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An exquisitely illustrated introduction to the gestural mark in the designed world, exploring the tension between marks, which are felt, and images and words, which are conceptual. In The Hidden Factor, Steven Skaggs provides a beautifully illustrated and explained introduction to the mark—from those as physical as a scratch made by an animal, to those as accidental as a splatter of paint, to those as intentional as hand-drawn characters. Skaggs makes the case that, in the visual arts, gestures and mark-making operate on an equal level with image and word. While we might think of content as that which is communicated through text and images, Skaggs shows, through visual examples, that the gestural mark is often hidden within both images and the typographic forms that convey words. By mapping different kinds of marks and showing how marks combine with image and word, The Hidden Factor explains that our desire for conceptual information suppresses our awareness of marking. This is especially the case with the tension between word and mark, where we desire legibility. As a result, one of the most conservative of arts—calligraphy—has the potential of being the most radical, since gesturally expressive handwriting is a natural threat to the legibility of a text. Filled with expressive calligraphic art, graffiti, and other gorgeous marks, The Hidden Factor is an eye-opening read that brings to the fore the importance—and indeed, the prevalence—of the mark in everything we see.
Discusses in the practical and theoretical aspects of one-period asset allocation, i.e. market Modeling, invariants estimation, portfolia evaluation, and portfolio optimization in the prexence of estimation risk The book is software based, many of the exercises simulate in Matlab the solution to practical problems and can be downloaded from the book's web-site
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
Originally published in 1984, this is a classic in its field. Not only is it the first book to promote reading the cards for your own insight, but it also shows you exactly how to do so. It revolutionizes learning Tarot through a combined emphasis on self-teaching techniques and personal insight. Never before has a Tarot book so comprehensively linked the many areas of New Age thought. You will find journal writing, mythology, psychology, self-help, relationships, prosperity and right livelihood, crystals, channeling, astrology, numerology, poetry, art, and occult metaphysics--all explored and integrated with the Tarot. This revised edition features: Expanded interpretations for the Minor Arcana. Reversed card meanings for all 78 cards. An entirely new history-based appendix on the latest research and discoveries. Information on your Shadow/Teacher cards. A new introduction. An updated bibliography. Tarot for Your Self uses meditations, rituals, spreads, mandalas, visualizations, dialogues, charts, affirmations, and other activities to help you establish your own relationship with the cards. All the information is presented using the best in traditional knowledge and know-how. This powerful breakthrough process will turn all your readings into truly transformative experiences.
The tarot classic that first promoted the practice of reading the cards not just for others but for one's own personal insight and self-transformation “Tarot for Your Self was ground-breaking when this book was first published and is still radically significant today.” —Benebell Wen, author of Holistic Tarot “Deciding to work with the Tarot is like embarking on a long, inward journey.”—Mary K. Greer This tarot classic by Mary K. Greer was the first book to promote reading the cards for your own insight, revolutionizing tarot through a combined emphasis on self-teaching techniques and personal growth. Tarot for Your Self uses meditations, rituals, spreads, mandalas, visualizations, dialogues, charts, affirmations, and other activities to help you establish your own relationship with the cards. All the information is presented using the best in traditional knowledge and know-how. This powerful breakthrough process will turn all your readings into truly transformative experiences. Tarot for Your Self covers interpretations for the major and minor arcana, reversed card meanings for all 78 cards, and enlightening information on your shadow/teacher cards.
"The tarot cards associated with your birth date and name form a pattern of personal destiny. They describe the theme of your life -- the challenges and the gifts. In Archetypal Tarot, tarot scholar and teacher Mary K. Greer connects astrology and numerology to the tarot to create an in-depth personality profile that can be used for self-realization and personal harmony." --
Analyzing Event Statistics in Corporate Finance provides new alternative methodologies to increase accuracy when performing statistical tests for event studies within corporate finance. In contrast to conventional surveys or literature reviews, Jeng focuses on various methodological defects or deficiencies that lead to inaccurate empirical results, which ultimately produce bad corporate policies. This work discusses the issues of data collection and structure, the recursive smoothing for systematic components in excess returns, the choices of event windows, different time horizons for the events, and the consequences of applications of different methodologies. In providing improvement for event studies in corporate finance, and based on the fact that changes in parameters for financial time series are common knowledge, a new alternative methodology is developed to extend the conventional analysis to more robust arguments.
X Table of Contents Table of Contents XI XII Table of Contents Table of Contents XIII XIV Table of Contents Table of Contents XV XVI Table of Contents K.S. Leung, L.-W. Chan, and H. Meng (Eds.): IDEAL 2000, LNCS 1983, pp. 3›8, 2000. Springer-Verlag Berlin Heidelberg 2000 4 J. Sinkkonen and S. Kaski Clustering by Similarity in an Auxiliary Space 5 6 J. Sinkkonen and S. Kaski Clustering by Similarity in an Auxiliary Space 7 0.6 1.5 0.4 1 0.2 0.5 0 0 10 100 1000 10000 10 100 1000 Mutual information (bits) Mutual information (bits) 8 J. Sinkkonen and S. Kaski 20 10 0 0.1 0.3 0.5 0.7 Mutual information (mbits) Analyses on the Generalised Lotto-Type Competitive Learning Andrew Luk St B&P Neural Investments Pty Limited, Australia Abstract, In generalised lotto-type competitive learning algorithm more than one winner exist. The winners are divided into a number of tiers (or divisions), with each tier being rewarded differently. All the losers are penalised (which can be equally or differently). In order to study the various properties of the generalised lotto-type competitive learning, a set of equations, which governs its operations, is formulated. This is then used to analyse the stability and other dynamic properties of the generalised lotto-type competitive learning.