nils-herrmann/clean_scirepeval huggingface dataset:
Transcription of Encoded Manuscripts with Image Processing Techniques
Venue: DH
Year: 2017

Historical hand written manuscripts are an important source of information for our cultural heritage, and automatic processing of these can help exploring their content faster and easier. A special type of hand written manuscripts that are relatively common in archives and libraries are encrypted, secret documents, so called ciphers. Ciphers may contain and hide important information for the history of science, religion or diplomacy and therefore shall be decrypted and made accessible. The automatic decryption of historical hand written ciphers is the main focus of the project DECODE: Automatic decoding of historical manuscripts. In order to reveal the content of these secret messages, we collect and digitize ciphertexts and keys from Early Modern times, build a database, and develop software tools for (semi )automatic decryption by crossdisciplinary research involving computer science, language technology, linguistics and philology. Ciphers use a secret method of writing, often by transposition or substitution of characters, special symbols, already existing alphabets, digits, or a mixture of these. The encoded sequences are usually meticulously written and often segmented character by character to avoid any kind of ambiguity for the receiver to be able to decode the content, but continuous writing of some sequences where the symbols are connected also exists. In addition, the cipher sequences might be embedded in cleartext, i.e. texts in a known natural language, as illustrated in the picture below (Archivio Segreto Vaticano, 2016)
Path finding of auto driving car using deep learning
Year: 2020

In this project, CNN has been applied as a training tool to process image classification and object avoidance on remote robotic cars built with the Nvidia Jetson Nano developer kit. The kit was programmed using the wireless programming environment, Jupyter notebook. In addition, two different CNN models have been applied to analyze the output result performance. The main purpose is to train the robot to identify objects and improve its accuracy. The recognition and accuracy rate under different conditions can be observed by comparing the two models with different graphic inputs conditions. This project adopts the pre train model for real time demonstrations and can be executed in a cloudless environment (without networks involved) As a result, the robot can achieve a high accuracy rate in both CNN models output result performance. Moreover, the pre train model can execute in local service to accomplish cloudless.
MOOCs, Artificial Intelligence Systems, and the Dilemma of Tertiary Education in the 21st Century
Year: 2020

Recent research on the application of artificial intelligence (AI) technology in the education industry for teaching and learning has stirred up a revolution via the use of platforms like the massive open online courses (MOOC) the likes of which the world have never seen before. Millions through this platform can now enroll online to get one form of education or the other. Many scholars, however, doubt the quality of education transmitted and acquired via these platforms; hence, some scholars describe the education gotten through this medium as artificial education. A situation that has resulted in a kind of revolution in the education industry described as education tsunami. The Marxian theory of alienation offers an appropriate theoretical platform for the analysis conducted in the paper. The ex post factor method of analysis and Deidra's critical analytic method was adopted for attaining the objectives of the paper. The dilemmas eroding the quality of education were identified. Blended learning approaches, as against present methods, were recommended. MOOCs, Artificial Intelligence Systems, and the Dilemma of Tertiary Education in the 21st Century: A Theoretical Appraisal of the Human Factors
The role of interpreters in accessing psychological support and developing relationships in mental health and Deafness
Year: 2017

The Deaf population are vulnerable to experiencing mental health difficulties. A qualitative meta synthesis, reported in section one of this thesis, sought to explore the experiences of deaf individuals who access mental health services and clinicians who provide those services. The synthesis considered the personal, social, communicative, service and professional factors that influence service accessibility for deaf people. It contends that current provision of mental health services does not meet client need. Consequently, the review considers how access to sign language interpreters, education, and collaboration between deaf clients, interpreters and mental health services are instrumental in generating change and improving access. In a further exploration of the experience of mental health care for deaf people, the research paper, reported in section two of the current thesis, examined the role of the British Sign Language (BSL) interpreter in the communication of compassion and development of therapeutic relationships between a mental health clinician and their deaf client. Findings identified that the therapeutic process relies on collaboration, continuity and trust between all individuals; The existence and nurturing of a 'triangle of care' between client, clinician and interpreter leads to stronger therapeutic relationships and better therapeutic outcomes. The research concluded that interpreters must be viewed as part of the clinical team and be supported in their role. Deaf clients must be involved in service development, and clinicians must be willing to improve their knowledge and adapt their practice. The critical appraisal, reported in section three of the current thesis, allowed an opportunity to reflect on personal and professional learning, the research process and results. The importance of reflexivity in qualitative research was considered, alongside research strengths and limitations.
Are certain types of instruction better for certain learners
Year: 2013

The goal of this study was to investigate a possible link between second language (L2) learners' background variables and the type of instruction learners receive in L2 classrooms. We specifically focused on the relationship between several learner background factors (e.g. L2 contact, native language literacy skills, general academic ability) and measures of L2 speaking by analyzing the data from a large scale longitudinal project investigating two different methods of teaching English as an L2 (comprehension based vs. "traditional" L2 program) We found that the learners who had greater contact with English, who showed more interest in reading, whose parents spoke more English, and who attained higher scores in French reading, English vocabulary recognition and general school ability tended to produce more accurate and comprehensible English sentences in an elicited imitation task. However, this relationship was stronger in the comprehension based than in the traditional program, revealing a possible interaction between type of instruction and learner background variables. Taken together, these findings suggest that certain types of instruction could be more beneficial for learners with certain learning profiles and highlight the importance of investigating interactions between learner background variables and type of instruction in authentic learning contexts.
A Simple Topology Preserving Max Flow Algorithm for Graph Cut Based Image Segmentation
Venue: MEMICS
Year: 2010

In this paper, we propose a modification to the Boykov Kolmogorov maximum flow algorithm in order to make the algorithm preserve the topology of an initial interface. This algorithm is being widely used in computer vision and image processing fields for its efficiency and speed when dealing with problems such as graph cut based image segmentation. Using our modification we are able to incorporate a topology prior into the algorithm allowing us to apply it in situations in which the inherent topological flexibility of graph cuts is inconvenient (e.g. biomedical image segmentation) Our approach exploits the simple point concept from digital geometry and is simpler and more straightforward to implement than previously introduced methods. Due to the NP completeness of the topology preserving problem our algorithm is only an approximation and is initialization dependent. However, promising results are demonstrated on graph cut based segmentation of both synthetic and real image data.
Sociopolitical ideology and the morality of green behaviour
Year: 2018

Combating climate change and protecting the environment is a significant topic amongst political leaders and concerned citizens across the globe. The degree to which individuals perceive green issues as important is connected to their politics, those subscribing to conservative ideologies being less supportive of pro environmental initiatives and less concerned about climate change than those endsorsing liberal ideologies. Examining political ideology as a uni and bi dimensional construct, the present research investigated whether political liberals (vs. conservatives) those higher (vs. lower) in right wing authoritarianism, and those higher (vs. lower) in social dominance orientation differ in their perceptions of the morality of green behaviours. In Studies 1 (n 200) and 2 (n 150) liberal (vs. conservative) ideologies related to perceiving pro environmental behaviours as more moral. Further, in Study 2, the relation between ideology and perceptions of green behaviours as moral was explained by positive feelings associated with the self engaging in green behaviours.
Binary Constrained Deep Hashing Network for Image Retrieval Without Manual Annotation
Venue: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV)
Year: 2019

Learning compact binary codes for image retrieval task using deep neural networks has attracted increasing attention recently. However, training deep hashing networks for the task is challenging due to the binary constraints on the hash codes, the similarity preserving property, and the requirement for a vast amount of labelled images. To the best of our knowledge, none of the existing methods has tackled all of these challenges completely in a unified framework. In this work, we propose a novel end to end deep learning approach for the task, in which the network is trained to produce binary codes directly from image pixels without the need o f manual annotation. In particular, to deal with the non smoothness of binary constraints, we propose a novel pairwise constrained loss function, which simultaneously encodes the distances between pairs of hash codes, and the binary quantization error. In order to train the network with the proposed loss function, we propose an efficient parameter learning algorithm. In addition, to provide similar dissimilar training images to train the network, we exploit 3D models reconstructed from unlabelled images for automatic generation of enormous training image pairs. The extensive experiments on image retrieval benchmark datasets demonstrate the improvements of the proposed method over the state of the art compact representation methods on the image retrieval problem.
Active CDS Trading and Managers' Voluntary Disclosure
Year: 2015

We investigate how the development of the credit default swap (CDS) market affects firms' voluntary disclosure choices. The CDS market has been criticized, inter alia, for (i) its vulnerability to insider trading by informed lenders who trade on borrowers' private information, and (ii) the reduction in lenders' monitoring efficiency due to their ability to shed credit risk exposure via CDSs. Consistent with voluntary disclosure theory, we predict that informed trading by lenders and the consequent threat of private information revelation in the spreads of actively traded CDSs will pressure managers to enhance their voluntary disclosures to mitigate the risks associated with non disclosure. Further, the reduction in lender monitoring will lead shareholders to intensify their own monitoring efforts and demand increased voluntary disclosures from managers. Consistent with these predictions, we find that managers are more likely to issue earnings forecasts and to forecast more frequently when their firms have actively traded CDSs. Our results also suggest that liquid CDSs discipline managers to disclose bad news earnings forecasts, despite their career and wealth related incentives to withhold adverse information. In addition to disclosure via management forecasts, we document that liquid CDSs also enhance disclosure via firm initiated press releases. Our findings suggest that the allegedly negative attributes of the CDS market could result in a positive externality for capital markets by eliciting enhanced voluntary disclosures and thus contribute to a richer information environment.
Carbon pools in China's terrestrial ecosystems: New estimates based on an intensive field survey
Venue: Proceedings of the National Academy of Sciences
Year: 2018

Previous estimations of carbon budgets in China's terrestrial ecosystems varied greatly because of the multiplicity of data sources and the inconsistency of methodologies. By conducting a methodologically consistent field campaign across the country, we estimated that the total carbon pool in China's forests, shrublands, grasslands, and croplands was 79.24 2.42 Pg C. The carbon density exhibited a strong dependence on climate regime: it decreased with temperature but increased with precipitation. The country's forests have a large potential of biomass carbon sequestration of 1.9 3.4 Pg C in the next 10 to 20 years assuming no removals. Our findings provide a benchmark to identify the effectiveness of the government's natural protection policies. China's terrestrial ecosystems have functioned as important carbon sinks. However, previous estimates of carbon budgets have included large uncertainties owing to the limitations of sample size, multiple data sources, and inconsistent methodologies. In this study, we conducted an intensive field campaign involving 14,371 field plots to investigate all sectors of carbon stocks in China's forests, shrublands, grasslands, and croplands to better estimate the regional and national carbon pools and to explore the biogeographical patterns and potential drivers of these pools. The total carbon pool in these four ecosystems was 79.24 2.42 Pg C, of which 82.9% was stored in soil (to a depth of 1 m) 16.5% in biomass, and 0.60% in litter. Forests, shrublands, grasslands, and croplands contained 30.83 1.57 Pg C, 6.69 0.32 Pg C, 25.40 1.49 Pg C, and 16.32 0.41 Pg C, respectively. When all terrestrial ecosystems are taken into account, the country's total carbon pool is 89.27 1.05 Pg C. The carbon density of the forests, shrublands, and grasslands exhibited a strong correlation with climate: it decreased with increasing temperature but increased with increasing precipitation. Our analysis also suggests a significant sequestration potential of 1.9 3.4 Pg C in forest biomass in the next 10 20 years assuming no removals, mainly because of forest growth. Our results update the estimates of carbon pools in China's terrestrial ecosystems based on direct field measurements, and these estimates are essential to the validation and parameterization of carbon models in China and globally.
Integrating AMR to Neural Machine Translation using Graph Attention Networks
Venue: 2020 7th NAFOSTED Conference on Information and Computer Science (NICS)
Year: 2020

Semantic representation is potentially useful to enforce meaning preservation and improve generalization performance of machine translation methods. In this paper, we incorporate semantic information from Abstract Meaning Representation (AMR) semantic graphs into neural machine translation. First, we use Graph Attention Networks (GATs) to encode the AMR graphs into a vector space. Then, we propose an effective way to integrate the semantic representation to the attention encoder decoder translation model. The experimental results show the improvements in BLEU scores over the baseline method on the English Vietnamese language pair.
Quechuismos en la Historica Relacion del Reino de Chile de Alonso de Ovalle
Year: 2019

espanolEl presente estudio analiza las voces procedentes del quechua en la obra de Alonso de Ovalle, jesuita y cronista de Indias del siglo XVII. Aunque la Historica Relacion ha sido estudiada desde diversos puntos de vista, hasta la fecha no se ha prestado atencion al aspecto linguistico. En nuestro analisis se examina la supervivencia de dichas voces en diversas obras lexicograficas publicadas en los ultimos ocho anos Academia Argentina de las Letras (2008) Alvarez Vita (2009) Asociacion de Academias de la Lengua Espanola (2010) Academia Chilena de la Lengua (2010) Real Academia Espanola de la Lengua (2014) Mino Garces (2016) Calvo Perez (2016) asi como la presencia de otros americanismos. EnglishThe present study analyzes the Quechua loanwords used in the work of Alonso de Ovalle, a 17th century jesuit chronicler of the Indies. Although the Historica Relacion has been studied from different points of view, to date no attention has been paid to the linguistic aspect. The present analysis examines the survival of these words in several lexicographic works published in the last eight years the Argentinian Academy of Language (2008) Alvarez Vita (2009) Association of Academies of the Spanish Language (2010) the Chilean Academy of Language (2010) the Royal Spanish Academy of Language (2014) Mino Garces (2016) Calvo Perez (2016) as well as the presence of other Americanisms.
Cross Polarization Reduction of a Shorted Patch Antenna With Broadside Radiation Using a Pair of Open Ended Stubs
Venue: IEEE Transactions on Antennas and Propagation
Year: 2020

A novel design concept to reduce high H plane cross polarization of a shorted patch antenna (SPA) with broadside radiated patterns is presented by loading a pair of open ended stubs. Initially, the nonbroadside <inline formula> <tex math notation="LaTeX"\vert E_{\mathrm \theta \vert /tex math>/inline formula> component of the traditional SPA at TM<inline formula> <tex math notation="LaTeX"$_{\mathrm {1/2,2} /tex math>/inline formula> mode is demonstrated to be much larger than its broadside <inline formula> <tex math notation="LaTeX"\vert E_{\varphi \vert /tex math>/inline formula> component in H plane or <italic>yoz</italic> plane radiation patterns. In order to maintain its peak radiation in the normal direction, the far zone radiated fields of the antenna are theoretically studied and analyzed. The results demonstrate that the dual nodal lines of the TM<inline formula> <tex math notation="LaTeX"$_{\mathrm {1/2,2} /tex math>/inline formula> modal fields could be gradually moved far away from each other by increasing the stub length. As such, its <inline formula> <tex math notation="LaTeX"\vert E_{\varphi \vert /tex math>/inline formula> and <inline formula> <tex math notation="LaTeX"\vert E_{\theta \vert /tex math>/inline formula> components in H plane or <italic>yoz</italic> plane radiation patterns could be progressively strengthened and weakened, respectively. After that, by reallocating these dual nodal lines around the corners of the radiating patch, the nonbroadside radiated fields of TM<sub>1/2,2</sub> mode are successfully transformed into the broadside radiation, while keeping a low H plane cross polarization level. Additionally, the symmetric open ended stubs are folded so as to reduce the dimensions of the core radiator. In final, the proposed SPA is fabricated and measured. Simulated and measured results are found in good agreement with each other, and both of them illustrate that the antenna has satisfactorily acquired a normal radiation pattern at reshaped TM<sub>1/2,2</sub> mode. Most importantly, its high H plane cross polarization is dramatically reduced from 4.3 to 21.4 dB as compared to the traditional SPA at TM<sub>1/2,0</sub> mode.
SISTEM PENDUKUNG KEPUTUSAN DALAM MENGANALISA PENJUALAN PRODUK BANGO MENGGUNAKAN METODE TSUKAMOTO
Year: 2020

Sistem pendukung keputusan ialah suatu sistem yang dapat membantu baik seseorang maupun perusahaan dalam mengambil keputusan secara akurat dan sesuai dengan tujuan yang di inginkan. Berbagai permasalahan yang dapat diselesaikan menggunakan sistem pendukung keputusan.Dalam masalah ini sistem pendukung keputusan digunakan untuk membantu karyawan dalam menganalisa penjualan produk kecap bango Pada PT. Lotte Mart Indonesia.Metode yang di gunakan dalam penelitian ini ialah metode Fuzzy Tsukamoto, karena metode ini yang paling cocok dan banyak di gunakan dalam memecahkan permasalahan penjualan produk. Hasil akhir dari penelitian ini yaitu dalam 1 bulan penjualan produk cekap bango terdapat minggu pertama dan kedua dengan nilai 75% dengan keputusan buruk, minggu ke tiga 77% dan minggu ke empat 76% dengan keputusan baik.
The determinants of consumer behaviour of students from Brno when purchasing organic food
Venue: Review of Economic Perspectives
Year: 2019

The subject of this paper is the analysis of consumer behaviour in the organic market, focused on the behavior of students from Brno. Our study brings information which can potentially be used for further research and will also be useful for organizations with a practical interest in the production sale and distribution of organic food. To investigate the influence of the various factors was used the extended model of Theory of Planned Behaviour (TPB) In the current concept, there is no research in the Czech Republic that would apply the approach of Yadav and Pathak (2016) to examine of consumer behaviour on the sample of students, i.e. young Czech generations who are a potential target group. The theoretical part deals with the concept of consumer behaviour, based on the findings of the latest studies, dealing with this topic. In the practical part, the own research is presented, realized on a sample of 403 young consumers, studying in the second largest city of the Czech Republic, the city of Brno. In the Czech Republic, the young consumer is influenced mainly by factors such as personal attitude and subjective norms. Limitations of this study are the fact that in our questionnaire we were interested in how the consumer viewed the purchase of organic food in general and not how they view the purchase of individual organic products and that the research may be limited by the fact that the questionnaire was aimed solely at the younger generation of consumers studying in Brno, the second largest city in the Czech Republic. The behaviour of the younger generation has received little investigation, and in the Czech Republic, there is a lack of research on the behaviour of this sector.