• Journal of Arbitration Studies
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• v.31 no.3
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• pp.25-42
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• 2021

Arbitration is an alternative dispute resolution mechanism based on the parties' agreement to resolve any disputes parties may have by arbitration rather than litigation in court. Parties' consent to arbitrate, which must be manifest in the parties' arbitration clause or agreement, is the foundation for arbitration; thus, the language of an arbitration agreement is often of utmost importance in determining the intent of the parties regarding many aspects of arbitration proceedings, such as, the scope of arbitral proceedings, arbitral seat, and authority of arbitral tribunals, among others. Recently, the U.S. Supreme Court held in Lamps Plus, Inc. v. Varela (2019) that ambiguity in arbitration agreement as to availability of class arbitration should be resolved in favor of individual arbitration, and therefore, class arbitration would be precluded. Such holding was met with criticism by four separate dissenting opinions, in which the dissenting Justices have disagreed with the majority's interpretation of the arbitration agreement at issue, as well as, its rejection of application of state law in resolving contractual ambiguity. This article analyzes the Supreme Court's decision and reviews the Court's approach in construction of the arbitration agreement. Nevertheless, because the Supreme Court declined to provide clear guidelines as to precisely what contractual basis is required to permit class arbitration, either silence or ambiguity in arbitration agreements will be resolved by disallowing class arbitration.

• School Mathematics
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• v.12 no.1
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• pp.79-95
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• 2010

The purpose of this study is to examine into how the mathematically gifted cope with ambiguity when they are encountered to learn via resolving ambiguity. In this study 6 gifted students are asked to resolve the ambiguity. Participant in this study appeared to experience the need of mathematical justification and the flexible change of perspective. The gifted have constructed unified mathematical knowledge by making a relation between two incompatible perspective in the process of resolving the ambiguity. We suggest that dealing with ambiguity in mathematics class can be a good opportunity for enhancing the gifted student mathematics education.

• International Journal of Costume and Fashion
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• v.7 no.2
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• pp.41-48
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• 2007

Dress and appearance are said to be related to power which results in in.f1uencing others. Fashion and appearance style of the first African American First Lady, Michelle Obama during the presidential campaign and the inaugural period were examined. It was analyzed how Mrs. Obama has used her appearance styling to give influence on the American people. Content analysis was applied to understand the meaning of her style. Cultural meaning of her appearance styling during presidential campaign was explained in terms of class ambivalence, racial tension, and gender ambivalence. Strategic negotiation among different classes, gender, and racial groups was shown in her styling and proven to be powerful.

• Bulletin of the Korean Chemical Society
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• v.35 no.3
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• pp.845-850
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• 2014

The rapid development of shotgun proteomics is paving the way for extensive proteome profiling, while providing extensive information on various post translational modifications (PTMs) that occur to a proteome of interest. For example, the current phosphoproteomic methods can yield more than 10,000 phosphopeptides identified from a proteome sample. Despite these developments, it remains a challenging issue to pinpoint the true phosphorylation sites, especially when multiple sites are possible for phosphorylation in the peptides. We developed the Phospho-UMC filter, which is a simple method of localizing the site of phosphorylation using unique mass classes (UMCs) information to differentiate phosphopeptides with different phosphorylation sites and increase the confidence in phosphorylation site localization. The method was applied to large scale phosphopeptide profiling data and was demonstrated to be effective in the reducing ambiguity associated with the tandem mass spectrometric data analysis of phosphopeptides.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.6
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• pp.79-86
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• 1978

The characteristics of contiguous pulse trains of stopped FM signals with binary phase coding, to be used as radar signals, were investigated. For this purpose, the general expressions for the spectra and the ambiguity functions of this class of signals were first obtained; these expressions were then compute6 and plotted by the use of computer for various coding scheme. The results show that alternate phase coding provides the best time resolution and the corresponding ambiguity functon has a configuration of "be6 of spikes" in the whole time-velocity plane.ity plane.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.85-90
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• 2005

MX and its analogs are synthesized and modeled by quantitative structure activity relationship (QSAR) study including comparative molecular field analysis (CoMFA). As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. Because hologram quantitative structure activity relationship (HQSAR) technique is based on the 2-dimensional descriptors, this is free of ambiguity of conformational selection and molecular alignment. In this study we tried to include all the data available from the literature, and modeled with the HQSAR technique. Among the parameters affecting fragmentation, connectivity was the most important one for the whole compounds, giving good statistics. Considering additional parameters such as bond specification only slightly improved the model. Therefore connectivity has been found to be the most appropriate to explain the mutagenicity for this class of compounds.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.219-226
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• 2006

For the accurate creation of annotation information in a free-form annotation environment, the ambiguity that arises in the analysis stage between the geometric information and annotations needs to be resolved. Therefore, this This paper identifies, analyzes, and proposes presents solutions methods for the ambiguity that can occur between free-form marking and various contexts in XML-based annotation environment. The proposed method is based on context which includes various textual and structure information between free-form marking and annotated part. The proposed method show that the annotated portions areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment. This study can be effectively applied to eLearning, Cyber-Class, and IETM

• Journal of Communications and Networks
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• v.17 no.5
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• pp.491-498
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• 2015

Recognition of radar emitter signals is one of core elements in radar reconnaissance systems. A novel method based on singular value decomposition (SVD) and the main ridge slice of ambiguity function (AF) is presented for attaining a higher correct recognition rate of radar emitter signals in case of low signal-to-noise ratio. This method calculates the AF of the sorted signal and ascertains the main ridge slice envelope. To improve the recognition performance, SVD is employed to eliminate the influence of noise on the main ridge slice envelope. The rotation angle and symmetric Holder coefficients of the main ridge slice envelope are extracted as the elements of the feature vector. And kernel fuzzy c-means clustering is adopted to analyze the feature vector and classify different types of radar signals. Simulation results indicate that the feature vector extracted by the proposed method has satisfactory aggregation within class, separability between classes, and stability. Compared to existing methods, the proposed feature recognition method can achieve a higher correct recognition rate.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.53-67
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• 2008

At present, for reuse of similar domains between feature model and class model. researches of transformation at the model level and of transformation using ontology between two models are being made. but consistent transformation through metamodel is not made. And the factors of modeling transformation targets are not sufficient, and especially, automatic transformation algorithm and supporting tools are not provided so reuse of domains between models is not activated. This paper proposes a method of transformation from feature model to class model using ontology on the metamodel. For this, it re-establishes the metamodel of feature model, class model, and ontology, and it defines the properties of modelling factors for each metamodel. Based on the properties, it defines the profiles of transformation rules between feature mndel and ontology, and between ontology and class model, using set theory and propositional calculus. For automation of the transformation, it creates transformation algorithm and supporting tools. Using the proposed transformation rules and tools, real application is made through Electronic Approval System. Through this, it is possible to transform from the existing constructed feature model to the class model and to use it again for a different development method. Especially, it is Possible to remove ambiguity of semantic transformation using ontology, and automation of transformation maintains consistence between models.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.