Abstract: Program slicing is the task of finding all statements in
a program that directly or indirectly influence the value of a variable
occurrence. The set of statements that can affect the value of a
variable at some point in a program is called a program backward
slice. In several software engineering applications, such as program
debugging and measuring program cohesion and parallelism, several
slices are computed at different program points. The existing
algorithms for computing program slices are introduced to compute a
slice at a program point. In these algorithms, the program, or the
model that represents the program, is traversed completely or
partially once. To compute more than one slice, the same algorithm
is applied for every point of interest in the program. Thus, the same
program, or program representation, is traversed several times.
In this paper, an algorithm is introduced to compute all forward
static slices of a computer program by traversing the program
representation graph once. Therefore, the introduced algorithm is
useful for software engineering applications that require computing
program slices at different points of a program. The program
representation graph used in this paper is called Program Dependence
Graph (PDG).
Abstract: Structured catalysts formed from the growth of
zeolites on substrates is an area of increasing interest due to the
increased efficiency of the catalytic process, and the ability to
provide superior heat transfer and thermal conductivity for both
exothermic and endothermic processes.
However, the generation of structured catalysts represents a
significant challenge when balancing the relationship variables
between materials properties and catalytic performance, with the
Na2O, H2O and Al2O3 gel composition paying a significant role in
this dynamic, thereby affecting the both the type and range of
application.
The structured catalyst films generated as part of this
investigation have been characterised using a range of techniques,
including X-ray diffraction (XRD), Electron microscopy (SEM),
Energy Dispersive X-ray analysis (EDX) and Thermogravimetric
Analysis (TGA), with the transition from oxide-on-alloy wires to
hydrothermally synthesised uniformly zeolite coated surfaces being
demonstrated using both SEM and XRD. The robustness of the
coatings has been ascertained by subjecting these to thermal cycling
(ambient to 550oC), with the results indicating that the synthesis time
and gel compositions have a crucial effect on the quality of zeolite
growth on the FeCrAlloy wires.
Finally, the activity of the structured catalyst was verified by a
series of comparison experiments with standard zeolite Y catalysts in
powdered pelleted forms.
Abstract: In this work we present a solution for DAGC (Digital
Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4
GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used
enables gain control over Low Noise Amplifier (LNA) and a
Variable Gain Amplifier (VGA). The control over those signals is
performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better
signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the
average power of the baseband signal close to the desired set point.
DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and
actual gain setting, adjusting a gain factor of the accumulation, and
applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying
the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the
DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.
Abstract: We consider power system expansion planning under
uncertainty. In our approach, integer programming and stochastic
programming provide a basic framework. We develop a multistage
stochastic programming model in which some of the variables are
restricted to integer values. By utilizing the special property of the
problem, called block separable recourse, the problem is transformed
into a two-stage stochastic program with recourse. The electric power
capacity expansion problem is reformulated as the problem with first
stage integer variables and continuous second stage variables. The
L-shaped algorithm to solve the problem is proposed.
Abstract: International trade involves both large and small firms
engaged in business overseas. Possible drivers that force companies
to enter international markets include increasing competition at the
domestic market, maturing domestic markets, and limited domestic
market opportunities. Technology is an important driving factor in
shaping international marketing strategy as well as in driving force
towards a more global marketplace, especially technology in
communication. It includes telephones, the internet, computer
systems and e-mail. There are three main marketing strategy choices,
namely standardization approach, adaptation approach and middleof-
the-road approach that companies implement to overseas markets.
The decision depends on situations and factors facing the companies
in the international markets. In this paper, the contingency concept is
considered that no single strategy can be effective in all contexts.
The effect of strategy on performance depends on specific situational
variables. Strategic fit is employed to investigate export marketing
strategy adaptation under certain environmental conditions, which in
turn can lead to superior performance.
Abstract: Due to environmental concerns, the recent regulation on automobile fuel economy has been strengthened. The market demand for efficient vehicles is growing and automakers to improve engine fuel efficiency in the industry have been paying a lot of effort. To improve the fuel efficiency, it is necessary to reduce losses or to improve combustion efficiency of the engine. VVA (Variable Valve Actuation) technology enhances the engine's intake air flow, reduce pumping losses and mechanical friction losses. And also, VVA technology is the engine's low speed and high speed operation to implement each of appropriate valve lift. It improves the performance of engine in the entire operating range. This paper presents a design procedure of DC motor and drive for VVA system and shows the validity of the design result by experimental result with prototype.
Abstract: the data of Taiwanese 8th grader in the 4th cycle of
Trends in International Mathematics and Science Study (TIMSS) are
analyzed to examine the influence of the science teachers- preference
in experimental teaching on the relationships between the affective
variables ( the perceived usefulness of science, ease of using science
and science learning interest) and the academic achievement in science.
After dealing with the missing data, 3711 students and 145 science
teacher-s data were analyzed through a Hierarchical Linear Modeling
technique. The major objective of this study was to determine the role
of the experimental teaching moderates the relationship between
perceived usefulness and achievement.
Abstract: How to maintain the service speeds for the business
to make the biggest profit is a problem worthy of study, which is
discussed in this paper with the use of queuing theory. An M/M/1/N
queuing model with variable input rates, variable service rates and
impatient customers is established, and the following conclusions
are drawn: the stationary distribution of the model, the relationship
between the stationary distribution and the probability that there are n
customers left in the system when a customer leaves (not including
the customer who leaves himself), the busy period of the system,
the average operating cycle, the loss probability for the customers
not entering the system while they arriving at the system, the mean
of the customers who leaves the system being for impatient, the
loss probability for the customers not joining the queue due to the
limited capacity of the system and many other indicators. This paper
also indicates that the following conclusion is not correct: the more
customers the business serve, the more profit they will get. At last,
this paper points out the appropriate service speeds the business
should keep to make the biggest profit.
Abstract: This study had two goals. First, it investigated marital
interaction variables as predictors of treatment outcome in panic
disorder with agoraphobia (PDA) in sixty-five couples with one
spouse suffering from PDA. Second, it analyzed the impact of PDA
improvement, following therapy, on marital interaction patterns of
both spouses. The partners were observed during a problem-solving
task, before and after treatment. Negative behaviors at the outset of
therapy, both in the PDA and the NPDA partners, predicted less
improvement at post-test. It also appears that improvement in some
PDA symptoms following therapy is linked to increase in the
dominant behavior of the NPDA spouse and to an improvement in
terms of his intrusiveness.
Abstract: In this paper we present a Adaptive Neuro-Fuzzy
System (ANFIS) with inputs the lagged dependent variable for the
prediction of Gross domestic Product growth rate in six countries.
We compare the results with those of Autoregressive (AR) model.
We conclude that the forecasting performance of neuro-fuzzy-system
in the out-of-sample period is much more superior and can be a very
useful alternative tool used by the national statistical services and the
banking and finance industry.
Abstract: Let {Xi}i≥1 be a martingale difference sequence with
Xi = Si - Si-1. Under some regularity conditions, we show that
(X2
1+· · ·+X2N
n)-1/2SNn is asymptotically normal, where {Ni}i≥1
is a sequence of positive integer-valued random variables tending
to infinity. In a similar manner, a backward (or reverse) martingale
central limit theorem with random indices is provided.
Abstract: In practice, we often come across situations where it is
necessary to make decisions based on incomplete or uncertain data.
In control systems it may be due to the unknown exact mathematical
model, or its excessive complexity (e.g. nonlinearity) when it is
necessary to simplify it, respectively, to solve it using a rule base. In
the case of databases, searching data we compare a similarity
measure with of the requirements of the selection with stored data,
where both the select query and the data itself may contain vague
terms, for example in the form of linguistic qualifiers. In this paper,
we focus on the processing of uncertain data in databases and
demonstrate it on the example multi-criteria decision making in the
selection of variants, specified by higher number of technical
parameters.
Abstract: Numerical studies on race car aerodynamics at wing
in ground effect have been carried out using a steady 3d, double
precision, pressure-based, and standard k-epsilon turbulence model.
Through various parametric analytical studies we have observed that
at a particular speed and ground clearance of the wings a favorable
negative lift was found high at a particular angle of attack for all the
physical models considered in this paper. The fact is that if the
ground clearance height to chord length (h/c) is too small, the
developing boundary layers from either side (the ground and the
lower surface of the wing) can interact, leading to an altered variation
of the aerodynamic characteristics at wing in ground effect. Therefore
a suitable ground clearance must be predicted throughout the racing
for a better performance of the race car, which obviously depends
upon the coupled effects of the topography, wing orientation with
respect to the ground, the incoming flow features and/or the race car
speed. We have concluded that for the design of high performance
and high speed race cars the adjustable wings capable to alter the
ground clearance and the angles of attack is the best design option for
any race car for racing safely with variable speeds.
Abstract: Hospital staff and managers are under pressure and
concerned for effective use and management of scarce resources. The
hospital admissions require many decisions that have complex and
uncertain consequences for hospital resource utilization and patient
flow. It is challenging to predict risk of admissions and length of stay
of a patient due to their vague nature. There is no method to capture
the vague definition of admission of a patient. Also, current methods
and tools used to predict patients at risk of admission fail to deal with
uncertainty in unplanned admission, LOS, patients- characteristics.
The main objective of this paper is to deal with uncertainty in
health system variables, and handles uncertain relationship among
variables. An introduction of machine learning techniques along with
statistical methods like Regression methods can be a proposed
solution approach to handle uncertainty in health system variables. A
model that adapts fuzzy methods to handle uncertain data and
uncertain relationships can be an efficient solution to capture the
vague definition of admission of a patient.
Abstract: Strong law of large numbers and complete convergence for sequences of *-mixing random variables are investigated. In particular, Teicher-s strong law of large numbers for independent random variables are generalized to the case of *-mixing random sequences and extended to independent and identically distributed Marcinkiewicz Law of large numbers for *-mixing.
Abstract: To respond to the Kyoto Protocol, the policy of Payment for Environmental Service (PES), which was entitled “Plain Landscape Afforestation Program (PLAP)", was certified by Executive Yuan in Taiwan on 31 August 2001 and has been implementing for six years since 1 January 2002. Although the PLAP has received a lot of positive comments, there are still many difficulties during the process of implementation, such as insufficient technology for afforestation, private landowners- low interests in participating in PLAP, insufficient subsidies, and so on, which are potential threats that hinder the PLAP from moving forward in future. In this paper, selecting Ping-Tung County in Taiwan as a sample region and targeting those private landowners with and without intention to participate in the PLAP, respectively, we conduct an empirical analysis based on the Logit model to investigate the factors that determine whether those private landowners join the PLAP, so as to realize the incentive effects of the PLAP upon the personal decision on afforestation. The possible factors that might determine private landowner-s participation in the PLAP include landowner-s characteristics, cropland characteristics, as well as policy factors. Among them, the policy factors include afforestation subsidy amount (+), duration of afforestation subsidy (+), the rules on adjoining and adjacent areas (+), and so on, which do not reach the remarkable level in statistics though, but the directions of variable signs are consistent with the intuition behind the policy. As for the landowners- characteristics, each of age (+), education level (–), and annual household income (+) variables reaches 10% of the remarkable level in statistics; as for the cropland characteristics, each of cropland area (+), cropland price (–), and the number of cropland parcels (–) reaches 1% of the remarkable level in statistics. In light of the above, the cropland characteristics are the dominate factor that determines the probability of landowner-s participation in the PLAP. In the Logit model established by this paper, the probability of correctly estimating nonparticipants is 98%, the probability of correctly estimating the participants is 71.8%, and the probability for the overall estimation is 95%. In addition, Hosmer-Lemeshow test and omnibus test also revealed that the Logit model in this paper may provide fine goodness of fit and good predictive power in forecasting private landowners- participation in this program. The empirical result of this paper expects to help the implementation of the afforestation programs in Taiwan.
Abstract: This paper features the modeling and design of a
Robust Decentralized Fast Output Sampling (RDFOS) Feedback
control technique for the active vibration control of a smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminium beam. Using model
order reduction technique, the reduced order model of the higher
order system is obtained based on dominant Eigen value retention
and the Davison technique. RDFOS feedback controllers are
designed for the above 5 multivariable-multimodel plant. The closed
loop responses with the RDFOS feedback gain and the magnitudes of
the control input are obtained and the performance of the proposed
multimodel smart structure system is evaluated for vibration control.
Abstract: This study was carried out to reveal the bacterial composition of aerosol in the studied abattoirs. Bacteria isolated were characterized according to microbiological standards. Factors such as temperature and distance were considered as variable in this study. The isolation was carried out at different temperatures such as 27oC, 31oC and 29oC and at various distances of 100meters and 200meters away from the slaughter sites. Result obtained showed that strains of Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Lactobacillus alimentarius and Micrococcus sp. were identified. The total viable counts showed that more microorganisms were present in the morning while the least viable count of 388cfu was recorded in the evening period of this study. This study also showed that more microbial loads were recorded the further the distance is to the slaughter site. Conclusively, the array of bacteria isolated suggests that abattoir sites may be a potential source of pathogenic organisms to commuters if located within residential environment.
Abstract: In the Equivalent Transformation (ET) computation
model, a program is constructed by the successive accumulation of
ET rules. A method by meta-computation by which a correct ET
rule is generated has been proposed. Although the method covers a
broad range in the generation of ET rules, all important ET rules
are not necessarily generated. Generation of more ET rules can be
achieved by supplementing generation methods which are specialized
for important ET rules. A Specialization-by-Equation (Speq) rule is
one of those important rules. A Speq rule describes a procedure in
which two variables included in an atom conjunction are equalized
due to predicate constraints. In this paper, we propose an algorithm
that systematically and recursively generate Speq rules and discuss
its effectiveness in the synthesis of ET programs. A Speq rule is
generated based on proof of a logical formula consisting of given
atom set and dis-equality. The proof is carried out by utilizing some
ET rules and the ultimately obtained rules in generating Speq rules.
Abstract: One of the essential sectors of Myanmar economy is
agriculture which is sensitive to climate variation. The most
important climatic element which impacts on agriculture sector is
rainfall. Thus rainfall prediction becomes an important issue in
agriculture country. Multi variables polynomial regression (MPR)
provides an effective way to describe complex nonlinear input output
relationships so that an outcome variable can be predicted from the
other or others. In this paper, the modeling of monthly rainfall
prediction over Myanmar is described in detail by applying the
polynomial regression equation. The proposed model results are
compared to the results produced by multiple linear regression model
(MLR). Experiments indicate that the prediction model based on
MPR has higher accuracy than using MLR.