nils-herrmann/clean_scirepeval huggingface dataset:
Semi-Supervised Chinese Word Segmentation Using Partial-Label Learning With Conditional Random Fields

There is rich knowledge encoded in online web data. For example, punctuation and entity tags in Wikipedia data define some word boundaries in a sentence. In this paper we adopt partial-label learning with conditional random fields to make use of this valuable knowledge for semi-supervised Chinese word segmentation. The basic idea of partial-label learning is to optimize a cost function that marginalizes the probability mass in the constrained space that encodes this knowledge. By integrating some domain adaptation techniques, such as EasyAdapt, our result reaches an F-measure of 95.98% on the CTB-6 corpus, a significant improvement from both the supervised baseline and a previous proposed approach, namely constrained decode.
Cooperative impedance control for multiple UAVs with a robotic arm

In this paper, an impedance control scheme for cooperative quadrotors with robotic arms is proposed in order to limit both the contact forces, due to the object/environment interaction, and the internal forces, due to the manipulators/ object interaction. To this aim, two impedance filters are used to determine the reference trajectories for manipulator end effectors: the first is aimed at conferring a compliant behavior at the object level (external impedance), while the second filter, is aimed at avoiding large internal loading of the object (internal impedance). Such trajectories are fed to a motion controller including an inverse kinematics algorithm and a PD controller with gravity compensation. The effectiveness of the proposed approach is then verified in simulation.
Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning

Analyzing Collaborative Learning Processes Automatically Running Head: ANALYZING COLLABORATIVE LEARNING PROCESSES AUTOMATICALLY Analyzing Collaborative Learning Processes Automatically: Exploiting the Advances of Computational Linguistics in Computer-Supported Collaborative Learning Carolyn Rosé, Yi-Chia Wang, Yue Cui, Jaime Arguello Carnegie Mellon University, USA Frank Fischer, Armin Weinberger, Karsten Stegmann University of Munich, Germany Corresponding author: Carolyn Rosé, Language Technologies Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh PA, 15213, Phone: ++1 (412) 268-7130,  268-6298, email: cprose@cs.cmu.edu
Searching for Audio by Sketching Mental Images of Sound: A Brave New Idea for Audio Retrieval in Creative Music Production

We propose a new paradigm for searching for sound by allowing users to graphically sketch their mental representation of sound as query. By conducting interviews with professional music producers and creators, we find that existing, text-based indexing and retrieval methods based on file names and tags to search for sound material in large collections (e.g., sample databases) do not reflect their mental concepts, which are often rooted in the visual domain and hence are far from their actual needs, work practices, and intuition. As a consequence, when creating new music on the basis of existing sounds, the process of finding these sounds is cumbersome and breaks their work flow by being forced to resort to browsing the collection. Prior work on organizing sound repositories aiming at bridging this conceptual gap between sound and vision builds upon psychological findings (often alluding to synaesthetic phenomena) or makes use of ad-hoc, technology-driven mappings. These methods foremost aim at visualizing the contents of collections or individual sounds and, again, facilitating browsing therein. For the purpose of indexing and querying, such methods have not been applied yet. We argue that the development of a search system that allows for visual queries to audio collections is desired by users and should inform and drive future research in audio retrieval. To explore this notion, we test the idea of a sketch interface with music producers in a semi-structured interview process by making use of a physical non-functional prototype. Based on the outcomes of this study, we propose a conceptual software prototype for visually querying sound repositories using image manipulation metaphors.
Determinants of antenatal care, institutional delivery and postnatal care services utilization in Nigeria

Utilization of antenatal care, institutional delivery and postnatal care services in Nigeria are poor even by african average.



We analysed the 2013 Nigeria DHS to determine factors associated with utilization of these health MCH indicators by employing both bivariate and multivariate logistic regressions.



Overall, 54% of women had at least four ANC visits, 37% delivered in health facility and 29% of new born had postnatal care within two of births. Factors that consistently predict the utilization of the three MCH services are maternal and husband's level education, place of residence, wealth level and parity. Antenatal care strongly predicts both health facility delivery (OR = 2.16, 95%CI: 1.99-2.34) and postnatal care utilization (OR = 4.67, 95%CI: 3.95-5.54); while health facility delivery equally predicting postnatal care (OR = 2.84, 95%CI: 2.20-2.80).



Improving utilization of these three MCH indicators will require targeting women in the rural areas and those with low level of education as well as creating demand for health facility delivery. Improving ANC use by making it available and accessible will have a multiplier effect of improving facility delivery which will lead to improved postnatal care utilization.
Optimization of standard cell based detailed placement for 16 nm FinFET process

FinFET transistors have great advantages over traditional planar MOSFET transistors in high performance and low power applications. Major foundries are adopting the Fin-FET technology for CMOS semiconductor device fabrication in the 16 nm technology node and beyond. Edge device degradation is among the major challenges for the FinFET process. To avoid such degradation, dummy gates are needed on device edges, and the dummy gates have to be tied to power rails in order not to introduce unconnected parasitic transistors. This requires that each dummy gate must abut at least one source node after standard cell placement. If the drain nodes at two adjacent cell boundaries abut each other, additional source nodes must be inserted in between for dummy gate power tying, which costs more placement area. Usually there is some flexibility during detailed placement to horizontally flip the cells or switch the positions of adjacent cells, which has little impact on the global placement objectives, such as timing conditions and net congestion. This paper proposes a detailed placement optimization strategy for the standard cell based designs. By flipping a subset of cells in a standard cell row and switching pairs of adjacent cells, the number of drain to drain abutments between adjacent cell boundaries can be optimally minimized, which saves additional source node insertion and reduces the length of the standard cell row. In addition, the proposed graph model can be easily modified to consider more complicated design rules. The experimental results show that the optimization of 100k cells is completed within 0.1 second, verifying the efficiency of the proposed algorithm.
New species of Phallodrilus (Oligochaeta, Tubificidae) from caves of northern Spain and southwestern France

A taxonomic account of a collection of Phallodrilus species inhabiting caves is given. The following three new species are described: P. subterraneus, P. crypticus and P. labouichensis. New material of P. aquaedulcis Hrabe, 1960 from northern Spain and southwestern France is reported. This species was previously known from West Germany. The relationship between Phallodrilus cave species and littoral and deep-sea species is discussed.
Performance evaluation of electric power steering with IPM motor and drive system

As the development of microprocessors, power electronic converters and electric motor drives, electric power steering (EPS) system which uses an electric motor came to use a few year ago. Electric power steering systems have many advantages over traditional hydraulic power steering systems in engine efficiency, space efficiency, and environmental compatibility. This paper deals with design and optimization of an interior permanent magnet (IPM) motor for power steering application. Simulated Annealing method is used for optimization. After optimization and finding motor parameters, An IPM motor and drive with mechanical parts of EPS system is simulated and performance evaluation of system is done.
Complementing Travel Diary Surveys with Twitter Data: Application of Text Mining Techniques on Activity Location, Type and Time

A growing body of literature in social science has been devoted to extracting new information from social media to assist authorities in manage crowd projects. In this paper geolocation (or spatial) based information provided in social media is investigated to utilize intelligent transportation services. Further, the general trend of travel activities during weekdays is studied. For this purpose, a dataset consisting of more than 40,000 tweets in south and west part of the Sydney metropolitan area is utilized. After a data processing effort, the tweets are clustered into seven main categories using text mining techniques, where each category represents a type of activity including shopping, recreation, and work. Unlike the previous studies in this area, the focus of this work is on the content of the tweets rather than only using geotagged data or sentiment analysis. Beside activity type, temporal and spatial distributions of activities are used in the classification exercise. Categories are mapped to the identified regions within the city of Sydney across four time slots (two peak periods and two off-peak periods). Each time slot is used to construct a network with nodes representing people, activities and locations and edges reflecting the association between the nodes. The constructed networks are used to study the trend of activities/locations in a typical working day.
Histones and histone modifications

Imagine trying to stuff about 10,000 miles of spaghetti inside a basketball. Then, if that was not difficult enough, attempt to find a unique one inch segment of pasta from the middle of this mess, or try to duplicate, untangle and separate individual strings to opposite ends. This simple analogy illustrates some of the daunting tasks associated with the transcription, repair and replication of the nearly 2 meters of DNA that is packaged into the confines of a tiny eukaryotic nucleus. The solution to each of these problems lies in the assembly of the eukaryotic genome into chromatin, a structural polymer that not only solves the basic packaging problem, but also provides a dynamic platform that controls all DNA-mediated processes within the nucleus. The basic unit of chromatin is the nucleosome core particle, which contains 147 bp of DNA wrapped nearly twice around an octamer of the core histones. The histone octamer is composed of a central heterotetramer of histones H3 and H4, flanked by two heterodimers of histones H2A and H2B. Each nucleosome is separated by 10–60 bp of ‘linker’ DNA, and the resulting nucleosomal array constitutes a chromatin fiber of ~10 nm in diameter. This simple ‘beads-ona-string’ arrangement is folded into more condensed, ~30 nm thick fibers that are stabilized by binding of a linker histone to each nucleosome core (note that linker histones are not related in sequence to the core histones). Such 30 nm fibers are then further condensed in vivo to form 100–400 nm thick interphase fibers or the more highly compacted metaphase chromosome structures. This organization of DNA into chromatin fibers hinders its accessibility to proteins that must ‘read’ and/or copy the nucleotide base sequence, and consequently such structures must be dynamic and capable of regulated unfolding–folding transitions. Each of the core histones has a related globular domain that mediates histone–histone interactions within the octamer, and that organizes the two wraps of nucleosomal DNA. Each histone also harbors an aminoterminal 20–35 residue segment that is rich in basic amino acids and extends from the surface of the nucleosome; histone H2A is unique in having an additional ~37 amino acid carboxy-terminal domain that protrudes from the nucleosome. These histone ‘tails’ do not contribute significantly to the structure of individual nucleosomes nor to their stability, but they do play an essential role in controlling the folding of nucleosomal arrays into higherorder structures. Indeed, in vitro removal of the histone tails results in nucleosomal arrays that cannot condense past the beads-on-astring 10 nm fiber. Although the highly basic histone tails are generally viewed as DNA-binding modules, their essential roles in tail-mediated chromatin folding also involve inter-nucleosomal histone–histone interactions.
An operational semantics for Stateflow

We present a formal operational semantics for Stateflow, the graphical Statecharts-like language of the Matlab/Simulink tool suite that is widely used in model-based development of embedded systems. Stateflow has many tricky features but our operational treatment yields a surprisingly simple semantics for the subset that is generally recommended for industrial applications. We have validated our semantics by developing an interpreter that allows us to compare its behavior against the Matlab simulator. We have used the semantics as a foundation for developing prototype tools for formal analysis of Stateflow designs.
Human Semantic Parsing for Person Re-identification

Person re-identification is a challenging task mainly due to factors such as background clutter, pose, illumination and camera point of view variations. These elements hinder the process of extracting robust and discriminative representations, hence preventing different identities from being successfully distinguished. To improve the representation learning, usually local features from human body parts are extracted. However, the common practice for such a process has been based on bounding box part detection. In this paper, we propose to adopt human semantic parsing which, due to its pixel-level accuracy and capability of modeling arbitrary contours, is naturally a better alternative. Our proposed SPReID integrates human semantic parsing in person re-identification and not only considerably outperforms its counter baseline, but achieves state-of-the-art performance. We also show that, by employing a simple yet effective training strategy, standard popular deep convolutional architectures such as Inception-V3 and ResNet-152, with no modification, while operating solely on full image, can dramatically outperform current state-of-the-art. Our proposed methods improve state-of-the-art person re-identification on: Market-1501 [48] by ~17% in mAP and ~6% in rank-1, CUHK03 [24] by ~4% in rank-1 and DukeMTMC-reID [50] by ~24% in mAP and ~10% in rank-1.
Dynamic objects detection through visual odometry and stereo-vision: a study of inaccuracy and improvement sources

Road safety, whatever the considered environment, relies heavily on the ability to detect and track moving objects from a moving point of view. In order to achieve such a detection, the vehicle’s ego-motion must first be estimated and compensated. This issue is crucial to complete a fully autonomous vehicle; this is why several approaches have already been proposed. This study presents a method, based solely on visual information that implements such a process. Information from stereo-vision and motion is derived to extract the vehicle’s ego-motion. Ego-motion extraction algorithm is thoroughly evaluated in terms of precision and uncertainty. Given those statistical attributes, a method for dynamic objects detection is presented. This method relies on 3D image registration and residual displacement field evaluation. This method is then evaluated on several real and synthetic data sequences. It will be shown that it allows a reliable and early detection, even in hard cases (e.g. occlusions,...). Given a few additional factors (detectable motion range), overall performances can be derived from visual odometry performances.
Moving in a Moving World: A Review on Vestibular Motion Sickness

Motion sickness is a common disturbance occurring in healthy people as a physiological response to exposure to motion stimuli that are unexpected on the basis of previous experience. The motion can be either real, and therefore perceived by the vestibular system, or illusory, as in the case of visual illusion. A multitude of studies has been performed in the last decades, substantiating different nauseogenic stimuli, studying their specific characteristics, proposing unifying theories, and testing possible countermeasures. Several reviews focused on one of these aspects; however, the link between specific nauseogenic stimuli and the unifying theories and models is often not clearly detailed. Readers unfamiliar with the topic, but studying a condition that may involve motion sickness, can therefore have difficulties to understand why a specific stimulus will induce motion sickness. So far, this general audience struggles to take advantage of the solid basis provided by existing theories and models. This review focuses on vestibular-only motion sickness, listing the relevant motion stimuli, clarifying the sensory signals involved, and framing them in the context of the current theories.
Pair-Matching Method for Estimating 2-D Angle of Arrival With a Cross-Correlation Matrix

This letter presents a novel method for pair matching of elevation and azimuth angles in two-dimensional (2-D) angles-of-arrival estimation employing two uniform linear arrays (ULAs). The proposed pair-matching method exploits the cross-correlation matrix of two received signals impinging on each ULA that shows the characteristics of the corresponding angle pairs, and is conducted by combining it with a propagator method. Numerical simulations using L-shaped array geometry revealed that the proposed method provided better robustness over the SNR, angular separation, and number of sources than that of conventional methods.
Applying Real-Time Scheduling Theory to the Synchronous Data Flow Model of Computation

Schedulability analysis techniques that are well understood within the real-time scheduling community are applied to the analysis of recurrent real-time workloads that are modeled using the synchronous data-flow graph (SDFG) model. An enhancement to the standard SDFG model is proposed, that permits the specification of a real-time latency constraint between a specified input and a specified output of an SDFG. A technique is derived for transforming such an enhanced SDFG to a collection of traditional 3-parameter sporadic tasks, thereby allowing for the analysis of systems of SDFG tasks using the methods and algorithms that have previously been developed within the real-time scheduling community for the analysis of systems of such sporadic tasks. The applicability of this approach is illustrated by applying prior results from real-time scheduling theory to construct an exact preemptive uniprocessor schedulability test for collections of recurrent processes that are each represented using the enhanced SDFG model.
Tree2Tree Neural Translation Model for Learning Source Code Changes

The way developers edit day-to-day code tend to be repetitive and often use existing code elements. Many researchers tried to automate this tedious task of code changes by learning from specific change templates and applied to limited scope. The advancement of Neural Machine Translation (NMT) and the availability of the vast open source software evolutionary data open up a new possibility of automatically learning those templates from the wild. However, unlike natural languages, for which NMT techniques were originally designed, source code and the changes have certain properties. For instance, compared to natural language source code vocabulary can be virtually infinite. Further, any good change in code should not break its syntactic structure. Thus, deploying state-of-the-art NMT models without domain adaptation may poorly serve the purpose. To this end, in this work, we propose a novel Tree2Tree Neural Machine Translation system to model source code changes and learn code change patterns from the wild. We realize our model with a change suggestion engine: CODIT. We train the model with more than 30k real-world changes and evaluate it with 6k patches. Our evaluation shows the effectiveness of CODIT in learning and suggesting abstract change templates. CODIT also shows promise in suggesting concrete patches and generating bug fixes.
Completeness Theorems for Syllogistic Fragments

Traditional syllogisms involve sentences of the following simple forms: All X are Y , Some X are Y , No X are Y ; similar sentences with proper names as subjects, and identities between names. These sentences come with the natural semantics using subsets of a given universe, and so it is natural to ask about complete proof systems. Logical systems are important in this area due to the prominence of syllogistic arguments in human reasoning, and also to the role they have played in logic from Aristotle onwards. We present complete systems for the entire syllogistic fragment and many sub-fragments. These begin with the fragment of All sentences, for which we obtain one of the easiest completeness theorems in logic. The last system extends syllogistic reasoning with the classical boolean operations and cardinality comparisons.
Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference

belief-network inference Adnan Darwiche and Gregory Provan Rockwell Science Center 1049 Camino Dos Rios Thousand Oaks, CA 91360 fdarwiche, provang@risc.rockwell.com Abstract We describe a new paradigm for implementing inference in belief networks, which consists of two steps: (1) compiling a belief network into an arithmetic expression called a Query DAG (Q-DAG); and (2) answering queries using a simple evaluation algorithm. Each non-leaf node of a Q-DAG represents a numeric operation, a number, or a symbol for evidence. Each leaf node of a Q-DAG represents the answer to a network query, that is, the probability of some event of interest. It appears that Q-DAGs can be generated using any of the standard algorithms for exact inference in belief networks | we show how they can be generated using the clustering algorithm. The time and space complexity of a Q-DAG generation algorithm is no worse than the time complexity of the inference algorithm on which it is based. The complexity of a Q-DAG evaluation algorithm is linear in the size of the Q-DAG, and such inference amounts to a standard evaluation of the arithmetic expression it represents. The main value of Q-DAGs is in reducing the software and hardware resources required to utilize belief networks in on-line, real-world applications. The proposed framework also facilitates the development of on-line inference on di erent software and hardware platforms due to the simplicity of the Q-DAG evaluation algorithm.