Reviewerly/exHarmony huggingface dataset:
Ticking clocks as dependent right adjoints: Denotational semantics for clocked type theory.

Clocked Type Theory (CloTT) is a type theory for guarded recursion useful for programming with coinductive types, allowing productivity to be encoded in types, and for reasoning about advanced programming language features using an abstract form of step-indexing. CloTT has previously been shown to enjoy a number of syntactic properties including strong normalisation, canonicity and decidability of the equational theory. In this paper we present a denotational semantics for CloTT useful, e.g., for studying future extensions of CloTT with constructions such as path types. The main challenge for constructing this model is to model the notion of ticks on a clock used in CloTT for coinductive reasoning about coinductive types. We build on a category previously used to model guarded recursion with multiple clocks. In this category there is an object of clocks but no object of ticks, and so tick-assumptions in a context can not be modelled using standard tools. Instead we model ticks using dependent right adjoint functors, a generalisation of the category theoretic notion of adjunction to the setting of categories with families. Dependent right adjoints are known to model Fitch-style modal types, but in the case of CloTT, the modal operators constitute a family indexed internally in the type theory by clocks. We model this family using a dependent right adjoint on the slice category over the object of clocks. Finally we show how to model the tick constant of CloTT using a semantic substitution. This work improves on a previous model by the first two named authors which not only had a flaw but was also considerably more complicated.
An adaptive level set method based on joint estimation dealing with intensity inhomogeneity

Automatic object segmentation has been a challenging task due to intensity inhomogeneity. The traditional way is to eliminate the intensity inhomogeneity, which causes the object to lose useful intensity information. The authors propose an adaptive level set method for the segmentation of intensity inhomogeneous images. Firstly, global and local features are utilised to collaboratively estimate the image, which devotes to compensating for intensity inhomogeneity. The local estimation retains detailed spatial information, and the global estimation mainly contains the regional information of the partitioned object. Then, during the construction of the energy functional, joint estimation is introduced to create the external energy. To acquire the precise location of the boundary, a weighting factor indicated by the gradient is introduced into the internal energy. Finally, after the numerical calculation of the energy functional by additive operator splitting algorithm, this method achieves the desired performance in terms of accuracy and robustness. Experimental results verify this method outperforms the comparative methods and can be applied to many real-world scenarios.
DIRECTIONS OF DEVELOPMENT OF BRICS HIGHER EDUCATION SYSTEMS: SELF-UNDERSTANDING AND SELF-PRESENTATION OF CHINESE AND RUSSIAN UNIVERSITIES

In the modern world, universities have become actors in the global market of higher education while retaining their connections with national higher education systems and staying embedded in their national culture and traditions. In this light, self-narratives of BRICS universities are of particular interest as they not only reflect these HEIs' understanding of their purpose and role in the national and international contexts but also the self-understandings of their national higher education systems. This study analyzes texts and visual elements of web-sites of Russian and Chinese universities as a part of their self-narratives and as means they use for communication with internal and external audiences. The study relies on the methodology of critical discourse analysis developed by Michelle Stack and the principles of multimodal analysis proposed by Luc Pauwels. The sample consists of five Russian and five Chinese HEIs which occupy top positions in QS University Ranking for BRICS 2019. National (Russian, Chinese) and international (English) versions of these universities' sites are analyzed. The study shows that Russian and Chinese universities are oriented primarily towards such key stakeholders as prospective students, current students and their families, and governmental agencies. Universities use their web-sites for promoting their brands among prospective students, both domestic and international, and for self-legitimization in the eyes of national governments. It was found that Chinese universities are generally more consistent in their pursuit of internationalization. Both Russian and Chinese universities, however, appear to be more focused on attracting international students rather than on establishing and developing official partnerships and academic collaborations. In their narratives, Chinese universities present themselves as rightful players on the global market that, while being embedded in national tradition and committed to innovation, are able to determine the future of the region and world in general. Russian universities, in their turn, seek to demonstrate their active involvement into the global academic context by highlighting their positions in world university rankings.
Kinds of Translation Error Made by the Students in Writing Abstract of the Theses and Dissertations

This research aims to find the kinds of translation error made in writing abstract of theses and dissertations. This research used descriptive quantitative method to analyze and expose the errors of abstracts of theses and dissertations. The data of this research was the abstracts of theses and dissertations of universities in Makassar. It took 61 abstracts of theses and dissertations from different universities. The abstracts is analyzed by using error analysis technique. The result of this research concluded that the abstracts are found various errors. Errors in the kinds of translation were Omission – Deviation – Modification – Addition - and the least is Inversion. The result of this research provides a new information about translation to the students especially to non-English students, and motivate them to translate the abstract well.
Virtual Reality, Augmented Reality and Beyond: Laboratory of Computer Applications for Health Care at University of São Paulo

The Laboratory of Computer Applications for Health Care at University of São Paulo develop multidisciplinary research involving Computer Science areas and other knowledge fields such as Physiotherapy, Psychiatry, Radiology, and Cardiology. Most studies use concepts besides Computer Science, by aggregating knowledge to solve real problems. In this paper we present the main projects in Virtual Reality and Augmented Reality areas, highlighting serious games, computer-aided diagnosis and therapy, simulation and training. Besides the social and scientific impact inherent to the type of the developed research, some systems are available to health professionals in order to allow technology transfer and consequent technological and economic impact in daily activities of health tasks.
Pathfinding and Navigation

Pathfinding is the algorithmic interpretation and implementation of attaining the shortest route(s) from a given source(s) to destination(s). While the paradigm falls under generic graph theory, there has been much research about different heuristic algorithms. The fundamental aspects of choosing the best-fit (least cost) route implies certain heuristics to be followed. In this section we will try to understand the different concepts of heuristic search algorithms, starting from basic Dijkstra Algorithm to variants of A* (A star). The need for different search algorithms is extremely essential since generic exhaustive algorithms such as breadth-first search (BFS) and depth first search (DFS) are not feasible for games, simulations, and robotics. As we proceed into the depths of each heuristic algorithm, we will encounter different trade-off metrics being employed, from time complexity to space complexity. We will also explore the fundamental aspects of navigation meshes and how to create an intelligent pathfinding agent that gets rewards when it reaches and finds the target object.
Sistem Pakar Diagnosa Penyakit Kulit pada Manusia dengan Metode Dempster Shafer

Skin is the broadest organ in the human body that covers the entire surface of the body and acts as a support for human life. Because of its outermost location, the skin is often attacked by various diseases. This research aims to build an expert system to diagnose 10 types of skin diseases caused by viruses, fungi, bacteria, and parasites based on the knowledge of 3 experts using the Dempster Shafer method to obtain conclusions of skin diseases. Each symptom of skin disease has a value of belief that is used to calculate conclusions in the Dempster Shafer method. Expert system applications that are built can run Android-based smartphones. Testing techniques used in this research are black-box testing, theoretical calculations, system accuracy and MOS (Mean Opinion Score). Comparison of the calculation on the system has been appropriate based on the theoretical calculations. System accuracy testing in 30 sample cases resulted in an accuracy of 90%, but if it was seen as a subsection of expert diagnosis, it resulted in a system accuracy of 92.22%. MOS testing on 30 respondents results in a MOS value of 4.24 from a scale of 5 which shows that the system is proper to use and categorized into a good system.
Identifying Complaints from Product Reviews: A Case Study on Hindi.

When an expectation does not meet reality in a real-world situation, the difference is usually expressed and communicated via an act which is complaint. Customers often post reviews on the products or services they purchase on the retailer websites and different social media platforms, and the reviews may reflect complaints about the products or services. Automatic recognition of customers’ complaints on products or services that they purchase can be crucial for the organizations, multinationals and online retailers since they can exploit this information to fulfil the customers’ expectations including managing and resolving the complaints. In this work, we present the supervised and semi-supervised learning strategies to identify users’ complaints from the language they use to post their reviews. In other words, we automatically identify complaints from the opinionated texts (reviews) about products posted in Hindi. For this, first we automatically crawled the Hindi reviews on different products from the the websites of the retail giant Amazon and the popular social media platform YouTube, and prepared a gold-standard data set via a systematic manual annotation process. We use state-of-the-art classification algorithms for the complaints identification task and our classification models achieve reasonable classification accuracy (F1 = 68.38%) on a gold-standard evaluation test set.
Internet-mediated Islamist semiotics: policing memes and the R4BIA pizza effect

This article explores the semiotics and trans-local dynamics of the decision by a Mancunian pizzeria to brand itself using what is widely regarded as a characteristically Islamist internet meme (the so-called ‘R4bia Sign’). The article explores the genesis, genealogy, and development of a salient religio-political symbol as a means to interrogate specific models of cultural production and reproduction. It focuses in particular on the character of meme-making as a mode of political participation and as part of dissident groups’ repertoires of action. In the process, it problematizes contemporary state policy in relation to policing internet-centred discourse among minority and dissident groups. It is particularly critical of indiscriminate interventions which obscure dynamic, reciprocal, and contextual transformations of meaning associated with ostensibly fixed symbols.
Tabib Family’s Role on Fracture Treatment in Aceh, 1950-2020: A Historical Reconstruction

This research traces the origin of traditional fracture treatment, and identifies the values of local wisdom, especially in traditional healing process performed by the tabib family and to describe how the traditional healing system is developed from ancient times to the present. This study used a qualitative approach and historical methods through topic selection, heuristics or collecting sources, verification or source criticism, and sources and historiography interpretation. Based on the research that has been conducted, the following results were obtained: (1) Fracture treatment has been performed since 1950 in Aceh, especially among the tabib family coming from South Aceh through the inheritance of knowledge from generation to generation; (2) The regeneration process was performed in the healer family, in this case the father inherited from his children or grandparents to his grandchildren to study this knowledge, and practiced it in their entire life; (3) Entering the modern era, traditional medicine has developed in several aspects, so, people tend to believe in this treatment. This study is a part of the historical local wisdom (HLW) to determine how the development of traditional medicine in Aceh from time to time.
ANDES at SemEval-2020 Task 12: A Jointly-trained BERT Multilingual Model for Offensive Language Detection

This paper describes our participation in SemEval-2020 Task 12: Multilingual Offensive Language Detection.We jointly-trained a single model by fine-tuning Multilingual BERT to tackle the task across all the proposed languages: English, Danish, Turkish, Greek and Arabic.Our single model had competitive results, with a performance close to top-performing systems in spite of sharing the same parameters across all languages.Zero-shot and few-shot experiments were also conducted to analyze the transference performance among these languages.We make our code public for further research 1 .
Robustness Analysis of Triangle Relations Attack in Social Recommender Systems

Cloud computing is applied in various domains, among which social recommender systems are well-received because of their effectivity to provide suggestions for users. Social recommender systems perform well in alleviating cold start problem, but it suffers from shilling attack due to its natural openness. Shilling attack is an injection attack mainly acting on the training process of machine learning, which aims to advance or suppress the recommendation ranking of target items. Some researchers have studied the influence of shilling attacks in two perspectives simultaneously, which are user-item's rating and user-user's relation. However, they take more consideration into user-item's rating, and up to now, the construction of user-user's relation has not been explored in depth. To explore shilling attacks with complex relations, in this paper, we propose two novel attack models based on triangle relations in social networks. Furthermore, we explore the influence of these models on five social recommendation algorithms. The experimental results on three datasets show that the recommendation can be affected by the triangle relation attacks. The attack model combined with triangle relation has a better attack effect than the model only based on rating injection and the model combined with random relation. Besides, we compare the functions of triangle relations in friend recommendation and product recommendation.
Robustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs

It has been shown that word embeddings can exhibit gender bias, and various methods have been proposed to quantify this. However, the extent to which the methods are capturing social stereotypes inherited from the data has been debated. Bias is a complex concept and there exist multiple ways to define it. Previous work has leveraged gender word pairs to measure bias and extract biased analogies. We show that the reliance on these gendered pairs has strong limitations: bias measures based off of them are not robust and cannot identify common types of real-world bias, whilst analogies utilising them are unsuitable indicators of bias. In particular, the well-known analogy “man is to computer-programmer as woman is to homemaker” is due to word similarity rather than bias. This has important implications for work on measuring bias in embeddings and related work debiasing embeddings.
Multi‐sensor particle filtering with multi‐step randomly delayed measurements

This paper develops particle filtering for multi-sensor systems with randomly delayed measurements, where the general case that random delay can be multi-step rather than one-step or two-step is considered. Moreover, different sensors can have different delay steps and delay probabilities. Random delays are assumed to be mutually independent for different sensors and modelled by a separate sequence of random variables obeying discrete distributions. Since random delay leads to the actual measurements being dependent rather than independent given states, and this dependence becomes more complicated with the increase of random delay step, a new formula of the local likelihood density is proposed and then a new weighting scheme is adopted in particle filtering to deal with these difficulties. The proposed method is applied to two examples to testify its effectiveness and superiority.
Simplifying Casts and Coercions (Extended Abstract).

This paper introduces norm_cast, a toolbox of tactics for the Lean proof assistant designed to manipulate expressions containing coercions and casts. These expressions can be frustrating for beginning and expert users alike; the presence of coercions can cause seemingly identical expressions to fail to unify and rewrites to fail. The norm_cast tactics aim to make reasoning with such expressions as transparent as possible. They are used extensively to eliminate boilerplate arguments in the Lean mathematical library and in external developments.
Research on Effect Evaluation of Online Advertisement Based on Resampling Method

With the rapid development of the Internet, the online advertising market has become larger and larger. Online advertisers often execute their advertising strategies based on the effect of online advertisements, so it is necessary to evaluate the advertising effect because it determines whether advertisers can display effective advertisements continually and remove ineffective advertisements timely. In practical scenarios, the quantity of ineffective online advertisements is always larger than that of effective online advertisements. The imbalanced distribution of them will bring serious bias to the evaluation models. We propose an improved undersampling method based on clustering (termed UBOC) to overcome the data imbalance. It can balance the advertising data into a more suitable data distribution. In addition, we adopt a new evaluation index for the effect evaluation of online advertisements based on C5.0 decision tree. Experimental results indicate the excellent performance of UBOC and the practical application of evaluation index for online advertisements. They can provide an effective evaluation of online advertisements and achieve the early removal of ineffective advertisements for advertisers, which will greatly increase the revenue brought by advertisements.
UI at SemEval-2020 Task 8: Text-Image Fusion for Sentiment Classification

This paper describes our system, UI, for task A: Sentiment Classification in SemEval-2020 Task 8 Memotion Analysis.We use a common traditional machine learning, which is SVM, by utilizing the combination of text and images features.The data consist text that extracted from memes and the images of memes.We employ n-gram language model for text features and pre-trained model, VGG-16, for image features.After obtaining both features from text and images in form of 2-dimensional arrays, we concatenate and classify the final features using SVM.The experiment results show SVM achieved 35% for its F1 macro, which is 0.132 points or 13.2% above the baseline model.
Education Virtualization Prospects In Pessimistic Light Of Technological Determinism By Jacques Ellul

The article discusses the phenomenon of "education virtualization", which is increasingly being proclaimed as an inevitable consequence of the transition to new technological order (and at the same time -as a catalyst for this process), in the context of the philosophy of technology by J. Ellul.Comparing his ideas with the thoughts of other anti-technicists and technicists, we confirm that this thinker has developed one of the most consistent and convincing versions of technological determinism, insisting that scientific and technological progress (hereinafter -STP) deprives humanity of the essence of freedom.Partially neutralizing the fatalism of J. Ellul, at the same time we agree with him that in modern civilization there are often "absurd and inflexible" attempts to take advantage of the opening technical opportunities without discussing the need for their use, the price and the consequences.Accordingly, concerning new technologies that reduce the teacher's involvement in the educational process, we emphasize the need for scientific discussions (involving the widest possible range of experts in the fields of philosophy of education, pedagogy, technical sciences, as well as the representatives of civil society) on whether to use this technical opportunity (and if so, to what extent and in what situation to do this).Thus, without denying the possibility of virtualization of the educational process, we assert the need to search for the "golden mean" that will not lead the learning process, and therefore the role of the teacher, to synchronous or asynchronous verification of the student's knowledge.
A Study on the Shift of Learning Towards online Platform in the Pandemic Situation

The main aim of this article is to explore the recent developments in the field of education. Due to the widespread of this COVID 19 virus lockdown were implemented in various parts of this globe. In the same manner, educational institutions remain closed due to this pandemic situation. So, the government and the educational institutions shift towards the online mode of teaching to the students. This paper explores both the advantages and the disadvantages to the students and the teachers in utilising the online mode of teaching.
Multifunctional ISO standard Dialogue Act tagging in Italian

The task of Dialogue Act (DA) tagging, a crucial component in many conversational agents, is often addressed assuming a single DA per speaker turn in the conversation. However, speakers’ turns are often multifunctional, that is they can contain more than one DA (i.e. “I’m Alex. Have we met before?” contains a ‘statement’, followed by a ‘question’). This work focuses on multifunctional DA tagging in Italian. First, we present iLISTEN2ISO, a novel resource with multifunctional DA annotation in Italian, created by annotating the iLISTEN corpus with the ISO standard. We provide an analysis of the corpus showing the importance of multifunctionality for DA tagging. Additionally, we train DA taggers for Italian on iLISTEN (achieving State of the Art results) and iLISTEN2ISO. Our findings indicate the importance of using a multifunctional approach for DA tagging.
Correction to: Biostratigraphy, facies analysis and sequence stratigraphy of the Sachun Formation (Interior Fars, Zagros, SW of Iran)

The article “Biostratigraphy, facies analysis and sequence stratigraphy of the Sachun Formation (Interior Fars, Zagros, SW of Iran)”, written by Kamal Karimi,Massih Afghah, Seyyed Hossein Ghetmiri and Mohammad Bahrami was originally published online on 09 October 2020 with Open Access under a Creative Commons Attribution 4.0 International License.