nils-herrmann/clean_scirepeval huggingface dataset:
Recent and robust query auto-completion

Query auto-completion (QAC) is a common interactive feature that assists users in formulating queries by providing completion suggestions as they type. In order for QAC to minimise the user's cognitive and physical effort, it must: (i) suggest the user's intended query after minimal input keystrokes, and (ii) rank the user's intended query highly in completion suggestions. Typically, QAC approaches rank completion suggestions by their past popularity. Accordingly, QAC is usually very effective for previously seen and consistently popular queries. Users are increasingly turning to search engines to find out about unpredictable emerging and ongoing events and phenomena, often using previously unseen or unpopular queries. Consequently, QAC must be both robust and time-sensitive -- that is, able to sufficiently rank both consistently and recently popular queries in completion suggestions. To address this trade-off, we propose several practical completion suggestion ranking approaches, including: (i) a sliding window of query popularity evidence from the past 2-28 days, (ii) the query popularity distribution in the last N queries observed with a given prefix, and (iii) short-range query popularity prediction based on recently observed trends. Using real-time simulation experiments, we extensively investigated the parameters necessary to maximise QAC effectiveness for three openly available query log datasets with prefixes of 2-5 characters: MSN and AOL (both English), and Sogou 2008 (Chinese). Optimal parameters vary for each query log, capturing the differing temporal dynamics and querying distributions. Results demonstrate consistent and language-independent improvements of up to 9.2% over a non-temporal QAC baseline for all query logs with prefix lengths of 2-3 characters. This work is an important step towards more effective QAC approaches.
One-Shot Segmentation in Clutter

We tackle the problem of one-shot segmentation: finding and segmenting a previously unseen object in a cluttered scene based on a single instruction example. We propose a novel dataset, which we call cluttered Omniglot. Using a baseline architecture combining a Siamese embedding for detection with a U-net for segmentation we show that increasing levels of clutter make the task progressively harder. Using oracle models with access to various amounts of ground-truth information, we evaluate different aspects of the problem and show that in this kind of visual search task, detection and segmentation are two intertwined problems, the solution to each of which helps solving the other. We therefore introduce MaskNet, an improved model that attends to multiple candidate locations, generates segmentation proposals to mask out background clutter and selects among the segmented objects. Our findings suggest that such image recognition models based on an iterative refinement of object detection and foreground segmentation may provide a way to deal with highly cluttered scenes.
Effects of elastic therapeutic taping on motor function in children with motor impairments: a systematic review.

The elastic therapeutic taping has been considered a promising resource for disabled children.



To systematically review the evidence of the effects of elastic therapeutic taping on motor function in children with motor impairments.



Three independent evaluators conducted searches in electronic databases (MEDLINE/PubMed, Scopus, LILACS, BIREME/BVS, Science Direct, SciELO, and PEDro). Clinical studies design, published until 2016, involving elastic therapeutic taping and children aged 0-12 years with motor impairments were included. The variables considered were the methodological aspects (study design, participants, outcome measurements, and experimental conditions); results presented in the studies, and also the methodological quality of studies.



Final selection was composed by 12 manuscripts (five randomized controlled trials), published in the last 10 years. Among them, cerebral palsy (CP) was the most recurrent disorder (n = 7), followed by congenital muscular torticollis (n = 2) and brachial plexus palsy (n = 2). Positive results were associated with taping application: improvement in the upper limb function, gross motor skills, postural control, muscular balance, and performance in the dynamics functional and daily activities.



Lower quality of the studies, clinical and population heterogeneity existed across studies.



The elastic therapeutic taping has been shown to be a promising adjunct resource to the conventional rehabilitation in children with motor impairments. However, high methodological studies about its efficacy in this population are already scarce. Implications for Rehabilitation Elastic therapeutic taping has been shown to be a promising adjunct resource to the conventional rehabilitation in disabled children. Clinical trials have indicated improvement in the postural control and functional activities with both, upper and lower limbs, and increase in the functional independency resulting from the taping use. Randomized control trials and well-established protocols are needed to increase the confidence in applying elastic therapeutic taping to specific clinical conditions.
MODEL AS A DESCRIPTIVE TOOL IN EVALUATING A VIRTUAL LEARNING ENVIRONMENT

This paper contributes the discussion about applying DeLone & McLean success model. Since its introduction in 1992, the model has been widely used and evaluated. In this paper the model is used as a descriptive tool in evaluating a virtual learning environment. The study relies on prior research and does not question the measures. Instead, the model contributes the evaluation and describes the virtual environment. Contrary to earlier use of the success model in virtual learning systems, this study focuses on degree-level studies. The paper shows that the model can be used as a descriptive tool because the six dimensions offer possibilities to explore and describe the environment from several approaches.
The human brain is intrinsically organized into dynamic, anticorrelated functional networks.

During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.
Time scales in motor learning and development.

A theoretical framework based on the concepts and tools of nonlinear dynamical systems is advanced to account for both the persistent and transitory changes traditionally shown for the learning and development of motor skills. The multiple time scales of change in task outcome over time are interpreted as originating from the system's trajectory on an evolving attractor landscape. Different bifurcations between attractor organizations and transient phenomena can lead to exponential, power law, or S-shaped learning curves. This unified dynamical account of the functions and time scales in motor learning and development offers several new hypotheses for future research on the nature of change in learning theory.
Spare register aware prefetching for graph algorithms on GPUs

More and more graph algorithms are being GPU enabled. Graph algorithm implementations on GPUs have irregular control flow and are memory-intensive with many irregular/data-dependent memory accesses. Due to these factors graph algorithms on GPUs have low execution efficiency. In this work we propose a mechanism to improve the execution efficiency of graph algorithms by improving their memory access latency tolerance. We propose a mechanism for prefetching data for load pairs that have one load dependent on the other - such pairs are common in graph algorithms. Our mechanism detects the target loads in hardware and injects instructions into the pipeline to prefetch data into spare registers that are not being used by any active threads. By prefetching data into registers, early eviction of prefetched data can be eliminated. We also propose a mechanism that uses the compiler to identify the target loads. Our mechanism improves performance over no prefetching by 10% on average and upto 51% for nine memory intensive graph algorithm kernels.
Wanted: Collaborative intelligence

a r t i c l e i n f o a b s t r a c t Although the original vision for artificial intelligence was the simulation of (implicitly human) intelligence, research has gradually shifted to autonomous systems that compete with people. The resultant popular attitude toward artificial intelligence, we argue here, is by turns disdain, grudging acceptance, and fear. That attitude not only limits our work's potential, but also imperils its support. This paper proposes a constructive alternative: the development of collaborative intelligence. As envisioned here, a collaborative intelligence does not require encyclopedic command and need not be limited to a single problem. The necessary components of a collaborative intelligence are nearly at hand, and the key issues readily identified. As a first step, this paper proposes three challenging but accessible problems that would both change the public perception of artificial intelligence and spur substantive research to advance our science.
Turing Test: 50 Years Later

The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the `other minds' problem, and similar topics in philosophy of mind are discussed. We also cover the sociological and psychological aspects of the Turing Test. Finally, we look at the current situation and analyze programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an influential and controversial topic.
Influence of automobile seat lumbar support prominence on spine and pelvic postures: a radiological investigation.

The use of lumbar supports has been associated with decreased reports of low back pain during driving exposures. However, there has been limited work investigating whether lumbar supports actually change spine and pelvic postures at the level of the vertebrae.



To investigate the effectiveness of a lumbar support in changing radiological measures of lumbar spine and pelvic postures and to examine the impact of support excursion magnitudes on these postures.



Eight male subjects were recruited with no history of back injury, pathologies or low back pain within the past 6 months. Radiographs were taken in four postures: standing, and sitting with 0 cm, 2 cm and 4 cm lumbar support prominence (LSP).



Lumbar lordosis angle increased from 20° with no support to 25° with 2 cm support and 30° with 4 cm support. Lumbar lordosis angles were significantly different between 0 cm support and 4 cm support (p < 0.0001) and between 2 cm support and 4 cm support (p = 0.0256). Increasing lumbar support reduced the flexion at intervertebral disc joints throughout the lumbar spine, however, these remained significantly different from upright standing (p > 0.001) with the exception of L1/L2 in 4 cm support (p = 0.1381) and L5/S1 for all seated postures (p = 0.0687). All measures of pelvic posture were significantly different in sitting compared to standing (p < 0.0001), however, the lumbar support had no significant impact on seated pelvic posture.



Lumbar supports were shown to impact the vertebral rotations of the lumbar spine yet had no effect on pelvis postures. Increasing support from the current maximum of 2 cm-4 cm resulted in increased lumbar lordosis. The changes were mostly imparted at the upper lumbar spine joints with the most marked change being exhibited at the approximate level of the lumbar support apex: in the L2/L3 joint.
Scribbles to Vectors: Preparation of Scribble Drawings for CAD Interpretation

This paper describes the work carried out on off-line paper based scribbles such that they can be incorporated into a sketch-based interface without forcing designers to change their natural drawing habits. In this work, the scribbled drawings are converted into a vectorial format which can be recognized by a CAD system. This is achieved by using pattern analysis techniques, namely the Gabor filter to simplify the scribbled drawing. Vector line are then extracted from the resulting drawing by means of Kalman filtering.
Capacity of Wireless Multi-hop Networks Using Physical Carrier Sense and Transmit Power Control

In this paper, we investigate the capacity of CSMA (Carrier Sense Multiple Access) based wireless multi-hop networks with random topologies described by the hop length distribution. First we develop an analytical model for the effective link capacity as a function of transmit power adaptation policy, physical carrier sense threshold, hop length distribution and medium access probability of p−persistent CSMA. Secondly, we devise an optimal transmit power control scheme that maximizes the network capacity by adjusting the transmit power and the corresponding physical carrier sense threshold. Thereafter, it is extended for the joint optimization of these parameters with the medium access probability of CSMA. Finally we compare the optimal power control scheme with the minimum transmit power policy in . Results show that the proposed power control scheme optimally trades off the spatial reuse (number of interfering links) to the link SIR (Signal-to-Interference Ratio) and achieves an amount of ∼%15 increase in network capacity when both schemes employ joint optimization.
A theorem on polygon cutting with applications

Let P be a simple polygon with N vertices, each being assigned a weight ∈ {0,1}, and let C, the weight of P, be the added weight of all vertices. We prove that it is possible, in O(N) time, to find two vertices a,b in P, such that the segment ab lies entirely inside the polygon P and partitions it into two polygons, each with a weight not exceeding 2C/3. This computation assumes that all the vertices have been sorted along some axis, which can be done in O(Nlog N) time. We use this result to derive a number of efficient divide-and-conquer algorithms for: 1. Triangulating an N-gon in O(Nlog N) time. 2. Decomposing an N-gon into (few) convex pieces in O(Nlog N) time. 3. Given an O(Nlog N) preprocessing, computing the shortest distance between two arbitrary points inside an N-gon (i.e., the internal distance), in O(N) time. 4. Computing the longest internal path in an N-gon in O(N2) time. In all cases, the algorithms achieve significant improvements over previously known methods, either by displaying better performance or by gaining in simplicity. In particular, the best algorithms for Problems 2,3,4, known so far, performed respectively in O(N2), O(N2), and O(N4) time.
An architecture for the aggregation and analysis of scholarly usage data

Although recording of usage data is common in scholarly information services, its exploitation for the creation of value-added services remains limited due to concerns regarding, among others, user privacy, data validity, and the lack of accepted standards for the representation, sharing and aggregation of usage data. This paper presents a technical, standards-based architecture for sharing usage information, which we have designed and implemented. In this architecture, OpenURL-compliant linking servers aggregate usage information of a specific user community as it navigates the distributed information environment that it has access to. This usage information is made OAI-PMH harvestable so that usage information exposed by many linking servers can be aggregated to facilitate the creation of value-added services with a reach beyond that of a single community or a single information service. This paper also discusses issues that were encountered when implementing the proposed approach, and it presents preliminary results obtained from analyzing a usage data set containing about 3,500,000 requests aggregated by a federation of linking servers at the California State University system over a 20 month period.
A Survey of Denial-of-Service and Distributed Denial of Service Attacks and Defenses in Cloud Computing

Cloud Computing is a computing model that allows ubiquitous, convenient and on-demand access to a shared pool of highly configurable resources (e.g., networks, servers, storage, applications and services). Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks are serious threats to the Cloud services’ availability due to numerous new vulnerabilities introduced by the nature of the Cloud, such as multi-tenancy and resource sharing. In this paper, new types of DoS and DDoS attacks in Cloud Computing are explored, especially the XML-DoS and HTTP-DoS attacks, and some possible detection and mitigation techniques are examined. This survey also provides an overview of the existing defense solutions and investigates the experiments and metrics that are usually designed and used to evaluate their performance, which is helpful for the future research in the domain.
A computational analysis of poetic style Imagism and its influence on modern professional and amateur poetry

How do standards of poetic beauty change as a function of time and expertise? Here we use computational methods to compare the stylistic features of 359 English poems written by 19th century professional poets, Imagist poets, contemporary professional poets, and contemporary amateur poets. Building upon techniques designed to analyze style and sentiment in texts, we examine elements of poetic craft such as imagery, sound devices, emotive language, and diction. We find that contemporary professional poets use significantly more concrete words than 19th century poets, fewer emotional words, and more complex sound devices. These changes are consistent with the tenets of Imagism, an early 20thcentury literary movement. Further analyses show that contemporary amateur poems resemble 19th century professional poems more than contemporary professional poems on several dimensions. The stylistic similarities between contemporary amateur poems and 19th century professional poems suggest that elite standards of poetic beauty in the past “trickled down” to influence amateur works in the present. Our 1 LiLT Volume 12, Issue 3, October 2015. A computational analysis of poetic style.  We suggest that computational linguistics may shed light on the forces and trends that shape poetic style. A computational analysis of poetic style / 3
Empirical studies of software engineering: a roadmap

In this article we summarize the strengths and weaknesses of empirical research in software engineering. We argue that in order to improve the current situation we must create better studies and draw more credible interpretations from them. We finally present a roadmap for this improvement, which includes a general structure for software empirical studies and concrete steps for achieving these goals: designing better studies, collecting data more effectively, and involving others in our empirical enterprises.
Speech Recognition Systems : A Comparative Review

Creating voice control for robots is very important and difficult task. Therefore, we consider different systems of speech recognition. We divided them into two main classes: (1) open-source and (2) close-source code. As close-source software the following were selected: Dragon Mobile SDK, Google Speech Recognition API, Siri, Yandex SpeechKit and Microsoft Speech API. While the following were selected as open-source software: CMU Sphinx, Kaldi, Julius, HTK, iAtros, RWTH ASR and Simon. The comparison mainly based on accuracy, API, performance, speed in real-time, response time and compatibility. the variety of comparison axes allow us to make detailed description of the differences and similarities, which in turn enabled us to adopt a careful decision to choose the appropriate system depending on our need.
A Puzzle-Based Defense Strategy Against Flooding Attacks Using Game Theory

In recent years, a number of puzzle-based defense mechanisms have been proposed against flooding denial-of-service (DoS) attacks in networks. Nonetheless, these mechanisms have not been designed through formal approaches and thereby some important design issues such as effectiveness and optimality have remained unresolved. This paper utilizes game theory to propose a series of optimal puzzle-based strategies for handling increasingly sophisticated flooding attack scenarios. In doing so, the solution concept of Nash equilibrium is used in a prescriptive way, where the defender takes his part in the solution as an optimum defense against rational attackers. This study culminates in a strategy for handling distributed attacks from an unknown number of sources.
Winter 2003 COMPETENCE , CULPABILITY , AND PUNISHMENT : IMPLICATIONS OF A TKINS FOR EXECUTING AND SENTENCING ADOLESCENTS

The Supreme Court has explored the issues of culpability, proportionality, and deserved punishment most fully in the context of capital punishment. In death penalty decisions addressing developmental impairments and culpability, the Court has considered the cases of defendants with mental retardation and older adolescents, and has created an anomalous inconsistency by reaching opposite conclusions about the deserved punishment for each group of defendants. Recently, in Atkins v. Virginia, the Court relied on both empirical and normative justifications to categorically prohibit states from executing defendants with mental retardation. Atkins reasoned that mentally retarded offenders lacked the reasoning, judgment, and impulse control necessary to equate their culpability with that of other death-eligible criminal defendants. This Article contends that the same psychological and developmental * Centennial Professor of Law, University of Minnesota, B.A., University of Pennsylvania, 1966; J.D., University of Minnesota Law School, 1969; Ph.D. (Sociology), Harvard University, 1973. 1 would like to thank Steven Drizin, Richard Frase, Wayne Logan, Monte Norgaard, and Victor Streib for critical and helpful comments on an earlier draft of this article. The questions and comments of faculty and student participants at the University of Houston Law School Symposium, January, 2004, helped to sharpen the analysis. I received outstanding research assistance from Brittany Stephens, Class of 2005. 1 Feld: Competence, Culpability, and Punishment: Implications of Atkins f Published by Scholarly Commons at Hofstra Law, 2003