Abstract: The inability to implement the principles of good
corporate governance (GCG) as demonstrated in the surveys is due to
a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming
from the structure of ownership. The issues in the internal constraints
mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to
achieve its goal to successfully implement GCG principles since it is
not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate
and leadership style of the top management.
To prove the correlation between internal function of organization
(in this case ethical work climate and transformational leadership)
and the successful implementation of GCG principles, this study
proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and
nineteen are private companies. These thirty corporations are listed in
the Jakarta Stock Exchange. All state-owned companies in the
samples are those which have been privatized.
The research showed that internal function of organization give
support to the successful implementation of GCG principle. In this
research we can prove that : (i) ethical work climate has positive
significance of correlation with the successful implementation of
social awareness principle (one of principles on GCG) and, (ii) only
at the state-owned companies, transformational leadership have
positive significance effect to forming the ethical work climate.
Abstract: This study reports an empirical investigation of
fatigue crack initiation and propagation in 2024 T351 aluminium
alloy using constant amplitude loading. In initiation stage, local
strain approach at the notch was used and in stable propagation stage
NASGRO model was applied.
In this investigation, the flat plate of double through crack at hole
is used. Based on experimental results (AFGROW Database), effect
of stress ratio, R, is highlights on fatigue initiation life (FIL) and
fatigue crack growth rate (FCGR). The increasing of dimension of
hole characterizing the notch effect decrease the fatigue life.
Abstract: Team distillation assisted by microwave extraction
(SDAM) considered as accelerated technique extraction is a
combination of microwave heating and steam distillation, performed
at atmospheric pressure. SDAM has been compared with the same
technique coupled with the cryogrinding of seeds (SDAM -CG).
Isolation and concentration of volatile compounds are performed by a
single stage for the extraction of essential oil from Cuminum
cyminum seeds. The essential oils extracted by these two methods for
5 min were quantitatively (yield) and qualitatively (aromatic profile)
no similar. These methods yield an essential oil with higher amounts
of more valuable oxygenated compounds, and allow substantial
savings of costs, in terms of time, energy and plant material. SDAM
and SDAM-CG is a green technology and appears as a good
alternative for the extraction of essential oils from aromatic plants.
Abstract: In this paper, real-coded genetic algorithm (RCGA) optimization technique has been applied for large-scale linear dynamic multi-input-multi-output (MIMO) system. The method is based on error minimization technique where the integral square error between the transient responses of original and reduced order models has been minimized by RCGA. The reduction procedure is simple computer oriented and the approach is comparable in quality with the other well-known reduction techniques. Also, the proposed method guarantees stability of the reduced model if the original high-order MIMO system is stable. The proposed approach of MIMO system order reduction is illustrated with the help of an example and the results are compared with the recently published other well-known reduction techniques to show its superiority.
Abstract: A spanning tree of a connected graph is a tree which
consists the set of vertices and some or perhaps all of the edges from
the connected graph. In this paper, a model for spanning tree
transformation of connected graphs into single-row networks, namely
Spanning Tree of Connected Graph Modeling (STCGM) will be
introduced. Path-Growing Tree-Forming algorithm applied with
Vertex-Prioritized is contained in the model to produce the spanning
tree from the connected graph. Paths are produced by Path-Growing
and they are combined into a spanning tree by Tree-Forming. The
spanning tree that is produced from the connected graph is then
transformed into single-row network using Tree Sequence Modeling
(TSM). Finally, the single-row routing problem is solved using a
method called Enhanced Simulated Annealing for Single-Row
Routing (ESSR).
Abstract: The problem addressed herein is the efficient management of the Grid/Cluster intense computation involved, when the preconditioned Bi-CGSTAB Krylov method is employed for the iterative solution of the large and sparse linear system arising from the discretization of the Modified Helmholtz-Dirichlet problem by the Hermite Collocation method. Taking advantage of the Collocation ma-trix's red-black ordered structure we organize efficiently the whole computation and map it on a pipeline architecture with master-slave communication. Implementation, through MPI programming tools, is realized on a SUN V240 cluster, inter-connected through a 100Mbps and 1Gbps ethernet network,and its performance is presented by speedup measurements included.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool developed to a more complex concept of
structural risk minimization (SRM). In this paper, SVM is
applied to signal detection in communication systems in the
presence of channel noise in various environments in the form
of Rayleigh fading, additive white Gaussian background noise
(AWGN), and interference noise generalized as additive color
Gaussian noise (ACGN). The structure and performance of
SVM in terms of the bit error rate (BER) metric is derived and
simulated for these advanced stochastic noise models and the
computational complexity of the implementation, in terms of
average computational time per bit, is also presented. The
performance of SVM is then compared to conventional binary
signaling optimal model-based detector driven by binary
phase shift keying (BPSK) modulation. We show that the
SVM performance is superior to that of conventional matched
filter-, innovation filter-, and Wiener filter-driven detectors,
even in the presence of random Doppler carrier deviation,
especially for low SNR (signal-to-noise ratio) ranges. For
large SNR, the performance of the SVM was similar to that of
the classical detectors. However, the convergence between
SVM and maximum likelihood detection occurred at a higher
SNR as the noise environment became more hostile.
Abstract: Capacitive electrocardiogram (ECG) measurement is an attractive approach for long-term health monitoring. However, there is little literature available on its implementation, especially for multichannel system in standard ECG leads. This paper begins from the design criteria for capacitive ECG measurement and presents a multichannel limb-lead capacitive ECG system with conductive fabric tapes pasted on a double layer PCB as the capacitive sensors. The proposed prototype system incorporates a capacitive driven-body (CDB) circuit to reduce the common-mode power-line interference (PLI). The presented prototype system has been verified to be stable by theoretic analysis and practical long-term experiments. The signal quality is competitive to that acquired by commercial ECG machines. The feasible size and distance of capacitive sensor have also been evaluated by a series of tests. From the test results, it is suggested to be greater than 60 cm2 in sensor size and be smaller than 1.5 mm in distance for capacitive ECG measurement.
Abstract: Flexible Job Shop Problem (FJSP) is an extension of
classical Job Shop Problem (JSP). The FJSP extends the routing
flexibility of the JSP, i.e assigning machine to an operation. Thus it
makes it more difficult than the JSP. In this study, Cooperative Coevolutionary
Genetic Algorithm (CCGA) is presented to solve the
FJSP. Makespan (time needed to complete all jobs) is used as the
performance evaluation for CCGA. In order to test performance and
efficiency of our CCGA the benchmark problems are solved.
Computational result shows that the proposed CCGA is comparable
with other approaches.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: One field experiment was conducted on corn (Zea
mays L.Var. SC 704) to study the effect of three different basic levels
of nitrogen (90, 140and 190 Kg/ha as urea) with 0.01% and 0.02%
pyridoxine pre-sowing seed soaking for 8 hours. Water-soaked seeds
were treated as controled. biomass production was recorded on 45,
70 and 95 days after sowing. Total dry material (TDM), leaf area
index (LAI), crop growth rate (CGR), relative growth rate (RGR) and
net assimilation rate (NAR) was calculated form 45until 95 days after
sowing. Yield and its components such as kernel yield, grain weight,
biologic yield, harvest index and protein percentage was measured at
harvest. In general, 0.02% pyridoxine and 190 Kg pure nitrogen/ha
was shown gave maximum value for growth and yield parameters.
N190 + 0.02 % pyridoxine enhanced seed yield and biologic yield by
57.15% and 62.98% compared to 90kg N and water – soaked
treatment.
Abstract: Thyroid cancer-s overall contribution to the
worldwide cancer burden is relatively small, but incidence rates have increased over the last three decades throughout the world. This trend has been hypothesised to reflect a combination of technological advances enabling increased detection, but also changes in
environmental factors, including population exposure to ionising radiation from fallout, diagnostic tests and treatment for benign and
malignant conditions. The Thyroid dose received apparently shielded
by cerrobend blocks was about 8cGy in 100cGy Expose
Abstract: TELMES project aims to develop a securized
multimedia system devoted to medical consultation teleservices. It
will be finalized with a pilot system for a regional telecenters
network that connects local telecenters, having as support
multimedia platforms. This network will enable the implementation
of complex medical teleservices (teleconsulations, telemonitoring,
homecare, urgency medicine, etc.) for a broader range of patients
and medical professionals, mainly for family doctors and those
people living in rural or isolated regions. Thus, a multimedia,
scalable network, based on modern IT&C paradigms, will result. It
will gather two inter-connected regional telecenters, in Iaşi and
Piteşti, Romania, each of them also permitting local connections of
hospitals, diagnostic and treatment centers, as well as local networks
of family doctors, patients, even educational entities. As
communications infrastructure, we aim to develop a combined fixmobile-
internet (broadband) links. Other possible communication
environments will be GSM/GPRS/3G and radio waves. The
electrocardiogram (ECG) acquisition, internet transmission and
local analysis, using embedded technologies, was already
successfully done for patients- telemonitoring.
Abstract: Diabetes mellitus (DM) is frequently characterized by
autonomic nervous dysfunction. Analysis of heart rate variability
(HRV) has become a popular noninvasive tool for assessing the
activities of autonomic nervous system (ANS). In this paper, changes
in ANS activity are quantified by means of frequency and time
domain analysis of R-R interval variability. Electrocardiograms
(ECG) of 16 patients suffering from DM and of 16 healthy volunteers
were recorded. Frequency domain analysis of extracted normal to
normal interval (NN interval) data indicates significant difference in
very low frequency (VLF) power, low frequency (LF) power and
high frequency (HF) power, between the DM patients and control
group. Time domain measures, standard deviation of NN interval
(SDNN), root mean square of successive NN interval differences
(RMSSD), successive NN intervals differing more than 50 ms (NN50
Count), percentage value of NN50 count (pNN50), HRV triangular
index and triangular interpolation of NN intervals (TINN) also show
significant difference between the DM patients and control group.
Abstract: Stainless steel has been employed in many
engineering applications ranging from pharmaceutical equipment to
piping in the nuclear reactors and storage to chemical products. In
this attempt, simulation of fatigue crack growth based on
experimental results of austenitic stainless steel 304L was presented
using AFGROW code when NASGRO mode laws adopted. Double
through crack at hole specimen is used in this investigation under
constant amplitude loading. Effect of mean stress is highlighted.
Results show that fatigue crack growth rate (FCGR) and fatigue life
were affected by maximum applied load and dimension of hole. An
equivalent of Paris law for this material was estimated.
Abstract: This paper describes a new supervised fusion (hybrid)
electrocardiogram (ECG) classification solution consisting of a new
QRS complex geometrical feature extraction as well as a new version
of the learning vector quantization (LVQ) classification algorithm
aimed for overcoming the stability-plasticity dilemma. Toward this
objective, after detection and delineation of the major events of ECG
signal via an appropriate algorithm, each QRS region and also its
corresponding discrete wavelet transform (DWT) are supposed as
virtual images and each of them is divided into eight polar sectors.
Then, the curve length of each excerpted segment is calculated
and is used as the element of the feature space. To increase the
robustness of the proposed classification algorithm versus noise,
artifacts and arrhythmic outliers, a fusion structure consisting of
five different classifiers namely as Support Vector Machine (SVM),
Modified Learning Vector Quantization (MLVQ) and three Multi
Layer Perceptron-Back Propagation (MLP–BP) neural networks with
different topologies were designed and implemented. The new proposed
algorithm was applied to all 48 MIT–BIH Arrhythmia Database
records (within–record analysis) and the discrimination power of the
classifier in isolation of different beat types of each record was
assessed and as the result, the average accuracy value Acc=98.51%
was obtained. Also, the proposed method was applied to 6 number
of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging
to 20 different records of the aforementioned database (between–
record analysis) and the average value of Acc=95.6% was achieved.
To evaluate performance quality of the new proposed hybrid learning
machine, the obtained results were compared with similar peer–
reviewed studies in this area.
Abstract: Atrial Fibrillation is the most common sustained
arrhythmia encountered by clinicians. Because of the invisible
waveform of atrial fibrillation in atrial activation for human, it is
necessary to develop an automatic diagnosis system. 12-Lead ECG
now is available in hospital and is appropriate for using Independent
Component Analysis to estimate the AA period. In this research, we
also adopt a second-order blind identification approach to transform
the sources extracted by ICA to more precise signal and then we use
frequency domain algorithm to do the classification. In experiment,
we gather a significant result of clinical data.
Abstract: In this paper, we propose an architecture for easily
constructing a robot controller. The architecture is a multi-agent
system which has eight agents: the Man-machine interface, Task
planner, Task teaching editor, Motion planner, Arm controller,
Vehicle controller, Vision system and CG display. The controller has
three databases: the Task knowledge database, the Robot database and
the Environment database. Based on this controller architecture, we
are constructing an experimental power distribution line maintenance
robot system and are doing the experiment for the maintenance tasks,
for example, “Bolt insertion task".
Abstract: Among other factors that characterize satellite communication
channels is their high bit error rate. We present a system for
still image transmission over noisy satellite channels. The system
couples image compression together with error control codes to
improve the received image quality while maintaining its bandwidth
requirements. The proposed system is tested using a high resolution
satellite imagery simulated over the Rician fading channel. Evaluation
results show improvement in overall system including image quality
and bandwidth requirements compared to similar systems with different
coding schemes.
Abstract: The Expert Witness Testimony in the Battered
Woman Syndrome Expert witness testimony (EWT) is a kind of
information given by an expert specialized in the field (here in BWS)
to the jury in order to help the court better understand the case. EWT
does not always work in favor of the battered women. Two main
decision-making models are discussed in the paper: the Mathematical
model and the Explanation model. In the first model, the jurors
calculate ″the importance and strength of each piece of evidence″
whereas in the second model they try to integrate the EWT with the
evidence and create a coherent story that would describe the crime.
The jury often misunderstands and misjudges battered women for
their action (or in this case inaction). They assume that these women
are masochists and accept being mistreated for if a man abuses a
woman constantly, she should and could divorce him or simply leave
at any time. The research in the domain found that indeed, expert
witness testimony has a powerful influence on juror’s decisions thus
its quality needs to be further explored. One of the important factors
that need further studies is a bias called the dispositionist worldview
(a belief that what happens to people is of their own doing). This
kind of attributional bias represents a tendency to think that a
person’s behavior is due to his or her disposition, even when the
behavior is clearly attributed to the situation. Hypothesis The
hypothesis of this paper is that if a juror has a dispositionist
worldview then he or she will blame the rape victim for triggering the
assault. The juror would therefore commit the fundamental
attribution error and believe that the victim’s disposition caused the
rape and not the situation she was in. Methods The subjects in the
study were 500 randomly sampled undergraduate students from
McGill, Concordia, Université de Montréal and UQAM.
Dispositional Worldview was scored on the Dispositionist
Worldview Questionnaire. After reading the Rape Scenarios, each
student was asked to play the role of a juror and answer a
questionnaire consisting of 7 questions about the responsibility,
causality and fault of the victim. Results The results confirm the
hypothesis which states that if a juror has a dispositionist worldview
then he or she will blame the rape victim for triggering the assault.
By doing so, the juror commits the fundamental attribution error
because he will believe that the victim’s disposition, and not the
constraints or opportunities of the situation, caused the rape scenario.