nils-herrmann/clean_scirepeval huggingface dataset:
Exploiting Redundancy in Question Answering

Our goal is to automatically answer brief factual questions of the form ``When was the Battle of Hastings?'' or ``Who wrote The Wind in the Willows?''. Since the answer to nearly any such question can now be found somewhere on the Web, the problem reduces to finding potential answers in large volumes of data and validating their accuracy. We apply a method for arbitrary passage retrieval to the first half of the problem and demonstrate that answer redundancy can be used to address the second half. The success of our approach depends on the idea that the volume of available Web data is large enough to supply the answer to most factual questions multiple times and in multiple contexts. A query is generated from a question and this query is used to select short passages that may contain the answer from a large collection of Web data. These passages are analyzed to identify candidate answers. The frequency of these candidates within the passages is used to ``vote'' for the most likely answer. The approach is experimentally tested on questions taken from the TREC-9 question-answering test collection. As an additional demonstration, the approach is extended to answer multiple choice trivia questions of the form typically asked in trivia quizzes and television game shows.
A vehicle license plate recognition system based on analysis of maximally stable extremal regions

Vehicle License Plate Recognition (VLPR) system is a core module in Intelligent Transportation Systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.
Action recognition from a distributed representation of pose and appearance

We present a distributed representation of pose and appearance of people called the “poselet activation vector”. First we show that this representation can be used to estimate the pose of people defined by the 3D orientations of the head and torso in the challenging PASCAL VOC 2010 person detection dataset. Our method is robust to clutter, aspect and viewpoint variation and works even when body parts like faces and limbs are occluded or hard to localize. We combine this representation with other sources of information like interaction with objects and other people in the image and use it for action recognition. We report competitive results on the PASCAL VOC 2010 static image action classification challenge.
FearNot! - An Experiment in Emergent Narrative

We discuss the experience of constructing the application FearNot! (Fun with Empathic Agents Reaching Novel Outcomes in Teaching), an application of virtual drama to anti-bullying education inspired by Forum Theatre. An appraisal-driven agent architecture is presented as a mechanism for generating an emergent, that is, unscripted, narrative. A small-scale evaluation is discussed and the lessons learned are described.
A Bandwidth Improved Circular Polarized Slot Antenna Using a Slot Composed of Multiple Circular Sectors

A circular polarized (CP) slot antenna is designed with a slot composed of multiple circular sectors (MCS). The design has advantages of having a wide 3 dB axial ratio (AR) bandwidth of 57.4%, achieving a good AR smaller than 2 dB in most areas of the frequency range. The design of the antenna follows a multi-objective optimization procedure that applies computational power rather than human tuning. A comparison of the optimized antenna design with other wideband CP antennas in the literature shows that it has advantages of having a smaller physical size in the cross-sectional area than the antennas with multiple feeding structures and a wider operating bandwidth than all the compared antennas.
Polygonal chain intersection

In order to find all intersections among polygonal chains, this paper presents a procedure consisting of two phases: (1) splitting polygonal chains into a minimal number of monotone chains and (2) finding intersections among the monotone chains. For the first phase, we suggest an optimal algorithm splitting polygonal chains into a minimal number of monotone chains, with an Oðn þ r log rÞ time complexity, where n is the number of line-segments in the polygonal chains and r is the number of C-subchains. For the second phase, we extend Bentley–Ottmann’s sweep-line algorithm and the time complexity is Oððn þ kÞlog mÞ; where k is the number of intersections, and m is the minimal number of monotone chains. r 2002 Elsevier
Efficient Data Structures for Massive N-Gram Datasets

The efficient indexing of large and sparse N-gram datasets is crucial in several applications in Information Retrieval, Natural Language Processing and Machine Learning. Because of the stringent efficiency requirements, dealing with billions of N-grams poses the challenge of introducing a compressed representation that preserves the query processing speed.
 In this paper we study the problem of reducing the space required by the representation of such datasets, maintaining the capability of looking up for a given N-gram within micro seconds. For this purpose we describe compressed, exact and lossless data structures that achieve, at the same time, high space reductions and no time degradation with respect to state-of-the-art software packages. In particular, we present a trie data structure in which each word following a context of fixed length k, i.e., its preceding k words, is encoded as an integer whose value is proportional to the number of words that follow such context. Since the number of words following a given context is typically very small in natural languages, we are able to lower the space of representation to compression levels that were never achieved before. Despite the significant savings in space, we show that our technique introduces a negligible penalty at query time.
Big Data and supply chain management: a review and bibliometric analysis

As Big Data has undergone a transition from being an emerging topic to a growing research area, it has become necessary to classify the different types of research and examine the general trends of this research area. This should allow the potential research areas that for future investigation to be identified. This paper reviews the literature on ‘Big Data and supply chain management (SCM)’, dating back to 2006 and provides a thorough insight into the field by using the techniques of bibliometric and network analyses. We evaluate 286 articles published in the past 10 years and identify the top contributing authors, countries and key research topics. Furthermore, we obtain and compare the most influential works based on citations and PageRank. Finally, we identify and propose six research clusters in which scholars could be encouraged to expand Big Data research in SCM. We contribute to the literature on Big Data by discussing the challenges of current research, but more importantly, by identifying and proposing these six research clusters and future research directions. Finally, we offer to managers different schools of thought to enable them to harness the benefits from using Big Data and analytics for SCM in their everyday work.
Mediating intimacy: designing technologies to support strong-tie relationships

Intimacy is a crucial element of domestic life, and many interactive technologies designed for other purposes have been appropriated for use within intimate relationships. However, there is a deficit in current understandings of how technologies are used within intimate relationships, and how to design technologies to support intimate acts. In this paper we report on work that has addressed these deficits. We used cultural probes and contextual interviews and other ethnographically informed techniques to investigate how interactive technologies are used within intimate relationships. From this empirical work we generated a thematic understanding of intimacy and the use of interactional technologies to support intimate acts. We used this understanding to inform the design of intimate technologies. A selection of our design concepts is also presented.
PUSHOVER ANALYSIS OF A MULTISTORIED BUILDING

To model the advanced behaviour of reinforced concrete analytically in its non-linear zone is difficult. This has led engineers in the past to believe heavily on empirical formulas that were derived from numerous experiments for the design of reinforced concrete structures. For structural design and assessment of reinforced concrete members, the nonlinear analysis has become a vital tool. The method can be used to study the behaviour of reinforced concrete structures as well as force redistribution. This analysis of the nonlinear response of RC structures to be distributed out in an exceedingly routine fashion. It helps within the investigation of the behaviour of the structure below completely different loading conditions and also the cracks pattern. In the present study, the non-linear response of RCC frame using the loading has been carried out with the intention to investigate the relative importance of many factors in the non-linear analysis of RCC frames. The structure was modelled and analyzed in STAAD Pro V8i, SAP2000 and designed manually. The description of the reinforcement was done in AutoCAD 2010. Keywordsmulti-storied building, STAAD PRO, Floor plan, SAP 2000, Push over analysis.
Balanced outcomes in social exchange networks

The study of bargaining has a long history, but many basic settings are still rich with unresolved questions. In particular, consider a set of agents who engage in bargaining with one another,but instead of pairs of agents interacting in isolation,agents have the opportunity to choose whom they want to negotiate with, along the edges of a graph representing social-network relations. The area of network exchange theory in sociology has developed a large body of experimental evidence for the way in which people behave in such network-constrained bargaining situations, and it is a challenging problem to develop models that are both mathematically tractable and in general agreement with the results of these experiments.
 We analyze a natural theoretical model arising in network exchange theory, which can be viewed as a direct extension of the well-known Nash bargaining solution to the case of multiple agents interacting on a graph. While this generalized Nash bargaining solution is surprisingly effective at picking up even subtle differences in bargaining power that have been observed experimentally on small examples, it has remained an open question to characterize the values taken by this solution on general graphs, or to find an efficient means to compute it.
 Here we resolve these questions, characterizing the possible values of this bargaining solution, and giving an efficient algorithm to compute the set of possible values. Our result exploits connections to the structure of matchings in graphs, including decomposition theorems for graphs with perfect matchings, and also involves the development of new techniques. In particular, the values we are seeking turn out to correspond to a novel combinatorially defined point in the interior of a fractional relaxation of the matching problem.
Monte Carlo Filtering Using Kernel Embedding of Distributions

Recent advances of kernel methods have yielded a framework for representing probabilities using a reproducing kernel Hilbert space, called kernel embedding of distributions. In this paper, we propose a Monte Carlo filtering algorithm based on kernel embeddings. The proposed method is applied to state-space models where sampling from the transition model is possible, while the observation model is to be learned from training samples without assuming a parametric model. As a theoretical basis of the proposed method, we prove consistency of the Monte Carlo method combined with kernel embeddings. Experimental results on synthetic models and real vision-based robot localization confirm the effectiveness of the proposed approach.
Asynchronous Consensus and Broadcast Protocols

A consensus protocol enables a system of n asynchronous processes, some of which are faulty, to reach agreement. There are two kinds of faulty processes: fail-stop processes that can only die and malicious processes that can also send false messages. The class of asynchronous systems with fair schedulers is defined, and consensus protocols that terminate with probability 1 for these systems are investigated. With fail-stop processes, it is shown that ⌈(n + 1)/2⌉ correct processes are necessary and sufficient to reach agreement. In the malicious case, it is shown that ⌈(2n + 1)/3⌉ correct processes are necessary and sufficient to reach agreement. This is contrasted with an earlier result, stating that there is no consensus protocol for the fail-stop case that always terminates within a bounded number of steps, even if only one process can fail. The possibility of reliable broadcast (Byzantine Agreement) in asynchronous systems is also investigated. Asynchronous Byzantine Agreement is defined, and it is shown that ⌈(2n + 1)/3⌉ correct processes are necessary and sufficient to achieve it.
GPCAD: a tool for CMOS op-amp synthesis

We present a method for optimizing and automating component and transistor sizing for CMOS operational amplifiers. We observe that a wide variety of performance measures can be formulated as posynomial functions of the design variables. As a result, amplifier design problems can be formulated as a geometric program, a special type of convex optimization problem for which very efficient global optimization methods have recently been developed. The synthesis method is therefore fast, and determines the globally optimal design; in particular the final solution is completely independent of the starting point (which can even be infeasible), and infeasible specifications are unambiguously detected. After briefly introducing the method, which is described in more detail by M. Hershenson et al., we show how the method can be applied to six common op-amp architectures, and give several example designs.
Confidence Measure for Automatic Face Recognition

This paper deals with the use of confidence measure for Automatic Face Recognition (AFR). AFR is realized by the adapted Kepenecki face recognition approach based on the Gabor wavelet transform. This work is motivated by the fact that obtained recognition rate on the real-world corpus is only about 50% which is not sufficient for our application, a system for automatic labelling of the photographs in a large database. The main goal of this work is thus the proposition of the post-processing of the classification result in order to remove the “incorrectly” classified face images. We show that the use of confidence measure to filter out incorrectly recognized faces is beneficial. Two confidence measures are proposed and evaluated on the Czech News Agency (̌ CTK) corpus. Experimental results confirm the benefit of the use of confidence measure for the automatic face recognition task.
A comparative analysis of common YouTube comment spam filtering techniques

Ever since its development in 2005, YouTube has been providing a vital social media platform for video sharing. Unfortunately, YouTube users may have malicious intentions, such as disseminating malware and profanity. One way to do so is using the comment field for this purpose. Although YouTube provides a built-in tool for spam control, yet it is insufficient for combating malicious and spam contents within the comments. In this paper, a comparative study of the common filtering techniques used for YouTube comment spam is conducted. The study deploys datasets extracted from YouTube using its Data API. According to the obtained results, high filtering accuracy (more than 98%) can be achieved with low-complexity algorithms, implying the possibility of developing a suitable browser extension to alleviate comment spam on YouTube in future.
Self-calibration of the 6-DOF parallel robot TRIPLANAR by identification of the geometry parameters

This paper presents a model-based procedure for the self-calibration of the parallel robot, TRIPLANAR, that gets by on just a relatively simple measuring system. The measuring device continuously quantifies the distance between the tool-center point (TCP) that is adjustable in all 6 degrees of freedom and a fixed reference point in the inertial coordinate system (ICS). After just one run over a suitable measuring trajectory and recording of the measuring data (distance TCP-ICS and actuator positions) a parameter identification is performed by minimizing the deviation between the measured pose (position and orientation) and the one that was determined from a model. The identified parameters are taken into account in an inverse kinematics model that is used for the feedforward control of the TriPlanar; thus positioning accuracy can be greatly increased.
Real-time Convolutional Networks for Depth-based Human Pose Estimation

We propose to combine recent Convolutional Neural Networks (CNN) models with depth imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to Human Robot Interaction (HRI) scenarios. Our hypothesis is that depth images contain less structures and are easier to process than RGB images while keeping the required information for human detection and pose inference, thus allowing the use of simpler networks for the task. Our contributions are threefold. (i) we propose a fast and efficient network based on residual blocks (called RPM) for body landmark localization from depth images; (ii) we created a public dataset DIH comprising more than 170k synthetic images of human bodies with various shapes and viewpoints as well as real (annotated) data for evaluation; (iii) we show that our model trained on synthetic data from scratch can perform well on real data, obtaining similar results to larger models initialized with pre-trained networks. It thus provides a good trade-off between performance and computation. Experiments on real data demonstrate the validity of our approach.
Improving Japanese-to-English Neural Machine Translation by Paraphrasing the Target Language

Neural machine translation (NMT) produces sentences that are more fluent than those produced by statistical machine translation (SMT). However, NMT has a very high computational cost because of the high dimensionality of the output layer. Generally, NMT restricts the size of the vocabulary, which results in infrequent words being treated as out-of-vocabulary (OOV) and degrades the performance of the translation. In order to improve the translation quality regarding words that are OOV in the target language, we propose a preprocessing method that paraphrases infrequent words or phrases expressed as OOV with frequent synonyms from the target side of the training corpus. In an evaluation using Japanese to English translation, we achieved a statistically significant BLEU score improvement of 0.55–0.77 over baselines that included the state-of-the-art method.
Risk factors for involvement in cyber bullying : Victims , bullies and bully – victims ☆

The use of online technology is exploding worldwide and is fast becoming a preferred method of interacting. While most online interactions are neutral or positive the Internet provides a new means through which children and youth are bullied. The aim of this grounded theory approach was to explore technology, virtual relationships and cyber bullying from the perspectives of students. Seven focus groups were held with 38 students between fifth and eighth grades. The participants considered cyber bullying to be a serious problem and some characterized online bullying as more serious than  ̳traditional‘ bullying because of the associated anonymity. Although the students depicted anonymity as integral to cyber bullying, the findings suggest that much of the cyber bullying occurred within the context of their social groups and relationships. Findings revealed five major themes: technology embraced at younger ages and becoming the dominant medium for communication; definitions and views of cyber bullying; factors unique to cyber bullying; types of cyber bullying; and telling adults. The findings highlight the complexity of the perceived anonymity provided by the Internet and how AC C EP TE D M AN U SC R IP T ACCEPTED MANUSCRIPT 3 this may impact cyber bullying. The study offers greater awareness of the meanings of online relationships for children and youth.
FILTERING OF LASER ALTIMETRY DATA USING A SLOPE ADAPTIVE FILTER

A point set obtained by laser altimetry represents points from not only the ground surface but also objects found on it. For civil works applications points representing the surface of non-ground objects have to be removed from the point set in a filtering process. This paper describes modifications made to an existing “slope based” filtering algorithm, and presents some results obtained from the use of the filter. The “slope based” filter operates on the assumption that terrain slopes do not rise above a certain threshold, and that features in the data that have slopes above this threshold do not belong to the natural terrain surface. However, this assumption limits the use of the filter to terrain with gentle slopes. To overcome this limitation, the filter was modified in manner that the threshold varies with respect to the slope of the terrain. The results of tests carried out using the modified filter confirm that the modification reduces the number of Type I errors (ground points in steep terrain are not filtered off). Further numerical comparison of the filter output with a reference data set for the same site (obtained photogrammetrically) show that the filter generates relatively minimal Type II errors. The output of the modified slope filter was also compared with the output from a filtering found in the commercial software package, “Terrascan”.