Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.
This paper proposes a ontology of tree structure approach for adaptive object recognition in a situation-variant environment. In this paper, we introduce a new concept, ontology of tree structure ontology, for context sensitivity, as we found that many developed systems work in a context-invariant environment. Due to the effects of illumination on a supreme obstinate designing context-sensitive recognition system, we have focused on designing such a context-variant system using ontology of tree structure. Ontology can be defined as an explicit specification of conceptualization of a domain typically captured in an abstract model of how people think about things in the domain. People produce ontologies to understand and explain underlying principles and environmental factors. In this research, we have proposed context ontology, context modeling, context adaptation, and context categorization to design ontology of tree structure based on illumination criteria. After selecting the proper light-ontology domain, we benefit from selecting a set of actions that produces better performance on that domain. We have carried out extensive experiments on these concepts in the area of object recognition in a dynamic changing environment, and we have achieved enormous success, which will enable us to proceed on our basic concepts.
In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.
In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.
Plant somatic cells can be reprogrammed into a pluripotent cell mass, called callus, which can be subsequently used for de novo shoot regeneration through a two-step in vitro tissue culture method. MET1-dependent CG methylation has been implicated in plant regeneration in Arabidopsis, because the met1-3 mutant exhibits increased shoot regeneration compared with the wild-type. To understand the role of MET1 in de novo shoot regeneration, we compared the genome-wide DNA methylomes and transcriptomes of wildtype and met1-3 callus and leaf. The CG methylation patterns were largely unchanged during leaf-to-callus transition, suggesting that the altered regeneration phenotype of met1-3 was caused by the constitutively hypomethylated genes, independent of the tissue type. In particular, MET1-dependent CG methylation was observed at the blue light receptor genes, CRYPTOCHROME 1 (CRY1) and CRY2, which reduced their expression. Coexpression network analysis revealed that the CRY1 gene was closely linked to cytokinin signaling genes. Consistently, functional enrichment analysis of differentially expressed genes in met1-3 showed that gene ontology terms related to light and hormone signaling were overrepresented. Overall, our findings indicate that MET1-dependent repression of light and cytokinin signaling influences plant regeneration capacity and shoot identity establishment.
To understand the responses of grapevines in response to cold stress causing the limited growth and development, differentially expressed genes (DEGs) were screened through transcriptome analysis of shoots from 2 grapevine cultivars ('Campbell Early' and 'Muscat Baily A') kept at -$2^{\circ}C$ for 4 days. In gene ontology analysis of DEGs from 'Campbell Early', there were 17,424 clones related with biological process, 28,954 with cellular component, and 6,972 with molecular function genes in response to freezing temperature. The major induced genes included dehydrin xero 1, K-box region and MADS-box transcription factor family protein, and MYB domain protein 36, and inhibited genes included light-harvesting chlorophyll B-binding protein 3, FASCICLIN-like arabinoogalactan 9, and pectin methylesterase 61 in 'Campbell Early' grapevines. In gene ontology analysis of DEGs from 'Muscat Baily A', there were 1,157 clones related with biological process, 1,350 with cellular component, and 431 with molecular function gene. The major induced genes of 'Muscat Baily A' included NB-ARC domain-containing disease resistance protein, fatty acid hydrozylase superfamily, and isopentenyltransferase 3, and inhibited genes included binding, IAP-like protein 1, and pentatricopeptide repeat superfamily protein. All major DEGs were shown to be expressed differentially by freezing temperature in real time-PCR analysis. Protein domain analysis using InterPro Scan revealed that ubiquitin-protein ligase was redundant in both tested grapevines. Transcriptome profile of shoots exposed to cold can provide new insights into the molecular basis of tolerance to low-temperature in grapevines, and can be used as resources for development new grapevines tolerant to coldness.
The main purpose of this paper is to examine Putnam's recent conception of ethics, and show that it gives rise to an ineluctable incoherence with his rationalism. This suggests that Putnam's philosophy has to be far more naturalized to make his new position cogent. Putnam recently has shown some explicit turn toward pragmatism a la James and Dewey under the name of "pragmatic pluralism." Putnam says that traditional ethics has presupposed some form of ontology in one way or another, which he sees is based on an unnecessary pursuit of a misleading conception of objectivity. Putnam tries to get rid of any notion of ontology in ethics, whereby we can talk about a third view which runs between traditional objectivism and nihilistic relativism. In this sense, he defines pragmatism as "fallibilism cum antiskepticism." Putnam's suggestion makes a good sense as far as it goes. However, his continuous transition toward pragmatism is critically impeded by his own adhesion to the normative conception of "reason." In this light, Putnam himself is wobbling between Kant and Dewey, just as he describes ethics is. Dewey's pragmatism does not have recourse to the very notion of reason to secure objectivity necessary to make sense of moral experience. Putnam needs to be far more naturalized to reach cogently where he espouses, and this can be done only by renouncing the normative conception of reason.
It is argued in this paper that, in determining semantic similarity, Korean words should be recategorized with a focus on the semantic relation to ontology in light of cross-linguistic morphological variations. It is proposed, in particular, that Korean semantic similarity should be measured on three tracks, human judgements track, relatedness track, and cross-part-of-speech relations track. As demonstrated in Yang et al. (2015), GloVe, the unsupervised learning machine on semantic similarity, is applicable to Korean with its performance being compared with human judgement results. Based on this compatability, it was further thought that the model's performance might most likely vary with different kinds of specific relations in different languages. An attempt was made to analyze them in terms of two major Korean-specific categories involved in their lexical and cross-POS-relations. It is concluded that languages must be analyzed by varying methods so that semantic components across languages may allow varying semantic distance in the vector space models.
Journal of the Korea Institute of Information and Communication Engineering
/
v.20
no.7
/
pp.1317-1324
/
2016
Utilizing the Arduino platform to express the emotions that reflect the colors expressed the jewelry. Emotional color expression utilizes Plutchik's Wheel of Emotions model was applied to the similarity of emotions and colors. It receives the recognized value from the temperature, lighting, sound, pulse sensor and gyro sensor of a smart jewelery that can be easily accessible from your smartphone processes that recognize and process the emotion applied the rules of inference based on ontology. The emotional feelings color depending on the color looking for the emotion seen in context and applied to the smart LED jewelry. The emotion and the color combination of contextual information extracted from the recognition sensors are reflected in the built-in smart LED Jewelry depending on the emotions of the wearer. Take a light plus the emotion in a smart jewelery can represent the emotions of the situation, the doctor will be able to be a tool of representation.
Kim, Ki-Il;Yoon, Jin-Hong;Park, Pyoung-Sun;Kim, Mi-Jin
한국HCI학회:학술대회논문집
/
2008.02b
/
pp.411-416
/
2008
The development of games has brought about the birth of game characters that are visually very realistic. At present, one sees much enthusiasm for giving the characters emotions through such devices as avatars and emoticons. However, in a freely changing environment of games, the devices merely allow for the expression of the value derived from a first input rather than creating expressions of emotion that actively respond to their surroundings. As such, there are as of yet no displays of deep emotions among game characters. In light of this, the present article proposes the 'CROSS(Character Reaction on Specific Situation) Model AE Engine' for game characters in order to develop characters that will actively express action and emotion within the environment of the changing face of games. This is accomplished by classifying the emotional components applicable to game characters based on the OCC model, which is one of the most well known cognitive psychological models. Then, the situation of game playing analysis of the commercialized RPG game is systematized by ontology.
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