nils-herrmann/clean_scirepeval huggingface dataset:
Heuristic Evaluation on Usability of Educational Games: A Systematic Review
Venue: Informatics Educ.
Year: 2019

This work presents a systematic review whose objective was to identify heuristics applicable to the evaluation of the usability of educational games. Heuristics are usability engineering methods that aim to detect problems in the use of a system during its development and or when its interface is in interaction with the user. Therefore, applying heuristics is an essential part of developing digital educational games. Search sources were articles available in all the databases present in the Capes MEC Brazil periodicals portal, in the available languages. The descriptors adopted were "educational games" "heuristic" and "usability" in Boolean search in titles, abstracts and keywords, with AND operator, for publications starting in 2014. The inclusion criteria were: (a) articles with a clear description of the methodology used in the usability analysis; (b) studies presenting primary data and (c) articles whose focus corresponds to the investigated question. Two examiners conducted the searches in the databases and a third the evaluation and general review of the data. Initially, 93 articles were identified, of which 19 were repeated, 5 were literature reviews. Of the 69 that remained, 57 were elected as not eligible with only 12 selected for full studies, of which 6 entered the final review. With this review we can deduce that the field of heuristics and usability for educational games is still little explored, with few specific evaluations validated or in the process of validation, requiring greater investment in the area. Through this review, we found at least one heuristic that meets the usability evaluation of educational software: Game User Experience Satisfaction Scale (GUESS)
Collective bargaining: a tool for industrial harmony in Ghanaian industrial settings
Year: 2009

Collective bargaining has been recognised in almost all industrial settings as the most civilised way of resolving industrial conflicts and disagreements. The main objective of this paper is to determine the extent to which collective bargaining can effectively minimise industrial conflicts in Ghana, with particular reference to the brewery industry in Ghana. It is a means of helping to foster cordial management labour relationships towards industrial harmony. The study was carried out with a focus on Ghana Breweries Ltd. The results of the study show that collective bargaining is a powerful and effective tool that can be used to minimise industrial conflicts and disagreements in industrial establishments. It is therefore recommended that employers should encourage the formation of trade unions to promote collective bargaining. It is further recommended that both management and labour should recognise collective bargaining as an effective tool for resolving conflicts and disagreements at the workplace.
The Ethics of Consent: Theory and Practice
Year: 2010

Preface Part One: Theoretical Perspectives 1. The Nature of Consent,  A History of Consent in Western Thought, David Johnston 3. Autonomy and Consent, Tom Beauchamp 4. Preface to the Theory of Transactions: Beyond Valid Consent, Franklin G. Miller and Alan Wertheimer 5. Paternalism and Consent, Douglas Husak 6. Hypothetical Consent, Arthur Kuflik 7. Consent to Harm, Vera Bergelson Part Two: Domains of Consent 8. Consent to Sexual Relations, Alan Wertheimer 9. Sex, Law, and Consent, Robin West 10. Contracts, Brian Bix 11. Consent with Inducements: The Case of Body Parts and Services, Janet Radcliffe Richards 12. Political Obligation and Consent, A. John Simmons 13. Advances in Informed Consent Research, Philip Candilis and Charles Lidz 14. Consent to Medical Care: The Importance of Fiduciary Context, Steven Joffe and Robert Truog 15. Consent to Clinical Research, Franklin G. Miller
How To Increase Employee Competence
Year: 2016

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Economizing the use of nitrogen fertilizer in wheat production through enriched compost
Venue: Renewable Agriculture and Food Systems
Year: 2008

Manipulation of organic wastes and their composts as a source of organic matter (OM) and nutrients is imperative for sustainable agriculture. Further, the fortification of composts with chemical fertilizer enhances agronomic effectiveness of both by reducing the amount of fertilizer and improving the quality of compost. The present study aimed to explore the potential of organic and chemical nutrient sources with their optimal application and integration for sustainable wheat production. Accordingly, waste fruits and vegetables were collected, dried, ground and processed in a composting vessel. During the enriched composting, waste material (300 kg) was fortified with 30 kg N, i.e. 25% of the standard rate (120 kg N ha 1) of N fertilizer. Treatments for both greenhouse and field experiments using wheat (Triticum aestivum L. included: control (without any compost or N fertilizer) compost (non enriched) fertilizer N 120 (120 kg N ha 1) nitrogen enriched compost (NEC) NEC+N 30 (30 kg N ha 1) and NEC+N 60 (60 kg N ha 1) Application rate of composts (non enriched or enriched) was 300 kg ha 1 in the respective treatments. Phosphorus and potassium fertilizers were applied at 90 kg P2O5 ha 1 and 60 kg K2O ha 1, respectively in all treatments. The crop was grown to maturity, and data on wheat growth and yield attributes were recorded. Application of NEC significantly improved the growth, yield and N, P and K contents of wheat compared with compost and control treatments. The performance of NEC+N 60 was statistically similar to that of fertilizer N 120. Economic analysis also revealed the superiority of NEC+N 60 over other treatments in terms of net return and relative increase in income; however, the value/cost ratio was highest with NEC alone. For effective and economical use of N fertilizer, it is suggested to integrate N fertilizer at reduced rates with NEC. Through enriched compost, application rates can be decreased from tonnes to kilograms per hectare, and dependence on chemical fertilizer can be reduced to a certain extent. So the approach is farmer friendly as it lowers compost application rates, and is economically acceptable as it saves N fertilizer. It is also environmentally sustainable due the recycling of organic waste and possible reduction of N losses to the environment. Thus, the study has wide application in the global environment and fertilizer market.
DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering.
Venue: IEEE transactions on neural networks and learning systems
Year: 2021

Clustering algorithms based on deep neural networks have been widely studied for image analysis. Most existing methods require partial knowledge of the true labels, namely, the number of clusters, which is usually not available in practice. In this article, we propose a Bayesian nonparametric framework, deep nonparametric Bayes (DNB) for jointly learning image clusters and deep representations in a doubly unsupervised manner. In doubly unsupervised learning, we are dealing with the problem of `unknown unknowns, where we estimate not only the unknown image labels but also the unknown number of labels as well. The proposed algorithm alternates between generating a potentially unbounded number of clusters in the forward pass and learning the deep networks in the backward pass. With the help of the Dirichlet process mixtures, the proposed method is able to partition the latent representations space without specifying the number of clusters a priori. An important feature of this work is that all the estimation is realized with an end to end solution, which is very different from the methods that rely on post hoc analysis to select the number of clusters. Another key idea in this article is to provide a principled solution to the problem of `trivial solution' for deep clustering, which has not been much studied in the current literature. With extensive experiments on benchmark datasets, we show that our doubly unsupervised method achieves good clustering performance and outperforms many other unsupervised image clustering methods.
Correlates of Alienation in Adolescents
Year: 2013

Research conducted in the field of adolescent behaviour depicts that, in the recent years a great deal of interest has been shown regarding the theme of alienation. Social commentators concern with growing frequency that, "Alienation" is one of the greatest problems confronting us today (Mohan, et al. 1999) Alienation is an experience which has become more and more a fact of life in these days of modernization. Probably adolescents feel this much more than the aged or children. They experience powerlessness, normlessness, rootlessness and drift in values. Though very old, the concept of alienation has become the hallmark of modern age. It is increasingly being recognized as a symptom of man's contemporary crisis a human problem which is reflected in the vast literature in the lonely crowd the dehumanization of modern man. It is revealed in large number of adolescents today who have lost faith in and are actively rebelling against many accepted standards of society and among others who dropout from the society (Sharma, 2002)
Emotional intelligence: The key to mitigating stress and fostering trust among software developers working on information system projects
Venue: Int. J. Inf. Manag.
Year: 2019

The successful accomplishment of information systems development (ISD) activities is reliant on the efforts of developers, who are largely responsible for creating the required system artefacts. Developers encounter numerous obstacles in their efforts to successfully complete activities, such as the need to develop software within highly complex broad ranging projects. These problems increase levels of stress, which subsequently affect developers' ability to self regulate their feelings and understanding. However, only scant attention has been paid to their personal skills and competency in overcoming these issues. This study therefore aimed to bridge this gap by exploring the impact of developers' emotional intelligence on stress, trust, and performance. Our empirical results show that emotional intelligence mitigates stress and fosters trust among software developers working on information system projects. Additionally, role ambiguity increases the effect of stress on performance.
Enhanced Security Identity Based Privacy Preserving Authentication Scheme Supporting Revocation for VANETs
Venue: IEEE Systems Journal
Year: 2020

Existing conditional privacy preserving communication protocols based on a tamper proof device (TPD) in vehicular ad hoc networks (VANETs) face the challenges of master key compromise and vehicle revocation. To address these challenges, we propose a new identity based anonymous authentication scheme. In this scheme, the master key of the system will not be directly installed in the TPD; hence, it is impossible for an adversary to obtain the system master key from the TPD. To generate the private key of the vehicle, an additional secret is required, and this secret is provided by the roadside unit (RSU) Therefore, revoking a malicious vehicle from the VANETs is efficient, since the RSU only needs to stop generating the up to date secret for the vehicle. In addition, the signature verification algorithm of the scheme involves no bilinear pairing operations, making the verification process more efficient. The security of the scheme is proved to be equivalent to the elliptic curve discrete logarithm assumption in the random oracle. The experimental results show that the authentication of the scheme is more efficient, and the communication cost has been diminished.
A geometry dependent surfaceLambertian equivalent reflectivity product at 466 nmfor UV/Vis retrievals: Part I. Evaluation over landsurfaces using measurements from OMI
Year: 2019

The anisotropy of the Earth's surface reflection has implications for satellite based retrieval algorithms that utilize climatological surface reflectivity databases that do not depend upon the observation geometry. This is the case for most of the current ultraviolet and visible (UV/Vis) cloud, aerosol, and trace gas algorithms. The illumination observation dependence of surface reflection is described by the bidirectional reflectance distribution function (BRDF) To account for the BRDF effect, we use the concept of geometry dependent surface Lambertian equivalent reflectivity (GLER) which is derived from the top of atmosphere (TOA) radiance computed with Rayleigh scattering and surface BRDF for the exact geometry of a satellite based pixel. We present details on the implementation of land and water surface BRDF models. We evaluate our GLER product over land surfaces using observed and computed sun normalized radiances at 466 nm. The input surface BRDF parameters for computing TOA radiance are derived from MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations. The observed TOA radiance for comparison is from the Ozone Monitoring Instrument (OMI) The comparison shows good agreement between observed and calculated OMI radiances in typical geographical regions, with correlation coefficients greater than 0.9 for a majority of the selected regions in the year of 2006. Seasonal variations of clear sky OMI radiances (i.e. with minimum clouds and aerosols) closely follow those computed using MODIS derived GLER over land. GLER also captures the cross track dependence of OMI radiances, although the observations are slightly higher than those computed using GLER presumably owing to residual cloud and aerosol (non absorbing) contamination, particularly over dark surfaces (heavily vegetated regions such as mixed forest, croplands and grasslands) The standard OMI climatological surface reflectivity database predicts higher radiances than GLER and OMI observations with different seasonal variations and cross track dependence over most of the selected regions. Overall, our evaluation demonstrates that the GLER product adequately accounts for surface BRDF effects while at the same time simplifies the surface BRDF implementation within the existing OMI retrieval infrastructure; use of our GLER product requires changes only to the input surface reflectivity database.
Clickstream Data Mining and Market Segmentation
Year: 2018

Clickstream data is one of the most important sources of information in websites USAge and customers' behavior in Banks e services. A number of web USAge mining scenarios are possible depending on the available information. While simple traffic analysis based on clickstream data may easily be performed to improve the e banks services. The banks need data mining techniques to substantially improve Banks e services activities. The relationships between data mining techniques and the Web USAge mining are studied. Web structure mining has three types of these types are web USAge structure, mining data streams, and web content. The integration between the Web USAge mining and data mining techniques are presented for processes at different stages, including the pattern discovery phases, and introduces banks cases, that have analytical mining technique. A general framework for fully integrating domain Web USAge mining and data mining techniques are represented for processes at different stages. Data Mining techniques can be very helpful to the banks for better performance, acquiring new customers, fraud detection in real time, providing segment based products, and analysis of the customers purchase patterns over time. And in Market Segmentation The importance of data mining techniques for market segmentation is becoming indispensable in the field of marketing research. This is the first identified academic literature review of the available data mining techniques related to market segmentation. This research paper provides surveys of the available literature on data mining techniques in market segmentation. Eight online journal databases were used for searching, and finally, 103 articles were selected and categorized into 13 groups based on data mining techniques. The utility of data mining techniques and suggestions are also discussed. The findings of this study show that neural networks is the most used method, and kernel based method is the most promising data mining techniques. Our research work provides a comprehensive understanding of past, present as well as future research trend on data mining techniques in market segmentation.
A Novel Metal Foreign Object Detection for Wireless High Power Transfer Using a Two Layer Balanced Coil Array with a Serial Resonance Maxwell Bridge
Year: 2020

In a wireless high power transfer system with a distance of several tens of centimeters apart between the transmitter and receiver coils, one of the most challenging issues is to detect metallic foreign objects between the transmitter and receiver coils. The metallic foreign objects must be detected and removed since these reduce the transmission efficiency and cause heat generation of the transmitter and receiver. This paper presents two layer symmetric balanced coil array so that if there are metallic foreign objects, it can be detected through the change of the inductance of the balanced coils. Since the balanced coil is composed of coils that are in a symmetrical relationship in position, there is no need for a reference coil, and interference between coils is reduced by dividing the coil into two layers. In addition, a novel serial resonance Maxwell bridge circuit to improve the inductance change detection performance is presented in this paper. The proposed metallic foreign object detection system is implemented using two layer balanced coil array with a serial resonance Maxwell bridge and the experimental results show that voltage changes of hundreds of mV to several V occur when a metallic foreign object is inserted, so that even small metals such as clips can be detected.
Assessment of heavy metal pollution, distribution and source apportionment in the sediment from Feni River estuary, Bangladesh.
Venue: Chemosphere
Year: 2018

Heavy metal pollution in sediment resources may pose serious threat to ecosystem and human health through food web. In this study, surface sediment samples of 10 stations along the Feni River estuary were analyzed to profile the accumulation, sources and pollution levels of heavy metals. The results revealed that the average contents (mg g 1) of eight selected heavy metals followed the order of Mn (37.85) Cr (35.28) Ni (33.27) Co (31.02) Pb (6.47) Ag (1.09) As (0.85) Hg (0.71) and the concentrations varied spatially and seasonally with relatively higher levels at upward stations and during the rainy season. According to sediment quality guidelines (SQGs) the sediment samples were heavily contaminated with Ag and Hg, and moderately with Co. Threshold effect concentration (TEC) and probable effect concentration (PEC) values indicated that the concentration of only Ni and Cr were likely to occasionally exhibit adverse effects on the ecosystem. Enrichment factor (EF) geo accumulation index (Igeo) and contamination factor (CF) analyses revealed that Ag, Co and Hg were at moderate to high pollution levels and the rests (As, Cr, Ni, Pb and Mn) were at no to low pollution levels. Potential ecological risk index (PERI) also showed that Ag, Co and Hg were the most potential ecological risk factor being determined in this studied area. Correlation matrix combined with multivariate principal component analysis and cluster analysis suggest that Ag, Co, Ni and Hg originated from anthropogenic sources (agrochemicals, silver nanoparticles anti microbial agent, silver plating) whereas As, Cr, Pb and Mn primarily originated from natural geological background.
Existence and uniqueness of strong solution for the incompressible micropolar fluid equations in domains of \mathbb{R}^3}
Year: 2010

We consider the initial boundary value problem for the system of equations describing the nonstationary flow of an incompressible micropolar fluid in a domain O of \mathbb{R}^3} Under hypotheses that are similar to the Navier Stokes equations, by using an iterative scheme, we prove the existence and uniqueness of strong solution in Lp(O) for p 3.
Climate variation drives dengue dynamics
Venue: Proceedings of the National Academy of Sciences
Year: 2016

Dengue is a vector borne infectious disease that threatens human health on a global scale. Because of climate change, globalization, and other factors, dengue has increasingly spread to new countries and over larger areas, from tropical to temperate zones. In this study, we found that climate has both direct effects on dengue incidence and indirect effects mediated by mosquito density, as mosquitoes are the vectors of dengue. The quantitative results derived from this study may be helpful toward advancing our understanding of how climate influences vector borne diseases and prove useful for the control and prevention of dengue fever. Dengue, a viral infection transmitted between people by mosquitoes, is one of the most rapidly spreading diseases in the world. Here, we report the analyses covering 11 y (2005 2015) from the city of Guangzhou in southern China. Using the first 8 y of data to develop an ecologically based model for the dengue system, we reliably predict the following 3 y of dengue dynamics years with exceptionally extensive dengue outbreaks. We demonstrate that climate conditions, through the effects of rainfall and temperature on mosquito abundance and dengue transmission rate, play key roles in explaining the temporal dynamics of dengue incidence in the human population. Our study thus contributes to a better understanding of dengue dynamics and provides a predictive tool for preventive dengue reduction strategies.
(Social) Identity Theory in an Era of Identity Politics: Theory and Practice
Year: 2020

As a social psychology meta theory, social identity theory (SIT) continues to evolve and expand in terms of areas of applicability and issues. Revisiting SIT can help IB scholars go beyond applying it to just in group/out group behaviour. SIT can also be used to explain collective action, emotion and social change in the face of uncertainty. Managers can use it to address increasing relevance of identity politics, uncertainty and divisiveness. The article overviews the current use of SIT by IB scholars, identifies potential areas of application and provides theoretical and managerial recommendations for the use of SIT.