There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Using Multivariate Statistics

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Preface 1. Introduction Overview A Brief History of LMIs in Control Theory Notes on the Style of the Book Origin of the Book 2. Some Standard Problems Involving LMIs. Linear Matrix Inequalities Some Standard Problems Ellipsoid Algorithm Interior-Point Methods Strict and Nonstrict LMIs Miscellaneous Results on Matrix Inequalities Some LMI Problems with Analytic Solutions 3. Some Matrix Problems. Minimizing Condition Number by Scaling Minimizing Condition Number of a Positive-Definite Matrix Minimizing Norm by Scaling Rescaling a Matrix Positive-Definite Matrix Completion Problems Quadratic Approximation of a Polytopic Norm Ellipsoidal Approximation 4. Linear Differential Inclusions. Differential Inclusions Some Specific LDIs Nonlinear System Analysis via LDIs 5. Analysis of LDIs: State Properties. Quadratic Stability Invariant Ellipsoids 6. Analysis of LDIs: Input/Output Properties. Input-to-State Properties State-to-Output Properties Input-to-Output Properties 7. State-Feedback Synthesis for LDIs. Static State-Feedback Controllers State Properties Input-to-State Properties State-to-Output Properties Input-to-Output Properties Observer-Based Controllers for Nonlinear Systems 8. Lure and Multiplier Methods. Analysis of Lure Systems Integral Quadratic Constraints Multipliers for Systems with Unknown Parameters 9. Systems with Multiplicative Noise. Analysis of Systems with Multiplicative Noise State-Feedback Synthesis 10. Miscellaneous Problems. Optimization over an Affine Family of Linear Systems Analysis of Systems with LTI Perturbations Positive Orthant Stabilizability Linear Systems with Delays Interpolation Problems The Inverse Problem of Optimal Control System Realization Problems Multi-Criterion LQG Nonconvex Multi-Criterion Quadratic Problems Notation List of Acronyms Bibliography Index.

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Linear Matrix Inequalities in System and Control Theory

OBJECTIVE
To determine if participation in group sessions as part of health supervision visits for infants improves outcomes compared with individual visits in high-risk mothers.


STUDY DESIGN
Randomized controlled clinical trial.


PARTICIPANTS
Mothers of young infants who had at least 1 of the following risk factors: aged younger than 20 years at delivery, participation in Medicaid, less than a high school education, previous or ongoing substance abuse, or history of abuse as a child.


SETTING
Two urban university pediatric clinics in Seattle, Wash.


INTERVENTIONS
Mother-infant dyads were randomized to receive group well-child care (GWCC) or individual well-child care (IWCC) before the infant was 4 months old; the intervention continued until the child was 15 months old. Mothers completed the Sense of Competence and Social Isolation subscales from the Parenting Stress Index and Sarason's Social Support Questionnaire at enrollment and again on completion of the study. During the 11-month study period, 7 health supervision visits were scheduled for each mother-infant dyad. Social workers met periodically with mothers during the study and assessed the following functional outcomes: return to school, return to work, enrollment in a substance abuse treatment program, and becoming pregnant. In addition, data on study children were collected from Child Protective Services to assess referrals because of suspected abuse and/or neglect.


RESULTS
Data were collected on 213 mother-infant dyads, including 108 who received GWCC and 105 who received IWCC. At the conclusion of the study period, similar proportions of GWCC and IWCC mothers scored in the high-risk range on the Sense of Competence subscale, Social Isolation subscale, and the Social Support Questionnaire (P=.57, .32, and .59, respectively). For more than 50% of the mothers, scores on the Sense of Competence and Social Isolation subscales deteriorated during the study period from the not-high-risk range to the high-risk range, regardless of assignment to GWCC or IWCC. No differences were noted between GWCC and IWCC mothers for any functional outcome. During the study period, 8.8% of children receiving GWCC were referred to Child Protective Services vs 8.3% of those receiving IWCC (P=.85).


CONCLUSION
The format of well-child care may not be an important determinant of outcomes among high-risk mothers.

Group Well-Child Care for High-Risk Families

A Raman fiber amplifier providing small signal gain of over 30dB in the U-band has been demonstrated. In addition, we present a dual wavelength pumped Raman amplifier with broad flattened gain (ripple better than 1.5 dB) over the spectral range 1600-1670nm.

Dual wavelength pumped L- and U-band Raman amplifier

Chemically amplified photoresists are widely used throughout the semiconductor industry due to the need for high throughput in the lithography process. Knowledge of the location of acid molecules in chemically amplified resists is of paramount importance for the process control of the image formation of almost all the lithographic techniques used in the semiconductor industry today. We have demonstrated a technique based on pH-dependent fluorescence which can measure directly the spatial distribution of the photoacid in photoresist films without the need of any other subsequent process after exposure. By adding a small amount of fluorescent material to the resist, a latent image can be formed when photogenerated acid molecules quench the fluorescence in exposed areas. We demonstrate images formed after exposure of SAL605 resist films to x-ray radiation, with no post-exposure bake, and show that the optical contrast is a function of dose. We also show that the same technique can be utilized for rapid evalu...

Imaging of photogenerated acid in a chemically amplified photoresist

Two cases of syringomyelia and syringobulbia, observed clinically over many years, and examined pathologically

A diode-pumped ytterbium-erbium ‘figure of eight’ laser is stabilised by the inclusion of a bandwidth-limiting element inside the cavity. Transform limited solitons with durations of l.35ps are generated, continuously tunable over 20nm. Temporal stabilisation is imposed through amplified feedback of light reflected by the nonlinear loop mirror.

James Taylor

Papers

Group Well-Child Care for High-Risk Families

Dual wavelength pumped L- and U-band Raman amplifier

Imaging of photogenerated acid in a chemically amplified photoresist

Two cases of syringomyelia and syringobulbia, observed clinically over many years, and examined pathologically

Spectral and temporal stabilisation of a diode-pumped ytterbium-erbium fibre soliton laser