nils-herrmann/clean_scirepeval huggingface dataset:
OntoSOC: Sociocultural Knowledge Ontology

This paper presents a sociocultural knowledge ontology (OntoSOC) modeling approach. OntoSOC modeling approach is based on Engeström‟s Human Activity Theory (HAT). That Theory allowed us to identify fundamental concepts and relationships between them. The top-down precess has been used to define differents sub-concepts. The modeled vocabulary permits us to organise data, to facilitate information retrieval by introducing a semantic layer in social web platform architecture, we project to implement. This platform can be considered as a « collective memory » and Participative and Distributed Information System (PDIS) which will allow Cameroonian communities to share an co-construct knowledge on permanent organized activities.
User-Centered Design: An Integrated Approach

This book results from a decade of presenting the user-centered design (UCD) methodology for hundreds of companies (p. xxiii) and appears to be the book complement to the professional development short course. Its purpose is to encourage software developers to focus on the total user experience of software products during the whole of the development cycle. The notion of the “total user experience” is valuable because it focuses attention on the whole product-use cycle, from initial awareness through productive use.
Real-Time Ray Tracing Using Nvidia OptiX

Modern GPUs with their several hundred cores and more accessible programming models are becoming attractive devices for compute-intensive applications. They are particularly well suited for applications, such as image processing, where the end result is intended to be displayed via the graphics card. One of the more versatile and powerful graphics techniques is ray tracing. However, tracing each ray of light in a scene is very computational expensive and have traditionally been preprocessed on CPUs over hours, if not days. In this paper, Nvidia’s new OptiX ray tracing engine is used to show how the power of modern graphics cards, such as the Nvidia Quadro FX 5800, can be harnessed to ray trace several scenes that represent real-life applications in real-time speeds ranging from 20.63 to 67.15 fps. Near-perfect speedup is demonstrated on dual GPUs for scenes with complex geometries. The impact on ray tracing of the recently announced Nvidia Fermi processor, is also discussed.
The therapeutic value of laughter in medicine.

The aim of this review is to identify, critically evaluate, and summarize the laughter literature across a number of fields related to medicine and health care to assess to what extent laughter health-related benefits are currently supported by empirical evidence.



A comprehensive laughter literature search was performed. A thorough search of the gray literature was also undertaken. A list of inclusion and exclusion criteria was identified.



It was necessary to distinguish between humor and laughter to assess health-related outcomes elicited by laughter only.



Thematic analysis was applied to summarize laughter health-related outcomes, relationships, and general robustness.



Laughter has shown physiological, psychological, social, spiritual, and quality-of-life benefits. Adverse effects are very limited, and laughter is practically lacking in contraindications. Therapeutic efficacy of laughter is mainly derived from spontaneous laughter (triggered by external stimuli or positive emotions) and self-induced laughter (triggered by oneself at will), both occurring with or without humor. The brain is not able to distinguish between these types; therefore, it is assumed that similar benefits may be achieved with one or the other. Although there is not enough data to demonstrate that laughter is an all-around healing agent, this review concludes that there exists sufficient evidence to suggest that laughter has some positive, quantifiable effects on certain aspects of health. In this era of evidence-based medicine, it would be appropriate for laughter to be used as a complementary/alternative medicine in the prevention and treatment of illnesses, although further well-designed research is warranted.
DESIGN OF A YAGI-UDA ANTENNA WITH GAIN AND BANDWIDTH ENHANCEMENT FOR WI-FI AND WIMAX APPLICATIONS

There are various patch antennas used for Wi-Fi and Wi-MAX applications. But, the problems with them are low gain, low power handling capacity and hence, conventional yagi-uda antennas are used. Conventional yagi-uda antennas are used in applications where high gain and directionality are required. Generally, number of directors are added to increase gain of these antennas. But, here we present modified yagi-uda antennas, in which the gain and bandwidth can be enhanced by not adding additional directors. In this paper, we initially discuss the designs of various yagi-uda antennas with uniform, non-uniform spacings between directors and then we discuss their gain and bandwidth enhancement by various approaches. Simulation results shows that, the proposed techniques can enhance gain as well as bandwidth when compared with the traditional yagi-uda antennas.
Comprehensive Load-Shedding System

The availability of reliable electrical power supply for petrochemical industries is extremely important not only to maintain continuous production but also from the point of view of overall plant safety. The costs, caused by production losses, due to a partial or a complete blackout easily run up to millions of dollars per blackout. If a proper load-shedding scheme is implemented, it is possible to save a plant from such occurrences. A lack of electrical power can be caused by loss of generation capacity or disconnection from the public power company supply. The load-shedding system ensures the availability of electrical power to all essential and most critical loads in the plant. This is achieved by switching off nonessential loads in the case of a lack of power in the plant electrical network, or parts of the plant electrical network. This paper discusses a comprehensive load-shedding scheme for industrial applications with a background on a similar system implemented at large integrated complexes such as refineries and petrochemical plants.
State Aware Imitation Learning

Imitation learning is the study of learning how to act given a set of demonstrations provided by a human expert. It is intuitively apparent that learning to take optimal actions is a simpler undertaking in situations that are similar to the ones shown by the teacher. However, imitation learning approaches do not tend to use this insight directly. In this paper, we introduce State Aware Imitation Learning (SAIL), an imitation learning algorithm that allows an agent to learn how to remain in states where it can confidently take the correct action and how to recover if it is lead astray. Key to this algorithm is a gradient learned using a temporal difference update rule which leads the agent to prefer states similar to the demonstrated states. We show that estimating a linear approximation of this gradient yields similar theoretical guarantees to online temporal difference learning approaches and empirically show that SAIL can effectively be used for imitation learning in continuous domains with non-linear function approximators used for both the policy representation and the gradient estimate.
Foodie fooderson a conversational agent for the smart kitchen

Conversational agents aim to offer an alternative to traditional methods for humans to engage with technology. This can mean to reduce the effort to complete a task using reasoning capabilities and by exploiting context, or allow voice interaction when traditional methods are not available or inconvenient. This paper introduces Foodie Fooderson, a conversational kitchen assistant built using IBM Watson technology. The aim of Foodie is to minimize food wastage by optimizing the use of groceries and assist families in improving their eating habits through recipe recommendations taking into account personal context, such as allergies and dietary goals, while helping reduce food waste and managing grocery budgets. This paper discusses Foodie’s architecture, use and benefits. Foodie uses services from CAPRecipes—our context-aware personalized recipe recommender system, SmarterContext—our personal context management system, and selected publicly available nutrition databases. Foodie reasons using IBM Watson’s conversational services to recognize users’ intents and understand events related to the users and their context. We also discuss our experiences in building conversational agents with Watson, including desired features that may improve the development experience with Watson for creating rich conversations in this exciting era of cognitive computing.
The Web SSO Standard OpenID Connect: In-depth Formal Security Analysis and Security Guidelines

Web-based single sign-on (SSO) services such as Google Sign-In and Log In with Paypal are based on the OpenID Connect protocol. This protocol enables so-called relying parties to delegate user authentication to so-called identity providers. OpenID Connect is one of the newest and most widely deployed single sign-on protocols on the web. Despite its importance, it has not received much attention from security researchers so far, and in particular, has not undergone any rigorous security analysis.In this paper, we carry out the first in-depth security analysis of OpenID Connect. To this end, we use a comprehensive generic model of the web to develop a detailed formal model of OpenID Connect. Based on this model, we then precisely formalize and prove central security properties for OpenID Connect, including authentication, authorization, and session integrity properties.In our modeling of OpenID Connect, we employ security measures in order to avoid attacks on OpenID Connect that have been discovered previously and new attack variants that we document for the first time in this paper. Based on these security measures, we propose security guidelines for implementors of OpenID Connect. Our formal analysis demonstrates that these guidelines are in fact effective and sufficient.
Visual Classification of Furniture Styles

Furniture style describes the discriminative appearance characteristics of furniture. It plays an important role in real-world indoor decoration. In this article, we explore the furniture style features and study the problem of furniture style classification. Differing from traditional object classification, furniture style classification aims at classifying different furniture in terms of the “style” that describes its appearance (e.g., American style, Gothic style, Rococo style, etc.) rather than the “kind” that is more related to its functional structure (e.g., bed, desk, etc.). To pursue efficient furniture style features, we construct a novel dataset of furniture styles that contains 16 common style categories and implement three strategies with respect to two categories of classification, that is, handcrafted classification and learning-based classification. First, we follow the typical image classification pipeline to extract the handcrafted features and train the classifier by support vector machine. Then we use the convolutional neural network to extract learning-based features from training images. To obtain comprehensive furniture style features, we finally combine the handcrafted image classification pipeline and the learning-based network. We experimentally evaluate the performances of handcrafted features and learning-based features of each strategy, and the results show the superiority of learning-based features and also the comprehensiveness of handcrafted features.
Cell-Type-Specific Activity in Prefrontal Cortex during Goal-Directed Behavior

The prefrontal cortex (PFC) plays a key role in controlling goal-directed behavior. Although a variety of task-related signals have been observed in the PFC, whether they are differentially encoded by various cell types remains unclear. Here we performed cellular-resolution microendoscopic Ca(2+) imaging from genetically defined cell types in the dorsomedial PFC of mice performing a PFC-dependent sensory discrimination task. We found that inhibitory interneurons of the same subtype were similar to each other, but different subtypes preferentially signaled different task-related events: somatostatin-positive neurons primarily signaled motor action (licking), vasoactive intestinal peptide-positive neurons responded strongly to action outcomes, whereas parvalbumin-positive neurons were less selective, responding to sensory cues, motor action, and trial outcomes. Compared to each interneuron subtype, pyramidal neurons showed much greater functional heterogeneity, and their responses varied across cortical layers. Such cell-type and laminar differences in neuronal functional properties may be crucial for local computation within the PFC microcircuit.
Text Mining - Knowledge extraction from unstructured textual data

In the general context of Knowledge Discovery, speciic techniques , called Text Mining techniques, are necessary to extract information from unstructured textual data. The extracted information can then be used for the classiication of the content of large textual bases. In this paper, we present two examples of information that can be automatically extracted from text collections: probabilistic associations of keywords and prototypical document instances. The Natural Language Processing (NLP) tools necessary for such extractions are also presented.
Effect of conjugated linoleic acids, vitamin E and their combination on the clinical outcome of Iranian adults with active rheumatoid arthritis.

Despite beneficial effects of conjugated linoleic acids (CLAs) in animal studies, there is little information on their effects on human inflammatory and autoimmune diseases.



To investigate the effects of CLAs as an adjuvant therapy on the clinical manifestations of rheumatoid arthritis (RA) in adults with an active disease.



In a randomized, double-blind placebo-controlled trial, 87 patients with active RA were divided into four groups receiving one of the following daily supplements for 3 months: group C: CLAs 2.5 g equivalent to 2 g mixture of cis 9-trans 11 and trans 10-cis12 CLAs at a rate of 50/50; group E: vitamin E: 400 mg; group CE: CLAs and vitamin E at above doses; group P: placebo. Serum alpha-tocopherol was determined by high-performance liquid chromatography. Clinical data was determined by physician examination and filling the questionnaire by interview. Complete blood count (CBC), erythrocyte sedimentation rate (ESR), C-Reactive protein (CRP) and rheumatoid factor (RF) were measured in each patient. DAS28 (diseases activity score) was also determined.



A 3-month supplementation resulted significant reduction in DAS28, pain and morning stiffness in the groups C and CE compared with group P (P < 0.05). Compared with the baseline, ESR levels decreased significantly in the groups C (P < or = 0.05), E (P < or = 0.05) and CE (P < or = 0.001). Group CE had significantly lower ESR levels than group P (P v 0.05). CRP dropped non-significantly in all four groups (P > 0.1). The reduction of white blood cell count was significant in group CE compared with other groups (P < 0.05). Decrease in platelet count was non-significant in groups CE, C, and E. Changes in RF, body mass index, red blood cell count and hemoglobin were not significant in four groups, while RF decreased non-significantly in groups CE and E. In comparison with the baseline, alpha-tocopherol increased significantly in groups C (P < or = 0.05), E (P < or = 0.01) and CE (P < or = 0.001) and in groups E and CE compared with group P.



CLA supplementation resulted in significant improvement in clinical manifestation among RA patients and may be useful in their treatments.
IGFTT: towards an efficient alternative to SIFT and SURF

The invariant feature detectors are essential components in many computer vision applications, such as tracking, simultaneous localization and mapping (SLAM), image search, machine vision, object recognition, 3D reconstruction from multiple images, augmented reality, stereo vision, and others. However, it is very challenging to detect high quality features while maintaining a low computational cost. Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) algorithms exhibit great performance under a variety of image transformations, however these methods rely on costly keypoint’s detection. Recently, fast and efficient variants such as Binary Robust Invariant Scalable Keypoints (BRISK) and Oriented Fast and Rotated BRIEF (ORB) were developed to offset the computational burden of these traditional detectors. In this paper, we propose to improve the Good Features to Track (GFTT) detector, coined IGFTT. It approximates or even outperforms the state-of-art detectors with respect to repeatability, distinctiveness, and robustness, yet can be computed much faster than Maximally Stable Extremal Regions (MSER), SIFT, BRISK, KAZE, Accelerated KAZE (AKAZE) and SURF. This is achieved by using the search of maximal-minimum eigenvalue in the image on scale-space and a new orientation extraction method based on eigenvectors. A comprehensive evaluation on standard datasets shows that IGFTT achieves quite a high performance with a computation time comparable to state-of-the-art real-time features. The proposed method shows exceptionally good performance compared to SURF, ORB, GFTT, MSER, Star, SIFT, KAZE, AKAZE and BRISK.
Towards an Information Systems Design Research Framework: A Critical Realist Perspective

Information Systems (IS) research has a serious utilization and relevance problem. To increase IS research utilization and relevance, scholars argue that the mainstream IS research, which is based on the behavioral science paradigm, should be complemented with research based on the design science paradigm. The current IS design science frameworks and approaches have a strong focus on the IT artifact, in most cases an exclusive focus on the IT artifact. The frameworks and approaches have very little discussions and clarifications regarding underpinning philosophies, but most seem to be based on positivism, traditional realism, or pragmatism. This paper presents an alternative framework for IS design science research. The framework builds on that the aim of IS design science research is to develop practical knowledge for the design and realization of different classes of IS initiatives, where IS are viewed as sociotechnical systems and not just IT artifacts. The underpinning philosophy of the framework is critical realism which has been developed as an alternative to positivism and traditional realism as well as to constructivism (relativism). The framework proposes that the output of IS design science research is practical IS design knowledge in the form of field-tested and grounded technological rules. The IS design knowledge is developed through an IS design science research cycle. The paper presents how technological rules can be developed as well as the nature of such rules.
Belowground environmental effects of transgenic crops: a soil microbial perspective.

Experimental studies investigated the effects of transgenic crops on the structure, function and diversity of soil and rhizosphere microbial communities playing key roles in belowground environments. Here we review available data on direct, indirect and pleiotropic effects of engineered plants on soil microbiota, considering both the technology and the genetic construct utilized. Plants modified to express phytopathogen/phytoparasite resistance, or traits beneficial to food industries and consumers, differentially affected soil microorganisms depending on transformation events, experimental conditions and taxa analyzed. Future studies should address the development of harmonized methodologies by taking into account the complex interactions governing soil life.
Economic evaluation of telemedicine: review of the literature and research guidelines for benefit-cost analysis.

Telemedicine programs provide specialty health services to remote populations using telecommunications technology. This innovative approach to medical care delivery has been expanding for several years and currently covers various specialty areas such as cardiology, dermatology, and pediatrics. Economic evaluations of telemedicine, however, remain rare, and few of those conducted have accounted for the wide range of economic costs and benefits. Rigorous benefit-cost analyses of telemedicine programs could provide credible and comparative evidence of their economic viability and thus lead to the adoption and/or expansion of the most successful programs. To facilitate more advanced economic evaluations, this article presents research guidelines for conducting benefit-cost analyses of telemedicine programs, emphasizing opportunity cost estimation, commonly used program outcomes, and monetary conversion factors to translate outcomes to dollar values. The article concludes with specific recommendations for future research.
Effective regulation of affect : An action control perspective on emotion regulation

Effective regulation of affect: An action control perspective on emotion regulation Thomas L. Webb a , Inge Schweiger Gallo b , Eleanor Miles a , Peter M. Gollwitzer c d & Paschal Sheeran a a Department of Psychology, University of Sheffield, Sheffield, UK b Departamento de Psicología Social, Universidad Complutense de Madrid, Madrid, Spain c Department of Psychology, New York University, New York, USA d Department of Psychology, University of Konstanz, Konstanz, Germany
Modeling of human body movement on personal mobility interface using LIDAR

This paper proposes the contactless measurement scheme using LIDAR (Light Detection And Ranging) and the modeling human body movment for the personal mobility interface including twisting motion. We have already proposed the saddle type human body motion interface. This interface uses not only conventional translational human motions but also twisting motion, namely it makes full use of the human motion characteristics. The mechanism of the interface consists of the saddle and universal joint connecting the saddle and personal mobility, and tracing loins motion. Due to these features, the proposed interface shows a potential to realize intuitive operation in the basic experiment. However, the problems have also remained: The height of the saddle should be adjuested for the users' height before riding on the PMV (Personal Mobility Vehicle). And there are plays between the saddle and buttocks of the user, and backlash of the saddle mechanism. This problem prevents a small human motion from measurment. This paper, therefore, proposes the contactless measurement using LIDAR and discusses the fitting methods from measured data points to human body movement.
A Model for Information Assurance : An Integrated Approach

ISBN 0-7803-9814-9/$10.00 The model presented in this paper is an extension of work reported in 1991 by John McCumber. His model provided an abstract research and pedagogic framework for the profession. In the decade since McCumber prepared his model, Information Systems Security (INFOSEC) has evolved into Information Assurance (IA). Although the framework remains sound, the growth of the profession has suggested that changes are needed. This extension of the model accommodates the expanded needs of the IA discipline and include three temporal measures have been included.
Design of a robotic upper extremity repetitive therapy device

Intensive repetitive therapy shows promise to improve motor function and quality of life for stroke patients. Intense therapies provided by individualized interaction between the patient and rehabilitation specialist to overcome upper extremity impairment are beneficial, however, they are expensive and difficult to evaluate quantitatively and objectively. The development of a pneumatic muscle (PM) driven therapeutic device, the RUPERT/spl trade/ has the potential of providing a low cost and safe take-home method of supplementing therapy in addition to in the clinic treatment. The device can also provide real-time, objective assessment of functional improvement from the therapy.