Channel length assisted symbol synchronization for OFDM systems in multipath fading channels Despite the promising role of orthogonal frequency-division multiplexing (OFDM) technology in communication systems, its synchronization in multipath fading channels remains an important and challenging issue. This work describes a novel synchronization algorithm that exploits channel length information for use in OFDM systems. A timing function that can identify the ISI-free region and subsequently the channel length is also developed based on both the redundancy of the cyclic prefix (CP), and the drastic increase in intersymbol interference (ISI) that rises with symbol timing error in multipath fading channels. Knowledge of the channel length information allows the symbol timing to be safely set in the middle of the ISI-free region, without any ISI. Simulation results indicate that the maximum value of the timing function occurs at the correct timing offset when the signal-to-noise ratio (SNR) is high. From low-to medium SNRs, the correct timing offset is guaranteed when the signal power induced by the channel tap is more significant than the noise power. Furthermore, an efficient search algorithm is derived to reduce the search complexity (search time and computation complexity). Orthogonal frequency-division multiplexing (OFDM) is a promising technology for broadband transmission. However, OFDM systems are sensitive to synchronization errors that may destroy the orthogonality among all sub-carriers. Accordingly, intercarrier interference (ICI) and intersymbol interference (ISI) are introduced by synchronization errors [1] [2] [3] [4] . First, the uncertain OFDM symbol arrival time introduces a symbol timing offset, which is estimated by the coarse symbol timing offset [5] and fine symbol timing offset [6, 7] . Second, the mismatch between the carrier frequencies of the oscillators of the transmitter and the receiver generates a carrier frequency offset (CFO), necessitating the elimination of the resulting fractional CFO [5] , integral CFO [8, 9] , and residual CFO [6, 7] . Moreover, the mismatch between the sampling clocks of the digital-to-analog converter (DAC) and the analog-to-digital converter (ADC) introduces a sampling clock frequency offset [7] .. The estimation of symbol timing is essential to the overall OFDM synchronization process, because a poor estimate of symbol timing severely degrades the signalto-interference-and-noise ratio (SINR) [2, 7] . Besides ISI, extra ICI is also introduced owing to a loss of orthogonality. The symbol timing is estimated to identify the correct starting position of the OFDM symbol for the fast Fourier transform (FFT) operation. The timing offset is assumed to be an integer and may be set anywhere within an OFDM symbol.. Synchronization algorithms have been extensively reported for OFDM. A good survey can be found in [10] . Some works are briefly described here. Specially designed training preambles in [6, 11] can be used for symbol synchronization. Although an accurate estimate can be made, the bandwidth efficiency is reduced by adding a preamble. To eliminate such a reduction, algorithms that use the redundancy of the cyclic prefix (CP) have been developed [5, [12] [13] [14] [15] [16] [17] . The symbol synchronization algorithm [5] adopts the maximum-likelihood (ML) approach. However, being assumed in additive white Gaussian noise (AWGN) channels, the algorithm estimates the center of mass of the channel intensity profile rather than locating the first arriving path when used in multipath channels. One work [12] carries out coarse symbol timing synchronization in multipath channels, utilizing a correlation length that equals the summation of the channel and CP lengths. To make the algorithm more practical for synchronization, the simplified algorithm in [12] uses the correlation length that is equivalent to twice the CP length, subsequently degrading the performance. Despite the ability to identify the ISI-free region in multipath channels, an approach in that work [13] may require many symbols to obtain an accurate symbol timing estimate. The computation complexity of the rank method in another study [14] is high and can be incorporated in continuous-transmission networks. Yet, the performance of another method [15] may be disturbed by the CFO. A discrete stochastic approximation algorithm (DSA) for adaptive time synchronization has been developed in [16] . A related work [17] describes a maximum-likelihood (ML) approach. Although ML estimation methods produce better performance than ad hoc algorithms and can perform close to the theoretical Cramér-Rao lower bound (CRLB) on the mean square error, and their complexity is typically considered to be very high. Other works [18, 19] use either (blind) data [18] or frequency-domain pilots [19] .. Conventional CP-based timing synchronization schemes may underper-form preamble-based ones. Despite the repeated structure in CP, its correlation cannot be designed to resemble the impulse shape of training symbols. Therefore, the complexity of CP-based synchronization should be considerably increased to enhance its performance; otherwise, training symbols that can reduce the bandwidth efficiency should be used. This work thus develops a new synchronization scheme (considering multipath channels) having comparable complexity (~O(N)) to that of the simplest approach in [5] (considering AWGN channels), where N denotes the number of subcarriers. As is well known, the channel length is related to the best symbol timing. However, this information is seldom used in literature. Conversely, to enhance the performance of symbol synchronization, the channel length is used explicitly in this work.. This work presents a new synchronization algorithm, assisted by channel length information, for OFDM systems based on the redundancy of CP. ISI significantly increases with symbol timing error in multipath fading channels [1, 2] . Due to the characteristics of ISI, a new timing function, whose value is proportional to the interference, is developed. Of priority concern is how to locate the symbol timing estimate in the middle of the ISI-free region, because SINR of the received signals includes no penalty in this region. The proposed approach increases the robustness of the proposed algorithm because only phase rotation is introduced in the ISI-free region, which can be simply compensated by using a single-tap equalizer. Simulation results demonstrate that the maximum value of this function is at the correct timing offset, when the signal-to-noise ratio (SNR) is high or the signal power induced by the channel tap exceeds the noise power. Since random fluctuation of the timing function is unavoidable, the channel length is also determined to assist in locating the symbol timing at the middle of the ISI-free region. The proposed method is a 2-D function of the symbol timing offset and channel length. To reduce the complexity, i.e., search time and computation complexity, this work also develops an efficient search algorithm. Although ad hoc, the proposed timing function is demonstrated to be efficient because a complexity~O (N) and significant performance improvement are achieved.. The rest of this paper is organized as follows. Section II introduces the OFDM signal model and its correlation characteristics in multipath fading channels. Section III presents the proposed channel length assisted symbol synchronization algorithm. Section IV discusses in detail the design issues. Section V demonstrates simulation results. Finally, Section VI draws conclusions. This work has presented a novel channel length assisted synchronization scheme based on the properties of OFDM signals. Only simple operations, such as the multiplication and addition operations, are necessary. Simulation results demonstrate that the maximum value obtained by the proposed timing function is correct when the SNR is high. Otherwise, the correct timing estimate is ensured when the signal power induced by the channel tap exceeds the noise power. This finding suggests that the channel tap can be identified when its induced signal power exceeds the AWGN power. This work also identifies the symbol timing in the middle of the ISI-free region by estimating the channel length through use of the proposed timing function. Simulation results verify that the proposed estimation markedly reduces the MSE of the symbol timing estimate in multipath fading channels.

B I O B I O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O


Probe Minimization by Schedule Optimization: Supporting Top-K Queries with Expensive Predicates Abstract-This paper addresses the problem of evaluating ranked top-k queries with expensive predicates. As major DBMSs now all support expensive user-defined predicates for Boolean queries, we believe such support for ranked queries will be even more important: First, ranked queries often need to model user-specific concepts of preference, relevance, or similarity, which call for dynamic user-defined functions. Second, middleware systems must incorporate external predicates for integrating autonomous sources typically accessible only by per-object queries. Third, ranked queries often accompany Boolean ranking conditions, which may turn predicates into expensive ones, as the index structure on the predicate built on the base table may be no longer effective in retrieving the filtered objects in order. Fourth, fuzzy joins are inherently expensive, as they are essentially user-defined operations that dynamically associate multiple relations. These predicates, being dynamically defined or externally accessed, cannot rely on index mechanisms to provide zero-time sorted output, and must instead require per-object probe to evaluate. To enable probe minimization, we develop the problem as cost-based optimization of searching over potential probe schedules. In particular, we decouple probe scheduling into object and predicate scheduling problems and develop an analytical object scheduling optimization and a dynamic predicate scheduling optimization, which combined together form a cost-effective probe schedule.Index Terms-Database query processing, distributed information systems, database systems. We have presented our framework and algorithms for evaluating ranked queries with expensive probe predicate. We identified that supporting probe predicates is essential, in order to incorporate user-defined functions, external predicates, post-filtering predicates, and fuzzy joins. Our work generally addresses supporting expensive predicates for ranked queries: More specifically, we enable probe minimization by a cost-based optimization over the space of probe schedules. In particular, we decouple probe scheduling into object and predicate scheduling, which together form a probe schedule. We also develop Algorithm MPro, which analytically determines the optimal object schedule with respect to a given predicate schedule. We develop an effective dynamic predicate scheduling scheme to efficiently identify a cost-effective predicate schedule.. We have implemented the algorithm described in this paper, based on which we performed extensive experiments with both real-life databases and synthetic data sets. Our experimental study validates the optimality of our analytic object scheduling as "lower bound" performances and the effectiveness of our dynamic predicate scheduling over the existing schemes. In the beginning, top-k queries have been actively studied for multimedia retrieval in the context of middlewares. Fagin [6] , [18] first pioneered ranked queries and established the well-known FA algorithm. Algorithm FA performs a parallel sorted access for all predicates and completely evaluates the objects accessed (using random accesses), until at least k objects are seen from the all accesses, i.e., the k objects outscore the upper bound scores of objects yet to be accessed.. Soon after, many works have followed, which can be categorized in the following two categories: First, [14] , [13] , [12] followed to FA to be optimal in a stronger sense, by improving the stopping condition such that the upper bounds of the unseen objects can be more tightly computed. Second, [14] , [16] , [17] , [19] then followed to propose algorithms for various access scenarios, beyond FA assuming the sorted accesses over all predicates. Recently, ranked retrieval research has been expanded, including, supporting ranking with arbitrary join conditions [20] , probabilistic text retrieval [21] , and peer-to-peer retrieval [22] . This paper falls into the second category of identifying a new scenario of supporting expensive predicates for ranked queries, providing unified abstraction for user-defined functions, external predicates, postfiltering predicates, and fuzzy joins. Concurrently with our preliminary work [5] , some related efforts emerge to support expensive external predicates [16] (and its extended version [17] ), with specific focus to external Web-based predicates in the form of weighted average functions. These works and our framework similarly adopt the branch-and-bound or best-first search techniques [23] ; however, our work clearly distinguishes itself in the following several aspects:. First, we aim at a different or more general problem of supporting general expensive predicates over arbitrary monotonic functions, unlike [16] , [17] which support only weighted average functions. A key challenge in extending ranking function for arbitrary monotonic function comes from identifying an ideal scheduling scheme for the arbitrary given function, while [16] , [17] develop a scheduling scheme by cost-weight ratio which is fundamentally restricted to weighted average functions. Second, our framework models probe minimization as probe scheduling optimization which decouples into object scheduling (finding objects to probe) from predicate scheduling (finding predicates to execute). In particular, we develop provably optimal object scheduling scheme, together with dynamic predicate scheduling schemes. Bruno et al. [16] , [17] employ the same intuition in object scheduling and capture the insight of predicate scheduling with heuristics of maximizing "expected score decrease" for weighted scoring functions. In contrast, we believe our systematic optimization integrating object and predicate scheduling enables the formal foundation of probe-optimality and achieves generality to support arbitrary monotonic scoring functions. Third, while our framework can generally deal with both per-object and per-query predicate scheduling, we choose to focus on the global strategy unlike the per-object strategies proposed in [16] , [17] . We analytically and empirically argue that the overhead of per-object scheduling generally offsets its benefit in Section 3.3 and Section 4.. This paper focuses on probe-only scenarios and, thus, provides a foundation for [19] uniformly supporting any arbitrary top-k access scenarios. A key difference is that [5] focuses on a probe-only scenario, which is a subset of arbitrary top-k scenarios supported by [19] and thus serves as the foundations of supporting arbitrary scenarios in the following two dimensions: First, the necessary-probe principle provides an analytic foundation for scheduling arbitrary accesses in [19] . Second, our predicate scheduling schemes developed in Section 3.3 is adopted in [19] in scheduling random accesses.. In summary, this paper is first to generally support expensive predicates. Further, we decouple probe scheduling into object and predicate scheduling, which together form a probe schedule. Our systematic development of schedule optimization, decoupled into object and predicate scheduling, provides a theoretical justification for the techniques proposed in our preliminary work [5] . Our proposed algorithm is thus optimal in principle, by analytically identifying a provably optimal object schedule with respect to which a given predicate schedule identified by a dynamic predicate scheduling optimization. This section reports our extensive experiments for studying the optimality and practicality of Algorithm MPro. Our experiments thus have a two-fold interpretation. First, to study the optimality, recall that, Algorithm MPro implements provably optimal object scheduling. To study this "lower bound" performance, we first isolate object scheduling and evaluate its performance over various configurations. Second, to study the practicality, we evaluate the effectiveness of our dynamic predicate scheduling over existing works for extensive and practical performance evaluations, respectively. In particular, we extensively compare our predicate scheduling framework to other existing schemes, over both synthetic and real-life data.. We measured two different performance metrics. Consider query Q ¼ Fðx; p 1 ; . . . ; p n Þ. First, to quantify the relative probe performance, we measure how MPro saves unnecessary probes with the probe ratio metric. Suppose that MPro performs m i probes for each p i . In contrast, complete probing will require m probes (where m is the database size) for every probe predicate. The overall probe ratio (in percentages) is thus. which is the sum of the predicate probe ratio. Further, to quantify the "absolute" performance, our second metric measured the elapsed time (in seconds) as the total time to process the query. This metric helps us to gauge how the framework can be practically applied with reasonable response time. It also more realistically quantifies the performance when predicates are of different costs, because we measure the actual time, which cannot be shown by counting the number of probes as in probe ratios.. Our experiments used both synthetic data as well as a "benchmark" database (with real-life data). For extensive study, Sections 4.1 and 4.2 report "simulations" over data synthesized with standard distributions. To understand the performance of MPro in real-world scenarios, we evaluate with a real-life real-estate database (essentially the same as our examples), which we report in the Appendix, which can be found on the Computer Society Digital Library at http:// computer.org/tkde/archives.htm, due to the space limitation. All experiments were conducted with a Pentium 2.4GHz PC with 512MB RAM.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


The

research

for

protecting

location

privacy

based

on

V-W

algorithm

With

the

development

of

mobile

internet,

protecting

location

privacy

has

already

been

an

important

issue.

Based

on

previous

studies

and

the

drawback

of

traditional

algorithms,

the

paper

proposes

a

novel

algorithm

for

protecting

location

privacy.

The

algorithm

is

based

on

the

voronoi

map

of

a

road

network,

considers

the

problem

of

side-weight

inference,

and

utilizes

the

information

entropy

as

metrics.

Meanwhile,

the

algorithm

can

defense

the

attack

of

side-weight

inference

and

replay.

Lastly,

we

verified

the

algorithm

based

on

the

real

data

of

the

road

network.

Results

of

experiences

show

that

the

improved

algorithm

has

the

better

performance

on

some

key

performance

metrics.

With

the

rapid

development

of

mobile

network,

the

leakage

of

location

privacy

has

become

a

problem

that

cannot

be

ignored.

So

lots

of

researchers

have

paid

more

attention

on

it.

So

far,

researches

on

protecting

location

privacy

mainly

focus

on

two

aspects:

The

infrastructure

of

a

location

privacy

protection

system

and

the

method

of

protecting

location

privacy.

Now,

the

mainstream

architectures

of

a

location

privacy

protection

system

are

usually

divided

into

three

categories:

non-cooperative

architecture,

distributed

peer-to-peer

architecture,

and

centralized

architecture

The

existing

methods

about

location

privacy

protection

mainly

include

false-name

location

privacy

protection,

landmark

location

privacy

protection,

false-address

location

privacy

protection,

and

spatial

anonymity

location

privacy

protection.

False-name

location

privacy

protection

replaces

the

real

identity

of

a

user

by

a

false

name

so

that

attackers

cannot

obtain

the

real

query

source

from

location-based

services

(LBS)

severs

Landmark

location

privacy

protection

only

utilizes

some

landmark

position

within

a

certain

range

instead

of

a

user's

real

position

to

interact

with

LBS,

so

attackers

cannot

identify

the

real

position

of

users

Through

the

further

research

on

landmark

method,

the

current

method

of

protecting

location

privacy

based

on

a

landmark

not

only

uses

landmark

position

to

replace

the

real

position

of

a

target,

but

also

utilizes

some

algorithms

to

give

a

false

position

to

replace

the

real

position

of

users.

For

instance,

literature

adopts

an

incremental

nearest

neighbor

query

algorithm

to

realize

location

privacy

protection.

In

literature

an

anonymous

regional

transformation

algorithm

is

adopted.

In

the

method

of

false-address

location

privacy

protection,

a

position

information

set,

that

includes

the

real

position

of

a

user

and

a

sequence

of

a

false

position

(dubbed

as

dummy),

is

sent

to

LBS,

so

attackers

have

no

way

to

distinguish

the

real

position

information

from

the

received

information

Spatial-anonymity

location

privacy

protection

is

also

a

very

interesting

method.

An

anonymous

server

makes

user

information

anonymous

to

obtain

a

fuzzy

space

or

user

set

and

then

uses

the

fuzzy

space

or

user

set

as

a

requester

body

to

interact

with

an

LBS

server.

So

far,

K-Anonymous

algorithm

proposed

by

Marco

Gruteser

is

the

most

classic

in

spatial-anonymity

location

privacy

protection

Based

on

K-Anonymous

algorithm,

some

scholars

propose

several

improved

algorithms

aimed

at

different

performance

demands.

For

instance,

literature

propose

personalized

K-Anonymous

algorithm

based

on

personalized

demands

of

users.

The

algorithm

can

adjust

the

requested

k

value

for

users

according

to

their

security

demand.

To

solve

the

problem

of

a

low

anonymous

success

rate

of

a

traditional

algorithm,

Xiao

et

al.

designed

an

efficient

directed

graph

based

on

choking

algorithms

The

Casper

algorithm

in

mainly

considers

a

largescale

requested

condition

and

personalized

anonymous

demand..

However,

the

current

researches

mostly

focus

on

Euclidean

geometric

space.

In

fact,

a

road

network

environment

limits

the

user's

activity

in

most

cases.

Meanwhile,

it

is

very

meaningful

to

make

further

research

on

location

privacy

protection

based

on

the

road

network.

In

Rubner

gives

a

method

that

transforms

Euclidean

geometric

space

into

the

road

network

environment.

Literature

gives

an

X-STAR

algorithm.

The

algorithm

regards

road

crossing

point

as

a

node

and

conducts

an

anonymous

process

to

users.

It

can

simultaneously

make

an

anonymous

set

satisfy

two

conditions,

k-anonymous

of

location

and

l-diversity

of

road.

According

to

the

road

network

environment,

an

anonymous

ring,

anonymous

tree,

or

anonymous

cellular

can

also

be

adopted

to

realize

location

privacy

protection

In

addition,

Zhao

et

al.

give

an

anonymous

method

based

on

a

voronoi

map.

The

anonymous

method

can

be

fulfilled

in

a

v

zone

after

satisfying

the

condition

of

K-Anonymous

and

l-diversity.

The

above

algorithms

have

their

own

advantages,

but

their

shortcomings

are

also

obvious.

For

example,

the

algorithm

in

has

too

low

security.

The

anonymous

success

rate

in

is

too

low,

and

its

computation

complexity

is

too

high.

In

a

too

large

anonymous

ring

may

result

in

the

serious

degradation

of

QOS.

Algorithms

in

do

not

consider

the

attack

of

side-weight

inference,

so

their

security

is

not

enough.

Therefore,

in

this

paper,

we

consider

the

problem

of

side-weight

inference

and

utilize

the

information

entropy

as

metrics,

then

propose

a

novel

algorithm

based

on

voronoi-weight

(V-W)

for

protecting

location

privacy..

The

remainder

of

this

paper

is

organized

as

follows.

We

analyze

the

related

issues

of

a

traditional

algorithm

and

determine

the

design

target

of

our

algorithm

in

Section

The

complete

design

is

given

in

Section

Section

presents

the

performance

evaluation

result

of

our

proposed

algorithm.

Finally,

the

paper

is

concluded

in

Section

This

paper

firstly

introduces

the

existing

method

on

location

privacy

protection.

Secondly,

we

analyze

the

drawback

of

traditional

algorithms

and

give

the

design

target

of

our

algorithm.

Lastly,

we

proposed

and

analyzed

the

V-W

algorithm,

then

compared

it

with

traditional

algorithms.

The

results

can

show

that

our

algorithm

can

provide

the

better

performance

on

location

privacy

protection.

O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B I O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I O O B I O O B I O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O


Privacy

preserving

collaborative

filtering

for

SaaS

enabling

PaaS

clouds

Recommender

systems

use,

amongst

others,

a

mechanism

called

collaborative

filtering

(CF)

to

predict

the

rating

that

a

user

will

give

to

an

item

given

the

ratings

of

other

items

provided

by

other

users.

While

reasonably

accurate

CF

can

be

achieved

with

various

well-known

techniques,

preserving

the

privacy

of

rating

data

from

individual

users

poses

a

significant

challenge.

Several

privacy

preserving

schemes

have,

so

far,

been

proposed

in

prior

work.

However,

while

these

schemes

are

theoretically

feasible,

there

are

many

practical

implementation

difficulties

on

real

world

public

cloud

computing

platforms.

In

this

paper,

we

present

our

implementation

experience

and

experimental

results

on

two

public

Software-as-a-Service

(SaaS)

enabling

Platform-as-a-Service

(PaaS)

clouds:

the

Google

App

Engine

for

Java

(GAE/J)

and

the

Amazon

Web

Services

Elastic

Beanstalk

(AWS

EBS).

a

Pooling

and

sharing

of

resources,

broad

network

access,

rapid

elasticity,

on-demand

service

provisioning

(with

a

strong

self-service

element),

offering

of

measured

service,

supporting

(although

not

necessitating)

multi-tenancy,

are

some

of

the

features

that

characterise

cloud

computing.

Cloud

architecture

offers

a

means

of

delivering

ICT

infrastructure,

platform

(i.e.

application

execution

environment)

and

software

as

a

service.

The

benefits

promised

by

this

paradigm

include

cost

and

performance

optimisation,

economy

of

scale,

flexible

utilisation

and

charging

model,

ease

of

connectivity

and

access

to

shared

services,

cost

efficient

introduction

of

redundancy

and

continuity

of

provision.

Security,

resilience

and

compliance

are

some

of

the

main

concerns

that

are

challenging

wider

use

of

cloud

computing

and

most

likely

to

drive

remaining

innovation

and

market

differentiation

efforts

in

this

area..

The

rapid

growth

of

information

services

provided

over

the

World

Wide

Web

has

resulted

in

individuals

having

to

sift

through

overwhelming

volumes

of

information

-the

problem

of

information

overload

Recommendation

systems

have

been

used

as

a

rescue.

Automated

*Correspondence:

abasu@cs.dm.u-tokai.ac.jp

Graduate

School

of

Engineering,

Tokai

University.

Takanawa,

Minato-ku,

Tokyo

Japan

Full

list

of

author

information

is

available

at

the

end

of

the

article

recommendation

systems

employ

two

techniques:

profile

analysis

and

collaborative

filtering

(CF).

The

former

matches

the

items

to

be

recommended

using

information

that

relate

to

users'

tastes;

while

CF

makes

use

of

the

recorded

preferences

of

the

community.

Profile-based

recommendation

for

a

user

with

rich

profile

information

is

thorough.

However,

CF

is

fairly

accurate

even

without

the

need

for

the

users'

profile

information.

CF

has,

thus,

positioned

itself

as

one

of

the

predominant

means

of

generating

recommendations..

Grouped

by

filtering

techniques,

numeric

rating

based

CF

is

broadly

classified

into:

memory-based

or

neighbourhood-based

and

model-based.

In

memory-based

approaches,

recommendations

are

developed

from

user

or

item

neighbourhoods,

i.e.

proximity

(or

deviation)

measures

between

the

ratings,

e.g.

cosine

similarity,

Euclidean

distance

and

various

statistical

correlation

coefficients.

Memory-based

CF

can

also

be

distinguished

into:

userbased

and

item-based.

In

the

former,

CF

is

performed

using

neighbourhood

between

users

computed

from

the

ratings

provided

by

them.

In

item-based

schemes,

prediction

is

obtained

using

item

neighbourhoods,

i.e.

proximity

(or

deviation)

of

ratings

between

various

items.

In

model-based

approaches,

the

original

user-item

ratings

dataset

is

used

to

train

a

compact

model,

which

is

then

used

for

prediction.

The

model

is

developed

by

methods

borrowed

from

artificial

intelligence,

such

as

Bayesian

classification,

latent

classes

and

neural

networks;

or,

from

linear

algebra,

e.g.

singular

value

decomposition

(SVD),

latent

semantic

indexing

(LSI)

and

principal

component

analysis

(PCA).

Model-based

algorithms

are

usually

fast

to

query

but

relatively

slow

to

update..

CF

based

approaches

perform

better

with

the

availability

of

more

data.

Cross

domain

recommendations

are

possible,

if

the

corresponding

data

can

be

utilised

(e.g.

a

person

with

a

strong

interest

in

horror

movies

may

also

rate

certain

Halloween

products

highly).

However,

the

sharing

of

user-item

preferential

(i.e.

rating)

data

for

use

in

CF

poses

significant

privacy

and

security

challenges.

Competing

organisations,

e.g.

Netflix

and

Blockbuster

may

not

wish

to

share

specific

user

information,

even

though

both

may

benefit

from

such

sharing.

Users

themselves

might

not

want

detailed

information

about

their

ratings

and

buying

habits

known

to

any

single

organisation.

To

overcome

this,

there

has

been

recent

work

in

privacy-preserving

collaborative

filtering

(PPCF)

that

can

enable

CF

without

leaking

private

information.

In

CF,

achieving

accuracy

and

preserving

privacy

are

orthogonal

problems.

The

two

main

directions

of

research

in

privacy-preserving

collaborative

filtering

are:

encryption-based

and

randomisation-based.

In

encryption-based

techniques,

prior

to

sharing

individual

user-item

ratings

data

are

encrypted

using

cryptosystems

that

support

homomorphic

properties.

In

randomisationbased

privacy

preserving

techniques,

the

ratings

data

is

randomised

either

through

random

data

swapping

or

data

perturbation

or

anonymisation..

However,

many

theoretically

feasible

collaborative

filtering

schemes

face

practical

implementation

difficulties

in

real

world

computing

infrastructures

like

public

cloud

computing

platforms.

These

difficulties

include

computational

complexity,

dataset

size

and

hence

scalability,

and

dependence

on

trusted

third

party

amongst

others.

In

this

paper,

we

re-visit

the

generalised

problem

of

privacy

preserving

collaborative

filtering:

we

present

and

extend

our

previously

proposed

novel

approach

and

realistic

implementations

of

a

privacy

preserving

weighted

Slope

One

scheme

on

the

Google

App

Engine

for

Java

(GAE/J)

and

the

Amazon

Web

Services

Elastic

Beanstalk

(AWS

EBS)

-two

specialised

Platform-as-a-Service

(PaaS)

cloud

services

that

enable

Software-as-a-Service

(SaaS)

construction.

Many

existing

privacy

preserving

collaborative

filtering

schemes

pose

challenges

with

practical

implementations

on

real

world

cloud

computing

platforms.

In

this

paper,

we

utilised

the

well-known

weighted

Slope

One

collaborative

filtering

predictor

to

demonstrate

a

novel

approach

for

privacy

preserving

collaborative

filtering

and

its

practical

applicability

on

two

public

Software-as-a-Service

enabling

Platform-as-a-Service

clouds:

the

Google

App

Engine

for

Java

and

the

Amazon

Elastic

Beanstalk.

In

our

scheme,

user's

rating

data

is

not

stored

in

the

cloud.

Our

scheme

does

not

rely

on

any

trusted

third

party

for

threshold

decryption

by

allowing

the

users

to

encrypt

and

decrypt

a

prediction

query

and

its

results

respectively.

The

results

of

our

experiments

show

that

the

user

can

obtain

predictions

quickly

despite

encrypted

rating

queries,

with

results

on

the

Amazon

Elastic

Beanstalk

outperforming

those

on

the

Google

App

Engine.

Author

details

In

recent

years,

privacy

has

attracted

a

lot

of

attention.

There

are

a

number

of

existing

works

on

privacypreserving

collaborative

filtering

(PPCF).

One

of

the

earliest

such

efforts

is

due

to

Canny

which

uses

a

partial

Singular

Value

Decomposition

(SVD)

model

and

homomorphic

encryption

to

devise

a

multi-party

PPCF

scheme.

Canny

also

proposes

a

new

solution

based

on

a

probabilistic

factor

analysis

model

that

can

handle

missing

data,

and

provides

privacy

through

a

peer-to-peer

protocol..

Polat

and

Du

have

also

investigated

this

problem

from

several

perspectives:

in

they

proposed

a

randomized

perturbation

technique

to

protect

individual

privacy

while

still

producing

accurate

recommendations

results;

in

the

authors

presented

a

privacy-preserving

protocol

for

collaborative

filtering

over

vertically

partitioned

data;

in

a

randomisation

based

SVD

approach

is

presented,

while

in

the

scheme

enables

recommendations

via

item-based

algorithms

using

randomized

response

techniques..

Berkovsky

et

al.

present

a

decentralized

distributed

storage

of

user

data

combined

with

data

modification

techniques

to

mitigate

privacy

issues.

Tada

et

al.

presented

a

privacy-preserving

item-based

collaborative

filtering

scheme

in

Cissée

and

Albayrak

develop

a

method

for

privacypreserving

recommender

systems

based

on

a

multi-agent

technology

which

enables

applications

to

generate

recommendations

via

various

filtering

techniques

while

preserving

the

privacy

of

all

participants.

Ahmad

and

Khokar

proposed

a

privacy

preserving

collaborative

filtering

schemes

for

web

portals

using

a

trusted

third

party

for

threshold

decryption.

Kaleli

and

Polat

propose

a

naïve

Bayesian

classifier

based

CF

over

a

topology

where

the

users

protect

the

privacy

of

their

data

using

masking,

which

is

comparable

to

randomisation.

Another

homomorphic

encryption

based

SVD

scheme

has

been

proposed

by

Han,

et

al.

but

the

authors

also

describe

that

their

scheme

does

not

scale

well

for

realistic

datasets.

Gong

et

al.

present

a

new

collaborative

filtering

technique

based

on

randomised

perturbation

and

secure

multiparty

computation.

However,

neither

are

these

techniques

built

for

the

cloud,

nor

are

they

efficient

enough

for

large-scale

general

purpose

use..

Our

work

is

the

first

PPCF

scheme

that

includes

a

practical

cloud-based

implementation

and

results.

In

we

have

proposed

a

privacy

preserving

(using

encryption)

CF

scheme

based

on

the

well

known

weighted

Slope

One

predictor

Our

prior

scheme

is

applicable

to

pure

horizontal

and

pure

vertical

dataset

partitions.

The

scheme

presented

in

this

paper

does

not

consider

dataset

partitioning

in

the

cloud

because

user's

rating

data

are

not

stored

in

the

cloud

at

all.

Even

so,

the

general

assumption

is

that

each

user

knows

only

his

or

her

own

ratings,

and

does

know

all

of

them

-similar

to

the

case

of

horizontal

partitioning

of

data

outside

the

cloud.

We

do

include

a

discussion

on

the

case

of

vertical

partitioning

of

data

outside

the

cloud.

We

have

also

experimented

with

an

actual

implementation

on

the

cloud,

but

since

of

the

other

existing

work

has

tested

their

implementation

on

a

cloud

computing

environment,

we

do

not

provide

any

explicit

comparative

evaluation.

B O B I O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O B I O O O O O O O O O B I B I O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O


Probabilistic BPRRC: Robust Change Detection against Illumination Changes and Background Movements This paper presents PrBPRRC (Probabilistic Bipolar Radial Reach Correlation) Amid rising concerns about security, surveillance systems have become a focus of attention in recent years. To realize practical surveillance systems, robust change detection for preprocessing is required. Change detection reduces the processing area of timeconsuming processes such as object recognition, human detection, and human behavior analysis; therefore, it reduces processing time of the whole system and increases the performance by reducing false positive detection from background region.. Though the environments in which practical surveillance systems operate may include many large disturbances such as illumination changes and background movements, most of the traditional change detection methods are robust against either illumination changes or background movements. For example, Bi-polar Radial Reach Correlation (BPRRC) [1] is robust against illumination changes by using texture model but not robust against background movements because of its rigid texture model.. We propose Probabilistic BPRRC (PrBPRRC), the extension of BPRRC, which preserves BPRRC's robustness against illumination changes and adds the robustness against background movements. PrBPRRC introduces a probabilistic model for background texture and learns a probabilistic background with inputs including background movements and foreground invasions. We show the superiority of our PrBPRRC with ATON Highway data [2] , Karlsruhe traffic sequence data [3] , and PETS 2007 data [4] .. In this paper we make several assumptions to define "change detection": (i) the camera is fixed so that background subtraction which compares input with learned background model can be used for change detection, (ii) change includes foreground objects which deviate from learned background, and (iii) change doesn't include background movements and illumination changes. These assumptions are natural in surveillance system.. The rest of this paper is organized as follows. We briefly review several former change detection methods in Section 2. We then describe the former BPRRC and our proposed PrBPRRC in Section 3. We compare the performance of the methods with public datasets in Section 4 and conclude in Section 5. In this paper, we proposed PrBPRRC, the extension of the BPRRC, which preserves BPRRC's robustness against illumination changes and adds the robustness against background movements.. We introduced a probabilistic background texture model into BPRRC. Our new method learns the distribution of background texture based on the intensity differences between target pixel and reference pixels, and detects changes with a probabilistic decision based on the texture distribution. It enables learning of a probabilistic background from the training images including background movements and foreground invasions such as moving cars, walking pedestrians, swaying trees, and falling snow.. We evaluated several change detection methods with ATON Highway data, Karlsruhe traffic sequence data, and PETS 2007 data and showed the superiority of our PrBPRRC in terms of stability against data disturbances and parameter setting.. In future work, we intend to improve the performance by introducing color texture information into the PrBPRRC model. Many background models for change detection have been proposed. One of the simplest background models is the single Gaussian model that models each pixel intensity with a single Gaussian distribution ( Fig. 1(a) ). The Gaussian distribution can model intensity fluctuation of each pixel caused by sensing devices but the model is too simple to model real environmental changes.. Stauffer et al. proposed Mixture of Gaussian (MoG) [5] that uses multiple Gaussian distributions to model multiple background intensity distributions caused by ripples on the water surface and flickering of the display ( Fig. 1(b) ). MoG is used in many applications but requires a decision on the number of Gaussian distributions. To avoid this decision, Nakai proposed a non-parametric pixel intensity model with pixel intensity histogram [6] (Fig. 1(c) ). Because, in contrast to the Gaussian model, it doesn't assume any parametric models, it can model arbitrary intensity distributions.. Pixel-intensity-based models such as MoG and the histogram model are not robust against illumination changes because illumination changes cause large intensity changes deviating from the past intensity history. For example, background models trained with images in the sun cannot cover inputs in the shade. To increase robustness against illumination changes, some methods introduced texture information. Texture information based on the intensity differences among local pixels is stable against illumination changes because all the local pixels change their intensities by almost the same amount and the intensity differences among them don't change. Satoh et al. proposed Peripheral Increment Sign Correlation (PISC) [7] and Heikkilä et al. proposed Local Binary Pattern (LBP) [8] that encode the intensity differences between target pixel and surrounding reference pixels as 0/1 binary code ( Fig. 1(d) ). Yokoi proposed Peripheral TErnary Sign Correlation (PTESC) [9] that encodes the intensity differences by −1/0/1 ternary codes to increase the robustness against illumination changes.. Though these texture-based methods are robust against illumination changes, they cannot work properly in the region without texture. Plain foreground objects before plain background with different intensity from foreground cannot be detected by these methods because both foreground and background have the same plain texture.

B I B B I O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O B I O O B O O B I O B I O O O O O O O O O B O B I O O O O O O B O B I O O O O O O O O B I O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Enhanced homogenization technique for magnetomechanical systems using the generalized finite element method Emerald Article: Enhanced homogenization technique for magnetomechanical systems using the generalized finite element method A. Hauck, T. Lahmer, M. KaltenbacherTo cite this document: A. Hauck, T. Lahmer, M. Kaltenbacher, (2009) With over forty years' experience, Emerald Group Publishing is a leading independent publisher of global research with impact in business, society, public policy and education. In total, Emerald publishes over 275 journals and more than 130 book series, as well as an extensive range of online products and services. Emerald is both COUNTER 3 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.*Related content and download information correct at time of download.Enhanced homogenization technique for magnetomechanical systems using the generalized finite element methodDepartment of Sensor Technology, University of Erlangen-Nuremberg, Erlangen, GermanyBauhaus Universitaet Weimar, Weimar, Germany, andDepartment of Applied Mechatronics, Alpen-Adria University of Klagenfurt, Klagenfurt, AustriaAbstract Purpose -The purpose of this paper is to present a homogenization approach to model mechanical structures with multiple scales and periodicity, as they occur, e.g. in power transformer windings, subjected to magnetic forces. Design/methodology/approach -The idea is based on the framework of generalized finite element methods (GFEM), where the normal polynomial finite element basis functions are enriched by problem dependent basis functions, which are, in this case, the eigenmodes of a quasi-periodic unit cell setup. These eigenmodes are used to enrich the standard polynomial basis functions of higher order on a coarse grid modeling the whole periodic structure. Findings -It is shown that heterogeneous magnetomechanical structures can be homogenized with the developed method, as demonstrated by homogenization of a transformer coil setup. Originality/value -An efficient homogenization procedure is proposed on the basis of the GFEM, which is extended using a special set of enrichment functions, i.e. the mechanic eigenmodes of a generalized eigenvalue problem. A typical example for a magnetomechanical system is an electric power transformer. Its complex core and winding structures with many small-scale features (laminated core and insulated conductors) exhibit problems for the geometric modeling and mesh generation. The main problems stem from the fact, that the overall dimension of a power transformer is typically in the range of a few meters, whereas the single strands in the coils have only a crossection of a few millimeters. In Figure 1 , a typical high-voltage (HV) coil can be seen, which consists of 80 layers of disc-type windings with 22 conductors each. Here, the width of one conductor is about 1.5 mm, whereas the overall height is about 1.2 m. The conductors itself (copper) are wrapped with insulating material (paper and epoxy). The single layers are separated by wooden spacer blocks, distributed in circumferential direction.. In pure magneto-dynamic simulation, especially the efficient treatment of the laminated core is already addressed quite well (Chiampi and Chiarabaglio, 1992) . Here, it is important to account for the correct distribution of eddy currents. However, the efficient and reliable computation of winding and tank vibrations due to Lorentz forces is still a major problem: here the accurate modeling of the complete transformer and especially the winding structure is of importance. The key issue lies in reducing the model complexity in the transformer coil by not resolving the single strands and isolation, but to take this small scale structure into account in a suitable way in a very coarse simulation model. As the permeability of those materials is in a similar range, the simulation model for the magnetic field does not have to resolve these structures in detail. However, the mechanical properties (stiffness and density) of the materials differ significantly, which demands for an accurate and efficient homogenization technique.. In the present work, we focus on this issue by utilizing the so-called generalized finite element method (GFEM) (Babuška and Melenk, 1997) to perform a two-scale homogenization of the mechanical winding structure of the HV coil of a power transformer. Here, the fact is exploited, that the coil exhibits a periodic structure, which allows to enrich the normal FEM by spectral information from a single periodic unit cell (Matache et al. 2000) .. The outline of this work is as follows: in Section 2, we will introduce the very universal framework of the GFEM, based on the partition of unity method (PUM). The applicability of this method for homogenization using the scale separation property is presented in the subsequent Section 3, together with some convergence properties for a 2D model problem. In the last part in Section 4, we utilize the method to homogenize the HV winding of a power transformer and compare the results with a heterogeneous solution. In this work, the framework of the generalized finite element and its most important properties are introduced. The applicability of this method to homogenization of elastic systems is shown by selecting the enrichment functions as eigenmodes of a suitable chosen, periodic unit cell problem. Some general convergence studies are performed for Figure 14 .

O B I O B I O O B I I I O O O B I O B I O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Automated Segmentation of the Melanocytes in Skin Histopathological Images Abstract-In the diagnosis of skin melanoma by analyzing histopathological images, the detection of the melanocytes in the epidermis area is an important step. However, the detection of melanocytes in the epidermis area is difficult because other keratinocytes that are very similar to the melanocytes are also present. This paper proposes a novel computer-aided technique for segmentation of the melanocytes in the skin histopathological images. In order to reduce the local intensity variant, a mean-shift algorithm is applied for the initial segmentation of the image. A local region recursive segmentation algorithm is then proposed to filter out the candidate nuclei regions based on the domain prior knowledge. To distinguish the melanocytes from other keratinocytes in the epidermis area, a novel descriptor, named local double ellipse descriptor (LDED), is proposed to measure the local features of the candidate regions. The LDED uses two parameters: region ellipticity and local pattern characteristics to distinguish the melanocytes from the candidate nuclei regions. Experimental results on 28 different histopathological images of skin tissue with different zooming factors show that the proposed technique provides a superior performance.Index Terms-Histopathological image analysis, image segmentation, local descriptor, object detection, pattern recognition. This paper presents a simple but effective computer-aided technique for segmentation of the melanocytes in the skin histopathological image. The candidate nuclei regions are first extracted through the mean shift, and the proposed local region recursive segmentation algorithm. The local double ellipse descriptor then incorporates the biological feature of melanocytes and provides robust parameters to identify the melanocytes. The evaluation using 30 histopathological images with different zooming factors shows that the proposed technique is able to segment the melanocytes with over 80% sensitivity rate and over 70% positive prediction rate. In future, we have planned to analyze the cytological and architectural features of the detected melanocytes in order to grade and diagnose the skin tissues.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I B I B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A fractal model for characterizing fluid flow in fractured rock masses based on randomly distributed rock fracture networks A fractal model that represents the geometric characteristics of rock fracture networks is 23 proposed to link the fractal characteristics with the equivalent permeability of the fracture networks. 24 The fracture networks are generated using the Monte Carlo method and have a power law size 25 distribution. The fractal dimension DT is utilized to represent the tortuosity of the fluid flow, and 26 another fractal dimension Df is utilized to represent the geometric distribution of fractures in the 27 networks. The results indicate that the equivalent permeability of a fracture network can be 28 significantly influenced by the tortuosity of the fluid flow, the aperture of the fractures and a 29 random number used to generate the fractal length distribution of the fractures in the network. The 30 correlation of fracture number and fracture length agrees well with the results of previous studies, 31 and the calculated fractal dimensions Df are consistent with their theoretical values, which confirms 32 the reliability of the proposed fractal length distribution and the stochastically generated fracture 33 network models. The optimal hydraulic path can be identified in the longer fractures along the fluid 34 flow direction. Using the proposed fractal model, a mathematical expression between the equivalent 35 permeability K and the fractal dimension Df is proposed for models with large values of Df. The 36 differences in the calculated flow volumes between the models that consider and those that do not 37 consider the influence of fluid flow tortuosity are as high as 17.64% -19.51%, which emphasizes 38 that the effects of tortuosity should not be neglected and should be included in the fractal model to 39 accurately estimate the hydraulic behavior of fracture networks. 40 41 2 43 44 3Permeability is a crucial hydro-mechanical property of rock masses and is important in many areas of 46 geosciences and geoengineering, including dam foundations and petroleum reservoirs. The permeability of a rock 47 mass is mainly governed by rock fractures that separate intact rock blocks with negligible matrix permeability 48 (e.g., granite and basalt) [1][2]. A tremendous amount of effort has been exerted to understand the behavior of fluid 49 flow in rock masses in recent decades [3][4][5][6][7]. However, accurately estimating the permeability of rock masses is 50 still challenging because of the complexities of fracture distributions at the macro-structural (i.e., geometry of the 51 fracture network) and micro-structural (i.e., geometry of the void spaces within single fractures) levels [8][9][10][11]. One 52 key difficulty is that rock fractures typically have rough surfaces between which fluid flows non-uniformly. A 53 particle will travel a longer distance along a tortuous path through a rough-walled fracture than through a 54 parallel-walled fracture. Another difficulty is mathematically describing the geometric distributions of rock 55 fractures in fracture networks, which usually contain several sets of fractures with different orientations, lengths 56 and apertures. Fortunately, the distribution of fractures in fracture networks have been found to exhibit fractal 57 characteristics [12][13][14][15][16], which provides a possible approach for describing the geometric characteristics of fracture 58 networks while considering both the macro-scale and micro-scale properties of the fractures. 59 A few predictive fractal models have been developed to calculate the permeability of stochastic rock fracture 60 networks. The purpose of their models and the outcome of their studies are summarized in Table 1 . 61Based on the fractal models proposed for the porous media [10] and regular tree networks [21, 27] to 62 calculate the permeability of rock masses, the present study focused on extending this fractal model to the 63 4 fractured media consisted of randomly generated stochastic discrete fracture networks (DFNs) using the Monte 64 Carlo method. A probability density function was derived to depict the trace length l of each rock fracture between 65 a minimum and maximum trace length, and the apertures of the fractures were correlated with their trace lengths. 66Flow simulations of models with various fractal dimensions were conducted, and the relations between the fractal 67 dimensions and the equivalent permeability were estimated. 68Mandelbrot (1982) [28] verified that the cumulative size distribution of islands on the surface of the earth 70 followed the power law 71 80 pore, and g is a geometric factor. The distribution of fractures in 2-D rock masses is considered to be analogous to 81 that of islands on the surface of the earth and that of pores in porous media, which yields 82 5 Rough surfaces of fractures render the streamlines of fluid flow nonlinear, which can increase the end-to-end 131 distances required for fluid flow through fractures and therefore reduce their equivalent permeability. Here, as 132 shown in Fig. 1, l is the straight length of the fracture pathways in the flow direction, lt is the tortuous length along 133 the fracture profile, and e is the hydraulic aperture of a single fracture [35]. Generally, lt > l, except for fractures 134 8 where N' is the total number of islands with an area A' greater than a constant a' and D is the fractal dimension 73 that represents the size distribution of the islands. where N is the total number of fractures with a length L greater than a constant fracture length l; Df is in the range 84 of [1, 2] for 2-D fracture networks; and lmax is the maximum trace length of fractures in a rock mass. Previous studies of fracture sizes from centimeters to meters at different sites have found that the aperture 117 and the trace length of fractures have positive linear correlations [30] [31] or power law correlations [32] [33] . 118. Longer fractures usually have higher permeabilities and larger apertures than shorter fractures. In this study, 119 assuming that the DFN models are composed of a large number of small fractures with small hydraulic apertures 120 and a much smaller number of longer fractures with larger apertures, the trace lengths of the fractures are 121 randomly generated according to Eq. (11) and are correlated with the fracture aperture as follows [4, 34] : 122 where erfinv is the inverse error function. 130 with flat surfaces (parallel plate model), where lt = l. The tortuosity is defined as a parameter to depict the ratio of 135 lt to l, in order to describe their difference induced by fracture surface roughness in 2-D rock fractures [36] . The 136 correlation of the tortuous length lt and the straight length l of fractures is also considered to be analogous to that 137 of pores in porous media [10, 37] , as expressed by . where q(i) is the fluid volume through the ith fracture, i P ∆ is the local hydraulic pressure difference applied 151 between the tips of the fracture, and µ is the viscosity of the fluid. fracture networks, the fracture elements outside the model, the isolated fracture elements, and the "dead-end" 163 fracture elements do not contribute to the fluid flow and should therefore be deleted. Second, parameters (i.e., 164 trace length, hydraulic aperture, and orientation) should be assigned to each fracture, and the mass continuity 165 equations at each fracture intersection should be established. The third aspect addresses the iteration scheme of 166 these equations for given boundary conditions. Steady-state fluid flow was adopted in this study for calculating 167 the equivalent permeability of DFNs, and a generic hydraulic boundary condition with a constant hydraulic 168 gradient in the x-direction was assumed, indicating that the directivity of the equivalent permeability is horizontal In a 2-D fracture network, fractures are line segments, and fracture intersection points are denoted as nodes. 171. The summation of the flow rate of each fracture connected to a node is zero or equals the added source term. 172. Similarly, the summation of the total flow rate of the entire fracture network equals zero or the summation of the 173 source terms added at each node. . where qn is the fluid volume through the fracture element n, M is the total number of fracture elements connected 178 to node m, Qm is a source term at node m, and Nnode is the total number of nodes in the entire fracture network. 179. Generally, under steady-state flow without any source terms, Qm = 0 and M ≤ 4 (two fractures intersect at one 180 node) given that the probability that more than two fractures intersect at the same node is nearly zero. Steady-state 181 flow was assumed; therefore, the fluid volume that flows into a fracture network is equal to that flowing out of the 182 network. The fluid rate at the outlet boundary was then utilized to estimate the equivalent permeability of the DFN 183 model. 184. Using Darcy's law as shown in Eq. (19), the equivalent permeability K is obtained in Eq. (20): 185 . where a'', b'', and c'' are three regression parameters equal to 0.4594, 0.2797 and 8.4968, respectively. 222. According to the definition of the mass density of fractures, dm can be expressed as follows: 223. where Lt is the theoretical model length. 225. Substituting Eq. (22) into Eq. (21), Lt can be calculated as follows: 226. Using the calculated value of Lt in Eq. (23), the number density of fractures dn, which defines the total 228 number of fractures in a given area of the fracture network, is obtained as follows: Table 2 . 238

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ADMIT-1: automatic differentiation and MATLAB interface toolbox ADMIT-1 enables the computation of sparse Jacobian and Hessian matrices, using automatic differentiation technology, from a MATLAB environment. Given a function to be differentiated, ADMIT-1 will exploit sparsity if present to yield sparse derivative matrices (in sparse MATLAB form). A generic automatic differentiation tool, subject to some functionality requirements, can be plugged into ADMIT-1; examples include ADOL-C (C/Cϩϩ target functions) and ADMAT (MATLAB target functions). ADMIT-1 also allows for the calculation of gradients and has several other related functions. This article provides an introduction to the design and usage of ADMIT-1. The efficient numerical solution of nonlinear systems of algebraic equations F͑x͒ ϭ 0, F͑x͒ : ᑬ n 3 ᑬ m , usually requires the repeated calculation or estimation of the matrix of first derivatives, the Jacobian matrix, J͑x͒ ʦ ᑬ mϫn . In large-scale problems, the matrix J is often sparse, and it is important to exploit this fact in order to efficiently determine, or estimate, the matrix J at a given argument x. The ADMIT-1 toolbox extends the MATLAB environment to provide a powerful computing environment for large-scale optimization and sensitivity analysis. The capability of doing automatic differentiation within the MATLAB opens up a wide range of applications which can easily use the AD technology.. The use of the ADMIT-1 tool with ADMAT as the plug-in tool is particularly interesting. Since ADMAT is written in MATLAB, it can be used just like any MATLAB toolbox without the need of external compilation steps (unlike the ADOL-C plug-in). Also, ADMAT can be readily applied to any of the thousands of different functions present in the MATLAB toolbox. With ADMAT, it is now possible to differentiate through a variety of MATLAB toolboxes, thus enabling automatic differentiation of complicated MATLAB applications. (However, ADMAT cannot differentiate through MEX files, since it needs the full MATLAB source code.)

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A DC piecewise affine model and a bundling technique in nonconvex nonsmooth minimization Abstract. We introduce an algorithm to minimize a function of several variables with no convexity nor smoothness assumptions. The main peculiarity of our approach is the use of an the objective function model which is the difference of two piecewise affine convex functions. Bundling and trust region concepts are embedded into the algorithm. Convergence of the algorithm to a stationary point is proved.

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Sequential selection procedures: Using sample means to improve efficiency Two-stage selection procedures have been widely studied and applied to determine appropriate sample sizes for selecting the best of k designs. However, standard "indifference-zone" procedures are derived with a statistically conservative least-favorable-configuration assumption. The Enhanced Two-Stage Selection (ETSS) is a procedure that takes into account not only the variance of samples but also the difference between sample means when determining the sample sizes. This paper discusses an implementation of sequential ranking and selection procedures due to the ETSS procedure to avoid relying too much on information obtained in just one stage. We show that the needed ratios of sample sizes to maximize the probability of correct selection is approximately maintained at all iterations. An experimental performance evaluation demonstrates the efficiency of our sequential procedures. Discrete-event simulation has been widely used to compare alternative system designs or operating policies. When evaluating k alternative system designs, we would like to select one as the best (or the best b designs) and to control the probability that the selected design really is the best, or to maximize the probability of correct selection with a pre-determined computing budget. Let µ i denote the expected response of design i. Our goal is to find a design with the smallest expected response µ * = min 1≤i≤k µ i . If the goal is to select a design with the biggest expected response, just replace min with max in the above. We achieve this constructing R&S procedures. Nelson et al. (2001) develop procedures for selecting the best when the number of alternative is large. Some drawbacks of two-stage selection procedures are that they rely heavily on the information obtained from only the first-stage, and the resources available may not be able to allocate the full sample sizes required for the second stage. , Chick and Inoue (2001) , and Kim and Nelson (2001) have developed sequential R&S procedures. For an overview of existing methods of R&S see Law and Kelton (2000) .. Let CS denote the event of "correct selection." In a stochastic simulation, CS can never be guaranteed with certainty. The possibility of CS, denoted by P(CS), depends on sample sizes and other uncontrollable factors. show that P(CS) is approximately maximized, or the sample size is approximately minimized, if the sample size for each design satisfies certain ratios (see Section 2.4). We propose a simple heuristic sequential R&S procedure such that the allocated sample size for each design approximately satisfies those ratios at each iteration.. The rest of this paper is organized as follows. In Section 2, we provide background necessary for the proposed procedure. In Section 3, we present the methodologies and the proposed R&S procedure. In Section 4, we give some empirical-experimental results. In Section 5, we give concluding remarks. Many two-stage indifference-zone-selection procedures ignore a large amount of first-stage sampling information. The ETSS procedure utilizes both the means and variances from the first stage. The marginal computation effort required for the ETSS procedure is minimal, yet the achieved efficiency improvement is significant. Moreover, the ETSS procedure has an intrinsic subset pre-selection. Some drawbacks of two-stage R&S procedures are that we rely heavily on the information from the first stage, and the computation budget may not be enough to obtain all the required samples for the second stage.. We propose a simple sequential R&S procedure based on the ETSS procedure to avoid relying too much on sample-mean estimates from only one stage. The SRS procedure can minimize the sample size with a given P * or maximize P(CS) with a pre-determined computing budget. The incremental sample sizes of different designs at each iteration are computed dynamically according to the difference between sample means and sample variances at each iteration, and the indifference amount d * . The SRS procedure allocates incremental sample sizes aggressively at earlier iterations, becomes less aggressive as the procedure proceeds, and effectively allocates additional replications or batches to more promising alternatives. Inferior designs are dropped from further consideration as the sequential procedure proceeds to reduce the overall computational effort. We improve the efficiency of the SRS procedure further by implementing all pairwise comparisons at each iteration.. The main advantage of SRS is that the algorithm determines the number of additional simulation replications based on both the means and variances, and approximately maintains the ratios required to maximize P(CS) with a given sample size at all iterations, so significantly improves the efficiency of R&S procedures. Unlike two-stage procedures, which are designed to guarantee P(CS) and assume all the required computing budget is available, the SRS procedure will be able to maximize P(CS) with a given computing budget.. Our experimental results show that the SRS procedure is a powerful tool for selecting the best b designs out of k alternatives. The SRS procedure improves P(CS) with slightly larger total simulation replications or batches compared to the ETSS procedure. Furthermore, incorporating all comparisons can improve the performance of R&S procedures in terms of P(CS) and sample size.. Let Φ(x) be the cdf (cumulative distribution function) of the standard normal distribution, let g(x) be the pdf (probability density function) of a chi-square distribution with r − 1 df (degrees of freedom), and let Q i l = Q for l = 2, 3, . . . , k. We then follow the steps in the proof of Proposition 1 in Rinott (1978) The term on the right-hand side is the lower confidence bound (LCB) and is at its tightest under the LFC. As the controlled distance d i increase, the LCB becomes looser because the difference between d i and d i 1 increases. This is a good property because as the d i increase we will have greater P(CS) on the pairwise comparison between designs i and i 1 , for i = i 1 .. Note that Q ij ≥ 0 and Z ij is N (0, 1), so It is well known that R&S procedures developed based on the LFC are conservative, and two-stage procedures rely heavily on information obtained from just one stage. OCBA is a sequential procedure that takes into consideration the difference between mean estimators.. However, OCBA is a fixed-sample-size procedure; it attempts to maximize P(CS) with a fixed total computing budget. Moreover, the achieved P(CS) cannot be estimated until the end of the procedure. If the achieved P(CS) is less than desired then the simulation needs to be restarted with a bigger simulation budget. The KN procedure described in Kim and Nelson (2001) First, some notation:

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O


From Microsoft Word 2003 to Microsoft Word 2007: Design Heuristics, Design Flaws and Lessons Learnt By tracing and comparing the number of key-presses taken to complete the functions in Word 2007 and Word 2003, the paper identifies eight design heuristics Word 2003 and Word 2007 could have violated, creating design flaws leading to potential usability problems. This paper concludes with design implications for software. Keywords: Microsoft Office Word 2003, Word 2007, design heuristics. Designers are often faced with the huge challenge of designing software and websites for a large number of different users, and do so by making the functionality of the software and websites as extensive as possible. In this one-size-fits-all approach, common goals of different types of users are identified. When introducing new interfaces or upgrades of existing software and websites, initial user confusion and poor adaptation are common user problems identified. The recent migration from Microsoft Office Word 2003 to Microsoft Office Word 2007 in late 2006 [3] is one such example that has generated poor reviews. This was evident from the numerous articles and blogs which have sprouted in the internet discussing this migration [4, 6] .. In this paper, we carried out an investigation of the learning problems faced by novice and expert users of Word 2003 when they migrating to Word 2007. We employed a heuristic evaluation of Microsoft Office Word 2003 and Office Word 2007 carried out to identify new or existing functions in Word 2007 that might cause usability problems based on established design heuristics [5] . The study reported in this paper was motivated by two concerns on users and usability research work on interactive systems [7] . Firstly, as evaluation techniques evolve to be more and more complicated and comprehensive, the impression designers/developers have towards usability engineering is often blocked by intimidation barriers such as "difficulty to conduct", "too time-consuming", "tedious" and "expensive". Secondly, there is a lack of practical evaluation techniques that designers can use to design and build more usable systems while meeting the time constraints of the design process. Using Microsoft Word 2007 as a case in point of committing serious design violations against well-known design heuristics, this paper argues that ignoring common sense design heuristics could lead to detrimental outcomes such as user confusion and usability problems.. Despite much work done on improving software accessibility, usability can still be improved as shown in Word 2007 [1] , and is worsened with new technologies and applications. Many argue that it can be too slow and costly for the financial and time constraints of the design process. It is not good enough to design an interactive system without subjecting it to some form of evaluation, because it is impossible to design an optimal user interface in the first try. Even if one has used the best methodology and model in the design of usable interactive system, one still needs to assess the design and test the system to ensure that it behaves as expected and meets end-users' requirements. Nielsen's [5] advice is that designers should simply conduct some form of testing. If designers were to do things well at the start, these types of usability problems could be ameliorated and/or prevented. Otherwise, remedial work after the new interfaces or upgrades have been done could be costly and time-consuming.

O O O O O O B I B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O B I O O O O O O O O O O O O O O O O O O O O B I I I B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B I I I O O B I O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O