Reviewerly/exHarmony huggingface dataset:
Technical Language Processing for Efficient Classification of Failure Events for Safety Critical Equipment

Previous research has investigated how automated annotation and technical language processing of maintenance work orders can support maintenance decisions for different types of equipment, e.g., Sexton et al. (2018) and Brundage et al. (2021). The objective of this paper is to investigate how technical language processing can be utilized for efficient and automated classification of failure events for safety critical equipment on petroleum facilities (e.g., gas detectors and shutdown valves). For such equipment, maintenance decisions are heavily influenced by the consequence of a failure, e.g., if the failure is classified as critical or degraded, or dangerous or safe.&#x0D; To explore the possibilities for automated classification of failure events, the paper will first present the fundamental concept hierarchy needed during annotation of safety critical equipment on petroleum facilities. This hierarchy is based on previous work where taxonomies from the ISO 14224:2016 standard (ISO 14224, (2016)) have been operationalised and detailed for safety critical equipment. The concept hierarchy is tested by a group of experts on a set of notifications to ensure that it is fit for purpose. The results from the test group are then used to refine the concept hierarchy before a larger group of persons, having different roles in the petroleum industry, is engaged in the entity typing of notifications. This entity typing will then provide the basis for mapping informal technical language to a computable format. By combining this knowledge with available structured information, such as failure mode and detection method, it is expected that an automated, standardised, and more efficient classification of failure events will be possible. Our database of several thousand manually classified notifications collected during the last decade, will finally enable us to evaluate the performance of the automated classification.
Novel Motion Display for Virtual Walking

In this study, a novel motion display device, having 10 DOF (degrees of freedom) for virtual walking is developed. The device consists of a motion seat and a foot module. The device creates synchronous motions of the whole body and lower legs, imparting the straight and turn walking sensations. The motion seat has four-DOF motions of lifting, rolling, pitching, and yawing coordinated by three linear actuators and a DC motor. The three-DOF foot module consists of a pedal-like footrest, which rotates (pitch motion), slides (back and forth translation), and laterally shifts (yaw rotation). Besides, the motions are controlled by microcomputers and 3D space software (Unity).
Detailed Features-Preserving 3D Facial Expression Transfer

In the 3D facial expression transfer field, aiming at the two hot problems of preserving the rich detailed information of the target model to make the generated new expressions realistic and natural, and reducing the training time, this paper presents a new detailed features-preserving 3D facial expression transfer method.Firstly, the detailed features are extracted from 3D face models to obtain the basic expression models without details.Then, the basic expression of source model is transferred to the target model with the improved parametric dimensionality reduction by unsupervised regression.Finally, the detailed features of the target model are restored by using the proposed detailed feature vector adjustment strategy.The visual contrast and quantitative analysis experiments with reconstruction accuracy and training time as the evaluation indexes are conducted on the 3D facial datasets such as COMA in the Matlab software under the Windows 10 environment.The results illustrate that compared with the nonlinear co-learning method, the method can not only transfer the expression of the source model to the target model without losses, but also well preserve the personalized detailed features of the target model, so it can make the generated expressions more realistic and natural.The method also effectively improves the training speed in facial expression transfer.
MCM@HOME: A CONCEPT FOR TEACHING AND LEARNING MATHEMATICS DURING THE CORONA CRISIS

The school lockdown due to the Corona pandemic is perceived as a major challenge by teachers, students and parents. The shift of teaching from the classroom to the children’s rooms results in a massive change in the organization of learning. With a view to the Corona situation in Germany and based on empirical studies on the German school situation, five major issues of distance learning are derived, namely the technical, social-organizational, didactical, content-related and also emotional challenge. In particular, the lack of familiar school structures, the lack of personal contact and issues for appropriate individual diagnosis and support are taken into consideration. Several studies show that these problems are exacerbated by asynchronous distance learning formats, which were predominant in Germany in spring 2020. Therefore, and based on the identified needs for teaching and learning during the school closure, the MCM@home concept is presented as a promising tool for synchronous distance learning in mathematics education. MCM@home is based on the outdoor learning platform MathCityMap and adapts this system for distance learning settings. In MCM@home, students work on digital learning path and can thereby retrieve hints or the sample solution on demand. To access these learning paths, students only need a smartphone with internet access and the installed MathCityMap app (free of costs; no registration required). Within the feature Digital Classroom, the teacher is enabled to monitor the student's progress in real time and provide specific support and feedback to the learner via chat (text, voice message or photo). MCM@home was piloted during the lockdown in spring 2020 and has since been used for digital math lessons in distance learning settings in several European countries. With regard to the theoretical considerations, both the benefits of MCM@home and its limitations are discussed. Finally, an outlook on the upcoming advancement of the concept is given. Within the Erasmus+ Strategic Partnership ASYMPTOTE (2021-2023), MCM@home will be further developed as a stand-alone learning platform and supplemented with adaptivity and learning analytics functions.
Interpretation of Airborne Radiometric data for possible hydrocarbon presence over Bornu basin and its environs, Northeast Nigeria using Thorium normalisation method

A new exploration technique called Thorium Normalisation Method has been applied on the airborne radiometric data of the Bornu basin and its environs to delineate favourable zones for hydrocarbon accumulations within the study area. This method is significant because it indicates the probable presence of hydrocarbon in a sedimentary basin. Separation of the radiospectrometric measurements over each lithologic unit and the estimation of the characteristic statistics of these units were carried out. The statistical treatment applied on the radioelements (K, eTh and eU) of the study area shows a relatively low coefficient of variability (CV%) value for K, eTh and eU signifying their high degree of homogeneity.  The mean value of the radioelements (K ranging from 0.6 to 2.0 %; Th ranging from 9.6 to 15.9 ppm and U ranging from 2.2 to 3.8 ppm) obtained from the statistical analysis correlates with the mean of natural radioelement (K ranging from 0.1 to 2.7 %; Th ranging from 0.4 to 11.2 ppm and U ranging from 0.1 to 3.7 ppm) content of sedimentary rocks which corresponds to shale, the main source rock for hydrocarbon accumulation in the study area. The DRAD (delineation of radioactive anomalies) result ranges from -0.77 to 1.83. The positive values are indicators of favourable zones for the presence of hydrocarbon accumulations. These results suggest that the preliminary information obtained from the use of the thorium normalisation method will guide the exploration of hydrocarbon in the study area.
DPR at SemEval-2021 Task 8: Dynamic Path Reasoning for Measurement Relation Extraction

Scientific documents are replete with measurements mentioned in various formats and styles.As such, in a document with multiple quantities and measured entities, the task of associating each quantity to its corresponding measured entity is challenging.Thus, it is necessary to have a method to efficiently extract all measurements and attributes related to them.To this end, in this paper, we propose a novel model for the task of measurement relation extraction (MRE) whose goal is to recognize the relation between measured entities, quantities and conditions mentioned in a document.Our model employs a deep translation-based architecture to dynamically induce the important words in the document to classify the relation between a pair of entities.Furthermore, we introduce a novel regularization technique based on Information Bottleneck (IB) to filter out the noisy information from the induced set of important words.Our experiments on the recent SemEval 2021 Task 8 datasets reveal the effectiveness of the proposed model.
R. Barnett’s Concept of Ecological University on the Role of the University in the World and for the World (Reflections on the Book)

The paper is devoted to the reflections on the work of Ronald Barnett The Ecological University: A Feasible Utopia. The research field of social philosophy of higher education is emerging, and the work of Barnett lays the foundations for the philosophical analysis of the university. It is shown that the ecological university is viewed not as another formation of the university among the many existing today, but as a counterform of the university, opposing such university models as entrepreneurial and digital universities. Applying the ecological ap­proach to the university will require a revolutionary transformation in thinking, denoting such a turn as shaping the university’s ecosophy. It is emphasized that the ecological university interacts with the world not in an instrumental, technical way, but rather in a transcendental, hermeneutic way: not through the imposition of changes, but through understanding. Particular attention is paid to the following main ideas of the book: the application of an ecosophical approach to the analysis of the new identity of the university in a changing world, a new vision of the interaction between the university and the larger world, based on the ethics of responsibility for the well-being of ecosystems in which the university is involved, and also the ideas of the knowledge ecology and epistemic responsibility. The urgent imperative of the ecological approach to rethinking the identity and the future of the university as a social institution is substantiated, starting from the concept of “deep ecology” the university builds new forms of interaction with the world. The main principles of this interaction are integrity, responsibility and critical dialogue. The authors believe that the research optics of the social and philosophical analysis of the university actualizes the purpose, responsibilities and influence of the university in the changing world.
A Usability Evaluation Process Proposal for ATM Interfaces

Usability evaluations are relevant to know the Usability of a software product. However, it is becoming increasingly important to obtain quantitative information that can be measured, and therefore be compared and be classified. In the ATM domain, not only there is very little literature on proposed methods, but in general very little information on usability benchmarking between ATM applications. In that sense, we propose a Usability Evaluation Process for ATM interfaces. This process allows, through an ordered set of stages, a set of artifacts, techniques and a checklist, to carry out a Usability Evaluation and to obtain both qualitative and quantitative information on the usability level of the interfaces of an ATM application, and to be able to make comparisons and benchmarking. Likewise, one of the proposed artifacts is a questionnaire of relevant aspects in the ATM domain. This process has been validated by usability experts and ATM domain experts. Finally, further validations are expected by applying this proposal in real measurement cases.
Technical Countermeasures for Security Risks of Artificial General Intelligence

Human beings might face significant security risks after entering into the artificial general intelligence (AGI) era. By summarizing the difference between AGI and traditional artificial intelligence, we analyze the sources of the security risks of AGI from the aspects of model uninterpretability, unreliability of algorithms and hardware, and uncontrollability over autonomous consciousness. Moreover, we propose a security risk assessment system for AGI from the aspects of ability, motivation, and behavior. Subsequently, we discuss the defense countermeasures in the research and application stages. In the research stage, theoretical verification should be improved to develop interpretable models, the basic values of AGI should be rigorously constrained, and echnologies should be standardized. In the application stage, man-made risks should be prevented, motivations should be selected for AGI, and human values should be given to AGI. Furthermore, it is necessary to strengthen international cooperation and the education of AGI professionals, to well prepare for the unknown coming era of AGI.
The best of both worlds: Multi-billion word “dynamic” corpora

Nearly all of the very large corpora of English are “static”, which allows a wide range of one-time, pre-processed data, such as collocates. The challenge comes with large “dynamic” corpora, which are updated regularly, and where preprocessing is much more difficult. This paper provides an overview of the NOW corpus (News on the Web), which is currently 8.2 billion words in size, and which grows by about 170 million words each month. We discuss the architecture of NOW, and provide many examples that show how data from NOW can (uniquely) be extracted to look at a wide range of ongoing changes in English.
A Bicategorical Model for Finite Nondeterminism

Finiteness spaces were introduced by Ehrhard as a refinement of the relational model of linear logic. A finiteness space is a set equipped with a class of finitary subsets which can be thought of being subsets that behave like finite sets. A morphism between finiteness spaces is a relation that preserves the finitary structure. This model provided a semantics for finite non-determism and it gave a semantical motivation for differential linear logic and the syntactic notion of Taylor expansion. In this paper, we present a bicategorical extension of this construction where the relational model is replaced with the model of generalized species of structures introduced by Fiore et al. and the finiteness property now relies on finite presentability.
Word-wise Explanation Method For Deep Learning Models Using Character N-gram Input

Estimating the contribution of input towards the prediction via model explainability methods can be insufficient to bring explainability to neural network models if the input consists of character n-grams. As characters can be within multiple words, the section where the prediction has obtained the most information from can not be localised within the text. In this study, novel methods to estimate the importance of words on the prediction of neural network models with character ngram inputs have been proposed. Proposed methods have been tested on text obtained from an e-commerce platform and their performances have been quantitatively compared.
A WGFS Based Approach to Extract Factors Influencing the Marketing of Korean Language in GCC

This research proposed an approach that is intended to determine the minimal set of important factors that influence the desire of learning Korean language in the Gulf Cooperation Council (GCC). Those factors will then influence marketing of the Korean language in GCC by guiding interested people to increase their commercial abilities, improve their information about Korean drama, and prepare them to study or travel to Korea. A total of 500 responses out of 526 questionnaires were used for the analysis process. Merging the weight by SVM and the weight guided feature selection (WGFS) techniques were proposed to build a strong hybrid model of reduction for the investigated dataset. Five different classifiers were used to test the results. Empirical results have showed that the generated factors (the reduct) are very significant to test the ability/inability of learning the Korean language. SVM was shown as the best with accuracy value of 94%. This research contributed to the literature by highlighting the importance of the Korean language in the GCC and by presenting the important factors that influence learners of the Korean language: encouragements and obstacles. Moreover, current research presented the best classifier which yields to the high performance of classification.
Inhibitors to the Electronic Teaching and Learning of Library Science in the Nigerian Universities of the Post-COVID-19 Pandemic Era and the Way Forward

This is a review of the extant literature on inhibitors to the electronic teaching and learning of Library and Information Science (LIS) in Nigerian universities.The university-wide inhibitors as identified by the study are non-provision or inadequacy of: funding, administrative and infrastructural supports, functional ICT laboratories/tools, ICT-compliant teaching staff and standby and responsive technical support for both teachers and students.Library schools' inhibitors include poor maintenance culture, lack of Internet presence, dedicated bandwidth and active websites while the teaching and learning inhibitors highlighted by the study are (older) teachers' poor attitude, concerns on how to retain the copyright of their lecture contents, plagiarism and the quality of students' work; fear of additional workload which may result in stress and burnt-out; lack of freedom or teaching autonomy (as teaching may now take the collaborations of colleagues, computer experts and instructional/graphic designers); teachers'/students' poor expertise and technology background and nature of course, among others.The author made suggestions on the way forward for an increased and a sustainable integration of ICTs in teaching and learning, especially in this Post-COVID-19 Pandemic Era where physical contact and interactions may need to be reduced to the barest minimum to contain contagious communication and consequent health hazards.This review has implications for library educators, students and educational managers in the universities of other developing countries.
A User Interface for Personalising WS-BPEL Scenarios

Due to the huge volume of web services available, both locally and in the cloud, the performance of users and systems need significant research attention. Since WS-BPEL is the dominant language for orchestrating individual web services into business processes, by composing WS-BPEL scripts/scenarios, graphical notations facilitating WS-BPEL design can be extremely useful. Current user interfaces allow WS-BPEL designers not only to invoke selected web services, but also to explicitly ask for recommendations. Then, the user interface appends the services achieving the highest score, according to the attributes’ importance, set by the designer, to their WS-BPEL scenario. However, since the final selection is produced automatically, rather than relying on the designers’ choices, many times, from a personalisation point of view, the adaptation fails. This work reports on the design, development and user evaluation of a user interface that incorporates functionalities that support the designers’ selection performance, thereby upgrading the personalisation level of the WS-BPEL scenarios, as well as the success of the adaptation.
Representation Learning for Out-of-distribution Generalization in Reinforcement Learning

Learning data representations that are useful for various downstream tasks is a cornerstone of artificial intelligence. While existing methods are typically evaluated on downstream tasks such as classification or generative image quality, we propose to assess representations through their usefulness in downstream control tasks, such as reaching or pushing objects. By training over 10,000 reinforcement learning policies, we extensively evaluate to what extent different representation properties affect out-of-distribution (OOD) generalization. Finally, we demonstrate zero-shot transfer of these policies from simulation to the real world, without any domain randomization or fine-tuning. This paper aims to establish the first systematic characterization of the usefulness of learned representations for real-world OOD downstream tasks.
Smooth Approximations and Relational Width Collapses

We prove that relational structures admitting specific polymorphisms (namely, canonical pseudo-WNU operations of all arities n ≥ 3) have low relational width. This implies a collapse of the bounded width hierarchy for numerous classes of infinite-domain CSPs studied in the literature. Moreover, we obtain a characterization of bounded width for first-order reducts of unary structures and a characterization of MMSNP sentences that are equivalent to a Datalog program, answering a question posed by Bienvenu et al.. In particular, the bounded width hierarchy collapses in those cases as well.
Implementation of Extreme Programming Method in Web Based Digital Report Value Information System Design

The process of data collection and processing of student scores that is carried out continuously from year to year is felt to be unable to produce fast, precise and accurate information, because it takes a long time. Computerized information system processing student grades is expected to be able to ease the work of homeroom teachers, so that they can produce valid information in a short time and can be accessed anywhere. With good processing and management, value data processing will be easier, faster, more accurate. The purpose of this research is to build a web-based digital report card information system as a solution offered to help solve problems faced by schools. The system development method used is Extreme Programming (XP) which has several stages, namely planning, designing, coding, testing and Software Increment. The results of this study are the creation of an information system that can provide several advantages as well as efficiency and effectiveness in processing information and managing value data up to the printing of student report cards.
A Survey on Preserving Data Confidentiality in Cloud Computing Using Different Schemes

Cloud Computing (CC) has motivated several individual users and organizations to store and access data remotely. The key advantage of using clouds is to make data available to the user or organization from any geographical location through a network (Internet). Most important benefit of cloud storage is the cost benefits it provides to the user or organization to maintain and store data on a cloud as there would be no need to buy new hardware from user or organization side. But, as the data leaves the user or organization premises, a major concern is about that data security. As the data may be stored on shared storage devices, the data confidentiality is a big challenge in CC among other security issues like data integrity and data availability. There are many schemes available to ensure confidentiality of the data. In many other researches, only cryptography is used. Other researchers have combined cryptography and distribution techniques in which the data is encrypted & split, then stored into diverse cloud spaces. In this paper, focus is on cryptography and introduces the basic concepts of cryptography and also popular algorithms used in cryptography. Comparing and analyzing results of the different algorithms used in cryptography will be the main theme of this paper.