1,456 research outputs found

    No.449 Jerald and Sandra Tanner

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    Transcript (97 pages) of interview(s) by Stan Larson and George D. Smith with Jerald and Sandra Tanner on April 2, 1997Jerald (1938-2006) and Sandra Tanner discuss their early experiences in the Church of Jesus Christ of Latter-day Saints, their meeting and marriage, and the events leading to requesting their names be removed from church membership rolls. Other topics include Modern Microfilm Company (later changed to Utah Lighthouse Ministry), doctrinal questions, Mark Hofmann, and researching Mormon history. Interviewers: Stan Larson and George D. Smit

    Jerald Bracken

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    Jerald Bracken is the son of Duane and Beulah Bracken of Roosevelt

    Jerald Atwood

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    Jerald D. Atwood is pictured his school year at Central Elementary. He is the son of Lawrence and Gladys Atwood. He served in the U.S. Air Force. He married Anna Faye Buttars. He was born April 22, 1933 and died March 25, 1985

    Jerald LaVern Hatch

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    Jerald LaVern Hatch is the son of Monroe and Sarah Hatch. He married Gail Glines in 1934 and died November 13, 1985

    Fort Worth artist Dickson Reeder, Billie Jerald and Sallie Gillespie

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    Fort Worth artist Dickson Reeder and his model, Billie Jerald, center. At right is Miss Sallie Gillespie stand around a portrait just completed by Mr. Reeder of Ms. Jerald. The painting was made during the Junior League\u27s art program held in the Fort Wort Art Association\u27s gallery in the Fort Worth Public Library. Sallie Gillespie gave a lecture. The audience was over one hundred sixth grade students from W. J. Turner and Diamond Hill schools. Mr. Reeder stands on the left in this photograph, holding an artist\u27s pallet. Next to him on an easel is the just completed portrait of Ms. Jerald. Ms. Jerald is seated between the painting and Sallie Gillespie, who is standing. This photograph was published in the October 2, 1941 morning edition of the Star-Telegram.https://mavmatrix.uta.edu/specialcollections_startelegram1940s/10299/thumbnail.jp

    Data for: Optimizing one-dimensional TiO2 for photocatalytic hydrogen production from a water-ethanol mixture and other electron donors

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    Data set for the following work:Optimizing one-dimensional TiO2 for photocatalytic hydrogen production from a water-ethanol mixture and other electron donors by Tao Peng, Jian Zhang, Srimanta Ray, Fatemeh Saadat Ghareh Bagh, Houssam Fakhouri, Farzaneh Arefi-Khonsari, Jerald A. Lalman. Submitted to Journal of Chemical Environmental Engineering

    Jerald and Sandra Tanner, \u3ci\u3eArchaeology and the Book of Mormon.\u3c/i\u3e

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    Review of Archaeology and the Book of Mormon (1972), by Jerald Tanner and Sandra Tanne

    A 1.83 μJ/Classification, 8-Channel, Patient-Specific Epileptic Seizure Classification SoC Using a Non-Linear Support Vector Machine

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    A non-linear support vector machine (NLSVM) seizure classification SoC with 8-channel EEG data acquisition and storage for epileptic patients is presented. The proposed SoC is the first work in literature that integrates a feature extraction (FE) engine, patient specific hardware-efficient NLSVM classification engine, 96 KB SRAM for EEG data storage and low-noise, high dynamic range readout circuits. To achieve on-chip integration of the NLSVM classification engine with minimum area and energy consumption, the FE engine utilizes time division multiplexing (TDM)-BPF architecture. The implemented log-linear Gaussian basis function (LL-GBF) NLSVM classifier exploits the linearization to achieve energy consumption of 0.39 mu J/operation and reduces the area by 28.2% compared to conventional GBF implementation. The readout circuits incorporate a chopper-stabilized DC servo loop to minimize the noise level elevation and achieve noise RTI of 0.81 mu. V-rms for 0.5-100 Hz bandwidth with an NEF of 4.0. The 5 x 5 mm(2) SoC is implemented in a 0.18 mu m 1P6M CMOS process consuming 1.83 /./ J/classification for 8-channel operation. SoC verification has been done with the Children's Hospital Boston-MIT EEG database, as well as with a specific rapid eye-blink pattern detection test, which results in an average detection rate, average false alarm rate and latency of 95.1%, 0.94% (0.27 false alarms/hour) and 2 s, respectively.N

    A 16-channel, 1-second latency patient-specific seizure onset and termination detection processor with dual detector architecture and digital hysteresis

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    This paper presents an area-power-efficient 16 channel seizure onset and termination detection processor with patient-specific machine learning techniques. This is the first work in literature to report an on-chip classification to detect both start and end of seizure event simultaneously with high accuracy. Frequency-Time Division Multiplexing (FTDM) filter architecture and Dual-Detector Architecture (D(2)A) is proposed, implemented and verified. The D(2)A incorporates two area efficient Linear Support Vector Machine (LSVM) classifiers along with digital hysteresis to achieve a high sensitivity and specificity of 95.7% and 98%, respectively, using CHB-MIT EEG database [1], with a small latency of is. The overall energy efficiency is measured as 1.85 mu J/Classification at 16-channel mode.N
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