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This article aims at analyzing and designing the multivalued high-capacity-associative memories based on recurrent neural networks with both asynchronous and distributed delays. In order to increase storage capacities, multivalued activation functions are introduced into associative memories. The stored patterns are retrieved by external input vectors instead of initial conditions, which can guarantee accurate associative memories by avoiding spurious equilibrium points. Some sufficient conditions are proposed to ensure the existence, uniqueness, and global exponential stability of the equilibrium point of neural networks with mixed delays. For neural networks with n neurons, m-dimensional input vectors, and 2k-valued activation functions, the autoassociative memories have (2k)n storage capacities and heteroassociative memories have min storage capacities. That is, the storage capacities of designed associative memories in this article are obviously higher than the 2n and min storage capacities of the conventional ones. Three examples are given to support the theoretical results.

Rule-based classification is one of the important tasks in data mining due to its wide applications, particularly in the domains that need to interpret the classification decision such as medical diagnosis. The rule-based classification is a combination of the classification and association rule mining fields which aims at building interpretable classifiers by means of classification rules. This paper presents a novel and efficient sequential covering strategy for Classification Rule Mining to improve the interpretability of classifiers using a Discrete Equilibrium Optimization Algorithm called DEOA-CRM. Our approach benefits from the advantages of associative classification and population-based intelligence. It is inspired by the recent meta-heuristic equilibrium optimization algorithm. New discrete operators defined enable our approach to avoid local solutions and find global ones, improving the exploration and exploitation power in the search space. The proposed DEOA-CRM is tested on a total of 12 test data sets of various sizes and benchmarked with four recent and well-known rule-based classification mining algorithms. The obtained results confirm the efficiency of our algorithm in three chosen measures. Our approach fully deserves its use for classification rules generation to help decision-makers generate accurate and interpretable models.

We present a complete representation theorem for nullnorms on bounded lattices. Explicitly, any nullnorm on a bounded lattice can be represented in terms of two order-preserving maps, a triangular conorm, a triangular norm and a conditionally associative function. As a particular case, we retrieve the known representation of nullnorms only taking values that are comparable with the annihilator (in terms of two order-preserving maps, a triangular conorm and a triangular norm). As an illustration of the representation theorem, we generate construction methods for nullnorms, especially those taking at least one value that is incomparable with the annihilator.

Age-related declines in associative memory are ubiquitous, having been observed across a wide array of stimuli and experimental paradigms. Research further shows that such decreases in behavioral discriminability arise from increases in false memories for recombined lures. The current study examined the underlying neural basis of associative false memories by using representational similarity analyses to examine both age differences in the reactivation of encoded representations during retrieval and the neural overlap in the similarity of neural patterns underlying targets and related lures during retrieval. Behaviorally, we observed an age-related reduction in d’, which was shown to be driven by increased false alarms in the older adults. While we found no age difference in the relationship between patterns of neural activity underlying hits across memory phases (as measured by ERS), the similarity of neural patterns underlying targets and lures was affected by age. Specifically, while younger and older adults exhibited overall higher pattern similarity between hits and CRs compared to hits and FAs (as measured by RSA), this difference was reduced in older adults within occipital cortices. Additionally, greater Hit-FA representational similarity correlated with increases in associative FAs across occipital, frontal, and parietal cortices. Results suggest that while neural representations underlying targets may not differ across age, greater pattern similarity between the neural representation of targets and lures may reflect reduced distinctiveness of the information encoded in memory, such that old and new items are more difficult to discriminate, leading to more false alarms.

[This article has been accepted for publication as a brief report for Psychonomic Bulletin & Review (https://www.springer.com/journal/13423) ]There is growing appreciation for the role of long-term memory in guiding temporalpreparation in speeded reaction time tasks. In experiments with variable foreperiodsbetween a warning stimulus (S1) and a target stimulus (S2), preparation is affected byforeperiod distributions experienced in the past, long after the distribution has changed.These effects from memory can shape preparation largely implicitly, outside of participants’awareness. Recent studies have demonstrated the associative nature of memory-guidedpreparation. When distinct S1s predict different foreperiods, they can trigger differentialpreparation accordingly. Here, we propose that memory-guided preparation allows foranother key feature of learning: the ability to generalize across acquired associations andapply them to novel situations. Participants completed a variable foreperiod task where S1was a unique image of either a face or a scene on each trial. Images of either category werepaired with different distributions with predominantly shorter versus predominantly longerforeperiods. Participants displayed differential preparation to never-before seen images ofeither category, without being aware of the predictive nature of these categories. Theycontinued doing so in a subsequent Transfer phase, after they had been informed that thesecontingencies no longer held. A novel rolling regression analysis revealed at a fine timescalehow category-guided preparation gradually developed throughout the task, and thatexplicit information about these contingencies only briefly disrupted memory-guidedpreparation. These results offer new insights into temporal preparation as the product of alargely implicit process governed by associative learning from past experiences.

We propose that the specificity with which associations in episodic memory can be remembered varies on a continuum. Older adults have been shown to forget highly specific information (Greene & Naveh-Benjamin, 2020b), and in Experiment 1, we provide further evidence that older adults' deficits in associative memory scale with the amount of specificity that needs to be retrieved. In Experiment 2, we address whether depleted attentional resources, simulated in young adults under divided attention at encoding, could account for older adults' associative memory specificity deficits. Participants studied face-scene pairs and later completed an associative recognition test, with test pairs that were old, highly similar or less similar to old pairs, or completely dissimilar. Participants rated their confidence in their decisions. False positive recognition responses increased with the amount of specificity needed to be retrieved. Whereas older adults' associative memory deficits scaled with how much specific information needed to be remembered, younger adults under divided attention had a more general deficit in associative memory. Confidence-accuracy analysis showed that participants were best able to calibrate their confidence when less specific information was needed to perform well. While divided attention young adults were generally prone to high-confidence errors, older adults' high-confidence errors were most apparent when highly specific information needed to be remembered. These results provide further evidence for levels of specificity in episodic memory. Access to the most specific levels is most vulnerable to forgetting, in line with a specificity principle of memory (Surprenant & Neath, 2009). Further, depleted attentional resources at encoding cannot entirely explain older adults' associative memory specificity deficits. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

We consider a three-dimensional associative noncommutative algebra Ã2 over the field C, which contains the algebra of bicomplex numbers B(C) as a subalgebra. In this paper we consider functions of the form Φ(ζ)=f1(ξ1, ξ2,ξ3)I1+ f2(ξ1, ξ2,ξ3)I2+ f3(ξ1, ξ2,ξ3)ρ of the variable ζ= ξ1I1+ ξ2I2+ ξ3ρ, where ξ1, ξ2, ξ3 are independent complex variables and f1, f2, f3 are holomorphic functions of three complex variables. We construct in an explicit form all functions defined by equalities dΦ =dζ·Φ´(ζ) or dΦ = Φ´(ζ) ·dζ. The obtained descriptions we apply to representation of the mentioned class of functions by series. Also we established integral representations of these functions.

Objective: This study aims to classify COVID-19 by applying the associative classification method on the gene data set consisting of open access COVID-19 negative and positive patients and revealing the disease relationship with these genes by identifying the genes that cause COVID-19. Method: In the study, an associative classification model was applied to the gene data set of patients with and without open access COVID-19. In this open-access data set used, 15979 genes are belonging to 234 individuals. Out of 234 people, 141 (60.3%) were COVID-19 negative and 93 (39.7%) were COVID-19 positives. In this study, LASSO, one of the feature selection methods, was performed to choose the relevant predictors. The models' performance was evaluated with accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score. Results: According to the study findings, the performance metrics from the associative classification model were accuracy of 92.70%, balanced accuracy of 91.80%, the sensitivity of 87.10%, the specificity of 96.50%, the positive predictive value of 94.20%, the negative predictive value of 91.90%, and F1-score of 90.50%. Conclusion: The proposed associative classification model achieved very high performances in classifying COVID-19. The extracted association rules related to the genes can help diagnose and treat the disease.

Text classification is imperative in order to search for more accessible and appropriate information. It utilized in various fields, including marketing, security, biomedical, etc. Apart from its usefulness, the available classifiers are vulnerable to two major problems, namely long processing time and low accuracy. They can result from a large amount of data presented in the text classification problem. In this paper, we propose a model called Class-Based Fuzzy Soft Associative (CBFSA). This model is a combination of the association rules method and fuzzy soft set model. We used Fuzzy Soft Set Association Rules Mining for generating classifiers and Fuzzy Decision Set of an FP-Soft Set for building classifiers. Our experiment for the 20 Newsgroups dataset on 20 class documents has shown that CBFSA is more accurate than the other soft set classifiers: Soft Set Classifier (SCC), Fuzzy Soft Set Classifier (FSSC) and Hybrid Fuzzy Classifier (HFC). Besides that, it has also shown that CBFSA is more accurate and efficient compared to other associative classifiers such as the classification Based on Association (CBA) method.

Evaluating faculty members' performance is a very complex area to study. In addition, predicting the performance of these faculty members is a very difficult and challenging task. However, the core of education is teaching and learning, and teaching-learning works to its fullest when there are effective teachers. Measuring the effectiveness of faculty members is done based on the student evaluation of faculty. This research aims to develop a model to predict the performance of the faculty members using associative rule based on the existing evaluation form used by PSU to evaluate faculty members. The model is designed to utilize the knowledge of text analytics rule capabilities that will provide great support for the decision-making of Pangasinan State University in the Philippines. The result reveals that the term good is still the top one terms occurred for all campuses followed by teaching. The results indicated that teacher/faculty members on all campuses are good teachers. Associating words reveal that "teaching good subject/topic," "explains simply" and other meaningful associated words can be utilized to evaluate the performance of the teacher. The results exposed not only the quantitative values of faculty evaluation it also exposed the qualitative opinion of the students in the performance of their faculty members. This study reveals important aspects of the faculty member's teaching performance in terms of words/association of words that will describe their teaching performance. The results can be utilized in coaching and mentoring faculty members to cope with their weaknesses. The proposed model can be utilized by Pangasinan State University to evaluate the faculty members in terms of their teaching performance by utilizing the comments/opinions of the students.

The issue of distributivity of aggregation operations is crucial for many different areas such as utility theory and integration theory. Of special interest are aggregation operations with annihilator. This paper is focused on the problem of distributivity for some so called associative, commutative aggregation operations with annihilator a, known as associative a-CAOA, and uninorms. The full characterization of distributive pairs for T-uninorms, S-uninorms and bi-uninorms is given.

We introduce three broad classes of nullnorms on a bounded lattice and lay bare the structure of their members. For that purpose, we introduce particular subsets of a bounded lattice, called upper (resp. lower) beams, and appropriate associative operations on them, called beam (resp. dual beam) operations, which conveniently generalize triangular norms (resp. triangular conorms). It is shown that nullnorms in the first (resp. second) class are characterized by a triangular conorm (resp. triangular norm) and a beam operation (resp. dual beam operation), while nullnorms in the third class are characterized by a triangular conorm and a triangular norm. We also discuss the relationships among these three classes.

Some aspects of our memory are enhanced by emotion, whereas other can be unaffected or even hinder. In particular, previous studies report impaired associative memory of emotional content, an effect termed associative 'emotional interference'. The current study utilized EEG and an associative recognition paradigm to investigate the cognitive and neural mechanisms associated with this effect. In two experiments, participants studied negative and neutral stimulus-pairs that were either semantically related or unrelated. In Experiment 1 emotions were relevant to the encoding task (valence judgment) whereas in Experiment 2 emotions were irrelevant (familiarity judgment). In a subsequent associative recognition test, EEG was recorded while participants discriminated between intact, rearranged, and new pairs. An associative emotional interference effect was observed in both experiments, but was attenuated for semantically related pairs when emotions were relevant to the study task. Moreover, a modulation of an early associative memory ERP component depended on task relevancy of emotions, and occurred for negative pairs when emotions were relevant, but for semantically related pairs when emotions were irrelevant. A later ERP component depicted a more general pattern, and was observed in all experimental conditions. These results suggest that both emotions and semantic relations can act as organizing principles that promote associative binding. Their ability to contribute to successful retrieval depends on specific task demands.

Expert systems and neural networks are new tools for the control of fermentation processes. With expert systems the fermentation plant and the process itself is modelled via a generalized, qualitative system description based on the experience of human experts. On the other hand neural networks and interpolating associative memories can learn the process behaviour directly by process observation. The paper at hand reports, how both control techniques can be combined for purposes like process supervision, modelling and optimization of biological plants.

The article presents the results of the study dedicated to native speakers sites of memory associated with key images of the Russian national culture. The investigation was inspired by the work of French historians Les lieus de mmoire (1984), whose ideas Yuri Nikolayevich Karaulov applied to the Russian Associative Dictionary (RAD). The study was initiated with the hypothesis elaborated by Yu. N. Karaulov that the Russian national memory could be studied through associative dictionaries. This provision is based on the linguistic personality concept formulated by Yu. N. Karaulov that is regarded as a personality expressed in a language / text and can be reconstructed on the basis of linguistic means. The texts that a language personality produces reflect the peculiarities of a persons vision of the environment (worldview). The hypothesis is tested on associative fields of the toponym Moscow and the lexemes war and Sunday using the data of several associative dictionaries compiled from 1988 to the current moment, i.e., the Russian Associative Dictionary, and Yu. N. Karaulov among the authors, as well as a number of later dictionaries developed on the basis of massive associative experiments carried out in the regions of Russia. The content and structural analyses of the associative fields of stimuli Moscow , war , and Sunday show that the associative material largely reflects the discursive space of the language personality and its functioning in texts that reproduce these sites of memory in a precedent form. The latter, however, can be found as various types of reactions (predications) of a non-stereotyped nature. Therefore, the sought-for data exist in different guises, obviously depending on the historical time and the discursive experience of native speakers of a language/culture, as well as on the region of their residence. This study confirms the psycholinguistic concept of meaning (including the associative one) as a sociocultural phenomenon.

Children's learning capabilities change while growing up. One framework that describes the cognitive and neural development of children's growing learning abilities is the two‐component model. It distinguishes processes that integrate separate features into a coherent memory representation (associative component) and executive abilities, such as elaboration, evaluation, and monitoring, that support memory processing (strategic component). In an fMRI study using an object‐location association paradigm, we investigated how the two components influence memory performance across development. We tested children (10–12 years, n = 31), late adolescents (18 years, n = 29), and adults (25+ years, n = 30). For studying the associative component, we also probed how the utilisation of prior knowledge (schemas) facilitates memory across age groups. Children had overall lower retrieval performance, while adolescents and adults did not differ from each other. All groups benefitted from schemas, but this effect did not differ between groups. Performance differences between groups were associated with deactivation of the dorsal medial prefrontal cortex (dmPFC), which in turn was linked to executive functioning. These patterns were stronger in adolescents and adults and seemed absent in children. Thus, the children's executive system, the strategic component, is not as mature and thus cannot facilitate memory performance in the same way as in adolescents/adults. In contrast, we did not find age‐related differences in the associative component; with activity in the angular gyrus predicting memory performance systematically across groups. Overall, our results suggest that differences of executive rather than associative abilities explain memory differences between children, adolescents, and adults., In an fMRI study, we investigated whether memory differences between children, adolescents, and adults stem from developmental changes in executive abilities, the strategic component, or rather from differences in mechanisms related to binding different features together into a memory representation, the associative component. Overall, our results suggest that differences of executive rather than associative abilities explain memory differences between children, adolescents and adults.

Much research has been executed to investigate how altering focus of attention impacts performance and feelings of fatigue. Using a within-participant design, the present study examined how an associative and dissociative attentional in addition to an internal and external attentional dimension influenced the running economy of nonprofessional runners. Twelve women (aged 18–30 years old) ran on a treadmill at 70% of their predetermined maximum velocity. Participants ran in four counterbalanced conditions (dissociative-external, dissociative-internal, associative-external, and associative-internal). Average oxygen volume, respiration volume and breathing frequency, heart rate, blood lactate level, and Borg rating of perceived exertion were measured. Our findings revealed when participants adopted a dissociative-external focus of attention, they consumed less oxygen, had lower blood lactate, and a lower rating of perceived exertion compared with trials completed using an associative attention strategy. The findings of this study demonstrate that running economy is improved and feelings of fatigue are lowest when using a combination of a dissociative-external focus of attention.

The specific national characteristics of stimulus Homeland in Russian and Spanish verbal associative network are described in this article. The contrastive analysis of one of the basic word-model-points, inherent to the Russian and Spanish native speakers, is being investigated for the first time. The qualitative indicators of the performed analysis constitute a kind of thesaurus of the associative norms of the Russian and Spanish languages and, together with the quantitative ones, can be the subject of linguo-psychological comparative analysis and provide additional information about the associative norms, structure, linguistic ability and national character of the speakers of the given language and culture.The theme may be interesting for specialists not only in philology, but also in psychology, sociology, culturology, mass media, commercial advertizing and other spheres connected with human activity.

Our brain can be recognized as a network of largely hierarchically organized neural circuits that operate to control specific functions, but when acting in parallel, enable the performance of complex and simultaneous behaviors. Indeed, many of our daily actions require concurrent information processing in sensorimotor, associative, and limbic circuits that are dynamically and hierarchically modulated by sensory information and previous learning. This organization of information processing in biological organisms has served as a major inspiration for artificial intelligence and has helped to create in silico systems capable of matching or even outperforming humans in several specific tasks, including visual recognition and strategy-based games. However, the development of human-like robots that are able to move as quickly as humans and respond flexibly in various situations remains a major challenge and indicates an area where further use of parallel and hierarchical architectures may hold promise. In this article we review several important neural and behavioral mechanisms organizing hierarchical and predictive processing for the acquisition and realization of flexible behavioral control. Then, inspired by the organizational features of brain circuits, we introduce a multi-timescale parallel and hierarchical learning framework for the realization of versatile and agile movement in humanoid robots.

The research is motivated by a construction of groups of oscillating growth by Kassabov and Pak [25] and a description of possible growth functions of finitely generated associative algebras by Bell and Zelmanov [9] . In this paper we address both, the question of possible growth functions in case of Lie algebras, and the Kurosh problem, because our examples of restricted Lie algebras have a nil p-mapping, which is an analogue of nillity for associative algebras or periodicity for groups. Namely, for any field of positive characteristic, we construct a family of 3-generated restricted Lie algebras of intermediate oscillating growth. We call them Phoenix algebras because, for infinitely many periods of time, the algebra is “almost dying” by having a quasi-linear growth, namely the lower Gelfand-Kirillov dimension is one, more precisely, the growth is of type n ( ln ⁡ ⋯ ln ︸ q times n ) κ , where q ∈ N , κ > 0 are constants. On the other hand, for infinitely many n the growth function has a rather fast intermediate behavior of type exp ⁡ ( n / ( ln ⁡ n ) λ ) , λ being a constant determined by characteristic, for such periods the algebra is “resuscitating”. Moreover, the growth function is bounded and oscillating between these two types of behavior. These restricted Lie algebras have a nil p-mapping, thus addressing the Kurosh problem as well.

In several examples it has been observed that a module category of a vertex operator algebra (VOA) is equivalent to a category of representations of some quantum group. The present article is concerned with developing such a duality in the case of the Virasoro VOA at generic central charge; arguably the most rudimentary of all VOAs, yet structurally complicated. We do not address the category of all modules of the generic Virasoro VOA, but we consider the infinitely many modules from the first row of the Kac table. Building on an explicit quantum group method of Coulomb gas integrals, we give a new proof of the fusion rules, we prove the analyticity of compositions of intertwining operators, and we show that the conformal blocks are fully determined by the quantum group method. Crucially, we prove the associativity of the intertwining operators among the first-row modules, and find that the associativity is governed by the $6j$-symbols of the quantum group. Our results constitute a concrete duality between a VOA and a quantum group, and they will serve as the key tools to establish the equivalence of the first-row subcategory of modules of the generic Virasoro VOA and the category of (type-1) finite-dimensional representations of $\mathcal{U}_{q}(\mathfrak{sl}_{2})$., Comment: 79 pages. Accepted for publication in Communications in Mathematical Physics

The article states that the mode of intentionality, being a socio-cultural phenomenon, manifests itself in the language personality in the form of its socio-communicative attitudes. In comparison with subconscious sets of the “general cultural script” which motivate and support the functioning of a socio-cultural system as a whole, the sociocommunicative attitudes of the language personality are much more flexible, susceptible to multiple changes in the social network of communication. The socio-communicative attitudes of the language personality are studied with the units of analysis that can be called semantic accentuations embodied in the multiplicity and multidimensionality of links in the human associative-verbal network (AVN). Yu. N. Karaulov’s ideas about the complementarity of word-changing, word-forming and semantic variability in the AVN of the Russian language personality (RLP) are developed and tested in the article on new materials in connection with the multiplicity of ways of concentrating meaning. Using the latest experimental materials of the associative-verbal database SIBAS 1 (2007–2013) and SIBAS 2 (2014– 2021), the author puts to the test different techniques of vector analysis, both on the entire array of associates and within individual associative fields (AFs). These techniques include: an automatic generation (extraction from the entire array of associates) of the AFs of the studied word-forming units; a comparative psychoglossic analysis of the current diachronic dynamics of the AFs of the selected stimuli; constructing vectors of lexico-grammatical variation of the reactions in these AFs against the background of their semantic vectors; extracting particular word-changing and word-forming paradigms from the entire array of associates with a subsequent analysis of their contribution to the concentration of meanings, etc. Such methods show different entrances to the AVN for access to the same points of concentration of meaning and help to assess the contribution of the dissipated throughout the network associative grammar to the formation of semantic accentuations of the RLP. Hypothetically, it seems possible to imagine the construction of the fluctuation dynamics of an associative-verbal hypernetwork (AVHN) of the RLP on the combination of accentuation vectors of its subsystems (networks of word-changing, word-forming or semantic variability) in the current diachrony and historical retrospective.

We construct a generalization of the Day convolution tensor product of presheaves that works for certain double $$\infty $$ ∞ -categories. Using this construction, we obtain an $$\infty $$ ∞ -categorical version of the well-known description of (one-object) operads as associative algebras in symmetric sequences; more generally, we show that (enriched) $$\infty $$ ∞ -operads with varying spaces of objects can be described as associative algebras in a double $$\infty $$ ∞ -category of symmetric collections.

Goldberg and Stein (2018) present an innovative agent-based computational model that shows how cultural associations can diffuse through superficial interpersonal interactions. They counterintuitively argue that segmented networks—for example, those resembling “small worlds” with dense local clustering—inhibit rather than promote cultural diffusion. This finding is notable because it breaks with a long line of influential research showing that local clustering is crucial to diffusion in cases where behaviors and practices—including cultural beliefs—require multiple reinforcements in order to spread. Replicating Goldberg and Stein’s model, we find this result only holds consistently in settings approximating small-group interactions. In models with larger populations, and where cultural associations require repeated reinforcement through social observation, locally clustered small-world networks can promote global cultural variation as well as globally-connected networks, and sometimes do so better. The complex interactions among parameters that lead to this reversal in Goldberg and Stein’s model are instructive for theoretical models of interpersonal influence.

In their insightful comment, DellaPosta and Davoodi argue that our finding (Goldberg and Stein 2018) that segmented networks inhibit cultural differentiation does not generalize to large networks. However, their demonstration rests on an incorrect implementation of the preference updating process in the associative diffusion model. We show that once this discrepancy is corrected, cultural differentiation is more pronounced in fully connected networks, irrespective of network size and even under extreme assumptions about cognitive decay. We use this as an opportunity to discuss the associative diffusion model’s assumptions and scope conditions, as well as to critically reassess prevailing contagion-based diffusion models.

На первом этапе исследования был проведен компонентный анализ лексемы «вежливость» в китайском языке для выявления инвариантного содержания речевого действия; на втором – анализ данных свободного ассоциативного эксперимента для экстрактирования личностных смыслов и расширения списка слов-стимулов, составляющих основу словарной статьи тезауруса. На третьем этапе был проведён свободный ассоциативный эксперимент, сформированы ассоциативные поля, включающие реакции носителей китайского языка. Ассоциативные данные в словаре представлены с учётом частотного и гендерного параметров. Разработка проекта мультилингвального ассоциативного словаря на основе систематизации лингвистических и ассоциативных данных позволяет выявить универсальные и этноспецифичные параметры речевого действия, а также проследить динамику образа мира индивида, принадлежащего определённой лингвокультуре.

У статті розглядаються розширені і стандартні описи гомоморфізмів груп E (n,R) ⊆G ⊆GL(n,R), n≥2 над асоціативними кільцями R з 1. Показано, що гомоморфізми з умовою (*) групи E (n,R) < G ⊆ GL(n,R), n≥4 над асоціативними кільцями R з 1 мають розширено стандартний опис, а при деяких обмеженнях стандартний опис на групах G і E(n,R). В роботі також описуються гомоморфізми з умовою (*) групи (n,R) ⊆ G ⊆ GL(n,R), n≥4, що відображають її у групу GL(m,K), m≥2, які є мономорфізмами (зокрема такими є ізоморфізми) або E (n,K) ⊆ΛE (n,R) над асоціативними кільцями R і K з 1. Показано, що такі гомоморфізми допускають стандартний опис на групі E (n,R).

We give a simple approach to determine when multiplication is associative for matrices of infinite size, extending recent results of Bossaller and Lopez-Permouth.

People tend to better remember same-race faces relative to other-race faces (an "own-race" bias). We examined whether the own-race bias extends to associative memory, particularly in the identification and recall of information paired with faces. In Experiment 1, we presented white participants with own- and other-race faces which either appeared alone or accompanied by a label indicating whether the face was a "criminal" or a "victim". Results revealed an own-race facial recognition advantage regardless of the presence of associative information. In Experiment 2, we again paired same- and other-race faces with either "criminal" or "victim" labels, but rather than a recognition test, participants were asked to identify whether each face had been presented as a criminal or a victim. White criminals were better categorised than Black criminals, but race did not influence the categorisation of victims. In Experiment 3, white participants were presented with same- and other-race faces and asked to remember where the person was from, their occupation, and a crime they committed. Results revealed a recall advantage for the associative information paired with same-race faces. Collectively, these findings suggest that the own-race bias extends to the categorisation and recall of information in associative memory.

We describe a geometric construction of all nondegenerate trigonometric solutions of the associative and classical Yang–Baxter equations. In the associative case, the solutions come from symmetric spherical orders over the irreducible nodal curve of arithmetic genus $1$, while in the Lie case they come from spherical sheaves of Lie algebras over the same curve.

Association rule mining is a technique that is widely used in data mining. This technique is used to identify interesting relationships between sets of items in a dataset and predict associative behavior for new data. Before the rule is formed, it must be determined in advance which items will be involved or called the frequent itemset. In this step, a threshold is used to eliminate items excluded in the frequent itemset which is also known as the minimum support. Furthermore, the threshold provides an important role in determining the number of rules generated. However, setting the wrong threshold leads to the failure of the association rule mining to obtain rules. Currently, user determines the minimum support value randomly. This leads to a challenge that becomes worse for a user that is ignorant of the dataset characteristics. It causes a lot of memory and time consumption. This is because the rule formation process is repeated until it finds the desired number of rules. The value of minimum support in the adaptive support model is determined based on the average and total number of items in each transaction, as well as their support values. Furthermore, the proposed method also uses certain criteria as thresholds, therefore, the resulting rules are in accordance with user needs. The minimum support value in the proposed method is obtained from the average utility value divided by the total existing transactions. Experiments were carried out on 8 specific datasets to determine the association rules using different dataset characteristics. The trial of the proposed adaptive support method uses 2 basic algorithms in the association rule, namely Apriori and Fpgrowth. The test is carried out repeatedly to determine the highest and lowest minimum support values. The result showed that 6 out of 8 datasets produced minimum and maximum support values for the apriori and fpgrowth algorithms. This means that the value of the proposed adaptive support has the ability to generate a rule when viewed from the quality as adaptive support produces at a lift ratio value of > 1. The dataset characteristics obtained from the experimental results can be used as a factor to determine the minimum threshold value.

Th e paper analyzes the state and management of country’s economics. A tuple of event-driven optimal management as a method of artifi cial intelligence has been developed. Th e characteristics of event-driven quality management of associative and structurally complex systems and processes are given. Th e events and probabilities in the management of economics and the state are considered. A measure of invalidation has been introduced for parameters. Th e method of synthesis of the probability of an event based on expert information is presented. Th e necessity of orthogonalization of the logical function and the transition to the probabilistic function have been substantiated. Th e eff ect of repeated initiating events is considered. One-dimensional optimization of the system on a logical model instead of arithmetic multiparameter optimization is presented. Schemes for managing of development and exit of economics from stagnation are given. Th e tools for event-driven quality management of systems and processes are described. Th e analysis of the shortcomings of the existing economic theory and the possibility of their elimination is carried out.

As a result of contact between mutually unintelligible Southern Chinese varieties like Hokkien and Cantonese, Colloquial Singapore Mandarin (csm) 有 yǒu ‘have’ has extended its semantic functions to include that of realis modality marker. This paper will demonstrate how a framework of ambiguity and semantic continuity can allow us to determine the associative links between different synchronous functions of the 有 yǒu ‘have’ construction. The ambiguous context that links the existential and realis modality functions of 有 yǒu ‘have’ is [没有 méi yǒu ‘not have’ + vp]. This ambiguous context allows 有 yǒu ‘have’ to be reanalyzed as a realis modality marker with méi ‘not’ as the negator. Additionally, the semantic continuity between the existential and realis modality marker functions further confirms such an association. While [yǒu + np] affirms the existence of someone or something, [yǒu + vp] affirms the existence of an event.

The current study leveraged experimental and individual differences methodology to examine whether false memories across different list-learning tasks arise from a common cause. Participants completed multiple false memory (associative and conjunction lure), working memory (operation and reading span), and source monitoring (verbal and picture) tasks. Memory discriminability in the associative and conjunction tasks loaded onto a single (general) factor and were unaffected by warnings provided at encoding. Consistent with previous research, source-monitoring ability fully mediated the relation between working memory and false memories. Moreover, individuals with higher source monitoring-ability were better able to recall contextual information from encoding to correctly reject lures. These results suggest that there are stable individual differences in false remembering across tasks. The commonality across tasks may be due, at least in part, to the ability to effectively use disqualifying monitoring processes.

We give a geometric classification of complex $n$-dimensional $2$-step nilpotent (all, commutative and anticommutative) algebras. Namely, has been found the number of irreducible components and their dimensions. As a corollary, we have a geometric classification of complex $5$-dimensional nilpotent associative algebras. In particular, it has been proven that this variety has $14$ irreducible components and $9$ rigid algebras., Comment: Theorem C is corrected. arXiv admin note: text overlap with arXiv:2007.01829, arXiv:2001.00253

Постановка задачи. Основной задачей исследования является установление динамики содержания базисного концепта Sicherheit (безопасность) в немецкой лингвокультуре. В качестве методов исследования авторы обращаются к анализу дефиниций толковых словарей, анализу сочетаемости исследуемого слова, контекстному анализу, свободному ассоциативному эксперименту. На основе разработанной модели значения авторы сопоставляют лексикографические данные и ассоциативное поле слова-стимула Sicherheit (безопасность) . Результаты. На основе сопоставления полученных данных авторы отмечают, что интегративные признаки, выделенные в сочетаемости лексем и признаки, выделенные в ассоциативном эксперименте, в значительной мере совпадают (‘источники безопасности’, ‘безопасная ситуация в мире / национальная безопасность’, ‘комфорт, стабильность’, ‘личные эмоциональные концепты’, ‘объект / предмет защиты’), хотя и различны в количественном значении. При этом сочетаемость лексемы позволяет говорить о недоверии к возможности стабильной и безопасной ситуации в целом. Однако данные свободного ассоциативного эксперимента, напротив, свидетельствуют об исключительно положительном отношении к исследуемому концепту. Согласно данным корпуса наиболее распространенной категорией является категория уверенность , которая представлена в ассоциативном эксперименте единичной реакцией. Наибольшее количество реакций ассоциативного эксперимента представляют Sicherheit как чувство защищенности от разного вида опасности. Выводы. Для носителей немецкой лингвокультуры концепт Sicherheit (безопасность) понимается как чувство защищенности от опасности, которое могут гарантировать индивиду семья или государственные органы. Гарантом безопасности выступают деньги. Для достижения безопасности необходимо соблюдение различных правил и мер безопасности. Statement of the problem. The aim of the article is to establish the dynamics of the content of the basic concept Sicherheit ( safety ) in German linguistic culture. As the main research methods, the authors turn to the analysis of definitions of explanatory dictionaries, the analysis of the compatibility of the studied word, context analysis, free associative experiment. On the basis of the developed model of meaning, the authors compare the lexicographic data and the associative field of the stimulus word Sicherheit ( safety ). Results. Based on the comparison of the obtained data, the authors note that the integrative features identified in the compatibility of lexemes and the features identified in the associative experiment largely coincide (‘sources of security’, ‘safe situation in the world / national security’, ‘comfort, stability’, ‘personal emotional concepts’, ‘object of protection’, although they are different in quantitative meaning. At the same time, we note that the compatibility of the lexeme allows us to speak of mistrust of the possibility of a stable and safe situation as a whole. However, the data of the free associative experiment, on the contrary, allow us to speak about an extremely positive attitude to the concept under study. According to the corpus, the most common category is the category of confidence, which is represented in the associative experiment by a single reaction. The largest number of reactions in the associative experiment represent Sicherheit as a feeling of protection from various types of danger. Conclusion. For representatives of the German linguistic culture, the concept of Sicherheit ( safety ) is understood as a sense of security from danger, which can be guaranteed to an individual by the family or government authorities. Money is the guarantor of security. To achieve safety, it is necessary to comply with various safety rules and measures.

Three major pillars of hippocampal function are spatial navigation1, Hebbian synaptic plasticity2 and spatial selectivity3. The hippocampus is also implicated in episodic memory4, but the precise link between these four functions is missing. Here we report the multiplexed selectivity of dorsal CA1 neurons while rats performed a virtual navigation task using only distal visual cues5, similar to the standard water maze test of spatial memory1. Neural responses primarily encoded path distance from the start point and the head angle of rats, with a weak allocentric spatial component similar to that in primates but substantially weaker than in rodents in the real world. Often, the same cells multiplexed and encoded path distance, angle and allocentric position in a sequence, thus encoding a journey-specific episode. The strength of neural activity and tuning strongly correlated with performance, with a temporal relationship indicating neural responses influencing behaviour and vice versa. Consistent with computational models of associative and causal Hebbian learning6,7, neural responses showed increasing clustering8 and became better predictors of behaviourally relevant variables, with the average neurometric curves exceeding and converging to psychometric curves. Thus, hippocampal neurons multiplex and exhibit highly plastic, task- and experience-dependent tuning to path-centric and allocentric variables to form episodic sequences supporting navigation.

Data Mining is an essential task because the digital world creates huge data daily. Associative classification is one of the data mining task which is used to carry out classification of data, based on the demand of knowledge users. Most of the associative classification algorithms are not able to analyze the big data which are mostly continuous in nature. This leads to the interest of analyzing the existing discretization algorithms which converts continuous data into discrete values and the development of novel discretizer Reliable Distributed Fuzzy Discretizer for big data set. Many discretizers suffer the problem of over splitting the partitions. Our proposed method is implemented in distributed fuzzy environment and aims to avoid over splitting of partitions by introducing a novel stopping criteria. Proposed discretization method is compared with existing distributed fuzzy partitioning method and achieved good accuracy in the performance of associative classifiers.

Despite its name, associative recognition is a paradigm thought to rely on memory recall. However, it remains unclear how associative information may be represented and retrieved from memory and what its relationship to other information, such as item memory, is. Here, we propose a computational model of associative recognition, where relational information is accessed in a generic, multistage retrieval process. The model explains the relative difficulty of associative recognition compared with item recognition, the difference in experimental outcomes when different types of lures are used, as well as the conditions leading to the emergence of associative ROC curves with different shapes.

A dendriform algebra is an associative algebra whose product splits into two binary operations and the associativity splits into three new identities. These algebras arise naturally from some combi...

The aim of this work is to provide a concrete list of non-isomorphic commutative power-associative superalgebras up to dimension 4 over an algebraically closed field of characteristic prime to 30. As a byproduct, we exhibit an example of a simple non-Jordan power-associative superalgebra whose even part is not semisimple.

Cued recall of word pairs is improved by asking participants to combine items in an interactive image. Meanwhile, interactive images facilitate serial-recall (Link Method), but even better when each item is imagined alongside a previously learned peg-word (Peg List Method). We asked if a peg system could support memory for pairs, hypothesising it would outperform interactive imagery. Tested with cued recall, five study strategies were manipulated between-subjects, across two experiments: (1) Both words linked to one peg; (2) Each word linked to a different peg; (3) Peg list method but studying as a serial list; (4) Interactive imagery (within-pairs); (5) Link Method. Participants were able to apply peg-list strategies to pairs, as anticipated by mathematical modelling. Error-patterns spoke to mathematical models; peg lists exhibited distance-based confusability, characteristic of positional-coding models, and errors tended to preserve within-pair position, even for inter-item associative strategies, suggesting models of association should incorporate position. However, the peg list strategies came with a speed-accuracy tradeoff and did not challenge the superiority of the interactive imagery strategy. Without extensive practice with peg list strategies, interactive imagery remains superior for associations. Peg strategies may excel instead in tasks that primarily test serial order or with extensive training.