From: neuron-request@CATTELL.PSYCH.UPENN.EDU ("Neuron-Digest Moderator")
Newsgroups: comp.ai.neural-nets
Subject: Neuron Digest V10 #17
Date: 8 Nov 92 22:06:40 GMT
Reply-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu>
Distribution: world
Organization: University of Pennsylvania

Neuron Digest   Sunday,  8 Nov 1992
                Volume 10 : Issue 17

Today's Topics:
                     Stock market scam more like it
          Fellowship Position: Neural Computation in Neurology
   Clinical and Research Opportunities at the VA GRECC(Salt Lake City)
                     Lectures announcement (Belgium)
         New version of Self-Organizing Maps PD program package
                            Audio Synthesizer
                         NIPS*92 and CME travel
            Re: Hotel reservation deadline for NIPS workshops


Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are
available from cattell.psych.upenn.edu (130.91.68.31). Back issues
requested by mail will eventually be sent, but may take a while.

----------------------------------------------------------------------

Subject: Stock market scam more like it
From:    bradski@cns.bu.edu (Gary Bradski)
Date:    Sat, 07 Nov 92 21:44:41 -0500

[[ See Editor's Note at the end. ]]

I can't see how you let that "educational stock market game" through.
What if I send you something asking people for money for an
"educational" poker game where I'd be willing to give part of my take
(for running the game) to the winner?  A scam is a scam and you've
just helped facilitate one for 50 bucks a pop.  This belongs in
Atlantic City, not on the net.
                                                --Gary
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@   ---------------
Gary Bradski                  I'net: bradski@park.bu.edu       | reverberate |  
Cognitive and Neural Systems                                   ---------------
Boston University.                                                 |  V V
111 Cummington St, Boston MA 02215                                 ^   Y
617/ 353-6426                                                     ^ ^  | 
                                                               --------------
                                                               |   or die!  |
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@   --------------



[[ Editor's Note: Because of Gary's note, I reread last issues's
submission of the stock market game and completly agree with him.  I had,
in fact, completely missed the entry fee portion of the message; if I had
understood, I probably would not have accepted it for publication.  I
know of other "stock market games" which do not require entry fees and
had assumed this was similar.  As long-time readers know, I routinely
reject only two types of articles: Jobs *wanted* (i.e., resumes) and
blatantly commercial postings designed primarily for financial gain.  In
retrospect, the "stock market game" falls under the second category and
violates the non-commercial intent of the Internet.  I strongly recommend
Neuron Digest readers *not* participate. -PM ]]



------------------------------

Subject: Fellowship Position: Neural Computation in Neurology
From:    "James A. Reggia" <reggia@cs.UMD.EDU>
Date:    Tue, 03 Nov 92 12:36:59 -0500


    Research Training Fellowship in Neural Modelling Available
                  (MD Degree required)

The Clinical Stroke Research Center at the University of Maryland School 
of Medicine will offer two Junior Javits research fellowships starting 
July 1, 1993.   One of these positions provides research training in the
use of neural networks in cerebrovascular disease.   A clinical back-
ground (MD degree and specialization in neurology) is required.

The Fellowship is for two years and is research intensive, but would 
also usually involve some clinical work in the Stroke Center.  There is 
substantial flexibility in the details of the research training and
research work. The first year salary is anticipated to be $33,000 plus
fringe benefits.

To apply send a letter and curriculum vitae to
    Dr. Thomas Price
    Director, Clinical Stroke Research Center
    University of Maryland Hospital
    22 South Greene Street
    Baltimore, MD 21201

Questions about the research program can be sent to:
   Jim Reggia
   reggia@cs.umd.edu


------------------------------

Subject: Clinical and Research Opportunities at the VA GRECC(Salt Lake City)
From:    soller@asylum.cs.utah.edu (Jerome Soller)
Date:    Tue, 03 Nov 92 17:04:57 -0700

        Dear Neuron Digest:
        Please post our job notice for the Research  Investigator and 
clinical positions position at the VA GRECC(I apologize for the duplicate
posting of this message to comp.ai.neural-nets).  Some examples of
computer research projects at the VA GRECC in these areas include:
applications of neural networks to large database systems, application of
neural networks to prediction of heart disease(Charles Rosenberg),
integrated data collection environments using pen based computers(Steven
Fehlauer), Semantic Networks(Judith Graves), expert systems(Bayesian and
fuzzy logic varieties), etc.., to real problems in medicine and nursing.
Close ties exist between the GRECC and U. of Utah Departments of Internal
Medicine, Bioengineering, Computer Science, Psychology, Medical
Informatics, and Nursing Informatics.  Another separate VA center in
Utah(VA Regional Information Systems Center, one of 7 in the U.S.)
provides access to the VA's DHCP database, which is a standard database
for 172 VA hospitals.  Some examples of neurological work done in
cooperation with our group are Dustman and Emerson's work on the effect
of exercise on the cognition of elderly people.

                                        Sincerely,


                                Jerome Soller
                                Computer Research Engineer, VA GRECC
                                Ph.D. Candidate, U. of Utah 
                                Department of Computer Science
                                soller@cs.utah.edu


The Salt Lake City Geriatric Research, Education and Clinical Center
(GRECC) and the University of Utah School of Medicine are recruiting
individuals to join the VA/University program in Geriatric Internal
Medicine.  University faculty rank is dependent on qualifications.
Candidates must hold an M.D. and/or Ph.D. and have interest in one or
more of the following:

Clinical Geriatric Internal Medicine
Basic Biological Mechanisms of Aging
Computer-based Strategies for "Real-Time" Assistance in
the Delivery of Health Care

Appointments will be in the SLC VAMC GRECC and in the appropriate
University of Utah academic department.

Send curriculum vitae and bibliography to:

Gerald Rothstein, M.D.
SLC GRECC (182)
500 Foothill Blvd.
SLC, UT  84148

Closing date March 31, 1993 or until suitable candidates are identified.
Please call 801-582-1565 ext 4161 for further information.

The Department of Veterans Affairs and the University of Utah are AA/EEO
Employers.


C. Steven Fehlauer, M.D. (fehlauer@msscc.med.utah.edu)
GRECC Research Investigator
Assistant Professor of Medicine
University of Utah

Charles Rosenberg, Ph.D. (crr@cogsci.psych.utah.edu)
GRECC Research Investigator



------------------------------

Subject: Lectures announcement (Belgium)
From:    Laurence Leherte <LEHERTE%BNANDP11.BitNet@pucc.PRINCETON.EDU>
Date:    Wed, 04 Nov 92 10:14:46

                    Announcement:

A Series of Lectures in the field of Chemistry and Artificial
Intelligence will be held at the Facultes Universitaires Notre-Dame de la
Paix (Namur, Belgium), on November the 19th.

                *****************************
                *  MOLECULAR SCENE ANALYSIS *
                *****************************

    Janice Glasgow, Dept. of Computing and Information Science
             Queen's University, Kingston, Canada

       Frank H. Allen, Cambridge Structural Data Centre,
                      Cambridge, UK.

    Suzanne Fortier, Dept. of Chemistry, Queen's University,
             Queen's University, Kingston, Canada


   The concept of "scene analysis" has been used in the context of
machine vision to refer to the set of processes associated with the
classification and understanding of complex images. Such analyses rely on
the availibility of domain knowledge in the form of structural templates,
rules or heuristics to locate and identify features in a scene. By
analogy we use the phrase "molecular scene analysis" to refer to the
processes associated with the reconstruction and interpretation of
molecular structures and molecular interactions.  This presentation, in
three parts, will describe some fundamental aspects of the Molecular
Scene Analysis project.

Computational Imagery :  Janice Glasgow
- ---------------------------------------
   At the core of our knowledge-based approach to molecular
scene analysis is the concept of imagery, that is the ability to reason
with three-dimensional images of molecular structure.  To provide a
computational framework that can imitate the human visualization
abilities, we are designing image representations that make explicit the
fundamental spatial and visual charactersitics of a molecular scene.
Applying the computational reasoning techniques of molecular imagery to
the information accumulated in a crystallographic knowledge base provides
the "intelligence" vital to molecular scene analysis.

>From Databases to Knowledge Bases : Frank Allen
- -----------------------------------------------
   Full 2D chemical and 3D crystallographic (coordinate) data for
180,000 crystal structures are now held in computerized databases.
Geometric results derived from these data form the basis for the
systematic acquisition of chemical and structural knowledge.  This
knowledge may be expressed in terms of numerical values (e.g. typical
geometries), chemical and structural concepts (e.g. conformational
descriptors), or as algorithmic relationships (e.g. correlations between
parameters).  A variety of knowledge acquisition methods that can help
transform the crystallographic databases into knowledge bases will be
illustrated.

Conceptual Clustering Applications to Crystallographic Data :
- ----------------------------------------------------  Suzanne Fortier
                                                    -----------------
   Our research in machine learning is motivated by the need for
techniques to structure, manage and compress the rapidly growing
crystallographic databases and transform them into knowledge bases.  An
incremental conceptual clustering algorithm, specifically designed for
objects/scenes composed of many parts, has been designed and implemented.
The algorithm and an initial application to pyranose sugar data will be
described.


Location:      Facultes Universitaires Notre-Dame de la Paix
- ---------      Chemistry Department
               Auditorium CH2
               Rue Grafe, 2
               B-5000 NAMUR
               Belgium

Schedule:      November, the 19th, 1992
- ---------      15:00

Information:   Prof. D. P. Vercauteren
- ------------   Dr. L. Leherte
               E. Titeca
               Laboratoire de Physico-Chimie Informatique
               email:vercau,leherte,titeca at scf.fundp.ac.be
               Tel:+32-81-724534, +32-81-724535
               Fax:+32-81-724530
Acknowledge-To: <LEHERTE@BNANDP11>


------------------------------

Subject: New version of Self-Organizing Maps PD program package
From:    LVQ_PAK <lvq@cochlea.hut.fi>
Date:    Tue, 03 Nov 92 12:29:14 +0700

************************************************************************
*                                                                      *
*                              SOM_PAK                                 *
*                                                                      *
*                                The                                   *
*                                                                      *
*                        Self-Organizing Map                           *
*                                                                      *
*                          Program  Package                            *
*                                                                      *
*                   Version 1.2 (November 2, 1992)                     *
*                                                                      *
*                          Prepared by the                             *
*                    SOM Programming Team of the                       *
*                 Helsinki University of Technology                    *
*           Laboratory of Computer and Information Science             *
*                Rakentajanaukio 2 C, SF-02150 Espoo                   *
*                              FINLAND                                 *
*                                                                      *
*                         Copyright (c) 1992                           *
*                                                                      *
************************************************************************

Some time ago we released the software package "LVQ_PAK" for the easy
application of Learning Vector Quantization algorithms.  Corresponding
public-domain programs for the Self-Organizing Map (SOM) algorithms are
now available via anonymous FTP on the Internet.

"What does the Self-Organizing Map mean?", you may ask --- See the
following reference, then: Teuvo Kohonen. The self-organizing map.
Proceedings of the IEEE, 78(9):1464-1480, 1990.

In short, Self-Organizing Map (SOM) defines a 'non-linear projection' of
the probability density function of the high-dimensional input data onto
the two-dimensional display. SOM places a number of reference vectors
into an input data space to approximate to its data set in an ordered
fashion.

This package contains all the programs necessary for the application of
Self-Organizing Map algorithms in an arbitrary complex data visualization
task.

This code is distributed without charge on an "as is" basis.  There is no
warranty of any kind by the authors or by Helsinki University of
Technology.

In the implementation of the SOM programs we have tried to use as simple
code as possible. Therefore the programs are supposed to compile in
various machines without any specific modifications made on the code. All
programs have been written in ANSI C. The programs are available in two
archive formats, one for the UNIX-environment, the other for MS-DOS. Both
archives contain exactly the same files.

These files can be accessed via FTP as follows:

1. Create an FTP connection from wherever you are to machine
   "cochlea.hut.fi". The internet address of this machine is
   130.233.168.48, for those who need it.

2. Log in as user "anonymous" with your own e-mail address as password.  

3. Change remote directory to "/pub/som_pak". 

4. At this point FTP should be able to get a listing of files in this
   directory with DIR and fetch the ones you want with GET. (The exact 
   FTP commands you use depend on your local FTP program.) Remember 
   to use the binary transfer mode for compressed files.

The som_pak program package includes the following files:

  - Documentation:
      README             short description of the package 
                         and installation instructions
      som_doc.ps         documentation in (c) PostScript format
      som_doc.ps.Z       same as above but compressed
      som_doc.txt        documentation in ASCII format

  - Source file archives (which contain the documentation, too):
      som_p1r2.exe       Self-extracting MS-DOS archive file
      som_pak-1.2.tar    UNIX tape archive file
      som_pak-1.2.tar.Z  same as above but compressed


An example of FTP access is given below

unix> ftp cochlea.hut.fi (or 130.233.168.48)
Name: anonymous
Password: <your email address>
ftp> cd /pub/som_pak
ftp> binary
ftp> get som_pak-1.2.tar.Z
ftp> quit
unix> uncompress som_pak-1.2.tar.Z
unix> tar xvfo som_pak-1.2.tar

See file README for further installation instructions.

All comments concerning this package should be
addressed to som@cochlea.hut.fi.


------------------------------

Subject: Audio Synthesizer
From:    warthman@garnet.berkeley.edu
Date:    Thu, 05 Nov 92 17:54:17 -0800

[[ Editor's Note: Ah, neural nets in "mainstream" art. Could someone give
a few more (technical) details about the project? -PM ]]

********************** News Release ************************

November 5, 1992


************************************************************
Neural-Network Audio Synthesizer Debuts at Paris Opera House
************************************************************

Palo Alto, California -- The old Opera House in Paris, France, will
feature five performances by the Merce Cunningham Dance Company, November
12 to 17, in which a new type of audio synthesizer based on an artificial
neural network will be used to generate electronic music. The
synthesizer's musical accompaniment was composed and will be performed by
David Tudor and his dance company colleague, Takehisa Kosugi.

The audio synthesizer is built around an integrated-circuit chip from
Intel Corporation in Santa Clara, California. The chip, called the Intel
80170NX electrically trainable analog neural network (ETANN), simulates
the function of nerve cells in a biological brain.

A remarkable range of audio effects can be generated with the electronic
synthesizer -- from unique space-age and science-fiction sounds to
passages that sound very much like birds, heart beats, porpoises,
engines, and acoustical, percussion or string musical instruments. Sounds
are generated internally by the synthesizer. External inputs such as
voice, music, or random sounds can optionally be used to enrich or
control the internally generated sounds.  In addition to generating
outputs to multiple audio speakers, the synthesizer can simultaneously
drive oscilloscopes or other visual devices.

The neural network chip's software consists of numeric values
representing interconnection strengths between inputs and outputs -- a
configuration analogous to the excitatory or inhibitory strengths of
synapse connections between biological nerve cells. The artificial
neurons can be connected in loops, using the programmable interconnection
strengths, or they can be connected outside the chip with cables and
feedback circuits. Audio oscillations occur as a result of delay in the
feedback paths and thermal noise in the neural network chip. The sounds
are generally rich because of the complexity of the circuitry.

The concept for the synthesizer evolved from a project begun in 1989 by
Forrest Warthman and David Tudor. The synthesizer was designed and built
by Warthman; Mark Thorson, a hardware designer and associate editor of
Microprocessor Report; and Mark Holler, Intel's program manager for
neural network products.

John Cage visited the design group in Palo Alto a few months before his
passing away at the age of 79 this year. His observations on the
synthesizer's role in musical composition and dance performance
contributed to its current design.

A description of the synthesizer's architecture and circuitry will appear
in the February 1993 issue of Dr.  Dobb's Journal.


------------------------------

Subject: NIPS*92 and CME travel
From:    Steve Hanson <jose@tractatus.siemens.com>
Date:    Thu, 05 Nov 92 10:05:59 -0500

NIPS*92 Goers: This is a annoucement will we try and send out to you in
the next week, but the date is so tight that I am sending it on the Net
first.  Please repost and send to your NIPS colleagues.  Thanks.

Steve Hanson
NIPS*92 General Chair 

CME Travel   (big mountain picture in background)

INVITATION TO ROCKIES:

On behalf of the NIPS Conference Coordinators, CME and CME Travel would
like to welcome you to the Vail Valley.  Your organization has selected
Colorado Mountain Express to assit with your travel needs while attending
the NEURAL INFORMATION PROCESSING SYSTEMS WORKSHOP at the Radissson
Resort in Vail Colorado, December 2-5, 1992.  In an effort to provide the
most economic and professional service, speical discounted airfare and
ground transportation rates have been negotiated to fly you into Denver
and transfer you on December 3 at 1:30pm from Marriott's City Center
Hotel to the Radisson in Vail and return you back to Denver Stapleton
Airport upon your requested departure.

Colorado Mountain Express located in the VAil Valley, has been serving
the Vail and Beaver Creek Resort since 1983.  Your speical group code
"NIPS" not only provides you access to SPECIAL AIRLINE FARES, negotiaed
on your behalf but also makes available preferred gound transfer rates
with Colorado Mountona Express or Hertz Car Rental.


                 ***NIPS***
         Special Group Code

 ******Preferred Airline Contracts******

******Discounted Ground Transportation****
via Colorado Mountain Express or Hertz Car
Rental


                1-800-525-6363


RSVP by NOVEMBER 18, 1992


We look forward to coordinating your travel arrangements.  Please contact
a CME travel Consultant at ext 6100 no later than Nov. 18th to secure
your travel plans.

                        Sincerely,
                        
                        Colorado Mountain Express
              & CME Travel




Stephen J. Hanson
Learning Systems Department
SIEMENS Research 
755 College Rd. East
Princeton, NJ 08540



------------------------------

Subject: Re: Hotel reservation deadline for NIPS workshops
From:    Steve Hanson <jose@tractatus.siemens.com>
Date:    Mon, 02 Nov 92 09:22:14 -0500

Note that in the last 6 months that

Mariott MARK Resort has been purchased by the Radisson and is now Called
Radisson Vail Resort (same place, same facilties). If you have gotten
reservations at the Mariott MARK Resort during this time under the
NIPS*92 group, they will be honored by the Radisson.

Everyone else who has yet to reserve a room at Vail, should call the
Radisson as Gerry suggests ASAP.

Steve
NIPS*92 General Chair


Stephen J. Hanson
Learning Systems Department
SIEMENS Research 
755 College Rd. East
Princeton, NJ 08540



------------------------------

End of Neuron Digest [Volume 10 Issue 17]
*****************************************
Newsgroups: comp.ai.nlang-know-rep