nils-herrmann/clean_scirepeval huggingface dataset:
Physics-based fast single image fog removal

Imaging in poor weather is often severely degraded by scattering due to suspended particles in the atmosphere such as haze, fog and mist. Poor visibility becomes a major problem for most outdoor vision applications. In this paper, we propose a novel fast defogging method from a single image of a scene based on a fast bilateral filtering approach. The complexity of our method is only a linear function of the number of input image pixels and this thus allows a very fast implementation. Results on a variety of outdoor foggy images demonstrate that our method achieves good restoration for contrast and color fidelity, resulting in a large improvement in image visibility.
Carbon footprint of nations: a global, trade-linked analysis.

Processes causing greenhouse gas (GHG) emissions benefit humans by providing consumer goods and services. This benefit, and hence the responsibility for emissions, varies by purpose or consumption category and is unevenly distributed across and within countries. We quantify greenhouse gas emissions associated with the final consumption of goods and services for 73 nations and 14 aggregate world regions. We analyze the contribution of 8 categories: construction, shelter, food, clothing, mobility, manufactured products, services, and trade. National average per capita footprints vary from 1 tCO2e/y in African countries to approximately 30/y in Luxembourg and the United States. The expenditure elasticity is 0.57. The cross-national expenditure elasticity for just CO2, 0.81, corresponds remarkably well to the cross-sectional elasticities found within nations, suggesting a global relationship between expenditure and emissions that holds across several orders of magnitude difference. On the global level, 72% of greenhouse gas emissions are related to household consumption, 10% to government consumption, and 18% to investments. Food accounts for 20% of GHG emissions, operation and maintenance of residences is 19%, and mobility is 17%. Food and services are more important in developing countries, while mobility and manufactured goods rise fast with income and dominate in rich countries. The importance of public services and manufactured goods has not yet been sufficiently appreciated in policy. Policy priorities hence depend on development status and country-level characteristics.
Research advances in intelligent collision avoidance and adaptive cruise control

This paper looks into recent developments and research trends in collision avoidance/warning systems and automation of vehicle longitudinal/lateral control tasks. It is an attempt to provide a bigger picture of the very diverse, detailed and highly multidisciplinary research in this area. Based on diversely selected research, this paper explains the initiatives for automation in different levels of transportation system with a specific emphasis on the vehicle-level automation. Human factor studies and legal issues are analyzed as well as control algorithms. Drivers’ comfort and well being, increased safety, and increased highway capacity are among the most important initiatives counted for automation. However, sometimes these are contradictory requirements. Relying on an analytical survey of the published research, we will try to provide a more clear understanding of the impact of automation/warning systems on each of the above-mentioned factors. The discussion of sensory issues requires a dedicated paper due to its broad range and is not addressed in this paper.
The Computation of Optical Flow

Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image displacements. These are usually called the optical flow field or the image velocity field. Provided that optical flow is a reliable approximation to two-dimensional image motion, it may then be used to recover the three-dimensional motion of the visual sensor (to within a scale factor) and the three-dimensional surface structure (shape or relative depth) through assumptions concerning the structure of the optical flow field, the three-dimensional environment, and the motion of the sensor. Optical flow may also be used to perform motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement. We investigate the computation of optical flow in this survey: widely known methods for estimating optical flow are classified and examined by scrutinizing the hypothesis and assumptions they use. The survey concludes with a discussion of current research issues.
A New Zero-Voltage-Switching Push-Pull Converter

A soft switching three-transistor push-pull(TTPP)converter is proposed in this paper. The 3rd transistor is inserted in the primary side of a traditional push-pull converter. Two primitive transistors can achieve zero-voltage-switching (ZVS) easily under a wide load range, the 3rd transistor can also realize zero-voltage-switching assisted by leakage inductance. The rated voltage of the 3rd transistor is half of that of the main transistors. The operation theory is explained in detail. The soft-switching realization conditions are derived. An 800 W with 83.3 kHz switching frequency prototype has been built. The experimental result is provided to verify the analysis.
Fields of Experts

We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The approach provides a practical method for learning high-order Markov random field (MRF) models with potential functions that extend over large pixel neighborhoods. These clique potentials are modeled using the Product-of-Experts framework that uses non-linear functions of many linear filter responses. In contrast to previous MRF approaches all parameters, including the linear filters themselves, are learned from training data. We demonstrate the capabilities of this Field-of-Experts model with two example applications, image denoising and image inpainting, which are implemented using a simple, approximate inference scheme. While the model is trained on a generic image database and is not tuned toward a specific application, we obtain results that compete with specialized techniques.
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks

Variational Autoencoders (VAEs) are expressive latent variable models that can be used to learn complex probability distributions from training data. However, the quality of the resulting model crucially relies on the expressiveness of the inference model. We introduce Adversarial Variational Bayes (AVB), a technique for training Variational Autoencoders with arbitrarily expressive inference models. We achieve this by introducing an auxiliary discriminative network that allows to rephrase the maximum-likelihoodproblem as a two-player game, hence establishing a principled connection between VAEs and Generative Adversarial Networks (GANs). We show that in the nonparametric limit our method yields an exact maximum-likelihood assignment for the parameters of the generative model, as well as the exact posterior distribution over the latent variables given an observation. Contrary to competing approaches which combine VAEs with GANs, our approach has a clear theoretical justification, retains most advantages of standard Variational Autoencoders and is easy to implement.
Application of Hierarchical Linear Models to Assessing Change

Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's status on some trait is modeled as a function of an individual growth trajectory plus random error. At the second, or between-subjects stage, the parameters of the individual growth trajectories vary as a function of differences between subjects in background characteristics, instructional experiences, and possibly experimental treatments. This two-stage conceptualization, illustrated with data on Head Start children, allows investigators to model individual change, predict future development, assess the quality of measurement instruments for distinguishing among growth trajectories, and to study systematic variation in growth trajectories as a function of background characteristics and experimental treatments.
Mathematical models of malaria - a review

Mathematical models have been used to provide an explicit framework for understanding malaria transmission dynamics in human population for over 100 years. With the disease still thriving and threatening to be a major source of death and disability due to changed environmental and socio-economic conditions, it is necessary to make a critical assessment of the existing models, and study their evolution and efficacy in describing the host-parasite biology. In this article, starting from the basic Ross model, the key mathematical models and their underlying features, based on their specific contributions in the understanding of spread and transmission of malaria have been discussed. The first aim of this article is to develop, starting from the basic models, a hierarchical structure of a range of deterministic models of different levels of complexity. The second objective is to elaborate, using some of the representative mathematical models, the evolution of modelling strategies to describe malaria incidence by including the critical features of host-vector-parasite interactions. Emphasis is more on the evolution of the deterministic differential equation based epidemiological compartment models with a brief discussion on data based statistical models. In this comprehensive survey, the approach has been to summarize the modelling activity in this area so that it helps reach a wider range of researchers working on epidemiology, transmission, and other aspects of malaria. This may facilitate the mathematicians to further develop suitable models in this direction relevant to the present scenario, and help the biologists and public health personnel to adopt better understanding of the modelling strategies to control the disease
Viterbi algorithm with sparse transitions (VAST) for nonintrusive load monitoring

Implementation of smart grid provides an opportunity for concurrent implementation of nonintrusive appliance load monitoring (NIALM), which disaggregates the total household electricity data into data on individual appliances. This paper introduces a new disaggregation algorithm for NIALM based on a modified Viterbi algorithm. This modification takes advantage of the sparsity of transitions between appliances' states to decompose the main algorithm, thus making the algorithm complexity linearly proportional to the number of appliances. By consideration of a series of data and integrating a priori information, such as the frequency of use and time on/time off statistics, the algorithm dramatically improves NIALM accuracy as compared to the accuracy of established NIALM algorithms.
Human Resource Information Systems: A Current Assessment

Human resource information systems (HRIS) have become a major MIS subfunction within the personnel areas of many large corporations. This article traces the development of HRIS as an entity independent of centralized MIS, assesses its current operation and technological base, and considers its future role in the firm, especially its relationship to the centralized MIS function. The results of a survey of HRIS professionals from 171 U.S. corporations are described in order to provide an overview of the current design, operation, and effectiveness of HRIS. The findings of the survey are discussed in terms of their implications for management of human resource information systems.
Mobile 3D graphics and virtual reality interaction

Mobile devices such as smartphones and tablets offer great new possibilities for the creation of 3D games and virtual reality environments. However, interaction with objects in these virtual worlds is often difficult -- for example due to the devices' small form factor. In this paper, we define different 3D visualization concepts and evaluate related interactions such as navigation and selection of objects. Detailed experiments with a smartphone and a tablet illustrate the advantages and disadvantages of the various 3D visualization concepts. Our results provide new insight with respect to interaction and highlight important aspects for the design of interactive virtual environments on mobile devices and related applications -- especially for mobile 3D gaming.
Empathy among Medical Students: Is There a Relation with Quality of Life and Burnout?

We aimed to assess medical students' empathy and its associations with gender, stage of medical school, quality of life and burnout.



A cross-sectional, multi-centric (22 medical schools) study that employed online, validated, self-reported questionnaires on empathy (Interpersonal Reactivity Index), quality of life (The World Health Organization Quality of Life Assessment) and burnout (the Maslach Burnout Inventory) in a random sample of medical students.



Out of a total of 1,650 randomly selected students, 1,350 (81.8%) completed all of the questionnaires. Female students exhibited higher dispositional empathic concern and experienced more personal distress than their male counterparts (p<0.05; d ≥ 0.5). There were minor differences in the empathic dispositions of students in different stages of their medical training (p<0.05; f<0.25). Female students had slightly lower scores for physical and psychological quality of life than male students (p<0.05; d<0.5). Female students scored higher on emotional exhaustion and lower on depersonalization than male students (p<0.001; d<0.5). Students in their final stage of medical school had slightly higher scores for emotional exhaustion, depersonalization and personal accomplishment (p<0.05; f<0.25). Gender (β = 0.27; p<0.001) and perspective taking (β = 0.30; p<0.001) were significant predictors of empathic concern scores. Depersonalization was associated with lower empathic concern (β =  -0.18) and perspective taking (β =  -0.14) (p<0.001). Personal accomplishment was associated with higher perspective taking (β = 0.21; p<0.001) and lower personal distress (β =  -0.26; p<0.001) scores.



Female students had higher empathic concern and personal distress dispositions. The differences in the empathy scores of students in different stages of medical school were small. Among all of the studied variables, personal accomplishment held the most important association with decreasing personal distress and was also a predicting variable for perspective taking.
Development of Low-Profile Patch and Semi-Circular SIW Cavity Hybrid Antennas

Two low-profile hybrid antennas are presented. One of the structures provides linearly polarized (LP) wave and the other one produces circularly polarized (CP) radiated field. half-mode substrate integrated waveguide (HMSIW) technique is used to make a semi-circular cavity for reducing the antenna size. Using proximity effect, TM010 mode of a rectangular patch is excited by the HMSIW cavity. An inset microstrip line is used to excite the structure which leads to capability of planar circuit integration. The effects of the HMSIW cavity-backed antenna with and without patches are investigated. The simulated results show that adding the patch increases bandwidth and improves antenna gain. Both proposed hybrid antennas are made on a single-layer substrate using printed circuit board (PCB) process. Two prototypes of the proposed antennas are designed, simulated and fabricated. It is shown that broadband impedance bandwidth of 10% and maximum gain of 7.5 dBi is obtained for the LP antenna. In the case of CP antenna, axial ratio (AR) bandwidth is at least 1% with maximum gain of 6.8 dBi. The proposed hybrid antennas are low profile and offer attractive features such as high gain, low cross polarization level and high front-to-back ratio.
FPGA Trust Zone: Incorporating trust and reliability into FPGA designs

This paper proposes a novel methodology FPGA Trust Zone (FTZ) to incorporate security into the design cycle to detect and isolate anomalies such as Hardware Trojans in the FPGA fabric. Anomalies are identified using violation to spatial correlation of process variation in FPGA fabric. Anomalies are isolated using Xilinx Isolation Design Flow (IDF) methodology. FTZ helps identify and partition the FPGA into areas that are devoid of anomalies and thus, assists to run designs securely and reliably even in an anomaly-infected FPGA. FTZ also assists IDF to select trustworthy areas for implementing isolated designs and trusted routes. We demonstrate the effectiveness of FTZ for AES and RC5 designs on Xilinx Virtex-7 and Atrix-7 FPGAs.
Local Atomicity Properties: Modular Concurrency Control for Abstract Data Types

Atomic actions (or transactions) are useful for coping with concurrency and failures. One way of ensuring atomicity of actions is to implement applications in terms of atomic data types: abstract data types whose objects ensure serializability and recoverability of actions using them. Many atomic types can be implemented to provide high levels of concurrency by taking advantage of algebraic properties of the type's operations, for example, that certain operations commute. In this paper we analyze the level of concurrency permitted by an atomic type. We introduce several local constraints on individual objects that suffice to ensure global atomicity of actions; we call these constraints local atomicity properties. We present three local atomicity properties, each of which is optimal: no strictly weaker local constraint on objects suffices to ensure global atomicity for actions. Thus, the local atomicity properties define precise limits on the amount of concurrency that can be permitted by an atomic type.
LCI: a social channel analysis platform for live customer intelligence

The rise of Web 2.0 with its increasingly popular social sites like Twitter, Facebook, blogs and review sites has motivated people to express their opinions publicly and more frequently than ever before. This has fueled the emerging field known as sentiment analysis whose goal is to translate the vagaries of human emotion into hard data. LCI is a social channel analysis platform that taps into what is being said to understand the sentiment with the particular ability of doing so in near real-time. LCI integrates novel algorithms for sentiment analysis and a configurable dashboard with different kinds of charts including dynamic ones that change as new data is ingested. LCI has been researched and prototyped at HP Labs in close interaction with the Business Intelligence Solutions (BIS) Division and a few customers. This paper presents an overview of the architecture and some of its key components and algorithms, focusing in particular on how LCI deals with Twitter and illustrating its capabilities with selected use cases.
A CMOS Low-Dropout Regulator With Dominant-Pole Substitution

A dominant-pole substitution (DPS) technique for low-dropout regulator (LDO) is proposed in this paper. The DPS technique involves signal-current feedforward and amplification such that an ultralow-frequency zero is generated to cancel the dominant pole of LDO, while a higher frequency pole substitutes in and becomes the new dominant pole. With DPS, the loop bandwidth of the proposed LDO can be significantly extended, while a standard value and large output capacitor for transient purpose can still be used. The resultant LDO benefits from both the fast response time due to the wide loop bandwidth and the large charge reservoir from the output capacitor to achieve the significant enhancement in the dynamic performances. Implemented with a commercial 0.18-μm CMOS technology, the proposed LDO with DPS is validated to be capable of delivering 100 mA at 1.0-V output from a 1.2-V supply, with current efficiency of 99.86%. Experimental results also show that the error voltage at the output undergoing 100 mA of load transient in 10-ns edge time is about 25 mV. Line transient responses reveal that no more than 20-mV instantaneous changes at the output when the supply voltage swings between 1.2 and 1.8 V in 100 ns. The power-supply rejection ratio at 3 MHz is -47 dB.
The IFC Standard - A Review of History, Development, and Standardization

IFC (Industry Foundation Classes) is an open and standardized data model intended to enable interoperability between building information modeling software applications in the AEC/FM industry. IFC has been in development by an industry consortium since 1994, and since the start of the effort, the evolving industry context, standardization organization, resource availability, and technology development have exposed the standardization process to a dynamic environment. While the overarching mission of IFC standardization has always been to enable interoperability between AEC/FM software applications, the approach for how best to operationalize that mission has changed over the years. Through a literature review supported by the general theory on IT standardization, this study follows the development process of the IFC standard from its origins in the early 1990s to its latest activities in 2012. The end result is both a descriptive review of the history of IFC standardization and the establishment of an initial connection to IT standardization research for the IFC standard by profiling the effort in accordance with existing IT standardization theories and typologies. The review highlights the evolution of IFC standardization through several distinct phases, and its gradual movement from emphasizing technical architecture development towards growing involvement in specifying the processes facilitating its use. The organization behind the standard has also seen changes in its modus operandi, from initially being a closed and loosely coupled alliance to evolving into a consortium incorporating open hybrid standardization, where a formal standards body publishes the standards prepared by the consortium. The consortium has faced many challenges compiling an ambitious interoperability standard with few resources, and were it not for the growing demand for the standard provided by public actors, momentum and enthusiasm for the effort might have petered out due to slow market uptake and low use of the data standard in actual construction projects thus far. While this paper does not investigate the adoption phenomenon in-depth, the moderate uptake of the standard can perhaps be explained to be a symptom of the slow adoption of collaborative model-based construction processes and industry reluctance to switch over to new IT tools, which in turn are prerequisites for the existence of demand for an open interoperability standard.
Syntax highlighting in business process models

Sense-making of process models is an important task in various phases of business process management initiatives. Despite this, there is currently hardly any support in business process modeling tools to adequately support model comprehension. In this paper we adapt the concept of syntax highlighting to workflow nets, a modeling technique that is frequently used for business process modeling. Our contribution is three-fold. First, we establish a theoretical argument to what extent highlighting could improve comprehension. Second, we formalize a concept for syntax highlighting in workflow nets and present a prototypical implementation with the WoPeD modeling tool. Third, we report on the results of an experiment that tests the hypothetical benefits of highlighting for comprehension. Our work can easily be transferred to other process modeling tools and other process modeling techniques.