Abstract: Process capability index Cpk is the most widely
used index in making managerial decisions since it provides bounds
on the process yield for normally distributed processes. However,
existent methods for assessing process performance which
constructed by statistical inference may unfortunately lead to fine
results, because uncertainties exist in most real-world applications.
Thus, this study adopts fuzzy inference to deal with testing of Cpk .
A brief score is obtained for assessing a supplier’s process instead of
a severe evaluation.
Abstract: The present study focuses on the discussion over the
parameter of Artificial Neural Network (ANN). Sensitivity analysis is
applied to assess the effect of the parameters of ANN on the prediction
of turbidity of raw water in the water treatment plant. The result shows
that transfer function of hidden layer is a critical parameter of ANN.
When the transfer function changes, the reliability of prediction of
water turbidity is greatly different. Moreover, the estimated water
turbidity is less sensitive to training times and learning velocity than
the number of neurons in the hidden layer. Therefore, it is important to
select an appropriate transfer function and suitable number of neurons
in the hidden layer in the process of parameter training and validation.
Abstract: In this paper motion analysis on a winding
stair-climbing is investigated using our proposed rotational arm type
of robotic wheelchair. For now, the robotic wheelchair is operated in
an open mode to climb winding stairs by a dynamic turning, therefore,
the dynamics model is required to ensure a passenger-s safety.
Equations of motion based on the skid-steering analysis are developed
for the trajectory planning and motion analysis on climbing winding
stairs. Since the robotic wheelchair must climb a winding staircase
stably, the winding trajectory becomes a constraint equation to be
followed, and the Baumgarte-s method is used to solve for the
constrained dynamics equations. Experimental results validate the
behavior of the prototype as it climbs a winding stair.
Abstract: This study investigates the roles of knowledge
acquisition, absorptive capacity, and innovation capability in finance
and manufacturing industries. With 362 valid questionnaires from
manufactures and financial industries in Taiwan, we examine the
relationships between absorptive capacity, knowledge acquisition and
innovation capability using a structural equation model. The results
indicate that absorptive capacity is the mediator between knowledge
acquisition and innovation capability, and that knowledge acquisition
has a positive effect on absorptive capacity.
Abstract: A new code synchronization algorithm is proposed in
this paper for the secondary cell-search stage in wideband CDMA
systems. Rather than using the Cyclically Permutable (CP) code in the
Secondary Synchronization Channel (S-SCH) to simultaneously
determine the frame boundary and scrambling code group, the new
synchronization algorithm implements the same function with less
system complexity and less Mean Acquisition Time (MAT). The
Secondary Synchronization Code (SSC) is redesigned by splitting into
two sub-sequences. We treat the information of scrambling code group
as data bits and use simple time diversity BCH coding for further
reliability. It avoids involved and time-costly Reed-Solomon (RS)
code computations and comparisons. Analysis and simulation results
show that the Synchronization Error Rate (SER) yielded by the new
algorithm in Rayleigh fading channels is close to that of the
conventional algorithm in the standard. This new synchronization
algorithm reduces system complexities, shortens the average
cell-search time and can be implemented in the slot-based cell-search
pipeline. By taking antenna diversity and pipelining correlation
processes, the new algorithm also shows its flexible application in
multiple antenna systems.
Abstract: The study describes chitosan membrane platform
modified with nanostructure pattern which using nanotechnology to
fabricate. The cell-substrate interaction between neuro-2a neuroblasts
cell lines and chitosan membrane (flat, nanostructure and
nanostructure pattern types) was investigated. The adhered
morphology of neuro-2a cells depends on the topography of chitosan
surface. We have found that neuro-2a showed different morphogenesis
when cells adhered on flat and nanostructure chitosan membrane. The
cell projected area of neuro-2a on flat chitosan membrane is larger
than on nanostructure chitosan membrane. In addition, neuro-2a cells
preferred to adhere on flat chitosan surface region than on
nanostructure chitosan membrane to immobilize and differentiation.
The experiment suggests surface topography can be used as a critical
mechanism to isolate group of neuro-2a to a particular rectangle area
on chitosan membrane. Our finding will provide a platform to take
patch clamp to record electrophysiological behavior about neurons in
vitro in the future.
Abstract: With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. However, the acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems. Thus, there is a need to research the factors that affect users- intention to use m-learning. Based on an updated information system (IS) success model, data collected from 350 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The data collected by questionnaire were analyzed to check the validity of constructs. Then hypotheses describing the relationships between the identified constructs and users- satisfaction were formulated and tested.
Abstract: In this paper, low end Digital Signal Processors (DSPs)
are applied to accelerate integer neural networks. The use of DSPs
to accelerate neural networks has been a topic of study for some
time, and has demonstrated significant performance improvements.
Recently, work has been done on integer only neural networks, which
greatly reduces hardware requirements, and thus allows for cheaper
hardware implementation. DSPs with Arithmetic Logic Units (ALUs)
that support floating or fixed point arithmetic are generally more
expensive than their integer only counterparts due to increased circuit
complexity. However if the need for floating or fixed point math
operation can be removed, then simpler, lower cost DSPs can be
used. To achieve this, an integer only neural network is created in
this paper, which is then accelerated by using DSP instructions to
improve performance.
Abstract: In this paper, by employing a new Lyapunov functional
and an elementary inequality analysis technique, some sufficient
conditions are derived to ensure the existence and uniqueness of
periodic oscillatory solution for fuzzy bi-directional memory (BAM)
neural networks with time-varying delays, and all other solutions of
the fuzzy BAM neural networks converge the uniqueness periodic
solution. These criteria are presented in terms of system parameters
and have important leading significance in the design and applications
of neural networks. Moreover an example is given to illustrate the
effectiveness and feasible of results obtained.
Abstract: In this paper, we study the existence, the boundedness and the asymptotic behavior of the positive solutions of a fuzzy nonlinear difference equations xn+1 = A + k i=0 Bi xn-i , n= 0, 1, · · · . where (xn) is a sequence of positive fuzzy numbers, A,Bi and the initial values x-k, x-k+1, · · · , x0 are positive fuzzy numbers. k ∈ {0, 1, 2, · · ·}.
Abstract: This study was conducted to explore the effects of two
countries model comparison program in Taiwan and Singapore in
TIMSS database. The researchers used Multi-Group Hierarchical
Linear Modeling techniques to compare the effects of two different
country models and we tested our hypotheses on 4,046 Taiwan
students and 4,599 Singapore students in 2007 at two levels: the class
level and student (individual) level. Design quality is a class level
variable. Student level variables are achievement and self-confidence.
The results challenge the widely held view that retention has a positive
impact on self-confidence. Suggestions for future research are
discussed.
Abstract: A data cutting and sorting method (DCSM) is proposed
to optimize the performance of data mining. DCSM reduces the
calculation time by getting rid of redundant data during the data
mining process. In addition, DCSM minimizes the computational units
by splitting the database and by sorting data with support counts. In the
process of searching for the relationship between metabolic syndrome
and lifestyles with the health examination database of an electronics
manufacturing company, DCSM demonstrates higher search
efficiency than the traditional Apriori algorithm in tests with different
support counts.