nils-herrmann/clean_scirepeval huggingface dataset:
An open source research platform for embedded visible light networking

Despite the growing interest in visible light communication, a reference networking platform based on commercial off-the-shelf components is not available yet. An open source platform would lower the barriers to entry of VLC network research and help the VLC community gain momentum. We introduce OpenVLC, an open source VLC research platform based on software-defined implementation. Built around a creditcard- sized embedded Linux platform with a simple opto-electronic transceiver front-end, OpenVLC offers a basic physical layer, a set of essential medium access primitives, as well as interoperability with Internet protocols. We investigate the performance of OpenVLC and show examples of how it can be used along with standard network diagnostics tools. Our software-defined implementation can currently reach throughput on the order of the basic rate of the IEEE 802.15.7 standard. We discuss several techniques that researchers and engineers could introduce to improve the performance of OpenVLC and envision several directions that can benefit from OpenVLC by adopting it as a reference platform.
Smart wheelchairs: A literature review.

Several studies have shown that both children and adults benefit substantially from access to a means of independent mobility. While the needs of many individuals with disabilities can be satisfied with traditional manual or powered wheelchairs, a segment of the disabled community finds it difficult or impossible to use wheelchairs independently. To accommodate this population, researchers have used technologies originally developed for mobile robots to create "smart wheelchairs." Smart wheelchairs have been the subject of research since the early 1980s and have been developed on four continents. This article presents a summary of the current state of the art and directions for future research.
Some future trends and implications for systems and software engineering processes

In response to the increasing criticality of software within systems and the increasing demands being put onto 21st century systems, systems and software engineering processes will evolve significantly over the next two decades. This paper identifies eight relatively surprise-free trends—the increasing interaction of software engineering and systems engineering; increased emphasis on users and end value; increased emphasis on systems and software dependability; increasingly rapid change; increasing global connectivity and need for systems to interoperate; increasingly complex systems of systems; increasing needs for COTS, reuse, and legacy systems and software integration; and computational plenty. It also identifies two “wild card” trends: increasing software autonomy and combinations of biology and computing. It then discusses the likely influences of these trends on systems and software engineering processes between now and 2025, and presents an emerging scalable spiral process model for coping with the resulting challenges and opportunities of developing 21st century software-intensive systems and systems of systems.
DualIso : Scalable Subgraph Pattern Matching On Large Labeled Graphs SUPPLEMENT

This supplement to the paper provides all figures and substantial code listings which would not fit into the paper due to page limitations.  The supplement is organized in the same manner as the main paper i.e. the section names in the main paper corresponds to the same section in the supplement for the easy reference.  In many cases, text from the main paper is included and or extended in order to provide context for the figures, tables, and code listings contained in this supplement. The figure numbers may get changed as some more figures are added in this supplement for detailed explanation. A. Graph Pattern Matching The goal of graph pattern matching is to find all subgraphs of a large graph, called the data graph, that are similar to a query graph structurally and semantically. To consider why this might be useful, look again at the graph displayed in Figure 1. Suppose a user of Facebook has just moved to Lyon, France from the United States and is looking for someone to accompany him to the U2 concert there. Thus, he wants to find out if any of his friends are friends with a person who lives in Lyon and who likes U2. Given that Facebook can be modeled as a graph like Figure 1, this question can be modeled as a graph query, as shown in Figure 2. In this query, the capital letters represent variables that the user would like filled in. In this case, using the graph in Figure 1, the query would return X = John and Y = Jim. In fact, Facebook Graph Search2 attempts to allow users to do just that, though at the moment it only has limited querying capabilities.
One-Dimensional Convolutional Neural Network Land-Cover Classification of Multi-Seasonal Hyperspectral Imagery in the San Francisco Bay Area, California

In this study, a 1-D Convolutional Neural Network (CNN) architecture was developed, trained and utilized to classify single (summer) and three seasons (spring, summer, fall) of hyperspectral imagery over the San Francisco Bay Area, California for the year 2015. For comparison, the Random Forests (RF) and Support Vector Machine (SVM) classifiers were trained and tested with the same data. In order to support space-based hyperspectral applications, all analyses were performed with simulated Hyperspectral Infrared Imager (HyspIRI) imagery. Three-season data improved classifier overall accuracy by 2.0% (SVM), 1.9% (CNN) to 3.5% (RF) over single-season data. The three-season CNN provided an overall classification accuracy of 89.9%, which was comparable to overall accuracy of 89.5% for SVM. Both three-season CNN and SVM outperformed RF by over 7% overall accuracy. Analysis and visualization of the inner products for the CNN provided insight to distinctive features within the spectral-temporal domain. A method for CNN kernel tuning was presented to assess the importance of learned features. We concluded that CNN is a promising candidate for hyperspectral remote sensing applications because of the high classification accuracy and interpretability of its inner products.
Process models in the practice of distributed software development: A systematic review of the literature

0950-5849/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.infsof.2010.03.009 * Corresponding author. E-mail addresses: rafaelp@pucrs.br ( Distributed Software Development (DSD) has recently become an active research area. Although considerable research effort has been made in this area, as yet, no agreement has been reached as to an appropriate process model for DSD.  This paper is intended to identify and synthesize papers that describe process models for distributed software development in the context of overseas outsourcing, i.e. ‘‘offshoring”.  We used a systematic review methodology to search seven digital libraries and one topic-specific conference.  We found 27 primary studies describing stage-related DSD process models. Only five of such studies looked into outsourcing to a subsidiary company (i.e. ‘‘internal offshoring”). Nineteen primary studies addressed the need for DSD process models. Eight primary studies and three literature surveys described stage-based DSD process models, but only three of such models were empirically evaluated.  We need more research aimed at internal offshoring. Furthermore, proposed models need to be empirically validated.
Offline Handwritten Character Recognition Techniques using Neural Network : A Review

This paper presents detailed review in the field of Off-line Handwritten Character Recognition. Various methods are analyzed that have been proposed to realize the core of character recognition in an optical character recognition system. The recognition of handwriting can, however, still is considered an open research problem due to its substantial variation in appearance. Even though, sufficient studies have performed from history to this era, paper describes the techniques for converting textual content from a paper document into machine readable form. Offline handwritten character recognition is a process where the computer understands automatically the image of handwritten script. This material serves as a guide and update for readers working in the Character Recognition area. Selection of a relevant feature extraction method is probably the single most important factor in achieving high recognition performance with much better accuracy in character recognition systems.
Uniport: A Uniform Programming Support Framework for Mobile Cloud Computing

Personal mobile devices (PMDs) have become the most used computing devices for many people. With the introduction of mobile cloud computing, we can augment the storage and computing capabilities of PMDs via cloud support. However, there are many challenges in developing mobile cloud applications (MCAs) that incorporate cloud computing efficiently, especially for developers targeting multiple mobile platforms. This paper presents Uniport, a uniform framework for developing MCAs. We introduce a uniform architecture for MCAs based on the Model-View-Controller (MVC) pattern and a set of programming primitives and runtime libraries. Not only can Uniport support the creation of new MCAs, it can also help transform existing mobile applications to MCAs efficiently. We demonstrate the applicability and flexibility of Uniport in a case study to transform three existing mobile applications on iOS, Android and Windows Phone, to their mobile cloud versions respectively. Evaluation results show that, with very few modifications, we can easily transform mobile applications to MCAs that can exploit the cloud support to improve performance by 3 - 7x and save more than half of their energy consumption.
Weighted Coverage based Reviewer Assignment

Peer reviewing is a standard process for assessing the quality of submissions at academic conferences and journals. A very important task in this process is the assignment of reviewers to papers. However, achieving an appropriate assignment is not easy, because all reviewers should have similar load and the subjects of the assigned papers should be consistent with the reviewers' expertise. In this paper, we propose a generalized framework for fair reviewer assignment. We first extract the domain knowledge from the reviewers' published papers and model this knowledge as a set of topics. Then, we perform a group assignment of reviewers to papers, which is a generalization of the classic Reviewer Assignment Problem (RAP), considering the relevance of the papers to topics as weights. We study a special case of the problem, where reviewers are to be found for just one paper ( and propose an exact algorithm which is fast in practice, as opposed to brute-force solutions. For the general case of having to assign multiple papers, which is too hard to be solved exactly, we propose a greedy algorithm that achieves a 1/2-approximation ratio compared to the exact solution. This is a great improvement compared to the 1/3-approximation solution proposed in previous work for the simpler coverage-based reviewer assignment problem, where there are no weights on topics. We theoretically prove the approximation bound of our solution and experimentally show that it is superior to the current state-of-the-art.
SoilJ : An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils

Noninvasive threeand four-dimensional X-ray imaging approaches have proved to be valuable analysis tools for vadose zone research. One of the main bottlenecks for applying X-ray imaging to data sets with a large number of soil samples is the relatively large amount of time and expertise needed to extract quantitative data from the respective images. SoilJ is a plugin for the free and open imaging software ImageJ that aims at automating the corresponding processing steps for cylindrical soil columns. It includes modules for automatic column outline recognition, correction of image intensity bias, image segmentation, extraction of particulate organic matter and roots, soil surface topography detection, as well as morphology and percolation analyses. In this study, the functionality and precision of some key SoilJ features were demonstrated on five different image data sets of soils. SoilJ has proved to be useful for strongly decreasing the amount of time required for image processing of large image data sets. At the same time, it allows researchers with little experience in image processing to make use of X-ray imaging methods. The SoilJ source code is freely available and may be modified and extended at will by its users. It is intended to stimulate further community-driven development of this software.
Nonparametric permutation tests for functional neuroimaging: a primer with examples.

Requiring only minimal assumptions for validity, nonparametric permutation testing provides a flexible and intuitive methodology for the statistical analysis of data from functional neuroimaging experiments, at some computational expense. Introduced into the functional neuroimaging literature by Holmes et al. ([1996]: J Cereb Blood Flow Metab 16:7-22), the permutation approach readily accounts for the multiple comparisons problem implicit in the standard voxel-by-voxel hypothesis testing framework. When the appropriate assumptions hold, the nonparametric permutation approach gives results similar to those obtained from a comparable Statistical Parametric Mapping approach using a general linear model with multiple comparisons corrections derived from random field theory. For analyses with low degrees of freedom, such as single subject PET/SPECT experiments or multi-subject PET/SPECT or fMRI designs assessed for population effects, the nonparametric approach employing a locally pooled (smoothed) variance estimate can outperform the comparable Statistical Parametric Mapping approach. Thus, these nonparametric techniques can be used to verify the validity of less computationally expensive parametric approaches. Although the theory and relative advantages of permutation approaches have been discussed by various authors, there has been no accessible explication of the method, and no freely distributed software implementing it. Consequently, there have been few practical applications of the technique. This article, and the accompanying MATLAB software, attempts to address these issues. The standard nonparametric randomization and permutation testing ideas are developed at an accessible level, using practical examples from functional neuroimaging, and the extensions for multiple comparisons described. Three worked examples from PET and fMRI are presented, with discussion, and comparisons with standard parametric approaches made where appropriate. Practical considerations are given throughout, and relevant statistical concepts are expounded in appendices.
Effect of gas type and flow rate on Cu free air ball formation in thermosonic wire bonding

0026-2714/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.microrel.2010.02.023 * Corresponding author. E-mail address: apequegn@uwaterloo.ca (A. Peque The development of novel Cu wires for thermosonic wire bonding is time consuming and the effects of shielding gas on the electrical flame off (EFO) process is not fully understood. An online method is used in this study for characterizing Cu free air balls (FABs) formed with different shielding gas types and flow rates. The ball heights before (HFAB) and after deformation (Hdef) are responses of the online method and measured as functions of gas flow rate. Sudden changes in the slopes of these functions, a non-parallelity of the two functions, and a large standard deviation of the HFAB measurements all identify FAB defects. Using scanning electron microscope (SEM) images in parallel with the online measurements golf-club shaped and pointed shaped FABs are found and the conditions at which they occur are identified. In general FAB defects are thought to be caused by changes in surface tension of the molten metal during EFO due to inhomogeneous cooling or oxidation. It is found that the convective cooling effect of the shielding gas increases with flow rate up to 0.65 l/min where the bulk temperature of a thermocouple at the EFO site decreases by 19 C. Flow rates above 0.7 l/min yield an undesirable EFO process due to an increase in oxidation which can be explained by a change in flow from laminar to turbulent. The addition of H2 to the shielding gas reduces the oxidation of the FAB as well as providing additional thermal energy during EFO. Different Cu wire materials yield different results where some perform better than others.
BinHunt: Automatically Finding Semantic Differences in Binary Programs

We introduce BinHunt, a novel technique for finding semantic differences in binary programs. Semantic differences between two binary files contrast with syntactic differences in that semantic differences correspond to changes in the program functionality. Semantic differences are difficult to find because of the noise from syntactic differences caused by, e.g., different register allocation and basic block re-ordering. BinHunt bases its analysis on the control flow of the programs using a new graph isomorphism technique, symbolic execution, and theorem proving. We implement a system based on BinHunt and demonstrate the application of the system with three case studies in which BinHunt manages to identify the semantic differences between an executable and its patched version, revealing the vulnerability that the patch eliminates.
Stochastic block model reveals maps of citation patterns and their evolution in time

In this study we map out the large-scale structure of citation networks of science journals and follow their evolution in time by using stochastic block models (SBMs). The SBM fitting procedures are principled methods that can be used to find hierarchical grouping of journals into blocks that show similar incoming and outgoing citations patterns. These methods work directly on the citation network without the need to construct auxiliary networks based on similarity of nodes. We fit the SBMs to the networks of journals we have constructed from the data set of around 630 million citations and find a variety of different types of blocks, such as clusters, bridges, sources, and sinks. In addition we use a recent generalization of SBMs to determine how much a manually curated classification of journals into subfields of science is related to the block structure of the journal network and how this relationship changes in time. The SBM method tries to find a network of blocks that is the best high-level representation of the network of journals, and we illustrate how these block networks (at various levels of resolution) can be used as maps of science. ∗darko.hric@aalto.fi †kimmo.kaski@aalto.fi ‡mikko.kivela@aalto.fi 1 ar X iv :1 70 5. 00 01 8v 1 [ ph ys ic s. so cph ] 2 8 A pr 2 01 7
Asynchronous frameless event-based optical flow

This paper introduces a process to compute optical flow using an asynchronous event-based retina at high speed and low computational load. A new generation of artificial vision sensors has now started to rely on biologically inspired designs for light acquisition. Biological retinas, and their artificial counterparts, are totally asynchronous and data driven and rely on a paradigm of light acquisition radically different from most of the currently used frame-grabber technologies. This paper introduces a framework for processing visual data using asynchronous event-based acquisition, providing a method for the evaluation of optical flow. The paper shows that current limitations of optical flow computation can be overcome by using event-based visual acquisition, where high data sparseness and high temporal resolution permit the computation of optical flow with micro-second accuracy and at very low computational cost.
LCC-Graph: A high-performance graph-processing framework with low communication costs

With the rapid growth of data, communication overhead has become an important concern in applications of data centers and cloud computing. However, existing distributed graph-processing frameworks routinely suffer from high communication costs, leading to very long waiting times experienced by users for the graph-computing results. In order to address this problem, we propose a new computation model with low communication costs, called LCC-BSP. We use this model to design and implement a high-performance distributed graph-processing framework called LCC-Graph. This framework eliminates the high communication costs in existing distributed graph-processing frameworks. Moreover, LCC-Graph also minimizes the computation workload of each vertex, significantly reducing the computation time for each superstep. Evaluation of LCC-Graph on a 32-node cluster, driven by real-world graph datasets, shows that it significantly outperforms existing distributed graph-processing frameworks in terms of runtime, particularly when the system is supported by a high-bandwidth network. For example, LCC-Graph achieves an order of magnitude performance improvement over GPS and GraphLab.
When private keys are public: results from the 2008 Debian OpenSSL vulnerability

We report on the aftermath of the discovery of a severe vulnerability in the Debian Linux version of OpenSSL. Systems affected by the bug generated predictable random numbers, most importantly public/private keypairs. To study user response to this vulnerability, we collected a novel dataset of daily remote scans of over 50,000 SSL/TLS-enabled Web servers, of which 751 displayed vulnerable certificates. We report three primary results. First, as expected from previous work, we find an extremely slow rate of fixing, with 30% of the hosts vulnerable when we began our survey on day 4 after disclosure still vulnerable almost six months later. However, unlike conventional vulnerabilities, which typically show a short, fast fixing phase, we observe a much flatter curve with fixing extending six months after the announcement. Second, we identify some predictive factors for the rate of upgrading. Third, we find that certificate authorities continued to issue certificates to servers with weak keys long after the vulnerability was disclosed.
Knowledge management, codification and tacit knowledge

This article returns to a theme addressed in Vol. 8(1) October 2002 of the journal: knowledge management and the problem of managing tacit knowledge.  The article is primarily a review and analysis of the literature associated with the management of knowledge. In particular, it focuses on the works of a group of economists who have studied the transformation of knowledge into information through the process of codification and the knowledge transaction topography they have developed to describe this process. Analysis. The article explores the theoretical and philosophical antecedents of the economists' views. It uses this as a basis for examining the dominant views of knowledge that appear in much of the literature on knowledge management and for performing a critical evaluation of their work.  The results of the analysis centre upon the question of when is it appropriate to codify knowledge. They present a basic summary of the costs and benefits of codification before looking in more detail at its desirability.  The conclusions concern the implications of the above for knowledge management and the management of tacit knowledge. They deal with the nature of knowledge management, some of the reasons why knowledge management projects fail to achieve their expectations and the potential problems of codification as a strategy for knowledge management.