nils-herrmann/clean_scirepeval huggingface dataset:
A dual-systems perspective on addiction: contributions from neuroimaging and cognitive training.

Dual-systems theories explain lapses in self-control in terms of a conflict between automatic and deliberative modes of behavioral control. Numerous studies have now tested whether the brain areas that control behavior are organized in a manner consistent with dual-systems models. Brain regions directly associated with the mesolimbic dopamine system, the nucleus accumbens and ventromedial prefrontal cortex in particular, capture some of the features assumed by automatic processing. Regions in the lateral prefrontal cortex are more closely linked to deliberative processing and the exertion of self-control in the suppression of impulses. While identifying these regions crudely supports dual-systems theories, important modifications to what constitutes automatic and deliberative behavioral control are also suggested. Experiments have identified various means by which automatic processes may be sculpted. Additional work decomposes deliberative processes into component functions such as generalized working memory, reappraisal of emotional stimuli, and prospection. The importance of deconstructing dual-systems models into specific cognitive processes is clear for understanding and treating addiction. We discuss intervention possibilities suggested by recent research, and focus in particular on cognitive training approaches to bolster deliberative control processes that may aid quit attempts.
Winding Function Approach for Winding Analysis

The winding factor is an operand in order to consider the effect of winding distribution and chording on the spatial distribution of the magnetic field in the air gap of synchronous and induction machines. The sinusoidal functions for winding factor calculation presented in literature are not defined and valid for every irregular winding, e.g., single-layer fractional-slot, combined star-delta, multilayer (greater than two), and asymmetrical windings. Although the summation of induced voltage phasors (star of slots) is the most accurate method, asymmetrical windings require to be decomposed in symmetrical components. In this paper, in addition to deriving the symmetrical components for asymmetrical multiphase windings, the analytical formulation is presented to relate the harmonic content of winding functions to winding factors. The harmonic leakage factor is accurately formulated from the winding function instead of the Görges diagram without the need for summing up an infinite number of normalized winding factors quadratically. Without restriction of the number of layers and the distribution of the winding, including full-pitch, chorded and fractional-slot symmetrical and asymmetrical windings, the suggested analysis method is validated with the star of slots and sinusoidal functions of distribution and pitch factors, where applicable.
Fast and Robust High Dynamic Range Image Generation with Camera and Object Movement

High dynamic range (HDR) images play an important role in todays computer graphics: Typical applications are the improved display of a photograph with a tone mapper and the relighting of a virtual object in a natural environment using an HDR environment map. Generating an HDR image usually requires a sequence of photographs with different exposure times which are combined to a single image. In practice two problems occur when taking an image sequence: The camera is moving or objects are moving during the sequence. This results in a blurry HDR image due to the camera movement and moving objects appear multiple times as ghost images in the combined image. In this paper, we present a simple and fast algorithm for a robust HDR generation that removes these artifacts without prior knowledge of the camera response function.
Syntactic methods for topic-independent authorship attribution

The efficacy of syntactic features for topic-independent authorship attribution is evaluated, taking a feature set of frequencies of words and punctuation marks as baseline. The features are ‘deep’ in the sense that they are derived by parsing the subject texts, in contrast to ‘shallow’ syntactic features for which a part-of-speech analysis is enough. The experiments are conducted on a corpus of novels written around the year 1900 by 20 different authors, and cover two tasks. In the first task, text samples are taken from books by one author, and the goal is to pair samples from the same book. In the second task, text samples are taken from several authors, but only one sample from each book, and the goal is to pair samples from the same author. In the first task, the baseline feature set outperformed the syntax-based feature set, but for the second task, the outcome was the opposite. This suggests that, compared to lexical features such as vocabulary and punctuation, syntactic features are more robust to changes in topic.
Real-time object tracking via CamShift-based robust framework

In recent years, lots of object tracking methods have been presented for better tracking accuracies. However, few of them can be applied to the real-time applications due to high computational cost. Aiming at achieving better realtime tracking performance, we propose an adaptive robust framework for object tracking based on the CamShift approach, which is notable for its simplicity and high processing efficiency. An adaptive local search method is presented to search for the best object candidate to avoid that the CamShift tracker gets confused by the surrounding background and erroneously incorporates it into the object region. A Kalman filter is also incorporated into our framework for prediction of the object's movement, so as to reduce the search effort and possible tracking failure caused by fast object motion. The experimental results demonstrate that the proposed tracking framework is robust and computationally effective.
Cruciform: Solving Crosswords with Natural Language Processing

Crossword puzzles are popular word games that require not only a large vocabulary, but also a broad knowledge of topics. Answering each clue is a natural language task on its own as many clues contain nuances, puns, or counter-intuitive word definitions. Additionally, it can be extremely difficult to ascertain definitive answers without the constraints of the crossword grid itself. This task is challenging for both humans and computers. We describe here a new crossword solving system, Cruciform. We employ a group of natural language components, each of which returns a list of candidate words with scores when given a clue. These lists are used in conjunction with the fill intersections in the puzzle grid to formulate a constraint satisfaction problem, in a manner similar to the one used in the Dr. Fill system[4]. We describe the results of several of our experiments with the system.
Text Extraction and Document Image Segmentation Using Matched Wavelets and MRF Model

In this paper, we have proposed a novel scheme for the extraction of textual areas of an image using globally matched wavelet filters. A clustering-based technique has been devised for estimating globally matched wavelet filters using a collection of groundtruth images. We have extended our text extraction scheme for the segmentation of document images into text, background, and picture components (which include graphics and continuous tone images). Multiple, two-class Fisher classifiers have been used for this purpose. We also exploit contextual information by using a Markov random field formulation-based pixel labeling scheme for refinement of the segmentation results. Experimental results have established effectiveness of our approach.
Vehicle-to-vehicle safety messaging in DSRC

This paper studies the design of layer-2 protocols for a vehicle to send safety messages to other vehicles. The target is to send vehicle safety messages with high reliability and low delay. The communication is one-to-many, local, and geo-significant. The vehicular communication network is ad-hoc, highly mobile, and with large numbers of contending nodes. The messages are very short, have a brief useful lifetime, but must be received with high probability. For this environment, this paper explores the efficacy of rapid repetition of broadcast messages. This paper proposes several random access protocols for medium access control. The protocols are compatible with the Dedicated Short Range Communications (DSRC) multi-channel architecture. Analytical bounds on performance of the proposed protocols are derived. Simulations are conducted to assess the reception reliability and channel usage of the protocols. The sensitivity of the protocol performance is evaluated under various offered traffic and vehicular traffic flows. The results show our approach is feasible for vehicle safety messages in DSRC.
An integrated approach to testing complex systems

The increasing complexity of today’s testing scenarios for complex systems demands an integrated, open, and flexible approach to support the management of the overall test process. “Classical” model-based testing approaches, where a complete and precise formal specification serves as a reference for automatic test generation, are often impractical. Reasons are, on the one hand, the absence of a suitable formal specification. As complex systems are composed of several components, either hardware or software, often pre-built and third party, it is unrealistic to assume that a formal specification exists a priori. On the other hand, a sophisticated test execution environment is needed that can handle distributed test cases. This is because the test actions and observations can take place on different subsystems of the overall system. This thesis presents a novel approach to the integrated testing of complex systems. Our approach offers a coarse grained test environment, realized in terms of a component-based test design on top of a library of elementary but intuitively understandable test case fragments. The relations between the fragments are treated orthogonally, delivering a test design and execution environment enhanced by means of light-weight formal verification methods. In this way we are able to shift the test design issues from total experts of the system and the used test tools to experts of the system’s logic only. We illustrate the practical usability of our approach by means of industrial case studies in two different application domains: Computer Telephony Integrated solutions and Web-based applications. As an enhancement of our integrated test approach we provide an algorithm for generating approximate models for complex systems a posteriori. This is done by optimizing a standard machine learning algorithm according to domain-specific structural properties, i.e. properties like prefix-closeness, input-determinism, as well as independency and symmetries of events. The resulting models can never be exact, i.e. reflect the complete and correct behaviour of the considered system. Nevertheless they can be useful in practice, to represent the cumulative knowledge of the system in a consistent description.
The Role of Instructional Design in Persuasion: A Comics Approach for Improving Cybersecurity

Although computer security technologies are the first line of defence to secure users, their success is dependent on individuals’ behaviour. It is therefore necessary to persuade users to practice good computer security. Our interview analysis of users’ conceptualization of security password guessing attacks, antivirus protection, and mobile online privacy shows that poor understanding of security threats influences users’ motivation and ability to practice safe behaviours. We designed and developed an online interactive comic series called Secure Comics based on instructional design principles to address this problem. An eye-tracking experiment suggests that the graphical and interactive components of the comics direct users’ attention and facilitate comprehension of the information. In our evaluations of Secure Comics, results from several user studies show that the comics improve understanding and motivate positive changes in security management behaviour. We discuss the implication of the findings to better understand the role of instructional design and persuasion in education technology.
A Review of Human Activity Recognition Methods

Recognizing human activities from video sequences or still images is a challenging task due to problems, such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance. Many applications, including video surveillance systems, human-computer interaction, and robotics for human behavior characterization, require a multiple activity recognition system. In this work, we provide a detailed review of recent and state-of-the-art research advances in the field of human activity classification. We propose a categorization of human activity methodologies and discuss their advantages and limitations. In particular, we divide human activity classification methods into two large categories according to whether they use data from different modalities or not. Then, each of these categories is further analyzed into sub-categories, which reflect how they model human activities and what type of activities they are interested in. Moreover, we provide a comprehensive analysis of the existing, publicly available human activity classification datasets and examine the requirements for an ideal human activity recognition dataset. Finally, we report the characteristics of future research directions and present some open issues on human activity recognition.
A multi-resonant gate driver for Very-High-Frequency (VHF) resonant converters

This paper presents the design and implementation of a Very-High-Frequency (VHF) multi-resonant gate drive circuit. The design procedure is greatly simplified compared with some VHF self-oscillating multi-resonant gate drivers presented in previous works. The proposed circuit has the potential to reduce long start-up time required in a self-oscillating resonant gate drive circuit and to better utilize fast transient capability of VHF converters. A prototype resonant gate driver is demonstrated and able to reduce 60 % of the gate driving loss of a 20 MHz 32 W Class-E power amplifier with Si MOSFET.
Effect of Electrode Impedance on the Transient Response of ECG Recording Amplifiers

The transient response of ECG amplifiers is investigated in the light of the IEC 60601 performance standard for ECG recording equipment. Simulations carried out using models of several modern electrodes reveal that the undershoot limit of 100 μV and the recovery slope limit of 300 μVs-1 in response to a narrow 3 mV–100 ms rectangular pulse are violated when the recommended input impedance of 10 MΩ and a high-pass cut-off frequency of 0.05 Hz are used in the amplifier. Signal distortions have been observed which have clinical diagnostic implications. The results suggest that an amplmer input impedance exceeding 1 GΩ and a cut-off frequency somewhat lower than 0.05 Hz are necessary in order to meet the IEC 60601 performance criteria and avoid distortion of the recorded ECG signal. The authors therefore recommend that future revisions and releases of the IEC 60601 standard should include an electrical model for the skin-electrode interface in the transient response specification.
Robust Driving Path Detection in Urban and Highway Scenarios Using a Laser Scanner and Online Occupancy Grids

Many driver assistant and safety systems depend on an accurate environmental model containing the positions of stationary objects, the states of dynamic objects and information about valid driving corridors. Therefore, a robust differentiation between moving and stationary objects is required. This is challenging for laser scanners, because these sensors are not able to measure the velocity of objects directly. Therefore, an advanced occupancy grid approach, the online map, is introduced, which enables the robust separation of moving and stationary objects. The online map is used for the robust detection of the road boundaries for the determination of driving corridors in urban and highway scenarios. An algorithm for the detection of arbitrary moving objects using the online map is proposed.
A Model for Context-Specific Route Directions

Wayfinding, i.e. getting from some origin to a destination, is one of the prime everyday problems humans encounter. It has received a lot of attention in research and many (commercial) systems propose assistance in this task. We present an approach to route directions based on the idea to adapt route directions to route and environment's characteristics. The lack of such an adaptation is a major drawback of existing systems. Our approach is based on an informationand representation-theoretic analysis of routes and takes into account findings of behavioral research. The resulting systematics is the framework for the optimization process. We discuss the consequences of using an optimization process for generating route directions and outline its algorithmic realization.
Affect Regulation , Mirror Neurons , and the Third Hand : Formulating

Visual empathy through empathic art interventions are discussed in this article with respect to attachment theory; recent research on the mirror neuron system; art, empathy, and mindfulness; and an artistic strategy for crafting third-hand interventions (Kramer, 1986). A case vignette demonstrates the art therapist’s applied use of visual art responses that help to organize complex information and reflect back the emotional center of a client’s communications. With careful attunement, art therapists can develop unique, aesthetic forms of empathic resonance that will help clients feel deeply seen and develop empathy for themselves and compassion for others.
Video-based raindrop detection for improved image registration

In this paper we present a novel approach to improved image registration in rainy weather situations. To this end, we perform monocular raindrop detection in single images based on a photometric raindrop model. Our method is capable of detecting raindrops precisely, even in front of complex backgrounds. The effectiveness is demonstrated by a significant increase in image registration accuracy which also allows for successful image restoration. Experiments on video sequences taken from within a moving vehicle prove the applicability to real-world scenarios.
A review of dental CAD/CAM: current status and future perspectives from 20 years of experience.

In this article, we review the recent history of the development of dental CAD/CAM systems for the fabrication of crowns and fixed partial dentures (FPDs), based on our 20 years of experience in this field. The current status of commercial dental CAD/CAM systems developed around the world is evaluated, with particular focus on the field of ceramic crowns and FPDs. Finally, we discuss the future perspectives applicable to dental CAD/CAM. The use of dental CAD/CAM systems is promising not only in the field of crowns and FPDs but also in other fields of dentistry, even if the contribution is presently limited. CAD/CAM technology will contribute to patients' health and QOL in the aging society.
Visualization of Eye Tracking Data: A Taxonomy and Survey

This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state-of-the-art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point-based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts’ feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.
Highly Sensitive, Flexible, and Wearable Pressure Sensor Based on a Giant Piezocapacitive Effect of Three-Dimensional Microporous Elastomeric Dielectric Layer.

We report a flexible and wearable pressure sensor based on the giant piezocapacitive effect of a three-dimensional (3-D) microporous dielectric elastomer, which is capable of highly sensitive and stable pressure sensing over a large tactile pressure range. Due to the presence of micropores within the elastomeric dielectric layer, our piezocapacitive pressure sensor is highly deformable by even very small amounts of pressure, leading to a dramatic increase in its sensitivity. Moreover, the gradual closure of micropores under compression increases the effective dielectric constant, thereby further enhancing the sensitivity of the sensor. The 3-D microporous dielectric layer with serially stacked springs of elastomer bridges can cover a much wider pressure range than those of previously reported micro-/nanostructured sensing materials. We also investigate the applicability of our sensor to wearable pressure-sensing devices as an electronic pressure-sensing skin in robotic fingers as well as a bandage-type pressure-sensing device for pulse monitoring at the human wrist. Finally, we demonstrate a pressure sensor array pad for the recognition of spatially distributed pressure information on a plane. Our sensor, with its excellent pressure-sensing performance, marks the realization of a true tactile pressure sensor presenting highly sensitive responses to the entire tactile pressure range, from ultralow-force detection to high weights generated by human activity.
From Queries to Cards: Re-ranking Proactive Card Recommendations Based on Reactive Search History

The growing accessibility of mobile devices has substantially reformed the way users access information. While the reactive search by query remains as common as before, recent years have witnessed the emergence of various proactive systems such as Google Now and Microsoft Cortana. In these systems, relevant content is presented to users based on their context without a query. Interestingly, despite the increasing popularity of such services, there is very little known about how users interact with them.
 In this paper, we present the first study on user interactions with information cards. We demonstrate that the usage patterns of these cards vary depending on time and location. We also show that while overall different topics are clicked by users on proactive and reactive platforms, the topics of the clicked documents by the same user tend to be consistent cross-platform. Furthermore, we propose a supervised framework for re-ranking proactive cards based on the user's context and past history. To train our models, we use the viewport duration and clicks to infer pseudo-relevance labels for the cards. Our results suggest that the quality of card ranking can be significantly improved particularly when the user's reactive search history is %leveraged and matched against the proactive data about the cards.
Directing Gaze in 3D Models with Stylized Focus

We present an interactive system for placing emphasis in stylized renderings of 3D models. The artist chooses a camera position, an area of interest, and a rendering style for the scene. The system then automatically renders the scene with emphasis in the area of interest, an effect we call "stylized focus." Stylized focus draws the viewer's gaze to the emphasized area, through local variations in shading effects such as color saturation and contrast as well as line qualities such as texture and density. We introduce a novel algorithm for local control of line density that exhibits a degree of temporal coherence suitable for animation. Animating the area of emphasis produces an effect we call the "stylized focus pull." Finally, an eye-tracking experiment verifies that the emphasis does indeed draw the viewer's gaze to the area of interest.