maintaining a high PSNR and subjective visual quality and taking into account the I/O transfer time, our algorithm achieves a high speedup of 147.3 times for a Lena image and 174.8 times for a 720p video, compared to the original single-threaded C CPU code with -O2 compiling optimization.
On Dual Co-Polarized SAR Measurements of the Ocean Surface

An effective methodology using satellite high-resolution polarized information to interpret and quantitatively assess various surface ocean phenomena is suggested. Using a sample RADARSAT-2 quad-polarization ocean synthetic aperture radar (SAR) scene, the dual co-polarization (VV and HH) radar data are combined into polarization difference, polarization ratio, and nonpolarized components. As demonstrated, these field quantities provide means to distinguish Bragg scattering mechanism and radar returns from breaking waves. As shown, quantitative characteristics of the surface manifestation of ocean currents, slicks, and wind field features in these dual co-polarization properties are very different and may be effectively used in the development of new SAR detection and discrimination algorithms.
More than just fun and games: assessing the value of educational video games in the classroom

The objective of this preliminary study is to investigate whether educational video games can be integrated into a classroom with positive effects for the teacher and students. The challenges faced when introducing a video game into a classroom are twofold: overcoming the notion that a "toy" does not belong in the school and developing software that has real educational value while stimulating the learner. We conducted an initial pilot study with 39 second grade students using our mathematic drill software Skills Arena. Early data from the pilot suggests that not only do teachers and students enjoy using Skills Arena, students have exceeded our expectations by doing three times more math problems in 19 days than they would have using traditional worksheets. Based on this encouraging qualitative study, future work that focuses on quantitative benefits should likely uncover additional positive results.
A Review on Document Clustering

Text mining has becoming an emerging research area in now-a-days that helps to extract useful information from large amount of natural language text documents. The need of grouping similar documents together for different applications has gaining the attention of researchers in this area. Document clustering organizes the documents into different groups called as clusters. The documents in one cluster have higher degree of similarity than the documents in other cluster. The paper provides an overview of the document clustering reviewed from different papers and the challenges in document clustering. KeywordsText Mining, Document Clustering, Similarity Measures, Challenges in Document Clustering
Gradient Vector Flow: A New External Force for Snakes

Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to concave boundaries, however, have limited their utility. This paper develops a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The resultant field has a large capture range and forces active contours into concave regions. Examples on simulated images and one real image are presented.
Public-private partnerships and contract negotiations : an empirical study

The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.
An updated meta-analysis of the ego depletion effect

The ego depletion effect is one of the most famous phenomena in social psychology. A recent meta-analysis showed that after accounting for small-studies effects by using a newly developed method called PET-PEESE, the ego depletion effect was indistinguishable from zero. However, it is too early to draw such rushing conclusion because of the inappropriate usage of PET-PEESE. The current paper reported a stricter and updated meta-analysis of ego depletion by carefully inspecting problems in the previous meta-analysis, including new studies not covered by it, and testing the effectiveness of each depleting task. The results suggest that attention video should be an ineffective depleting task, whereas emotion video should be the most effective one. Future studies are needed to confirm the effectiveness of each depletion task revealed by the current meta-analysis.
High Power Density Capacitor Charging Power Supply Development for Repetitive Pulsed Power

Power modulators for compact, repetitive systems are continually faced with new requirements as the corresponding system objectives increase. Changes in pulse rate frequency or number of pulses significantly impact the design of the power conditioning system. In order to meet future power supply requirements, we have developed several high voltage (HV) capacitor charging power supplies (CCPS). This effort focuses on a volume of 6" x 6" x 14" and a weight of 25 lbs. The primary focus was to increase the effective capacitor charge rate, or power output, for the given size and weight. Although increased power output was the principal objective, efficiency and repeatability were also considered. A number of DC-DC converter topologies were compared to determine the optimal design. In order to push the limits of output power, numerous resonant converter parameters were examined. Comparisons of numerous topologies, HV transformers and rectifiers, and switching frequency ranges are presented. The impacts of the control system and integration requirements are also considered.
QFN challenges: Second bond improvement to eliminate the weak stitch (fish tail) failure mechanism on pre plated lead frame

Most of the device's technology has been moving towards the complex and produce of Nano-IC with demands for cheaper cost, smaller size and better thermal and electrical performance. One of the marketable packages is Quad Flat No-Lead (QFN) package. Due to the high demand of miniaturization of electronic products, QFN development becomes more promising, such as the lead frame design with half edge, cheaper tape, shrinkage of package size as to achieve more units per lead frame (cost saving) and etc . The improvement methods in the lead frame design, such as lead frame metal tie bar and half edge features are always the main challenges for QFN package. With reduced the size of metal tie bar, it will fasten the package singulation process, whereas the half edge is designed for the mold compound locking for delamination reduction purpose. This paper specifically will discuss how the critical wire bonding parameters, capillary design and environmental conditions interact each other result to the unstable leads (second bond failures). During the initial evaluation of new package SOT1261 with rough PPF lead frame, several short tails and fish tails observed on wedge bond when applied with the current parameter setting which have been qualified in other packages with same wire size (18um Au wire). These problems did not surface out in earlier qualified devices mainly due to the second bond parameter robustness, capillary designs, lead frame design changes, different die packages, lead frame batches and contamination levels. One of the main root cause been studied is the second bond parameter setting which is not robust enough for the flimsy lead frame. The new bonding methodology, with the concept of low base ultrasonic and high force setting applied together with scrubbing mechanism to eliminate the fish tail bond and also reduce short tail occurrence on wedge. Wire bond parameters optimized to achieve zero fish tail, and wedge pull reading with >4.0gf. Destructive test such as wedge pull test used to test the bonding quality. Failure modes are analyzed using high power optical scope microscope and Scanning Electronic Microscope (SEM). By looking through into all possible root causes, and identifying how the factors are interacting, some efforts on the Design of Experiments (DOE) are carried out and good solutions were implemented.
Effects of weight gain and weight loss on regional fat distribution.

Normal-weight adults gain lower-body fat via adipocyte hyperplasia and upper-body subcutaneous (UBSQ) fat via adipocyte hypertrophy.



We investigated whether regional fat loss mirrors fat gain and whether the loss of lower-body fat is attributed to decreased adipocyte number or size.



We assessed UBSQ, lower-body, and visceral fat gains and losses in response to overfeeding and underfeeding in 23 normal-weight adults (15 men) by using dual-energy X-ray absorptiometry and abdominal computed tomography scans. Participants gained ∼5% of weight in 8 wk and lost ∼80% of gained fat in 8 wk. We measured abdominal subcutaneous and femoral adipocyte sizes and numbers after weight gain and loss.



Volunteers gained 3.1 ± 2.1 (mean ± SD) kg body fat with overfeeding and lost 2.4 ± 1.7 kg body fat with underfeeding. Although UBSQ and visceral fat gains were completely reversed after 8 wk of underfeeding, lower-body fat had not yet returned to baseline values. Abdominal and femoral adipocyte sizes, but not numbers, decreased with weight loss. Decreases in abdominal adipocyte size and UBSQ fat mass were correlated (ρ = 0.76, P = 0.001), as were decreases in femoral adipocyte size and lower-body fat (ρ = 0.49, P = 0.05).



UBSQ and visceral fat increase and decrease proportionately with a short-term weight gain and loss, whereas a gain of lower-body fat does not relate to the loss of lower-body fat. The loss of lower-body fat is attributed to a reduced fat cell size, but not number, which may result in long-term increases in fat cell numbers.
Darpa Urban Challenge Technical Report Executive Summary

with input from many other team members 6/1/2007 "DISCLAIMER: The information contained in this paper does not represent the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency (DARPA) or the Department of Defense. DARPA does not guarantee the accuracy or reliability of the information in this paper." Austin Robot Technology's (ART's) entry in the DARPA Urban Challenge has two main goals. First and foremost, the team aims to create a fully autonomous vehicle that is capable of safely and robustly meeting all of the criteria laid out in the Technical Evaluation Criteria document . Second, and almost as important, the team aims to produce, educate, and train members of the next generation of computer science and robotics researchers. This technical report documents our significant progress towards both of these goals as of May 2007 and presents a concrete plan to achieve them both fully by the time of the National Qualifying Event (NQE) in October. Specifically, it presents details of both our complete hardware system and our in-progress software, including design rationale, preliminary results, and future plans towards meeting the challenge. In addition, it provides details of the significant undergraduate research component of our efforts and emphasizes the educational value of the project.
ADDING TIME-OFFSETS TO SCHEDULABILITY ANALYSIS

This paper discusses the addition of so-called time offsets to task sets dispatched according to fixed priorities. The motivation for this work is two-fold: firstly, direct expression of time offsets is a useful structuring approach for designing complex hard real-time systems. Secondly, analysis directly addressing time offsets can be very much less pessimistic than extant analysis. In this report we extend our current fixed priority schedulability analysis, and then present two major worked examples, illustrating the approach.
Performance Error Detection and Post-Processing for Fast and Accurate Symbolic Music Alignment

This paper presents a fast and accurate alignment method for polyphonic symbolic music signals. It is known that to accurately align piano performances, methods using the voice structure are needed. However, such methods typically have high computational cost and they are applicable only when prior voice information is given. It is pointed out that alignment errors are typically accompanied by performance errors in the aligned signal. This suggests the possibility of correcting (or realigning) preliminary results by a fast (but not-so-accurate) alignment method with a refined method applied to limited segments of aligned signals, to save the computational cost. To realise this, we develop a method for detecting performance errors and a realignment method that works fast and accurately in local regions around performance errors. To remove the dependence on prior voice information, voice separation is performed to the reference signal in the local regions. By applying our method to results obtained by previously proposed hidden Markov models, the highest accuracies are achieved with short computation time. Our source code is published in the accompanying web page, together with a user interface to examine and correct alignment results.
Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners

This paper summarizes some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques. We discuss their achievements in terms of accuracy and sound quality, and the current challenges, such as availability of data and computing resources. We also discuss the impact that these advances do and will have on listeners and singers when they are integrated in commercial applications.
DPPred: An Effective Prediction Framework with Concise Discriminative Patterns

In the literature, two series of models have been proposed to address prediction problems including classification and regression. Simple models, such as generalized linear models, have ordinary performance but strong interpretability on a set of simple features. The other series, including tree-based models, organize numerical, categorical, and high dimensional features into a comprehensive structure with rich interpretable information in the data. In this paper, we propose a novel Discriminative Pattern-based Prediction framework (<inline-formula> <tex-math notation="LaTeX">$\sf {DPPred}$</tex-math><alternatives><inline-graphic xlink:href="shang-ieq1-2757476.gif"/> </alternatives></inline-formula>) to accomplish the prediction tasks by taking their advantages of both effectiveness and interpretability. Specifically, <inline-formula><tex-math notation="LaTeX">$\sf {DPPred}$</tex-math><alternatives> <inline-graphic xlink:href="shang-ieq2-2757476.gif"/></alternatives></inline-formula> adopts the concise discriminative patterns that are on the prefix paths from the root to leaf nodes in the tree-based models. <inline-formula> <tex-math notation="LaTeX">$\sf {DPPred}$</tex-math><alternatives><inline-graphic xlink:href="shang-ieq3-2757476.gif"/> </alternatives></inline-formula> selects a limited number of the useful discriminative patterns by searching for the most effective pattern combination to fit generalized linear models. Extensive experiments show that in many scenarios, <inline-formula><tex-math notation="LaTeX">$\sf {DPPred}$</tex-math><alternatives> <inline-graphic xlink:href="shang-ieq4-2757476.gif"/></alternatives></inline-formula> provides competitive accuracy with the state-of-the-art as well as the valuable interpretability for developers and experts. In particular, taking a clinical application dataset as a case study, our <inline-formula><tex-math notation="LaTeX">$\sf {DPPred}$</tex-math> <alternatives><inline-graphic xlink:href="shang-ieq5-2757476.gif"/></alternatives></inline-formula> outperforms the baselines by using only 40 concise discriminative patterns out of a potentially exponentially large set of patterns.
Does overgrowth of costal cartilage cause pectus carinatum? A three-dimensional computed tomography evaluation of rib length and costal cartilage length in patients with asymmetric pectus carinatum.

To evaluate whether the overgrowth of costal cartilage may cause pectus carinatum using three-dimensional (3D) computed tomography (CT).



Twenty-two patients with asymmetric pectus carinatum were included. The fourth, fifth and sixth ribs and costal cartilages were semi-automatically traced, and their full lengths were measured on three-dimensional CT images using curved multi-planar reformatted (MPR) techniques. The rib length and costal cartilage length, the total combined length of the rib and costal cartilage and the ratio of the cartilage and rib lengths (C/R ratio) in each patient were compared between the protruding side and the opposite side at the levels of the fourth, fifth and sixth ribs.



The length of the costal cartilage was not different between the more protruded side and the contralateral side (55.8 ± 9.8 mm vs 55.9 ± 9.3 mm at the fourth, 70 ± 10.8 mm vs 71.6 ± 10.8 mm at the fifth and 97.8 ± 13.2 mm vs 99.8 ± 15.5 mm at the sixth; P > 0.05). There were also no significant differences between the lengths of ribs. (265.8 ± 34.9 mm vs 266.3 ± 32.9 mm at the fourth, 279.7 ± 32.7 mm vs 280.6 ± 32.4 mm at the fifth and 283.8 ± 33.9 mm vs 283.9 ± 32.3 mm at the sixth; P > 0.05). There was no statistically significant difference in either the total length of rib and costal cartilage or the C/R ratio according to side of the chest (P > 0.05).



In patients with asymmetric pectus carinatum, the lengths of the fourth, fifth and sixth costal cartilage on the more protruded side were not different from those on the contralateral side. These findings suggest that overgrowth of costal cartilage cannot explain the asymmetric protrusion of anterior chest wall and may not be the main cause of pectus carinatum.
[Acute gastric dilatation in a bulimic patient; systemic efects].

To demonstrate through a clinical case the systemic effetcss and complications that can arise after an acute gastric dilatation caused by an eating binge.



A young woman diagnosed of bulimia nervosa presents to the emergency room after a massive food intake. She shows important abdominal distention and refers inability to self-induce vomit. A few hours later she commences to show signs of hemodynamic instability and oliguria. A CT scan is performed; it shows bilateral renal infarctions due to compression of the abdominal aorta and some of its visceral branches.



The evaluation procedures included quantification of the gastric volume by CT. A decompression gastrostomy was performed; it allowed the evacuation of a large amount of gastric content and restored blood supply to the abdomen, which improved renal perfusion.



CT is a basic diagnostic tool that not only allows us to quantify the degree of acute gastric dilatation but can also evaluate the integrity of the adjacent organs which may be suffering compression hypoperfusion.
Preface-Emerging Technologies and Landmark Systems for Learning Mathematics and Science: Dedicated to the Memory of Erica Melis-Part 2

It is our distinct pleasure, as co-editors, to introduce this special edition of the International Journal of Artificial Intelligence in Education. Not only dowe have four very interesting and high quality papers about emerging educational technologies in mathematics and science to present, but we also have the opportunity to dedicate this volume to our colleague and friend, EricaMelis, who passed away in February 2011 at the age of 61.We all knewErica well and two of us (McLaren, Sosnovsky) worked closely with her for several years and personally witnessed the bravery with which she fought her illness and faced her mortality. Erica was an important figure in AI in Education (AIED) research, tirelessly working on both new ideas and more established, landmark research in the area of education and technology. This volume focuses on one aspect of Erica’s research life – new ideas. A soon-to-be released companion issue of the International Journal of Artificial Intelligence in Education will focus on the second passion of Erica’s research life – landmark instructional systems for supporting learners and learning. Erica was a dedicated and rigorous researcher, and led a full life. She was born in Cuba in 1949 to a German Jewish family in exile, eventually returning to Germany to live and lead her academic life. In East Germany, where she first lived upon returning to Germany, she studied Kripke Logic. When she moved to the west, her academic interests shifted to a study of analogy and case-based reasoning, subfields of artificial intelligence. She also did seminal proof planning work with Joerg Siekmann, who eventually became her husband. She was always keenly interested in international collaborations, spending time