nils-herrmann/clean_scirepeval huggingface dataset:
Dynamics of variables underlying Willingness to Communicate (WTC) in English (L2) A case study of postgraduate business students at a university classroom in Sukkur, Pakistan
Year: 2016

Modern approaches to second language (L2) pedagogy emphasise authentic L2 use for successful L2 learning. However, it has been a common observation L2 contexts that despite possessing years of experience in L2 learning, sometimes even students with higher L2 proficiency shy away from communication, while others plunge themselves in a conversation involving L2. It has been argued that in order for learners to become successful L2 users they not only have to have competence and motivation but a higher willingness to communicate in the target language as well. The present study was, therefore, designed to explore the situational variables and their interaction determining the willingness to communicate (WTC) in English (L2) of six postgraduate business students in a university classroom in Pakistan. While much research has been undertaken to examine trait like psychological antecedents, only a few studies have examined the nature of the interaction between situational variables affecting L2 WTC in a classroom context. Adopting the Dynamic Systems Theory (DST) framework, the present study utilised classroom observations, learners' diaries, stimulated recall interviews and biographic questionnaires to collect the data over ten weeks. The study results showed that participants' L2 WTC emerged as a result of the complex, dynamic and non linear interaction between contextual, psychological, linguistic and physiological factors. Most notably, the study revealed that while learners' L2 use was a manifestation of their willingness to talk, their silence was not always a reflection of their un willingness but involved an active cognitive engagement in L2 communication. The current study, therefore, reinforces the need for teachers to be aware of the multiple factors which affect learners' L2 WTC and silence in L2 classroom. Owing to the complexity and non linearity of interaction of variables, the current study proposes pre service and in service teacher training for English language teachers in Pakistan.
Revisiting the relationship between traffic accidents, real economic activity and other factors in Spain.
Venue: Accident; analysis and prevention
Year: 2020

This paper analyzes the relationship between road traffic accidents and real economic activity in Spain, using data on accidents, fatalities and injuries from January 1975 to December 2016. Our results show the historical asymmetric cyclical behavior of traffic accidents variables. This relationship is more evident for accidents and injuries, while fatalities have shown a different pattern since 2002. Besides using aggregate data, we have analyzed urban and nonurban accidents separately. We analyze the effect of economic variables, public policy interventions and other potential factors affecting traffic series. Regarding policy interventions, we confirm a permanent reduction in all accident rates associated with the mandatory use of seatbelts on car passengers since 1992. However, the penalty points system introduced in July 2006 has only had temporary effects. We have also shown the effect of economic variables such as Industrial Production Index, gasoline and diesel consumption and registration of new vehicles and, as a novelty, the benefits of using the composite coincident and leading indicators of the Spanish economy.
Face Detection Based on Fuzzy Cascade Classifier with Scale invariant Features
Year: 2006

Viola et al. have introduced a rapid object detection framework based on a boosted cascade of simple feature classifiers. In this paper we extend their work and achieve two contributions. Firstly, we propose a novel feature definition and introduce a feature shape mask to represent it. The defined features are scale invariant which means the features can be rescaled easily and reduce the performance degradation introduced by rounding. The feature shape mask can be computed efficiently and expanded conveniently, which can simulate feature shapes used by others and thus enriches the haar like feature pool. Secondly, we present an improved cascade structured classifier which is called fuzzy cascade classifier. The cascade structured classifier owns the disadvantage of neglecting confidence of the prior stage classifiers while only using the binary output of prior stages. Motivated by fuzzy theory, we expand the output of each stage to three states: face, non face, and potential face and set probability being face to each candidate window to make full use of the information of prior stages. Merged by voting, we improve the hit rate at similar false alarm rate.  Face detection, AdaBoost, Scale invariant feature, Fuzzy cascade classifier
Attaining digital advocacy behaviour through destination image and satisfaction
Year: 2020

This study aims to examine the consequences of tourism destination image and satisfaction on digital advocacy in a touristic environment. The study also tested the mediation role of satisfaction in the relationship between the tourism destination image and tourists' advocacy.  This study adopts a quantitative research design, suing the intercept survey method to collect data from 185 international tourists in New Zealand. The process macro regression method was used to analyse the collected data.  The findings from this study are: firstly, the study demonstrates that tourism destination image influenced tourists' digital advocacy behaviour. Secondly, tourists' satisfaction significantly changed tourists' advocacy behaviour. Thirdly, tourists' satisfaction mediates the relationship between the tourism destination image and tourists' advocacy behaviour in this study.  This study examined tourism destination image and satisfaction as predictors of tourist digital advocacy behaviour; the findings have some valuable impacts for organisations, especially the destination marketing organisation's tourism strategies. The result also implies that customer satisfaction is a predictor of advocacy behaviours; and the need to focus on increasing tourist satisfaction by putting in place well crafted tourism products and services.  The finding also implies that customer satisfaction is an important antecedent of advocacy behaviours; and the need to focus on increasing tourist satisfaction by putting in place well crafted tourism based strategies.  This study is one of the few investigations on tourists' digital advocacy behaviour. The study also assessed the mediating impact of customer satisfaction in the relationship between tourism destination image and tourists' advocacy behaviour, an area, which suffers from a languor of research.
Tropical food legumes: virus diseases of economic importance and their control.
Venue: Advances in virus research
Year: 2014

Diverse array of food legume crops (Fabaceae: Papilionoideae) have been adopted worldwide for their protein rich seed. Choice of legumes and their importance vary in different parts of the world. The economically important legumes are severely affected by a range of virus diseases causing significant economic losses due to reduction in grain production, poor quality seed, and costs incurred in phytosanitation and disease control. The majority of the viruses infecting legumes are vectored by insects, and several of them are also seed transmitted, thus assuming importance in the quarantine and in the epidemiology. This review is focused on the economically important viruses of soybean, groundnut, common bean, cowpea, pigeonpea, mungbean, urdbean, chickpea, pea, faba bean, and lentil and begomovirus diseases of three minor tropical food legumes (hyacinth bean, horse gram, and lima bean) Aspects included are geographic distribution, impact on crop growth and yields, virus characteristics, diagnosis of causal viruses, disease epidemiology, and options for control. Effectiveness of selection and planting with virus free seed, phytosanitation, manipulation of crop cultural and agronomic practices, control of virus vectors and host plant resistance, and potential of transgenic resistance for legume virus disease control are discussed.
A laboratory study on synthetic fiber filter for further treatment of turbid stormwater from construction sites
Year: 2019

On the purpose of conform the more stringent government regulation for turbid stormwater from construction sites, the feasibility and availability of synthetic fiber placing after the conventional protection barrier were tested in this study. Initially, comparative work on the filtering performance of fiber media and conventional gravel filter was carried out, 27% higher filtration capacity was obtained under the similar operational conditions. The filter efficiency was about 20 to 52% with a varying filter depth of 5 to 15cm, presuming at extreme storm flow conditions (800 1500 m/day of filtration rates) Fiber filter was found to have a similar filtration prosperity as grain media; namely, the separation efficiency is directly and inversely proportional to filter depth and rate, respectively. The effects of filter aid (polyaluminium chloride) on filter performance was also investigated, it greatly affected the turbidity reduction at the dosage of 2 mg/L. At the time of breakthrough, a simple filter washing was carried out, herein, the solid recovery achieved over than 88% and greatly determined by operational parameters. Based on the operational data, the empirical models aimed for predicting filtration efficiency were established, which can effectively determine the required filter depth and filtration area in field.
HBase: The Definitive Guide
Year: 2011

If your organization is looking for a storage solution to accommodate a virtually endless amount of data, this book will show you how Apache HBase can fulfill your needs. As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant.  The Definitive Guide provides the details you require, whether you simply want to evaluate this high performance, non relational database, or put it into practice right away. HBase's adoption rate is beginning to climb, and several IT executives are asking pointed questions about this high capacity database. This is the only book available to give you meaningful answers. Learn how to distribute large datasets across an inexpensive cluster of commodity servers Develop HBase clients in many programming languages, including Java, Python, and Ruby Get details on HBase's primary storage system, HDFS Hadoop's distributed and replicated filesystem Learn how HBase's native interface to Hadoop's MapReduce framework enables easy development and execution of batch jobs that can scan entire tables Discover the integration between HBase and other facets of the Apache Hadoop project
A MODEL OF CHARACTER EDUCATION AS REFLECTED IN FUADY'S NEGERI LIMA MENARA
Year: 2016

Negeri Lima Menara oleh Fuady telah melanda bagi banyak pembaca. Novel ini bercerita tentang kehidupan di pesantren Islam. Kisah novel yang mencerminkan pengalaman penulis selama studi di Pondok Pesantren Darassalam Ponorogo, Jawa Timur pada tahun 1980. Madani Pesantren sebagai lembaga pendidikan utama di dalam menunjukkan peran dalam membangun karakter siswa dengan mengintegrasikan modernitas dan ajaran Islam pada saat yang sama .Fuady mencoba untuk menunjukkan model yang baik tentang bagaimana lembaga pendidikan (Madani Pondok Pesantren) dapat mendidik siswa untuk meningkatkan perkembangan pribadi mereka. Madani Pondok Pesantren memiliki sistem pendidikan yang baik dan tegas untuk bertanggung jawab atas perilaku siswa nya dari dasar sampai dengan akhir proses pembelajaran.Artikel ini menganalisa peran Madani Pondok Pesantre dalam mengembangkan siswa bangunan karakter. penulis memperoleh beberapa temuan dari novel Negeri Lima Menara pada bagaimana pondok pesantren madani berhasil bisa mendidik siswa untuk memiliki karakter yang baik dengan mengoptimalkan peran guru sebagai motivator dan model yang baik bagi siswa; membangun ikatan emosional antara guru dan siswa; dan memberikan kesadaran dan nilai nilai moral kepada siswa.
Self Supervised Relationship Probing
Venue: NeurIPS
Year: 2020

Structured representations of images that model visual relationships are beneficial for many vision and vision language applications. However, current humanannotated visual relationship datasets suffer from the long tailed predicate distribution problem which limits the potential of visual relationship models. In this work, we introduce a self supervised method that implicitly learns the visual relationships without relying on any ground truth visual relationship annotations. Our method relies on 1) intraand inter modality encodings to respectively model relationships within each modality separately and jointly, and 2) relationship probing, which seeks to discover the graph structure within each modality. By leveraging masked language modeling, contrastive learning, and dependency tree distances for self supervision, our method learns better object features as well as implicit visual relationships. We verify the effectiveness of our proposed method on various vision language tasks that benefit from improved visual relationship understanding.
Reducing the hazardous effect of mineral nitrogen fertilizers on pepper production by using compost and compost extract in saline soil
Year: 2018

A field experiment was carried out during two successive seasons; 2015/16 and 2016/17 at Gilbana village of Sahl El Tina, North Sinia Governorate, Egypt. The objective of this study was to evaluate the environmental risk of mineral nitrogen fertilizers on soil water table and plant, Compost and Compost extract were used as complementary application. This experiment was designed in a Randomized Complete Block Design with three replicates. Two sources of nitrogen fertilizers are used in the experiment (NH4) 2SO4 NO3NH4) The treatments were T1 100% Recommended dose of ammonium sulphate (140 kg. N fed) T2 75% of recommended dose of ammonium sulphate (105 kg. N/fed) (1 feddan (fed) 4200 m2 0.42 hectares 1.038 acres) and Compost at the rate of (2 t fed 1) T3 50% of recommended dose of ammonium sulphate Compost at the rate of (4 t fed 1) T4 100% Recommended dose of ammonium nitrate (140 kg. N/fed) T5 75% of recommended dose of ammonium nitrate (105 kg. N/fed) and Compost at the rate of (2t fed 1) and T6 50% of recommended dose of ammonium nitrate (70 kg. N/fed) Compost at the rate of (4t fed 1) The results indicated that the addition of the fertilizer requirements as (Ammonium sulphate and Ammonium nitrate) by 100% (140 kg. N/fed) of each, produce (6.4 and 9.0) ton/fed of pepper production in the first season; respectively, in the second season, were (7.4 and 9.4) tons fed; respectively. On the other hand, T3 (50% Ammonium sulphate (70 kg. N/fed) 50% compost) was the superior treatment for pepper production, and the lowest contamination of nitrates and nitrite in pepper fruit and loss in ground water.
Achieve Privacy Preserving Truth Discovery in Crowdsensing Systems
Venue: CIKM
Year: 2019

To solve the problem that the data collected in crowdsensing systems are not reliable, a large number of truth discovery protocols have been proposed. However, most of them neglect the privacy protection existing in crowdsensing systems. Some truth discovery protocols that consider privacy only provide limited privacy protection, such as only protecting the privacy of collected data. To bridge the gap, in this paper, we propose a more comprehensive privacy preserving truth discovery protocol that can simultaneously protect the privacy of participants and truth results. Specifically, our protocol encrypts participants' observed data based on Paillier Homomorphic Cryptosystem. Then, through the interaction between two servers, we can calculate participants' weights and estimate the truth results in the encrypted domain. Moreover, based on the data perturbation technology, the privacy of sensitive data exchanged between the two servers is protected in our protocol. Theoretical analysis and experimental results demonstrate that our protocol can effectively protect the privacy of participants and truth results without losing the accuracy of truth results.
Detection of Aeromonas hydrophila DNA oligonucleotide sequence using a biosensor design based on Ceria nanoparticles decorated reduced graphene oxide and Fast Fourier transform square wave voltammetry.
Venue: Analytica chimica acta
Year: 2015

A new strategy was introduced for ssDNA immobilization on a modified glassy carbon electrode. The electrode surface was modified using polyaniline and chemically reduced graphene oxide decorated cerium oxide nanoparticles (CeO2NPs RGO) A single stranded DNA (ssDNA) probe was immobilized on the modified electrode surface. Fast Fourier transform square wave voltammetry (FFT SWV) was applied as detection technique and [Ru(bpy)3](2+/3+ redox signal was used as electrochemical marker. The hybridization of ssDNA with its complementary target caused a dramatic decrease in [Ru(bpy)3](2+/3+ FFT SW signal. The proposed electrochemical biosensor was able to detect Aeromonas hydrophila DNA oligonucleotide sequence encoding aerolysin protein. Under optimal conditions, the biosensor showed excellent selectivity toward complementary sequence in comparison with noncomplementary and two base mismatch sequences. The dynamic linear range of this electrochemical DNA biosensor for detecting 20 mer oligonucleotide sequence of A. hydrophila was from 1 x 10( 15) to 1 x 10( 8) mol L( 1) The proposed biosensor was successfully applied for the detection of DNA extracted from A. hydrophila in fish pond water up to 0.01 mg mL( 1) with RSD of 5% Besides, molecular docking was applied to consider the [Ru(bpy)3](2+/3+ interaction with ssDNA before and after hybridization.
Rapid Increase in Prevalence of Carbapenem Resistant Enterobacteriaceae (CRE) and Emergence of Colistin Resistance Gene mcr 1 in CRE in a Hospital in Henan, China
Venue: Journal of Clinical Microbiology
Year: 2018

The global spread of carbapenem resistant Enterobacteriaceae (CRE) is one of the most severe threats to human health in a clinical setting. The recent emergence of plasmid mediated colistin resistance gene mcr 1 among CRE strains greatly compromises the use of colistin as a last resort for the treatment of infections caused by CRE. This study aimed to understand the current epidemiological trends and characteristics of CRE from a large hospital in Henan, the most populous province in China. From 2014 to 2016, a total of 7,249 Enterobacteriaceae isolates were collected from clinical samples, among which 18.1% (1,311/7,249) were carbapenem resistant. Carbapenem resistant Klebsiella pneumoniae and carbapenem resistant Escherichia coli were the two most common CRE species, with Klebsiella pneumoniae carbapenemases (KPC) and New Delhi metallo b lactamases (NDM) respectively, responsible for the carbapenem resistance of the two species. Notably, >57.0% (n 589) of the K. pneumoniae isolates from the intensive care unit were carbapenem resistant. Furthermore, blaNDM 5 and mcr 1 were found to coexist in one E. coli isolate, which exhibited resistance to almost all tested antibiotics. Overall, we observed a significant increase in the prevalence of CRE isolates during the study period and suggest that carbapenems may no longer be considered to be an effective treatment for infections caused by K. pneumoniae in the studied hospital.
Persian text classification via character level convolutional neural networks
Venue: 2018 8th Conference of AI Robotics and 10th RoboCup Iranopen International Symposium (IRANOPEN)
Year: 2018

Text classification is an important task in the field of text mining. Due to the ever increasing volume of text data on the Internet, text classification is needed more than ever before. In the last decades, researchers have been trying to offer accurate models to distinguish data of each class from the other class. Many researches aimed to find a set of features that would increase the accuracy of classification. Recently, deep learning has been considered as the ideal approach in big data issues, and has proved the impact of using convolutional networks on improving the results. These models mainly represent text based on words. Due to the complexity of natural languages and the importance of having extra knowledge, researchers are still trying to achieve a more efficient method. In this research, we used a deep convolutional neural network and applied it on the Persian corpus. A remarkable feature of this model is the use of character based convolutional layers to extract features from text, which has a higher accuracy (0.49) than other character based representations.
Optimization of Plant Layout in Jordan Light Vehicle Manufacturing Company
Year: 2020

The generation of layout alternatives is a critical step in the facilities planning process since the layout selected will serve to establish the physical relationships between activities. This paper is concerned with the evaluation and analysis of the existing facility layout in Jordan Light Vehicle Manufacturing Company and investigating the possibility for improvement to cope with increased demand and better utilization of available resources. Five alternatives were proposed using systematic layout planning for a possible arrangement of different facilities within the plant. The proposed alternatives were compared and ranked using the analytic hierarchy process based on the total traveling distance of materials between production facilities, total space usage, and activity relationships. The alternatives were ranked using three criteria, and the overall consistency was determined (6.918% fair well below 10% This case is implemented in a military institution in Jordan, and the used tools were not applied before.
Theory Studies: Archetypical Retail Practices In Contemporary Interior Design
Year: 2011

This thesis is written in contribution to the ongoing Intypes (Interior Archetypes) Research and Teaching Project, established at Cornell University in 1997. Intypes are derived from historical interior design practices that are reiterative and represent design ideals that span time, style and culture. This study identifies, classifies, and names archetypical interior design practices in professionally designed contemporary retail interiors. Intypes offer an interior design specific vocabulary for the analysis and criticism of the creative dimension of design. Prior to the Intypes Project, established archetypes had not formally been identified in interior design as in the architecture discipline. Associating names with interior archetypes provides a tool for the study and practice of interior design. Generating a body of knowledge and placing contemporary interior design practice within a historical context affords credibility to the profession. The methodology is one of typology, or classification. Images of retail interiors were gathered and sorted based on common design traits and potential archetypes were proposed to the greater research group. The strongest and most far reaching traits were deemed intypes, given intuitive names, and put forth for further examination. Retail is an important practice type to study through the lens of design typologies because of its societal and cultural impact. Shopping is a popular leisure activity, and stores, as semi public spaces, contribute significantly to the urban fabric and sense of place.