Abstract: Studies have shown that the SnAgCu solder family has been widely used as a replacement for conventional Sn-Pb solders. An attractive approach is by introducing alloying additives (rare earth elements (RE), Zn, Co, Fe, Ni, Sb) into the SnAgCu solder, which helps in refining the microstructure also improving the mechanical and wetting properties of the solder. The present work focuses on the effect of additions of 0.5% Ce and Fe into Sn-3.0Ag-0.5Cu solder, in attempt to reduce the intermetallic compound (IMC) growth and reflow properties of the solder on Cu and Ni (P) surface finish, as well as effects thermal aging on the formation of intermetallic compound (IMC) on different surface finish. Excessive intermetallic compound growth may effect the interface and solder joint due to the brittle nature of the intermetallic compounds. Thus, by introducing alloying elements, IMC layer thickness can be decrease, resulting in better joint and solder reliability.
Abstract: The Requirements Abstraction Model (RAM) helps in managing abstraction in requirements by organizing them at four levels (product, feature, function and component). The RAM is adaptable and can be tailored to meet the needs of the various organizations. Because software requirements are an important source of information for developing high-level tests, organizations willing to adopt the RAM model need to know the suitability of the RAM requirements for developing high-level tests. To investigate this suitability, test cases from twenty randomly selected requirements were developed, analyzed and graded. Requirements were selected from the requirements document of a Course Management System, a web based software system that supports teachers and students in performing course related tasks. This paper describes the results of the requirements document analysis. The results show that requirements at lower levels in the RAM are suitable for developing executable tests whereas it is hard to develop from requirements at higher levels.
Abstract: This paper presents an approach for the design of
fuzzy logic power system stabilizers using genetic algorithms. In the
proposed fuzzy expert system, speed deviation and its derivative
have been selected as fuzzy inputs. In this approach the parameters of
the fuzzy logic controllers have been tuned using genetic algorithm.
Incorporation of GA in the design of fuzzy logic power system
stabilizer will add an intelligent dimension to the stabilizer and
significantly reduces computational time in the design process. It is
shown in this paper that the system dynamic performance can be
improved significantly by incorporating a genetic-based searching
mechanism. To demonstrate the robustness of the genetic based
fuzzy logic power system stabilizer (GFLPSS), simulation studies on
multimachine system subjected to small perturbation and three-phase
fault have been carried out. Simulation results show the superiority
and robustness of GA based power system stabilizer as compare to
conventionally tuned controller to enhance system dynamic
performance over a wide range of operating conditions.
Abstract: Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system - the central processing unit (CPU) of computers. The quantity of organization for several generations of CPUs shows a double exponential rate of change of organization with time. The exact functional dependence has a fine, S-shaped structure, revealing some of the mechanisms of self-organization. The principle of least action helps to explain the mechanism of increase of organization through quantity accumulation and constraint and curvature minimization with an attractor, the least average sum of actions of all elements and for all motions. This approach can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self organization to improve their quality. It can be applied to other complex systems from Physics, Chemistry, Biology, Ecology, Economics, Cities, network theory and others where complex systems are present.
Abstract: Segmenting the lungs in medical images is a
challenging and important task for many applications. In particular,
automatic segmentation of lung cavities from multiple magnetic
resonance (MR) images is very useful for oncological applications
such as radiotherapy treatment planning. However, distinguishing of
the lung areas is not trivial due to largely changing lung shapes, low
contrast and poorly defined boundaries. In this paper, we address
lung segmentation problem from pulmonary magnetic resonance
images and propose an automated method based on a robust regionaided
geometric snake with a modified diffused region force into the
standard geometric model definition. The extra region force gives the
snake a global complementary view of the lung boundary
information within the image which along with the local gradient
flow, helps detect fuzzy boundaries. The proposed method has been
successful in segmenting the lungs in every slice of 30 magnetic
resonance images with 80 consecutive slices in each image. We
present results by comparing our automatic method to manually
segmented lung cavities provided by an expert radiologist and with
those of previous works, showing encouraging results and high
robustness of our approach.
Abstract: In this paper we present the deep study about the Bio-
Medical Images and tag it with some basic extracting features (e.g.
color, pixel value etc). The classification is done by using a nearest
neighbor classifier with various distance measures as well as the
automatic combination of classifier results. This process selects a
subset of relevant features from a group of features of the image. It
also helps to acquire better understanding about the image by
describing which the important features are. The accuracy can be
improved by increasing the number of features selected. Various
types of classifications were evolved for the medical images like
Support Vector Machine (SVM) which is used for classifying the
Bacterial types. Ant Colony Optimization method is used for optimal
results. It has high approximation capability and much faster
convergence, Texture feature extraction method based on Gabor
wavelets etc..
Abstract: The most influential programming paradigm today
is object oriented (OO) programming and it is widely used in
education and industry. Recognizing the importance of equipping
students with OO knowledge and skills, it is not surprising that most
Computer Science degree programs offer OO-related courses. How
do we assess whether the students have acquired the right objectoriented
skills after they have completed their OO courses? What are
object oriented skills? Currently none of the current assessment
techniques would be able to provide this answer. Traditional forms of
OO programming assessment provide a ways for assigning numerical
scores to determine letter grades. But this rarely reveals information
about how students actually understand OO concept. It appears
reasonable that a better understanding of how to define and assess
OO skills is needed by developing a criterion referenced model. It is
even critical in the context of Malaysia where there is currently a
growing concern over the level of competency of Malaysian IT
graduates in object oriented programming. This paper discussed the
approach used to develop the criterion-referenced assessment model.
The model can serve as a guideline when conducting OO
programming assessment as mentioned. The proposed model is
derived by using Goal Questions Metrics methodology, which helps
formulate the metrics of interest. It concluded with a few suggestions
for further study.
Abstract: A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.
Abstract: increased competition and increased costs of
designing made it important for the firms to identify the right
products and the right methods for manufacturing the products. Firms
should focus on customers and identify customer demands directly to
design the right products. Several management methods and
techniques that are currently available improve one or more functions
or processes in an industry and do not take the complete product life
cycle into consideration. On the other hand target costing is a method
/ philosophy that takes financial, manufacturing and customer aspects
into consideration during designing phase and helps firms in making
product design decisions to increase the profit / value of the
company. It uses various techniques to identify customer demands, to
decrease costs of manufacturing and finally to achieve strategic goals.
Target Costing forms an integral part of total product design /
redesign based on strategic plans.
Abstract: The Philosophy of Sufficiency Economy, bestowed
by His Majesty the King Bhumibol Adulyadej to the people of
Thailand, highlights a balanced way of living. Three principles of
moderation reasonableness, and immunity, along with the conditions
for morality and knowledge, can be applied to any level of the
society–from an individual to the nation. The Philosophy of
Sufficiency Economy helps address the current development
challenges, which are issues on institutions, environmental
sustainability, human well-being, and the role of the government.
Abstract: There-s a lack in understanding the indoor climate of Malaysian residential. The assumption of traditional house could
provide the best indoor environment is too good to be true. This research is to understand indoor environment in three types of
Malaysian residential and thermo recorder TR72Ui were placed in
indoor spaces for measurement. There are huge differences of indoor
environment between housing types, and building material helps to control indoor climate. Traditional house indoor climate was similar to
the outdoor. Temperature in the bedroom of terrace and town houses were slightly higher than the living room. Indoor temperature was 2oC
lower in the rainy season than the hot season. It was hard to control
indoor humidity level in traditional house compared with terrace and
town house. As for conclusion, town house provides the best thermal
environment to the building occupants and can be improved with good
roof insulation.
Abstract: Software engineering education not only embraces
technical skills of software development but also necessitates
communication and interaction among learners. In this paper, it is
proposed to adapt the PBL methodology that is especially designed to
be integrated into software engineering classroom in order to promote
collaborative learning environment. This approach helps students
better understand the significance of social aspects and provides a
systematic framework to enhance teamwork skills. The adaptation of
PBL facilitates the transition to an innovative software development
environment where cooperative learning can be actualized.
Abstract: Importance of strategic planning is unquestionable. However, the practical implementation of a strategic plan faces too many obstacles. The aim of the article is explained the importance of strategic planning and to find how companies in Moravian-Silesian Region deal with strategic planning, and to introduce the model, which helps to set strategic goals in financial indicators area. This model should be part of the whole process of strategic planning and can be use to predict the future values of financial indicators of the company with regard to the factor, which influence these indicators.
Abstract: This paper presents the stabilization potential of Class
F pond ash (PA) from a coal fired thermal power station on tropical
peat soil. Peat or highly organic soils are well known for their high
compressibility, natural moisture content, low shear strength and
long-term settlement. This study investigates the effect of different
amount (i.e., 5, 10, 15 and 20%) of PA on peat soil, collected from
Sarawak, Malaysia, mainly compaction and unconfined compressive
strength (UCS) properties. The amounts of PA added to the peat soil
sample as percentage of the dry peat soil mass. With the increase in
PA content, the maximum dry density (MDD) of peat soil increases,
while the optimum moisture content (OMC) decreases. The UCS
value of the peat soils increases significantly with the increase of PA
content and also with curing periods. This improvement on
compressive strength of tropical peat soils indicates that PA has the
potential to be used as a stabilizer for tropical peat soil. Also, the use
of PA in soil stabilization helps in reducing the pond volume and
achieving environment friendly as well as a sustainable development
of natural resources.
Abstract: This paper presents design and characterization of a
microaccelerometer designated for integration into cataract surgical
probe to detect hardness of different eye tissues during cataract
surgery. Soft posterior lens capsule of eye can be easily damaged in
comparison with hard opaque lens since the surgeon can not see
directly behind cutting needle during the surgery. Presence of
microsensor helps the surgeon to avoid rupturing posterior lens
capsule which if occurs leads to severe complications such as
glaucoma, infection, or even blindness. The microsensor having
overall dimensions of 480 μm x 395 μm is able to deliver significant
capacitance variations during encountered vibration situations which
makes it capable to distinguish between different types of tissue.
Integration of electronic components on chip ensures high level of
reliability and noise immunity while minimizes space and power
requirements. Physical characteristics and results on performance
testing, proves integration of microsensor as an effective tool to aid
the surgeon during this procedure.
Abstract: Software and applications are subjected to serious and damaging security threats, these threats are increasing as a result of increased number of potential vulnerabilities. Security testing is an indispensable process to validate software security requirements and to identify security related vulnerabilities. In this paper we analyze and compare different available vulnerabilities testing techniques based on a pre defined criteria using analytical hierarchy process (AHP). We have selected five testing techniques which includes Source code analysis, Fault code injection, Robustness, Stress and Penetration testing techniques. These testing techniques have been evaluated against five criteria which include cost, thoroughness, Ease of use, effectiveness and efficiency. The outcome of the study is helpful for researchers, testers and developers to understand effectiveness of each technique in its respective domain. Also the study helps to compare the inner working of testing techniques against a selected criterion to achieve optimum testing results.
Abstract: Supplier selection, in real situation, is affected by
several qualitative and quantitative factors and is one of the most
important activities of purchasing department. Since at the time of
evaluating suppliers against the criteria or factors, decision makers
(DMS) do not have precise, exact and complete information, supplier
selection becomes more difficult. In this case, Grey theory helps us
to deal with this problem of uncertainty. Here, we apply Technique
for Order Preference by Similarity to Ideal Solution (TOPSIS)
method to evaluate and select the best supplier by using interval
fuzzy numbers. Through this article, we compare TOPSIS with some
other approaches and afterward demonstrate that the concept of
TOPSIS is very important for ranking and selecting right supplier.
Abstract: The autonomic nervous system has a regulatory
structure that helps people adapt to changes in their environment by
adjusting or modifying some functions in response to stress, and regulating involuntary function of human organs. The purpose of this
study was to investigate the effect of combined stimulation, both
far-infrared heating and chiropractic, on the autonomic nervous system
activities using thermal image and heart rate variability. Six healthy subjects participated in this test. We compared the before and after
autonomic nervous system activities through obtaining thermal image
and photoplethysmogram signal. The thermal images showed that the
combined stimulation changed subject-s body temperature more
highly and widely than before. The result of heart rate variability
indicated that LF/HF ratio decreased. We concluded that combined
stimulation activates autonomic nervous system, and expected other
possibilities of this combined stimulation.
Abstract: In this paper, we propose a selective mutation method
for improving the performances of genetic algorithms. In selective
mutation, individuals are first ranked and then additionally mutated
one bit in a part of their strings which is selected corresponding to
their ranks. This selective mutation helps genetic algorithms to fast
approach the global optimum and to quickly escape local optima.
This results in increasing the performances of genetic algorithms.
We measured the effects of selective mutation with four function
optimization problems. It was found from extensive experiments that
the selective mutation can significantly enhance the performances of
genetic algorithms.
Abstract: A renewable energy system discussed in this paper is
a stand-alone wind-hydrogen system for a remote island in Australia.
The analysis of an existing wind-diesel power system was performed.
Simulation technique was used to model the power system currently
employed on the island, and simulated different configurations of
additional hydrogen energy system. This study aims to determine the
suitable hydrogen integrated configuration to setting up the prototype
system for the island, which helps to reduce the diesel consumption
on the island. A set of configurations for the hydrogen system and
associated parameters that consists of wind turbines, electrolysers,
hydrogen internal combustion engines, and storage tanks has been
purposed. The simulation analyses various configurations that
perfectly balances the system to meet the demand on the island.