nils-herrmann/clean_scirepeval huggingface dataset:
Derivation of GFDM based on OFDM principles

This paper starts with presenting a fundamental principle based on which the celebrated orthogonal frequency division multiplexing (OFDM) waveform is constructed. It then extends the same principle to construct the newly introduced generalized frequency division multiplexing (GFDM) signals. This novel derivation sheds light on some interesting properties of GFDM. In particular, our derivation seamlessly leads to an implementation of GFDM transmitter which has significantly lower complexity than what has been reported so far. Our derivation also facilitates a trivial understanding of how GFDM (similar to OFDM) can be applied in MIMO channels.
A 570fsrms integrated-jitter ring-VCO-based 1.21GHz PLL with hybrid loop

Sampling clock jitter significantly degrades the circuit performance and dynamic range of an ADC . This paper presents a 570fsrms integrated-jitter 1.21GHz PLL with a hybrid loop. A ring VCO has a much inferior phase noise characteristic as compared to an LC VCO, but its area efficiency is attractive. To suppress the phase noise of a ring VCO, a wide-loop-bandwidth PLL with sufficiently low in-band noise is indispensable. An all-digital PLL (ADPLL)  has insufficiently low in-band phase noise because of the quantization error of the time-to-digital converter (TDC) without employing additional techniques such as power-hungry time amplification . On the other hand, a conventional analog PLL has a superior in-band phase noise but needs a large loop-filter capacitor to maintain a wide tuning range due to a high control sensitivity of the ring VCO. The dual-tuning topology is useful for minimizing the size of the loop filter while maintaining low in-band phase noise [4, 5]. However, it also suffers from strong reference spurs, as it is the case in the conventional analog PLL having a wide loop bandwidth. The proposed PLL employs a hybrid loop consisting of a type-II ADPLL and a type-I analog PLL. The type-II ADPLL enables the wide tuning range without a large loop-filter capacitor. The loop-filter capacitor in the analog PLL is also minimized since it does not need to cover a wide tuning range. The analog PLL eliminates the residual quantization error of the TDC in the ADPLL and achieves a sufficiently low in-band phase noise. Overall, the proposed PLL suppresses the phase noise contribution from the ring digital/voltage-controlled oscillator (DVCO).
Human emotion recognition from videos using spatio-temporal and audio features

In this paper, we present human emotion recognition systems based on audio and spatio-temporal visual features. The proposed system has been tested on audio visual emotion data set with different subjects for both genders. The mel-frequency cepstral coefficient (MFCC) and prosodic features are first identified and then extracted from emotional speech. For facial expressions spatio-temporal features are extracted from visual streams. Principal component analysis (PCA) is applied for dimensionality reduction of the visual features and capturing 97 % of variances. Codebook is constructed for both audio and visual features using Euclidean space. Then occurrences of the histograms are employed as input to the state-of-the-art SVM classifier to realize the judgment of each classifier. Moreover, the judgments from each classifier are combined using Bayes sum rule (BSR) as a final decision step. The proposed system is tested on public data set to recognize the human emotions. Experimental results and simulations proved that using visual features only yields on average 74.15 % accuracy, while using audio features only gives recognition average accuracy of 67.39 %. Whereas by combining both audio and visual features, the overall system accuracy has been significantly improved up to 80.27 %.
Background modeling from a free-moving camera by Multi-Layer Homography Algorithm

This paper proposes a novel multi-layer homography algorithm for background modeling from a free-moving camera. Background is composed of many planes. Different planes satisfy with different homographies which can be found by our algorithm. Each pixel except for the moving pixel definitely belongs to some plane. Rectified by the corresponding homography, each static pixel in the shared view can find its match in the previous frame. Thus, frames can be rectified to a specific viewpoint for background modeling. Experiment shows it is effective. Our approach can be used in motion detection from a free-moving camera.
Context Sensitive Lemmatization Using Two Successive Bidirectional Gated Recurrent Networks

We introduce a composite deep neural network architecture for supervised and language independent context sensitive lemmatization. The proposed method considers the task as to identify the correct edit tree representing the transformation between a word-lemma pair. To find the lemma of a surface word, we exploit two successive bidirectional gated recurrent structures the first one is used to extract the character level dependencies and the next one captures the contextual information of the given word. The key advantages of our model compared to the state-of-the-art lemmatizers such as Lemming and Morfette are (i) it is independent of human decided features (ii) except the gold lemma, no other expensive morphological attribute is required for joint learning. We evaluate the lemmatizer on nine languages Bengali, Catalan, Dutch, Hindi, Hungarian, Italian, Latin, Romanian and Spanish. It is found that except Bengali, the proposed method outperforms Lemming and Morfette on the other languages. To train the model on Bengali, we develop a gold lemma annotated dataset1 (having 1, 702 sentences with a total of 20, 257 word tokens), which is an additional contribution of this work.
Beyond Binary Labels: Political Ideology Prediction of Twitter Users

Automatic political preference prediction from social media posts has to date proven successful only in distinguishing between publicly declared liberals and conservatives in the US. This study examines users’ political ideology using a sevenpoint scale which enables us to identify politically moderate and neutral users – groups which are of particular interest to political scientists and pollsters. Using a novel data set with political ideology labels self-reported through surveys, our goal is two-fold: a) to characterize the political groups of users through language use on Twitter; b) to build a fine-grained model that predicts political ideology of unseen users. Our results identify differences in both political leaning and engagement and the extent to which each group tweets using political keywords. Finally, we demonstrate how to improve ideology prediction accuracy by exploiting the relationships between the user groups.
The Winograd Schema Challenge and Reasoning about Correlation

The Winograd Schema Challenge is an alternative to the Turing Test that may provide a more meaningful measure of machine intelligence. It poses a set of coreference resolution problems that cannot be solved without human-like reasoning. In this paper, we take the view that the solution to such problems lies in establishing discourse coherence. Specifically, we examine two types of rhetorical relations that can be used to establish discourse coherence: positive and negative correlation. We introduce a framework for reasoning about correlation between sentences, and show how this framework can be used to justify solutions to some Winograd Schema problems.
ROC analysis of classifiers in machine learning: A survey

The use of ROC (Receiver Operating Characteristics) analysis as a tool for evaluating the performance of classification models in machine learning has been increasing in the last decade. Among the most notable advances in this area are the extension of two-class ROC analysis to the multi-class case as well as the employment of ROC analysis in cost-sensitive learning. Methods now exist which take instance-varying costs into account. The purpose of our paper is to present a survey of this field with the aim of gathering important achievements in one place. In the paper, we present application areas of the ROC analysis in machine learning, describe its problems and challenges and provide a summarized list of alternative approaches to ROC analysis. In addition to presented theory, we also provide a couple of examples intended to illustrate the described approaches.
A survey of neural network accelerators

Machine-learning techniques have recently been proved to be successful in various domains, especially in emerging commercial applications. As a set of machine-learning techniques, artificial neural networks (ANNs), requiring considerable amount of computation and memory, are one of the most popular algorithms and have been applied in a broad range of applications such as speech recognition, face identification, natural language processing, ect. Conventionally, as a straightforward way, conventional CPUs and GPUs are energy-inefficient due to their excessive effort for flexibility. According to the aforementioned situation, in recent years, many researchers have proposed a number of neural network accelerators to achieve high performance and low power consumption. Thus, the main purpose of this literature is to briefly review recent related works, as well as the DianNao-family accelerators. In summary, this review can serve as a reference for hardware researchers in the area of neural networks.
Information systems strategy for small and medium sized enterprises: an organisational perspective

Information systems strategy (ISS) use is under-developed for, and under-researched in, small and medium sized enterprises (SMEs). This paper reviews existing approaches to ISS for SMEs, ®nding them now out-dated and technology-focussed. The paper develops an approach that re ̄ects on the role of information as a strategic resource. It argues that ISS recommendations in small ®rms need to take account of organisational change issues as much as information system implementation. The revised approach to ISS for SMEs is demonstrated through its application to over 40 cases in the UK West Midlands. The in ̄uences from the processes on outcomes are discussed and the effectiveness of tools and techniques recommended is assessed. q 2000 Elsevier Science B.V. All rights reserved.
A 77-GHz SiGe frequency multiplier (×18) for radar transceivers

For 77-GHz automotive radar applications, a monolithic frequency multiplier with a multiplication factor of 18 is presented. The main circuit of the multiplier chain consists of two frequency tripler and one doubler. Additionally interstage amplifiers and filters are integrated in a 200-GHz SiGe:C production technology. The output power is −1dBm for a wide input power range (−20dBm − +8 dBm) at room temperature and 76.5 GHz output frequency. The output power flatness is better than 2 dB for an output frequency range of 69 GHz to 80 GHz. The power consumption of the multiplier is 170mW at a single supply voltage of 3.3V.
Muscle-plotter: An Interactive System based on Electrical Muscle Stimulation that Produces Spatial Output

We explore how to create interactive systems based on electrical muscle stimulation that offer expressive output. We present muscle-plotter, a system that provides users with input and output access to a computer system while on the go. Using pen-on-paper interaction, muscle-plotter allows users to engage in cognitively demanding activities, such as writing math. Users write formulas using a pen and the system responds by making the users' hand draw charts and widgets. While Anoto technology in the pen tracks users' input, muscle-plotter uses electrical muscle stimulation (EMS) to steer the user's wrist so as to plot charts, fit lines through data points, find data points of interest, or fill in forms. We demonstrate the system at the example of six simple applications, including a wind tunnel simulator.
 The key idea behind muscle-plotter is to make the user's hand sweep an area on which muscle-plotter renders curves, i.e., series of values, and to persist this EMS output by means of the pen. This allows the system to build up a larger whole. Still, the use of EMS allows muscle-plotter to achieve a compact and mobile form factor. In our user study, muscle-plotter made participants draw random plots with an accuracy of ±4.07 mm and preserved the frequency of functions to be drawn up to 0.3 cycles per cm.
A simplified thermal model for variable speed self cooled industrial induction motor

In this paper, a simplified thermal model for variable speed self cooled induction motors is proposed and experimentally verified. The thermal model is based on simple equations that are compared with more complex equations well known in literature. The proposed thermal model allows to predict the over temperature in the main parts of the motor, starting from the measured or the estimated losses in the machine. In the paper the description of the thermal model set up is reported in detail. Finally, the model is used to define the correct power derating for a variable speed PWM induction motor drive.
Automated software testing as a service

This paper makes the case for TaaS--automated software testing as a cloud-based service. We present three kinds of TaaS: a "programmer's sidekick" enabling developers to thoroughly and promptly test their code with minimal upfront resource investment; a "home edition" on-demand testing service for consumers to verify the software they are about to install on their PC or mobile device; and a public "certification service," akin to Underwriters Labs, that independently assesses the reliability, safety, and security of software.
 TaaS automatically tests software, without human involvement from the service user's or provider's side. This is unlike today's "testing as a service" businesses, which employ humans to write tests. Our goal is to take recently proposed techniques for automated testing--even if usable only on to y programs--and make them practical by modifying them to harness the resources of compute clouds. Preliminary work suggests it is technically feasible to do so, and we find that TaaS is also compelling from a social and business point of view.
Spanking and child development during the first 5 years of life.

Using data from the Fragile Families and Child Wellbeing Study (N=3,870) and cross-lagged path analysis, the authors examined whether spanking at ages 1 and 3 is adversely associated with cognitive skills and behavior problems at ages 3 and 5. The authors found spanking at age 1 was associated with a higher level of spanking and externalizing behavior at age 3, and spanking at age 3 was associated with a higher level of internalizing and externalizing behavior at age 5. The associations between spanking at age 1 and behavioral problems at age 5 operated predominantly through ongoing spanking at age 3. The authors did not find an association between spanking at age 1 and cognitive skills at age 3 or 5.
Rapid octree construction from image sequences

The construction of a three-dimensional object model from a set of images taken from different viewpoints is an important problem in computer vision. One of the simplest ways to do this is to use the silhouettes of the object (the binary classification of images into object and background) to construct a bounding volume for the object. To efficiently represent this volume, we use an octree, which represents the object as a tree of recursively subdivided cubes. We develop a new algorithm for computing the octree bounding volume from multiple silhouettes and apply it to an object rotating on a turntable in front of a stationary camera. The algorithm performs a limited amount of processing for each viewpoint and incrementally builds the volumetric model. The resulting algorithm requires less total computation than previous algorithms, runs in close to real-time, and builds a model whose resolution improves over time.
An Evaluation of Similarity Coefficients for Software Fault Localization

Automated diagnosis of software faults can improve the efficiency of the debugging process, and is therefore an important technique for the development of dependable software. In this paper we study different similarity coefficients that are applied in the context of a program spectral approach to software fault localization (single programming mistakes). The coefficients studied are taken from the systems diagnosis/automated debugging tools Pinpoint, Tarantula, and AMPLE, and from the molecular biology domain (the Ochiai coefficient). We evaluate these coefficients on the Siemens Suite of benchmark faults, and assess their effectiveness in terms of the position of the actual fault in the probability ranking of fault candidates produced by the diagnosis technique. Our experiments indicate that the Ochiai coefficient consistently outperforms the coefficients currently used by the tools mentioned. In terms of the amount of code that needs to be inspected, this coefficient improves 5% on average over the next best technique, and up to 30% in specific cases
DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions

The Database of Interacting Proteins (DIP: http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. It provides the scientific community with an integrated set of tools for browsing and extracting information about protein interaction networks. As of September 2001, the DIP catalogs approximately 11 000 unique interactions among 5900 proteins from >80 organisms; the vast majority from yeast, Helicobacter pylori and human. Tools have been developed that allow users to analyze, visualize and integrate their own experimental data with the information about protein-protein interactions available in the DIP database.
Developing multi-agent systems with a FIPA-compliant agent framework

To ease large-scale realization of agent applications there is an urgent need for frameworks, methodologies and toolkits that support the effective development of agent systems. Moreover, since one of the main tasks for which agent systems were invented is the integration between heterogeneous software, independently developed agents should be able to interact successfully. In this paper, we present JADE (Java Agent Development Environment), a software framework to build agent systems for the management of networked information resources in compliance with the FIPA specifications for inter-operable intelligent multi-agent systems. The goal of JADE is to simplify development while ensuring standard compliance through a comprehensive set of system services and agents. JADE can then be considered to be an agent middle-ware that implements an efficient agent platform and supports the development of multi-agent systems. It deals with all the aspects that are not peculiar to agent internals and that are independent of the applications, such as message transport, encoding and parsing, or agent life-cycle management.
Ontological modelling of form and function for architectural design

Form, function and the relationship between the two are notions that have served a crucial role in design science. Within architectural design, key aspects of the anticipated function of buildings, or of spatial environments in general, are supposed to be determined by their structural form, i.e., their shape, layout, or connectivity. Whereas the philosophy of form and function is a well-researched topic, the practical relations and dependencies between form and function are only known implicitly by designers and architects. Specifically, the formal modelling of structural form and resulting artefactual function within design and design assistance systems remains elusive. In our work, we aim at making these definitions explicit by the ontological modelling of domain entities, their properties and related constraints. We thus have to particularly focus on formal interpretation of the terms “(structural) form” and “(artefactual) function”. We put these notions into practice by formalising ontological specifications accordingly by using modularly constructed ontologies for the architectural design domain. A key aspect of our modelling approach is the use of formal qualitative spatial calculi and conceptual requirements as a link between the structural form of a design and the differing functional capabilities that it affords or leads to. We demonstrate the manner in which our ontological modelling reflects notions of architectural form and function, and how it facilitates the conceptual modelling of requirement constraints for architectural design.
A Hierarchical Phrase-Based Model for Statistical Machine Translation

We present a statistical phrase-based translation model that useshierarchical phrases — phrases that contain subphrases. The model is formally a synchronous context-free grammar but is learned from a bitext without any syntactic information. Thus it can be seen as a shift to the formal machinery of syntaxbased translation systems without any linguistic commitment. In our experiments using BLEU as a metric, the hierarchical phrasebased model achieves a relative improvement of 7.5% over Pharaoh, a state-of-the-art phrase-based system.
Generating electricity while walking with loads.

We have developed the suspended-load backpack, which converts mechanical energy from the vertical movement of carried loads (weighing 20 to 38 kilograms) to electricity during normal walking [generating up to 7.4 watts, or a 300-fold increase over previous shoe devices (20 milliwatts)]. Unexpectedly, little extra metabolic energy (as compared to that expended carrying a rigid backpack) is required during electricity generation. This is probably due to a compensatory change in gait or loading regime, which reduces the metabolic power required for walking. This electricity generation can help give field scientists, explorers, and disaster-relief workers freedom from the heavy weight of replacement batteries and thereby extend their ability to operate in remote areas.
Portable fire evacuation guide robot system

Robot technology is emerging for applications in disaster prevention with devices such as fire-fighting robots, rescue robots, and surveillance robots. In this paper, we suggest an portable fire evacuation guide robot system that can be thrown into a fire site to gather environmental information, search displaced people, and evacuate them from the fire site. This spool-like small and light mobile robot can be easily carried and remotely controlled by means of a laptop-sized tele-operator. It contains the following functional units: a camera to capture the fire site; sensors to gather temperature data, CO gas, and O2 concentrations; and a microphone with speaker for emergency voice communications between firefighter and victims. The robot's design gives its high-temperature protection, excellent waterproofing, and high impact resistance. Laboratory tests were performed for evaluating the performance of the proposed evacuation guide robot system.
Data in Randomized Block and Split-Plot Designs Estimation of the Box Correction for Degrees of Freedom from Sample

It has been suggested that when the variance assumptions of a repeated measures ANOVA are not met, the df of the mean square ratio should be adjusted by the sample estimate of the Box correction factor, e. This procedure works well when e is low, but the estimate is seriously biased when this is not the case. An alternate estimate is proposed which is shown by Monte Carlo methods to be less biased for moderately large e.
Types of Common-Sense Knowledge Needed for Recognizing Textual Entailment

Understanding language requires both linguistic knowledge and knowledge about how the world works, also known as common-sense knowledge. We attempt to characterize the kinds of common-sense knowledge most often involved in recognizing textual entailments. We identify 20 categories of common-sense knowledge that are prevalent in textual entailment, many of which have received scarce attention from researchers building collections of knowledge.