Symmetric Relations Research Articles

Normal orthogonality spaces

An orthogonality space is a set X together with a symmetric and irreflexive binary relation ⊥, called the orthogonality relation. A block partition of X is a partition of a maximal set of mutually orthogonal elements of X, and a decomposition of X is a collection of subsets of X each of which is the orthogonal complement of the union of the others. (X,⊥) is called normal if any block partition gives rise to a unique decomposition of the space. The set of one-dimensional subspaces of a Hilbert space equipped with the usual orthogonality relation provides the motivating example. Together with the maps that are, in a natural sense, compatible with the formation of decompositions from block partitions, the normal orthogonality spaces form a category, denoted by NOS. The objective of the present paper is to characterise both the objects and the morphisms of NOS from various perspectives as well as to compile basic categorical properties of NOS.

Time-Varying Vibration Compensation Based on Segmented Interference for Triangular FMCW LiDAR Signals

Frequency modulation continuous wave (FMCW) light detection and ranging (LiDAR) 3D imaging system may suffer from time-varying vibrations which will affect the accuracy of ranging and imaging of a target. The system uses only a single-period FMCW LiDAR signal to measure the range of each spot; however, traditional methods may not work well to compensate for the time-varying vibrations in a single period because they generally assume the vibration velocity is constant. To solve this problem, we propose a time-varying vibration compensation method based on segmented interference. We first derive the impact of time-varying vibrations on the range measurement of the FMCW LiDAR system, in which we divide the time-varying vibration errors into primary errors caused by the vibrations with a constant velocity and quadratic errors. Second, we estimate the coefficients of quadratic vibration errors by using a segmented interference method and build a quadratic compensation filter to eliminate the quadratic vibration errors from the original signals. Finally, we use the symmetrical relations of signals in a triangular FMCW period to estimate the vibration velocity and establish a primary compensation filter to eliminate the primary vibration errors. Numerical tests verify the applicability of this method in eliminating time-varying vibration errors with only a one-period triangular FMCW signal and its superiority over traditional methods.

MRE: A Military Relation Extraction Model Based on BiGRU and Multi-Head Attention

A great deal of operational information exists in the form of text. Therefore, extracting operational information from unstructured military text is of great significance for assisting command decision making and operations. Military relation extraction is one of the main tasks of military information extraction, which aims at identifying the relation between two named entities from unstructured military texts. However, the traditional methods of extracting military relations cannot easily resolve problems such as inadequate manual features and inaccurate Chinese word segmentation in military fields, failing to make full use of symmetrical entity relations in military texts. With our approach, based on the pre-trained language model, we present a Chinese military relation extraction method, which combines the bi-directional gate recurrent unit (BiGRU) and multi-head attention mechanism (MHATT). More specifically, the conceptual foundation of our method lies in constructing an embedding layer and combining word embedding with position embedding, based on the pre-trained language model; the output vectors of BiGRU neural networks are symmetrically spliced to learn the semantic features of context, and they fuse the multi-head attention mechanism to improve the ability of expressing semantic information. On the military text corpus that we have built, we conduct extensive experiments. We demonstrate the superiority of our method over the traditional non-attention model, attention model, and improved attention model, and the comprehensive evaluation value F1-score of the model is improved by about 4%.

Indifference to symmetry in Hrushovski's ab initio construction

Denote Hrushovski's non-collapsed ab initio construction for an n-ary relation by M≁ and the analogous construction for a symmetric n-ary relation by M∼. We show that M≁ is isomorphic to a proper reduct of M∼ and vice versa, and that the combinatorial pregeometries associated with both structures are isomorphic.

COVID-19 and the crisis in the internationalization of higher education in emerging contexts

This article analyzes the effects of the COVID-19 pandemic in the Brazilian context and highlights the impacts of internationalization of higher education in the country. Qualitative in nature, the article is characterized as an exploratory-descriptive research, carried out from a bibliographic and documentary examination. Analysis: it was revealed that Latin America and the Caribbean are parts of the global regions most affected by the pandemic that experienced severe negative aggravation in their economies. In particular, in Brazil, findings reveal that the repercussions of the crisis impacted the public resources for education through budget cuts, while the private institutions suffered from an increase in defaults and evasion. Internationalization as a transversal dimension of higher education also suffered from the effects of the pandemic, and in Brazil, information and communication technologies were used to maintain international and intercultural learning and academic cooperation. This made it possible to increase the number of students benefited and to print out an equitable perspective on internationalization of higher education. For the future, it will be necessary to consolidate strategies that include information and communication technologies and promote the strengthening of cooperation networks, with the development of policies that support a more symmetrical relationship in the South–South and South–North, even in unfavorable scenarios.

Research on Projection Gray Target Model Based on FANP-QFD for Weapon System of Systems Capability Evaluation

The construction and evaluation of weapon system of systems (SoS) construction should start from the perspective of demand so that the system construction can better meet the actual demand. Based on the in-depth analysis of SoS architecture, an integrated framework for SoS requirements decomposition and capability evaluation is proposed. First of all, quality function development (QFD) is used to decompose the SoS requirements step-by-step. According to the house of quality mapping from missions to capabilities and performances, SoS evaluation indicator elements are determined and the requirement analysis framework is primarily formed. Second, the fuzzy analytical network process (FANP) is used to capture both symmetrical and asymmetrical relationships between the factors of each level in which priorities are calculated under subjective, vague, and uncertain preference information. And then, weighted by priorities of performance requirements that calculated by integrating FANP and QFD model, a projection gray target model is constructed for SoS capability evaluation under uncertain information and poor data. Finally, the proposed model is verified effectively and accurately by a case study, which provides an integrated method for both SoS requirement analysis and capability evaluation, and lays a theoretical foundation for system design and system optimization. Capability evaluation, fuzzy analytical network process (FANP), gray target model, quality function development (QFD), requirements analysis, weapon system of systems (SoS).

A Technology Acceptance Model-Based Analytics for Online Mobile Games Using Machine Learning Techniques

In recent years, the enhancement in technology has been envisioning for people to complete tasks in an easier way. Every manufacturing industry requires heavy machinery to accomplish tasks in a symmetric and systematic way, which is much easier with the help of advancement in the technology. The technological advancement directly affects human life as a result. It is found that humans are now fully dependent on it. The online game industry is one example of technology breakthrough. It is now a prominent industry to develop online games at world level. In this paper, our main objective is to analyze major factors which encourage mobile games industry to expand. Analyzing the system and symmetric relations inside can be done into two phases. The first phase is through a TAM Model, which is a very efficient way to solve statistical problems, and the second phase is with machine learning (ML) techniques, such as SVM, logistic regression, etc. Both strategies are popular and efficient in analyzing a system while maintaining the symmetry in a better way. Therefore, according to results from both the TAM model and ML approach, it is clear that perceived usefulness, attitude, and symmetric flow are important factors for game industry. The analytics provide a clear insight that perceived usefulness is an important parameter over behavior intention for the online mobile game industry.

ICT-enabled organisational flexibility to support sustainable growth in Europe amidst a pandemic

PurposeInformation and communications technology (ICT) is helping to create a sustainable information society and foster development. This study aims to investigate the interdependencies of organisational flexibility enabled by ICT, demographics and containment measures in the ever more dismal economic performances seen during COVID-19 with a view to preparing socio-economic systems for similar future shocks.Design/methodology/approachUsing non-classical fuzzy-set qualitative comparative analysis, the authors are able to capture the asymmetric relationships and complexities found in real life.FindingsAnalysing data acquired from the Oxford COVID-19 Government Response Tracker and Eurostat, the authors find these conditions give mixed results depending on how they are combined. The results imply that countries under strict containment measures might only be able to survive when fully equipped with ICT solutions. E-commerce also plays an important role in countries with a below-average decrease in their growth rate. Put differently, the presence and absence of telework produces mixed results. If the population is old, telework seems to generate the desired outcomes. Yet, when the population is young, it might be more beneficial to avoid this practice.Originality/valueUnlike studies that mainly assumed symmetrical effects and linear relationships, this study investigates the interdependencies of organisational and macro-level factors. On the micro level, this study is useful for managers allocating IT investments for any future occurrence of a general disaster/pandemic. On the macro level, the study can act as an example for the rest of the world regarding the appropriateness of assorted COVID-19 pandemic responses as witnessed in European countries.

On a Riemann–Hilbert problem for the NLS-MB equations

In this paper, we study a coupled system of the nonlinear Schrödinger (NLS) equation and the Maxwell–Bloch (MB) equation with nonzero boundary conditions by Riemann–Hilbert (RH) method. We obtain the formulae of the simple-pole and the multi-pole solutions via a matrix Riemann–Hilbert problem (RHP). The explicit form of the soliton solutions for the NLS-MB equations is obtained. The soliton interaction is also given. Furthermore, we show that the multi-pole solutions can be viewed as some proper limits of the soliton solutions with simple poles, and the multi-pole solutions constitute a novel analytical viewpoint in nonlinear complex phenomena. The advantage of this way is that it avoids solving the complex symmetric relations and repeatedly solving residue conditions.

Three-Way Multi-Attribute Decision Making Based on Outranking Relations under Intuitionistic Fuzzy Environments

With the increasing complexity of the human social environment, it is impossible to describe each object in detail with accurate numbers when solving multiple attribute decision-making (MADM) problems. Compared with the fuzzy set (FS), the intuitionistic fuzzy set (IFS) not only has obvious advantages in allocating ambiguous values to the object to be considered, but also takes into account the degree of membership and non-membership, so it is more suitable for decision makers (DMs) to deal with complex realistic problems. Therefore, it is of great significance to propose a MADM method under an intuitionistic fuzzy environment. Moreover, compared with the traditional 2WD, by putting forward the option of delay, the decision-making risk can be effectively reduced using three-way decision (3WD). In addition, the binary relations between objects in the decision-making process have been continuously generalized, such as equivalence relation which have symmetrical relationship, dominance relation and outranking relation, which are worthy of study. In this paper, we propose 3WD-MADM method based on IF environment and the objective IFS is calculated by using the information table. Then, the hybrid information table is used to solve the supplier selection problem to demonstrate the effectiveness of the proposed method.

Thinking with autoethnography in collaborative research: A critical, reflexive approach to relational ethics

In this article, we propose a distinctive critical, reflexive approach to relational ethics in ‘collaborative, democratic and transformative’ research. Underpinning the approach is the view that the buzzwords of ‘collaboration’ and ‘co-creation/co-production’ may signify equitable, symmetrical power relations and, as a result, romanticise collaborative research as straightforward processes of inclusion. The approach integrates critical, reflexive analysis of the play of power in the ‘with’ in ‘research with, not on, people’ and the ‘co’ in ‘co-creating knowledge’ into the ongoing collaborative research process. As a main method for critical, reflexive analysis, the approach uses ‘thinking with’ autoethnography. In the article, we illustrate the approach by showing how we ‘think with’ autoethnographic texts to respond to discomfort and analyse the tensions in the co-constitution of knowledge and subjectivities in the preliminary phase of a collaborative, participatory research project on dance for people with Parkinson’s disease and their spouses.

Classification of Motor Imagery Electroencephalography Signals Based on Image Processing Method.

In recent years, more and more frameworks have been applied to brain-computer interface technology, and electroencephalogram-based motor imagery (MI-EEG) is developing rapidly. However, it is still a challenge to improve the accuracy of MI-EEG classification. A deep learning framework termed IS-CBAM-convolutional neural network (CNN) is proposed to address the non-stationary nature, the temporal localization of excitation occurrence, and the frequency band distribution characteristics of the MI-EEG signal in this paper. First, according to the logically symmetrical relationship between the C3 and C4 channels, the result of the time-frequency image subtraction (IS) for the MI-EEG signal is used as the input of the classifier. It both reduces the redundancy and increases the feature differences of the input data. Second, the attention module is added to the classifier. A convolutional neural network is built as the base classifier, and information on the temporal location and frequency distribution of MI-EEG signal occurrences are adaptively extracted by introducing the Convolutional Block Attention Module (CBAM). This approach reduces irrelevant noise interference while increasing the robustness of the pattern. The performance of the framework was evaluated on BCI competition IV dataset 2b, where the mean accuracy reached 79.6%, and the average kappa value reached 0.592. The experimental results validate the feasibility of the framework and show the performance improvement of MI-EEG signal classification.

How language shapes interpersonal distance: An analysis of pronominal forms of address in Spanish, Polish and Italian

The aim of the present article is to compare the formal and functional aspects of pronominal forms of address in three languages: Spanish, Polish and Italian. The classic typology of the category analysed divides it in two groups: the T-forms applied in the conversations between the participants of symmetrical relations and the V-forms considered reverential and asymmetrical. The present study demonstrates and analyses the pronominal systems in two Romance languages, Spanish and Italian, and a Slavic language, Polish. We classify the pronouns according to the confidentiality/distance parameter, showing the similarities and differences between the formal characteristics, as well as the socio-cultural factors that determine the election of determined pronominal form of address.

Touch in the relationship between the child and the educator. An example of a crèche

The article poses the question: how can an educator, accompanying in development, touch a young child, in what situation? When can the educator refrain from touching the child? The analysis of the literature shows that the touch in the relationship of an adult and a child coexists with the look and the word. It can be compared to a dialogue. It becomes an opportunity to create conditions that allow a child to participate in a relationship with an adult, be active, and do something on his own. The analysis of the literature allows to characterize the non-directive concept of education and the symmetrical relations of the educator and the young child in relation to touch. It allows the educator to think about how to respect the desires and abilities of the child.

Emergence of intraverbals after reading a text: learning principles involved in reading comprehension

ABSTRACT We studied the effect of learning two symmetrical verbal relations in areading comprehension task. We explored emergence of intraverbals after 7- and 8-year-old children read ashort text with sentences in which a word A was related to B and B to C(e.g., “Argentina,” “Buenos Aires,” and “El Botánico”). Thereafter, all ABC intraverbal combinations (e.g., C-A– “Name the country of El Botánico”) were probed without reinforcement with written stimuli and responses. In Experiments 1 and 2, seven of 12 children demonstrated the emergence of all intraverbals. In Experiments 3 and 4, 6 experimentally naïve children and the five children who failed to demonstrate the emergence of all intraverbals learned first simpler, symmetrical intraverbals (e.g., that acountry is Argentina and that Argentina is acountry). All 11 children immediately demonstrated the emergence of all ABC intraverbals. Thus, results evidence reading comprehension facilitated by learning symmetrical intraverbals.

L-Fuzzy Rough Approximation Operators Based on Co-Implication and Their (Single) Axiomatic Characterizations

For L a complete co-residuated lattice and R an L-fuzzy relation, an L-fuzzy upper approximation operator based on co-implication adjoint with L is constructed and discussed. It is proved that, when L is regular, the new approximation operator is the dual operator of the Qiao–Hu L-fuzzy lower approximation operator defined in 2018. Then, the new approximation operator is characterized by using an axiom set (in particular, by single axiom). Furthermore, the L-fuzzy upper approximation operators generated by serial, symmetric, reflexive, mediate, transitive, and Euclidean L-fuzzy relations and their compositions are characterize through axiom set (single axiom), respectively.

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Much attention has been paid on the soil-water characteristic curve (SWCC) during decades because it plays great roles in unsaturated soil mechanics. However, it is time-consuming and costly to obtain a series of entire saturation-suction data by experiments. The curves acquired by directly fitting empirical equations to limited experimental data are greatly different from the actual SWCC, and the relevant soil parameters obtained by inaccurate curve are also incorrect. Thus, an improved prediction method for more accurate entire SWCC was established. This novel method was based on the analysis of shape characteristics of SWCC with three critical points S , C 1 , and C 2 under the hypothesis of geometrical symmetric relation. The theoretical computation was specifically deduced under conventional Gardner, VG, and FX models, respectively, and then inferred on different soil types of 45 collected SWCC datasets. This geometrical symmetric relation exhibited well in all these three conventional empirical equations, especially in Gardner equation. Finally, a series of filer paper tests on sand, silt, and clay were also carried out to acquire entire SWCC curve for the verification and evaluation of the proposed geometrical method. Results show that this improved prediction method effectively decreases deviation resulting from directly fitting empirical equations to limited data of wide types of soils. The averaged improvement was larger under VG equation than under Gardner and FX equation. It proved that the accuracy of predicting greatly depends on the shape characteristic point of maximum curve curvature (point C 2 ), other than the number of points. This research provides a novel computation method to improve prediction accuracy even under relative less experimental data.

Generalized Fitch Graphs III: Symmetrized Fitch maps and Sets of Symmetric Binary Relations that are explained by Unrooted Edge-labeled Trees

Binary relations derived from labeled rooted trees play an import role in mathematical biology as formal models of evolutionary relationships. The (symmetrized) Fitch relation formalizes xenology as the pairs of genes separated by at least one horizontal transfer event. As a natural generalization, we consider symmetrized Fitch maps, that is, symmetric maps $\varepsilon$ that assign a subset of colors to each pair of vertices in $X$ and that can be explained by a tree $T$ with edges that are labeled with subsets of colors in the sense that the color $m$ appears in $\varepsilon(x,y)$ if and only if $m$ appears in a label along the unique path between $x$ and $y$ in $T$. We first give an alternative characterization of the monochromatic case and then give a characterization of symmetrized Fitch maps in terms of compatibility of a certain set of quartets. We show that recognition of symmetrized Fitch maps is NP-complete. In the restricted case where $|\varepsilon(x,y)|\leq 1$ the problem becomes polynomial, since such maps coincide with class of monochromatic Fitch maps whose graph-representations form precisely the class of complete multi-partite graphs.

A New Intuition into Tourism-Inclusive Growth Nexus in Turkey and Nigeria (1995 – 2018)

Abstract This paper examines the symmetric and asymmetric causal relationships between tourism and inclusive growth in Turkey and Nigeria over the period 1995Q1-2018Q4. The study employs a bootstrap simulation method with leverage adjustments to achieve the objective of the study. The method is used to see whether positive or negative tourism shocks cause inclusive growth and whether positive or negative inclusive growth shocks cause tourism activity. The results show no evidence of asymmetric causality between tourism and inclusive growth, while there is evidence of symmetric causality running from tourism to inclusive growth in Turkey. On the other hand, there is neither symmetric nor asymmetric causal relationship between tourism and inclusive growth in Nigeria. In sum, both neutrality and tourism-led growth hypothesis hold in Turkey, while Nigeria gives credence to neutrality hypothesis. The recommendations coming from the findings are that the tourism sector in both countries, Nigeria in particular, should be repositioned for better performance and effectiveness in stimulating inclusive growth. Rather than focusing on pro-poor and micro-based tourism policies that favour selected communities and localities, tourism should be included in development plans nationally, in order to ensure wider participation and more encompassing trickle-down effects on the citizenry. Furthermore, both countries should implement policies that will stimulate their tourism sectors for a larger and more significant contribution to real GDP.

LAPREL: A Label-Aware Parallel Network for Relation Extraction

Relation extraction is a crucial task in natural language processing (NLP) that aims to extract all relational triples from a given sentence. Extracting overlapping relational triples from complex texts is challenging and has received extensive research attention. Most existing methods are based on cascade models and employ language models to transform the given sentence into vectorized representations. The cascaded structure can cause exposure bias issue; however, the vectorized representation of each sentence needs to be closely related to the relation extraction with pre-defined relation types. In this paper, we propose a label-aware parallel network (LAPREL) for relation extraction. To solve the exposure bias issue, we apply a parallel network, instead of the cascade framework, based on the table-filling method with a symmetric relation pair tagger. To obtain task-related sentence embedding, we embed the prior label information into the token embedding and adjust the sentence embedding for each relation type. The proposed method can also effectively deal with overlapping relational triples. Compared with 10 baselines, extensive experiments are conducted on two public datasets to verify the performance of our proposed network. The experimental results show that LAPREL outperforms the 10 baselines in extracting relational triples from complex text.