Miracle-dz/UniFAR-FTUs huggingface dataset:
The e ¤ ect of R & D tax credits on rm performance

Norwegian business spending on R&D is rather low by OECD standards. In 2002 the Norwegian government introduced a tax based incentive, SkatteFUNN, in order to stimulate business R&D. We analyse the e¤ects of SkatteFUNN on rm performance using Norwegian micro data. Our estimates of reduced form productivity equations are generally in line with results in the literature. R&D spending stimulates productivity growth at the rm level even after controlling for a number of possible e¤ects relating to industries, types of innovation, common shocks etc. The e¤ect of the tax credit is generally not signi cant in these models. The interpretation is that to the extent that the tax credit increases R&D, its e¤ect is captured by our R&D variables just like R&D spending in general. JEL classi cation: C33; C52; D24; O38
Log analysis for embedded real-time operating system based on state machine

Testing is critical for testers to verify embedded real-time operating system's (RTOS) design and find run time problem. Current testing methods for RTOS are mainly based on manual measurement. These methods are inefficient and error-prone. State machine based log analysis need a state machine model for the operation at first. Then drive by system log messages, the state machine can under test itself and find out problems when the operation do not meet the specification. We apply this method in RTOS testing and conclude that the state machine based log analysis is helpful for us to test RTOS quickly and efficiently.
Implementation of Multi-view Generation System Based on DIBR

Although more and more 3D display technology is proposed, 3D contents are still not rich enough to satisfy the future market. There is a rising demand on new techniques for automatically converting 2D image content to stereoscopic 3D image displays. In this paper, an efficient multi-view generation system is presented using edge restoration algorithm from depth image based rendering with adaptive directions for virtual-view images enhancement. The edge restoration algorithm provides good hole-filling with adaptive directions information, which is used to fix with virtual-view images for eliminating the rough problem and achieve high quality virtual-view images based rendering. The experimental results show that the latest scheme can achieve relatively high quality virtual-view images output.
Efficient chemical-disease identification and relationship extraction using Wikipedia to improve recall

Awareness of the adverse effects of chemicals is important in biomedical research and healthcare. Text mining can allow timely and low-cost extraction of this knowledge from the biomedical literature. We extended our text mining solution, LeadMine, to identify diseases and chemical-induced disease relationships (CIDs). LeadMine is a dictionary/grammar-based entity recognizer and was used to recognize and normalize both chemicals and diseases to Medical Subject Headings (MeSH) IDs. The disease lexicon was obtained from three sources: MeSH, the Disease Ontology and Wikipedia. The Wikipedia dictionary was derived from pages with a disease/symptom box, or those where the page title appeared in the lexicon. Composite entities (e.g. heart and lung disease) were detected and mapped to their composite MeSH IDs. For CIDs, we developed a simple pattern-based system to find relationships within the same sentence. Our system was evaluated in the BioCreative V Chemical–Disease Relation task and achieved very good results for both disease concept ID recognition (F1-score: 86.12%) and CIDs (F1-score: 52.20%) on the test set. As our system was over an order of magnitude faster than other solutions evaluated on the task, we were able to apply the same system to the entirety of MEDLINE allowing us to extract a collection of over 250 000 distinct CIDs.
Hierarchical secure virtualization model for cloud

Cloud services are providing on-demand resources via virtualization technologies. This will make cloud computing a potential target for cyber attacks. Most proposed security models for virtualization are working above virtualization on host OS. Almost all proposed cloud security models suffers from this problem in that these models have very limited control over virtualization. In this paper a Hierarchical Secure Virtualization Model (HSVM) is proposed to provide threat quarantine and conquer in addition to complete control on virtualization. HSVM needs to be implemented under the virtualization level and eventually moving up to the guest OS. This security model has the potential to protect various cloud service models implemented by cloud vendors, such as IaaS, PaaS, dSaaS, and SaaS, and improves cloud vendor control level in IaaS. To the best of our knowledge, there is no similar model or implementation like HSVM, able to protect the cloud from DDoS attack, unauthorized access, data leakage as well.
The Sensation Seeking Tendency and the Fashion Exploratory Behavior according to the Difference Age

To pursue youth and agelessness can be regarded as a global trend today. The younger a woman recognizes herself to be, the more sensation seeking tendency and the more active fashion exploratory behavior of younger generation she would show. This study attempted to empirically examine the relationship between sensation seeking behavior and fashion exploratory behavior according to the difference age in women in their 30's to 50s'. After the survey, a total of 480 questionnaires was used for data analysis. The results of this study are as follows, 1. It was found that there was a very high correlation among cognitive ages, and the lower cognitive age a woman had, the higher difference age she showed. 2. Sensation seeking tendency of adult women was shown in two factors of change seeking and artistic sensation seeking, and these factors accounted for 73.99% of the total variances. Fashion exploratory behavior had 4 factors such as fashion leadership, behavior of hedonic shopping, behavior of clothing communication and behavior of clothing purchase with taking a risk, and these four factors accounted for 75.87% of the total variances. 3. The higher difference age and the higher tendency of sensation seeking an adult woman had, the higher fashion exploratory behavior was shown, and the higher the difference age, the higher tendency of change seeking and artistic sensation seeking.
Auto-Assessor: Computerized Assessment System for Marking Student's Short-Answers Automatically

A number of Learning Management Systems (LMSs) exist on the market today. A subset of a LMS is the component in which student assessment is managed. In some forms of assessment, such as short-answer questions, the LMS is incapable of evaluating the students' responses and therefore human intervention is necessary. This study leverages the research conducted in recent Natural Language Processing studies to provide a fair, timely and accurate assessment of student short-answers based on the semantic meaning of those answers. A component-based system utilizing a Text Pre-Processing phase and a Word/Synonym Matching phase has been developed to automate the marking process. An evaluation plan is also made to verify the possibility of applying such computerized assessment system in practical situations as well as to reveal areas in which the system could be improved later.
A magnetoencephalographic study of sensorimotor activity differences during unilateral and bilateral forearm movements

This study compared activation of the sensorimotor area using magnetoencephalography after unilateral and bilateral movements. Thirteen healthy individuals and a patient with mild hemiplegia performed unilateral and bilateral forearm pronation movements. Among healthy participants, there were no significant differences in motor-evoked field during unilateral and bilateral movements, and equivalent current dipoles were located around the sensorimotor area. In the patient, motor-evoked field was measured in the lesional hemisphere clearly during bilateral movements, and the locus of equivalent current dipoles was estimated to be around the mean location in healthy individuals. In contrast, unilateral movements were estimated outside the area of sensorimotor activation. We speculate that bilateral movements may be more effective for functional recovery during rehabilitation.
The Application of Semantic Classification Trees to Natural Language Understanding

This article describes a new method for building a natural language understanding (NLU) system, in which the system's rules are learnt automatically from training data. The method has been applied to design of a speech understanding (SU) system. Designers of such systems rely increasingly on robust matchers to perform the task of extracting meaning from one or several word sequence hypotheses generated by a speech recognizer. We describe a new data structure, the semantic classification tree (SCT), that learns semantic rules from training data and can be a building block for robust matchers for NLU tasks. By reducing the need for handcoding and debugging a large number of rules, this approach facilitates rapid construction of an NLU system. In the case of an SU system, the rules learned by an SCT are highly resistant to errors by the speaker or by the speech recognizer because they depend on a small number of words in each utterance. Our work shows that semantic rules can be learned automatically from training data, yielding successful NLU for a realistic application. >
The Private Memory of Aggregate Shocks

We study constrained efficient aggregate risk sharing and its consequence for the behavior of macro-aggregates in a dynamic Mirrlees’s (1971) setting. Privately observed idiosyncratic productivity shocks are assumed to be independent of i.i. d. publicly observed aggregate shocks. Yet, private allocations display memory with respect to past aggregate shocks, when idosyncratic shocks are also i.i. d. Under a mild restriction on the nature of optimal allocations the result extends to more persistent idiosyncratic shocks, for all but the limit at which idiosyncratic risk disappears, and the model collapses to a pure heterogeneity repeated Mirrlees economy identical to Werning [2007]. When preferences are iso-elastic we show that an allocation is memoryless only if it displays a strong form of separability with respect to aggregate shocks. Separability characterizes the pure heterogeneity limit as well as the general case with log preferences. With less than full persistence and risk aversion different from unity both memory and non-separability characterize optimal allocations. Exploiting the fact that non-separability is associated with state-varying labor wedges, we apply a business cycle accounting procedure (e.g. Chari et al. [2007]) to the aggregate data generated by the model. We show that, whenever risk aversion is great than one our model produces efficient counter-cyclical labor wedges.
An Enhanced Web-based Platform for Mobile Learning Management System

mobile learning management system which promotes the learner’s knowledge, and the entire individual learning system. Though traditional but formal, the classroom has being the adopted way of teaching and learning in most institutions. In this type of learning, students can miss lectures for reasons beyond their control. It is for these reasons that the research and development of a web-based platform for mobile learning is of essence. Making learning mobile and informal can actually provide the required solution. This work presents an enhanced web-based platform solution for mobile learning management system for addressing these problems. The inclusion of an online quiz in the system aids students to know how to properly study the learning materials presented by each specific lecturer and this increases their learning speed and ability. The system therefore is an improvement on the system presented by [1]. The development architecture of the system consists of the Interactive layer, Logic layer, Access layer, and the Storage layer. The Interactive layer is the user interface which is made up of the system user, the mobile devices used to access the internet and also context discovery. The implementation was carried out using Adobe Dreamweaver and Xampp server. The evaluation of the system showed that the practice of mLearning will considerably improve learning system in different facets of learning.
Cost-effectiveness of trastuzumab in the adjuvant treatment of early breast cancer: a model-based analysis of the HERA and FinHer trial.

BACKGROUND Routine adjuvant administration of trastuzumab (T) has been implemented in most centers, but its economic impact has not yet been well examined. METHODS A Markov model was constructed based on clinical data of the Herceptin Adjuvant (HERA) and the Finland Herceptin (FinHer) trials. Costs from the perspective of a Swiss health care provider were calculated based on resource use. RESULTS On the basis of HERA data, our model yielded an overall survival rate of 71.8% for the T group versus 62.8% for the control group [risk ratio (RR) = 0.87) after 10 years and 62.9% versus 52.7% (RR = 0.84) after 15 years. Cost-effectiveness resulted in 40505 Euros (EUR) per life years gained (LYG) after 10 years and 19673 EUR per LYG after 15 years. For the FinHer regimen, overall survival after 10 and 15 years resulted in 81.8% versus 66.1% (RR = 0.81) and 73.6% versus 57.0% (RR = 0.77). Costs of 8497 EUR per patient could be saved after 10 years and 9256 EUR after 15 years compared with the control group. CONCLUSION In a long-term perspective, adjuvant T based on the HERA regimen can be considered cost-effective. The regimen used in the FinHer trial is even cost saving, but estimations are based on a single small trial.
How to Train a Compact Binary Neural Network with High Accuracy?

How to train a binary neural network (BinaryNet) with both high compression rate and high accuracy on large scale dataset? We answer this question through a careful analysis of previous work on BinaryNets, in terms of training strategies, regularization, and activation approximation. Our findings first reveal that a low learning rate is highly preferred to avoid frequent sign changes of the weights, which often makes the learning of BinaryNets unstable. Secondly, we propose to use PReLU instead of ReLU in a BinaryNet to conveniently absorb the scale factor for weights to the activation function, which enjoys high computation efficiency for binarized layers while maintains high approximation accuracy. Thirdly, we reveal that instead of imposing L2 regularization, driving all weights to zero which contradicts with the setting of BinaryNets, we introduce a regularization term that encourages the weights to be bipolar. Fourthly, we discover that the failure of binarizing the last layer, which is essential for high compression rate, is due to the improper output range. We propose to use a scale layer to bring it to normal. Last but not least, we propose multiple binarizations to improve the approximation of the activations. The composition of all these enables us to train BinaryNets with both high compression rate and high accuracy, which is strongly supported by our extensive empirical study.
Extending touch: towards interaction with large-scale surfaces

Touch is a very intuitive modality for interacting with objects displayed on arbitrary surfaces. However, when using touch for large-scale surfaces, not every point is reachable. Therefore, an extension is required that keeps the intuitivity provided by touch: pointing. We will present our system that allows both input modalities in one single framework. Our method is based on 3D reconstruction, using standard RGB cameras only, and allows seamless switching between touch and pointing, even while interacting. Our approach scales very well with large surfaces without modifying them. We present a technical evaluation of the system's accuracy, as well as a user study. We found that users preferred our system to a touch-only system, because they had more freedom during interaction and could solve the presented task significantly faster.
The Spread of a Rumour – the Growth and Diffusion of Golf in Norway

Abstract This article discusses the spread and growth of Norwegian golf from 1985 to 2005. Finding that the number of golf players is following a shape that resembles a logistic growth curve, we look at the governing processes behind this development. We use the metaphor of ‘spreading the rumour’ to symbolise this development, seeing golf as an innovation that has been diffused in Norwegian society mostly via word of mouth. However, in order to explain the growth and diffusion, this metaphor needed sociological support. Concepts like social distinction, cultural imperialism, globalisation, and innovation diffusion were discussed in relation to the empirical data. The empirical data shows the closest fit to the mechanisms that Rogers (2003) claims determine the diffusion of innovations in a society. First, the decision process behind adopting golf consists of five stages: knowledge, persuasion, decision, implementation and confirmation. The decision to start playing golf seems to correspond to these stages. Second, there are certain attributes of golf that determine golf’s rate of adoption. We present and discuss findings that specify which attributes appeal to prospective golf players. Third, the tendency of adopting innovations is assumed to be normally distributed in a society. Findings indicate that three of five adopter categories have already been recruited in Norwegian golf. Fourth, the spread of the innovations takes place within certain diffusion networks. In Norway these networks are both homophilous and heterophilous. In addition, some factors in the Norwegian society, like social class, political and economic institutions, values and norms, worked as constraints against the “spread of the rumour” (i.e. the game of golf). In this paper we also point at some important implications for sport management and sport policy, golf organisations, golf clubs and golf investors.
Comparative assessment of fluorescent proteins for in vivo imaging in an animal model system

Fluorescent protein tags are fundamental tools used to visualize gene products and analyze their dynamics in vivo. Recent advances in genome editing have enabled precise insertion of fluorescent protein tags into the genomes of diverse organisms. These advances expand the potential of in vivo imaging experiments, and they facilitate experimentation with new, bright, photostable fluorescent proteins. Most quantitative comparisons of the brightness and photostability of different fluorescent proteins have been made in vitro, removed from biological variables that govern their performance in cells or organisms. To address the gap we quantitatively assessed fluorescent protein properties in vivo in an animal model system. We generated transgenic C. elegans strains expressing green, yellow, or red fluorescent proteins in embryos, and we imaged embryos expressing different fluorescent proteins under the same conditions for direct comparison. We found that mNeonGreen was not bright in vivo as predicted based on in vitro data, but that mNeonGreen is a better tag than GFP for specific kinds of experiments, and we report on optimal red fluorescent proteins. These results identify ideal fluorescent proteins for imaging in vivo in C. elegans embryos, and they suggest good candidate fluorescent proteins to test in other animal model systems. Abbreviations FP fluorescent protein GFP green fluorescent protein mNG monomeric neon green mYPet monomeric yellow fluorescent protein for energy transfer CRISPR clustered, regularly interspersed, short palindromic repeats
Design and analysis of AC to DC converters for input Power Factor Correction

In this paper various control techniques for power factor improvement are analyzed and simulated using MATLAB software. Various applications need to regulate the output dc voltage with excellent performance characteristics. Till now the circuitry involved for utility interface was a diode rectifier and a capacitor filter. Thus several agencies had started imposing certain recommendations and standards for equipments connected to the utility such that input current harmonics is reduced thus implying on the improvement of power factor.
TofCut: Towards Robust Real-time Foreground Extraction using Time-of-flight Camera

Foreground extraction for live video sequence is a challenging task in vision. Traditional methods often make various assumptions to simplify the problem, which make them less robust in real-world applications. Recently, Time-ofFlight (TOF) cameras provide a convenient way to sense the scene depth at video frame-rate. Compared to the appearance or motion cues, depth information is less sensitive to environment changes. Motivated by the fact that TOF cameras have not been widely used in video segmentation application, we in this paper investigate the problem of performing robust, real-time bi-layer segmentation using a TOF camera and propose an effective algorithm named TofCut. TofCut combines color and depth cues in a unified probabilistic fusion framework and a novel adaptive weighting scheme is employed to control the influence of these two cues intelligently. By comparing our segmentation results with ground truth data, we demonstrate the effectiveness of TofCut on an extensive set of experimental results.
A Look at Variables Affecting Parent Satisfaction with IEP Meetings.

A study examined the influence of professional etiquette, procedural factors, demographic factors, and child eligibility code factors on parent satisfaction with Individualized Education Programs (IEPs). Surveys and interviews were conducted with 207 parents in the Southwest border region whose children had been evaluated for special education services and who had attended an IEP meeting. Results indicate that each of the four independent variables influenced satisfaction with IEP meetings. Direct positive relationships existed when professional etiquette and procedural factors were examined as sole indicators of satisfaction. Three features of parent and child demographics demonstrated inverse relationships to satisfaction. Those were family income, parent education, and male participant attending with spouse/partner. With regard to student eligibility codes, less satisfaction was reported for meetings held for children with physical or health impairments. When viewed as part of an interaction, all four independent variables revealed significance. Either in first-level or second-level interactions, demographic features, annual family income, and parent education showed interaction with etiquette and procedural factors. Ethnicity had no effect on satisfaction scores. The eligibility code of physical or health impairments continued to be significant when combined with other independent variables. Recommendations include training professionals and parents regarding special education and IEPs; simplifying educational jargon; following through with IEP provisions; having appropriate personnel present at IEP meetings; and ensuring the environment is conducive to decision making. (Contains 29 references). (TD) Reproductions supplied by EDRS are the best that can be made from the ori inal document. A Look at Variables Affecting Parent Satisfaction with IEP Meetings PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY