snu-aidas/HVMap-dataset huggingface dataset:
Probabilistic graph and hypergraph matching

We consider the problem of finding a matching between two sets of features, given complex relations among them, going beyond pairwise. Each feature set is modeled by a hypergraph where the complex relations are represented by hyper-edges. A match between the feature sets is then modeled as a hypergraph matching problem. We derive the hyper-graph matching problem in a probabilistic setting represented by a convex optimization. First, we formalize a soft matching criterion that emerges from a probabilistic interpretation of the problem input and output, as opposed to previous methods that treat soft matching as a mere relaxation of the hard matching problem. Second, the model induces an algebraic relation between the hyper-edge weight matrix and the desired vertex-to-vertex probabilistic matching. Third, the model explains some of the graph matching normalization proposed in the past on a heuristic basis such as doubly stochastic normalizations of the edge weights. A key benefit of the model is that the global optimum of the matching criteria can be found via an iterative successive projection algorithm. The algorithm reduces to the well known Sinkhorn [15] row/column matrix normalization procedure in the special case when the two graphs have the same number of vertices and a complete matching is desired. Another benefit of our model is the straight-forward scalability from graphs to hyper-graphs.
Semantic audio content-based music recommendation and visualization based on user preference examples

Preference elicitation is a challenging fundamental problem when designing recommender systems. In the present work we propose a content-based technique to automatically generate a semantic representation of the user’s musical preferences directly from audio. Starting from an explicit set of music tracks provided by the user as evidence of his/her preferences, we infer high-level semantic descriptors for each track obtaining a user model. To prove the benefits of our proposal, we present two applications of our technique. In the first one, we consider three approaches to music recommendation, two of them based on a semantic music similarity measure, and one based on a semantic probabilistic model. In the second application, we address the visualization of the user’s musical preferences by creating a humanoid cartoon-like character – the Musical Avatar – automatically inferred from the semantic representation. We conducted a preliminary evaluation of the proposed technique in the context of these applications with 12 subjects. The results are promising: the recommendations were positively evaluated and close to those coming from state-ofthe-art metadata-based systems, and the subjects judged the generated visualizations to capture their core preferences. Finally, we highlight the advantages of the proposed semantic user model for enhancing the user interfaces of information filtering systems. 2012 Elsevier Ltd. All rights reserved.
An estimation of the number of cells in the human body.

BACKGROUND
All living organisms are made of individual and identifiable cells, whose number, together with their size and type, ultimately defines the structure and functions of an organism. While the total cell number of lower organisms is often known, it has not yet been defined in higher organisms. In particular, the reported total cell number of a human being ranges between 10(12) and 10(16) and it is widely mentioned without a proper reference.


AIM
To study and discuss the theoretical issue of the total number of cells that compose the standard human adult organism.


SUBJECTS AND METHODS
A systematic calculation of the total cell number of the whole human body and of the single organs was carried out using bibliographical and/or mathematical approaches.


RESULTS
A current estimation of human total cell number calculated for a variety of organs and cell types is presented. These partial data correspond to a total number of 3.72 × 10(13).


CONCLUSIONS
Knowing the total cell number of the human body as well as of individual organs is important from a cultural, biological, medical and comparative modelling point of view. The presented cell count could be a starting point for a common effort to complete the total calculation.
Technologies for Augmented Reality Systems: Realizing Ultrasound-Guided Needle Biopsies

We present a real-time stereoscopic video-see-through augmented reality (AR) system applied to the medical procedure known as ultrasound-guided needle biopsy of the breast. The AR system was used by a physician during procedures on breast models and during non-invasive examinations of human subjects. The system merges rendered live ultrasound data and geometric elements with stereo images of the patient acquired through head-mounted video cameras and presents these merged images to the physician in a head-mounted display. The physician sees a volume visualization of the ultrasound data directly under the ultrasound probe, properly registered within the patient and with the biopsy needle. Using this system, a physician successfully guided a needle into an artificial tumor within a training phantom of a human breast. We discuss the construction of the AR system and the issues and decisions which led to the system architecture and the design of the video see-through head-mounted display. We designed methods to properly resolve occlusion of the real and synthetic image elements. We developed techniques for realtime volume visualization of timeand position-varying ultrasound data. We devised a hybrid tracking system which achieves improved registration of synthetic and real imagery and we improved on previous techniques for calibration of a magnetic tracker. CR
Reliability of lower limb motor evoked potentials in stroke and healthy populations: How many responses are needed?

OBJECTIVE
To determine the intra- and inter-session reliability of motor evoked potential (MEP) size parameters in the lower limb of patients with stroke, focussing on the number of MEPs collected and the method of measuring MEP size.


METHODS
Transcranial magnetic stimulation was used to elicit MEPs in the soleus muscle of patients with stroke (n=13) and age-matched healthy participants (n=13) during low level muscle activation. Two sets of 10 responses were collected in the first session and a further 10 responses collected in a second session held 7 days later. Four MEP size measurements were made using 4, 6, 8, or all 10 of the MEPs collected. Intra- and inter-session reliability was examined using intraclass correlation coefficients (ICC) and typical percentage error.


RESULTS
Intrasession ICC statistics using 6 or more MEPs were >0.85 in the stroke group but intersession values were all <0.5. Reliability was best when measuring parameters from individual MEPs rather than averaged responses.


CONCLUSIONS
Reliability of intrasession MEP size is excellent in the lower limb of patients with stroke using as few as 6 MEPs but intersession reliability is poor.


SIGNIFICANCE
Comparing MEP size measures across two or more sessions is questionable in the lower limb of patients with stroke.
Bringing PageRank to the citation analysis

The paper attempts to provide an alternative method for measuring the importance of scientific papers based on the Google’s PageRank. The method is a meaningful extension of the common integer counting of citations and is then experimented for bringing PageRank to the citation analysis in a large citation network. It offers a more integrated picture of the publications’ influence in a specific field. We firstly calculate the PageRanks of scientific papers. The distributional characteristics and comparison with the traditionally used number of citations are then analyzed in detail. Furthermore, the PageRank is implemented in the evaluation of research influence for several countries in the field of Biochemistry and Molecular Biology during the time period of 2000–2005. Finally, some advantages of bringing PageRank to the citation analysis are concluded. 2007 Elsevier Ltd. All rights reserved.
Scaling HDFS to More Than 1 Million Operations Per Second with HopsFS

HopsFS is an open-source, next generation distribution of the Apache Hadoop Distributed File System(HDFS) that replaces the main scalability bottleneck in HDFS, single node in-memory metadata service, with a no-sharedstate distributed system built on a NewSQL database. By removing the metadata bottleneck in Apache HDFS, HopsFS enables significantly larger cluster sizes, more than an order of magnitude higher throughput, and significantly lower clientlatencies for large clusters. In this paper, we detail the techniques and optimizations that enable HopsFS to surpass 1 million file system operations per second - at least 16 times higher throughput than HDFS. In particular, we discuss how we exploit recent high performance features from NewSQL databases, such as application defined partitioning, partition-pruned index scans, and distribution aware transactions. Together with more traditional techniques, such as batching and write-ahead caches, we show how many incremental optimizations have enabled a revolution in distributed hierarchical file system performance.
Interventions in Small Food Stores to Change the Food Environment, Improve Diet, and Reduce Risk of Chronic Disease

INTRODUCTION
Many small-store intervention trials have been conducted in the United States and other countries to improve the food environment and dietary behaviors associated with chronic disease risk. However, no systematic reviews of the methods and outcomes of these trials have been published. The objective of this study was to identify small-store interventions and to determine their impact on food availability, dietary behaviors, and psychosocial factors that influence chronic disease risk.


METHODS
From May 2009 through September 2010, we used PubMed, web-based searches, and listservs to identify small-store interventions that met the following criteria: 1) a focus on small food stores, 2) a completed impact evaluation, and 3) English-written documentation (peer-reviewed articles or other trial documents). We initially identified 28 trials; 16 met inclusion criteria and were used for analysis. We conducted interviews with project staff to obtain additional information. Reviewers extracted and reported data in a table format to ensure comparability between data.


RESULTS
Reviewed trials were implemented in rural and urban settings in 6 countries and primarily targeted low-income racial/ethnic minority populations. Common intervention strategies included increasing the availability of healthier foods (particularly produce), point-of-purchase promotions (shelf labels, posters), and community engagement. Less common strategies included business training and nutrition education. We found significant effects for increased availability of healthy foods, improved sales of healthy foods, and improved consumer knowledge and dietary behaviors.


CONCLUSION
Trial impact appeared to be linked to the increased provision of both healthy foods (supply) and health communications designed to increase consumption (demand).
The CL-SciSumm Shared Task 2018: Results and Key Insights

This overview describes the official results of the CL-SciSumm Shared Task 2018 – the first medium-scale shared task on scientific document summarization in the computational linguistics (CL) domain. This year, the dataset comprised 60 annotated sets of citing and reference papers from the open access research papers in the CL domain. The Shared Task was organized as a part of the 41 Annual Conference of the Special Interest Group in Information Retrieval (SIGIR), held in Ann Arbor, USA in July 2018. We compare the participating systems in terms of two evaluation metrics. The annotated dataset and evaluation scripts can be accessed and used by the community from: https://github.com/WING-NUS/scisumm-corpus.
Advanced Engineering Electromagnetics (Balanis, C.A.; 2012) [Book Review]

Since 2012 the second edition of this book is available. This new edition has all the attractive features of the first one and in my opinion it contains some new features and additions that are very useful in the EMC playground. In particular: A section on metamaterials (Section 5.7) is helpful for electromagnetic shielding oriented studies; A section on artificial impedance surfaces (AIS, EBG, PBG, HIS, AMC, PMC) (Section 8.8), is a solid base for any issue related to EBGs; and, in general, Additional smaller inserts throughout the book make it easier and enjoyable to understand; and new figures, photos, and tables have been added. As in the first edition, this second edition is a thorough and detailed engineer-oriented book. The analytical detail, rigor, and thoroughness allow many of the topics to be traced to their origin, and they are presented in sufficient detail so that the reader will follow the analytical developments. The material is presented in a methodical, sequential, and unified manner, and each chapter is subdivided into sections or subsections whose individual headings clearly identify the topics discussed, examined, or illustrated. An exhaustive list of references is included at the end of each chapter to allow the interested reader to trace each topic. A number of appendixes of mathematical identities and special functions, some represented also in tabular and graphical forms, are included. A very useful feature is a set of fortyeight basic MATLAB® computer programs developed and included in the website that is part of the book. They are an aid, also for the skilled reader, for a conceptual fruition of the results based upon the analytical formulations included throughout the book.
Painting Outside the Box: Image Outpainting with GANs

The challenging task of image outpainting (extrapolation) has received comparatively little attention in relation to its cousin, image inpainting (completion). Accordingly, we present a deep learning approach based on [4] for adversarially training a network to hallucinate past image boundaries. We use a three-phase training schedule to stably train a DCGAN architecture on a subset of the Places365 dataset. In line with [4], we also use local discriminators to enhance the quality of our output. Once trained, our model is able to outpaint 128 × 128 color images relatively realistically, thus allowing for recursive outpainting. Our results show that deep learning approaches to image outpainting are both feasible and promising.
Paralinguistics in speech and language - State-of-the-art and the challenge

Paralinguistic analysis is increasingly turning into a mainstream topic in speech and language processing. This article aims to provide a broad overview of the constantly growing field by defining the field, introducing typical applications, presenting exemplary resources, and sharing a unified view of the chain of processing. It then presents the first broader Paralinguistic Challenge organised at INTERSPEECH 2010 by the authors including a historical overview of the Challenge tasks of recognising age, gender, and affect, a summary of methods used by the participants, and their results. In addition, we present the new benchmark obtained by fusion of participants’ predictions and conclude by discussing ten recent and emerging trends in the analysis of paralinguistics in speech and language. © 2012 Elsevier Ltd. All rights reserved.
The Romance of Learning from Disagreement. The Effect of Cohesiveness and Disagreement on Knowledge Sharing Behavior and Individual Performance Within Teams

PURPOSE: The purpose of this study was to explore the effects of disagreement and cohesiveness on knowledge sharing in teams, and on the performance of individual team members. DESIGN/METHODOLOGY/APPROACH: Data were obtained from a survey among 1,354 employees working in 126 teams in 17 organizations. FINDINGS: The results show that cohesiveness has a positive effect on the exchange of advice between team members and on openness for sharing opinions, whereas disagreement has a negative effect on openness for sharing opinions. Furthermore, the exchange of advice in a team has a positive effect on the performance of individual team members and acts as a mediator between cohesiveness and individual performance. IMPLICATIONS: Managers who want to stimulate knowledge sharing processes and performance within work teams may be advised to take measures to prevent disagreement between team members and to enhance team cohesiveness. ORIGINALITY/VALUE: Although some gurus in organizational learning claim that disagreement has a positive effect on group processes such as knowledge sharing and team learning, this study does not support this claim.
A survey of code-based change impact analysis techniques

Software change impact analysis (CIA) is a technique for identifying the effects of a change, or estimating what needs to be modified to accomplish a change. Since the 1980s, there have been many investigations on CIA, especially for code-based CIA techniques. However, there have been very few surveys on this topic. This article tries to fill this gap. And 30 papers that provide empirical evaluation on 23 code-based CIA techniques are identified. Then, data was synthesized against four research questions. The study presents a comparative framework including seven properties, which characterize the CIA techniques, and identifies key applications of CIA techniques in software maintenance. In addition, the need for further research is also presented in the following areas: evaluating existing CIA techniques and proposing new CIA techniques under the proposed framework, developing more mature tools to support CIA, comparing current CIA techniques empirically with unified metrics and common benchmarks, and applying the CIA more extensively and effectively in the software maintenance phase. Copyright © 2012 John Wiley & Sons, Ltd.
Efficient Edge Detection on Low-Cost FPGAs

Improving the efficiency of edge detection in embedded applications, such as UAV control, is critical for reducing system cost and power dissipation. Field programmable gate arrays (FPGA) are a good platform for making improvements because of their specialised internal structure. However, current FPGA edge detectors do not exploit this structure well. A new edge detection architecture is proposed that is better optimised for FPGAs. The basis of the architecture is the Sobel edge kernels that are shown to be the most suitable because of their separability and absence of multiplications. Edge intensities are calculated with a new 4:2 compressor that consists of two custom-designed 3:2 compressors. Addition speed is increased by breaking carry propagation chains with look-ahead logic. Testing of the design showed it gives a 28% increase in speed and 4.4% reduction in area over previous equivalent designs, which demonstrated that it will lower the cost of edge detection systems, dissipate less power and still maintain highspeed control. Keywords—edge detection; FPGA; compressor; low-cost; UAV
The effects of social media on emotions , brand relationship quality , and word of mouth : An empirical study of music festival attendees

This article focuses on two under-researched areas of tourism management e the management of music festivals, and the influence of social media on customer relationships. In the new digital era of marketing communications little is known about how social media interactions with tourism brands affect how consumers think and feel about those brands, and consequently how those interactions affect desired marketing outcomes such as word mouth. Based on the literature, a conceptual model was developed and was tested using structural equation modeling. The results show that social media does indeed have a significant influence on emotions and attachments to festival brands, and that social media-based relationships lead to desired outcomes such as positive word of mouth. © 2014 Elsevier Ltd. All rights reserved.
Habanero-Java library: a Java 8 framework for multicore programming

With the advent of the multicore era, it is clear that future growth in application performance will primarily come from increased parallelism. We believe parallelism should be introduced early into the Computer Science curriculum to educate students on the fundamentals of parallel computation. In this paper, we introduce the newly-created Habanero-Java library (HJlib), a pure Java 8 library implementation of the pedagogic parallel programming model [12]. HJlib has been used in teaching a sophomore-level course titled "Fundamentals of Parallel Programming" at Rice University.
 HJlib adds to the Java ecosystem a powerful and portable task parallel programming model that can be used to parallelize both regular and irregular applications. By relying on simple orthogonal parallel constructs with important safety properties, HJlib allows programmers with a basic knowledge of Java to get started with parallel programming concepts by writing or refactoring applications to harness the power of multicore architecture. The HJlib APIs make extensive use of lambda expressions and can run on any Java 8 JVM. HJlib runtime feedback capabilities, such as the abstract execution metrics and the deadlock detector, help the programmer to obtain feedback on theoretical performance as well as the presence of potential bugs in their program.
 Being an implementation of a pedagogic programming model, HJlib is also an attractive tool for both educators and researchers. HJlib is actively being used in multiple research projects at Rice and also by external independent collaborators. These projects include exploitation of homogeneous and heterogeneous multicore parallelism in big data applications written for the Hadoop platform [20, 43].
Comparison of Two β-Alanine Dosing Protocols on Muscle Carnosine Elevations.

OBJECTIVE
β-alanine (BA) is a nonproteogenic amino acid that combines with histidine to form carnosine. The amount taken orally in individual doses, however, is limited due to symptoms of paresthesia that are associated with higher doses. The use of a sustained-release formulation has been reported to reduce the symptoms of paresthesia, suggesting that a greater daily dose may be possible. The purpose of the present study was to determine whether increasing the daily dose of BA can result in a similar increase in muscle carnosine in a reduced time.


METHODS
Eighteen men and twelve women were randomized into either a placebo (PLC), 6-g BA (6G), or 12-g BA (12G) groups. PLC and 6G were supplemented for 4 weeks, while 12G was supplemented for 2 weeks. A resting blood draw and muscle biopsy were obtained prior to (PRE) and following (POST) supplementation. Plasma and muscle metabolites were measured by high-performance liquid chromatography. The loss in peak torque (ΔPT) was calculated from maximal isometric contractions before and after 250 isokinetic kicks at 180°·sec-1 PRE and POST.


RESULTS
Both 12G (p = 0.026) and 6G (p = 0.004) increased muscle carnosine compared to PLC. Plasma histidine was decreased from PRE to POST in 12G compared to PLC (p = 0.002) and 6G (p = 0.001), but no group x time interaction (p = 0.662) was observed for muscle histidine. No differences were observed for any hematological measure (e.g., complete blood counts) or in symptoms of paresthesia among the groups. Although no interaction was noted in ΔPT, a trend (p = 0.073) was observed.


CONCLUSION
Results of this investigation indicate that a BA supplementation protocol of 12 g/d-1, using a sustained-release formulation, can accelerate the increase in carnosine content in skeletal muscle while attenuating paresthesia.