snu-aidas/HVMap-dataset huggingface dataset:
Document concept lattice for text understanding and summarization

We argue that the quality of a summary can be evaluated based on how many concepts in the original document(s) that can be preserved after summarization. Here, a concept refers to an abstract or concrete entity or its action often expressed by diverse terms in text. Summary generation can thus be considered as an optimization problem of selecting a set of sentences with minimal answer loss. In this paper, we propose a document concept lattice that indexes the hierarchy of local topics tied to a set of frequent concepts and the corresponding sentences containing these topics. The local topics will specify the promising sub-spaces related to the selected concepts and sentences. Based on this lattice, the summary is an optimized selection of a set of distinct and salient local topics that lead to maximal coverage of concepts with the given number of sentences. Our summarizer based on the concept lattice has demonstrated competitive performance in Document Understanding Conference 2005 and 2006 evaluations as well as follow-on tests. 2007 Elsevier Ltd. All rights reserved.
Fast and Accurate Closest Point Search on Triangulated Surfaces and its Application to Head Motion Estimation

The Iterative Closest Point (ICP) algorithm is widely used to register two roughly aligned surfaces. Its most expensive step is the search for the closest point. Many efficient variants have been proposed to speed up this step, however they do not guarantee that the closest point on a triangulated surface is found. Instead they might result in an approximation of the closest point. In this paper we present a method for the closest point search that is fast and exact. The method was implemented and used to evaluate the accuracy of head motion estimation using dense 3D data obtained from a stereo camera system. The results show that the accuracy of the estimated head motion is better than 1 mm for translational movements and better than 1 degree for rotations. Key-Words: Iterative Closest Point, 3D Registration, Stereo, Head Motion Estimation
Increasing fruit and vegetable intake by changing environments, policy and pricing: restaurant-based research, strategies, and recommendations.

BACKGROUND
Restaurants are among the most important and promising venues for environmental, policy, and pricing initiatives to increase fruit and vegetable (F&V) intake. This article reviews restaurant-based environmental, policy and pricing strategies for increasing intake of fruits and vegetables and identifies promising strategies, research needs, and innovative opportunities for the future.


METHODS
The strategies, examples, and research reported here were identified through an extensive search of published journal articles, government documents, the internet, and inquiries to leaders in the field. Recommendations were expanded based on discussion by participants in the CDC/ACS-sponsored Fruit and Vegetable, Environment Policy and Pricing Workshop held in September of 2002.


RESULTS
Six separate types of restaurant-based interventions were identified: increased availability, increased access, reduced prices and coupons, catering policies, point-of-purchase (POP) information, and promotion and communication. Combination approaches have also been implemented. Evaluation data on these interventions show some significant impact on healthful diets, particularly with point-of-purchase information. However, most published reports emphasize low-fat eating, and there is a need to translate and evaluate interventions focused on increasing fruit and vegetable intake.


CONCLUSIONS
Several models for changing environments, policy and pricing to increase fruit and vegetable availability, access, attractiveness and consumption in restaurants have been tested and found to have some promise. There is a need to evaluate fruit and vegetable-specific strategies; to obtain data from industry; to disseminate promising programs; and to enhance public-private partnerships and collaboration to expand on current knowledge.
A mixture model for preferences data analysis

A mixture model for preferences data, which adequately represents the composite nature of the elicitation mechanism in ranking processes, is proposed. Both probabilistic features of the mixture distribution and inferential and computational issues arising from the maximum likelihood parameters estimation are addressed. Moreover, empirical evidence from different data sets confirming the goodness of fit of the proposed model to many real preferences data is shown. © 2004 Elsevier B.V. All rights reserved.
Deep Neural Networks for Object Detection

Deep Neural Networks (DNNs) have recently shown outstanding performance on image classification tasks [14]. In this paper we go one step further and address the problem of object detection using DNNs, that is not only classifying but also precisely localizing objects of various classes. We present a simple and yet powerful formulation of object detection as a regression problem to object bounding box masks. We define a multi-scale inference procedure which is able to produce high-resolution object detections at a low cost by a few network applications. State-of-the-art performance of the approach is shown on Pascal VOC.
Photoshopping the selfie: Self photo editing and photo investment are associated with body dissatisfaction in adolescent girls.

OBJECTIVE
Social media engagement by adolescent girls is high. Despite its appeal, there are potential negative consequences for body dissatisfaction and disordered eating from social media use. This study aimed to examine, in a cross-sectional design, the relationship between social media use in general, and social media activities related to taking "selfies" and sharing specifically, with overvaluation of shape and weight, body dissatisfaction, and dietary restraint.


METHOD
Participants were 101 grade seven girls (M(age)  = 13.1, SD = 0.3), who completed self-report questionnaires of social media use and body-related and eating concerns measures.


RESULTS
Results showed that girls who regularly shared self-images on social media, relative to those who did not, reported significantly higher overvaluation of shape and weight, body dissatisfaction, dietary restraint, and internalization of the thin ideal. In addition, among girls who shared photos of themselves on social media, higher engagement in manipulation of and investment in these photos, but not higher media exposure, were associated with greater body-related and eating concerns, including after accounting for media use and internalization of the thin ideal.


DISCUSSION
Although cross-sectional, these findings suggest the importance of social media activities for body-related and eating concerns as well as potential avenues for targeted social-media-based intervention.
Artificial Bee Colony algorithm for optimization of truss structures

The main goal of the structural optimization is to minimize the weight of structures while satisfying all design requirements imposed by design codes. In this paper, the Artificial Bee Colony algorithm with an adaptive penalty function approach (ABC-AP) is proposed to minimize the weight of truss structures. The ABC algorithm is swarm intelligence based optimization technique inspired by the intelligent foraging behavior of honeybees. Five truss examples with fixed-geometry and up to 200 elements were studied to verify that the ABC algorithm is an effective optimization algorithm in the creation of an optimal design for truss structures. The results of the ABC-AP compared with results of other optimization algorithms from the literature show that this algorithm is a powerful search and optimization technique for structural design. © 2010 Elsevier B.V. All rights reserved.
Swarm intelligence and robotics

Purpose – The aim of this paper is to provide a review of recent developments in the application of swarm intelligence to robotics. Design/methodology/approach – This paper initially considers swarm intelligence and then discusses its application to robotics through reference to a number of recent research programmes. Findings – Based on the principles of swarm intelligence, which is derived from the swarming behaviour of biological entities, swarm robotics research is widespread but still at an early stage. Much aims to gain an understanding of biological swarming and apply it to autonomous, mobile multi-robot systems. European activities are particularly strong and several large, collaborative projects are underway. Research in the USA has a military bias and much is funded by defence agencies. Originality/value – The paper provides an up-to-date insight into swarm robot research and development.
A Span-Extraction Dataset for Chinese Machine Reading Comprehension

Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, the existing reading comprehension datasets are mostly in English. In this paper, we introduce a SpanExtraction dataset for Chinese Machine Reading Comprehension to add language diversities in this area. The dataset is composed by near 20,000 real questions annotated by human on Wikipedia paragraphs. We also annotated a challenge set which contains the questions that need comprehensive understanding and multi-sentence inference throughout the context. With the release of the dataset, we hosted the Second Evaluation Workshop on Chinese Machine Reading Comprehension (CMRC 2018). We hope the release of the dataset could further accelerate the machine reading comprehension research in Chinese language.1
Explicit reference modeling methodology in parametric CAD system

Today parametric associative CAD systems must help companies to create more efficient virtual development processes. While dealing with complex parts (e.g. the number of surfaces of the solid) no CAD modeling methodology is existing. Based on the analysis of industrial designers’ practices as well as student practices on CAD, we identified key factors that lead to better performance. Our objective in this article is to propose a practical method for complex parts modeling in parametric CAD system. An illustration of the performances and the results obtained by this method are presented comparing the traditional method with the proposed one while using an academic case and then an industrial case. 2013 Elsevier B.V. All rights reserved.
SELF-SERV: A Platform for Rapid Composition of Web Services in a Peer-to-Peer Environment

The automation of Web services interoperation is gaining a considerable momentum as a paradigm for effective Business-to-Business collaboration [2]. Established enterprises are continuously discovering new opportunities to form alliances with other enterprises, by offering value-added integrated services. However, the technology to compose Web services in appropriate time-frames has not kept pace with the rapid growth and volatility of available opportunities. Indeed, the development of integrated Web services is often ad-hoc and requires a considerable effort of lowlevel programming. This approach is inadequate given the size and the volatility of the Web. Furthermore, the number of services to be integrated may be large, so that approaches where the development of an integrated service requires the understanding of each of the underlying services are inappropriate. In addition, Web services may need to be composed as part of a short term partnership, and disbanded when the partnership is no longer profitable. Hence, the integration of a large number of Web services requires scalable and flexible techniques, such as those based on declarative languages. Also, the execution of an integrated service in existing approaches is usually centralised, whereas the underlying services are distributed and autonomous. This calls for the investigation of distributed execution paradigms (e.g., peer-to-peer models), that do not suffer of the scalability and availability problems of centralised coordination [3]. Motivated by these concerns, we have developed the SELF-SERV platform for rapid composition of Web
Metal nanogrids , nanowires , and nanofi bers for transparent electrodes

VOLUME 36 • OCTOBER 2011 • www.mrs.org/bulletin © 2011 Materials Research Society Introduction Transparent electrodes are ubiquitously used in optoelectronic devices where light must pass through a section, and current or voltage needs to be applied. These devices include thin-fi lm solar cells (organic, inorganic, hybrid), displays (liquid-crystal display, plasma display, organic light-emitting diode [OLED]), touch screens (resistive, capacitive), electronic books, smart windows, fl exible lighting, and passive devices (such as transparent heating, transparent speakers). 1 The properties of transparent electrodes are extremely important for device performance, and the specifi cations vary based on types of devices. For example, while source roughness and work function are insignifi cant for resistive touch screens, they are crucial for OLEDs and organic solar cells. 1 Moreover, the optical haze of particular transparent electrodes is benefi cial for high-effi ciency solar cells but problematic for certain types of displays. The mechanical properties of the electrode are crucial for fl exible devices but not important for devices on rigid substrates. Across all devices, however, the optical transparency ( T ) and electrical sheet resistance ( Rs ) are the two most important parameters. Unfortunately, these two parameters are in constant competition with one another. Since Rs values are often reported at different transparencies, it is hard to compare two transparent electrodes directly, and hence a fi gure of merit ( σ dc / σ op , where σ dc is the dc conductivity, and σ op is the optical conductivity) Metal nanogrids, nanowires, and nanofi bers for transparent electrodes
Patient and nurse preferences for nurse handover-using preferences to inform policy: a discrete choice experiment protocol.

INTRODUCTION
Nursing bedside handover in hospital has been identified as an opportunity to involve patients and promote patient-centred care. It is important to consider the preferences of both patients and nurses when implementing bedside handover to maximise the successful uptake of this policy. We outline a study which aims to (1) identify, compare and contrast the preferences for various aspects of handover common to nurses and patients while accounting for other factors, such as the time constraints of nurses that may influence these preferences.; (2) identify opportunities for nurses to better involve patients in bedside handover and (3) identify patient and nurse preferences that may challenge the full implementation of bedside handover in the acute medical setting.


METHODS AND ANALYSIS
We outline the protocol for a discrete choice experiment (DCE) which uses a survey design common to both patients and nurses. We describe the qualitative and pilot work undertaken to design the DCE. We use a D-efficient design which is informed by prior coefficients collected during the pilot phase. We also discuss the face-to-face administration of this survey in a population of acutely unwell, hospitalised patients and describe how data collection challenges have been informed by our pilot phase. Mixed multinomial logit regression analysis will be used to estimate the final results.


ETHICS AND DISSEMINATION
This study has been approved by a university ethics committee as well as two participating hospital ethics committees. Results will be used within a knowledge translation framework to inform any strategies that can be used by nursing staff to improve the uptake of bedside handover. Results will also be disseminated via peer-reviewed journal articles and will be presented at national and international conferences.
Features for Measuring Credibility on Facebook Information

Abstract—Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.
Neck lift my way: an update.

BACKGROUND
The author updates prior descriptions of an approach to the surgical neck lift that aims for a maximum degree of control over the size, shape, and position of every anatomical feature of the neck that is negatively affecting its appearance.


METHODS
A 38-year clinical experience guided the development of the operative tactics that define the strategy. Data collected from a records review of 522 consecutive neck lifts performed during the 10-year period 2004 through 2013 further inform the report. The approach has eight features: (1) nearly routine use of open submental access to all tissue layers of the central neck, including a regimen that curbed the problems that may attend an extensive tissue dissection; (2) management of lax neck skin by lateral excision using a specific postauricular incision, or by using the nonexcisional method of redistribution; (3) open lipectomy for precise removal of excess subcutaneous neck and jawline fat; (4) individualized modifications to subplatysmal fat, perihyoid fascia, and anterior digastric muscles; (5) treatment of large, ptotic, or malpositioned submandibular salivary glands by partial excision using a transcutaneous traction suture; (6) the current version of the corset platysmaplasty, which is used to treat static paramedian platysma muscle bands, and to avoid contour imperfections following subplatysmal maneuvers; (7) an approach that facilitates an isolated neck lift; and (8) durable results.


RESULTS
Case examples demonstrate outcomes.


CONCLUSION
Although the updated approach remains relatively complex and invasive, the author believes that the ends justify the means.
Synthetic Biology for Space Exploration : Promises and Societal Implications
MAPGEN: Mixed-Initiative Planning and Scheduling for the Mars Exploration Rover Mission

8 1094-7167/04/$20.00 © 2004 IEEE IEEE INTELLIGENT SYSTEMS to elucidate the planet’s past climate, water activity, and habitability. Science is MER’s primary driver, so making best use of the scientific instruments, within the available resources, is a crucial aspect of the mission. To address this criticality, the MER project team selected MAPGEN (Mixed Initiative Activity Plan Generator) as an activity-planning tool. MAPGEN combines two existing systems, each with a strong heritage: the APGEN activity-planning tool1 from the Jet Propulsion Laboratory and the Europa planning and scheduling system2 from NASA Ames Research Center. This article discusses the issues arising from combining these tools in this mission’s context.
The Case Research Strategy in Studies of Information Systems

This article defines and discusses one of these qualitative methods--the case research strategy. Suggestions are provided for researchers who wish to undertake research employing this approach. Criteria for the evaluation of case research are established and several characteristics useful for categorizing the studies are identified. A sample of papers drawn from information systems journals is reviewed. The paper concludes with examples of research areas that are particularly wellsuited to investigation using the case research approach. ACM categories: H.O., J.O.
Adversarial Deep Structural Networks for Mammographic Mass Segmentation

Mass segmentation is an important task in mammogram analysis, providing effective morphological features and regions of interest (ROI) for mass detection and classification. Inspired by the success of using deep convolutional features for natural image analysis and conditional random fields (CRF) for structural learning, we propose an end-to-end network for mammographic mass segmentation. The network employs a fully convolutional network (FCN) to model a potential function, followed by a CRF to perform structured learning. Because the mass distribution varies greatly with pixel position, the FCN is combined with a position priori. Due to the small size of mammogram datasets, we use adversarial training to control over-fitting. Four models with different convolutional kernels are further fused to improve the segmentation results. Experimental results on two public datasets, INBreast and DDSM-BCRP, demonstrate that our end-to-end network achieves the state-of-the-art results. 1
Learning How to Combine Internal and External Denoising Methods

Different methods for image denoising have complementary strengths and can be combined to improve image denoising performance, as has been noted by several authors [11, 7]. Mosseri et al. [11] distinguish between internal and external methods depending whether they exploit internal or external statistics [13]. They also propose a rule-based scheme (PatchSNR) to combine these two classes of algorithms. In this paper, we test the underlying assumptions and show that many images might not be easily split into regions where internal methods or external methods are preferable. Instead we propose a learning based approach using a neural network, that automatically combines denoising results from an internal and from an external method. This approach outperforms both other combination methods and state-of-the-art stand-alone image denoising methods, hereby further closing the gap to the theoretically achievable performance limits of denoising [9]. Our denoising results can be replicated with a publicly available toolbox.
A new classification of lip zones to customize injectable lip augmentation.

OBJECTIVES
To present a new classification of 15 anatomical lip zones used to direct placement of injectable fillers during lip augmentation and to evaluate the new classification's ability to customize lip contour and size.


METHODS
Study participants were consecutive patients presenting to a facial plastic and reconstructive surgery practice for injectable lip augmentation with a nonanimal-sourced stabilized hyaluronic acid (Restylane; Medicis Aesthetic Inc, Scottsdale, Arizona). A nonrandomized, prospective case series.


RESULTS
A total of 137 treatments were performed on lips of 66 patients. The mean (SD) satisfaction score was 4.5 (0.6) on an integral scale of 1 (dissatisfied) to 5 (most satisfied). The mean (SD) persistence until lips returned to preoperative appearance based on patient subjective evaluation was 4.9 (1.5) months. Patients were free of adverse effects.


CONCLUSIONS
Using a new classification of lip anatomical zones to direct the injection of a nonanimal-sourced stabilized hyaluronic acid has increased my ability to better control lip shape and size in lip augmentation. This technique was met with high patient satisfaction and no adverse effects. Persistence of injected nonanimal-sourced stabilized hyaluronic acid was similar to that seen in other studies.