The
9th
ACIS/IEEE
International
Conference
on
Computer
Science
and
Information
Science,
held
in
Kaminoyama,
Japan
on
August
18-20
is
aimed
at
bringing
together
researchers
and
scientists,
businessmen
and
entrepreneurs,
teachers
and
students
to
discuss
the
numerous
fields
of
computer
science,
and
to
share
ideas
and
information
in
a
meaningful
way.
This
publication
captures
18
of
the
conference’s
most
promising
papers,
and
we
impatiently
await
the
important
contributions
that
we
know
these
authors
will
bring
to
the
?eld.
In
chapter
1,
Taewan
Gu
et
al.
propose
a
method
of
software
reliability
estimation
based
on
IEEE
Std.
1633
which
is
adaptive
in
the
face
of
frequent
changes
to
software
requirements,
and
show
why
the
adaptive
approach
is
necessary
when
software
requirements
are
changed
frequently
through
a
case
study.
In
chapter
2,
Keisuke
Matsuno
et
al.
investigate
the
capacity
of
incremental
learning
in
chaotic
neural
networks,
varying
both
the
refractory
parameter
and
the
learning
parameter
with
network
size.
This
approach
is
investigated
through
simulations,
which
?nd
that
capacity
can
be
increased
in
greater
than
direct
proportion
to
size.
In
chapter
3,
Hongwei
Zeng
and
Huaikou
Miao
extend
the
classical
labeled
transition
system
models
to
make
both
abstraction
and
compositional
reasoning
applicable
to
deadlock
detection
for
parallel
composition
of
components,
and
propose
a
compositional
abstraction
re?nement
n/a
9th
ACIS/IEEE
International
Conference
on
Computer
Science
and
Information
Science,
held
in
Kaminoyama,
Japan
on
August
18-20
is
aimed
at
bringing
together
researchers
and
scientists,
businessmen
and
entrepreneurs,
teachers
and
students
to
discuss
the
numerous
fields
of
computer
science,
and
to
share
ideas
and
information
in
a
meaningful
way.
This
publication
captures
18
of
the
conference’s
most
promising
papers,
and
we
impatiently
await
the
important
contributions
that
we
know
these
authors
will
bring
to
the
?eld.
In
chapter
1,
Taewan
Gu
et
al.
propose
a
method
of
software
reliability
estimation
based
on
IEEE
Std.
1633
which
is
adaptive
in
the
face
of
frequent
changes
to
software
requirements,
and
show
why
the
adaptive
approach
is
necessary
when
software
requirements
are
changed
frequently
through
a
case
study.
In
chapter
2,
Keisuke
Matsuno
et
al.
investigate
the
capacity
of
incremental
learning
in
chaotic
neural
networks,
varying
both
the
refractory
parameter
and
the
learning
parameter
with
network
size.
This
approach
is
investigated
through
simulations,
which
?nd
that
capacity
can
be
increased
in
greater
than
direct
proportion
to
size.
In
chapter
3,
Hongwei
Zeng
and
Huaikou
Miao
extend
the
classical
labeled
transition
system
models
to
make
both
abstraction
and
compositional
reasoning
applicable
to
deadlock
detection
for
parallel
composition
of
components,
and
propose
a
compositional
abstraction
re?nement
approach.
Textul de pe ultima coperta
The
purpose
of
the
9th
IEEE/ACIS
International
Conference
on
Computer
and
Information
Science
(ICIS
2010)
was
held
on
August
18-20,
2010
in
Kaminoyama,
Japan
is
to
bring
together
scientist,
engineers,
computer
users,
students
to
share
their
experiences
and
exchange
new
ideas,
and
research
results
about
all
aspects
(theory,
applications
and
tools)
of
computer
and
information
science,
and
to
discuss
the
practical
challenges
encountered
along
the
way
and
the
solutions
adopted
to
solve
themThe
conference
organizers
selected
the
best
18
papers
from
those
papers
accepted
for
presentation
at
the
conference
in
order
to
publish
them
in
this
volume.
The
papers
were
chosen
based
on
review
scores
submitted
by
members
of
the
program
committee,
and
underwent
further
rigorous
rounds
of
review.
