nils-herrmann/clean_scirepeval huggingface dataset:
American attitudes toward nudges

To successfully select and implement nudges, policy makers need a psychological understanding of who opposes nudges, how they are perceived, and when alternative methods (e.g. forced choice) might work better. Using two representative samples, we examined four factors that influence U.S. attitudes toward nudges aEUR" types of nudges, individual dispositions, nudge perceptions, and nudge frames. Most nudges were supported, although opt out defaults for organ donations were opposed in both samples. aEURoeSystem 1aEUR nudges (e.g. defaults and sequential orderings) were viewed less favorably than aEURoeSystem 2aEUR nudges (e.g. educational opportunities or reminders) System 1 nudges were perceived as more autonomy threatening, whereas System 2 nudges were viewed as more effective for better decision making and more necessary for changing behavior. People with greater empathetic concern tended to support both types of nudges and viewed them as the aEURoerightaEUR kind of goals to have. Individualists opposed both types of nudges, and conservatives tended to oppose both types. Reactant people and those with a strong desire for control opposed System 1 nudges. To see whether framing could influence attitudes, we varied the description of the nudge in terms of the target (Personal vs. Societal) and the reference point for the nudge (Costs vs. Benefits) Empathetic people were more supportive when framing highlighted societal costs or benefits, and reactant people were more opposed to nudges when frames highlighted the personal costs of rejection.
Do People Like Nudges

In recent years, there has been a great deal of debate about the ethical questions associated with "nudges," understood as approaches that steer people in certain directions while maintaining their freedom of choice. Evidence about people's views cannot resolve the ethical questions, but in democratic societies (and nondemocratic ones as well) those views will inevitably affect what public officials are willing to do. Existing evidence, including a nationally representative survey, supports six general conclusions. First, there is widespread support for nudges of the kind that democratic societies have adopted or seriously considered in the recent past; surprisingly, that support can be found across partisan lines. While people tend to have serious objections to mandates as such, they do not have similar objections to nudges. Second, the support evaporates when people suspect the motivations of those who are engaged in nudging, and when they fear that because of inertia and inattention, citizens might end up with outcomes that are inconsistent with their interests or their values. Third, there appears to be somewhat greater support for nudges that appeal to conscious, deliberative thinking than for nudges that affect subconscious or unconscious processing, though this conclusion is highly qualified, and there can be widespread approval of the latter as well (especially if they are meant to combat self control problems) Fourth, people's assessment of nudges in general will be greatly affected by the political valence of the particular nudges that they have in mind (or that are brought to their minds) Fifth, transparency about nudging will not, in general, reduce the effectiveness of nudges, because most nudges are already transparent, and because people will not, in general, rebel against nudges. Sixth, there is preliminary but suggestive evidence of potential "reactance" against certain nudges.
Behavioral Perspective of Strategic Human Resource Management: Theoretical Causality Model

this paper is a holistic study of how value is created in organization, from behavioral perspective of strategic human resource management. Alignment between organizational strategies, human resource system and employee role behavior contribute significantly to organizational performance. However, theoretical and empirical studies exist previously, analyzed causal relationships between variables in behavioral perspective of strategic human resource management in linear manner. The main objective of this paper is to synthesize theoretical and empirical studies related to causal relationships between variables in behavioral perspective of strategic human resource management. The results of literature review indicate that there are interdependence relationship between variables in behavioral perspective of strategic human resource management. That interdependence relationships are illustrated in integrative theoretical model in behavioral perspective of strategic human resource management, which become a major contribution of this paper. Suggested theoretical model can be used to improve understanding of how organizational performance is achieved by optimizing strengthens of organization's internal resources. Further empirical studies are needed to understand interdependence relationships between variables by relying on empirical data.
Complementarities of Human Resource Management Practices: A Case for a Behavioral Economics Perspective

We stress the relevance of complementarities of human resource management (HRM) practices for explaining persistent productivity differences across organizations. We give an overview of economics as well as strategic HRM literature, document gaps, and show how insights from behavioral economics can inform the analysis. To this end, we develop a simple agency model illustrating how social preferences influence the design and consequences of incentive schemes, investigate how auxiliary HRM practices can strengthen this interaction, and discuss other behavioral subfields that are also suited to inform research on complementarities. Finally, we give an outlook on further research in this field.
The use of Comic Books in the Software requirements specification
Venue: 2016 11th Iberian Conference on Information Systems and Technologies (CISTI)

Some of the greatest challenges for Software requirements elicitation are related with the identification of what is needed to be developed and with the understanding of the organization business rules. In this context, this paper aims to suggest the use of Comic Books in the process of requirements elicitation within a business model and evaluate the results of applying this technique. To reach this target, authors proposed a scenario simulation method using Comic Books. Two experiments were applied to validate the proposal outlined in this paper. The first involved 8 professionals from a software development company and the second involved 17 professionals. All those professionals developed a comic book in order to map a business process within their work environment. In the end of the experiment, those professionals have answered a questionnaire, analyzing the comic books which had been developed. The results have been assessed in a positive way, showing thereby that the use of comic books facilitates the details and requirements elicitation process.
Polarization reconfigurable metasurface superstrate antenna with low profile
Venue: 2016 10th European Conference on Antennas and Propagation (EuCAP)

A polarization reconfigurable antenna using metasurface superstrate is proposed in this paper. The proposed antenna consists of a planar coupling slot with an array of metallic rectangular patches with PIN diodes which can be view as a reconfigurable metasurface superstrate, and a DC bias controlling circuit. When the PIN switches are OFF, the antenna can produce left hand circular polarized (LHCP) wave. The simulated results show that the 10 dB impedance bandwidth is 22.6% from 5.1 to 6.4 GHz, and 3 dB AR bandwidth is 16.9% from 5.4 to 6.4 GHz with an average gain of 7.0 dBi. When the PIN switches are ON, the antenna generates linear polarized (LP) wave, the simulated 10 dB impedance bandwidth is 24.6% from 5.0 to 6.4 GHz with an average gain of 6.1 dBi.
Metasurface Superstrate Antenna With Wideband Circular Polarization for Satellite Communication Application
Venue: IEEE Antennas and Wireless Propagation Letters

A new wideband circularly polarized antenna using metasurface superstrate for C band satellite communication application is proposed in this letter. The proposed antenna consists of a planar slot coupling antenna with an array of metallic rectangular patches that can be viewed as a polarization dependent metasurface superstrate. The metasurface is utilized to adjust axial ratio (AR) for wideband circular polarization. Furthermore, the proposed antenna has a compact structure with a low profile of 0.07l0 l0 stands for the free space wavelength at 5.25 GHz) and ground size of 34.5x28 mm2. Measured results show that the 10 dB impedance bandwidth for the proposed antenna is 33.7% from 4.2 to 5.9 GHz, and 3 dB AR bandwidth is 16.5% from 4.9 to 5.9 GHz with an average gain of 5.8 dBi. The simulated and measured results are in good agreement to verify the good performance of the proposed antenna.
Going deeper in facial expression recognition using deep neural networks
Venue: 2016 IEEE Winter Conference on Applications of Computer Vision (WACV)

Automated Facial Expression Recognition (FER) has remained a challenging and interesting problem in computer vision. Despite efforts made in developing various methods for FER, existing approaches lack generalizability when applied to unseen images or those that are captured in wild setting (i.e. the results are not significant) Most of the existing approaches are based on engineered features (e.g. HOG, LBPH, and Gabor) where the classifier's hyper parameters are tuned to give best recognition accuracies across a single database, or a small collection of similar databases. This paper proposes a deep neural network architecture to address the FER problem across multiple well known standard face datasets. Specifically, our network consists of two convolutional layers each followed by max pooling and then four Inception layers. The network is a single component architecture that takes registered facial images as the input and classifies them into either of the six basic or the neutral expressions. We conducted comprehensive experiments on seven publicly available facial expression databases, viz. MultiPIE, MMI, CK+ DISFA, FERA, SFEW, and FER2013. The results of our proposed architecture are comparable to or better than the state of the art methods and better than traditional convolutional neural networks in both accuracy and training time.
Voice recognition based on adaptive MFCC and deep learning
Venue: 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)

In this paper, we propose an enhanced voice recognition method using Adaptive MFCC and Deep Learning. To improve the voice recognition rate, it is important to extract the audio data from original signal. However the existing Algorithms which is used to remove the noise of particular band deteriorate the audio signal. Differently from the existing MFCC, the proposed filter is built up compactly in the data density area to reduce data loss, and impose the weighted value to the data area. As a result, it prevents the data loss which results in improving the recognition rate. In addition the Deep Learning makes it possible to use the Voice recognition without DB. Therefore, it can be effectively used for electronic devices with small memory.
Using voice recognition software in learning of Chinese pronunciation.

This paper is based on the notion that what matters most in language learning is communication. We argue that if a learner can speak what can be understood by native speakers while at the same time understanding what the native speaker say then we can conclude that this learner has successfully acquired the target language. We present a set of ideas based on the voice recognition exercise which was done with 20 students from different African countries who had studied Chinese language for 3 months at Hebei University. Voice recognition application on smart phones and tablets was used for pronunciation practice purpose in order to boast students' confidence in spoken Chinese. In this exercise the phone acts as the decoding person and it represents how a native Chinese speaker will decode the learner's speech. The results showed that during the exercise students become more and more conscious of their errors and adjust their pronunciation. Apart from that, voice recognition applications helps to determine whether or not the learner's pronunciation is stable. Based on the results of the exercise we concluded that it is possible to turn voice recognition application on smart phones into a game that language learners can use to practice their spoken Chinese. This method is cheap and it promotes self evaluation as well as boasting interest in learning Chinese language.
Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation
Venue: Nature

Concerted political attention has focused on reducing deforestation, and this remains the cornerstone of most biodiversity conservation strategies. However, maintaining forest cover may not reduce anthropogenic forest disturbances, which are rarely considered in conservation programmes. These disturbances occur both within forests, including selective logging and wildfires, and at the landscape level, through edge, area and isolation effects. Until now, the combined effect of anthropogenic disturbance on the conservation value of remnant primary forests has remained unknown, making it impossible to assess the relative importance of forest disturbance and forest loss. Here we address these knowledge gaps using a large data set of plants, birds and dung beetles (1,538, 460 and 156 species, respectively) sampled in 36 catchments in the Brazilian state of Para. Catchments retaining more than 69 80% forest cover lost more conservation value from disturbance than from forest loss. For example, a 20% loss of primary forest, the maximum level of deforestation allowed on Amazonian properties under Brazil's Forest Code, resulted in a 39 54% loss of conservation value: 96 171% more than expected without considering disturbance effects. We extrapolated the disturbance mediated loss of conservation value throughout Para, which covers 25% of the Brazilian Amazon. Although disturbed forests retained considerable conservation value compared with deforested areas, the toll of disturbance outside Para's strictly protected areas is equivalent to the loss of 92,000 139,000 km2 of primary forest. Even this lowest estimate is greater than the area deforested across the entire Brazilian Amazon between 2006 and 2015  Species distribution models showed that both landscape and within forest disturbances contributed to biodiversity loss, with the greatest negative effects on species of high conservation and functional value. These results demonstrate an urgent need for policy interventions that go beyond the maintenance of forest cover to safeguard the hyper diversity of tropical forest ecosystems.
Smart city interoperability framework based on city infrastructure model and service prioritization
Venue: 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN)

The urban development vision that is `smart city' is fast becoming a target of modern cities. However, it is hard to find a general reference architecture and interoperability standards to help with the effective realization of such a vision. This paper sets o ut to do two things: first, we look to develop a general model of city structure, and then we suggest a smart city interoperability framework based on it. For the city model two modeling skills were applied; infrastructure oriented modeling of a system and the value flows within the system. The skills support modeling of a city at a manageable level of granularity and the handling of emerging ICT functions of smart city at the same level, an infrastructure. Derived high level architecture model of a smart city integration is general enough to use for the development of interoperability framework of smart city. A process of selecting preferable smart city services is formulated, aiming to enhance the effectiveness of interoperability framework; it is necessary effort, since smart city is on a convergence technology that should be leaded by the virtue of the convergence, the effectiveness of innovation. Based on both researches on the infrastructure oriented modeling of a city and service prioritization, we developed a smart city interoperability framework conforming to a practical ICT infrastructure system as an efficient and effective vehicle of smart city realization.
Epidemiology of Hepatocellular Carcinoma in the Asia Pacific Region
Venue: Gut and liver

Hepatocellular carcinoma (HCC) is the predominant primary liver cancer in many countries and is the third most common cause of cancer related death in the Asia Pacific region. The incidence of HCC is higher in men and in those over 40 years old. In the Asia Pacific region, chronic hepatitis B virus and hepatitis C virus infections are the main etiological agents; in particular, chronic hepatitis B infection (CHB) is still the major cause in all Asia Pacific countries except for Japan. Over the past two decades, the incidence of HCC has remained stable in countries in the region except for Singapore and Hong Kong, where the incidence for both sexes is currently decreasing. Chronic hepatitis C infection (CHC) is an important cause of HCC in Japan, representing 70% of HCCs. Over the past several decades, the prevalence of CHC has been increasing in many Asia Pacific countries, including Australia, New Zealand, and India. Despite advancements in treatment, HCC is still an important health problem because of the associated substantial mortality. An effective surveillance program could offer early diagnosis and hence better treatment options. Antiviral treatment for both CHB and CHC is effective in reducing the incidence of HCC.
Potential for Zika virus introduction and transmission in resource limited countries in Africa and the Asia Pacific region: a modelling study.
Venue: The Lancet. Infectious diseases

As the epidemic of Zika virus expands in the Americas, countries across Africa and the Asia Pacific region are becoming increasingly susceptible to the importation and possible local spread of the virus. To support public health readiness, we aim to identify regions and times where the potential health, economic, and social effects from Zika virus are greatest, focusing on resource limited countries in Africa and the Asia Pacific region.  Our model combined transportation network analysis, ecological modelling of mosquito occurrences, and vector competence for flavivirus transmission, using data from the International Air Transport Association, entomological observations from Zika's primary vector species, and climate conditions using WorldClim. We overlaid monthly flows of airline travellers arriving to Africa and the Asia Pacific region from areas of the Americas suitable for year round transmission of Zika virus with monthly maps of climatic suitability for mosquito borne transmission of Zika virus within Africa and the Asia Pacific region.  An estimated 2*6 billion people live in areas of Africa and the Asia Pacific region where the presence of competent mosquito vectors and suitable climatic conditions could support local transmission of Zika virus. Countries with large volumes of travellers arriving from Zika virus affected areas of the Americas and large populations at risk of mosquito borne Zika virus infection include India (67 422 travellers arriving per year; 1*2 billion residents in potential Zika transmission areas) China (238 415 travellers; 242 million residents) Indonesia (13 865 travellers; 197 million residents) Philippines (35 635 travellers; 70 million residents) and Thailand (29 241 travellers; 59 million residents) INTERPRETATION Many countries across Africa and the Asia Pacific region are vulnerable to Zika virus. Strategic use of available health and human resources is essential to prevent or mitigate the health, economic, and social consequences of Zika virus, especially in resource limited countries.
Automated Fourier space region recognition filtering for off axis digital holographic microscopy.
Venue: Biomedical optics express

Automated label free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label free imaging tool that retrieves structural details of cellular samples non invasively. In off axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region recognition approach that combines shape recognition with an iterative thresholding method to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here paves way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures.
Modeling Uncertainty in Ontologies using Rough Set

Modeling the uncertain aspect of the world in ontologies is attracting a lot of interests to ontologies builders especially in the World Wide Web community. This paper defines a way of handling uncertainty in description logic ontologies without remodeling existing ontologies or altering the syntax of existing ontologies modeling languages. We show that the source of vagueness in an ontology is from vague attributes and vague roles. Therefore, to have a clear separation between crisp concepts and vague concepts, the set of roles R is split into two distinct sets and representing the set of crisp roles and the set of vague roles respectively. Similarly, the set of attributes A was split into two distinct sets and representing the set of crisp attributes and the set of vague attributes respectively. Concepts are therefore clearly classified as crisp concepts or vague concepts depending on whether vague attributes or vague roles are used in its conceptualization or not. The concept of rough set introduced by Pawlak is used to measure the degree of satisfiability of vague concepts as well as vague roles. In this approach, the cost of reengineering existing ontologies in order to cope with reasoning over the uncertain aspects of the world is minimal.
An Adaptive Fuzzy Logic Traffic Control System in Conditions of Saturated Transport Stream
Venue: TheScientificWorldJournal

This paper considers the problem of building adaptive fuzzy logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach.
Internet of Things for Smart Cities: Interoperability and Open Data
Venue: IEEE Internet Computing

The Internet of Things (IoT) has become a promising technology for addressing societal challenges by connecting smart devices and leveraging Big Data analytics to create smart cities worldwide. As the IoT scales up, it's important to provide interoperability among different devices. Yet current simple standard protocols lack sufficient openness and interoperability. IoT for smart cities needs to guarantee the accessibility of open data and cloud services to allow industries and citizens to develop new services and applications. Here, the authors provide a case study of the GreenIoT platform in Uppsala, Sweden, to demonstrate the idea of interoperability and open data for smart cities.