Abstract: This paper presents positive and negative full-wave
rectifier. The proposed structure is based on OTA using
commercially available ICs (LT1228). The features of the proposed
circuit are that: it can rectify and amplify voltage signal with
controllable output magnitude via input bias current: the output
voltage is free from temperature variation. The circuit description
merely consists of 1 single ended and 3 fully differential OTAs. The
performance of the proposed circuit are investigated though PSpice.
They show that the proposed circuit can function as positive/negative
full-wave rectifier, where the voltage input wide-dynamic range from
-5V to 5V. Furthermore, the output voltage is slightly dependent on
the temperature variations.
Abstract: Smith Predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system and very sensitive to uncertain system with variable time-delay. In this paper is concerned with a design method of smith predictor for temperature control system by Coefficient Diagram Method (CDM). The simulation results show that the control system with smith predictor design by CDM is stable and robust whilst giving the desired time domain system performance.
Abstract: The aim of the study was to identify seat belt wearing
factor among road users in Malaysia. Evidence-based approach
through in-depth crash investigation was utilised to determine the
intended objectives. The objective was scoped into crashes
investigated by Malaysian Institute of Road Safety Research
(MIROS) involving passenger vehicles within 2007 and 2010. Crash
information of a total of 99 crash cases involving 240 vehicles and
864 occupants were obtained during the study period. Statistical test
and logistic regression analysis have been performed. Results of the
analysis revealed that gender, seat position and age were associated
with seat belt wearing compliance in Malaysia. Males are 97.6%
more likely to wear seat belt compared to females (95% CI 1.317 to
2.964). By seat position, the finding indicates that frontal occupants
were 82 times more likely to be wearing seat belt (95% CI 30.199 to
225.342) as compared to rear occupants. It is also important to note
that the odds of seat belt wearing increased by about 2.64% (95% CI
1.0176 to 1.0353) for every one year increase in age. This study is
essential in understanding the Malaysian tendency in belting up
while being occupied in a vehicle. The factors highlighted in this
study should be emphasized in road safety education in order to
increase seat belt wearing rate in this country and ultimately in
preventing deaths due to road crashes.
Abstract: This paper proposes a low power SRAM based on
five transistor SRAM cell. Proposed SRAM uses novel word-line
decoding such that, during read/write operation, only selected cell
connected to bit-line whereas, in conventional SRAM (CV-SRAM),
all cells in selected row connected to their bit-lines, which in turn
develops differential voltages across all bit-lines, and this makes
energy consumption on unselected bit-lines. In proposed SRAM
memory array divided into two halves and this causes data-line
capacitance to reduce. Also proposed SRAM uses one bit-line and
thus has lower bit-line leakage compared to CV-SRAM.
Furthermore, the proposed SRAM incurs no area overhead, and has
comparable read/write performance versus the CV-SRAM.
Simulation results in standard 0.25μm CMOS technology shows in
worst case proposed SRAM has 80% smaller dynamic energy
consumption in each cycle compared to CV-SRAM. Besides, energy
consumption in each cycle of proposed SRAM and CV-SRAM
investigated analytically, the results of which are in good agreement
with the simulation results.
Abstract: This paper presents an application of 5S lean technology to a production facility. Due to increased demand, high product variety, and a push production system, the plant has suffered from excessive wastes, unorganized workstations, and unhealthy work environment. This has translated into increased production cost, frequent delays, and low workers morale. Under such conditions, it has become difficult, if not impossible, to implement effective continuous improvement studies. Hence, the lean project is aimed at diagnosing the production process, streamlining the workflow, removing/reducing process waste, cleaning the production environment, improving plant layout, and organizing workstations. 5S lean technology is utilized for achieving project objectives. The work was a combination of both culture changes and tangible/physical changes on the shop floor. The project has drastically changed the plant and developed the infrastructure for a successful implementation of continuous improvement as well as other best practices and quality initiatives.
Abstract: Due to the environmental and price issues of current
energy crisis, scientists and technologists around the globe are
intensively searching for new environmentally less-impact form of
clean energy that will reduce the high dependency on fossil fuel.
Particularly hydrogen can be produced from biomass via thermochemical
processes including pyrolysis and gasification due to the
economic advantage and can be further enhanced through in-situ
carbon dioxide removal using calcium oxide. This work focuses on
the synthesis and development of the flowsheet for the enhanced
biomass gasification process in PETRONAS-s iCON process
simulation software. This hydrogen prediction model is conducted at
operating temperature between 600 to 1000oC at atmospheric
pressure. Effects of temperature, steam-to-biomass ratio and
adsorbent-to-biomass ratio were studied and 0.85 mol fraction of
hydrogen is predicted in the product gas. Comparisons of the results
are also made with experimental data from literature. The
preliminary economic potential of developed system is RM 12.57 x
106 which equivalent to USD 3.77 x 106 annually shows economic
viability of this process.
Abstract: With major technological advances and to reduce the
cost of training apprentices for real-time critical systems, it was
necessary the development of Intelligent Tutoring Systems for
training apprentices in these systems. These systems, in general, have
interactive features so that the learning is actually more efficient,
making the learner more familiar with the mechanism in question. In
the home stage of learning, tests are performed to obtain the student's
income, a measure on their use. The aim of this paper is to present a
framework to model an Intelligent Tutoring Systems using the UML
language. The various steps of the analysis are considered the
diagrams required to build a general model, whose purpose is to
present the different perspectives of its development.
Abstract: Clustering large populations is an important problem
when the data contain noise and different shapes. A good clustering
algorithm or approach should be efficient enough to detect clusters
sensitively. Besides space complexity, time complexity also gains
importance as the size grows. Using hierarchies we developed a new
algorithm to split attributes according to the values they have and
choosing the dimension for splitting so as to divide the database
roughly into equal parts as much as possible. At each node we
calculate some certain descriptive statistical features of the data
which reside and by pruning we generate the natural clusters with a
complexity of O(n).
Abstract: Information regarding early onset neonatal sepsis
(EONS) pathogens may vary between regions. Global perspectives
showed Group B Streptococcal (GBS) as the most common causative
pathogens, but the widespread use of intrapartum antibiotics has
changed the pathogens pattern towards gram negative
microorganisms, especially E. coli. Objective of this study is to
describe the pathogens isolated, to assess current treatment and risk
of EONS. Records of 899 neonates born in three General Hospitals
between 2009 until 2012 were retrospectively reviewed. Proven was
found in 22 (3%) neonates. The majority was isolated with gram
positive organisms, 17 (2.3%). All grams positive and most gram
negative organisms showed sensitivity to the tested antibiotics. Only
two rare gram negative organisms showed total resistant. Male was
possible risk of proven EONS. Although proven EONS remains
uncommon in Malaysia, nonetheless, the effect of intrapartum
antibiotics still required continuous surveillance.
Abstract: This paper presents the effects of migration at the
urban sites with an integrated model under the sustainable local
development policies for the conservation and revitalization of the
site areas as a case at Reyhan heritage site in Bursa. It is known as
the “City of immigrants" because of its richness of cultural plurality.
The city has always regarded the dynamic impact of immigration as a
positive contribution. As a result of this situation, the city created the
earliest urbanization practices: being the first capital city of the
Ottoman Empire. Bursa created the first modern movement practices
and set the first Organized Industrial Zone. The most important aim
of the study is to be offer a model for the similar areas with the
context of conservation and revitalization of the historical areas,
subjected to the local integrated sustainable development policies of
local goverments.
Abstract: This paper attempts to establish the fact that Multi
State Network Classification is essential for performance
enhancement of Transport protocols over Satellite based Networks. A
model to classify Multi State network condition taking into
consideration both congestion and channel error is evolved. In order
to arrive at such a model an analysis of the impact of congestion and
channel error on RTT values has been carried out using ns2. The
analysis results are also reported in the paper. The inference drawn
from this analysis is used to develop a novel statistical RTT based
model for multi state network classification.
An Adaptive Multi State Proactive Transport Protocol consisting
of Proactive Slow Start, State based Error Recovery, Timeout Action
and Proactive Reduction is proposed which uses the multi state
network state classification model. This paper also confirms through
detail simulation and analysis that a prior knowledge about the
overall characteristics of the network helps in enhancing the
performance of the protocol over satellite channel which is
significantly affected due to channel noise and congestion.
The necessary augmentation of ns2 simulator is done for
simulating the multi state network classification logic. This
simulation has been used in detail evaluation of the protocol under
varied levels of congestion and channel noise. The performance
enhancement of this protocol with reference to established protocols
namely TCP SACK and Vegas has been discussed. The results as
discussed in this paper clearly reveal that the proposed protocol
always outperforms its peers and show a significant improvement in
very high error conditions as envisaged in the design of the protocol.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.
Abstract: The model-based approach to user interface design relies on developing separate models that are capturing various aspects about users, tasks, application domain, presentation and dialog representations. This paper presents a task modeling approach for user interface design and aims at exploring the mappings between task, domain and presentation models. The basic idea of our approach is to identify typical configurations in task and domain models and to investigate how they relate each other. A special emphasis is put on application-specific functions and mappings between domain objects and operational task structures. In this respect, we will distinguish between three layers in the task decomposition: a functional layer, a planning layer, and an operational layer.
Abstract: This paper describes a complex energy signal model
that is isomorphic with digital human fingerprint images. By using
signal models, the problem of fingerprint matching is transformed
into the signal processing problem of finding a correlation between
two complex signals that differ by phase-rotation and time-scaling. A
technique for minutiae matching that is independent of image
translation, rotation and linear-scaling, and is resistant to missing
minutiae is proposed. The method was tested using random data
points. The results show that for matching prints the scaling and
rotation angles are closely estimated and a stronger match will have a
higher correlation.
Abstract: A mathematical model of the respiratory system is
introduced in this study. Geometrical dimensions of the respiratory
system were used to compute the acoustic properties of the
respiratory system using the electro-acoustic analogy. The effect of
the geometrical proportions of the respiratory system is observed in
the paper.
Abstract: Image-based Rendering(IBR) techniques recently
reached in broad fields which leads to a critical challenge to build up
IBR-Driven visualization platform where meets requirement of high
performance, large bounds of distributed visualization resource
aggregation and concentration, multiple operators deploying and
CSCW design employing. This paper presents an unique IBR-based
visualization dataflow model refer to specific characters of IBR
techniques and then discusses prominent feature of IBR-Driven
distributed collaborative visualization (DCV) system before finally
proposing an novel prototype. The prototype provides a well-defined
three level modules especially work as Central Visualization Server,
Local Proxy Server and Visualization Aid Environment, by which
data and control for collaboration move through them followed the
previous dataflow model. With aid of this triple hierarchy architecture
of that, IBR oriented application construction turns to be easy. The
employed augmented collaboration strategy not only achieve
convenient multiple users synchronous control and stable processing
management, but also is extendable and scalable.
Abstract: This paper presents the design of a ring-shaped tri-axial fore sensor that can be incorporated into the tip of a guidewire for use in minimally invasive surgery (MIS). The designed sensor comprises a ring-shaped structure located at the center of four cantilever beams. The ringdesign allows surgical tools to be easily passed through which largely simplified the integration process. Silicon nanowires (SiNWs) are used aspiezoresistive sensing elementsembeddedon the four cantilevers of the sensor to detect the resistance change caused by the applied load.An integration scheme with new designed guidewire tip structure having two coils at the distal end is presented. Finite element modeling has been employed in the sensor design to find the maximum stress location in order to put the SiNWs at the high stress regions to obtain maximum output. A maximum applicable force of 5 mN is found from modeling. The interaction mechanism between the designed sensor and a steel wire has been modeled by FEM. A linear relationship between the applied load on the steel wire and the induced stress on the SiNWs were observed.
Abstract: A new algorithm called Character-Comparison to Character-Access (CCCA) is developed to test the effect of both: 1) converting character-comparison and number-comparison into character-access and 2) the starting point of checking on the performance of the checking operation in string searching. An experiment is performed using both English text and DNA text with different sizes. The results are compared with five algorithms, namely, Naive, BM, Inf_Suf_Pref, Raita, and Cycle. With the CCCA algorithm, the results suggest that the evaluation criteria of the average number of total comparisons are improved up to 35%. Furthermore, the results suggest that the clock time required by the other algorithms is improved in range from 22.13% to 42.33% by the new CCCA algorithm.
Abstract: In this paper newly reported Cosh window function is
used in the design of prototype filter for M-channel Near Perfect
Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). Local
search optimization algorithm is used for minimization of distortion
parameters by optimizing the filter coefficients of prototype filter.
Design examples are presented and comparison has been made with
Kaiser window based filterbank design of recently reported work.
The result shows that the proposed design approach provides lower
distortion parameters and improved far-end suppression than the
Kaiser window based design of recent reported work.