Hypothetical Spaces Research Articles

Encoding of data sets and algorithms

In many high-impact applications, it is important to ensure the quality of the output of a machine learning algorithm as well as its reliability in comparison to the complexity of the algorithm used. In this paper, we have initiated a mathematically rigorous theory to decide which models (algorithms applied on data sets) are close to each other in terms of certain metrics, such as performance and the complexity level of the algorithm. This involves creating a grid on the hypothetical spaces of data sets and algorithms so as to identify a finite set of probability distributions from which the data sets are sampled and a finite set of algorithms. A given threshold metric acting on this grid will express the nearness (or statistical distance) of each algorithm and data set of interest to any given application. A technically difficult part of this project is to estimate the so-called metric entropy of a compact subset of functions of infinitely many variables that arise in the definition of these spaces.

현대시에 나타난 자아확장 회복탄력성의 인지기호학적 고찰

This study confirms that resilience is embodied by the pragmatic function ‘ego expansion' revealed in the poems of the above three poets. The poems in which the ‘ego expansion' that is the foundation of resilience emerged revealed the process of meaning generation in a new light. The formation of the relationship between the medium and the goal by the pragmatic function ‘ego expansion' contained in each text is illustrated by the meaning-generating process of resilience. The difference of the ego expansion from general growth is in relationality. Cognitive structures have emerged in which the medium and the goal by the connectivist spread resilience through the principle of sameness. Mental space, which is the operating element of ego expansion, was typed into ‘time spaces', ‘space spaces', ‘domain spaces', ‘hypothetical spaces', etc, to form a semantic space. In the poem of Yun Dongju, the resilience caused by the ego expansion into the multi-ego of ego is revealed as a type of mental space of ‘domain spaces', ‘hypothetical spaces' and ‘time spaces'. In particular, the cognitive background of time spaces was generally implied, and cognitive settings that ruminate on the ego in time spaces were dominant. The ego expansion is revealed in the superego and the split ego, and the ego expansion into the split ego is highlighted. The resilience, the orientation of the superego to overcome the agony of ego that pursues the ideal goal to overcome the difficulty of the reality and the internal and external hardship is expressed was watched. Even in the trial product that calls the past ego and forms the split ego, the will of resilience of possitive future was expressed. In the poem of Han Yongun, the transitional ego expansion into the subject’s object was represented by ‘hypothetical spaces’, and the type of mental space of ‘space spaces’ was revealed dominant and evidently so the resilience of transitional aspect into the object of the subject was clearly highlighted. The will to overcome the absolute pursuit of cognitive object and the cognitive distance with the cognitive object was expressed in the subject and objective ideology by conectivist’s ego expansion of pragmatic function. The cognitive attitude to identify the subject and the object was reinforced through the transitional ego expansion into the object of the subject. The orientation into the identity of the subject and the object appeared in the text was firm, and the resilience of ego expansion by the mental action seen as the cognitive action principle was expressed. In the poem of Baek Seok, the ‘time spaces’ was lied in the text in the cognitive situation setting where the exclusive ego expansion into the community of the object is occurred, specially the ‘domain spaces’ was evidently revealed. That is because the multi-layer time spaces cognitively forms several activity areas of our life. On the other hand, it was possible to identify even the type of ‘space spaces’, and it shows the space that has no spatial limit of community. In the text, such symbols as the holidays, residential space, lifetool, agriculture, food, solar term, daily life were used to represent the resilience of family community and local community. In the part focused by community consiciousness that is originated from the natural object and object, the poetic setting that recognizes the community consciousness where the time spaces is expanded was focused. The generation of positivity and happiness that attract the resilience appeared in the text was seen as the community dimension rather than the personal dimension.

Fantastic Architecture in Cinema

Movies represent society's dream, which is to tell a story; characters interact with each other to create this story, their mere presence on screen creating space. Thus, filmmakers become architects in their effort to communicate these spaces, whether they are interior or urban, to enhance and add to their story telling. They are not constrained by the limits of the architect nor, especially in the case of Sci-fi and Fantasy movies, even by the constraints of reality, imagining and creating architecture from a wholly different perspective: a story perspective. The characters interact with their hypothetical spaces and this shows what they require of the architecture to convey their story. Thus, the hypothetical spaces represent people's aspirations and their deepest fears for architecture. Part of an architect's job is making dreams a reality. However, in the architectural industry, design is accomplished in a step-by-step process that has undergone little change since its establishment. While this makes the job easier, it also leads to recycling, putting limits on architects' imaginations. This research analyzed an array of fantasy and sci-fi movies from an architectural point of view and explored the inspirations behind them. Patterns were found in the arrangement of spaces and the urban characteristics in the films. Then, the themes and messages behind the architecture were explored. Findings indicate how the cinematic architectural designs have played off of real life architecture and inspired one another since the creation of moving pictures. From a practical lens, these findings reignite architects' imaginations, proposing new tools to achieve the fulfillment of society's dreams.

THE PHILOSOPHICAL APPROXIMATIONS IN INTERNATIONAL CONTEMPORARY FORMATION

The recent research deals with the philosophical approximations in international contemporary formation. The research deals with an introduction that includes the problem and significance of it. This significance has represented by consideration of art as a language that has many complicated intellectual processes. This type of language has been ascertained by the Phenomenological Interpretation through constructing an artwork by using the same perception , and making approximation with the space that express a visual language. The research aims at finding out the philosophical approximations in international contemporary formation. The limits of the research is restricted to the study of philosophical approximations in contemporary formation specially the conceptual art from 1965 to 1970. The research has four sections : The first section deals with the meaning of concept in philosophical thinking: The research focuses on tracing back the concept process in philosophy. It presents many possibilities concerning the concept, the imagination and the thought. The second section deals with the concept as an interpretation : It states the idea of art prosperity through its quality not quantity. The third section deals with the philosophy of conceptual art ( Applications and Interpretations) : The artistic phenomenon can not be achieved without practice. This is a feature of ontology which requires the discovery of any phenomenon through its ontological function. This means the melting of an artwork with the outer atmosphere and horizons.The fourth section has the conclusions that have been drawn by the researcher. They are as follow : 1. The concept of text in (The Minimal Edge Art) is regarded as a meeting of texts. The text with its performing and formative types has depended on outer codes that make transformation in meaning. This results from ambiguity and connotations that are connected with hypothetical spaces. There is a renewal of old texts in every period. 2. The Discourse level of the performing arts (Body Language) has decreased to the degree of Civilized Decline. Dealing with mixed references has its spread over participations. This results from inadequate translation of synonyms which have mysterious and symbolic space limits. The research has a list of references, and English abstract.

Privileged Information for Data Clustering

Many machine learning algorithms assume that all input samples are independently and identically distributed from some common distribution on either the input space X, in the case of unsupervised learning, or the input and output space X × Y in the case of supervised and semi-supervised learning. In the last number of years the relaxation of this assumption has been explored and the importance of incorporation of additional information within machine learning algorithms became more apparent. Traditionally such fusion of information was the domain of semi-supervised learning. More recently the inclusion of knowledge from separate hypothetical spaces has been proposed by Vapnik as part of the supervised setting. In this work we are interested in exploring Vapnik’s idea of ‘master-class’ learning and the associated learning using ‘privileged’ information, however within the unsupervised setting. Adoption of the advanced supervised learning paradigm for the unsupervised setting instigates investigation into the difference between privileged and technical data. By means of our proposed aRi-MAX method stability of the K-Means algorithm is improved and identification of the best clustering solution is achieved on an artificial dataset. Subsequently an information theoretic dot product based algorithm called P-Dot is proposed. This method has the ability to utilize a wide variety of clustering techniques, individually or in combination, while fusing privileged and technical data for improved clustering. Application of the P-Dot method to the task of digit recognition confirms our findings in a real-world scenario.

Privileged information for data clustering

Many machine learning algorithms assume that all input samples are independently and identically distributed from some common distribution on either the input space X, in the case of unsupervised learning, or the input and output space X×Y in the case of supervised and semi-supervised learning. In the last number of years the relaxation of this assumption has been explored and the importance of incorporation of additional information within machine learning algorithms became more apparent. Traditionally such fusion of information was the domain of semi-supervised learning. More recently the inclusion of knowledge from separate hypothetical spaces has been proposed by Vapnik as part of the supervised setting. In this work we are interested in exploring Vapnik’s idea of ‘master-class’ learning and the associated learning using ‘privileged’ information, however within the unsupervised setting.Adoption of the advanced supervised learning paradigm for the unsupervised setting instigates investigation into the difference between privileged and technical data. By means of our proposed aRi-MAX method stability of the K-Means algorithm is improved and identification of the best clustering solution is achieved on an artificial dataset. Subsequently an information theoretic dot product based algorithm called P-Dot is proposed. This method has the ability to utilize a wide variety of clustering techniques, individually or in combination, while fusing privileged and technical data for improved clustering. Application of the P-Dot method to the task of digit recognition confirms our findings in a real-world scenario.

Storm - A Novel Information Fusion and Cluster Interpretation Technique

Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporated into automatic analysis. Incorporation of expert knowledge is frequently a matter of combining multiple data sources from disparate hypothetical spaces. In cases where such spaces belong to different data types, this task becomes even more challenging. In this paper we present a novel immune-inspired method that enables the fusion of such disparate types of data for a specific set of problems. We show that our method provides a better visual understanding of one hypothetical space with the help of data from another hypothetical space. We believe that our model has implications for the field of exploratory data analysis and knowledge discovery.

Learning geographical information from hypothetical maps

People show biases or distortions in their geographical judgments, such as mistakenly judging Rome to be south of Chicago (the Chicago-Rome illusion). These errors may derive from either perceptual heuristics or categorical organization. However, previous work on geographic knowledge has generally examined people's judgments of real-world locations for which learning history is unknown. This article reports experiments on the learning of hypothetical geographical spaces, in which participants acquired information in a fashion designed to control real-world factors, such as variable travel experiences or stereotypes about other countries, as well as to mimic initial encounters with locations through reading or conventional school-based geography education. Five experiments combine to suggest that biases in judgment based on learning of this kind are different in key regards from those seen with real-world geography and may be based more on the use of perceptual heuristics than on categorical organization.

저빈도어를 고려한 개념학습 기반 의미 중의성 해소

This study proposes a Word Sense Disambiguation (WSD) algorithm, based on concept learning with special emphasis on statistically meaningful lowest frequency words. Previous works on WSD typically make use of frequency of collocation and its probability. Such probability based WSD approaches tend to ignore the lowest frequency words which could be meaningful in the context. In this paper, we show an algorithm to extract and make use of the meaningful lowest frequency words in WSD. Learning method is adopted from the Find-Specific algorithm of Mitchell (1997), according to which the search proceeds from the specific predefined hypothetical spaces to the general ones. In our model, this algorithm is used to find contexts with the most specific classifiers and then moves to the more general ones. We build up small seed data and apply those data to the relatively large test data. Following the algorithm in Yarowsky (1995), the classified test data are exhaustively included in the seed data, thus expanding the seed data. However, this might result in lots of noise in the seed data. Thus we introduce the "maximum a posterior hypothesis" based on the Bayes` assumption to validate the noise status of the new seed data. We use the Naive Bayes Classifier and prove that the application of Find-Specific algorithm enhances the correctness of WSD. (Korea University)

DEVELOPMENT OF A RAY TRACING COMPUTER MODEL FOR THE PREDICTION OF THE SOUND FIELD IN LONG ENCLOSURES

A ray tracing computer model, NORMAL, has been developed for predicting the sound field in any shaped enclosed space without curved surfaces, including long enclosures of rectangular cross-section. The model was developed specifically as a basis for the modelling of speech intelligibility in underground stations. The model predicts sound propagation throughout a space, and the impulse response at defined receiver points from which various acoustic parameters for the assessment of speech intelligibility can be calculated. This paper describes the way in which NORMAL models the space, receivers and sources, and the mathematics involved in tracing a ray and calculating the energy contributed to a receiver. The model has been tested in two hypothetical spaces to show that it is capable of predicting the characteristics of the sound fields that would be expected both in a diffuse space, and in a long, non-diffuse, enclosure. The reverberation time tail compensation, used to compensate for the loss of later reflections in the predicted energy decay curve, is described. The effects of including this compensation method on predicted reverberation time in diffuse and non-diffuse spaces are discussed, together with the feasibility of applying this correction method to long enclosures.