nils-herrmann/clean_scirepeval huggingface dataset:
Correspondence-free pose estimation for 3D objects from noisy depth data

Estimating the pose of objects from depth data is a problem of considerable practical importance for many vision applications. This paper presents an approach for accurate and efficient 3D pose estimation from noisy 2.5D depth images obtained from a consumer depth sensor. Initialized with a coarsely accurate pose, the proposed approach applies a hypothesize-and-test scheme that combines stochastic optimization and graphics-based rendering to refine the supplied initial pose, so that it accurately accounts for a sensed depth image. Pose refinement employs particle swarm optimization to minimize an objective function that quantifies the misalignment between the acquired depth image and a rendered one that is synthesized from a hypothesized pose with the aid of an object mesh model. No explicit correspondences between the depth data and the model need to be established, whereas pose hypothesis rendering and objective function evaluation are efficiently performed on the GPU. Extensive experimental results demonstrate the superior performance of the proposed approach compared to the ICP algorithm, which is typically used for pose refinement in depth images. Furthermore, the experiments indicate the graceful degradation of its performance to limited computational resources and its robustness to noisy and reduced polygon count models, attesting its suitability for use with automatically scanned object models and common graphics hardware.
Infants’ Metaphysics: The Case of Numerical Identity

Adults conceptualize the world in terms of enduring physical objects. Sortal concepts provide conditions of individuation (establishing the boundaries of objects) and numerical identity (establishing whether an object is the same one as one encountered at some other time). In the adult conceptual system, there are two roughly hierarchical levels of object sortals. Most general is the sortal bounded physical object itself, for which spatiotemporal properties provide the criteria for individuation and identity. More specific sortals, such as dog or car, rely on additional types of properties to provide criteria for individuation and identity. We conjecture that young infants might represent only the general sortal, object, and construct more specific sortals later (the Object-first Hypothesis). This is closely related to Bower's (1974) conjecture that infants use spatiotemporal information to trace identity before they use property information. Five studies using the visual habituation paradigm were conducted to address the Object-first Hypothesis. In these studies, 10-month-old infants were able to use spatiotemporal information but failed to use property/kind information to set up representations of numerically distinct individuals, thus providing empirical evidence for the Object-first Hypothesis. Finally, infants succeed at object individuation in terms of more specific sortals by 12 months. The relation between success at our task and early noun comprehension is discussed.
Understanding Continuance Intention of Blog Users: A Perspective of Flow and Expectation Confirmation Theory

Blogs are currently very popular. Many website portals, such as Yahoo Blog, PChome Blog, and Sina, offer different functions and personal services to attract potential blog users, as this generates greater advertising income. Ensuring that users continue to use blog is important to the survival of these portals. Previous articles investigate the system functions and information quality of blogs, but these technologies are already mature. Relatively few studies discuss the flow experience of using blogs. This study investigates whether the users’ flow experience affects their satisfaction with, and intention to continue using, blogs. This study surveys 303 bloggers online. Research findings indicate that confirmation, perceived usefulness, flow, challenge, and arousal positively affected bloggers’ satisfaction with using blogs; perceived usefulness, satisfaction, and flow also positively influenced bloggers’ intentions to continue using blogs. In addition, the findings point out that the higher satisfaction users have, the more are continuance intention users get. This study provides recommendations on how service providers can increase blogger continuance intentions.
Markov Logic Networks for Natural Language Question Answering

Our goal is to answer elementary-level science questions using knowledge extracted automatically from science textbooks, expressed in a subset of first-order logic. Given the incomplete and noisy nature of these automatically extracted rules, Markov Logic Networks (MLNs) seem a natural model to use, but the exact way of leveraging MLNs is by no means obvious. We investigate three ways of applying MLNs to our task. In the first, we simply use the extracted science rules directly as MLN clauses. Unlike typical MLN applications, our domain has long and complex rules, leading to an unmanageable number of groundings. We exploit the structure present in hard constraints to improve tractability, but the formulation remains ineffective. In the second approach, we instead interpret science rules as describing prototypical entities, thus mapping rules directly to grounded MLN assertions, whose constants are then clustered using existing entity resolution methods. This drastically simplifies the network, but still suffers from brittleness. Finally, our third approach, called Praline, uses MLNs to align the lexical elements as well as define and control how inference should be performed in this task. Our experiments, demonstrating a 15% accuracy boost and a 10x reduction in runtime, suggest that the flexibility and different inference semantics of Praline are a better fit for the natural language question answering task.
Artificial neural networks applied to forecasting time series.

This study offers a description and comparison of the main models of Artificial Neural Networks (ANN) which have proved to be useful in time series forecasting, and also a standard procedure for the practical application of ANN in this type of task. The Multilayer Perceptron (MLP), Radial Base Function (RBF), Generalized Regression Neural Network (GRNN), and Recurrent Neural Network (RNN) models are analyzed. With this aim in mind, we use a time series made up of 244 time points. A comparative study establishes that the error made by the four neural network models analyzed is less than 10%. In accordance with the interpretation criteria of this performance, it can be concluded that the neural network models show a close fit regarding their forecasting capacity. The model with the best performance is the RBF, followed by the RNN and MLP. The GRNN model is the one with the worst performance. Finally, we analyze the advantages and limitations of ANN, the possible solutions to these limitations, and provide an orientation towards future research.
Using Multi-Locators to Increase the Robustness of Web Test Cases

The main reason for the fragility of web test cases is the inability of web element locators to work correctly when the web page DOM evolves. Web elements locators are used in web test cases to identify all the GUI objects to operate upon and eventually to retrieve web page content that is compared against some oracle in order to decide whether the test case has passed or not. Hence, web element locators play an extremely important role in web testing and when a web element locator gets broken developers have to spend substantial time and effort to repair it. While algorithms exist to produce robust web element locators to be used in web test scripts, no algorithm is perfect and different algorithms are exposed to different fragilities when the software evolves. Based on such observation, we propose a new type of locator, named multi-locator, which selects the best locator among a candidate set of locators produced by different algorithms. Such selection is based on a voting procedure that assigns different voting weights to different locator generation algorithms. Experimental results obtained on six web applications, for which a subsequent release was available, show that the multi-locator is more robust than the single locators (about -30% of broken locators w.r.t. the most robust kind of single locator) and that the execution overhead required by the multiple queries done with different locators is negligible (2-3% at most).
Introduction to the CoNLL-2000 Shared Task Chunking

We describe the CoNLL-2000 shared task: dividing text into syntactically related nonoverlapping groups of words, so-called text chunking. We give background information on the data sets, present a general overview of the systems that have taken part in the shared task and briefly discuss their performance. 1 I n t r o d u c t i o n Text chunking is a useful preprocessing step for parsing. There has been a large interest in recognizing non-overlapping noun phrases (Ramshaw and Marcus (1995) and follow-up papers) but relatively little has been written about identifying phrases of other syntactic categories. The CoNLL-2000 shared task at tempts to fill this gap. 2 T a s k d e s c r i p t i o n Text chunking consists of dividing a text into phrases in such a way that syntactically related words become member of the same phrase. These phrases are non-overlapping which means that one word can only be a member of one chunk. Here is an example sentence: [NP He ] [vP reckons ] [NP the current account deficit ] [vP will narrow ] NP only £ 1.8 billion ] [pp in ][NP September ] . Chunks have been represented as groups of words between square brackets. A tag next to the open bracket denotes the type of the chunk. As far as we know, there are no annotated corpora available which contain specific information about dividing sentences into chunks of words of arbitrary types. We have chosen to work with a corpus with parse information, the Wall Street Journal WSJ part of the Penn Treebank II corpus (Marcus et al., 1993), and to extract chunk information from the parse trees in this corpus. We will give a global description of the various chunk types in the next section.
Narrow Band FLIP for Liquid Simulations

The Fluid Implicit Particle method (FLIP) for liquid simulations uses particles to reduce numerical dissipation and provide important visual cues for events like complex splashes and small-scale features near the liquid surface. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume. Furthermore, the vast majority of these FLIP particles contribute nothing to the fluid’s visual appearance, especially for larger volumes of liquid. We present a method that only uses FLIP particles within a narrow band of the liquid surface, while efficiently representing the remaining inner volume on a regular grid. We show that a naïve realization of this idea introduces unstable and uncontrollable energy fluctuations, and we propose a novel coupling scheme between FLIP particles and regular grid which overcomes this problem. Our method drastically reduces the particle count and simulation times while yielding results that are nearly indistinguishable from regular FLIP simulations. Our approach is easy to integrate into any existing FLIP implementation.
Microcomputer Control for Sensorless Brushless Motor

The microcomputer control of a brushless motor without a shaft position sensor is studied. A method which permits the determination of the permanent magnet rotor position by the back electromotive force (EMF) induced in the stator windings and the starting technique which uses the motor as a synchronous motor at standstill are explained. The motor voltage is chopped by commutator transistors to change the motor speed. The control system consists of a 4-b single-chip microcomputer and two quad-comparators.
FloDB: Unlocking Memory in Persistent Key-Value Stores

Log-structured merge (LSM) data stores enable to store and process large volumes of data while maintaining good performance. They mitigate the I/O bottleneck by absorbing updates in a memory layer and transferring them to the disk layer in sequential batches. Yet, the LSM architecture fundamentally requires elements to be in sorted order. As the amount of data in memory grows, maintaining this sorted order becomes increasingly costly. Contrary to intuition, existing LSM systems could actually lose throughput with larger memory components.
 In this paper, we introduce FloDB, an LSM memory component architecture which allows throughput to scale on modern multicore machines with ample memory sizes. The main idea underlying FloDB is essentially to bootstrap the traditional LSM architecture by adding a small in-memory buffer layer on top of the memory component. This buffer offers low-latency operations, masking the write latency of the sorted memory component. Integrating this buffer in the classic LSM memory component to obtain FloDB is not trivial and requires revisiting the algorithms of the user-facing LSM operations (search, update, scan). FloDB's two layers can be implemented with state-of-the-art, highly-concurrent data structures. This way, as we show in the paper, FloDB eliminates significant synchronization bottlenecks in classic LSM designs, while offering a rich LSM API.
 We implement FloDB as an extension of LevelDB, Google's popular LSM key-value store. We compare FloDB's performance to that of state-of-the-art LSMs. In short, FloDB's performance is up to one order of magnitude higher than that of the next best-performing competitor in a wide range of multi-threaded workloads.
Extending the Definitions of Antenna Gain and Radiation Pattern into the Time Domain

Many of the classical parameters of frequency domain (CW) antennas, such as gain and radiation pattern, are defined only in the frequency domain, and currently have no meaning in the time domain. The purpose of this note is to extend their definitions into the time domain. We develop here the concept of waveform norms as a mechanism for comparing the radiated field to the driving voltage. The concept of gain that we develop then compares a norm of the radiated field to a norm of the derivative of the driving voltage. The transient gain is therefore a function of both the choice of norm, and of the choice of driving waveform. A key feature of our definitions of gain and pnttcrn factor is that they arc equivalent in both transmit and receive modes. .
A Systematic Review of Virtual Reality in Education.

Virtual reality has existed in the realm of education for over half a century. However, its widespread adoption is still yet to occur. This is a result of a myriad of limitations to both the technologies themselves, and the costs and logistics required to deploy them. In order to gain a better understanding of what these issues are, and what it is that educators hope to gain by using these technologies in the first place, we have performed both a systematic review of the use of virtual reality in education, as well as two distinct thematic analyses. The first analysis investigated the applications and reported motivations provided by educators in academic literature for developing virtual reality educational systems, while the second investigated the reported problems associated with doing so. These analyses indicate that the majority of researchers use virtual reality to increase the intrinsic motivation of students, and refer to a narrow range of factors such as constructivist pedagogy, collaboration, and gamification in the design of their experiences. Similarly, a small number of educational areas account for the vast majority of educational virtual reality implementations identified in our analyses. Next, we introduced and compared a multitude of recent virtual reality technologies, discussing their potential to overcome several of the problems identified in our analyses, including cost, user experience and interactivity. However, these technologies are not without their own issues, thus we conclude this paper by providing several novel techniques to potentially address them, as well as potential directions for future researchers wishing to apply these emerging technologies to education.
Analysis and design of asymmetrical ZVS PWM half bridge forward converter with flyback type transformer

A new asymmetrical zero-voltage switching (ZVS) pulse width modulation (PWM) half bridge forward converter with flyback type transformer is proposed. The ZVS operation of proposed converter can be maintained from no load to full load condition since the magnetizing current of the transformer contributes to the ZVS operation at the light load without a considerable conduction loss of the transformer and switch. The synchronous rectification is employed to reduce the rectification loss. The operational principle, large signal modeling, ZVS analysis, and design equations are presented. Experimental results demonstrate that the proposed converter can achieve a large ZVS range and significant improvement in the efficiency for a 100 W (5 V, 20 A) prototype converter.
Skin force sensor using piezoresistive PEDOT:PSS with arabitol on flexible PDMS

In this paper, a flexible conducting polymer based force sensor array has been developed. A conducting polymer, namely poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) with additive arabitol, was utilized as the piezoresistive layer on a flexible polydimethylsiloxane (PDMS) substrate owing to its high conductivity and stretchability. A simplified strain sensor has been developed to demonstrate the properties of the arabitol-PEDOT:PSS. Suitable curing conditions and arabitol concentration have been established with design of experiment. The arabitol-PEDOT:PSS can be stretched up to 20% and it shows a significant gauge factor of 11.5. A flexible interdigital force sensor array has been developed to demonstrate the effectiveness of arabitol-PEDOT:PSS on PDMS as a force sensor.
Rates of Phenotypic and Genomic Evolution during the Cambrian Explosion

The near-simultaneous appearance of most modern animal body plans (phyla) ~530 million years ago during the Cambrian explosion is strong evidence for a brief interval of rapid phenotypic and genetic innovation, yet the exact speed and nature of this grand adaptive radiation remain debated. Crucially, rates of morphological evolution in the past (i.e., in ancestral lineages) can be inferred from phenotypic differences among living organisms-just as molecular evolutionary rates in ancestral lineages can be inferred from genetic divergences. We here employed Bayesian and maximum likelihood phylogenetic clock methods on an extensive anatomical and genomic data set for arthropods, the most diverse phylum in the Cambrian and today. Assuming an Ediacaran origin for arthropods, phenotypic evolution was ~4 times faster, and molecular evolution ~5.5 times faster, during the Cambrian explosion compared to all subsequent parts of the Phanerozoic. These rapid evolutionary rates are robust to assumptions about the precise age of arthropods. Surprisingly, these fast early rates do not change substantially even if the radiation of arthropods is compressed entirely into the Cambrian (~542 mega-annum [Ma]) or telescoped into the Cryogenian (~650 Ma). The fastest inferred rates are still consistent with evolution by natural selection and with data from living organisms, potentially resolving "Darwin's dilemma." However, evolution during the Cambrian explosion was unusual (compared to the subsequent Phanerozoic) in that fast rates were present across many lineages.
Irregularities in the Distribution of Primes and Twin Primes By

The maxima and minima of sL(x)) — n(x), iR(x)) — n(x), and sL2(x)) — n2(x) in various intervals up to x = 8 x 10 are tabulated. Here n(x) and n2(x) are respectively the number of primes and twin primes not exceeding x, L(x) is the logarithmic integral, R(x) is Riemann's approximation to ir(x), and L2(x) is the Hardy-Littlewood approximation to ti"2(;c). The computation of the sum of inverses of twin primes less than 8 x 10 gives a probable value 1.9021604 ± 5 x 10~7 for Brun's constant. 1. Approximations to nix). Let P= {2, 3, 5, • • • } be the set of primes, and let 7r(x) be the number of primes not exceeding x. Two well-known approximations to 7t(x) for x > 1 are the logarithmic integral: rx dt (1.1) L{x) = \v ; J o log t O-2) =T + log(logx)+Í: ^> k=\ k-k and Riemann's approximation: (1.3) R{x)=Z^L{xi'k) k=i k (1.4) =1 + ¿Jtó_ fz. k\kl{k + 1) Note that (1.1) differs by 1(2) = 1.04516378... from the frequently used approximation f2 dt/log t. We are interested in the errors O-5) r.{x) = (L(x)> n{x) and (1 6) r2(x) = (Rix)) n{x), where <y> denotes the integer closest to y {i.e., the integer part of (y + W)). k Received July 5, 1974. AMS (MOS) subject classifications (1970).  10H25, 10H15; Secondary 10A25, 10A40, 10H05, 65A05, 65B05.
Efficient Autoscaling in the Cloud Using Predictive Models for Workload Forecasting

Large-scale component-based enterprise applications that leverage Cloud resources expect Quality of Service(QoS) guarantees in accordance with service level agreements between the customer and service providers. In the context of Cloud computing, auto scaling mechanisms hold the promise of assuring QoS properties to the applications while simultaneously making efficient use of resources and keeping operational costs low for the service providers. Despite the perceived advantages of auto scaling, realizing the full potential of auto scaling is hard due to multiple challenges stemming from the need to precisely estimate resource usage in the face of significant variability in client workload patterns. This paper makes three contributions to overcome the general lack of effective techniques for workload forecasting and optimal resource allocation. First, it discusses the challenges involved in auto scaling in the cloud. Second, it develops a model-predictive algorithm for workload forecasting that is used for resource auto scaling. Finally, empirical results are provided that demonstrate that resources can be allocated and deal located by our algorithm in a way that satisfies both the application QoS while keeping operational costs low.
Near-optimal hybrid analog and digital precoding for downlink mmWave massive MIMO systems

Millimeter wave (mmWave) massive MIMO can achieve orders of magnitude increase in spectral and energy efficiency, and it usually exploits the hybrid analog and digital precoding to overcome the serious signal attenuation induced by mmWave frequencies. However, most of hybrid precoding schemes focus on the full-array structure, which involves a high complexity. In this paper, we propose a near-optimal iterative hybrid precoding scheme based on the more realistic subarray structure with low complexity. We first decompose the complicated capacity optimization problem into a series of ones easier to be handled by considering each antenna array one by one. Then we optimize the achievable capacity of each antenna array from the first one to the last one by utilizing the idea of successive interference cancelation (SIC), which is realized in an iterative procedure that is easy to be parallelized. It is shown that the proposed hybrid precoding scheme can achieve better performance than other recently proposed hybrid precoding schemes, while it also enjoys an acceptable computational complexity.