nils-herrmann/clean_scirepeval huggingface dataset:
The Role of Attention in Discourse , Cognition , & Syntax : Dynamic Processes Require Dynamic Theory

The human conceptual system contains categorical knowledge about the world that supports online processing (perception, categorization, inference, action) and offline processing (memory, language, thought). Semantic memory, the classic view of the conceptual system, typically portrays it as modular, amodal, abstractive, and static. Alternatively, the conceptual system can be viewed as non-modular, modal, situated, and dynamic. According to this perspective, the conceptual system is non-modular and modal because it shares representational mechanisms with modality-specific systems in the brain. On a given occasion, modality-specific information about a category's members is reenacted in relevant modality-specific systems to represent it. Furthermore these simulations are situated, preparing the conceptualizer for situated action with the category. Not only do these situated simulations represent the target category, they also represent background settings, actions, and mental perspectives, thereby placing the conceptualizer in the simulation, prepared for goal pursuit. Because the optimal conceptualization of a category varies across different courses of situated action, category representations are dynamic, not static. Behavioral and neural evidence is presented to support this view of the conceptual system. Among the central problems of linguistic inquiry is the problem of use, of specifying the conditions under which semantically equivalent expressions are formed or selected as speakers engage in real time discourse. Increasingly, linguists appeal to a role for cognition in capturing how linguistic structures are deployed in discourse, with attention of particular interest. This paper discusses the place of attention in understanding, theoretically and empirically, how dynamic conceptual representations get mapped into linguistic structures during discourse production. The lexicalization of event-denoting expressions has emerged as the area of semantics with the most extreme cross-linguistic variation. This makes the mapping between the semantic level of 'event' and the syntactic level of 'clause' one of the greatest challenges to semantics, syntax and typology. One dimension of this problem is working out how much complexity, in terms of event structure, can be accommodated within a single clause. Cross-linguistic studies of causatives, benefactive and instrumental constructions, and motion events have showed us that single-clause English expressions like I dropped the cup, I baked Mary a cake, I cut the bread with a knife and The ball rolled down the hill are all syntactically decomposable in some languages into multi-clause expressions of the type I made/let the cup fall, I baked cake gave Mary and The ball descended the hill, rolling. A wide range of languages employ such strategies, through …
Designing parts feeders using dynamic simulation

We consider the problem of designing traditional (e.g. vibratory bowl) feeders for singulating and orienting industrial parts. Our ultimate goal is to prototype new designs using analyticallyand geometrically-based methods. We have developed a tool for designing industrial parts feeders based on dynamic simulation. Our tool allows us to automatically perform multiple feeder design experiments, and to evaluate their outcomes. These results can then be used to compute the probabilities of a Markov model for the feeder. To demonstrate our technique, we present preliminary results for the design of two simple feeders. Our findings suggest that using dynamic simulation is a promising approach for designing parts feeders.
Design of RYSEN: An Intrinsically Safe and Low-Power Three-Dimensional Overground Body Weight Support

Body weight support (BWS) systems are widely used in gait research and rehabilitation. This letter introduces a new three-dimensional overground BWS system, called the RYSEN. The RYSEN is designed to be intrinsically safe and low power consuming, while still performing at least as well as existing BWS systems regarding human–robot interaction. These features are mainly achieved by decoupling degrees of freedom between motors: slow/high-torque motors for vertical motion and fast/low-torque motors for horizontal motion. This letter explains the design and evaluates its performance on power consumption and safety. Power consumption is expressed in terms of the sum of the positive mechanical output power of all motor axes. Safety is defined as the difference between the mechanical power available for horizontal and vertical movements and the mechanical power that is needed to perform its task. The results of the RYSEN are compared to the performance of three similar systems: a gantry, the FLOAT, and a classic cable robot. The results show that the RYSEN and a gantry consume approximately the same amount of power. The amount is approximately half the power consumed by the next-best system. For the safety, the gantry is taken as the benchmark, because of its perfect decoupling of directions. The RYSEN has a surplus of 268 W and 126 W for horizontal and vertical movements, respectively. This is significantly lower than the next-best system, which has a surplus of 1088 W and 1967 W, respectively.
LateralPaD: A surface-haptic device that produces lateral forces on a bare finger

The LateralPaD is a surface haptic device that generates lateral (shear) force on a bare finger, by vibrating the touch surface simultaneously in both out-of-plane (normal) and in-plane (lateral) directions. A prototype LateralPaD has been developed in which the touch surface is glass, and piezoelectric actuators drive normal and lateral resonances at the same ultrasonic frequency (~22.3 KHz). The force that develops on the finger can be controlled by modulating the relative phase of the two resonances. A 2DOF load cell setup is used to characterize the dependence of induced lateral force on vibration amplitude, relative phase, and applied normal force. A Laser Doppler Vibrometer (LDV) is used to measure the motion of glass surface as well as of the fingertip. Together, these measurements yield insight into the mechanism of lateral force generation. We show evidence for a mechanism dependent on tilted impacts between the LateralPaD and fingertip.
Enrollment Prediction through Data Mining

In this paper, we describe our study on enrollment prediction using support vector machines and rule-based predictive models. The goal is to predict the total enrollment headcount that is composed of new (freshman and transfer), continued and returned students. The proposed approach builds predictive models for new, continued and returned students, respectively first, and then aggregates their predictive results from which the model for the total headcount is generated. The types of data utilized during the mining process include population, employment, tuition and fees, household income, high school graduates, and historical enrollment data. Support vector machines produce the initial predictive results, which are then used by a tool called Cubist to generate easy-to-understand rule-based predictive models. Finally we present some empirical results on enrollment prediction for computer science students at California State University, Sacramento
Solid state Marx Generator using series-connected IGBTs

This paper describes a newly developed novel repetitive impulse voltage generator using a boost converter array. To solve problems such as short life time, low operating frequency, and the fixed pulse width of conventional generators, the proposed generator is designed with a boost converter array that employs series-connected capacitors and insulated gate bipolar transistors. The circuit can easily obtain a high-voltage pulse without any high-voltage direct current source and pulse transformer. Thus, the proposed circuit not only allows elimination of the expensive high-frequency transformer but also allows operation at a frequency up to several kilohertz with high reliability and longer life span. To validate the proposed circuit, two pulse generators rated at 1.8 kV, 40 A and 20 kV, 300 A are implemented and tested.
A review on human action analysis in videos for retrieval applications

Today, the number of available videos on the Internet is significantly increased. Content-based video retrieval is used for finding the users’ desired items among these big video data. Memorizing details of the videos and intricate relations between included objects in videos can be considered as the major challenges of this big data topic. A large portion of video data relates to the humans. Thus, human action retrieval has been introduced as a new big data topic that seeks to find video objects based on the included human action. Human action retrieval has been applicated in different domains such as video search, intelligent human–computer interaction, robotics, video surveillance and human behavior analysis. There are some challenges such as variations in rotation, scale, style and above-mentioned challenges for the big video data that can impress the retrieval accuracy. In this paper, a survey on human action retrieval studies is presented that the methodologies have been analyzed from action representation and retrieving perspectives. Moreover, limitations and common datasets of human action retrieval are introduced before describing the state-of-the-arts’ methodologies.
Efficiently Answering Technical Questions - A Knowledge Graph Approach

More and more users prefer to ask their technical questions online. For machines, understanding a question is nontrivial. Current approaches lack explicit background knowledge. In this paper, we introduce a novel technical question understanding approach to recommending probable solutions to users. First, a knowledge graph is constructed which contains abundant technical information, and an augmented knowledge graph is built on the basis of the knowledge graph, to link the knowledge graph and documents. Then we develop a light weight question driven mechanism to select candidate documents. To improve the online performance, we propose an index-based random walk to support the online search. We use comprehensive experiments to evaluate the effectiveness of our approach on a large scale of real-world query logs. Our system outperforms main-stream search engine and the state-of-art information retrieval methods. Meanwhile, extensive experiments confirm the efficiency of our index-based online search mechanism.
EFRS:Enabling Efficient and Fine-Grained Range Search on Encrypted Spatial Data

Range search of spatial data, has been applied in many scenarios such as geometric queries, location-based services, and computational geometry, etc. Due to the increasing amount of spatial data, which are usually outsourced to the cloud for saving storage and computational overhead. However, a common privacy issue is that the cloud server may steal user's sensitive information utilizing its powerful computing advantages. A feasible way of managing this bottleneck is to encrypt spatial data before outsourcing it. Nevertheless, the availability of data will be significantly reduced because of the query difficulty over the encrypted cloud data. In this paper, we propose an Efficient Range Search scheme (EFRS) which can achieve fine- grained query over encrypted spatial data. We original contributions are threefold. First, polynomial fitting technique and orderpreserving encryption are introduced to realize the efficient and fine- grained range query over encrypted cloud data. Then, in order to improve the search efficiency, we exploit the Rtree to significantly decreased the search space. Finally, we theoretically proved the security of our proposed scheme in terms of confidentially of spatial data, privacy protection of index and trapdoor, and the unlinkability of trapdoor. Besides, extensive experiments demonstrate the high efficiency of our proposed model compared with existing schemes.
An empirical investigation of mobile ticketing service adoption in public transportation

In this paper, we present results from a study of mobile ticketing service adoption in public transportation. The theoretical background of the study is based on technology adoption and trust theories, which are augmented with concepts of mobile use context and mobility. Our empirical findings from analyses of a survey data suggest that compatibility of the mobile ticketing service with consumer behavior is a major determinant of adoption. Mobility and contextual factors, including budget constraints, availability of other alternatives, and time pressure in the service use situation were also found to have a strong effect on the adoption decision. Our findings suggest that contextual and mobile service-specific features are important determinants of mobile service adoption and should thus be integrated into the traditional adoption models.
Personality and Performance at the Beginning of the New Millennium : What Do We Know and Where Do We Go Next ?

As we begin the new millennium, it is an appropriate time to examine what we have learned about personality-performance relationships over the past century and to embark on new directions for research. In this study we quantitatively summarize the results of 15 prior meta-analytic studies that have investigated the relationship between the Five Factor Model (FFM) personality traits and job performance. Results support the previous findings that conscientiousness is a valid predictor across performance measures in all occupations studied. Emotional stability was also found to be a generalizable predictor when overall work performance was the criterion, but its relationship to specific performance criteria and occupations was less consistent than was conscientiousness. Though the other three Big Five traits (extraversion, openness and agreeableness) did not predict overall work performance, they did predict success in specific occupations or relate to specific criteria. The studies upon which these results are based comprise most of the research that has been conducted on this topic in the past century. Consequently, we call for a moratorium on meta-analytic studies of the type reviewed in our study and recommend that researchers embark on a new research agenda designed to further our understanding of personalityperformance linkages.
Five-Level Reduced-Switch-Count Boost PFC Rectifier With Multicarrier PWM

A multilevel boost power factor correction (PFC) rectifier is presented in this paper controlled by cascaded controller and multicarrier pulse width modulation technique. The presented topology has less active semiconductor switches compared to similar ones reducing the number of required gate drives that would shrink the manufactured box significantly. A simple controller has been implemented on the studied converter to generate a constant voltage at the output while generating a five-level voltage waveform at the input without connecting the load to the neutral point of the dc bus capacitors. Multicarrier pulse-width modulation technique has been used to produce switching pulses from control signal at a fixed switching frequency. Multilevel voltage waveform harmonics has been analyzed comprehensively which affects the harmonic contents of input current and the size of required filters directly. Full experimental results confirm the good dynamic performance of the proposed five-level PFC boost rectifier in delivering power from ac grid to the dc loads while correcting the power factor at the ac side as well as reducing the current harmonics remarkably.
SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine

We publicly release a new large-scale dataset, called SearchQA, for machine comprehension, or question-answering. Unlike recently released datasets, such as DeepMind CNN/DailyMail and SQuAD, the proposed SearchQA was constructed to reflect a full pipeline of general question-answering. That is, we start not from an existing article and generate a question-answer pair, but start from an existing question-answer pair, crawled from J! Archive, and augment it with text snippets retrieved by Google. Following this approach, we built SearchQA, which consists of more than 140k question-answer pairs with each pair having 49.6 snippets on average. Each question-answer-context tuple of the SearchQA comes with additional meta-data such as the snippet’s URL, which we believe will be valuable resources for future research. We conduct human evaluation as well as test two baseline methods, one simple word selection and the other deep learning based, on the SearchQA. We show that there is a meaningful gap between the human and machine performances. This suggests that the proposed dataset could well serve as a benchmark for question-answering.
Incremental multi-step Q-learning

This paper presents a novel incremental algorithm that combines Q-learning, a well-known dynamic-programming based reinforcement learning method, with the TD(λ) return estimation process, which is typically used in actor-critic learning, another well-known dynamic-programming based reinforcement learning method. The parameter λ is used to distribute credit throughout sequences of actions, leading to faster learning and also helping to alleviate the non-Markovian effect of coarse state-space quatization. The resulting algorithm.Q(λ)-learning, thus combines some of the best features of the Q-learning and actor-critic learning paradigms. The behavior of this algorithm has been demonstrated through computer simulations.
Dynamic Thermal Management for High-Performance Microprocessors

With the increasing clock rate and transistor count of today’s microprocessors, power dissipation is becoming a critical component of system design complexity. Thermal and power-delivery issues are becoming especially critical for high-performance computing systems. In this work, we investigate dynamic thermal management as a technique to control CPUpower dissipation. With the increasing usage of clock gating techniques, the average power dissipation typically seen by common applications is becoming much less than the chip’s rated maximum power dissipation. However; system designers still must design thermal heat sinks to withstand the worst-case scenario. We define and investigate the major components of any dynamic thermal management scheme. Specijcally we explore the tradeoffs between several mechanisms for responding to periods of thermal trauma and we consider the effects of hardware and sofnyare implementations. With appropriate dynamic thermal management, the CPU can be designed for a much lower maximum power rating, with minimal performance impact for typical applications.
A human gut microbial gene catalogue established by metagenomic sequencing

To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ∼150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively.
Public health implications of altered puberty timing.

Changes in puberty timing have implications for the treatment of individual children, for the risk of later adult disease, and for chemical testing and risk assessment for the population. Children with early puberty are at a risk for accelerated skeletal maturation and short adult height, early sexual debut, potential sexual abuse, and psychosocial difficulties. Altered puberty timing is also of concern for the development of reproductive tract cancers later in life. For example, an early age of menarche is a risk factor for breast cancer. A low age at male puberty is associated with an increased risk for testicular cancer according to several, but not all, epidemiologic studies. Girls and, possibly, boys who exhibit premature adrenarche are at a higher risk for developing features of metabolic syndrome, including obesity, type 2 diabetes, and cardiovascular disease later in adulthood. Altered timing of puberty also has implications for behavioral disorders. For example, an early maturation is associated with a greater incidence of conduct and behavior disorders during adolescence. Finally, altered puberty timing is considered an adverse effect in reproductive toxicity risk assessment for chemicals. Recent US legislation has mandated improved chemical testing approaches for protecting children's health and screening for endocrine-disrupting agents, which has led to changes in the US Environmental Protection Agency's risk assessment and toxicity testing guidelines to include puberty-related assessments and to the validation of pubertal male and female rat assays for endocrine screening.
Fingerprint Quality Indices for Predicting Authentication Performance

The performance of an automatic fingerprint authentication system relies heavily on the quality of the captured fingerprint images. In this paper, two new quality indices for fingerprint images are developed. The first index measures the energy concentration in the frequency domain as a global feature. The second index measures the spatial coherence in local regions. We present a novel framework for evaluating and comparing quality indices in terms of their capability of predicting the system performance at three different stages, namely, image enhancement, feature extraction and matching. Experimental results on the IBM-HURSLEY and FVC2002 DB3 databases demonstrate that the global index is better than the local index in the enhancement stage (correlation of 0.70 vs. 0.50) and comparative in the feature extraction stage (correlation of 0.70 vs. 0.71). Both quality indices are effective in predicting the matching performance, and by applying a quality-based weighting scheme in the matching algorithm, the overall matching performance can be improved; a decrease of 1.94% in EER is observed on the FVC2002 DB3 database.
An empirical investigation of student adoption model toward mobile e-textbook: UTAUT2 and TTF model

Faculty of Economics in Universitas Atma Jaya Yogyakarta (UAJY) has replaced printed textbooks with e-textbooks for its academic activities since 2015. These e-textbooks can be accessed via iPad which is given to each student. Hence, the objective of this study is to test the proposed research model based on integrated UTAUT2 and TTF. Questionnaires were distributed to 326 students in 10 classes. Only junior and sophomore students were eligible to fulfill the questionnaires. The result of the study shows that performance expectancy, effort expectancy, social influence, facilitating condition, and habit have a direct significant relationship on behavioral intention to use mobile e-textbook. The result also shows that both Task technology and technology characteristic positively affect task technology fit. There is also a direct significant relationship between Task technology fit and performance expectancy. We suggest that further studies include experimentation to investigate performance expectancy of mobile e-book. 2) More evaluation should be held in the future in more mature environment. The finding of this study can help policymakers in the Faculty of Economics UAJY to evaluate the policy and formulate better strategy. In addition, these findings can be used by others faculties and universities as mobile e-textbook adoption case reference.