Shelia Guberman (born 25 February 1930, Ukraine, USSR) is a scientist in computer science, nuclear physics, geology, geophysics, medicine, artificial intelligence and perception. He proposed the D-waves theory of Earth seismicity,cf. Guberman, Sh. A. (1979) D Waves and Earthquakes. Theory and Analysis of Seismological Observations. Computational Seismology, Vol. 12. Nauka, Moscow, transl. Allerton Press, pp. 158-188; D-waves and earthquake forecasting, Computational Seismology, Vol. 13. Nauka, Moscow, transl. Allerton Press, pp. 22-27. algorithms of Gestalt-perception (1980) and Image segmentation, and programs for the technology of oil and gas fields exploration (1985).
Life and career He is the son of Aizik Guberman (writer, poet) and his wife Etya (teacher). From 1947 to 1952 Guberman studied at the Institute of Electrical Communications, Odessa, USSR, graduating in radio engineering. From 1952 to 1958 he worked as field geophysicist in the Soviet oil industry. From 1958 to 1961 he studied as a postgraduate at the Oil and Gas Institute in Moscow. In 1962 he received a PhD. in nuclear physics, followed by a PhD. in applied mathematics in 1971. In 1971 he was appointed for full professorship in computer science. After authoring the first applied pattern recognition program in 1962, Guberman specialized in artificial intelligence implementing principles of Gestalt perception in computer programs for geological data analysis. In 1966 he was invited by the outstanding mathematician of the XX century Prof. Israel Gelfand to lead the Artificial Intelligence team in Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences. He applied the pattern recognition technology to earthquake prediction, oil and gas exploration, handwriting recognition, speech compression, and medical imaging. From 1989 to 1992 Guberman held the chair professorship at Moscow Open University (Department of Geography). Since 1992 he is living in the US. Guberman is the inventor of the handwriting recognition technology implemented in the commercial product by the company "Paragraph International" founded by Stepan Pachikov, and used today by Microsoft in Windows CE.cf. In-Q-Tel communication, June 3, 2003 He is author of core technologies for five US companies, and owns a patent on speech compression.
Achievements Handwriting recognition The common approach to computer handwriting recognition was computer learning on a set of examples (characters or words) presented as visual objects. Guberman proposed that it is more adequate for the psycho-physiology of human perception to present the script as a kinematic object, a gesture, i.e. synergy of movements of the stylus producing the script.Guberman, S., Rosenzweig V., The algorithm for recognizing handwritten texts. Avtomatika iTelemekhanika (Automation and Telemechanics), 1976, No. 5, 122-129. The handwriting consists of 7 primitives. The variations, which characters undergo during the writing, are restricted by the rule: each element can be transformed only into his neighbor in the ordered sequence of primitives. During the evolution of Latin-like writing acquired resistance to natural variations in character shape: when one of the primitives is substituted by his neighbor the interpretation of the character does not change to another one. Based on this approach two USA companies and Parascript developed the first commercial products for on-line and off-line free handwriting recognition, which were licensed by Apple, Microsoft, Boeing, Siemens and others.Dzuba G. et al (1997) Check Amount Validation of Courtesy and Legal Amount Fields. IJPRAI 11(4): 639-655. "Most commercially available natural handwriting software is based on ParaGraph or Parascript technology".Fakhr M. On-line handwriting recognition. 2011. Arab Academy for Science, Technical Report
The hypothesis that humans perceive the handwriting as well as other linear drawings (in general – the communication signals) not in visual modality but in the motor modality was later confirmed by the discovery of mirror neurons. The difference is that in the classical mirroring phenomena the motor response appears in parallel with the observed movement ("immediate action perception"), and during the handwriting recognition the static stimulus is transformed into a time process by tracing the path of the pen on the paper. In both cases the observer is trying to understand the intention of the correspondent: "the understanding of what the person is doing and why he is doing it, is acquired through a mechanism that directly transforms visual information into a motor format".Rizzolatti G, Fabbri-Destro M. Mirror neurons: From discovery to autism. Exp Brain Res (2010) 200:223–237 DOI 10.1007/s00221-009-2002-3
Speech parallel coding The speech is traditionally presented as a time sequence of phonemes - vowels and consonants. Each vowel is mainly determined by the relationship between the volume sizes of the front and the back of the voice tract. The ratio is defined by 1) horizontal position of tongue (back–forth), 2) the position of the lips (back-forth), and 3) the size of pharynx that can extend the cavity of the voice tract far back. Most consonants can be described with 3 parameters: 1) place of articulation (lips, teeth and so on), 2) time pattern of interaction with the voice tract (explosive or not), and 3) voiced or not voiced sound. Because of the inertia of the articulatory organs (tongue, lips, jaw) any phoneme interferes with the neighbors and changes its sounding (co-articulation). As a result, each phoneme sounds different in different context. Guberman presents the parallel model of speech production.Guberman S. and Andreevsky E.., 1996, from Language pathology to Automatic Language Recognition ... and Return. Cybernetics and Human Knowing, 3, 41–53. It states that vowels and consonants are generated not in sequence but in parallel. The two channels manage two different gropes of muscles, which together define the geometry of the voice tract, and, respectively, voice signal. The separation is possible because the generation of vowels and of consonants involves different muscles. For the vowels [o], [u] the lips are managed by muscles Mentalis and Orbicularis Oris for protrusion and rounding, and for [i], [e] by Buccinator and Risorius for retracting the lips. The tongue participate in creating the vowels by innervating Superior Longitudinal and Vertical for lifting and for moving the whole tongue back and forth, and Genioglossus for all consonants articulated in the front of the mouth )when jaw is fixed). For the lip consonant [p], [b], [v], [f] the lips are managed by Labii Inferioris and Orbicularis Oris muscles for moving the lips and the jaw up and down, and Zygomaticus Minor for moving the lower lip back for [v], [f]. From the hypothesis of Parallel Phonetic Coding follows: 1. Because the vowels are defined as a particular ratio of front and back volumes of voice tract, the vowels are present at any moment of the speech (even during silence – the neutral vowel [ə] when no muscle of the voice tract is innervated). 2. Any consonant in speech appears on the background of a vowel. The last consonant in the word, is pronounced on the background of the neutral vowel [ə]. In clusters the consonants are produced in parallel with [ə] except the last one. In the past in Russian writing after consonant at the end of the word has to be written a special character denoting the neutral vowel – Ъ (the rule was canceled in 1918). 3. The correct written code for words soda and word is shown in (N) where the number of vowels in syllable reflects the relative duration of the vowel. Such coding is used in Hebrew: in the word יצֵירֵ (peace) two points under characters denote vowel [e]). In Arabic the two channels carry different functions: the consonant stream keeps the meaning, (the root), and the vowel stream either modify the meaning of the root, or expresses a grammatical category: kitab means "book"; katib "writer"; ia-ktub-u "he is writing"; ma-ktab "school".
Giant oil/gas fields exploration In the '70s and '80s Guberman developed an artificial intelligence software and the appropriate technology for geological applications, and used it for predicting places of giant oil/gas deposits.Guberman S., Izvekova M., Holin A., Hurgin Y., Solving geophysical problems by mean of pattern recognition algorithm, Doklady of the Acad. of Sciens. of USSR 154 (5), (1964).Gelfand, I.M., et al. Pattern recognition applied to earthquake epicenters in California. Phys. Earth and Planet. Inter., 1976, 11: 227–283.Guberman S. (2008) Unorthodox geology and geophysics. Polimetrica, MilanoRantsman E, Glasko M (2004) Morphostructural knots–the sites of extreme natural events. Media-Press, Moscow. In 1986 the team published a prognostic map for discovering giant oil and gas fields at the Andes in South AmericaS. Guberman, M. Zhidkov, Y. Pikovsky, E. Rantsman (1986). Some criteria of oil and gas potential of morphostructural nodes in the Andes, South America. Doklady of the USSR Academy of Sciences, Earth Science Sections, 291. based on abiogenic petroleum origin theory. The model proposed by Prof. Yury Pikovsky (Moscow State University) assumes that petroleum moves from the mantel to the surface through permeable channels created at the intersection of deep faults.Pikovsky Y. Natural and Technogenic Flows of Hydrocarbons in the Environment. Moscow University Publishing, 1993 The technology uses 1) maps of morphostructural zoning (method proposed and developed by Prof. E.Rantsman), which outlines the morphostructural nodes (intersections of faults), and 2) pattern recognition program that identify nodes containing giant oil/gas fields. It was forecasted that eleven nodes, which had not been developed at that time, contain giant oil or gas fields. These 11 sites covered only 8% of the total area of all the Andes basins. 30 years later (in 2018) was published the result of comparing the prognosis and the reality. Since publication of the prognostic map in 1986, only six giant oil/gas fields were discovered in the Andes region: Cano–Limon, Cusiana, Capiagua, and Volcanera (Llanos basin, Colombia), Camisea (Ukayali basin, Peru), and Incahuasi (Chaco basin, Bolivia). All discoveries were made in places shown on the 1986 prognostic map as promising areas.
The result is convincingly positive, and this is a strong contribution in support of abiogenic theory of oil origin.
D-waves theory In the middle of the 20th century, the attention of seismologists was attracted by the phenomenon of chains of earthquakes consistently arising along big faults.Mogi K. Migration of seismic activity. Bull. EarthquakeRes.Inst., 46, 53, 1968.Wood M.D. and Allen S.S. Nature,244, 5413, 1973. Later it was interpreted as waves of tectonic strainE. V. Vilkovich, Sh. A. Guberman, and V. I. Keilis-Borok, Tectonic strain waves along large faults. Dokl. Akad. Nauk SSSR 219(1), 77 (1974). K. Mogi, Bull. Earthquake Res. Inst. 46, 53 (1968). In 1975 Guberman proposed the D-waves theory that separates the local processes of stress accumulation and the triggering of earthquakes.Guberman, Sh A. "On some regularities of the occurrence of earthquakes." Doklady Akademii Nauk. Vol. 224. No. 3. Russian Academy of Sciences, 1975. The basic postulates of this theory are: a) a strong earthquake changes the distribution of mass in the Earth's core and accordingly its rate of rotation ω; b) at times when ω reaches a local minimum the disturbances occur at both poles, which propagate along meridians at a constant rate of 0.15°/year (D waves); c) A strong earthquake occurs at the place where tectonic stresses have accumulated, and at a time when two D waves (from poles N and S) have met at that point. (Fig ). This hypothesis and its consequences were supported by seismological data.