Abstract: Relation between tolerance class and indispensable attribute and knowledge dependency in rough set model with tolerance relation is explored. After giving definitions and concepts of knowledge dependency and knowledge dependency degree for incomplete information system in tolerance rough set model by distinguishing decision attribute containing missing attribute value or not, the result of maintaining reflectivity, transitivity, augmentation, decomposition law and merge law for complete knowledge dependency is proved. Knowledge dependency degrees (not complete knowledge dependency degrees) only satisfy some laws after transitivity, augmentation and decomposition operations. An algorithm to solve attribute reduction in an incomplete decision table is designed. The correctness is checked by an example.
Abstract: Some invariant properties of incomplete information systems homomorphism are studied in this paper. Demand conditions of tolerance class, attribute reduction, indispensable attribute and dispensable attribute being invariant under homomorphism in incomplete information system are revealed and discussed. The existing condition of endohomomorphism on an incomplete information system is also explored. It establishes some theoretical foundations for further investigations on incomplete information systems in rough set theory, like in information systems.
Abstract: Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.
Abstract: In rough set models, tolerance relation, similarity
relation and limited tolerance relation solve different situation
problems for incomplete information systems in which there exists a
phenomenon of missing value. If two objects have the same few
known attributes and more unknown attributes, they cannot
distinguish them well. In order to solve this problem, we presented two
improved limited and variable precision rough set models. One is
symmetric, the other one is non-symmetric. They all use more
stringent condition to separate two small probability equivalent objects
into different classes. The two models are needed to engage further
study in detail. In the present paper, we newly form object classes with
a different respect comparing to the first suggested model. We
overcome disadvantages of non-symmetry regarding to the second
suggested model. We discuss relationships between or among several
models and also make rule generation. The obtained results by
applying the second model are more accurate and reasonable.
Abstract: With the rapid development of computer technology,
the design of computers and keyboards moves towards a trend of
slimness. The change of mobile input devices directly influences
users’ behavior. Although multi-touch applications allow entering
texts through a virtual keyboard, the performance, feedback, and
comfortableness of the technology is inferior to traditional keyboard,
and while manufacturers launch mobile touch keyboards and
projection keyboards, the performance has not been satisfying.
Therefore, this study discussed the design factors of slim
pressure-sensitive keyboards. The factors were evaluated with an
objective (accuracy and speed) and a subjective evaluation
(operability, recognition, feedback, and difficulty) depending on the
shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and
6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard.
Moreover, MANOVA and Taguchi methods (regarding
signal-to-noise ratios) were conducted to find the optimal level of each
design factor. The research participants, by their typing speed (30
words/ minute), were divided in two groups. Considering the
multitude of variables and levels, the experiments were implemented
using the fractional factorial design. A representative model of the
research samples were established for input task testing. The findings
of this study showed that participants with low typing speed primarily
relied on vision to recognize the keys, and those with high typing
speed relied on tactile feedback that was affected by the thickness and
force of the keys. In the objective and subjective evaluation, a
combination of keyboard design factors that might result in higher
performance and satisfaction was identified (L-shaped, 3mm, and
60±10g) as the optimal combination. The learning curve was analyzed
to make a comparison with a traditional standard keyboard to
investigate the influence of user experience on keyboard operation.
The research results indicated the optimal combination provided input
performance to inferior to a standard keyboard. The results could serve
as a reference for the development of related products in industry and
for applying comprehensively to touch devices and input interfaces
which are interacted with people.
Abstract: In the past, the most comprehensively adopted light
source was incandescent light bulbs, but with the appearance of LED
light sources, traditional light sources have been gradually replaced by
LEDs because of its numerous superior characteristics. However,
many of the standards do not apply to LEDs as the two light sources
are characterized differently. This also intensifies the significance of
studies on LEDs. As a Kansei design study investigating the visual
glare produced by traffic arrows implemented with LEDs, this study
conducted a semantic analysis on the styles of traffic arrows used in
domestic and international occasions. The results will be able to
reduce drivers’ misrecognition that results in the unsuccessful arrival
at the destination, or in traffic accidents. This study started with a
literature review and surveyed the status quo before conducting
experiments that were divided in two parts. The first part involved a
screening experiment of arrow samples, where cluster analysis was
conducted to choose five representative samples of LED displays. The
second part was a semantic experiment on the display of arrows using
LEDs, where the five representative samples and the selected ten
adjectives were incorporated. Analyzing the results with
Quantification Theory Type I, it was found that among the
composition of arrows, fletching was the most significant factor that
influenced the adjectives. In contrast, a “no fletching” design was
more abstract and vague. It lacked the ability to convey the intended
message and might bear psychological negative connotation including
“dangerous,” “forbidden,” and “unreliable.” The arrow design
consisting of “> shaped fletching” was found to be more concrete and
definite, showing positive connotation including “safe,” “cautious,”
and “reliable.” When a stimulus was placed at a farther distance, the
glare could be significantly reduced; moreover, the visual evaluation
scores would be higher. On the contrary, if the fletching and the shaft
had a similar proportion, looking at the stimuli caused higher
evaluation at a closer distance. The above results will be able to be
applied to the design of traffic arrows by conveying information
definitely and rapidly. In addition, drivers’ safety could be enhanced
by understanding the cause of glare and improving visual
recognizability.
Abstract: This paper proposes rough set models with three
different level knowledge granules in incomplete information system
under tolerance relation by similarity between objects according to
their attribute values. Through introducing dominance relation on the
discourse to decompose similarity classes into three subclasses: little
better subclass, little worse subclass and vague subclass, it dismantles
lower and upper approximations into three components. By using
these components, retrieving information to find naturally hierarchical
expansions to queries and constructing answers to elaborative queries
can be effective. It illustrates the approach in applying rough set
models in the design of information retrieval system to access different
granular expanded documents. The proposed method enhances rough
set model application in the flexibility of expansions and elaborative
queries in information retrieval.
Abstract: Using maximal consistent blocks of tolerance relation
on the universe in incomplete decision table, the concepts of join block
and meet block are introduced and studied. Including tolerance class,
other blocks such as tolerant kernel and compatible kernel of an object
are also discussed at the same time. Upper and lower approximations
based on those blocks are also defined. Default definite decision rules
acquired from incomplete decision table are proposed in the paper. An
incremental algorithm to update default definite decision rules is
suggested for effective mining tasks from incomplete decision table
into which data is appended. Through an example, we demonstrate
how default definite decision rules based on maximal consistent
blocks, join blocks and meet blocks are acquired and how optimization
is done in support of discernibility matrix and discernibility function
in the incomplete decision table.
Abstract: This paper presents the benchmarking results and
performance evaluation of differentclustersbuilt atthe National Center
for High-Performance Computingin Taiwan. Performance of
processor, memory subsystem andinterconnect is a critical factor in the
overall performance of high performance computing platforms. The
evaluation compares different system architecture and software
platforms. Most supercomputer used HPL to benchmark their system
performance, in accordance with the requirement of the TOP500 List.
In this paper we consider system memory access factors that affect
benchmark performance, such as processor and memory
performance.We hope these works will provide useful information for
future development and construct cluster system.