Semantic Inconsistencies Research Articles

Indicators for Speech Comprehension in Migrant Children. A comparison of Extreme Groups

Objective Children with migrant background learning German as second language are frequently considered having problems in speech comprehension and speaking; nevertheless, it is very difficult to objectify that for young children. For this purpose risk-factors should be determined empirically. Material and Methods The study comprised 126 children from a developmental longitudinal study in 7 day-care centers in Frankfurt/M and Darmstadt. The sample was sorted into two extreme groups by their achievement in oral German language comprehension: criterion T-score ≥46=age appropriate (N=61) vs. T-score ≤32=poor (N=65). The study used an assumed best-subtests variable-selection (intelligence; grammatical based comprehension; verbal conceptualization; recognition of semantic and grammatical inconsistencies) to examine risk-factors for the quality of development in German as second language. Results Intelligence was average in both groups, however, significantly different (T-score=54.1; SD 6.7 vs. T-score=42.2; SD 8.8; p<0,001). Risk-factors for a separation between rather convenient and less convenient conditions for the development of German as second language could be identified by applying discriminant analyses (in order of descending magnitude): intelligence; recognition of verbal inconsistencies; mother's level of education; grammatical based comprehension. Regarding the group affiliation, 88% of the children with poor and 84% of those with age appropriate oral comprehension could be correctly classified within the selected samples. Conclusions The results provide an acceptable standard to distinguish migrant children with an age appropriate oral comprehension in German as the second language from such with a poorer one.

Privacy policies verification in composite services using OWL

Privacy has been an important issue for online services collecting customer data. P3P is a privacy policy language with a fixed vocabulary to express privacy practices of online services. The matching between the privacy practices (P3P policies) and users' privacy preferences facilitates the users to be aware of services' usage of their data. However, the change from single to composite online services raises more privacy concern due to the increasing amount of user data being collected, stored and shared. This change impacts on P3P since it was designed from a single service perspective. In addition, P3P allows the specification of policies containing semantic inconsistencies. In this paper, we extend P3P to be suitable for composite services and propose a formal semantics for P3P using OWL to facilitate reasoning about semantic ambiguities in P3P policies. The constraints defined in our ontology are used to verify potential semantic inconsistencies and to check for conflicts occurring from P3P policies of service members. We have implemented a P3P verification tool and verified five hundred P3P policies collected from actual websites. The verification result shows that more than half of these P3P policies contain conflicts.

Supporting collaborative software development over GitHub

SummaryGitHub is a web‐based, distributed Software Configuration Management (SCM) system build over Git, which enables developers to host shared repositories over the Internet and access them from any location, at any time. It helps developers to effectively orchestrate their activities over shared codebases by capturing direct conflicts arising because of concurrent editing on the same shared artifact. However, SCM systems have limited support for capturing inconsistencies arising because of indirect conflicts which arise because of software dependency relationships that exist between related artifacts, and lead to the introduction of syntactic and semantic inconsistencies in codebases.In this paper, we propose a novel collaborative software development (CSD) tool named, Collaboration Over GitHub (COG), that provides real‐time information about arising direct and indirect conflicts among collaborative developers, working over GitHub, through a collection of workspace awareness widgets. These widgets provide people‐centric information about direct and indirect collaborators over GitHub. Resource‐centric information about current and conflicting activities of real‐time collaborators is captured and propagated to others, based on the dependency relationships between software artifacts being manipulated by them. COG uses dependency graphs to store and process dependency relationship information which is required to ascertain information about indirect conflicts. Notably, the most important novel contribution of COG is that it not only captures indirect conflicts that lead to the introduction of syntactic inconsistencies but also changes that lead to semantic inconsistencies in the codebase. It also does so at finer levels of granularity, with changes to individual method's body being traced, thereby capturing statement‐level conflicts as well. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Складні сполучникові речення з асиметрією форми й змісту як периферія синтаксичної підсистеми сучасної української мови

The article outlines the typical symptoms of quantitative and qualitative asymmetry of the form and content at the level of complex conjunctive structures of the modern Ukrainian language. The analyzed material proves the prevalence of formal semantic inconsistencies in the syntax of a complex conjunctive sentence and proves the need for holistic and comprehensive studies of this phenomenon on the syntactic level of the Ukrainian language system as a whole.

Inconsistency Detection in Software Component Source Code using Ant Colony Optimization and Neural Network Algorithm

Objectives: Inconsistency detection is one of the major challenges in source code for the software developers. There is the need of consistent identifiers to reduce the code inconsistencies. So, developers should either have the knowledge to create conceptual identifiers or the knowledge to detect the inconsistencies in source code. Methods/Statistical Analysis: There is the availability of a list of tools for the detection of different types of inconsistencies. But the existing tools are not much appropriate for Semantic, Syntactic Inconsistencies and Part of Speech tagging. Findings: In the paper, an autonomous tool Automatic Bad Code Detector (ABCD) is developed to detect semantic, syntactic and part of speech inconsistency in the source code. ABCD tool identifies the inconsistencies in the source code based on the detected Code Clones. These Clones are detected by matching the test code with Code Repository. A java project based code repository is considered for experimentation. ABCD is evaluated for different java projects in order to find inconsistencies in source code. In ABCD tool main inconsistency detector are Ant Colony Optimization and Neural Network Back Propagation algorithm. Further, ABCD is useful in re-implementing the new versions of the java code. Applications/Improvements: The current concept is evaluated for the Semantic, Syntactic, POS-Word and POS-Phrase inconsistencies based on evaluation parameter of precision. The efficiency of ABCD is evaluated as an overall value for the precision, recall and f-measure.

Semantic inconsistencies without semantics? Semantically inconsistent objects elicit N400 responses on both real-world and apparently meaningless synthesized scenes

Semantic inconsistencies without semantics? Semantically inconsistent objects elicit N400 responses on both real-world and apparently meaningless synthesized scenes

Meditation training influences mind wandering and mindless reading.

It is challenging for individuals to maintain their attention on ongoing cognitive tasks without being distracted by task-unrelated thought. The wandering mind is thus a considerable obstacle when attention must be maintained over time. Mental training through meditation has been proposed as an effective method of attenuating the ebb and flow of attention to thoughts and feelings that distract from one’s foremost present goals. We provide evidence from 2 longitudinal studies that intensive meditation training in focused attention and monitoring meditation is associated with attenuated lapses of attention while reading. Across 2 studies, participants completed a reading task requiring ongoing error monitoring to detect episodes of semantic inconsistency. In a preliminary study, training participants were assessed at the beginning and end of a 3-month shamatha meditation retreat and again 7 years later. In a second study, training and experiencematched control participants were assessed at the beginning and end of a 1-month insight meditation retreat. Across both studies, training participants engaged in less mind wandering and less mindless reading following meditation training. Intensive meditation training may promote reductions in mind wandering among practitioners when required to maintain attention during a complex cognitive task.

Hebrew Nominal Patterns in the Speaker’s Mind

Some psycholinguists have claimed that the seven verbal Hebrew patterns are part of the mental lexicon (alongside the lexemes and the roots) whereas the nominal patterns are not. The difference is explained by the great number (over 100) of the nominal patterns and their semantic inconsistency. This claim is questioned by the present article. The number of the living or productive nominal patterns system is around thirty. Thirteen of them are common to the verbal and the nominal systems (five regular noun actions, five active participles, three perfective participles), and they are as frequent as the verbal forms themselves. The living nominal pattern system acts similarly to that of the verbal patterns. This is demonstrated by three phenomena that display the speakers’ awareness of the nominal patterns’ functions: a) pattern switching when there is no matching between the pattern and the content of the word; b) colloquial derivation in the living patterns; c) acceptance or rejection of proposed new items according to the extent of their adaptation to the pattern’s function. The evidence is naturalistic data taken from the speakers’ linguistic behavior as manifested in spoken and written sources including the Internet and television shows.

Formalizing UML Model Metrics Using Z Language

Till now, a large variety of researchers have carried out lots of efforts on object-oriented and UML model metrics from different views. They put forward numerous of metrics and carried out some series of theoretical and experimental verifications on understandability, analyzability, maintainability, fault-proneness, change-proneness and reuse. However, there is no formal semantic specification for UML model metrics, which may lead to potential semantic inconsistency and ambiguity. To solve this problem, this paper provided formalization for UML model metrics at the level of UML Meta models. This formalization can not only help people to understand the meaning of UML model metrics, but also can be used in the application domain of UML model metrics in a more rigorous way.

Modification of stative predicates

Manner and locative expressions modifying stative predicates, as in own (something) honestly and (be) quiet in the car, are rare compared to those modifying dynamic predicates, and it has been claimed (for example, in Maienborn 2005 and Katz 2008) that they are systematically excluded on semantic grounds. I argue here that this is not so: in fact, they are perfectly acceptable once the restrictions on them are understood. I propose further that these restrictions take the form of (i) a pragmatic condition that generally bans locative modification of stative predicates, but that may be overridden in certain defined contexts, and (ii) regular semantic incompatibilities between adverbs and stative predicates, which, being semantically ‘impoverished’, have relatively few modifiable semantic features compared to dynamic predicates. These proposals are supported by extensive examples. The conclusions indicate that there is no need to treat states as fundamentally different from other eventualities, whether by invoking Kimian states or by avoiding eventuality variables altogether in their representations.

Resolving semantic inconsistencies in elibrary.ru based on fuzzy inference

An approach to solving semantic inconsistency problems in critical information systems based on the generation of the fuzzy rules database and further application of the Mamdani fuzzy inference scheme is proposed. The approach is considered with the electronic library elibrary.ru taken as an example. The composition of the compared fields and form of membership functions for input linguistic variables are validated. Examples of resolving inconsistencies for making a decision on the possibility of attributing a specific publication or reference to it to a particular category (new or already available publication) are presented.

Approximate and selective reasoning on knowledge graphs: A distributional semantics approach

Tasks such as question answering and semantic search are dependent on the ability of querying and reasoning over large-scale commonsense knowledge bases (KBs). However, dealing with commonsense data demands coping with problems such as the increase in schema complexity, semantic inconsistency, incompleteness and scalability. This paper proposes a selective graph navigation mechanism based on a distributional relational semantic model which can be applied to querying and reasoning over heterogeneous knowledge bases (KBs). The approach can be used for approximative reasoning, querying and associational knowledge discovery. In this paper we focus on commonsense reasoning as the main motivational scenario for the approach. The approach focuses on addressing the following problems: (i) providing a semantic selection mechanism for facts which are relevant and meaningful in a specific reasoning and querying context and (ii) allowing coping with information incompleteness in large KBs. The approach is evaluated using ConceptNet as a commonsense KB, and achieved high selectivity, high selectivity scalability and high accuracy in the selection of meaningful navigational paths. Distributional semantics is also used as a principled mechanism to cope with information incompleteness.

Consistency maintenance of compound operations in real-time collaborative environments

In real-time collaborative environments, address space transformation strategy can be used to achieve consistency maintenance of shared documents. However, as for the execution of compound operations, they are firstly decomposed into primitive operations, the relationships between the referencing objects and referenced objects are lost during the decomposition process. Besides, the Undo operations in this environment are targeted at compound operations, but not decomposed basic ones. However, the traditional algorithms take primitive operation as the manipulation unit, thus leading to semantic inconsistencies of compound Undo operations. This paper appends two history buffers to maintain the relationships between the original operations and the decomposed ones and introduces “Retrace-Undo-VT-Redo-Retrace” strategy to realize the consistency maintenance of compound operations. Also, this paper introduces the version-decomposition strategy, describes the main algorithms of the compound Undo operations and analyses the validity of the strategy. Case analysis is given to show the effectiveness of the strategy.

From specific examples to general knowledge in language learning

The extraction of general knowledge from individual episodes is critical if we are to learn new knowledge or abilities. Here we uncover some of the key cognitive mechanisms that characterise this process in the domain of language learning. In five experiments adult participants learned new morphological units embedded in fictitious words created by attaching new affixes (e.g., -afe) to familiar word stems (e.g., “sleepafe is a participant in a study about the effects of sleep”). Participants’ ability to generalise semantic knowledge about the affixes was tested using tasks requiring the comprehension and production of novel words containing a trained affix (e.g., sailafe). We manipulated the delay between training and test (Experiment 1), the number of unique exemplars provided for each affix during training (Experiment 2), and the consistency of the form-to-meaning mapping of the affixes (Experiments 3–5). In a task where speeded online language processing is required (semantic priming), generalisation was achieved only after a memory consolidation opportunity following training, and only if the training included a sufficient number of unique exemplars. Semantic inconsistency disrupted speeded generalisation unless consolidation was allowed to operate on one of the two affix-meanings before introducing inconsistencies. In contrast, in tasks that required slow, deliberate reasoning, generalisation could be achieved largely irrespective of the above constraints. These findings point to two different mechanisms of generalisation that have different cognitive demands and rely on different types of memory representations.

Linked data practice at different levels of semantic precision: The perspective of libraries, archives and museums

EDITOR'S SUMMARYLibraries, archives and museums rely on structured schemas and vocabularies to indicate classes in which a resource may belong. In the context of linked data, key organizational components are the RDF data model, element schemas and value vocabularies, with simple ontologies having minimally defined classes and properties in order to facilitate reuse and interoperability. Simplicity over formal semantics is a tenet of the open‐world assumption underlying ontology languages central to the Semantic Web, but the result is a lack of constraints, data quality checks and validation capacity. Inconsistent use of vocabularies and ontologies that do not follow formal semantics rules and logical concept hierarchies further complicate the use of Semantic Web technologies. The Simple Knowledge Organization System (SKOS) helps make existing value vocabularies available in the linked data environment, but it exchanges precision for simplicity. Incompatibilities between simple organized vocabularies, Resource Description Framework Schemas and OWL ontologies and even basic notions of subjects and concepts prevent smooth translations and challenge the conversion of cultural institutions' unique legacy vocabularies for linked data. Adopting the linked data vision requires accepting loose semantic interpretations. To avoid semantic inconsistencies and illogical results, cultural organizations following the linked data path must be careful to choose the level of semantics that best suits their domain and needs.

Multi-talker background and semantic priming effect.

The reported studies have aimed to investigate whether informational masking in a multi-talker background relies on semantic interference between the background and target using an adapted semantic priming paradigm. In 3 experiments, participants were required to perform a lexical decision task on a target item embedded in backgrounds composed of 1–4 voices. These voices were Semantically Consistent (SC) voices (i.e., pronouncing words sharing semantic features with the target) or Semantically Inconsistent (SI) voices (i.e., pronouncing words semantically unrelated to each other and to the target). In the first experiment, backgrounds consisted of 1 or 2 SC voices. One and 2 SI voices were added in Experiments 2 and 3, respectively. The results showed a semantic priming effect only in the conditions where the number of SC voices was greater than the number of SI voices, suggesting that semantic priming depended on prime intelligibility and strategic processes. However, even if backgrounds were composed of 3 or 4 voices, reducing intelligibility, participants were able to recognize words from these backgrounds, although no semantic priming effect on the targets was observed. Overall this finding suggests that informational masking can occur at a semantic level if intelligibility is sufficient. Based on the Effortfulness Hypothesis, we also suggest that when there is an increased difficulty in extracting target signals (caused by a relatively high number of voices in the background), more cognitive resources were allocated to formal processes (i.e., acoustic and phonological), leading to a decrease in available resources for deeper semantic processing of background words, therefore preventing semantic priming from occurring.

Detection Algorithm of Semantic Inconsistency for Fuzzy Ontology Merging

Fuzzy ontology can be built to effectively deal with uncertainty and ambiguity for domain knowledge modeling. Merging multiple fuzzy local ontologies may implement semantic integration of multiple data sources and semantic interoperability between heterogeneous systems in distributed environment. In order to solve the problem of semantic inconsistency mappings for fuzzy ontology merging system, we proposed a detection algorithm of semantic inconsistency mapping which includes sub detection methods of circular semantic inconsistency, subclass-of axiom redundancy semantic inconsistency, attribute membership semantic inconsistency and disjoint axioms redundancy semantic inconsistency. With the detection algorithm of semantic inconsistency, we establish fuzzy ontology merging system in experiment.

Cross-linguistic variation in the neurophysiological response to semantic processing: Evidence from anomalies at the borderline of awareness

The N400 event-related brain potential (ERP) has played a major role in the examination of how the human brain processes meaning. For current theories of the N400, classes of semantic inconsistencies which do not elicit N400 effects have proven particularly influential. Semantic anomalies that are difficult to detect are a case in point (“borderline anomalies”, e.g. “After an air crash, where should the survivors be buried?”), engendering a late positive ERP response but no N400 effect in English (Sanford, Leuthold, Bohan, & Sanford, 2011). In three auditory ERP experiments, we demonstrate that this result is subject to cross-linguistic variation. In a German version of Sanford and colleagues′ experiment (Experiment 1), detected borderline anomalies elicited both N400 and late positivity effects compared to control stimuli or to missed borderline anomalies. Classic easy-to-detect semantic (non-borderline) anomalies showed the same pattern as in English (N400 plus late positivity). The cross-linguistic difference in the response to borderline anomalies was replicated in two additional studies with a slightly modified task (Experiment 2a: German; Experiment 2b: English), with a reliable LANGUAGE×ANOMALY interaction for the borderline anomalies confirming that the N400 effect is subject to systematic cross-linguistic variation. We argue that this variation results from differences in the language-specific default weighting of top-down and bottom-up information, concluding that N400 amplitude reflects the interaction between the two information sources in the form-to-meaning mapping.

Impossible to _gnore: Word-Form Inconsistency Slows Preschool Children's Word-Learning

Many studies have examined language acquisition under morphosyntactic or semantic inconsistency, but few have considered word-form inconsistency. Many young learners encounter word-form inconsistency due to accent variation in their communities. The current study asked how preschoolers recognize accent-variants of newly learned words. Can preschoolers generalize recognition based on partial match to the learned form? When learning in two accents simultaneously, do children ignore inconsistent elements, or encode two word forms (one per accent)? Three- to 5-year-olds learned words in a novel-word learning paradigm but did not generalize to new accent-like pronunciations (Experiment 1) unless familiar-word recognition trials were interspersed (Experiments 3 and 4), which apparently generated a familiar-word-recognition pragmatic context. When exposure included two accent-variants per word, children were less accurate (Experiment 2) and slower to look to referents (Experiments 2, 5) relative to one-accent learning. Implications for language learning and accent processing over development are discussed.

Semantic Constraints Satisfaction Based Improved Quality of Ontology Alignment

Development of informative and telecommunication technologies have caused to create much dissimilar information. As well with growing different information resources in ontology designs, the importance of management these dissimilar resources has increased. In spite of most matchers use diverse measures for discovery the mappings, some semantic inconsistencies in final alignment are unavoidable. So it is essential to enhance a post-processing phase to training error patterns in the final alignment. The impartial of this research was refining the ontology semantic constraints over defining semantic constraints by a different measure for suitable weighting to the constraints. The outcomes indicated that the standard evaluation measures better in the suggestive method and comparing with other top ranked matchers the used method can create enhanced outcomes.