nils-herrmann/clean_scirepeval huggingface dataset:
Dynamic Data Selection and Weighting for Iterative Back Translation
Venue: EMNLP
Year: 2020

Back translation has proven to be an effective method to utilize monolingual data in neural machine translation (NMT) and iteratively conducting back translation can further improve the model performance. Selecting which monolingual data to back translate is crucial, as we require that the resulting synthetic data are of high quality \textit{and} reflect the target domain. To achieve these two goals, data selection and weighting strategies have been proposed, with a common practice being to select samples close to the target domain but also dissimilar to the average general domain text. In this paper, we provide insights into this commonly used approach and generalize it to a dynamic curriculum learning strategy, which is applied to iterative back translation models. In addition, we propose weighting strategies based on both the current quality of the sentence and its improvement over the previous iteration. We evaluate our models on domain adaptation, low resource, and high resource MT settings and on two language pairs. Experimental results demonstrate that our methods achieve improvements of up to 1.8 BLEU points over competitive baselines.
Evolving conceptual spaces for symbol grounding in language games
Venue: BICA 2015
Year: 2015

A standard approach in the simulation of language evolution is the use of Language Games to model communicative interactions between intelligent agents. Usually, in such language games, an agent uses the results from its perceptual layer to categorize and to conceptualize world objects, a process named categorization. In this paper, we develop an approach to the categorization process, where the decomposition of reality in meaningful experiences is co evolved with the lexicon formation in the language game. This approach brings some insights on how meaning might be assigned to symbols, in a dynamic and continuously changing environment being experienced by an agent. In order to do that, we use Barsalou's notion of mental simulation and Gardenfors' notion of conceptual spaces such that, together with ESOM neural networks, a cognitive architecture can be developed, where mental concepts formation and lexicon formation are able to co evolve during a language game. The performance of our cognitive architecture is evaluated and the results show that the architecture is able to fulfill its semantics function, by allowing a population of agents to exchange the meaning of linguistic symbols during a naming game, without relying on "a priori" categorization scheme provided by an external expert or a set of examples for training a neural network in a previous discrimination game. These results, beyond bringing evidence on potential ways for symbols to get meaning on a biologically realistic way, open a set of possibilities for further uses of conceptual spaces on a much more complex problem: the grounding of a grammatical language.
Challenges in long term care facilities for older adults in Hispanic American countries
Year: 2020

Pouco se sabe sobre o enfrentamento e a mitigacao da COVID 19 em instituicoes de longa permanencia para idosos (ILPIs) na America Latina.  Descrever como os gestores de ILPIs de paises hispano americanos planejaram e adequaram suas rotinas de enfrentamento da COVID 19 e se foram capazes de cumprir as recomendacoes da Organizacao Mundial da Saude (OMS) METODOLOGIA: Estudo transversal baseado na aplicacao de uma pesquisa on line dirigida aos gestores de ILPIs situadas em paises hispano americanos. Um questionario de 46 questoes (adotando os principios da OMS) foi enviado aos participantes. Estatistica descritiva foi usada para resumir os dados.  Vinte e tres gestores responderam a pesquisa, totalizando 874 idosos (5 min 270 max) um questionario foi excluido por falta de respostas. Quatorze ILPIs (63,60% eram privadas com fins lucrativos. A taxa de adesao as recomendacoes da OMS foi superior a 70% para a maioria das questoes. Pouco mais da metade das instituicoes elaborou um plano estrategico de enfrentamento, ou identificou estrategias para lidar com obitos de casos suspeitos. Dificuldade para a aquisicao de equipamentos de protecao individual (EPIs) foi relatada por 59,10% das ILPIs investigadas. A capacidade de testagem para o SARS Cov 2 foi reduzida (36,36% das instituicoes nao dispunham de nenhum teste) CONCLUSOES: A taxa de adesao as recomendacoes propostas pela OMS para o enfrentamento da COVID 19 foi superior a 70% para a maioria das ILPIs investigadas. Planos estrategicos de enfrentamento foram elaborados em pouco mais da metade das instituicoes. A disponibilidade de EPIs e a capacidade de testagem para o SARS Cov 2 mostraram se bastante insatisfatorias.
Vibration reduction turnout pedestal system and assembly method
Year: 2014

The invention belongs to the field of rail traffic, and provides a vibration reduction turnout pedestal system and an assembly method. The vibration reduction turnout pedestal system comprises a lower bottom plate (1) a middle elastic insulating pad (2) an upper bottom plate (3) a turnout fastener base (7) a distance adjusting connecting positioning assembly and the like. The upper bottom plate (3) and the turnout fastener base (7) are connected together through the distance adjusting connecting positioning assembly, and the relative position of the turnout fastener base (7) and the upper bottom plate (3) can be adjusted through the distance adjusting connecting positioning assembly. The lower bottom plate (1) the middle elastic insulating pad (2) and the upper bottom plate (3) are locked and connected together. The vibration reduction turnout pedestal system has the advantages of being easy to machine and manufacture, low in cost, detachable, low in maintenance and replacement cost, convenient to install on the scene and the like.
Cybersecurity in the context of industry 4.0: A structured classification of critical assets and business impacts
Venue: Comput. Ind.
Year: 2020

An increasing number of cybersecurity breaches adversely affect business performance, by leveraging the vulnerabilities of networked manufacturing machines. In some cases, cyber attacks on critical industrial equipment are able to undermine the corporate business model. Knowing and evaluating in advance the main critical assets to be protected from potential cyber attacks and the business impacts that could occur is a source of competitive advantage. Through the analysis of literature and an ethnographic research approach, this study proposes a structured classification of critical industrial assets within Industry 4.0 and potential adverse impacts on business performance due to breaches of cybersecurity. In particular, cybersecurity is analysed in terms of loss of confidentiality, integrity and availability of data associated with networked manufacturing machines. It is also suggested how critical assets and business impacts are correlated and how business impacts can be assessed. The proposed results can be organized in four steps for supporting companies in making decisions on cybersecurity policies. Moreover, both industry and academia can benefit from these results to conduct future analysis and investigation activities in the field of cybersecurity.
A study on public space design strategies in Japanese National Museums focusing on The National Museum of Western Art and The National Art Center in Tokyo
Venue: Journal of Asian Architecture and Building Engineering
Year: 2019

This study examines the prototypes, characteristics, and perspectives of public space in museums whose existential values and concepts have continuously changed based on their historical contexts. Based on an understanding of museum architecture and its cultural and social context in Japan, this research focuses on two national museums that represent Japanese modern and contemporary eras. In particular, this research examines The National Museum of Western Art in Tokyo designed by Le Corbusier, an internationally known French architect, in the 20th century and the public space of The National Art Centre the fifth national museum in Japan which was designed in the environment of Japanese museums by a Japanese representative architect, Kisho Kurokawa. This research concentrates on the public space within museums that reflects the flows and social demands of the era, rather than focusing on the architects' design concepts or architectural analysis. A thorough analysis will be conducted, focusing on the museums' floor plans, sections, images, and diagrams to showcase the characteristics and perspectives of public space in 21st century museums
Dual Mode Microcavity Semiconductor Lasers
Venue: IEEE Journal of Selected Topics in Quantum Electronics
Year: 2019

Dual mode microcavity semiconductor lasers are investigated for potential applications in photonic microwave and optical frequency comb (OFC) generation. By regulating whispering gallery modes (WGMs) in square microcavities, dual mode lasing is achieved with frequency intervals ranging from tens to hundreds of gigahertz. In the square microcavities, the fundamental and first order transverse WGMs have spatially separated field distributions, which allow stable dual transverse mode lasing with mode intervals inversely proportional to the cavity areas. Dual transverse mode square microcavity lasers are experimentally demonstrated with frequency intervals ranging from ~35 to ~150 GHz. Photonic microwaves and OFCs are successfully generated based on the dual mode square microcavity lasers. To enhance the transverse mode intervals, circular side square microcavity lasers with a square hole in the center are proposed and demonstrated, and dual transverse mode lasing with a frequency interval up to ~0.56 THz is obtained. Furthermore, a square Fabry Perot coupled cavity microlaser is demonstrated to increase the output power and introduce an additional degree for manipulating the lasing modes. Dual mode lasing is realized with a frequency interval of ~0.5 THz, a single mode optical fiber coupled power of ~3 mW, and a wavelength tuning range of ~10 nm.
Co creating value with customers: a study of mobile hotel bookings in China
Year: 2018

This study aimed to develop a framework to explain the reciprocity of the value co creation process in mobile hotel booking context, and to clarify values for customer and supplier.  A research framework was developed based on the previous literature to derive insights on value co creation process. Online surveys were conducted among mobile hotel bookers in China. Confirmatory factor analysis and structural equation modeling were used to test the proposed framework.  The findings suggested that suppliers should improve the values for customers (Functionality, Usability, and Perceived Value) to achieve values for themselves [Customer Lifetime Value (CLV) Customer Knowledge Value(CKV) Customer Referral Value (CRV) and Customer Influencer Value (CIV) The relation between satisfaction and CLV was moderated by the CIV from other customers.  Suppliers should enhance customer value from the aspects of functionality, usability, and perceived va.
A Complex Suicide by Ligature Strangulation and Hanging Using Two Different Ligatures
Year: 2019

According to the statistics of the Malaysian National Suicide Registry, hanging is the most common method of suicide in Malaysia  However, hanging in combination with suicidal ligature strangulation is rather uncommon. A ligature strangulation case should be considered as a homicide unless proven otherwise. This article reports a case of suicidal strangulation by ligature, coupled with hanging, of an individual who had no previous medical or psychiatric disorder. He initiated self strangulation using a shoelace, followed by hanging using a High Definition Multimedia Interface (HDMI) cable. Scene assessment and post mortem findings concurred with suicide. The unusual case of suicidal ligature strangulation in combination with hanging using two different ligatures is reported in this case.
A Scalable Two Stage Approach to Computing Optimal Decision Sets
Venue: AAAI
Year: 2021

Machine learning (ML) is ubiquitous in modern life. Since it is being deployed in technologies that affect our privacy and safety, it is often crucial to understand the reasoning behind its decisions, warranting the need for explainable AI. Rulebased models, such as decision trees, decision lists, and decision sets, are conventionally deemed to be the most interpretable. Recent work uses propositional satisfiability (SAT) solving (and its optimization variants) to generate minimumsize decision sets. Motivated by limited practical scalability of these earlier methods, this paper proposes a novel approach to learn minimum size decision sets by enumerating individual rules of the target decision set independently of each other, and then solving a set cover problem to select a subset of rules. The approach makes use of modern maximum satisfiability and integer linear programming technologies. Experiments on a wide range of publicly available datasets demonstrate the advantage of the new approach over the state of the art in SAT based decision set learning.
BUILDING MEMORY On the symbolic function of contemporary memorial architecture
Year: 2020

In late modernity, the symbolic function of architecture, that the architectural avant gardes of the twentieth century have tried to abolish, emerges in the memorial buildings dedicated to the commemoration of the tragedies of the last century. In this article, it is treated from the architectural analysis, to reveal the significance of these traumatic events for contemporary societies. It argues some methodological procedures for articulating architectural language: how symbolic structures establish connections that affect both sensitivity and knowledge and how body, memory, space and time all together constitute an experiential nature unit.
Big Data for the Sustainability of Healthcare Project Financing
Venue: Sustainability
Year: 2019

This study aims to detect if and how big data can improve the quality and timeliness of information in infrastructural healthcare Project Finance (PF) investments, making them more sustainable, and increasing their overall efficiency. Interactions with telemedicine or disease management and prediction are promising but are still underexploited. However, given rising health expenditure and shrinking budgets, data driven cost cutting is inevitably required. An interdisciplinary approach combines complementary aspects concerning big data, healthcare information technology, and PF investments. The methodology is based on a business plan of a standard healthcare Public Private Partnership (PPP) investment, compared with a big data driven business model that incorporates predictive analytics in different scenarios. When Public and Private Partners interact through networking big data and interoperable databases, they boost value co creation, improving Value for Money and reducing risk. Big data can also help by shortening supply chain steps, expanding economic marginality and easing the sustainable planning of smart healthcare investments. Flexibility, driven by timely big data feedbacks, contributes to reducing the intrinsic rigidity of long termed PF healthcare investments. Healthcare is a highly networked and systemic industry, that can benefit from interacting with big data that provide timely feedbacks for continuous business model re engineering, reducing the distance between forecasts and actual occurrences. Risk shrinks and sustainability is fostered, together with the bankability of the infrastructural investment.
Several Classes of Minimal Linear Codes With Few Weights From Weakly Regular Plateaued Functions
Venue: IEEE Transactions on Information Theory
Year: 2020

Minimal linear codes have significant applications in secret sharing schemes and secure two party computation. There are several methods to construct linear codes, one of which is based on functions over finite fields. Recently, many construction methods for linear codes from functions have been proposed in the literature. In this paper, we generalize the recent construction methods given by Tang et al. in [ 2016] to weakly regular plateaued functions over finite fields of odd characteristic. We first construct three weight linear codes from weakly regular plateaued functions based on the second generic construction and then determine their weight distributions. We also give a punctured version and subcode of each constructed code. We note that they may be (almost) optimal codes and can be directly employed to obtain (democratic) secret sharing schemes, which have diverse applications in the industry. We next observe that the constructed codes are minimal for almost all cases and finally describe the access structures of the secret sharing schemes based on their dual codes.
Comparison of chassis frame design of Go Kart vehicle powered by internal combustion engine and electric motor
Year: 2020

Go Kart design and development helps in implying the theoretical knowledge into the practical aspect. It also helps to learn about various parameters that can be altered and implied to try to improve the performance of the kart. Go kart is of various types namely internal combustion engine (IC) powered, Electric driven, solar powered and Hybrid. This project is aimed to convert an IC engine Go kart into an Electric driven kart, the Frame of the IC engine kart requires a single mount as it needs only Engine and it is developed using SOLIDWORKS, whereas in Electric driven it is a combination of Battery, Motor and Controller and hence it requires a large number of mounts and cross members to support the components, the conversion of IC powered engine frame into an Electric driven needs some alteration to support the components and a new frame was developed using SOLIDWORKS. Both frames are analysed using ANSYS for different types of impacts namely front, side and rear in accordance with the load distribution that acts in the frame and the deformation results are compared.
Total disc replacement versus anterior cervical discectomy and fusion: A SYSTEMATIC REVIEW WITH META ANALYSIS OF DATA FROM A TOTAL OF 3160 PATIENTS ACROSS 14 RANDOMIZED CONTROLLED TRIALS WITH BOTH SHORT AND MEDIUM TO LONG TERM OUTCOMES
Venue: The bone joint journal
Year: 2018

The aim of this study was to determine how the short and medium to long term outcome measures after total disc replacement (TDR) compare with those of anterior cervical discectomy and fusion (ACDF) using a systematic review and meta analysis.  Databases including Medline, Embase, and Scopus were searched. Inclusion criteria involved prospective randomized control trials (RCTs) reporting the surgical treatment of patients with symptomatic degenerative cervical disc disease. Two independent investigators extracted the data. The strength of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria. The primary outcome measures were overall and neurological success, and these were included in the meta analysis. Standardized patient reported outcomes, including the incidence of further surgery and adjacent segment disease, were summarized and discussed.  A total of 22 papers published from 14 RCTs were included, representing 3160 patients with follow up of up to ten years. Meta analysis indicated that TDR is superior to ACDF at two years and between four and seven years. In the short term, patients who underwent TDR had better patient reported outcomes than those who underwent ACDF, but at two years this was typically not significant. Results between four and seven years showed significant differences in Neck Disability Index (NDI) 36 Item Short Form Health Survey (SF 36) physical component scores, dysphagia, and satisfaction, all favouring TDR. Most trials found significantly less adjacent segment disease after TDR at both two years (short term) and between four and seven years (medium to long term) Conclusion TDR is as effective as ACDF and superior for some outcomes. Disc replacement reduces the risk of adjacent segment disease. Continued uncertainty remains about degeneration of the prosthesis. Long term surveillance of patients who undergo TDR may allow its routine use.
The walkthrough method: An approach to the study of apps
Venue: New Media Soc.
Year: 2018

Software applications (apps) are now prevalent in the digital media environment. They are the site of significant sociocultural and economic transformations across many domains, from health and relationships to entertainment and everyday finance. As relatively closed technical systems, apps pose new methodological challenges for sociocultural digital media research. This article describes a method, grounded in a combination of science and technology studies with cultural studies, through which researchers can perform a critical analysis of a given app. The method involves establishing an app's environment of expected use by identifying and describing its vision, operating model and modes of governance. It then deploys a walkthrough technique to systematically and forensically step through the various stages of app registration and entry, everyday use and discontinuation of use. The walkthrough method establishes a foundational corpus of data upon which can be built a more detailed analysis of an app's intended purpose, embedded cultural meanings and implied ideal users and uses. The walkthrough also serves as a foundation for further user centred research that can identify how users resist these arrangements and appropriate app technology for their own purposes.
Beyond the numbers: Mining the Annual Reports for Hidden cues Indicative of Financial Statement Fraud
Venue: Intell. Syst. Account. Finance Manag.
Year: 2012

Unlike previous fraud detection research, a vast majority of which has focused primarily on the use of quantitative financial information to predict fraud, in this study we examine qualitative textual content in annual reports to predict fraud and see whether there are discernible differences in the writing and presentation style between companies that committed fraud and those that did not. We believe that while numeric financial information in the annual reports can hide details of fraud, textual information relating to writing and presentation styles in such reports provides valuable clues pertaining to the existence of fraud. In this study we use the chi square test to analyse our data and test hypotheses about predictors of fraud that may explain linguistic feature variations in fraudulent and nonfraudulent annual reports. We provide new results on the usefulness of the qualitative content of annual reports in detecting fraud.
Local mean decomposition method based on B spline interpolation
Year: 2010

The local mean decomposition (LMD) is a relatively new approach of adaptive signal analysis.The core of LMD is to decompose an original signal into several production functions (PF),and each of which is a product of an envelope function and a pure frequency modulated one.Both the local mean function and the envelope estimation of the signal need to be extracted in the LMD algorithm,while the conventional extraction approach brings the local error and a slow rate of decomposition.To solve these problems,a new approach for extracting the local mean and the envelope estimation using the cubic B spline interpolation (CBI) was proposed.The upper envelope and the lower envelope were obtained by using the CBI firstly,and then the local mean and the envelope estimation were extracted from these two envelopes.The comparative experiments between the simulated signals and the mechanical vibration signals verified the superiority of this new approach.