Semantic Concepts Research Articles

Hypothesising in Contemporary Organisational Management Research. What Really Matters?

Abstract Management is an economic science and more than ever, temporal, as a direct effect of the level of social development, with many interdependencies with other fields of knowledge. Generically said, studies and research in the field of organisational management involve a high level of difficulty compared to other types of sciences because they primarily investigate aspects related to the soft component of the organisation, the human resource. The results, operationalised through the design and implementation of decisions, are achieved by people, for people, and people are involved in the (micro or macro) organisational universe with different experiences and expertise, different attitudes, different expectations, transforming other types of resources. It is difficult to translate purely qualitative aspects, which can be extracted from an organisational framework often by observation, into quantitative contexts that support the transformation of conclusions into judgements of principle value. In this context, the article examines the role, importance and usability of the hypothesis as a management tool. Starting from the highlighting of topical issues in the field of management science, an attempt is made to answer the following questions: in what situations can hypotheses be used? what are the application peculiarities and, subsequently, the advantages and disadvantages? what established typologies have been highlighted in the investigation of management issues? The theoretical observations are doubled in significance by a case study based on the use of the Competing Hypotheses Model (CHA). To summarize, the quality of the conceptual representations and semantics of the construction of a working hypothesis can bring us closer or further away from the organisational reality of interest, with direct effects on the relevance and effects of the activity undertaken.

Functional and stylistic differentiation of language within integrative paradigm

The relevance of the work is due to the need to study sociolects as socially marked variants of a language that have similarities and differences in the lexico-semantic and word-formation systems. In this regard, its purpose is to analyze and describe similar and contrasting elements in the sociolects of traders and criminals on the material of Russian and English languages. In the course of the study, the method of sociological observation, experiment, questioning, the method of cognitive semantics, the method of cognitive derivation, the method of questioning and associative experiment was used. The results obtained include: similarity (the presence of the same names of thematic series, the use of morphological, lexico-semantic methods of word formation), the presence of contrasts (consisting in the composition of thematic series of vocabulary, the presence of many polysemantic words, homonyms in the sociolect of criminals, phraseological units, ambiguous in origin) and stylistic affiliation, in the difference in the methods of word formation used in the sociolect of traders (abbreviation, acronymization, truncation). An integrative approach has been applied to the study of the sociolects of traders and criminals, based on expansionist, functional and anthropocentric principles. The use of the anthropocentric principle manifested itself in the description of the specifics of the social groups of criminals and traders. Expansionism was expressed in the use of methods of various sciences (cognitive linguistics, sociolinguistics, contrastive linguistics). The use of the principle of functionalism consists in describing the functions of the compared sociolects, in identifying their similar and different functions. It is concluded that the sociolects of traders and criminals are indeed socially marked variants of the language, since the compared subsystems of the language have a specific system of lexical units, that manifest themselves in the ways of word formation, and various functions due to the social characteristics of their speakers. It is noted that the article is notable for its novelty, since the study of the sociolects of traders and comparative aspect is carried out for the first time. The study of compared sociolects within the framework of the integrative methodological paradigm is also new.

The Encyclopaedic Meaning of Erythros in Koine Greek Toponyms. A Cognitive Approach to the Definition of the Ancient Colour Cardinal Points System

Summary The cartographic and historiographic traditions interpreting the Greek toponym Erythra Thalassa indicate this expression could designate several water basins in classical historiography, though it is usually rendered univocally as the Red Sea. This research applies cognitive semantics to the history of geography to retrieve the encyclopaedic meaning of the term erythros in relation to its dictionary meaning “red”. Computationally generated lists of frequency from about 50 ancient Greek and Latin oeuvres denote a predominant toponymic use of the term and a fixed collocation in conjunction with thalassa “sea”. Additional statistical data extrapolated from the Septuagint and the Greek New Testament reveal the tendency in the biblical tradition to use exclusively the inflected form erythra in fully fixed collocations with the term thalassa. The paper finds out that the specific shade of red denoted by erythors has been used since the seventh century BCE in a number of other toponyms and ethnonyms to convey the conceptual meaning of “southern”. To comparatively verify this hypothesis, several Greek toponyms incorporating the term leukos – “white” or “western” – are discussed in relation to their relative position in the oikumene. Based on comparative chronologies and diatopic attestations of the phenomenon, the hypothesis that the Turkic colour cardinal points system and the linguistic means to convey it was introduced to Greece during the period of contact with the Scythe people is proposed.

ДЕГРАДАЦІЙНА СИЛА КАЛЬКИ

The article highlights the structural-semantic and functional-motivational description of the degradation of the calque element widely used in modern mass media – radio, television, press, office work and everyday speech as diverse representatives of Ukrainian society: radio and TV presenters, scientists, people’s deputies, writers, musicians, athletes, which took root as a result of long assimilation processes, when Ukraine was under the rule of Tsarist Russia, and then the USSR. This linguistic acquisition, due to such conditions, was inherited in the broadcasting of residents of sovereign Ukraine and potentially continues to function in the most influential mass media for the formation of speech culture. Such protracted process of assimilation purification and restoration of the historically established Ukrainian language general literary norms of oral and written speech is due to the reorientation of the Russian-speaking population to the state language of independent Ukraine under martial law with the Russian Federation and the lack of highly intelligent employees of radio and TV channels. And although linguists have prepared and published enough educational and reference literature for the educational process of secondary and higher educational institutions, however, insufficient attention was paid to the issue of clearing assimilative calque elements of the Russian language, especially those that in the context could clearly distinguish semantic concepts about quality, since this word is polysemous. Moreover, mastering the native language in the professional direction with the annual reduction in the number of hours can not give the full and harmonious knowledge of the language culture that every member of the modern spiritually renewed society should receive and improve during their life in order to get rid of those Surzhik twists that have become the chronic speech disease of Ukrainianness, which has won independence and defends it by the power of its freedom-loving word.

The heart of the matter: A matter of the heart

AbstractWhy should Jesus die? I attempt to investigate the symbolic roots and significance of the crucifixion by means of the conceptual tools and methodology of cognitive semantics. In particular, I propose that we approach the meaning of Jesus’ death on four symbolic levels:the level where Jesus is a sacrificial lamb;the level where Jesus is a scapegoat and a sufferer for people’s sins;the level where Jesus is a redeemer and a savior;the level where Jesus is bread and wine in the Holy Communion.I suggest that all four levels prove distinct yet interdependent interpretations for the crucifixion. The different interpretations bring to the fore different aspects of the figure of Jesus and his death. While all of these aspects have been studied extensively by various authors from a cognitive linguistic perspective, my focus will be on the interrelations and interdependence of the four interpretations of Jesus’ figure and death.

Distinct but cooperating brain networks supporting semantic cognition.

Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgment task and a pattern-matching control task, each with 2 levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed 2 task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain-general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronized with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.

Dissociation between function and manipulation in semantic representations of motor impaired subjects: A new test

ABSTRACT A fundamental problem in semantic cognition is the representation of human concepts in the brain. Much of the knowledge acquired in the last decades comes from the study of dissociations found in patients with acquired difficulties in language, perception, and action. In particular, some deficits involve loss of knowledge about tools. The dissociation between two relevant aspects of tools, function and manipulation, has been the focus of several studies. In this paper, a new test designed to study the dissociation between function and manipulation is proposed and normative values for a control population are provided. This novel test was additionally administered to and evaluated in a group of Parkinson's disease patients. The Graded-Controlled Hub-and-Spoke model of Lambon Ralph, Jefferies, Patterson and Rogers was used as a theoretical guide to interpret the results.

Fine-grained semantic type discovery for heterogeneous sources using clustering

We focus on the key task of semantic type discovery over a set of heterogeneous sources, an important data preparation task. We consider the challenging setting of multiple Web data sources in a vertical domain, which present sparsity of data and a high degree of heterogeneity, even internally within each individual source. We assume each source provides a collection of entity specifications, i.e. entity descriptions, each expressed as a set of attribute name-value pairs. Semantic type discovery aims at clustering individual attribute name-value pairs that represent the same semantic concept. We take advantage of the opportunities arising from the redundancy of information across such sources and propose the iterative RaF-STD solution, which consists of three key steps: (i) a Bayesian model analysis of overlapping information across sources to match the most locally homogeneous attributes; (ii) a tagging approach, inspired by NLP techniques, to create (virtual) homogeneous attributes from portions of heterogeneous attribute values; and (iii) a novel use of classical techniques based on matching of attribute names and domains. Empirical evaluation on the DI2KG and WDC benchmarks demonstrates the superiority of RaF-STD over alternative approaches adapted from the literature.

Construction of a Multimodal Corpus of College Students’ Spoken English Based on Semantic Concepts

With the rapid development of multimedia technology, multimodal corpus came into being, which also opened up a new idea for oral English grammar teaching. In view of the problems existing in the current traditional English grammar textbooks, this paper applies the concepts of “corpus driven” and “multimodality” to grammar textbooks and tries to describe language use in a more authentic, reliable, and up-to-date form. In view of the problems existing in the current traditional English grammar teaching materials, this paper applies the semantic concept to the grammar teaching materials and tries to describe the language use in a more authentic, reliable, and up-to-date form. Based on the semantic concept, this paper studies the construction of college students’ oral English multimodal corpus. After the experiment, the results of the language fluency, accuracy, and complexity of the subjects in the experimental group and the control group are tested. The differences between the two groups were analyzed by one-way ANOVA as follows: in terms of language fluency, F 1 , 62 = 0.835 , P > 0.04 , which showed that there was no significant difference between the two groups after the experiment. In terms of accuracy, F 1 , 62 = 10.693 , P < 0.04 . There was significant difference between the two groups after the experiment. In this study, by analyzing and counting the distribution of conjunctions in students’ oral discourse, the types of conjunctions, their frequency of use, and the types of errors in use, we hope to understand the level and limitations of students’ use of conjunctions in oral discourse, so that students can better apply semantic conceptual cohesion and speak a coherent discourse, First of all, we should help students establish the awareness of textual cohesion and coherence.

Message-Based Logic Semantics and Intentional Linguistic Semantics of Paul Grice.

The paper considers new logical semantics for the classic propositional logic which states that a propositional formula refers to a special structure – “the tree of messages”. This tree of message determines the truth values for the elements of the propositional formula. The source of inspiration for creating a concept of such semantics is a philosophical-linguistic program advanced by H.P. Grice. Grice made a hypothesis according to which the meaning of the speech act is defined more by speaker’s intention than by the “conventional” meaning of utterances. A speaker may have hidden intentions towards his speech act – he is manipulating his audience for political or economic aims, for example. Thus, the true meaning of the utterance the speaker uses may even contradict the “conventional” meanings of those expressions. As a consequence, to understand the true meaning of those utterances you should take the speaker's true intentions into consideration. A message is a textual expression of such intentions. In general, messages can express different meta-rules which specify the context for the propositional formula which refers to the “tree”. Messages can cooperate between each other as well as with the messages from different trees creating specific kinds of “algebras”. By specifying these “algebras” the variety of different alternative propositional logics based on this semantics can be created. By interpreting messages and accordingly modifying the truth values of propositional formulas the situation described by Grice can be emulated. However, it should be admitted that the idea of such logical semantics is wider than just an emulation of the particular linguistic theory.

Dense Semantics-Assisted Networks for Video Action Recognition

Most existing action recognition approaches directly leverage the video-level features to recognize human actions from videos. Although these methods have made remarkable progress, the accuracy is still unsatisfied. When the test video involves complex backgrounds and activities, existing methods usually suffer from a significant drop in accuracy. Human action is inherently a high-level concept. Merely applying a video classification model without a detailed semantic understanding of the video content, e.g., objects, scene context, object motions, object interactions, is inadequate to tackle the challenges for action recognition. Fine-level semantic understanding of videos generates elementary semantic concepts from the raw video data, such as the semantics of objects and background regions. It can be employed to bridge the gap between the raw video data and the high-level concept of human actions. In this work, we leverage dense semantic segmentation masks, which encode rich semantic details, provide extra information for the network training, and improve the performance of action recognition. We propose a novel deep architecture which is named as Dense Semantics-Assisted Convolutional Neural Networks (DSA-CNNs) to effectively utilize dense semantic information of video by a bottom-up attention way in the spatial stream, while by the way of branch fusion in the temporal stream. To verify the effectiveness of our approach, we conduct extensive experiments on publicly available datasets – UCF101, HMDB51, and Kinetics. The experimental results demonstrate that our approach substantially improves existing methods and achieves very competitive performance. It also shows that our approach is superior to other related methods that utilize extra information for action recognition.

Abnormal Behavior Learning Based on Edge Computing toward a Crowd Monitoring System

Abnormal behavior poses a great threat to social security and stability. The resulting violence or crime leads to terrible consequences. How to utilize reasonable means to predict the dangerous intentions of massive crowds and prevent the potential hazard to the public is significant for social security. A crowd monitoring and management system is an effective way to detect abnormal behavior. In this article, we release unmanned aerial vehicles as well as fixed ground devices to achieve multi-level and multi-modal behavioral sensing on a massive crowd, deploy a hybrid model in edge cloud to extract global features from behavioral data of a massive crowd, and then utilize these global features to construct decent classification algorithms for action recognition and behavioral semantic cognition. With the cooperation of behavioral data and cognitive algorithms, we can understand the instantaneous emotions of the crowd. On the basis of behavioral data and the emotional state of the crowd, the correlation between daily behavior and any dangerous intention of a massive crowd has been revealed by utilizing behavioral big data analysis, which is a key foundation for predicting people's dangerous intentions. Finally, we conduct a case study of abnormal behavior detection based on pix2pix and continuous video frames. The experimental results show that the performance of our method is better than other algorithms in both public datasets and the customized Hajj dataset. The proposed novel pattern for the effective learning of a massive crowd is validated to effectively eliminate some of the possible dangers caused by abnormal behavior.

Effects of semantic diversity and word frequency on single word processing.

Some research suggests that semantic diversity (SemD), a measure of the variability of contexts in which a word appears, plays an important role in language processing, determining the availability of word representations (e.g., Adelman et al., 2006) and causing task-specific benefits or detriments to performance (e.g., Hoffman & Woollams, 2015). Some researchers have claimed that word frequency has no effect once such diversity measures are taken into account (Adelman et al., 2006). Taking advantage of the power of five large-scale databases, we investigated the effects of SemD, word frequency, and their interaction in five tasks, including word reading, lexical and concreteness decision, object picture naming, and word repetition. We found: (a) word frequency and SemD effects were consistently distinct; (b) effects of SemD were facilitatory in nearly all tasks, but inhibitory effects were also found; contrary to existing claims, we conclude that inhibitory SemD effects do not necessarily imply semantic selection requirements; (c) the presence of SemD effects minimally influenced the size of frequency effects when SemD was left uncontrolled, suggesting that SemD does not explain absent frequency effects in the patient literature; and (d) word frequency and SemD only interact in the largest data sets. Results are discussed in the context of rational models of memory (Anderson & Milson, 1989; Anderson & Schooler, 1991) and the Controlled Semantic Cognition framework (Lambon Ralph et al., 2017). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

ECONOMIC RECOVERY STRATEGY FOR THE COMMUNITY AND MSME PERFORMERS IN MEDAN CITY IN THE ADAPTATION ERA OF NEW HABITS

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Integrative Brain Dynamics in Childhood Bullying Victimization: Cognitive and Emotional Convergence Associated With Stress Psychopathology.

Bullying victimization is a form of psychological stress that is associated with poor outcomes in the areas of mental health and learning. Although the emotional maladjustment and memory impairment following interpersonal stress are well documented, the mechanisms of complex cerebral dysfunctions have neither been outlined nor studied in depth in the context of childhood bullying victimization. As a contribution to the cross-disciplinary field of developmental psychology and neuroscience, we review the neuropathophysiology of early life stress, as well as general psychological stress to synthesize the data and clarify the versatile dynamics within neuronal networks linked to bullying victimization. The stress-induced neuropsychological cascade and associated cerebral networks with a focus on cognitive and emotional convergence are described. The main findings are that stress-evoked neuroendocrine reactivity relates to neuromodulation and limbic dysregulation that hinder emotion processing and executive functioning such as semantic cognition, cognitive flexibility, and learning. Developmental aspects and interacting neural mechanisms linked to distressed cognitive and emotional processing are pinpointed and potential theory-of-mind nuances in targets of bullying are presented. The results show that childhood stress psychopathology is associated with a complex interplay where the major role belongs to, but is not limited to, the amygdala, fusiform gyrus, insula, striatum, and prefrontal cortex. This interplay contributes to the sensitivity toward facial expressions, poor cognitive reasoning, and distress that affect behavioral modulation and emotion regulation. We integrate the data on major brain dynamics in stress neuroactivity that can be associated with childhood psychopathology to help inform future studies that are focused on the treatment and prevention of psychiatric disorders and learning problems in bullied children and adolescents.

The role of the angular gyrus in semantic cognition: a synthesis of five functional neuroimaging studies

Semantic knowledge is central to human cognition. The angular gyrus (AG) is widely considered a key brain region for semantic cognition. However, the role of the AG in semantic processing is controversial. Key controversies concern response polarity (activation vs. deactivation) and its relation to task difficulty, lateralization (left vs. right AG), and functional–anatomical subdivision (PGa vs. PGp subregions). Here, we combined the fMRI data of five studies on semantic processing (n = 172) and analyzed the response profiles from the same anatomical regions-of-interest for left and right PGa and PGp. We found that the AG was consistently deactivated during non-semantic conditions, whereas response polarity during semantic conditions was inconsistent. However, the AG consistently showed relative response differences between semantic and non-semantic conditions, and between different semantic conditions. A combined analysis across all studies revealed that AG responses could be best explained by separable effects of task difficulty and semantic processing demand. Task difficulty effects were stronger in PGa than PGp, regardless of hemisphere. Semantic effects were stronger in left than right AG, regardless of subregion. These results suggest that the AG is engaged in both domain-general task-difficulty-related processes and domain-specific semantic processes. In semantic processing, we propose that left AG acts as a “multimodal convergence zone” that binds different semantic features associated with the same concept, enabling efficient access to task-relevant features.

Linguistic Data Model for Natural Languages and Artificial Intelligence. Part 7. Internal logic 2 Oleg M. Polyakov

Introduction. The article continues a series of publications on the linguistics of relations (hereinafter referred to as R-linguistics) and is devoted to the study of the functioning of logical connectives with nouns and adjectives. The article is the second part of the discussion of internal logic, which examines the use of logical connectives within sentences. This research involves the formation of semantic logic, that is, logic that takes into account the semantics of sentences.Methodology and sources. The results obtained in the previous parts of the series are used as research tools. To develop the necessary mathematical representations in the field of internal logic, the previously formulated semantic concepts and operations are used.Results and discussion. Two types of negation are introduced and their properties are defined. The properties of the linguistic model are formulated. The use of logical connectives with nouns and adjectives is analyzed. It is shown that the connective NOT can be attributed to both external and internal logic. The connectives AND and OR do not have a logical content, but serve to identify the state of a particular concept. Three semantic substitutions are defined. The reasons for the stability of semantic interpretation when changing the state of relations are substantiated.Conclusion. Abandoning the traditional view of natural language logic means abandoning logical operations and inference. This forces us to consider logical operations that now take into account semantics, since they are related to the structure of the linguistic model. Analysis of the functioning of logical connectives with nouns and adjectives shows that they either provide identification of the state of concepts, or can be transferred to external logic, or can operate within the framework of a linguistic model. The formulated substitution rules provide semantically correct substitutions and justify the stability of semantic interpretation in the conditions of changing states of concepts.

Promoting Student Competencies in Informatics Education by Combining Semantic Waves and Algorithmic Thinkingv

We live in a digital age, not least accelerated by the COVID-19 pandemic. It is all the more important in our society that students learn and master the key competence of algorithmic thinking to understand the informatics concepts behind every digital phenomena and thus is able to actively shape the future. For this to be successful, concepts must be identified that can convey this key competence to all students in such a way that algorithmic thinking is integrated in the subject of informatics - beyond a pure programming course. Furthermore, based on the Legitimation Code Theory, semantic waves provide a way to develop and review lesson plans. Therefore, we planned a workshop, that follow the phases of a semantic wave addressing algorithmic problems using a blockbased programming language. Considering this, we suggest the so-called SWAT concept (Semantic Wave Algorithmic Thinking concept), which is carried out and analyzed in a workshop with students. The workshop was carried out in online format in an 8th grade of a high school during a coronavirus lockdown. The level of algorithmic thinking was measured using a pretest and posttest both in the treatment group and in a control group and with the help of the approximate adjusted fractional Bayes factors for testing informative hypotheses statistically and through a reductive, qualitative content analysis of the students’ work results (worksheets and created programs) evaluated. The semantic wave concept was measured using several cognitive load ratings of the students during the workshop and also statistically evaluated with the approximate adjusted fractional Bayes factors for testing informative hypotheses, as well as a qualitative content analysis of the worksheets. Results of this pilot study provide first insights, that the SWAT-concept can be used in combination of unplugged and plugged parts.

Group-level stability but individual variability of neurocognitive status after awake resections of right frontal IDH-mutated glioma

Awake surgery for low-grade gliomas is currently considered the best procedure to improve the extent of resection and guarantee a "worth living life" for patients, meaning avoiding not only motor but also cognitive deficits. However, tumors located in the right hemisphere, especially in the right frontal lobe, are still rarely operated on in awake condition; one of the reasons possibly being that there is little information in the literature describing the rates and nature of long-lasting neuropsychological deficits following resection of right frontal glioma. To investigate long-term cognitive deficits after awake surgery in right frontal IDH-mutated glioma. We retrospectively analyzed a consecutive series of awake surgical resections between 2012 and 2020 for right frontal IDH-mutated glioma. We studied the patients' subjective complaints and objective neuropsychological evaluations, both before and after surgery. Our results were then put in perspective with the literature. Twenty surgical cases (including 5 cases of redo surgery) in eighteen patients (medium age: 42.5 [range 26–58]) were included in the study. The median preoperative volume was 37 cc; WHO grading was II, III and IV in 70%, 20%, and 10% of cases, respectively. Preoperatively, few patients had related subjective cognitive or behavioral impairment, while evaluations revealed mild deficits in 45% of cases, most often concerning executive functions, attention, working memory and speed processing. Immediate postoperative evaluations showed severe deficits of executive functions in 75% of cases but also attentional deficits (65%), spatial neglect (60%) and behavioral disturbances (apathy, aprosodia/amimia, emotional sensitivity, anosognosia). Four months after surgery, although psychometric z-scores were unchanged at the group level, individual evaluations showed a slight decrease of performance in 9/20 cases for at least one of the following domains: executive functions, speed processing, attention, semantic cognition, social cognition. Our results are generally consistent with those of the literature, confirming that the right frontal lobe is a highly eloquent area and suggesting the importance of operating these patients in awake conditions.

Indoor Positioning and Navigation Model Based on Semantic Grid

Traditional GPS positioning technology cannot be used in indoor space. With the development of the new positioning technology and the Internet of things, the indoor mobile object positioning and navigation model have been the focus of the relevant research institutions at home and abroad. Based on this, indoor positioning technology was studied starting from Wi-Fi, RFID, and iBeacon technology in this paper. However, the accuracy of indoor positioning and navigation needs to be further improved. This paper presents a semantic space model based on artificial intelligence technology, through semantic pattern matching, semantic concept extension, semantic reasoning and semantic mapping, and interior semantic localization is realized. The indoor semantic network and indoor grid navigation model are constructed, and the indoor semantic path is modeled from time, location, user, and congestion. At the same time, the improved Term Frequency-Inverse Document Frequency is combined with the Hidden Markov Model to improve the accuracy of matching the stay area with the most likely location to visit and improve the accuracy of semantic annotation. It was found that the research on the indoor positioning and navigation model based on the semantic grid can realize the uniform expression of the complex spatial semantics of the theme, geometry, connectivity, and distance, which can promote the development of indoor positioning and navigation.