Reviewerly/exHarmony huggingface dataset:
Reconhecimento Automático Multilingue de Entidades Mencionadas em Diversos Domínios, para Efeitos de Anonimização de Tradução Automática

The following article describes the research developed at Unbabel, a Portuguese Machine-Translation start-up, that combines Machine Translation (MT) with human post-edition with a focus on customer service content. With the work carried out within a real multilingual AI powered, human-refined, MT industry, we aim to contribute to furthering MT quality and good-practices, by exposing the importance of having continuously in development, robust Named Entity Recognition systems for General Data Protection Regulation (GDPR) compliance. We will report three different experiments, resulting from a shared work with Unbabel´s linguists and Unbabel´s Artificial Intelligence (AI) engineering team, matured over a year. The first experiment focused on developing a methodology for the identification and annotation of domain-specific Named Entities (NEs) for the Food-Industry. The devised methodology allows the construction of gold standards for building domain specific NER systems and can be applied for a myriad of different domains. With the implementation of the designed method, we were able to identify the following domain-specific NEs set: Restaurant Names; Restaurant Chains; Dishes; Beverage, Ingredients. The second and third experiments explored the possibilities of constructing, in a semi-automatically way, multilingual NER gold standards for different domains and language pairs, using aligners that project Named Entities across a parallel corpus. Both experiments made it possible to benchmark four different open-source aligners (SimAlign; Fastalign; AwesomeAlign; Eflomal), allowing to identify the one with better performance and, simultaneously, validate the aforementioned approach. This work should be taken as a statement of multidisciplinary, proving and validating the much-needed articulation between different scientific fields that compose and characterize the area of Natural Language Processing (NLP).
Aquisição e desenvolvimento linguísticos: investigação e aplicações – sintaxe de português europeu L2

This paper has two major goals. The first one is to present a summary of some of the studies which have been conducted on the L2 acquisition of syntactic properties in European Portuguese within a generative framework, considering the research questions, the phenomena, and the learner profiles which have been investigated, the methodologies used, and the main conclusions which have been reached by these studies. Building on this summary, our second goal is to identify some of the gaps in the existing research and to propose some ideas for future work.
Web Book Recommendation System Based on Collaborative Filtering and Association Mining

Recommendation systems are used to make suggestions for products to buy or view. They steer consumers to the things that will meet their demands by sifting through a big database of information. For recommending items, several techniques such as content filtering, collaborative filtering, and association mining techniques have been employed. This improves performance by integrating collaborative-based filtering with association rule mining to overcome the problem of data sparsity. The results show that the suggested recommendation algorithms outperform the competition and address issues like data sparsity and scalability. To overcome the issue of no similarity, the proposed recommending system is based on similar items by computing similarity between user chosen items and available database items.
PENINGKATAN KEMAMPUAN MENGENAL TUJUAN DAN FUNGSI TEKS TANGGAPAN DENGAN MODEL PEMBELAJARAN LEARNING COMMUNITY SISWA KELAS 9 G MTsN 1 TUBAN

In the 2013 curriculum, the implementation of Indonesian language learning is done on a text-based. One of the texts taught in response text. Indicators of the success of learning response texts include students being able to recognize the purpose and function of response texts. It was found that many students had difficulty in learning. This is caused by the selection of an inappropriate learning model. Therefore, research was conducted to increase the ability to recognize the purpose and function of the response text by using the learning community learning model. The research method used is classroom action research. The subjects of this study were students of class 9G MTsN 1 Tuban. The process of implementing classroom action is through four stages starting from (1) planning, (2) action, (3) observing, and (4) reflecting. The types of instruments used are student observation sheets and teacher observation sheets, group evaluation sheets, test questions, and questionnaires. To test the validity of the data, the researcher used method triangulation and source triangulation techniques. The results of this study indicate that the learning of simple response texts has increased by using the learning community learning model. This can be seen from the average score of students before being given the action was 55.5, after being given the action at the end of the first cycle the average score became 61.80. Furthermore, at the end of the second cycle, the average score obtained was 71.80. While in the third cycle obtained an average score of 80.08. Overall, at the end of the third cycle, all aspects and criteria for recognizing the purpose and function of simple response texts experienced a significant increase
Highly Adaptive and Fast Tetrahedral Mesh Generator for Multi-Compartment Human Head Model with Deep Brain Structures with EEG Application

Abstract Purpose : This paper introduces a highly adaptive and fast approach for generating a finite element (FE) discretization mesh for a given multi-compartment human head model obtained through a magnetic resonance imaging (MRI) dataset. The goal is to create accurate deep brain structures for electroencephalographic (EEG) source localization and applications. Methods : We present a recursive application of solid angle labeling for surface segmentation with an adaptive scheme, i.e., a set of smoothing, inflation, and optimization tasks to enhance the mesh quality. Results : The results indicate that our approach can produce a FE mesh with an accuracy greater than 1.0 millimeters, a significant milestone for 3D structure discretization and EEG source localization estimation. Conclusions : Our method, implemented in the Matlab-based Zeffiro Interface, can manage the labeling aspect remarkably well to achieve human head FE meshes with complex deep brain structures using a time-effective parallel computing system.
Practice of Symbiosis Education Theory in the Management of Primary School by Head Teachers

At this stage, China has implemented a new round of educational reform.After a period of practice, the development of China's education has made considerable progress.However, there are still some problems.It is difficult to effectively communicate and coordinate the development between teachers, students and students, which affects the promotion of quality education.In particular, primary education is a key shaping period in school education, which is related to children's quality and quality cultivation.Under the policy of double reduction, the key to carry out quality education is to find out the educational concept and mode of transformation from examination oriented education to quality education.The symbiotic education theory attaches great importance to giving play to the advantages and enthusiasm of students and teachers.Both parties participate in class management and form a good symbiotic circle by exploring appropriate symbiotic points.In order to promote and realize quality education, the author, based on teaching practice, integrates the symbiosis theory into class management, attaches importance to cultivating and giving play to students' individual advantages, actively participates in class collective management, and achieves common progress through assistance, thus forming a class collective with distinctive class culture and strong cohesion, and realizing a new model for the common development of individuals and collectives.Through the cultivation of symbiotic education mode, the cohesion of the author's class has been significantly enhanced, teachers, students and students can develop
The Stylistic Classification of Modern Chinese Adverbs for Automatic Style Recognition

In natural language understanding, different styles are generally identified by the characteristics of words and sentence patterns.However, the current research on style in linguistics mainly focuses on the construction of the Chinese style system and its characteristics.It has not yet involved the classification of style for specific words, which has the problem of mismatch between theory and application.In the linguistic field, adverbs are generally classified from the perspective of semantics, while this paper is oriented toward the automatic identification of style.Therefore, we classified the adverbs from the perspective of style.Firstly, the modern Chinese style is regarded as a hierarchical system, and we divide it into formal and informal styles, with formal style including elegant style and written formal style, and informal style including spoken mandarin style and dialect style.Secondly, we proposed the criteria for classifying Chinese adverbial style, and they are composition characteristics, rhyme, morphology, and frequency.Finally, we also proposed the concept of "cross-style adverbs" and introduced it.It can not only provide a reference for the corpora classification of other Chinese words but also provide a database for the automatic recognition of Chinese corpora, and further improve the accuracy of the automatic recognition of corpora.
Application of Spatial Data Mining in the Process of Discovering Interesting and Previously Unknown, but Potentially Useful, Patterns from Large Spatial Datasets

Spatial data mining has been typically used in the Geographical Information system from physical datasets and locations to real-world events. One of the procedures generally used in capital data mining is vector data representation. Vector data is the most commonly used data across the world. Information in this format consists of tips, angles, and quadrilaterals. It is the simplest method of analysing the data where the vector data consists of tips correlate pairs to indicate a physical location in the world. These points can be joined in a particular way to form closed areas marked as quadrilaterals. Vector data is extremely useful for storing and representing data that has discrete boundaries such as international borders, streets, buildings, and many more. Modern technologies such as Google use geological information and open street maps to represent the data in vector data stricture wise. Keyword : Spatial data mining, Vector data, Information system, Security, Data
Expert Systems for Emulating the Decision Making Ability of a Human Expert

Expert systems are a type of technology that supports an organization to identify the challenges of a project and help the organization to take effective steps to resolve the challenges. The research study is based on the utilization of expert systems on the decision-making ability of human experts. The research study has adopted a positivist research philosophy, exploratory research design, and deductive research approach to mitigate the research objectives. On the other hand, the research study has been done through the implication of a secondary quantitative data collection method. Based on the secondary quantitative research study, the study has shown the potential impact of an expert system on the decision-making ability of human experts. This research study has explained the way expert systems are creating a positive influence on the operational efficiency of an organization and the utilization of expert systems has also enhanced the decision-making ability of human exports up to 42%. Moreover, the implication of expert systems is beneficial for providing growth in business. Keyword : Human experts, project, Artificial intelligence, technology, expert systems.
Few-Shot Named Entity Recognition with Hybrid Multi-Prototype Learning

Abstract Information extraction provides the basic technical support for knowledge graph construction and Web applications. Named entity recognition(NER) is one of the fundamental tasks of information extraction. Recognizing unseen entities from numerous contents with the support of only a few labeled samples, also termed as few-shot learning, is a crucial issue to be studied. Few-shot NER aims at identifying emerging named entities from the context with the support of a few labeled samples. Existing methods mainly use the same strategy to construct a single prototype for each entity or non-entity class, which has limited expressiveness power and even biased representation. In this work, we propose a novel hybrid multi-prototype class representation approach. Specifically, for entity classes, we first insert labels after entities in support sentences to enrich the learned token and label embeddings with more contextual information. Then, for each entity span, the contextual token embeddings are averaged to form its entity-level prototype, while the contextual label embedding is considered as its label-level prototype. The set of prototypes for all entities in a class constitute the multi-prototype of this entity class. For non-entity class, we directly use the set of token embeddings to represent it, where multi-prototype refers to the multiple token embeddings. By treating the entity and non-entity classes differently, our hybrid strategy can extract more precise class representations from the support examples. Furthermore, we establish a harder and more reasonable experimental setting of few-shot NER by offering a rigorous sampling strategy. Extensive empirical results show that our proposal improves F1 scores by 3%∼10% absolute points over prior models on popular benchmark Few-NERD under both loose and our proposed rigorous sampling constraints, achieving state-of-the-art performance.
Analisis Debit Banjir Untuk Perencanaan Bendung Malunda Kabupaten Majene

This study aims to analyze the flood discharge of the Malunda Weir design. This research can be used as a reference for similar research. Due to the earthquake in Palu, the dam cracked in several parts, then collapsed due to flooding. Planning for flood control, river security, and other water structures can be carried out properly if the planned flood discharge in the river is known. Regional average rainfall is calculated by the Algebraic Average method. Then analyzed by calculating the design rainfall using the Gumbel method, Log Pearson Type III and Log Normal. Then determine the flood discharge using the HSS Nakayasu and HSS Gama I methods with return periods of 25, 50, and 100 years. Based on the calculation results of the Nakayasu HSS method, the flood discharge for a period of 25 years = 791.570 m3/second; 50 years = 903.575 m3/second ; and 100 years = 1014, 533 m3/sec. In the HSS Gama I method, the flood discharge for a period of 25 years = 860,794 m3/second; 50 years = 1005.687 m3/second ; and 100 years = 1149, 507 m3/sec. From the calculation of the 2 HSS methods, it can be concluded that the closest Synthetic Unit Hydrograph is the Synthetic Unit Hydrograph. From the calculation of the 2 HSS methods, it can be concluded that the closest Synthetic Unit Hydrograph is the Synthetic Unit Hydrograph.
Analysis of Individual Factors in Improving Knowledge Sharing: Case Study of Accounting Education Students

Education is a long-term investment in human resources for the survival of human civilisation in the world. Advances in technology can be used as a supporting tool in the learning process. However, the technology used can be influenced by individual and organisational factors in its use. This study aims to determine individual, organisational and technological factors in the student knowledge sharing process. This study uses a quantitative approach with a descriptive survey design method. Respondents in this study were students of the Accounting Education, Universitas Sebelas Maret class 2018-2020, with 149 students. The indicators used in the measurement are individual factors (self-efficacy, willingness to share, and reciprocal rules), organisational factors (lecturer support and competitiveness), and technological factors (availability of technology and use of technology). The data analysis method uses the SEM model. The study results show that individual and technology factors affect the knowledge-sharing process, and the organisation does not affect the knowledge-sharing process.
Construction and prediction of China's financial stress index based on the A-E-L coupling perspective

As economic globalisation and financial liberalisation continue to develop, domestic and international shocks have increased the pressure on China's financial system. To this end, this paper constructs the China Financial Stress Index (CFSI) to analyse China's financial situation. This paper selects 10 representative indicators of the banking, bond, foreign exchange, real estate and insurance markets for the period 2011from 2021. Based on the dimensionality reduction of the indicators, the paper uses the hierarchical analysis method (AHP) and the entropy weighting method (EWM) to assign weights, and couples them with the Lagrange multiplier method to obtain the China Financial Stress Index, and finally uses the long and short-term memory network model (LSTM) to forecast. The results show that the CFSI constructed in this paper can better portray the dynamic financial stress situation in China, and the overall financial stress in China can be divided into three trends.
A Mimetic Method

&#x0D; &#x0D; &#x0D; How does a practice of mimesis — as dramatic enactment in a live-action role-playing game (LARP) — relate to the design of artificial intelligence systems? In this article, I trace the contours of a mimetic method, working through an auto-ethnographic approach in tandem with new materialist theory and in conjunction with recent tendencies in design research to argue that mimesis carries strong potential as a practice through which to encounter, negotiate, and design with artificial intelligence imaginaries. Building on a new materialist conception of mimesis as more-than-human sympathy, I illuminate how LARP that centered on the enactment of a fictional artificial intelligence system sustained an encounter with artificial intelligence imaginaries. In what can be understood as a decidedly mimetic way of doing ethnography of algorithmic systems, I argue that we need to consider the value of mimesis — understood as a practice and a method — as a way to render research into artificial intel- ligence imaginaries.&#x0D; &#x0D; &#x0D;
Analysis of pottery from Žďár nad Sázavou – taré město with a focus on the technology of the assemblage

The study focuses on ceramic production from Žďár nad Sázavou – Staré město, an agglomeration that formed in the third quarter of 13th century and was abandoned after the founding of the ‘new’ town in the early 14th century. The large pottery collection is well dated and captures changes in pottery production during the medieval transformation, tightly connected with the colonisation of the Bohemian-Moravian Highlands. The pottery assemblage from the 2004 excavation season was processed in this study. Material from the pottery kiln discovered in 2006 and found during the review of the research documentation was supplemented afterwards. The main part of study evaluates ceramic production technology, which was rapidly changing during this period. Pottery fragments were divided into ceramic classes according to the properties of the ceramic mass and firing. The descriptive system of technological marks is a part of the study, but it could be used for other medieval pottery collections. Detailed attention was paid to pottery-forming technique marks: coiling, wheel forming and wheel throwing. The analysis of pottery technology is based on the chaîne opératoire of medieval ceramic production. The macroscopic analysis of pottery-making technology is connected with the conclusions of natural science analyses. Their aim was to validate and specify the macroscopic description of ceramic classes and also detailed information about pottery provenance and technology. The analysis of the pottery provides information for the future productiondistribution model of pottery production in the area.
Hyperimage Index

Image has gone hyper, can research catch up? This essay proposes collective indexing as an alternative to academic publishing for rendering research on fast-changing and larger-than-human subjects such as algorithmic images. Following the introduction of notions of network and scale in my research, the essay articulates the value of collective indexing while mapping out contemporary examples. Collective indexing produces new ways of knowledge making and community building, as well as new forms of research aesthetics apt for addressing the distributed nature of algorithmic image systems.
Crisi. Una conversazione interdisciplinare su una parola chiave della nostra congiuntura storica

This collaborative essay aims to provide a theoretical and discursive background to the thematic issue of Languages Cultures Mediation – LCM devoted to exploring crisis/crises. It consists, therefore, of two parts. The first one starts with a few considerations on the current conjuncture, in which “crisis” stands out as a powerful keyword which is ubiquitous across mainstream communication and public debate. It continues by foregrounding some thoughts on the definitions of this term and its deceptive intuitiveness, concurring to highlight some slippages and shifts in its usage and meanings over time. Finally, it attempts to stylize some assumptions, premises, perspectives and theoretical issues concerning the conceptualization of crisis and how to interpret it, including narratives and memory work. The second part of the essay provides a review and a discussion of theoretical perspectives and interpretive tools for addressing more specifically the category of crisis as a discursive, affective and imaginative construction. In the process, it engages in a conversation with some recent analytical approaches to crisis pertaining, mostly, to the conceptual and ideological arenas of linguistics, critical discourse analysis, narrative and metaphor studies, political communication.
Inconsistent Projections

&#x0D; &#x0D; &#x0D; In this paper we propose a time-based digital tool, a diagram-in-the-making, as to learn about computer vision in the field of security. With this method we want to map the heterogeneous and multiple nature of security vision tech- nologies and their imaginaries. Concretely, we conducted qualitative interviews with professionals who develop, use or militate against these technologies and asked them to draw a diagram as to support their narrative. In spatialising the conversation, the diagrams allow for a wide variety of actants and relations to emerge. The time-based unfolding of the lines enacts imaginaries of computer vision practices which are intrinsically intertwined with the narratives of which they are part. It creates space for hesitation, uncertainties, incongruities and complexities that would have been rendered invisible in a geographic map. Through the spatial, material and temporal unfoldings of the diagrams we learn that security vision imaginaries are partial and contradictory.&#x0D; &#x0D; &#x0D;